diff --git a/.agents/skills/create-cuda-python-pull-request/SKILL.md b/.agents/skills/create-cuda-python-pull-request/SKILL.md
new file mode 100644
index 00000000000..4e3a07b83c1
--- /dev/null
+++ b/.agents/skills/create-cuda-python-pull-request/SKILL.md
@@ -0,0 +1,127 @@
+---
+name: create-cuda-python-pull-request
+description: Create a CUDA Python pull request from an approved personal or organization-owned fork, including the GitHub CLI GraphQL fallback for renamed organization-owned forks. Use when the user directly requests creating or opening a CUDA Python pull request. Do not use for local implementation, commits, pushes, branch preparation, PR advice, or general GitHub work without that direct request.
+---
+
+# Create CUDA Python Pull Request
+
+This skill supplies technical procedure after the user directly asks to create
+a pull request. It does not define when a pull request should be created or
+authorize one without that direct request. Do not infer the request from
+completed work, a local commit, a push request, or the existence of a suitable
+fork.
+
+## Inspect the topology and proposed change
+
+1. Run `git status --short --branch`, inspect the branch diff, and confirm the
+   intended base branch.
+2. Run `git remote -v` and resolve the complete `OWNER/REPOSITORY` names of the
+   base repository and intended fork. Do not rely on remote names alone.
+3. Confirm through GitHub that the push target is a fork of the base repository
+   and is not the base repository itself.
+4. Confirm that the intended push target complies with the repository's
+   remote-write policy and the user's request.
+5. Inspect the repository's pull-request template, available labels, and open
+   milestones. Do not guess required metadata; ask the user when it is unclear.
+
+## Validate and push
+
+Run the checks appropriate to the change and review the final diff. Push the
+current branch to the approved fork using the explicit remote and branch:
+
+```bash
+git push <fork-remote> <branch>
+```
+
+## Create the pull request
+
+Prepare a complete body from the repository's pull-request template. Every
+pull request must have at least one assignee, one label, and a milestone; CI
+enforces this through `pr-metadata-check`.
+
+Use `gh pr create` when it can identify the fork unambiguously. Select the base
+repository and branch explicitly and supply the required metadata:
+
+```bash
+gh pr create \
+  --repo <base-owner>/<base-repository> \
+  --base <base-branch> \
+  --head <fork-owner>:<head-branch> \
+  --title "<title>" \
+  --body-file <path-to-pr-body> \
+  --assignee <assignee> \
+  --label <label> \
+  --milestone <milestone>
+```
+
+Add `--draft` when the user requests a draft pull request.
+
+## Handle renamed organization-owned forks
+
+[GitHub CLI issue cli/cli#10093](https://github.com/cli/cli/issues/10093)
+tracks `gh pr create` support for cross-repository pull requests within one
+organization. Check whether the issue has been resolved before using the
+workaround.
+
+If `gh pr create` cannot identify an organization-owned fork whose repository
+name differs from the base repository, create the pull request with GitHub's
+GraphQL API and pass `headRepositoryId` explicitly.
+
+Resolve the repository node IDs:
+
+```bash
+BASE_REPO="<base-owner>/<base-repository>"
+HEAD_REPO="<fork-owner>/<fork-repository>"
+BASE_REPO_ID="$(gh api "repos/${BASE_REPO}" --jq '.node_id')"
+HEAD_REPO_ID="$(gh api "repos/${HEAD_REPO}" --jq '.node_id')"
+```
+
+Create the pull request. Set `draft` to match the user's request.
+
+```bash
+gh api graphql \
+  -f repositoryId="${BASE_REPO_ID}" \
+  -f headRepositoryId="${HEAD_REPO_ID}" \
+  -f baseRefName="<base-branch>" \
+  -f headRefName="<head-branch>" \
+  -f title="<title>" \
+  -F body="@<path-to-pr-body>" \
+  -F draft=false \
+  -f query='
+    mutation CreatePullRequest(
+      $repositoryId: ID!
+      $headRepositoryId: ID!
+      $baseRefName: String!
+      $headRefName: String!
+      $title: String!
+      $body: String!
+      $draft: Boolean!
+    ) {
+      createPullRequest(input: {
+        repositoryId: $repositoryId
+        headRepositoryId: $headRepositoryId
+        baseRefName: $baseRefName
+        headRefName: $headRefName
+        title: $title
+        body: $body
+        draft: $draft
+      }) {
+        pullRequest { number url }
+      }
+    }' \
+  --jq '.data.createPullRequest.pullRequest'
+```
+
+The GraphQL API does not populate the pull-request template automatically.
+After creation, add the required metadata to the returned pull-request number:
+
+```bash
+gh pr edit <pr-number> \
+  --repo "${BASE_REPO}" \
+  --add-assignee "<assignee>" \
+  --add-label "<label>" \
+  --milestone "<milestone>"
+```
+
+Verify the resulting URL, base branch, head repository and branch, draft state,
+body, assignee, label, and milestone before reporting completion.
diff --git a/.agents/skills/create-cuda-python-pull-request/agents/openai.yaml b/.agents/skills/create-cuda-python-pull-request/agents/openai.yaml
new file mode 100644
index 00000000000..1d2725a7696
--- /dev/null
+++ b/.agents/skills/create-cuda-python-pull-request/agents/openai.yaml
@@ -0,0 +1,10 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+interface:
+  display_name: "Create CUDA Python PR"
+  short_description: "Open an explicitly requested CUDA Python pull request"
+  default_prompt: "Use $create-cuda-python-pull-request to create the CUDA Python pull request I explicitly requested."
+policy:
+  allow_implicit_invocation: true
diff --git a/.coveragerc b/.coveragerc
index 1e1776fd566..46993e6abcc 100644
--- a/.coveragerc
+++ b/.coveragerc
@@ -11,11 +11,12 @@ plugins = Cython.Coverage
 core = ctrace
 branch = False
 relative_files = True
-# Omits specific definition files that causes plugin errors
+# Cython.Coverage cannot build a FileReporter for .pxd/.pxi (not standalone
+# translation units). Pattern in [run], not an enumeration: a new file of
+# either kind otherwise breaks `coverage html`. Must be [run], not [report].
 omit =
-    */windll.pxd
-    */_lib/windll.pxd
-    */_lib/utils.pxd
+    */*.pxd
+    */*.pxi
 
 [report]
 show_missing = true
diff --git a/.github/ISSUE_TEMPLATE/release_checklist.yml b/.github/ISSUE_TEMPLATE/release_checklist.yml
index f7307fbe92a..1edc0e9e12b 100644
--- a/.github/ISSUE_TEMPLATE/release_checklist.yml
+++ b/.github/ISSUE_TEMPLATE/release_checklist.yml
@@ -20,6 +20,7 @@ body:
         - label: File an internal nvbug to communicate test plan & release schedule with QA
         - label: Ensure all pending PRs are reviewed, tested, and merged
         - label: Check (or update if needed) the dependency requirements
+        - label: Sweep deprecations whose stated removal version has arrived (`grep -rn 'deprecated::' cuda_core/cuda`) and remove any that are due
         - label: "Finalize the doc update, including release notes (\"Note: Touching docstrings/type annotations in code is OK during code freeze, apply your best judgement!\")"
         - label: Update the docs for the new version
         - label: Create a public release tag
diff --git a/.github/RELEASE-core.md b/.github/RELEASE-core.md
index 01e182c76ef..a93b3ed8d61 100644
--- a/.github/RELEASE-core.md
+++ b/.github/RELEASE-core.md
@@ -64,6 +64,29 @@ platforms as appropriate for each release.
 Review `cuda_core/pyproject.toml` and verify that all dependency
 requirements are current.
 
+Update the cuda_core dependency in `cuda_python/setup.py`.
+
+---
+
+## Sweep deprecations whose removal version has arrived
+
+Deprecated APIs are marked in the source with a Sphinx `deprecated`
+directive naming the version that introduced the deprecation, and their
+docstrings state the version in which they will be removed. Find them all
+with:
+
+```console
+$ grep -rn 'deprecated::' cuda_core/cuda
+```
+
+For each hit, check the stated removal version against the version being
+released. If the release has reached or passed it, remove the API, its
+runtime `DeprecationWarning`, and any tests asserting that warning.
+
+This must happen *before* the release tag is cut. Removals are breaking
+changes, so they are only permitted at a major-version boundary per the
+[support policy](https://nvidia.github.io/cuda-python/cuda-core/latest/support.html).
+
 ---
 
 ## Finalize the doc update, including release notes
diff --git a/.github/actionlint.yaml b/.github/actionlint.yaml
index db23ece3410..bad051f4642 100644
--- a/.github/actionlint.yaml
+++ b/.github/actionlint.yaml
@@ -8,3 +8,10 @@ self-hosted-runner:
   labels:
     - linux-amd64-cpu8
     - linux-amd64-gpu-l4-latest-1
+
+# GitHub supports queued concurrency runs, but the latest actionlint release
+# does not yet recognize the concurrency.queue key.
+paths:
+  ".github/workflows/ci-workflow-health.yml":
+    ignore:
+      - 'unexpected key "queue" for "concurrency" section'
diff --git a/.github/actions/fetch_ctk/action.yml b/.github/actions/fetch_ctk/action.yml
index 5ffed69f99a..994e35924fc 100644
--- a/.github/actions/fetch_ctk/action.yml
+++ b/.github/actions/fetch_ctk/action.yml
@@ -11,10 +11,6 @@ inputs:
     required: true
   cuda-version:
     required: true
-  cuda-channel:
-    description: "CUDA package channel: stable redistributables or prerelease packages"
-    required: false
-    default: "stable"
   cuda-components:
     description: "A list of the CTK components to install as a comma-separated list. e.g. 'cuda_nvcc,cuda_nvrtc,cuda_cudart'"
     required: false
@@ -34,52 +30,19 @@ runs:
         # Use the runtime workspace mount so this also works inside container jobs.
         CTK_REDIST_TOOL="${GITHUB_WORKSPACE}/ci/tools/fetch_ctk_redistrib.py"
         CTK_CACHE_COMPONENTS=${{ inputs.cuda-components }}
-        CTK_PREVIEW_PACKAGES=
-        CTK_PREVIEW_INSTALLER_URL=
-        CTK_PREVIEW_INSTALLER_SHA256=
-        if [[ "${{ inputs.cuda-channel }}" == "stable" ]]; then
-          CTK_JSON_URL="https://developer.download.nvidia.com/compute/cuda/redist/redistrib_${{ inputs.cuda-version }}.json"
-          CTK_CACHE_COMPONENTS="$(python "$CTK_REDIST_TOOL" filter-components \
-            --host-platform "${{ inputs.host-platform }}" \
-            --cuda-version "${{ inputs.cuda-version }}" \
-            --components "$CTK_CACHE_COMPONENTS" \
-            --metadata-url "$CTK_JSON_URL")"
-        elif [[ "${{ inputs.cuda-channel }}" == "prerelease" ]]; then
-          if [[ "${{ inputs.host-platform }}" == linux* ]]; then
-            CTK_PREVIEW_PACKAGES="$(python "$CTK_REDIST_TOOL" preview-packages \
-              --host-platform "${{ inputs.host-platform }}" \
-              --cuda-version "${{ inputs.cuda-version }}" \
-              --components "$CTK_CACHE_COMPONENTS")"
-            CTK_CACHE_COMPONENTS="$CTK_PREVIEW_PACKAGES"
-          elif [[ "${{ inputs.host-platform }}" == win* ]]; then
-            IFS=$'\t' read -r CTK_PREVIEW_INSTALLER_URL CTK_PREVIEW_INSTALLER_SHA256 <<< \
-              "$(python "$CTK_REDIST_TOOL" preview-installer \
-                --host-platform "${{ inputs.host-platform }}" \
-                --cuda-version "${{ inputs.cuda-version }}")"
-            CTK_CACHE_COMPONENTS="${CTK_PREVIEW_INSTALLER_URL}:${CTK_PREVIEW_INSTALLER_SHA256}:${CTK_CACHE_COMPONENTS}"
-          else
-            echo "CUDA prerelease packages are not supported for host-platform ${{ inputs.host-platform }}" >&2
-            exit 1
-          fi
-        else
-          echo "Unsupported CUDA package channel: ${{ inputs.cuda-channel }}" >&2
-          exit 1
-        fi
+        CTK_JSON_URL="https://developer.download.nvidia.com/compute/cuda/redist/redistrib_${{ inputs.cuda-version }}.json"
+        CTK_CACHE_COMPONENTS="$(python "$CTK_REDIST_TOOL" filter-components \
+          --host-platform "${{ inputs.host-platform }}" \
+          --cuda-version "${{ inputs.cuda-version }}" \
+          --components "$CTK_CACHE_COMPONENTS" \
+          --metadata-url "$CTK_JSON_URL")"
 
         HASH=$(echo -n "${CTK_CACHE_COMPONENTS}" | sha256sum | awk '{print $1}')
-        CHANNEL_CACHE_SEGMENT=
-        if [[ "${{ inputs.cuda-channel }}" != "stable" ]]; then
-          CHANNEL_CACHE_SEGMENT="-${{ inputs.cuda-channel }}"
-        fi
-        echo "CTK_CACHE_KEY=mini-ctk${CHANNEL_CACHE_SEGMENT}-${{ inputs.cuda-version }}-${{ inputs.host-platform }}-$HASH" >> $GITHUB_ENV
+        echo "CTK_CACHE_KEY=mini-ctk-${{ inputs.cuda-version }}-${{ inputs.host-platform }}-$HASH" >> $GITHUB_ENV
         echo "CTK_CACHE_FILENAME=mini-ctk-${{ inputs.cuda-version }}-${{ inputs.host-platform }}-$HASH.tar.gz" >> $GITHUB_ENV
         echo "CTK_CACHE_COMPONENTS=${CTK_CACHE_COMPONENTS}" >> $GITHUB_ENV
-        echo "CTK_PREVIEW_PACKAGES=${CTK_PREVIEW_PACKAGES}" >> $GITHUB_ENV
-        echo "CTK_PREVIEW_INSTALLER_URL=${CTK_PREVIEW_INSTALLER_URL}" >> $GITHUB_ENV
-        echo "CTK_PREVIEW_INSTALLER_SHA256=${CTK_PREVIEW_INSTALLER_SHA256}" >> $GITHUB_ENV
 
     - name: Install dependencies
-      if: ${{ startsWith(inputs.host-platform, 'linux') }}
       uses: ./.github/actions/install_unix_deps
       continue-on-error: false
       with:
@@ -102,135 +65,51 @@ runs:
         # Everything under this folder is packed and stored in the GitHub Cache space,
         # and unpacked after retrieving from the cache.
         CACHE_TMP_DIR="./cache_tmp_dir"
-        WORK_TMP_DIR="./cache_work_dir"
-        rm -rf $CACHE_TMP_DIR $WORK_TMP_DIR
+        rm -rf $CACHE_TMP_DIR
         mkdir $CACHE_TMP_DIR
-        CTK_REDIST_TOOL="${GITHUB_WORKSPACE}/ci/tools/fetch_ctk_redistrib.py"
-
-        if [[ "${{ inputs.cuda-channel }}" == "prerelease" ]]; then
-          if [[ "${{ inputs.host-platform }}" == linux* ]]; then
-            source /etc/os-release
-            DISTRO_CODENAME="${VERSION_CODENAME:-}"
-            case "$DISTRO_CODENAME" in
-              bookworm|jammy|noble|resolute|trixie) ;;
-              *)
-                echo "Unsupported distribution for CUDA prerelease packages: ${DISTRO_CODENAME:-unknown}" >&2
-                exit 1
-                ;;
-            esac
-
-            KEYRING_DEB="$CACHE_TMP_DIR/nvidia-preview-keyring.deb"
-            curl -fLSs "https://packages.nvidia.com/${DISTRO_CODENAME}/nvidia-preview-keyring.deb" -o "$KEYRING_DEB"
-            sudo dpkg -i "$KEYRING_DEB"
-            sudo apt-get update
-
-            DEB_DIR="$CACHE_TMP_DIR/debs"
-            DEB_ROOT="$CACHE_TMP_DIR/deb-root"
-            mkdir -p "$DEB_DIR/partial" "$DEB_ROOT"
-            DEB_DIR="$(realpath "$DEB_DIR")"
-            IFS=, read -ra PREVIEW_PACKAGES <<< "$CTK_PREVIEW_PACKAGES"
-            sudo apt-get install --yes --download-only --no-install-recommends \
-              -o "Dir::Cache::archives=$DEB_DIR" \
-              "${PREVIEW_PACKAGES[@]}"
-            for package in "$DEB_DIR"/*.deb; do
-              dpkg-deb -x "$package" "$DEB_ROOT"
-            done
-
-            CUDA_SHORT_VERSION="${{ inputs.cuda-version }}"
-            CUDA_SHORT_VERSION="${CUDA_SHORT_VERSION%.*}"
-            CUDA_PACKAGE_ROOT="$DEB_ROOT/usr/local/cuda-${CUDA_SHORT_VERSION}"
-            if [[ ! -d "$CUDA_PACKAGE_ROOT/include" ]]; then
-              echo "CUDA prerelease packages did not provide $CUDA_PACKAGE_ROOT/include" >&2
-              exit 1
-            fi
-            cp -a "$CUDA_PACKAGE_ROOT/." "$CACHE_TMP_DIR/"
-            rm -rf "$DEB_DIR" "$DEB_ROOT" "$KEYRING_DEB"
-          elif [[ "${{ inputs.host-platform }}" == win* ]]; then
-            WORK_TMP_DIR="./cache_work_dir"
-            INSTALLER_PATH="$WORK_TMP_DIR/$(basename "$CTK_PREVIEW_INSTALLER_URL")"
-            EXTRACT_ROOT="$WORK_TMP_DIR/installer-root"
-            mkdir -p "$WORK_TMP_DIR"
-            curl -fLSs "$CTK_PREVIEW_INSTALLER_URL" -o "$INSTALLER_PATH"
-            echo "$CTK_PREVIEW_INSTALLER_SHA256  $INSTALLER_PATH" | sha256sum --check --strict -
-
-            SEVEN_ZIP="$(command -v 7z || true)"
-            if [[ -z "$SEVEN_ZIP" && -x "/c/Program Files/7-Zip/7z.exe" ]]; then
-              SEVEN_ZIP="/c/Program Files/7-Zip/7z.exe"
-            fi
-            if [[ -z "$SEVEN_ZIP" || ! -x "$SEVEN_ZIP" ]]; then
-              echo "7-Zip is required to extract the CUDA prerelease installer" >&2
-              exit 1
-            fi
-
-            IFS=, read -ra PREVIEW_WINDOWS_ARCHIVES <<< \
-              "$(python "$CTK_REDIST_TOOL" preview-windows-archives \
-                --host-platform "${{ inputs.host-platform }}" \
-                --cuda-version "${{ inputs.cuda-version }}" \
-                --components "${{ inputs.cuda-components }}")"
 
-            PREVIEW_WINDOWS_ARCHIVE_PATTERNS=()
-            for archive_dir in "${PREVIEW_WINDOWS_ARCHIVES[@]}"; do
-              PREVIEW_WINDOWS_ARCHIVE_PATTERNS+=("${archive_dir}/*")
-            done
-
-            mkdir -p "$EXTRACT_ROOT"
-            "$SEVEN_ZIP" x -y "$INSTALLER_PATH" "${PREVIEW_WINDOWS_ARCHIVE_PATTERNS[@]}" "-o$EXTRACT_ROOT"
-
-            python "$CTK_REDIST_TOOL" merge-windows-preview \
-              --host-platform "${{ inputs.host-platform }}" \
-              --cuda-version "${{ inputs.cuda-version }}" \
-              --components "${{ inputs.cuda-components }}" \
-              --extract-root "$EXTRACT_ROOT" \
-              --destination "$CACHE_TMP_DIR"
-
-            rm -rf "$WORK_TMP_DIR"
-          else
-            echo "CUDA prerelease extraction is not supported for host-platform ${{ inputs.host-platform }}" >&2
-            exit 1
-          fi
-        else
-          # The binary archives (redist) are guaranteed to be updated as part of the release posting.
-          # Use the runtime workspace mount so this also works inside container jobs.
-          CTK_BASE_URL="https://developer.download.nvidia.com/compute/cuda/redist/"
-          CTK_JSON_URL="$CTK_BASE_URL/redistrib_${{ inputs.cuda-version }}.json"
-          CTK_JSON_FILE="$CACHE_TMP_DIR/redistrib.json"
-          curl -fLSs "$CTK_JSON_URL" -o "$CTK_JSON_FILE"
-          if [[ "${{ inputs.host-platform }}" == linux* ]]; then
-            function extract() {
-              tar -xvf $1 -C $CACHE_TMP_DIR --strip-components=1
-            }
-          elif [[ "${{ inputs.host-platform }}" == win* ]]; then
-            function extract() {
-              _TEMP_DIR_=$(mktemp -d)
-              unzip $1 -d $_TEMP_DIR_
-              cp -r $_TEMP_DIR_/*/* $CACHE_TMP_DIR
-              rm -rf $_TEMP_DIR_
-              # see commit NVIDIA/cuda-python@69410f1d9228e775845ef6c8b4a9c7f37ffc68a5
-              chmod 644 $CACHE_TMP_DIR/LICENSE
-            }
-          fi
-          function populate_cuda_path() {
-            # take the component name as a argument
-            function download() {
-              curl -fLSs $1 -o $2
-            }
-            CTK_COMPONENT=$1
-            CTK_COMPONENT_REL_PATH="$(python "$CTK_REDIST_TOOL" component-relative-path \
-              --host-platform "${{ inputs.host-platform }}" \
-              --component "$CTK_COMPONENT" \
-              --metadata-path "$CTK_JSON_FILE")"
-            CTK_COMPONENT_URL="${CTK_BASE_URL}/${CTK_COMPONENT_REL_PATH}"
-            CTK_COMPONENT_COMPONENT_FILENAME="$(basename $CTK_COMPONENT_REL_PATH)"
-            download $CTK_COMPONENT_URL $CTK_COMPONENT_COMPONENT_FILENAME
-            extract $CTK_COMPONENT_COMPONENT_FILENAME
-            rm $CTK_COMPONENT_COMPONENT_FILENAME
+        # The binary archives (redist) are guaranteed to be updated as part of the release posting.
+        # Use the runtime workspace mount so this also works inside container jobs.
+        CTK_REDIST_TOOL="${GITHUB_WORKSPACE}/ci/tools/fetch_ctk_redistrib.py"
+        CTK_BASE_URL="https://developer.download.nvidia.com/compute/cuda/redist/"
+        CTK_JSON_URL="$CTK_BASE_URL/redistrib_${{ inputs.cuda-version }}.json"
+        CTK_JSON_FILE="$CACHE_TMP_DIR/redistrib.json"
+        curl -LSs "$CTK_JSON_URL" -o "$CTK_JSON_FILE"
+        if [[ "${{ inputs.host-platform }}" == linux* ]]; then
+          function extract() {
+            tar -xvf $1 -C $CACHE_TMP_DIR --strip-components=1
+          }
+        elif [[ "${{ inputs.host-platform }}" == win* ]]; then
+          function extract() {
+            _TEMP_DIR_=$(mktemp -d)
+            unzip $1 -d $_TEMP_DIR_
+            cp -r $_TEMP_DIR_/*/* $CACHE_TMP_DIR
+            rm -rf $_TEMP_DIR_
+            # see commit NVIDIA/cuda-python@69410f1d9228e775845ef6c8b4a9c7f37ffc68a5
+            chmod 644 $CACHE_TMP_DIR/LICENSE
           }
-
-          # Get headers and shared libraries in place
-          for item in $(echo $CTK_CACHE_COMPONENTS | tr ',' ' '); do
-              populate_cuda_path "$item"
-          done
         fi
+        function populate_cuda_path() {
+          # take the component name as a argument
+          function download() {
+            curl -LSs $1 -o $2
+          }
+          CTK_COMPONENT=$1
+          CTK_COMPONENT_REL_PATH="$(python "$CTK_REDIST_TOOL" component-relative-path \
+            --host-platform "${{ inputs.host-platform }}" \
+            --component "$CTK_COMPONENT" \
+            --metadata-path "$CTK_JSON_FILE")"
+          CTK_COMPONENT_URL="${CTK_BASE_URL}/${CTK_COMPONENT_REL_PATH}"
+          CTK_COMPONENT_COMPONENT_FILENAME="$(basename $CTK_COMPONENT_REL_PATH)"
+          download $CTK_COMPONENT_URL $CTK_COMPONENT_COMPONENT_FILENAME
+          extract $CTK_COMPONENT_COMPONENT_FILENAME
+          rm $CTK_COMPONENT_COMPONENT_FILENAME
+        }
+
+        # Get headers and shared libraries in place
+        for item in $(echo $CTK_CACHE_COMPONENTS | tr ',' ' '); do
+            populate_cuda_path "$item"
+        done
         # TODO: check Windows
         if [[ "${{ inputs.host-platform }}" == linux* && -d "${CACHE_TMP_DIR}/lib" ]]; then
           mv $CACHE_TMP_DIR/lib $CACHE_TMP_DIR/lib64
@@ -277,14 +156,6 @@ runs:
         cp -r $CACHE_TMP_DIR/* $CUDA_PATH
         rm -rf $CACHE_TMP_DIR $CTK_CACHE_FILENAME
         ls -l $CUDA_PATH
-        # redistrib.json is present for stable-channel installs; include/ is
-        # present for prerelease installs (enforced at cache-creation time).
-        # Components that don't ship headers (e.g. cuda_sanitizer_api) have
-        # neither, so checking only for include/ incorrectly rejects them.
-        if [[ ! -e "$CUDA_PATH/redistrib.json" && ! -d "$CUDA_PATH/include" ]]; then
-          echo "CTK restore appears incomplete: neither redistrib.json nor include/ found in $CUDA_PATH" >&2
-          exit 1
-        fi
 
     - name: Set output environment variables
       shell: bash --noprofile --norc -xeuo pipefail {0}
diff --git a/.github/actions/griffe-api-check/action.yml b/.github/actions/griffe-api-check/action.yml
new file mode 100644
index 00000000000..6c090ddeb43
--- /dev/null
+++ b/.github/actions/griffe-api-check/action.yml
@@ -0,0 +1,44 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+name: griffe API check
+
+description: >-
+  Check a package's public API (as defined by `__all__`) for changes using
+  griffe.
+
+inputs:
+  package-name:
+    description: "Importable package name to check, e.g. cuda.core"
+    required: true
+  package-dir:
+    description: "Directory to search for the package sources, e.g. cuda_core"
+    required: true
+  merge-base:
+    description: >-
+      Git ref/sha to compare the current code against, typically the PR's
+      merge-base with its target branch.
+    required: true
+
+runs:
+  using: composite
+  steps:
+    - name: Install uv
+      uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39  # v8.2.0
+      with:
+        enable-cache: false
+
+    - name: Check API
+      shell: bash --noprofile --norc -euo pipefail {0}
+      env:
+        PACKAGE_NAME: ${{ inputs.package-name }}
+        PACKAGE_DIR: ${{ inputs.package-dir }}
+        MERGE_BASE: ${{ inputs.merge-base }}
+      run: |
+        uvx griffe check "$PACKAGE_NAME" \
+          --search "$PACKAGE_DIR" \
+          --find-stubs-packages \
+          --against "$MERGE_BASE" \
+          --format github \
+          2>&1
diff --git a/.github/workflows/backport.yml b/.github/workflows/backport.yml
index a3573bc14d4..e8cfda1e2c8 100644
--- a/.github/workflows/backport.yml
+++ b/.github/workflows/backport.yml
@@ -34,7 +34,7 @@ jobs:
          }}
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+      - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Load branch name
         id: get-branch
@@ -43,7 +43,7 @@ jobs:
           echo "OLD_BRANCH=${OLD_BRANCH}" >> $GITHUB_ENV
 
       - name: Create backport pull requests
-        uses: korthout/backport-action@66065406958f46e82238fd59546f5a99e69e22aa  # v4.5.2
+        uses: korthout/backport-action@2e830a1d0b8269505846ddd407a70876913ad1f8  # v4.6.0
         with:
           copy_assignees: true
           copy_labels_pattern: true
@@ -54,7 +54,7 @@ jobs:
     if: github.repository_owner == 'nvidia' && github.event_name == 'workflow_dispatch'
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+      - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Load branch from environment name
         if: inputs.backport-branch == null
@@ -67,7 +67,7 @@ jobs:
         run: echo "BACKPORT_BRANCH=${{ inputs.backport-branch }}" >> $GITHUB_ENV
 
       - name: Create backport pull requests
-        uses: korthout/backport-action@66065406958f46e82238fd59546f5a99e69e22aa  # v4.5.2
+        uses: korthout/backport-action@2e830a1d0b8269505846ddd407a70876913ad1f8  # v4.6.0
         with:
           copy_assignees: true
           copy_labels_pattern: true
diff --git a/.github/workflows/bandit.yml b/.github/workflows/bandit.yml
index bd09d8e66ce..543fbbe5aeb 100644
--- a/.github/workflows/bandit.yml
+++ b/.github/workflows/bandit.yml
@@ -23,10 +23,10 @@ jobs:
       security-events: write
     steps:
       - name: Checkout
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Install uv
-        uses: astral-sh/setup-uv@fac544c07dec837d0ccb6301d7b5580bf5edae39  # v8.2.0
+        uses: astral-sh/setup-uv@20cfd1bf945f4377ade1205e4dbc17946fc9a30d  # v10.0.1
         with:
           enable-cache: false
 
@@ -41,10 +41,10 @@ jobs:
 
           echo "codes=$(uvx toml2json ./ruff.toml | jq -r '.lint.ignore | map(select(test("^S\\d+"))) | join(",")')" >> "$GITHUB_OUTPUT"
       - name: Perform Bandit Analysis using Ruff
-        uses: astral-sh/ruff-action@0ce1b0bf8b818ef400413f810f8a11cdbda0034b  # v4.0.0
+        uses: astral-sh/ruff-action@278981a28ce3188b1e39527901f38254bf3aac89  # v4.1.0
         with:
           args: "check --select S --ignore ${{ steps.ignore-codes.outputs.codes }} --output-format sarif --output-file results.sarif"
       - name: Upload SARIF file
-        uses: github/codeql-action/upload-sarif@8aad20d150bbac5944a9f9d289da16a4b0d87c1e  # v4.36.2
+        uses: github/codeql-action/upload-sarif@cdf488f595d80d6e07e03d4674febd5ab45fa938  # v4.37.9
         with:
           sarif_file: results.sarif
diff --git a/.github/workflows/build-docs.yml b/.github/workflows/build-docs.yml
index 32a92214648..bef2a7e84c0 100644
--- a/.github/workflows/build-docs.yml
+++ b/.github/workflows/build-docs.yml
@@ -55,7 +55,7 @@ jobs:
         shell: bash -el {0}
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           fetch-depth: 1
           ref: ${{ inputs.git-tag }}
@@ -64,10 +64,8 @@ jobs:
         run: |
           if [[ -f ci/versions.yml ]]; then
             BUILD_CTK_VER=$(yq '.cuda.build.version' ci/versions.yml)
-            BUILD_CTK_CHANNEL=$(yq '.cuda.build.channel // "stable"' ci/versions.yml)
           elif [[ -f ci/versions.json ]]; then
             BUILD_CTK_VER=$(jq -r '.cuda.build.version' ci/versions.json)
-            BUILD_CTK_CHANNEL=$(jq -r '.cuda.build.channel // "stable"' ci/versions.json)
           else
             echo "error: cannot find ci/versions.yml or ci/versions.json" >&2
             exit 1
@@ -77,7 +75,6 @@ jobs:
             exit 1
           fi
           echo "BUILD_CTK_VER=${BUILD_CTK_VER}" >> "$GITHUB_ENV"
-          echo "BUILD_CTK_CHANNEL=${BUILD_CTK_CHANNEL}" >> "$GITHUB_ENV"
 
       # TODO: This workflow runs on GH-hosted runner and cannot use the proxy cache
 
@@ -103,7 +100,6 @@ jobs:
         with:
           host-platform: linux-64
           cuda-version: ${{ env.BUILD_CTK_VER }}
-          cuda-channel: ${{ env.BUILD_CTK_CHANNEL }}
 
       - name: Set environment variables
         run: |
@@ -352,7 +348,7 @@ jobs:
 
       - name: Deploy doc update
         if: ${{ inputs.deploy-docs && (github.ref_name == 'main' || inputs.is-release) }}
-        uses: JamesIves/github-pages-deploy-action@d92aa235d04922e8f08b40ce78cc5442fcfbfa2f  # v4.8.0
+        uses: JamesIves/github-pages-deploy-action@fa24774553152dd7873cd16ebd8d959b010c5445  # v4.9.0
         with:
           git-config-name: cuda-python-bot
           git-config-email: cuda-python-bot@users.noreply.github.com
diff --git a/.github/workflows/build-wheel.yml b/.github/workflows/build-wheel.yml
index a1fad62c3de..52d2370f44c 100644
--- a/.github/workflows/build-wheel.yml
+++ b/.github/workflows/build-wheel.yml
@@ -11,17 +11,14 @@ on:
       cuda-version:
         required: true
         type: string
-      cuda-channel:
-        required: false
-        type: string
-        default: stable
       prev-cuda-version:
         required: true
         type: string
-      python-versions:
+      workplan:
+        description: JSON workplan. An empty value builds and tests everything.
         required: false
         type: string
-        default: '["3.10", "3.11", "3.12", "3.13", "3.14", "3.14t", "3.15", "3.15t"]'
+        default: ""
       single-cuda-major:
         description: "Build wheels for only the current CUDA major; skip the prior-major build and wheel merge"
         required: false
@@ -33,14 +30,37 @@ defaults:
     shell: bash --noprofile --norc -xeuo pipefail {0}
 
 permissions:
+  actions: read
   contents: read  # This is required for actions/checkout
 
 jobs:
   build:
+    env:
+      BUILD_PATHFINDER: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.pathfinder.needs_build }}
+      BUILD_BINDINGS: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.bindings.needs_build }}
+      BUILD_CORE: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.core.needs_build }}
+      BUILD_PYTHON: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.python.needs_build }}
+      TEST_BINDINGS: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.bindings.needs_test }}
+      TEST_CORE: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.core.needs_test }}
+      BASELINE_RUN_ID: ${{ inputs.workplan != '' && fromJSON(inputs.workplan).baseline.run_id || '' }}
+      BASELINE_SHA: ${{ inputs.workplan != '' && fromJSON(inputs.workplan).baseline.sha || '' }}
     strategy:
       fail-fast: false
       matrix:
-        python-version: ${{ fromJSON(inputs.python-versions) }}
+        python-version:
+          - "3.10"
+          - "3.11"
+          - "3.12"
+          - "3.13"
+          - "3.14"
+          - "3.14t"
+          - "3.15"
+          - "3.15t"
+        exclude:
+          # CPython 3.10 has no official Windows ARM64 build (neither
+          # nuget-cpython nor actions/setup-python's manifest carries one),
+          # so it cannot be built or tested on win-arm64.
+          - python-version: ${{ (inputs.host-platform == 'win-arm64' && '3.10') || '' }}
     name: py${{ matrix.python-version }}
     runs-on: ${{ (inputs.host-platform == 'linux-64' && 'linux-amd64-cpu8') ||
                  (inputs.host-platform == 'linux-aarch64' && 'linux-arm64-cpu8') ||
@@ -48,7 +68,7 @@ jobs:
                  (inputs.host-platform == 'win-arm64' && 'windows-11-arm') }}
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # Treeless clone: setuptools-scm needs the commit graph (`git describe`)
           # but not historical blobs.
@@ -56,7 +76,7 @@ jobs:
           filter: blob:none
 
       - name: Install latest rapidsai/sccache
-        if: ${{ startsWith(inputs.host-platform, 'linux') }}
+        if: ${{ startsWith(inputs.host-platform, 'linux') && (env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true') }}
         run: |
           curl -fsSL "https://github.com/rapidsai/sccache/releases/latest/download/sccache-$(uname -m)-unknown-linux-musl.tar.gz" \
             | sudo tar -C /usr/local/bin -xvzf - --wildcards --strip-components=1 -x '*/sccache'
@@ -64,6 +84,7 @@ jobs:
 
       # xref: https://github.com/orgs/community/discussions/42856#discussioncomment-7678867
       - name: Adding addtional GHA cache-related env vars
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' }}
         uses: actions/github-script@v9
         with:
           script: |
@@ -83,7 +104,7 @@ jobs:
 
       - name: Set up Python
         id: setup-python1
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           # WAR: setup-python is not relocatable, and cibuildwheel hard-wires to 3.12...
           # see https://github.com/actions/setup-python/issues/871
@@ -91,20 +112,15 @@ jobs:
           architecture: ${{ ((inputs.host-platform == 'linux-aarch64' || inputs.host-platform == 'win-arm64') && 'arm64') || 'x64' }}
 
       - name: Set up MSVC
-        if: ${{ startsWith(inputs.host-platform, 'win') }}
+        if: ${{ startsWith(inputs.host-platform, 'win') && (env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' || env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true') }}
         uses: step-security/msvc-dev-cmd@22c98154b708dbd743e6f27a933cf6ceba3305c4  # v1.13.1
         with:
           arch: ${{ (inputs.host-platform == 'win-arm64' && 'arm64') || 'x64' }}
 
-      - name: Verify Windows ARM64 runner
-        if: ${{ inputs.host-platform == 'win-arm64' }}
-        run: |
-          python -c "import platform; machine = platform.machine().lower(); print(machine); assert machine in {'arm64', 'aarch64'}"
-
       - name: Set up yq
         # GitHub made an unprofessional decision to not provide it in their Windows VMs,
         # see https://github.com/actions/runner-images/issues/7443.
-        if: ${{ startsWith(inputs.host-platform, 'win') && !inputs.single-cuda-major }}
+        if: ${{ startsWith(inputs.host-platform, 'win') && env.BUILD_CORE == 'true' }}
         env:
           YQ_VERSION: v4.52.5
           YQ_ARCH: ${{ (inputs.host-platform == 'win-arm64' && 'arm64') || 'amd64' }}
@@ -143,11 +159,21 @@ jobs:
 
       # To keep the build workflow simple, all matrix jobs will build a wheel for later use within this workflow.
       - name: Build and check cuda.pathfinder wheel
+        if: ${{ env.BUILD_PATHFINDER == 'true' }}
         run: |
           pushd cuda_pathfinder
           pip wheel -v --no-deps .
           popd
 
+      - name: Download reusable cuda.pathfinder wheel
+        if: ${{ env.BUILD_PATHFINDER != 'true' }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: cuda-pathfinder-wheel
+          path: cuda_pathfinder
+          github-token: ${{ github.token }}
+          run-id: ${{ env.BASELINE_RUN_ID }}
+
       - name: List the cuda.pathfinder artifacts directory
         run: |
           if [[ "${{ inputs.host-platform }}" == win* ]]; then
@@ -161,10 +187,24 @@ jobs:
       # We only need/want a single pure python wheel, pick linux-64 index 0.
       # This is what we will use for testing & releasing.
       - name: Check cuda.pathfinder wheel
-        if: ${{ strategy.job-index == 0 && inputs.host-platform == 'linux-64' }}
+        if: ${{ env.BUILD_PATHFINDER == 'true' && strategy.job-index == 0 && inputs.host-platform == 'linux-64' }}
         run: |
           twine check --strict cuda_pathfinder/*.whl
 
+      - name: Constrain builds to the local cuda.pathfinder wheel
+        if: ${{ env.BUILD_BINDINGS == 'true' }}
+        run: |
+          pathfinder_wheels=(cuda_pathfinder/cuda_pathfinder-*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          mkdir -p wheel-constraints
+          if [[ "${{ inputs.host-platform }}" == win* ]]; then
+            pathfinder_uri="file:///$(cygpath -am "${pathfinder_wheels[0]}")"
+          else
+            pathfinder_uri="file:///host$(realpath "${pathfinder_wheels[0]}")"
+          fi
+          printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}" | tee wheel-constraints/cuda-bindings.txt
+
       - name: Upload cuda.pathfinder build artifacts
         if: ${{ strategy.job-index == 0 && inputs.host-platform == 'linux-64' }}
         uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a  # v7.0.1
@@ -174,21 +214,23 @@ jobs:
           if-no-files-found: error
 
       - name: Set up mini CTK
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' || env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' }}
         uses: ./.github/actions/fetch_ctk
         continue-on-error: false
         with:
           host-platform: ${{ inputs.host-platform }}
           cuda-version: ${{ inputs.cuda-version }}
-          cuda-channel: ${{ inputs.cuda-channel }}
 
       - name: Build cuda.bindings wheel
-        uses: pypa/cibuildwheel@294735312765b09d24a2fbec22660ce817587d55  # v4.1.0
+        if: ${{ env.BUILD_BINDINGS == 'true' }}
+        uses: pypa/cibuildwheel@1828c10ab37f080699c7b81cea34097c684a7074  # v4.2.0
         with:
           package-dir: ./cuda_bindings/
           output-dir: ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}
         env:
           CIBW_BUILD: ${{ env.CIBW_BUILD }}
-          CIBW_ARCHS_WINDOWS: ${{ (inputs.host-platform == 'win-arm64' && 'ARM64') || 'AMD64' }}
+          CIBW_BEFORE_BUILD_LINUX: 'python -m pip install --upgrade "pip>=25.3"'
+          CIBW_BEFORE_BUILD_WINDOWS: 'python -m pip install --upgrade "pip>=25.3" delvewheel'
           # TODO: remove cpython-prerelease once 3.15 is officially supported
           # Allow CPython pre-release builds (currently 3.15 / 3.15t). This is a
           # no-op for stable Python versions because CIBW_BUILD still filters
@@ -198,6 +240,8 @@ jobs:
           CIBW_ENVIRONMENT_LINUX: >
             CUDA_PATH=/host/${{ env.CUDA_PATH }}
             CUDA_PYTHON_PARALLEL_LEVEL=${{ env.CUDA_PYTHON_PARALLEL_LEVEL }}
+            PIP_BUILD_CONSTRAINT=/host/${{ github.workspace }}/wheel-constraints/cuda-bindings.txt
+            PIP_CONSTRAINT=/host/${{ github.workspace }}/wheel-constraints/cuda-bindings.txt
             CC="/host/${{ env.SCCACHE_PATH }} cc"
             CXX="/host/${{ env.SCCACHE_PATH }} c++"
             SCCACHE_GHA_ENABLED=true
@@ -211,6 +255,8 @@ jobs:
           CIBW_ENVIRONMENT_WINDOWS: >
             CUDA_PATH="$(cygpath -w ${{ env.CUDA_PATH }})"
             CUDA_PYTHON_PARALLEL_LEVEL=${{ env.CUDA_PYTHON_PARALLEL_LEVEL }}
+            PIP_BUILD_CONSTRAINT="$(cygpath -w ./wheel-constraints/cuda-bindings.txt)"
+            PIP_CONSTRAINT="$(cygpath -w ./wheel-constraints/cuda-bindings.txt)"
           # check cache stats before leaving cibuildwheel
           CIBW_BEFORE_TEST_LINUX: >
             "/host/${{ env.SCCACHE_PATH }}" --show-adv-stats &&
@@ -222,13 +268,22 @@ jobs:
             echo "ok!"
 
       - name: Report sccache stats (cuda.bindings)
-        if: ${{ !startsWith(inputs.host-platform, 'win') }}
+        if: ${{ env.BUILD_BINDINGS == 'true' && !startsWith(inputs.host-platform, 'win') }}
         uses: ./.github/actions/sccache-summary
         with:
           json-file: sccache_bindings.json
           label: "cuda.bindings"
           build-step: "Build cuda.bindings wheel"
 
+      - name: Download reusable cuda.bindings wheel
+        if: ${{ env.BUILD_BINDINGS != 'true' }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: ${{ env.CUDA_BINDINGS_ARTIFACT_BASENAME }}-${{ env.BASELINE_SHA }}
+          path: ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}
+          github-token: ${{ github.token }}
+          run-id: ${{ env.BASELINE_RUN_ID }}
+
       - name: List the cuda.bindings artifacts directory
         run: |
           if [[ "${{ inputs.host-platform }}" == win* ]]; then
@@ -240,9 +295,32 @@ jobs:
           ls -lahR ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}
 
       - name: Check cuda.bindings wheel
+        if: ${{ env.BUILD_BINDINGS == 'true' }}
         run: |
           twine check --strict ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}/*.whl
 
+      - name: Constrain cuda.core to the local cuda.bindings wheel
+        if: ${{ env.BUILD_CORE == 'true' }}
+        run: |
+          pathfinder_wheels=(cuda_pathfinder/cuda_pathfinder-*.whl)
+          bindings_wheels=("${CUDA_BINDINGS_ARTIFACTS_DIR}"/cuda_bindings-"${BUILD_CUDA_MAJOR}".*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test "${#bindings_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          test -f "${bindings_wheels[0]}"
+          mkdir -p wheel-constraints
+          if [[ "${{ inputs.host-platform }}" == win* ]]; then
+            pathfinder_uri="file:///$(cygpath -am "${pathfinder_wheels[0]}")"
+            bindings_uri="file:///$(cygpath -am "${bindings_wheels[0]}")"
+          else
+            pathfinder_uri="file:///host$(realpath "${pathfinder_wheels[0]}")"
+            bindings_uri="file:///host$(realpath "${bindings_wheels[0]}")"
+          fi
+          {
+            printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}"
+            printf 'cuda-bindings @ %s\n' "${bindings_uri}"
+          } | tee wheel-constraints/cuda-core.txt
+
       - name: Upload cuda.bindings build artifacts
         uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a  # v7.0.1
         with:
@@ -251,13 +329,15 @@ jobs:
           if-no-files-found: error
 
       - name: Build cuda.core wheel
-        uses: pypa/cibuildwheel@294735312765b09d24a2fbec22660ce817587d55  # v4.1.0
+        if: ${{ env.BUILD_CORE == 'true' }}
+        uses: pypa/cibuildwheel@1828c10ab37f080699c7b81cea34097c684a7074  # v4.2.0
         with:
           package-dir: ./cuda_core/
           output-dir: ${{ env.CUDA_CORE_ARTIFACTS_DIR }}
         env:
           CIBW_BUILD: ${{ env.CIBW_BUILD }}
-          CIBW_ARCHS_WINDOWS: ${{ (inputs.host-platform == 'win-arm64' && 'ARM64') || 'AMD64' }}
+          CIBW_BEFORE_BUILD_LINUX: 'python -m pip install --upgrade "pip>=25.3"'
+          CIBW_BEFORE_BUILD_WINDOWS: 'python -m pip install --upgrade "pip>=25.3" delvewheel'
           # TODO: remove cpython-prerelease once 3.15 is officially supported
           # Allow CPython pre-release builds (currently 3.15 / 3.15t). This is a
           # no-op for stable Python versions because CIBW_BUILD still filters
@@ -268,7 +348,8 @@ jobs:
             CUDA_PATH=/host/${{ env.CUDA_PATH }}
             CUDA_PYTHON_PARALLEL_LEVEL=${{ env.CUDA_PYTHON_PARALLEL_LEVEL }}
             CUDA_CORE_BUILD_MAJOR=${{ env.BUILD_CUDA_MAJOR }}
-            PIP_FIND_LINKS=/host/${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}
+            PIP_BUILD_CONSTRAINT=/host/${{ github.workspace }}/wheel-constraints/cuda-core.txt
+            PIP_CONSTRAINT=/host/${{ github.workspace }}/wheel-constraints/cuda-core.txt
             CC="/host/${{ env.SCCACHE_PATH }} cc"
             CXX="/host/${{ env.SCCACHE_PATH }} c++"
             SCCACHE_GHA_ENABLED=true
@@ -283,7 +364,8 @@ jobs:
             CUDA_PATH="$(cygpath -w ${{ env.CUDA_PATH }})"
             CUDA_PYTHON_PARALLEL_LEVEL=${{ env.CUDA_PYTHON_PARALLEL_LEVEL }}
             CUDA_CORE_BUILD_MAJOR=${{ env.BUILD_CUDA_MAJOR }}
-            PIP_FIND_LINKS="$(cygpath -w ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }})"
+            PIP_BUILD_CONSTRAINT="$(cygpath -w ./wheel-constraints/cuda-core.txt)"
+            PIP_CONSTRAINT="$(cygpath -w ./wheel-constraints/cuda-core.txt)"
           # check cache stats before leaving cibuildwheel
           CIBW_BEFORE_TEST_LINUX: >
             "/host${{ env.SCCACHE_PATH }}" --show-adv-stats &&
@@ -295,7 +377,7 @@ jobs:
             echo "ok!"
 
       - name: Report sccache stats (cuda.core)
-        if: ${{ !startsWith(inputs.host-platform, 'win') }}
+        if: ${{ env.BUILD_CORE == 'true' && !startsWith(inputs.host-platform, 'win') }}
         uses: ./.github/actions/sccache-summary
         with:
           json-file: sccache_core.json
@@ -303,6 +385,7 @@ jobs:
           build-step: "Build cuda.core wheel"
 
       - name: List the cuda.core artifacts directory and rename
+        if: ${{ env.BUILD_CORE == 'true' }}
         run: |
           if [[ "${{ inputs.host-platform }}" == win* ]]; then
             export CHOWN=chown
@@ -324,24 +407,33 @@ jobs:
 
           ls -lahR ${{ env.CUDA_CORE_ARTIFACTS_DIR }}
 
-      - name: Finalize single-major cuda.core wheel
-        if: ${{ inputs.single-cuda-major }}
-        run: |
-          for wheel in "${{ env.CUDA_CORE_ARTIFACTS_DIR }}"/cu"${BUILD_CUDA_MAJOR}"/*.cu"${BUILD_CUDA_MAJOR}".whl; do
-            base_name=$(basename "${wheel}" ".cu${BUILD_CUDA_MAJOR}.whl")
-            mv "${wheel}" "${{ env.CUDA_CORE_ARTIFACTS_DIR }}/${base_name}.whl"
-          done
-          ls -lahR "${{ env.CUDA_CORE_ARTIFACTS_DIR }}"
+      - name: Download reusable cuda.core wheel
+        if: ${{ env.BUILD_CORE != 'true' }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: ${{ env.CUDA_CORE_ARTIFACT_BASENAME }}-${{ env.BASELINE_SHA }}
+          path: ${{ env.CUDA_CORE_ARTIFACTS_DIR }}
+          github-token: ${{ github.token }}
+          run-id: ${{ env.BASELINE_RUN_ID }}
 
       # We only need/want a single pure python wheel, pick linux-64 index 0.
       - name: Build and check cuda-python wheel
-        if: ${{ strategy.job-index == 0 && inputs.host-platform == 'linux-64' }}
+        if: ${{ env.BUILD_PYTHON == 'true' && strategy.job-index == 0 && inputs.host-platform == 'linux-64' }}
         run: |
           pushd cuda_python
           pip wheel -v --no-deps .
           twine check --strict *.whl
           popd
 
+      - name: Download reusable cuda-python wheel
+        if: ${{ env.BUILD_PYTHON != 'true' && strategy.job-index == 0 && inputs.host-platform == 'linux-64' }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: cuda-python-wheel
+          path: cuda_python
+          github-token: ${{ github.token }}
+          run-id: ${{ env.BASELINE_RUN_ID }}
+
       - name: List the cuda-python artifacts directory
         if: ${{ strategy.job-index == 0 && inputs.host-platform == 'linux-64' }}
         run: |
@@ -362,24 +454,26 @@ jobs:
           if-no-files-found: error
 
       - name: Set up Python
-        if: ${{ !inputs.single-cuda-major }}
         id: setup-python2
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        if: ${{ env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' }}
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
-          # TODO: Pin beta.2 precisely until cibuildwheel catches up (b4 broke ABI for Cython);
-          # this precise pin requires the explicit `freethreaded`.
-          # When 3.15 is officially supported we can also remove the `allow-prereleases` override.
-          python-version: ${{ startsWith(matrix.python-version, '3.15') && '3.15.0-beta.2' || matrix.python-version }}
-          freethreaded: ${{ endsWith(matrix.python-version, 't') }}
-          architecture: ${{ ((inputs.host-platform == 'linux-aarch64' || inputs.host-platform == 'win-arm64') && 'arm64') || 'x64' }}
+          python-version: ${{ matrix.python-version }}
+          # TODO: remove allow-prereleases once 3.15 is officially supported
           allow-prereleases: ${{ startsWith(matrix.python-version, '3.15') }}
 
+      - name: Enable Scientific Python Nightly Wheels for Python 3.15
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true') && startsWith(matrix.python-version, '3.15') }}
+        run: |
+          echo "PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple" >> "$GITHUB_ENV"
+          echo "PIP_ONLY_BINARY=numpy" >> "$GITHUB_ENV"
+
       - name: verify free-threaded build
-        if: ${{ !inputs.single-cuda-major && endsWith(matrix.python-version, 't') }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true') && endsWith(matrix.python-version, 't') }}
         run: python -c 'import sys; assert not sys._is_gil_enabled()'
 
       - name: Set up Python include paths
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' }}
         run: |
           if [[ "${{ inputs.host-platform }}" == linux* ]]; then
             echo "CPLUS_INCLUDE_PATH=${Python3_ROOT_DIR}/include/python${{ matrix.python-version }}" >> $GITHUB_ENV
@@ -390,78 +484,19 @@ jobs:
           echo "PY_EXT_SUFFIX=$(python -c "import sysconfig; print(sysconfig.get_config_var('EXT_SUFFIX'))")" >> $GITHUB_ENV
 
       - name: Install cuda.pathfinder (required for next step)
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' }}
         run: |
           pip install cuda_pathfinder/*.whl
 
       - name: Hide GNU link.exe so Meson finds MSVC link.exe
-        if: ${{ !inputs.single-cuda-major && startsWith(inputs.host-platform, 'win') }}
+        if: ${{ startsWith(inputs.host-platform, 'win') && (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true') }}
         run: |
           if [ -f "/c/Program Files/Git/usr/bin/link.exe" ]; then
             mv "/c/Program Files/Git/usr/bin/link.exe" "/c/Program Files/Git/usr/bin/link.exe.bak"
           fi
 
-      # TODO: remove the numpy pre-build steps once 3.15 is officially supported
-      # (numpy will publish pre-built 3.15 wheels at that point)
-      - name: Download and patch numpy sdist (pre-release Python)
-        if: ${{ !inputs.single-cuda-major && startsWith(matrix.python-version, '3.15') }}
-        run: |
-          pip download --no-binary numpy --no-deps "numpy>=1.21.1" -d numpy-sdist/
-          cd numpy-sdist && tar xf numpy-*.tar.gz && rm numpy-*.tar.gz
-          # WAR: numpy 2.4.x ships [tool.cibuildwheel] config that is
-          # incompatible with cibuildwheel v4.0 (cpython-freethreading enable
-          # group, OpenBLAS before-build scripts, etc.). Strip the cibuildwheel
-          # sections but preserve [tool.meson-python] (vendored meson path).
-          python -c "
-          import glob
-          for f in glob.glob('numpy-*/pyproject.toml'):
-              lines, skip = open(f).readlines(), False
-              out = []
-              for line in lines:
-                  hdr = line.strip()
-                  if hdr.startswith('[tool.cibuildwheel') or hdr.startswith('[[tool.cibuildwheel'):
-                      skip = True
-                      continue
-                  if skip and hdr.startswith('[') and 'cibuildwheel' not in hdr:
-                      skip = False
-                  if not skip:
-                      out.append(line)
-              open(f, 'w').writelines(out)
-          "
-          echo "NUMPY_SRC_DIR=$(pwd)/$(ls -d numpy-*/)" >> $GITHUB_ENV
-
-      - name: Build numpy wheel (pre-release Python)
-        if: ${{ !inputs.single-cuda-major && startsWith(matrix.python-version, '3.15') }}
-        uses: pypa/cibuildwheel@294735312765b09d24a2fbec22660ce817587d55  # v4.1.0
-        env:
-          CIBW_BUILD: ${{ env.CIBW_BUILD }}
-          CIBW_SKIP: "*-musllinux* *-win32"
-          CIBW_ARCHS_LINUX: "native"
-          CIBW_ARCHS_WINDOWS: ${{ (inputs.host-platform == 'win-arm64' && 'ARM64') || 'AMD64' }}
-          CIBW_BUILD_VERBOSITY: 1
-          CIBW_CONFIG_SETTINGS: "setup-args=-Dallow-noblas=true"
-          CIBW_CONFIG_SETTINGS_WINDOWS: "setup-args=--vsenv setup-args=-Dallow-noblas=true"
-          CIBW_BEFORE_BUILD_WINDOWS: "pip install delvewheel"
-          CIBW_REPAIR_WHEEL_COMMAND_WINDOWS: "delvewheel repair -w {dest_dir} {wheel}"
-          CIBW_ENABLE: "cpython-prerelease"
-        with:
-          package-dir: ${{ env.NUMPY_SRC_DIR }}
-          output-dir: numpy-wheel/
-
-      - name: Upload numpy wheel
-        if: ${{ !inputs.single-cuda-major && startsWith(matrix.python-version, '3.15') }}
-        uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a  # v7.0.1
-        with:
-          name: numpy-python${{ env.PYTHON_VERSION_FORMATTED }}-${{ inputs.host-platform }}
-          path: numpy-wheel/*.whl
-          if-no-files-found: error
-
-      - name: Install numpy wheel
-        if: ${{ !inputs.single-cuda-major && startsWith(matrix.python-version, '3.15') }}
-        run: pip install numpy-wheel/*.whl
-
       - name: Build cuda.bindings Cython tests
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ env.TEST_BINDINGS == 'true' }}
         run: |
           pip install ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}/*.whl --group ./cuda_bindings/pyproject.toml:test
           pushd ${{ env.CUDA_BINDINGS_CYTHON_TESTS_DIR }}
@@ -469,7 +504,7 @@ jobs:
           popd
 
       - name: Upload cuda.bindings Cython tests
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ env.TEST_BINDINGS == 'true' }}
         uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a  # v7.0.1
         with:
           name: ${{ env.CUDA_BINDINGS_ARTIFACT_NAME }}-tests
@@ -477,15 +512,25 @@ jobs:
           if-no-files-found: error
 
       - name: Build cuda.core Cython tests
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ env.TEST_CORE == 'true' }}
         run: |
-          pip install ${{ env.CUDA_CORE_ARTIFACTS_DIR }}/"cu${BUILD_CUDA_MAJOR}"/*.whl --group ./cuda_core/pyproject.toml:test
+          pip install ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}/*.whl
+          if ${{ env.BUILD_CORE == 'true' }}; then
+            core_wheel=$(find "${{ env.CUDA_CORE_ARTIFACTS_DIR }}/cu${BUILD_CUDA_MAJOR}" -maxdepth 1 -type f -name '*.whl' -print -quit)
+          else
+            core_wheel=$(find "${{ env.CUDA_CORE_ARTIFACTS_DIR }}" -maxdepth 1 -type f -name '*.whl' -print -quit)
+          fi
+          if [[ -z "${core_wheel}" ]]; then
+            echo "No cuda.core wheel found" >&2
+            exit 1
+          fi
+          pip install "${core_wheel}" --group ./cuda_core/pyproject.toml:test
           pushd ${{ env.CUDA_CORE_CYTHON_TESTS_DIR }}
           bash build_tests.sh
           popd
 
       - name: Upload cuda.core Cython tests
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ env.TEST_CORE == 'true' }}
         uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a  # v7.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}-tests
@@ -494,7 +539,7 @@ jobs:
 
       # Note: This overwrites CUDA_PATH etc
       - name: Set up mini CTK
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ !inputs.single-cuda-major && (env.BUILD_CORE == 'true' || env.TEST_CORE == 'true') }}
         uses: ./.github/actions/fetch_ctk
         continue-on-error: false
         with:
@@ -503,13 +548,13 @@ jobs:
           cuda-path: "./cuda_toolkit_prev"
 
       - name: Build cuda.core test binaries
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ !inputs.single-cuda-major && env.TEST_CORE == 'true' }}
         run: |
           nvcc --version
           python "${{ env.CUDA_CORE_TEST_BINARIES_DIR }}/build_test_binaries.py"
 
       - name: Upload cuda.core test binaries
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ !inputs.single-cuda-major && env.TEST_CORE == 'true' }}
         uses: actions/upload-artifact@043fb46d1a93c77aae656e7c1c64a875d1fc6a0a  # v7.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}-test-binaries
@@ -520,7 +565,7 @@ jobs:
           if-no-files-found: error
 
       - name: Download cuda.bindings build artifacts from the prior branch
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ !inputs.single-cuda-major && env.BUILD_CORE == 'true' }}
         env:
           GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
@@ -537,25 +582,56 @@ jobs:
           fi
 
           OLD_BRANCH=$(yq '.backport_branch' ci/versions.yml)
-          OLD_BASENAME="cuda-bindings-python${PYTHON_VERSION_FORMATTED}-cuda*-${{ inputs.host-platform }}*"
-          LATEST_PRIOR_RUN_ID=$(./ci/tools/lookup-run-id --branch "${OLD_BRANCH}" NVIDIA/cuda-python "CI")
-
-          gh run download $LATEST_PRIOR_RUN_ID -p ${OLD_BASENAME} -R NVIDIA/cuda-python
-          rm -rf ${OLD_BASENAME}-tests  # exclude cython test artifacts
-          ls -al $OLD_BASENAME
-          mkdir -p "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"
-          mv $OLD_BASENAME/*.whl "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"
-          rmdir $OLD_BASENAME
+          OLD_ARTIFACT_PATTERN="cuda-bindings-python${PYTHON_VERSION_FORMATTED}-cuda*-${{ inputs.host-platform }}-*[0-9a-f]"
+          LATEST_PRIOR_RUN_ID=$(./ci/tools/lookup-run-id \
+            --branch "${OLD_BRANCH}" \
+            --artifact "${OLD_ARTIFACT_PATTERN}" \
+            NVIDIA/cuda-python "CI")
+          PREV_BINDINGS_DIR="cuda_bindings/dist-prev"
+
+          gh run download \
+            "${LATEST_PRIOR_RUN_ID}" \
+            -p "${OLD_ARTIFACT_PATTERN}" \
+            -R NVIDIA/cuda-python
+          OLD_ARTIFACT_DIR=$(compgen -G "${OLD_ARTIFACT_PATTERN}")
+          test -d "${OLD_ARTIFACT_DIR}"
+          ls -al "${OLD_ARTIFACT_DIR}"
+          mkdir -p "${PREV_BINDINGS_DIR}"
+          mv "${OLD_ARTIFACT_DIR}"/*.whl "${PREV_BINDINGS_DIR}"
+          rmdir "${OLD_ARTIFACT_DIR}"
+
+      - name: Constrain previous cuda.core to the downloaded cuda.bindings wheel
+        if: ${{ !inputs.single-cuda-major && env.BUILD_CORE == 'true' }}
+        run: |
+          pathfinder_wheels=(cuda_pathfinder/cuda_pathfinder-*.whl)
+          bindings_wheels=(cuda_bindings/dist-prev/cuda_bindings-"${BUILD_PREV_CUDA_MAJOR}".*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test "${#bindings_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          test -f "${bindings_wheels[0]}"
+          mkdir -p wheel-constraints
+          if [[ "${{ inputs.host-platform }}" == win* ]]; then
+            pathfinder_uri="file:///$(cygpath -am "${pathfinder_wheels[0]}")"
+            bindings_uri="file:///$(cygpath -am "${bindings_wheels[0]}")"
+          else
+            pathfinder_uri="file:///host$(realpath "${pathfinder_wheels[0]}")"
+            bindings_uri="file:///host$(realpath "${bindings_wheels[0]}")"
+          fi
+          {
+            printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}"
+            printf 'cuda-bindings @ %s\n' "${bindings_uri}"
+          } | tee wheel-constraints/cuda-core-prev.txt
 
       - name: Build cuda.core wheel
-        if: ${{ !inputs.single-cuda-major }}
-        uses: pypa/cibuildwheel@294735312765b09d24a2fbec22660ce817587d55  # v4.1.0
+        if: ${{ !inputs.single-cuda-major && env.BUILD_CORE == 'true' }}
+        uses: pypa/cibuildwheel@1828c10ab37f080699c7b81cea34097c684a7074  # v4.2.0
         with:
           package-dir: ./cuda_core/
           output-dir: ${{ env.CUDA_CORE_ARTIFACTS_DIR }}
         env:
           CIBW_BUILD: ${{ env.CIBW_BUILD }}
-          CIBW_ARCHS_WINDOWS: ${{ (inputs.host-platform == 'win-arm64' && 'ARM64') || 'AMD64' }}
+          CIBW_BEFORE_BUILD_LINUX: 'python -m pip install --upgrade "pip>=25.3"'
+          CIBW_BEFORE_BUILD_WINDOWS: 'python -m pip install --upgrade "pip>=25.3" delvewheel'
           # TODO: remove cpython-prerelease once 3.15 is officially supported
           # Allow CPython pre-release builds (currently 3.15 / 3.15t). This is a
           # no-op for stable Python versions because CIBW_BUILD still filters
@@ -566,7 +642,8 @@ jobs:
             CUDA_PATH=/host/${{ env.CUDA_PATH }}
             CUDA_PYTHON_PARALLEL_LEVEL=${{ env.CUDA_PYTHON_PARALLEL_LEVEL }}
             CUDA_CORE_BUILD_MAJOR=${{ env.BUILD_PREV_CUDA_MAJOR }}
-            PIP_FIND_LINKS=/host/${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}
+            PIP_BUILD_CONSTRAINT=/host/${{ github.workspace }}/wheel-constraints/cuda-core-prev.txt
+            PIP_CONSTRAINT=/host/${{ github.workspace }}/wheel-constraints/cuda-core-prev.txt
             CC="/host/${{ env.SCCACHE_PATH }} cc"
             CXX="/host/${{ env.SCCACHE_PATH }} c++"
             SCCACHE_GHA_ENABLED=true
@@ -581,7 +658,8 @@ jobs:
             CUDA_PATH="$(cygpath -w ${{ env.CUDA_PATH }})"
             CUDA_PYTHON_PARALLEL_LEVEL=${{ env.CUDA_PYTHON_PARALLEL_LEVEL }}
             CUDA_CORE_BUILD_MAJOR=${{ env.BUILD_PREV_CUDA_MAJOR }}
-            PIP_FIND_LINKS="$(cygpath -w ${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }})"
+            PIP_BUILD_CONSTRAINT="$(cygpath -w ./wheel-constraints/cuda-core-prev.txt)"
+            PIP_CONSTRAINT="$(cygpath -w ./wheel-constraints/cuda-core-prev.txt)"
           # check cache stats before leaving cibuildwheel
           CIBW_BEFORE_TEST_LINUX: >
             "/host${{ env.SCCACHE_PATH }}" --show-adv-stats &&
@@ -593,7 +671,7 @@ jobs:
             echo "ok!"
 
       - name: Report sccache stats (cuda.core prev)
-        if: ${{ !inputs.single-cuda-major && !startsWith(inputs.host-platform, 'win') }}
+        if: ${{ !inputs.single-cuda-major && env.BUILD_CORE == 'true' && !startsWith(inputs.host-platform, 'win') }}
         uses: ./.github/actions/sccache-summary
         with:
           json-file: sccache_core_prev.json
@@ -601,7 +679,7 @@ jobs:
           build-step: "Build cuda.core wheel"
 
       - name: List the cuda.core artifacts directory and rename
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ !inputs.single-cuda-major && env.BUILD_CORE == 'true' }}
         run: |
           if [[ "${{ inputs.host-platform }}" == win* ]]; then
             export CHOWN=chown
@@ -625,7 +703,7 @@ jobs:
           ls -lahR ${{ env.CUDA_CORE_ARTIFACTS_DIR }}
 
       - name: Merge cuda.core wheels
-        if: ${{ !inputs.single-cuda-major }}
+        if: ${{ !inputs.single-cuda-major && env.BUILD_CORE == 'true' }}
         run: |
           pip install wheel
           python ci/tools/merge_cuda_core_wheels.py \
@@ -633,7 +711,17 @@ jobs:
             "${{ env.CUDA_CORE_ARTIFACTS_DIR }}"/cu"${BUILD_PREV_CUDA_MAJOR}"/cuda_core*.whl \
             --output-dir "${{ env.CUDA_CORE_ARTIFACTS_DIR }}"
 
+      - name: Finalize single-major cuda.core wheel
+        if: ${{ inputs.single-cuda-major && env.BUILD_CORE == 'true' }}
+        run: |
+          for wheel in "${{ env.CUDA_CORE_ARTIFACTS_DIR }}"/cu"${BUILD_CUDA_MAJOR}"/*.cu"${BUILD_CUDA_MAJOR}".whl; do
+            base_name=$(basename "${wheel}" ".cu${BUILD_CUDA_MAJOR}.whl")
+            mv "${wheel}" "${{ env.CUDA_CORE_ARTIFACTS_DIR }}/${base_name}.whl"
+          done
+          ls -lahR "${{ env.CUDA_CORE_ARTIFACTS_DIR }}"
+
       - name: Check cuda.core wheel
+        if: ${{ env.BUILD_CORE == 'true' }}
         run: |
           twine check --strict ${{ env.CUDA_CORE_ARTIFACTS_DIR }}/*.whl
 
diff --git a/.github/workflows/ci-nightly.yml b/.github/workflows/ci-nightly.yml
index 0188ebf2524..a3179c1e155 100644
--- a/.github/workflows/ci-nightly.yml
+++ b/.github/workflows/ci-nightly.yml
@@ -38,7 +38,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repository
-        uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10  # v6.0.3
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           fetch-depth: 1
 
@@ -49,6 +49,7 @@ jobs:
           python -m pytest -v --noconftest ci/tools/tests
 
   find-wheels:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     outputs:
       RUN_ID: ${{ steps.find.outputs.run_id }}
@@ -56,7 +57,7 @@ jobs:
       CUDA_BUILD_VER: ${{ steps.find.outputs.cuda_build_ver }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           fetch-depth: 1
 
@@ -309,7 +310,7 @@ jobs:
 
   checks:
     name: Nightly check status
-    if: always()
+    if: ${{ always() && github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     needs:
       - test-ci-tools-for-release
diff --git a/.github/workflows/ci-pixi-source-test.yml b/.github/workflows/ci-pixi-source-test.yml
index 93e31272161..1fa0261c02b 100644
--- a/.github/workflows/ci-pixi-source-test.yml
+++ b/.github/workflows/ci-pixi-source-test.yml
@@ -15,6 +15,11 @@
 #   - build-smoke (PRs): CPU-only. Source-builds bindings + core, imports them,
 #     builds the cython test extensions and checks placement. Catches the
 #     compile / ABI / .so-placement regressions WITHOUT a GPU.
+#   - build-identity-roundtrip (nightly + manual): CPU-only. cu13 -> cu12 ->
+#     cu13 in one checkout, so build artifacts cannot be reused across CUDA
+#     majors. Kept off PRs to avoid adding another job to the org's shared
+#     concurrent-job quota; the fast unit tests in
+#     cuda_core/tests/test_build_hooks.py cover the same intent per-PR.
 #   - full-test (nightly + manual): GPU runner, full `pixi run test`.
 
 name: "CI: pixi run test (source build)"
@@ -59,6 +64,114 @@ env:
   PIXI_VERSION: "v0.73.0"
 
 jobs:
+  # ── PR guard: CPU-only build + import + placement smoke ──
+  build-smoke:
+    name: "build smoke (cu13, linux-64, CPU)"
+    if: >-
+      github.repository_owner == 'nvidia' &&
+      (github.event_name == 'pull_request' || github.event_name == 'workflow_dispatch')
+    runs-on: ubuntu-latest
+    timeout-minutes: 45
+    steps:
+      - name: Checkout ${{ github.event.repository.name }}
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
+        with:
+          # Full history + tags so setuptools-scm derives the real (13.x)
+          # package version; a shallow checkout yields 0.1.dev1, which trips
+          # cuda.core's "cuda.bindings 12.x or 13.x must be installed" guard.
+          fetch-depth: 0
+
+      - name: Setup pixi
+        # Pinned to a commit SHA; install logic lives in the action and is
+        # auditable/pinned (vs. a curl|bash of an unverified installer).
+        uses: prefix-dev/setup-pixi@d3f436a425481402e6a95a1d1fc10331c708cd9e # v0.10.2
+        with:
+          pixi-version: ${{ env.PIXI_VERSION }}
+          run-install: false
+
+      - name: Source-build + import + cython-placement smoke
+        env:
+          CUDA_ENV: ${{ inputs.cuda-env || 'cu13' }}
+        run: |
+          # pathfinder: pure-Python, no GPU.
+          pixi run -e "${CUDA_ENV}" test-pathfinder
+
+          # bindings + core: force the source build (catches nvrtc/driver
+          # compile errors like #2182) and import them (catches ABI mismatches).
+          pixi run --manifest-path cuda_bindings -e "${CUDA_ENV}" \
+            python -c "import cuda.bindings.driver, cuda.bindings.nvrtc, cuda.bindings.runtime; print('bindings import OK')"
+          pixi run --manifest-path cuda_core -e "${CUDA_ENV}" \
+            python -c "import cuda.core; print('core import OK')"
+
+          # cython test extensions: build them and confirm each .so landed next
+          # to its .pyx in tests/cython (catches the placement regression #2180).
+          pixi run --manifest-path cuda_bindings -e "${CUDA_ENV}" build-cython-tests
+          pixi run --manifest-path cuda_core -e "${CUDA_ENV}" build-cython-tests
+          for d in cuda_bindings/tests/cython cuda_core/tests/cython; do
+            if ! compgen -G "${d}/*.cpython-*.so" > /dev/null; then
+              echo "::error::no compiled cython test .so in ${d} (placement regression)"
+              exit 1
+            fi
+          done
+          echo "cython test extensions placed correctly"
+
+  # ── Nightly guard: build artifacts must be CUDA-major aware ──
+  #
+  # Neither Cython nor setuptools tracks the CUDA major in its own up-to-date
+  # check: Cython does not hash `compile_time_env`, and an editable install's
+  # .so is named by the Python ABI tag alone. Before build_hooks keyed them,
+  # a cu13 build followed by a cu12 build in the same checkout failed while
+  # compiling cu13-generated C++ against CUDA 12 headers.
+  #
+  # The round trip (not just cu13 -> cu12) is what catches the second half:
+  # coming back to cu13 must not silently reuse the cu12 extension.
+  #
+  # cuda_core only: cuda_bindings cannot be source-built in its cu12
+  # environment at all, for reasons unrelated to stale artifacts.
+  build-identity-roundtrip:
+    name: "cu13 -> cu12 -> cu13 round trip (linux-64, CPU)"
+    if: ${{ (github.event_name == 'schedule' || github.event_name == 'workflow_dispatch') && github.repository_owner == 'nvidia' }}
+    runs-on: ubuntu-latest
+    timeout-minutes: 60
+    steps:
+      - name: Checkout ${{ github.event.repository.name }}
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
+        with:
+          # Full history + tags so setuptools-scm derives the real (13.x)
+          # package version; a shallow checkout yields 0.1.dev1, which trips
+          # cuda.core's "cuda.bindings 12.x or 13.x must be installed" guard.
+          fetch-depth: 0
+
+      - name: Setup pixi
+        # Pinned to a commit SHA; install logic lives in the action and is
+        # auditable/pinned (vs. a curl|bash of an unverified installer).
+        uses: prefix-dev/setup-pixi@d3f436a425481402e6a95a1d1fc10331c708cd9e # v0.10.2
+        with:
+          pixi-version: ${{ env.PIXI_VERSION }}
+          run-install: false
+
+      - name: Build cu13, then cu12, then cu13 again in one checkout
+        run: |
+          for cuda_env in cu13 cu12 cu13; do
+            echo "::group::${cuda_env}"
+            pixi run --manifest-path cuda_core -e "${cuda_env}" \
+              python -c "import cuda.core; print('core import OK')"
+            echo "::endgroup::"
+          done
+          # The last build was cu13, and each major must have kept its own
+          # generated sources rather than overwriting the other's.
+          stamp=$(cat cuda_core/build/.build-cuda-major)
+          if [ "${stamp}" != "13" ]; then
+            echo "::error::build stamp is '${stamp}', expected 13"
+            exit 1
+          fi
+          for major in cu12 cu13; do
+            if [ ! -d "cuda_core/build/cython/${major}" ]; then
+              echo "::error::no ${major} generated-source directory"
+              exit 1
+            fi
+          done
+
   # ── Nightly: full `pixi run test` on a GPU runner ──
   full-test:
     name: "pixi run test (${{ inputs.cuda-env || 'cu13' }}, linux-64, GPU)"
@@ -68,6 +181,8 @@ jobs:
     container:
       options: -u root --security-opt seccomp=unconfined --shm-size 16g
       image: ubuntu:24.04
+      env:
+        NVIDIA_VISIBLE_DEVICES: ${{ env.NVIDIA_VISIBLE_DEVICES }}
     steps:
       - name: Ensure GPU is working
         run: nvidia-smi
@@ -81,7 +196,7 @@ jobs:
             ca-certificates git libgl1 libegl1
 
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1 # v7.0.1
         with:
           # Full history + tags so setuptools-scm derives the real (13.x)
           # package version; a shallow checkout yields 0.1.dev1, which trips
@@ -95,7 +210,7 @@ jobs:
       - name: Setup pixi
         # Pinned to a commit SHA; install logic lives in the action and is
         # auditable/pinned (vs. a curl|bash of an unverified installer).
-        uses: prefix-dev/setup-pixi@5185adfbffb4bd703da3010310260805d89ebb11 # v0.9.6
+        uses: prefix-dev/setup-pixi@d3f436a425481402e6a95a1d1fc10331c708cd9e # v0.10.2
         with:
           pixi-version: ${{ env.PIXI_VERSION }}
           run-install: false
diff --git a/.github/workflows/ci-workflow-health.yml b/.github/workflows/ci-workflow-health.yml
new file mode 100644
index 00000000000..0a17564b20f
--- /dev/null
+++ b/.github/workflows/ci-workflow-health.yml
@@ -0,0 +1,259 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+name: "CI: Track workflow health"
+
+on:
+  workflow_run:
+    # These names must exactly match the top-level workflows. Keep this list in
+    # sync when an unattended CI workflow is added or renamed.
+    workflows:
+      - "CI"
+      - "CI: Coverage"
+      - "CI: Nightly optional-deps"
+      - "CI: pixi run test (source build)"
+      - "Security Suite (Pulse + CodeQL)"
+      - "Static Analysis: Bandit Scan"
+    types:
+      - completed
+    branches:
+      - main
+
+# Serialize updates to one incident while allowing scheduled and main-push
+# health to be tracked independently for workflows that support both. Queue all
+# events; the script also rejects stale completions because dispatch order is
+# not guaranteed.
+concurrency:
+  group: >-
+    ${{ github.workflow }}-${{ github.event.workflow_run.workflow_id }}-${{
+      github.event.workflow_run.event }}
+  queue: max
+
+permissions: {}
+
+jobs:
+  update-incident:
+    name: Update CI health issue
+    if: >-
+      github.repository == 'NVIDIA/cuda-python' &&
+      (
+        github.event.workflow_run.event == 'schedule' ||
+        (
+          github.event.workflow_run.event == 'push' &&
+          github.event.workflow_run.head_branch == github.event.repository.default_branch
+        )
+      ) &&
+      (
+        github.event.workflow_run.conclusion == 'success' ||
+        contains(
+          fromJSON('["action_required","failure","stale","startup_failure","timed_out"]'),
+          github.event.workflow_run.conclusion
+        ) ||
+        (
+          github.event.workflow_run.event == 'schedule' &&
+          github.event.workflow_run.conclusion == 'cancelled'
+        )
+      )
+    runs-on: ubuntu-latest
+    timeout-minutes: 5
+    permissions:
+      actions: read
+      issues: write
+    steps:
+      - name: Open, update, or close the workflow incident
+        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3  # v9.0.0
+        with:
+          github-token: ${{ github.token }}
+          script: |
+            const run = context.payload.workflow_run;
+            const scheduled = run.event === "schedule";
+            const scopeKey = scheduled ? "schedule" : "push-main";
+            const scopeLabel = scheduled ? "scheduled runs" : "on main";
+            const trackerMarker =
+              `<!-- cuda-python-ci-health:${run.workflow_id}:${scopeKey} -->`;
+            const eventMarker =
+              `<!-- cuda-python-ci-health-event:${run.id}:${run.run_attempt} -->`;
+            const incidentLabel = "ci-workflow-health";
+            const title = `[CI failure] ${run.name} ${scopeLabel}`;
+            const repositoryUrl =
+              `${process.env.GITHUB_SERVER_URL}/${context.repo.owner}/${context.repo.repo}`;
+            const runUrl = `${run.html_url}/attempts/${run.run_attempt}`;
+            const shortSha = run.head_sha.slice(0, 7);
+            const report = [
+              `[${run.name} run #${run.run_number}, attempt ${run.run_attempt}](${runUrl}) ` +
+                `concluded with **${run.conclusion}**.`,
+              "",
+              `- Trigger: \`${run.event}\``,
+              `- Branch: \`${run.head_branch}\``,
+              `- Commit: [\`${shortSha}\`](${repositoryUrl}/commit/${run.head_sha})`,
+              `- Completed: \`${run.updated_at}\``,
+            ].join("\n");
+
+            const {data: {workflow_runs: completedRuns}} =
+              await github.rest.actions.listWorkflowRuns({
+                ...context.repo,
+                workflow_id: run.workflow_id,
+                branch: run.head_branch,
+                event: run.event,
+                status: "completed",
+                per_page: 100,
+              });
+            const isNewer = (candidate, reference) =>
+              candidate.run_number > reference.run_number ||
+              (
+                candidate.run_number === reference.run_number &&
+                candidate.run_attempt > reference.run_attempt
+              );
+            const unhealthyConclusions = new Set([
+              "action_required",
+              "failure",
+              "stale",
+              "startup_failure",
+              "timed_out",
+            ]);
+            const actionableRuns = completedRuns.filter((candidate) =>
+              candidate.conclusion === "success" ||
+              unhealthyConclusions.has(candidate.conclusion) ||
+              (
+                candidate.event === "schedule" &&
+                candidate.conclusion === "cancelled"
+              ),
+            );
+            const latestRun = actionableRuns.reduce(
+              (latest, candidate) => isNewer(candidate, latest) ? candidate : latest,
+              run,
+            );
+            if (isNewer(latestRun, run)) {
+              core.info(
+                `Ignoring stale completion for run #${run.run_number}, attempt ` +
+                  `${run.run_attempt}; run #${latestRun.run_number}, attempt ` +
+                  `${latestRun.run_attempt} has already completed.`,
+              );
+              return;
+            }
+
+            const openIssues = await github.paginate(
+              github.rest.issues.listForRepo,
+              {
+                ...context.repo,
+                state: "open",
+                per_page: 100,
+              },
+            );
+            const incidents = openIssues
+              .filter((issue) =>
+                !issue.pull_request &&
+                typeof issue.body === "string" &&
+                issue.body.includes(trackerMarker),
+              )
+              .sort((left, right) => left.number - right.number);
+
+            if (incidents.length > 1) {
+              core.warning(
+                `Found ${incidents.length} open incidents for ${run.name} (${scopeKey}).`,
+              );
+            }
+
+            for (const incident of incidents) {
+              const hasIncidentLabel = incident.labels.some((label) =>
+                (typeof label === "string" ? label : label.name) === incidentLabel,
+              );
+              if (!hasIncidentLabel) {
+                await github.rest.issues.addLabels({
+                  ...context.repo,
+                  issue_number: incident.number,
+                  labels: [incidentLabel],
+                });
+              }
+            }
+
+            async function eventAlreadyRecorded(issue) {
+              if (issue.body.includes(eventMarker)) {
+                return true;
+              }
+              const comments = await github.paginate(
+                github.rest.issues.listComments,
+                {
+                  ...context.repo,
+                  issue_number: issue.number,
+                  per_page: 100,
+                },
+              );
+              return comments.some((comment) =>
+                typeof comment.body === "string" &&
+                comment.body.includes(eventMarker),
+              );
+            }
+
+            if (run.conclusion === "success") {
+              if (incidents.length === 0) {
+                core.info(`No open incident for ${run.name} (${scopeKey}).`);
+                return;
+              }
+
+              for (const incident of incidents) {
+                if (!(await eventAlreadyRecorded(incident))) {
+                  await github.rest.issues.createComment({
+                    ...context.repo,
+                    issue_number: incident.number,
+                    body: [
+                      eventMarker,
+                      "### Recovered",
+                      "",
+                      report,
+                      "",
+                      "Closing this incident automatically.",
+                    ].join("\n"),
+                  });
+                }
+                await github.rest.issues.update({
+                  ...context.repo,
+                  issue_number: incident.number,
+                  state: "closed",
+                  state_reason: "completed",
+                });
+              }
+              return;
+            }
+
+            if (incidents.length === 0) {
+              await github.rest.issues.create({
+                ...context.repo,
+                title,
+                labels: ["bug", "CI/CD", "triage", incidentLabel],
+                body: [
+                  trackerMarker,
+                  eventMarker,
+                  "This issue tracks an unhealthy unattended CI workflow.",
+                  "Subsequent failures are recorded in comments; a successful run in the",
+                  "same trigger scope closes the issue automatically.",
+                  "",
+                  "### First unhealthy run",
+                  "",
+                  report,
+                  "",
+                  "_Created automatically by the CI workflow-health monitor._",
+                ].join("\n"),
+              });
+              return;
+            }
+
+            const incident = incidents[0];
+            if (await eventAlreadyRecorded(incident)) {
+              core.info(
+                `Run ${run.id}, attempt ${run.run_attempt} is already recorded in ` +
+                  `issue #${incident.number}.`,
+              );
+              return;
+            }
+            await github.rest.issues.createComment({
+              ...context.repo,
+              issue_number: incident.number,
+              body: [
+                eventMarker,
+                "### Another unhealthy run",
+                "",
+                report,
+              ].join("\n"),
+            });
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index e1d7071b7c7..ca993c55298 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -28,14 +28,16 @@ on:
 
 jobs:
   ci-vars:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     outputs:
       CUDA_BUILD_VER: ${{ steps.get-vars.outputs.cuda_build_ver }}
-      CUDA_BUILD_CHANNEL: ${{ steps.get-vars.outputs.cuda_build_channel }}
       CUDA_PREV_BUILD_VER: ${{ steps.get-vars.outputs.cuda_prev_build_ver }}
+      WINDOWS_ARM64_SUPPORTED: ${{ steps.get-vars.outputs.windows_arm64_supported }}
+      WINDOWS_ARM64_SINGLE_CUDA_MAJOR: ${{ steps.get-vars.outputs.windows_arm64_single_cuda_major }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           fetch-depth: 1
       - name: Get CUDA build versions
@@ -44,20 +46,49 @@ jobs:
           cuda_build_ver=$(yq '.cuda.build.version' ci/versions.yml)
           echo "cuda_build_ver=$cuda_build_ver" >> $GITHUB_OUTPUT
 
-          cuda_build_channel=$(yq '.cuda.build.channel // "stable"' ci/versions.yml)
-          echo "cuda_build_channel=$cuda_build_channel" >> $GITHUB_OUTPUT
-
           cuda_prev_build_ver=$(yq '.cuda.prev_build.version' ci/versions.yml)
           echo "cuda_prev_build_ver=$cuda_prev_build_ver" >> $GITHUB_OUTPUT
 
+          # Windows ARM64 is available starting with CUDA 13.4.
+          if [[ "$cuda_build_ver" =~ ^([0-9]+)\.([0-9]+)(\.|$) ]]; then
+            cuda_build_major="${BASH_REMATCH[1]}"
+            cuda_build_minor="${BASH_REMATCH[2]}"
+          else
+            echo "Invalid CUDA build version: $cuda_build_ver" >&2
+            exit 1
+          fi
+          if (( cuda_build_major > 13 || (cuda_build_major == 13 && cuda_build_minor >= 4) )); then
+            windows_arm64_supported=true
+          else
+            windows_arm64_supported=false
+          fi
+          echo "windows_arm64_supported=$windows_arm64_supported" >> $GITHUB_OUTPUT
+
+          # No CUDA 13 windows-arm64 toolkit exists for a major other than the
+          # current one (windows-arm64 support started mid-way through the 13.x
+          # series), so cuda.core can only be built against a single CUDA major
+          # while the build major is still 13. Once the build major advances to
+          # 14, a CUDA 13 windows-arm64 toolkit will exist as the prior major.
+          if [[ "$cuda_build_major" == "13" ]]; then
+            windows_arm64_single_cuda_major=true
+          else
+            windows_arm64_single_cuda_major=false
+          fi
+          echo "windows_arm64_single_cuda_major=$windows_arm64_single_cuda_major" >> $GITHUB_OUTPUT
+
   should-skip:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      pull-requests: read
     outputs:
       skip: ${{ steps.get-should-skip.outputs.skip }}
       doc-only: ${{ steps.get-should-skip.outputs.doc_only }}
+      base-ref: ${{ steps.get-should-skip.outputs.base_ref }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
       - name: Compute whether to skip builds and tests
         id: get-should-skip
         env:
@@ -66,182 +97,280 @@ jobs:
           set -euxo pipefail
           if ${{ startsWith(github.ref_name, 'pull-request/') }}; then
             pr_number="$(grep -Po '(\d+)$' <<< '${{ github.ref_name }}')"
-            pr_title="$(gh pr view "${pr_number}" --json title --jq '.title')"
+            pr="$(gh pr view "${pr_number}" --json baseRefName,title)"
+            pr_title="$(jq -r '.title' <<< "${pr}")"
+            base_ref="$(jq -r '.baseRefName' <<< "${pr}")"
             skip="$(echo "${pr_title}" | grep -q '\[no-ci\]' && echo true || echo false)"
             doc_only="$(echo "${pr_title}" | grep -q '\[doc-only\]' && echo true || echo false)"
           else
             skip=false
             doc_only=false
+            base_ref=""
           fi
           echo "skip=${skip}" >> "$GITHUB_OUTPUT"
           echo "doc_only=${doc_only}" >> "$GITHUB_OUTPUT"
+          echo "base_ref=${base_ref}" >> "$GITHUB_OUTPUT"
 
-  # Detect which top-level modules were touched by the PR so downstream build
-  # and test jobs can avoid rebuilding/retesting modules unaffected by the
-  # change. See issue #299.
+  # Detect which packages were touched by the PR so downstream build and test
+  # jobs can avoid rebuilding/retesting packages unaffected by the change.
+  # See issue #299.
   #
   # Dependency graph (verified in pyproject.toml files):
   #   cuda_pathfinder   -> (no internal deps)
   #   cuda_bindings     -> cuda_pathfinder
   #   cuda_core         -> cuda_pathfinder, cuda_bindings
-  #   cuda_python       -> cuda_bindings (meta package)
+  #   cuda_python       -> cuda_pathfinder, cuda_bindings, cuda_core (meta package)
   #
   # A change to cuda_pathfinder (or shared infra) forces a rebuild of every
   # downstream module. A change to cuda_bindings forces rebuild of cuda_core.
-  # A change to cuda_core alone skips rebuilding/retesting cuda_bindings.
+  # A change to cuda_core alone skips rebuilding/retesting cuda_bindings and
+  # cuda_pathfinder, but still retests the downstream cuda-python metapackage.
+  # Shared build/orchestration changes run the full pipeline; test-only CI
+  # infrastructure runs every test suite without rebuilding package wheels.
   # On push to main, tag refs, schedule, or workflow_dispatch events we
   # unconditionally run everything because there is no meaningful "changed
   # paths" baseline for those events.
   detect-changes:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
+    needs: should-skip
+    permissions:
+      actions: read
+      contents: read
     outputs:
-      bindings: ${{ steps.compose.outputs.bindings }}
-      core: ${{ steps.compose.outputs.core }}
-      pathfinder: ${{ steps.compose.outputs.pathfinder }}
-      python_meta: ${{ steps.compose.outputs.python_meta }}
-      test_helpers: ${{ steps.compose.outputs.test_helpers }}
-      shared: ${{ steps.compose.outputs.shared }}
-      build_bindings: ${{ steps.compose.outputs.build_bindings }}
-      build_core: ${{ steps.compose.outputs.build_core }}
-      build_pathfinder: ${{ steps.compose.outputs.build_pathfinder }}
-      test_bindings: ${{ steps.compose.outputs.test_bindings }}
-      test_core: ${{ steps.compose.outputs.test_core }}
-      test_pathfinder: ${{ steps.compose.outputs.test_pathfinder }}
+      workplan: ${{ steps.workplan.outputs.workplan }}
     steps:
       - name: Checkout repository
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
-          # Treeless clone: commit graph is needed for `git merge-base` and
-          # `git diff --name-only` below, but historical blobs aren't.
+          # Treeless clone: the commit graph is needed to resolve the PR merge
+          # base and classify its changed paths, but historical blobs aren't.
           fetch-depth: 0
           filter: blob:none
 
-      # copy-pr-bot pushes every PR (whether it targets main or a backport
-      # branch such as 12.9.x) to pull-request/<N>, so the base branch
-      # cannot be inferred from github.ref_name. Look it up via the
-      # upstream PR metadata so the diff below is rooted at the right place.
-      - name: Resolve PR base branch
-        id: pr-info
-        if: ${{ startsWith(github.ref_name, 'pull-request/') }}
-        uses: nv-gha-runners/get-pr-info@main
-
-      - name: Detect changed paths
-        id: filter
+      - name: Resolve PR merge base
+        id: merge-base
         if: ${{ startsWith(github.ref_name, 'pull-request/') }}
         env:
-          # GitHub Actions evaluates step-level `env:` expressions eagerly —
-          # the step's `if:` gate does NOT short-circuit them. On non-PR
-          # events (push/tag/schedule), `pr-info` is skipped and its outputs
-          # are empty strings, so `fromJSON('')` would raise a template error
-          # and fail the step despite `if:` being false. Guard the
-          # `fromJSON` call with a short-circuit so the expression resolves
-          # to an empty string on non-PR events; the step is still gated
-          # off by `if:`, so `BASE_REF` is never consumed there.
-          BASE_REF: ${{ steps.pr-info.outputs.pr-info && fromJSON(steps.pr-info.outputs.pr-info).base.ref || '' }}
+          BASE_REF: ${{ needs.should-skip.outputs.base-ref }}
         run: |
-          # Diff against the merge base with the PR's actual target branch.
-          # Uses merge-base so diverged branches only show files changed on
-          # the PR side, not upstream commits.
+          set -euo pipefail
           if [[ -z "${BASE_REF}" ]]; then
-            echo "Could not resolve PR base branch from get-pr-info output" >&2
+            echo "Could not resolve PR base branch" >&2
             exit 1
           fi
+
           base=$(git merge-base HEAD "origin/${BASE_REF}")
-          changed=$(git diff --name-only "$base"...HEAD)
+          echo "sha=${base}" >> "$GITHUB_OUTPUT"
 
-          has_match() {
-            grep -qE "$1" <<< "$changed" && echo true || echo false
+      - name: Resolve reusable base artifacts
+        id: baseline
+        if: ${{ startsWith(github.ref_name, 'pull-request/') }}
+        env:
+          BASE_REF: ${{ needs.should-skip.outputs.base-ref }}
+          MERGE_BASE: ${{ steps.merge-base.outputs.sha }}
+          GH_TOKEN: ${{ github.token }}
+        run: |
+          set -uo pipefail
+
+          unavailable() {
+            echo "No complete reusable artifact set was found; this run will build and test everything." >> "$GITHUB_STEP_SUMMARY"
+            exit 0
           }
 
+          if [[ -z "${BASE_REF}" ]]; then
+            unavailable
+          fi
+
+          merge_base="${MERGE_BASE}"
+          if [[ -z "${merge_base}" ]]; then
+            unavailable
+          fi
+          if ! runs=$(gh run list \
+            --repo "${{ github.repository }}" \
+            --branch "${BASE_REF}" \
+            --commit "${merge_base}" \
+            --event push \
+            --workflow ci.yml \
+            --status success \
+            --limit 1 \
+            --json databaseId,headSha); then
+            unavailable
+          fi
+
+          # Reuse only artifacts produced from the exact commit used as the
+          # PR diff base. Using the latest base-branch run is unsafe for a PR
+          # that was opened before newer changes landed on that branch.
+          run_id=$(jq -r '.[0].databaseId // empty' <<< "$runs")
+          run_sha=$(jq -r '.[0].headSha // empty' <<< "$runs")
+          if [[ -z "${run_id}" || "${run_sha}" != "${merge_base}" ]]; then
+            unavailable
+          fi
+
+          if ! artifact_names=$(gh api \
+            "repos/${{ github.repository }}/actions/runs/${run_id}/artifacts?per_page=100" \
+            --paginate \
+            --jq '.artifacts[] | select(.expired == false) | .name'); then
+            unavailable
+          fi
+
+          has_artifact() {
+            grep -Fxq "$1" <<< "$artifact_names"
+          }
+
+          missing=()
+          for name in cuda-pathfinder-wheel cuda-python-wheel; do
+            has_artifact "$name" || missing+=("$name")
+          done
+
+          cuda_version=$(yq '.cuda.build.version' ci/versions.yml)
+          if ! python_versions=$(yq -r '.jobs.build.strategy.matrix."python-version"[]' .github/workflows/build-wheel.yml); then
+            unavailable
+          fi
+          if ! platforms=$(yq -r '.platforms[]' ci/test-matrix.yml); then
+            unavailable
+          fi
+          if [[ -z "${python_versions}" || -z "${platforms}" ]]; then
+            unavailable
+          fi
+          while IFS= read -r python_version; do
+            python=${python_version//./}
+            while IFS= read -r platform; do
+              binding="cuda-bindings-python${python}-cuda${cuda_version}-${platform}-${merge_base}"
+              core="cuda-core-python${python}-${platform}-${merge_base}"
+              has_artifact "$binding" || missing+=("$binding")
+              has_artifact "$core" || missing+=("$core")
+            done <<< "${platforms}"
+          done <<< "${python_versions}"
+
+          if (( ${#missing[@]} != 0 )); then
+            printf 'Missing reusable artifact: %s\n' "${missing[@]}" >&2
+            unavailable
+          fi
+
+          echo "run_id=${run_id}" >> "$GITHUB_OUTPUT"
           {
-            echo "bindings=$(has_match '^cuda_bindings/')"
-            echo "core=$(has_match '^cuda_core/')"
-            echo "pathfinder=$(has_match '^cuda_pathfinder/')"
-            echo "python_meta=$(has_match '^cuda_python/')"
-            echo "test_helpers=$(has_match '^cuda_python_test_helpers/')"
-            echo "shared=$(has_match '^(\.github/|ci/|scripts/|toolshed/|conftest\.py$|pyproject\.toml$|pixi\.(toml|lock)$|pytest\.ini$|ruff\.toml$)')"
-          } >> "$GITHUB_OUTPUT"
-
-      - name: Compose gating outputs
-        id: compose
+            echo
+            echo "Reusable artifacts: run \`${run_id}\` at \`${merge_base}\` on \`${BASE_REF}\`."
+          } >> "$GITHUB_STEP_SUMMARY"
+
+      - name: Test CI workplan planner
+        run: python3 -m unittest ci/tools/tests/test_compute_ci_plan.py
+
+      - name: Compute CI workplan
+        id: workplan
         env:
-          IS_PR: ${{ startsWith(github.ref_name, 'pull-request/') }}
-          BINDINGS: ${{ steps.filter.outputs.bindings || 'false' }}
-          CORE: ${{ steps.filter.outputs.core || 'false' }}
-          PATHFINDER: ${{ steps.filter.outputs.pathfinder || 'false' }}
-          PYTHON_META: ${{ steps.filter.outputs.python_meta || 'false' }}
-          TEST_HELPERS: ${{ steps.filter.outputs.test_helpers || 'false' }}
-          SHARED: ${{ steps.filter.outputs.shared || 'false' }}
+          MERGE_BASE: ${{ steps.merge-base.outputs.sha }}
+          BASELINE_RUN_ID: ${{ steps.baseline.outputs.run_id }}
         run: |
-          set -euxo pipefail
-          # Non-PR events (push to main, tag push, schedule, workflow_dispatch)
-          # always exercise the full pipeline because there is no baseline for
-          # a meaningful diff.
-          if [[ "${IS_PR}" != "true" ]]; then
-            bindings=true
-            core=true
-            pathfinder=true
-            python_meta=true
-            test_helpers=true
-            shared=true
-          else
-            bindings="${BINDINGS}"
-            core="${CORE}"
-            pathfinder="${PATHFINDER}"
-            python_meta="${PYTHON_META}"
-            test_helpers="${TEST_HELPERS}"
-            shared="${SHARED}"
+          set -euo pipefail
+          workplan=$(python3 ci/tools/compute_ci_plan.py \
+            --merge-base "$MERGE_BASE" \
+            --baseline-run-id "$BASELINE_RUN_ID")
+          echo "workplan=$workplan" >> "$GITHUB_OUTPUT"
+          {
+            echo
+            echo "### CI workplan"
+            echo '```json'
+            jq . <<< "$workplan"
+            echo '```'
+          } >> "$GITHUB_STEP_SUMMARY"
+
+  api-check-core-vs-release:
+    name: API check (cuda_core vs. latest release)
+    if: >-
+      ${{ !fromJSON(needs.should-skip.outputs.skip) &&
+          fromJSON(needs.detect-changes.outputs.workplan).jobs.core_api_checks }}
+    runs-on: ubuntu-latest
+    needs:
+      - should-skip
+      - detect-changes
+    permissions:
+      contents: read
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
+        with:
+          fetch-depth: 1
+          filter: blob:none
+
+      - name: Find latest release tag
+        id: latest-tag
+        shell: bash --noprofile --norc -euo pipefail {0}
+        env:
+          GH_TOKEN: ${{ github.token }}
+        run: |
+          # --paginate fetches all pages; jq outputs one name per line per page;
+          # sed prints the first (newest) match while consuming all pages, so
+          # gh can complete without SIGPIPE. Fails if no cuda-core-v* tag is found.
+          tag="$(gh api "repos/$GITHUB_REPOSITORY/tags" --paginate \
+            --jq '.[] | select(.name | startswith("cuda-core-v")) | .name' \
+            | sed -n '1p')"
+          if [[ -z "${tag}" ]]; then
+            echo "::error::No cuda-core-v* tag found in the repository." >&2
+            exit 1
           fi
+          echo "tag=${tag}" >> "$GITHUB_OUTPUT"
 
-          or_flag() {
-            for v in "$@"; do
-              if [[ "${v}" == "true" ]]; then
-                echo "true"
-                return
-              fi
-            done
-            echo "false"
-          }
+      - name: Fetch release tag
+        shell: bash --noprofile --norc -euo pipefail {0}
+        run: |
+          git fetch --depth=1 --filter=blob:none origin \
+            "refs/tags/${{ steps.latest-tag.outputs.tag }}:refs/tags/${{ steps.latest-tag.outputs.tag }}"
 
-          # Build gating: pathfinder change forces rebuild of bindings and
-          # core; bindings change forces rebuild of core. shared changes force
-          # a full rebuild.
-          build_pathfinder="$(or_flag "${shared}" "${pathfinder}")"
-          build_bindings="$(or_flag "${shared}" "${pathfinder}" "${bindings}")"
-          build_core="$(or_flag "${shared}" "${pathfinder}" "${bindings}" "${core}")"
+      - name: Check cuda_core public API
+        id: griffe
+        uses: ./.github/actions/griffe-api-check
+        with:
+          package-name: cuda.core
+          package-dir: cuda_core
+          merge-base: ${{ steps.latest-tag.outputs.tag }}
+
+  api-check-core-vs-base:
+    name: API check (cuda_core vs. merge base)
+    if: >-
+      ${{ startsWith(github.ref_name, 'pull-request/') &&
+          !fromJSON(needs.should-skip.outputs.skip) &&
+          fromJSON(needs.detect-changes.outputs.workplan).jobs.core_api_checks }}
+    runs-on: ubuntu-latest
+    needs:
+      - should-skip
+      - detect-changes
+    permissions:
+      contents: read
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
+        with:
+          fetch-depth: 1
+          filter: blob:none
 
-          # Test gating: tests for a module must run whenever that module, any
-          # of its runtime dependencies, the shared test helper package, or
-          # shared infra changes. pathfinder tests are cheap and always run.
-          test_pathfinder=true
-          test_bindings="$(or_flag "${shared}" "${pathfinder}" "${bindings}" "${test_helpers}")"
-          test_core="$(or_flag "${shared}" "${pathfinder}" "${bindings}" "${core}" "${test_helpers}")"
+      - name: Fetch merge base commit
+        shell: bash --noprofile --norc -euo pipefail {0}
+        run: |
+          git fetch --depth=1 --filter=blob:none origin \
+            "${{ fromJSON(needs.detect-changes.outputs.workplan).merge_base }}"
 
-          {
-            echo "bindings=${bindings}"
-            echo "core=${core}"
-            echo "pathfinder=${pathfinder}"
-            echo "python_meta=${python_meta}"
-            echo "test_helpers=${test_helpers}"
-            echo "shared=${shared}"
-            echo "build_bindings=${build_bindings}"
-            echo "build_core=${build_core}"
-            echo "build_pathfinder=${build_pathfinder}"
-            echo "test_bindings=${test_bindings}"
-            echo "test_core=${test_core}"
-            echo "test_pathfinder=${test_pathfinder}"
-          } >> "$GITHUB_OUTPUT"
+      - name: Check cuda_core public API
+        id: griffe
+        uses: ./.github/actions/griffe-api-check
+        with:
+          package-name: cuda.core
+          package-dir: cuda_core
+          merge-base: ${{ fromJSON(needs.detect-changes.outputs.workplan).merge_base }}
 
   # NOTE: Build jobs are intentionally split by platform rather than using a single
-  # matrix. This allows each test job to depend only on its corresponding build,
-  # so faster platforms can proceed through build & test without waiting for slower
-  # ones. Keep these job definitions textually identical except for:
+  # matrix. This lets each test job consume its platform-specific artifacts as
+  # soon as they are ready. ARM64 and Windows tests also wait for linux-64,
+  # which produces the universal pathfinder and cuda-python wheels. Keep these
+  # job definitions textually identical except for:
   #   - host-platform value
   #   - if: condition (build-linux-64 omits doc-only check since it's needed for docs)
   build-linux-64:
     needs:
       - ci-vars
       - should-skip
+      - detect-changes
     strategy:
       fail-fast: false
       matrix:
@@ -249,96 +378,95 @@ jobs:
           - linux-64
     name: Build ${{ matrix.host-platform }}, CUDA ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
     if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) }}
+    permissions:
+      actions: read
+      contents: read
     secrets: inherit
     uses: ./.github/workflows/build-wheel.yml
     with:
       host-platform: ${{ matrix.host-platform }}
       cuda-version: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-      cuda-channel: ${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}
       prev-cuda-version: ${{ needs.ci-vars.outputs.CUDA_PREV_BUILD_VER }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
   # See build-linux-64 for why build jobs are split by platform.
   build-linux-aarch64:
     needs:
       - ci-vars
       - should-skip
+      - detect-changes
     strategy:
       fail-fast: false
       matrix:
         host-platform:
           - linux-aarch64
     name: Build ${{ matrix.host-platform }}, CUDA ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) && !fromJSON(needs.should-skip.outputs.doc-only) }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.skip) &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.linux }}
+    permissions:
+      actions: read
+      contents: read
     secrets: inherit
     uses: ./.github/workflows/build-wheel.yml
     with:
       host-platform: ${{ matrix.host-platform }}
       cuda-version: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-      cuda-channel: ${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}
       prev-cuda-version: ${{ needs.ci-vars.outputs.CUDA_PREV_BUILD_VER }}
-
-  # Warm the shared CTK cache before the Windows matrix starts. This avoids
-  # downloading the multi-gigabyte prerelease installer once per Python job.
-  prepare-windows-ctk:
-    needs:
-      - ci-vars
-      - should-skip
-    name: Prepare win-64 CTK ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) && !fromJSON(needs.should-skip.outputs.doc-only) }}
-    runs-on: windows-2022
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
-        with:
-          fetch-depth: 1
-      - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
-        with:
-          python-version: "3.12"
-      - name: Populate mini CTK cache
-        uses: ./.github/actions/fetch_ctk
-        with:
-          host-platform: win-64
-          cuda-version: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-          cuda-channel: ${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
   # See build-linux-64 for why build jobs are split by platform.
   build-windows:
     needs:
       - ci-vars
       - should-skip
-      - prepare-windows-ctk
+      - detect-changes
     strategy:
       fail-fast: false
       matrix:
         host-platform:
           - win-64
     name: Build ${{ matrix.host-platform }}, CUDA ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) && !fromJSON(needs.should-skip.outputs.doc-only) }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.skip) &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.windows }}
+    permissions:
+      actions: read
+      contents: read
     secrets: inherit
     uses: ./.github/workflows/build-wheel.yml
     with:
       host-platform: ${{ matrix.host-platform }}
       cuda-version: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-      cuda-channel: ${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}
       prev-cuda-version: ${{ needs.ci-vars.outputs.CUDA_PREV_BUILD_VER }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
-  # Windows ARM64 supports only the current CUDA major because the platform is
-  # new in CUDA 13.4; no prior-major toolkit or wheel artifacts exist.
+  # Windows ARM64 is available starting with CUDA 13.4. Build only the current
+  # CUDA major because no prior-major toolkit or wheel artifacts exist.
   build-windows-arm64:
     needs:
       - ci-vars
       - should-skip
+      - detect-changes
     name: Build win-arm64, CUDA ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) && !fromJSON(needs.should-skip.outputs.doc-only) && needs.ci-vars.outputs.CUDA_BUILD_CHANNEL == 'prerelease' }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.skip) &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            needs.ci-vars.outputs.WINDOWS_ARM64_SUPPORTED == 'true' &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.windows }}
+    permissions:
+      actions: read
+      contents: read
     secrets: inherit
     uses: ./.github/workflows/build-wheel.yml
     with:
       host-platform: win-arm64
       cuda-version: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-      cuda-channel: ${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}
       prev-cuda-version: ${{ needs.ci-vars.outputs.CUDA_PREV_BUILD_VER }}
-      single-cuda-major: true
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
+      single-cuda-major: ${{ needs.ci-vars.outputs.WINDOWS_ARM64_SINGLE_CUDA_MAJOR == 'true' }}
 
   # NOTE: test-sdist jobs are split by platform (mirroring build-* and test-wheel-*)
   # so platform-specific sources (e.g. cuda_bindings/*_windows.pyx selected by
@@ -350,29 +478,45 @@ jobs:
     needs:
       - ci-vars
       - should-skip
+      - detect-changes
+      - build-linux-64
     name: Test sdist linux-64
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) && !fromJSON(needs.should-skip.outputs.doc-only) }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.skip) &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.sdist_tests }}
+    permissions:
+      actions: read
+      contents: read
     secrets: inherit
     uses: ./.github/workflows/test-sdist-linux.yml
     with:
       host-platform: linux-64
       cuda-version: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-      cuda-channel: ${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
   # See test-sdist-linux for why sdist test jobs are split by platform.
   test-sdist-windows:
     needs:
       - ci-vars
       - should-skip
-      - prepare-windows-ctk
+      - detect-changes
+      - build-linux-64
+      - build-windows
     name: Test sdist win-64
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) && !fromJSON(needs.should-skip.outputs.doc-only) }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.skip) &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.sdist_tests }}
+    permissions:
+      actions: read
+      contents: read
     secrets: inherit
     uses: ./.github/workflows/test-sdist-windows.yml
     with:
       host-platform: win-64
       cuda-version: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
-      cuda-channel: ${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
   # NOTE: Test jobs are split by platform for the same reason as build jobs (see
   # build-linux-64). Keep these job definitions textually identical except for:
@@ -386,8 +530,11 @@ jobs:
         host-platform:
           - linux-64
     name: Test ${{ matrix.host-platform }}
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.doc-only) }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.linux }}
     permissions:
+      actions: read
       contents: read  # This is required for actions/checkout
     needs:
       - ci-vars
@@ -401,7 +548,7 @@ jobs:
       host-platform: ${{ matrix.host-platform }}
       build-ctk-ver: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
       nruns: ${{ (github.event_name == 'schedule' && 5) || 1}}
-      skip-bindings-test: ${{ !fromJSON(needs.detect-changes.outputs.test_bindings) }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
   # See test-linux-64 for why test jobs are split by platform.
   test-linux-aarch64:
@@ -411,13 +558,17 @@ jobs:
         host-platform:
           - linux-aarch64
     name: Test ${{ matrix.host-platform }}
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.doc-only) }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.linux }}
     permissions:
+      actions: read
       contents: read  # This is required for actions/checkout
     needs:
       - ci-vars
       - should-skip
       - detect-changes
+      - build-linux-64
       - build-linux-aarch64
     secrets: inherit
     uses: ./.github/workflows/test-wheel-linux.yml
@@ -426,7 +577,7 @@ jobs:
       host-platform: ${{ matrix.host-platform }}
       build-ctk-ver: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
       nruns: ${{ (github.event_name == 'schedule' && 5) || 1}}
-      skip-bindings-test: ${{ !fromJSON(needs.detect-changes.outputs.test_bindings) }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
   # See test-linux-64 for why test jobs are split by platform.
   test-windows:
@@ -436,13 +587,17 @@ jobs:
         host-platform:
           - win-64
     name: Test ${{ matrix.host-platform }}
-    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.doc-only) && needs.ci-vars.outputs.CUDA_BUILD_CHANNEL != 'prerelease' }}
+    if: ${{ github.repository_owner == 'nvidia' &&
+            !fromJSON(needs.should-skip.outputs.doc-only) &&
+            fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.windows }}
     permissions:
+      actions: read
       contents: read  # This is required for actions/checkout
     needs:
       - ci-vars
       - should-skip
       - detect-changes
+      - build-linux-64
       - build-windows
     secrets: inherit
     uses: ./.github/workflows/test-wheel-windows.yml
@@ -451,7 +606,7 @@ jobs:
       host-platform: ${{ matrix.host-platform }}
       build-ctk-ver: ${{ needs.ci-vars.outputs.CUDA_BUILD_VER }}
       nruns: ${{ (github.event_name == 'schedule' && 5) || 1}}
-      skip-bindings-test: ${{ !fromJSON(needs.detect-changes.outputs.test_bindings) }}
+      workplan: ${{ needs.detect-changes.outputs.workplan }}
 
   doc:
     name: Docs
@@ -469,14 +624,48 @@ jobs:
     with:
       is-release: ${{ github.ref_type == 'tag' }}
 
+  precommit-windows:
+    name: Pre-commit on Windows
+    runs-on: windows-latest
+    if: ${{ github.repository_owner == 'nvidia' && !fromJSON(needs.should-skip.outputs.skip) }}
+    needs:
+      - should-skip
+    permissions:
+      contents: read
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
+        with:
+          fetch-depth: 1
+          persist-credentials: false
+
+      - name: Set up Python
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
+        with:
+          python-version: '3.13'
+
+      - name: Install pre-commit
+        shell: bash
+        run: |
+          set -euxo pipefail
+          python -m pip install --upgrade pip pre-commit
+
+      - name: Run pre-commit
+        shell: bash
+        run: |
+          set -euxo pipefail
+          SKIP=lychee pre-commit run --all-files
+
   checks:
     name: Check job status
-    if: always()
+    if: ${{ always() && github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     needs:
       - ci-vars
       - should-skip
       - detect-changes
+      - build-linux-64
+      - build-linux-aarch64
       - build-windows
       - build-windows-arm64
       - test-sdist-linux
@@ -484,9 +673,14 @@ jobs:
       - test-linux-64
       - test-linux-aarch64
       - test-windows
+      - api-check-core-vs-release
+      - api-check-core-vs-base
       - doc
+      - precommit-windows
     steps:
       - name: Exit
+        env:
+          NEEDS_JSON: ${{ toJSON(needs) }}
         run: |
           # GitHub treats `result == 'skipped'` as success for required
           # status checks (see CCCL gate comment + cccl#605). The previous
@@ -503,10 +697,16 @@ jobs:
           fi
 
           doc_only="${{ needs.should-skip.outputs.doc-only }}"
-          cuda_build_channel="${{ needs.ci-vars.outputs.CUDA_BUILD_CHANNEL }}"
+          linux_selected="${{ needs.detect-changes.outputs.workplan && fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.linux || false }}"
+          windows_selected="${{ needs.detect-changes.outputs.workplan && fromJSON(needs.detect-changes.outputs.workplan).jobs.platforms.windows || false }}"
+          windows_arm64_supported="${{ needs.ci-vars.outputs.WINDOWS_ARM64_SUPPORTED }}"
+          build_selected="${{ needs.detect-changes.outputs.workplan && fromJSON(needs.detect-changes.outputs.workplan).jobs.sdist_tests || false }}"
+          run_core_api_check="${{ needs.detect-changes.outputs.workplan && fromJSON(needs.detect-changes.outputs.workplan).jobs.core_api_checks || false }}"
+          is_pr="${{ startsWith(github.ref_name, 'pull-request/') }}"
           status="success"
           check_result() {
-            name=$1; expected=$2; result=$3
+            local name=$1 expected=$2 result
+            result=$(jq -r --arg name "$name" '.[$name].result // "missing"' <<< "$NEEDS_JSON")
             echo "Checking $name: result='$result' (expected '$expected')"
             if [[ "$result" != "$expected" ]]; then
               echo "::error::$name did not match expected result"
@@ -514,38 +714,53 @@ jobs:
             fi
           }
 
-          # always expected to succeed (even in [doc-only] mode)
-          check_result "ci-vars"        "success" "${{ needs.ci-vars.result }}"
-          check_result "should-skip"    "success" "${{ needs.should-skip.result }}"
-          check_result "detect-changes" "success" "${{ needs.detect-changes.result }}"
-          check_result "doc"            "success" "${{ needs.doc.result }}"
-
-          # [doc-only] skips all builds and tests. Windows preview wheel builds
-          # run, but GPU tests remain skipped until suitable runners are available.
-          if [[ "$doc_only" == "true" ]]; then
-            linux_expected="skipped"
-            windows_build_expected="skipped"
-            windows_arm_build_expected="skipped"
-            windows_sdist_expected="skipped"
-            windows_test_expected="skipped"
-          else
+          # Control jobs, the universal linux build, docs, and Windows
+          # pre-commit checks always run.
+          check_result "ci-vars"           "success"
+          check_result "should-skip"       "success"
+          check_result "detect-changes"    "success"
+          check_result "build-linux-64"    "success"
+          check_result "doc"               "success"
+          check_result "precommit-windows" "success"
+
+          # Optional platform builds and wheel tests share the platform plan.
+          linux_expected="skipped"
+          if [[ "$doc_only" != "true" && "$linux_selected" == "true" ]]; then
             linux_expected="success"
-            windows_build_expected="success"
-            windows_sdist_expected="success"
-            if [[ "$cuda_build_channel" == "prerelease" ]]; then
-              windows_arm_build_expected="success"
-              windows_test_expected="skipped"
-            else
-              windows_arm_build_expected="skipped"
-              windows_test_expected="success"
-            fi
           fi
-          check_result "build-windows"      "$windows_build_expected" "${{ needs.build-windows.result }}"
-          check_result "build-windows-arm64" "$windows_arm_build_expected" "${{ needs.build-windows-arm64.result }}"
-          check_result "test-sdist-linux"   "$linux_expected" "${{ needs.test-sdist-linux.result }}"
-          check_result "test-sdist-windows" "$windows_sdist_expected" "${{ needs.test-sdist-windows.result }}"
-          check_result "test-linux-64"      "$linux_expected" "${{ needs.test-linux-64.result }}"
-          check_result "test-linux-aarch64" "$linux_expected" "${{ needs.test-linux-aarch64.result }}"
-          check_result "test-windows"       "$windows_test_expected" "${{ needs.test-windows.result }}"
+          windows_expected="skipped"
+          if [[ "$doc_only" != "true" && "$windows_selected" == "true" ]]; then
+            windows_expected="success"
+          fi
+          check_result "build-linux-aarch64" "$linux_expected"
+          check_result "build-windows"       "$windows_expected"
+
+          windows_arm64_expected="skipped"
+          if [[ "$windows_arm64_supported" == "true" ]]; then
+            windows_arm64_expected="$windows_expected"
+          fi
+          check_result "build-windows-arm64" "$windows_arm64_expected"
+
+          # Sdist tests follow build selection; wheel tests follow the platform plan.
+          expected="skipped"
+          if [[ "$doc_only" != "true" && "$build_selected" == "true" ]]; then
+            expected="success"
+          fi
+          check_result "test-sdist-linux"   "$expected"
+          check_result "test-sdist-windows" "$expected"
+
+          check_result "test-linux-64"      "$linux_expected"
+          check_result "test-linux-aarch64" "$linux_expected"
+          check_result "test-windows"       "$windows_expected"
+
+          # API compatibility checks run for cuda_core source changes and for
+          # conservative full runs when reusable base artifacts are unavailable.
+          expected="skipped"
+          if [[ "$run_core_api_check" == "true" ]]; then expected="success"; fi
+          check_result "api-check-core-vs-release" "$expected"
+
+          expected="skipped"
+          if [[ "$is_pr" == "true" && "$run_core_api_check" == "true" ]]; then expected="success"; fi
+          check_result "api-check-core-vs-base" "$expected"
 
           [[ "$status" == "success" ]]
diff --git a/.github/workflows/cleanup-pr-previews.yml b/.github/workflows/cleanup-pr-previews.yml
index de9e348f430..4c367f415c3 100644
--- a/.github/workflows/cleanup-pr-previews.yml
+++ b/.github/workflows/cleanup-pr-previews.yml
@@ -28,7 +28,7 @@ jobs:
     if: github.repository_owner == 'NVIDIA'
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v7.0.0
+        uses: actions/checkout@v7.0.1
         with:
           # Treeless clone: `git worktree add gh-pages` needs the commit graph,
           # but historical blobs aren't required.
diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml
deleted file mode 100644
index 87bcd8e58d5..00000000000
--- a/.github/workflows/codeql.yml
+++ /dev/null
@@ -1,46 +0,0 @@
-# SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
-
-name: "Static Analysis: CodeQL Scan"
-
-on:
-  push:
-    branches:
-      - "pull-request/[0-9]+"
-      - "ctk-next"
-      - "main"
-concurrency:
-  group: ${{ github.workflow }}-${{ github.ref }}-${{ github.event_name }}
-  cancel-in-progress: true
-
-jobs:
-  analyze:
-    name: Analyze (${{ matrix.language }})
-    runs-on: ubuntu-latest
-    permissions:
-      actions: read
-      contents: read
-      security-events: write
-
-    strategy:
-      fail-fast: false
-      matrix:
-        include:
-        - language: python
-          build-mode: none
-    steps:
-    - name: Checkout repository
-      uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
-
-    - name: Initialize CodeQL
-      uses: github/codeql-action/init@8aad20d150bbac5944a9f9d289da16a4b0d87c1e  # v4.36.2
-      with:
-        languages: ${{ matrix.language }}
-        build-mode: ${{ matrix.build-mode }}
-        queries: security-extended
-
-    - name: Perform CodeQL Analysis
-      uses: github/codeql-action/analyze@8aad20d150bbac5944a9f9d289da16a4b0d87c1e  # v4.36.2
-      with:
-        category: "/language:${{matrix.language}}"
diff --git a/.github/workflows/coverage.yml b/.github/workflows/coverage.yml
index f1b8eb9f3a2..6015db55c9d 100644
--- a/.github/workflows/coverage.yml
+++ b/.github/workflows/coverage.yml
@@ -17,12 +17,13 @@ env:
 
 jobs:
   coverage-vars:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     outputs:
       CUDA_VER: ${{ steps.get-vars.outputs.cuda_ver }}
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
       - name: Get CUDA version
         id: get-vars
         run: |
@@ -64,7 +65,7 @@ jobs:
           apt-get install -y git
 
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # Treeless clone: setuptools-scm needs the commit graph (`git describe`)
           # but not historical blobs.
@@ -99,7 +100,7 @@ jobs:
           echo "CUDA_PYTHON_COVERAGE=1" >> $GITHUB_ENV
 
       - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           python-version: ${{ env.PY_VER }}
         env:
@@ -118,18 +119,51 @@ jobs:
         run: |
           python -m venv .venv
 
-      - name: Build cuda-pathfinder
+      - name: Install pip with build-constraint support
+        run: .venv/bin/python -m pip install "pip>=25.3"
+
+      - name: Build and install cuda-pathfinder wheel
         run: |
-          cd cuda_pathfinder
-          ../.venv/bin/pip install -v . --group test
+          .venv/bin/pip wheel -v --no-deps ./cuda_pathfinder -w ./wheels/
+          .venv/bin/pip install -v ./wheels/cuda_pathfinder*.whl --group ./cuda_pathfinder/pyproject.toml:test
 
-      - name: Build cuda-bindings
+      - name: Constrain builds to the local cuda-pathfinder wheel
         run: |
-          cd cuda_bindings
-          ../.venv/bin/pip install -v . --group test
+          pathfinder_wheels=(wheels/cuda_pathfinder-*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file://$(realpath "${pathfinder_wheels[0]}")"
+          printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}" | tee wheel-constraints/cuda-bindings.txt
+
+      - name: Build and install cuda-bindings wheel
+        run: |
+          export PIP_BUILD_CONSTRAINT="$(pwd)/wheel-constraints/cuda-bindings.txt"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
+          .venv/bin/pip wheel -v --no-deps ./cuda_bindings -w ./wheels/
+          .venv/bin/pip install -v ./wheels/cuda_bindings*.whl --group ./cuda_bindings/pyproject.toml:test
+
+      - name: Constrain cuda-core to the local cuda-bindings wheel
+        run: |
+          CUDA_MAJOR="${CUDA_VER%%.*}"
+          pathfinder_wheels=(wheels/cuda_pathfinder-*.whl)
+          bindings_wheels=(wheels/cuda_bindings-"${CUDA_MAJOR}".*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test "${#bindings_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          test -f "${bindings_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file://$(realpath "${pathfinder_wheels[0]}")"
+          bindings_uri="file://$(realpath "${bindings_wheels[0]}")"
+          {
+            printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}"
+            printf 'cuda-bindings @ %s\n' "${bindings_uri}"
+          } | tee wheel-constraints/cuda-core.txt
 
-      - name: Build cuda-core
+      - name: Build and install cuda-core
         run: |
+          export PIP_BUILD_CONSTRAINT="$(pwd)/wheel-constraints/cuda-core.txt"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
           cd cuda_core
           ../.venv/bin/pip install -v . --group test
 
@@ -199,7 +233,7 @@ jobs:
       CUDA_VER: ${{ needs.coverage-vars.outputs.CUDA_VER }}
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # Treeless clone: setuptools-scm needs the commit graph (`git describe`)
           # but not historical blobs.
@@ -207,7 +241,7 @@ jobs:
           filter: blob:none
 
       - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           python-version: ${{ env.PY_VER }}
 
@@ -225,23 +259,65 @@ jobs:
         run: |
           python -m venv .venv
 
-      - name: Build and install cuda.pathfinder
+      - name: Build cuda.pathfinder wheel
         run: |
-          .venv/Scripts/pip install wheel setuptools Cython
+          .venv/Scripts/python -m pip install "pip>=25.3" wheel setuptools Cython
           .venv/Scripts/pip wheel -v --no-deps ./cuda_pathfinder -w ./wheels/
 
+      - name: Constrain builds to the local cuda.pathfinder wheel
+        run: |
+          pathfinder_wheels=(wheels/cuda_pathfinder-*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file:///$(cygpath -am "${pathfinder_wheels[0]}")"
+          printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}" | tee wheel-constraints/cuda-bindings.txt
+
       - name: Build cuda.bindings wheel
         run: |
+          export PIP_BUILD_CONSTRAINT="$(cygpath -w "$(pwd)/wheel-constraints/cuda-bindings.txt")"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
           cd cuda_bindings
           ../.venv/Scripts/pip wheel -v --no-deps . -w ../wheels/
 
+      - name: Constrain cuda.core to the local cuda.bindings wheel
+        run: |
+          CUDA_MAJOR="${CUDA_VER%%.*}"
+          pathfinder_wheels=(wheels/cuda_pathfinder-*.whl)
+          bindings_wheels=(wheels/cuda_bindings-"${CUDA_MAJOR}".*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test "${#bindings_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          test -f "${bindings_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file:///$(cygpath -am "${pathfinder_wheels[0]}")"
+          bindings_uri="file:///$(cygpath -am "${bindings_wheels[0]}")"
+          {
+            printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}"
+            printf 'cuda-bindings @ %s\n' "${bindings_uri}"
+          } | tee wheel-constraints/cuda-core.txt
+
       - name: Build cuda.core wheel
         run: |
-          export PIP_FIND_LINKS="$(pwd)/wheels"
-          export PIP_PRE=1
+          export PIP_BUILD_CONSTRAINT="$(cygpath -w "$(pwd)/wheel-constraints/cuda-core.txt")"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
           cd cuda_core
           ../.venv/Scripts/pip wheel -v --no-deps . -w ../wheels/
 
+      # Vendor the DLLs these wheels were built against, the way cibuildwheel
+      # does for every other Windows build.  --namespace-pkg is needed because
+      # `cuda` is a namespace package.
+      - name: Repair the Windows wheels
+        run: |
+          .venv/Scripts/pip install delvewheel
+          mkdir -p wheels-repaired
+          for whl in ./wheels/cuda_bindings-*.whl ./wheels/cuda_core-*.whl; do
+            .venv/Scripts/delvewheel repair --namespace-pkg cuda \
+              --exclude "torch_cpu.dll;torch_python.dll" \
+              -w ./wheels-repaired "$whl"
+          done
+          mv -f ./wheels-repaired/*.whl ./wheels/
+
       - name: List wheel artifacts
         run: |
           echo "=== Windows wheel artifacts ==="
@@ -273,7 +349,7 @@ jobs:
         shell: bash --noprofile --norc -xeuo pipefail {0}
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           fetch-depth: 1
 
@@ -296,7 +372,7 @@ jobs:
           nvidia-smi
 
       - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           python-version: ${{ env.PY_VER }}
 
@@ -335,7 +411,6 @@ jobs:
 
       - name: Install test dependencies and coverage tools
         run: |
-          .venv/Scripts/pip install -v ./cuda_python_test_helpers
           .venv/Scripts/pip install coverage pytest-cov Cython
           .venv/Scripts/pip install --group ./cuda_pathfinder/pyproject.toml:test
           .venv/Scripts/pip install --group ./cuda_bindings/pyproject.toml:test
@@ -393,16 +468,16 @@ jobs:
     name: Combine Coverage and Deploy
     needs: [coverage-linux, coverage-windows]
     runs-on: ubuntu-latest
-    if: always()
+    if: ${{ always() && github.repository_owner == 'nvidia' }}
     permissions:
       id-token: write
       contents: write
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           python-version: ${{ env.PY_VER }}
 
@@ -467,7 +542,8 @@ jobs:
           echo "=== Combining coverage data ==="
           coverage combine --rcfile=./.coveragerc --keep .coverage.*
 
-          # Generate reports
+      - name: Generate coverage reports
+        run: |
           echo ""
           echo "=== Generating HTML, XML, and text reports ==="
           coverage html --rcfile=./.coveragerc
@@ -491,7 +567,7 @@ jobs:
           include-hidden-files: true
 
       - name: Deploy to gh-pages
-        uses: JamesIves/github-pages-deploy-action@d92aa235d04922e8f08b40ce78cc5442fcfbfa2f  # v4.8.0
+        uses: JamesIves/github-pages-deploy-action@fa24774553152dd7873cd16ebd8d959b010c5445  # v4.9.0
         with:
           git-config-name: cuda-python-bot
           git-config-email: cuda-python-bot@users.noreply.github.com
diff --git a/.github/workflows/pr-metadata-check.yml b/.github/workflows/pr-metadata-check.yml
index 6f60ec45bf4..62110dcd93b 100644
--- a/.github/workflows/pr-metadata-check.yml
+++ b/.github/workflows/pr-metadata-check.yml
@@ -17,6 +17,9 @@ on:
       - reopened
       - ready_for_review
 
+permissions:
+  pull-requests: read
+
 jobs:
   check-metadata:
     name: PR has assignee, labels, and milestone
diff --git a/.github/workflows/release-cuda-pathfinder.yml b/.github/workflows/release-cuda-pathfinder.yml
index f3d1952e9ec..37bef236fec 100644
--- a/.github/workflows/release-cuda-pathfinder.yml
+++ b/.github/workflows/release-cuda-pathfinder.yml
@@ -33,6 +33,7 @@ jobs:
   # Collect release metadata, find the CI run, create a draft release.
   # --------------------------------------------------------------------------
   prepare:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     permissions:
       contents: write
@@ -59,7 +60,7 @@ jobs:
             echo "version=${version}"
           } >> "$GITHUB_OUTPUT"
 
-      - uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+      - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # lookup-run-id resolves the git tag to a SHA; we need tags but not history.
           fetch-depth: 1
@@ -161,7 +162,7 @@ jobs:
       TAG: ${{ needs.prepare.outputs.tag }}
       RUN_ID: ${{ needs.prepare.outputs.run-id }}
     steps:
-      - uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+      - uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           fetch-depth: 1
           ref: ${{ needs.prepare.outputs.tag }}
@@ -233,7 +234,7 @@ jobs:
           ls -la dist
 
       - name: Publish to TestPyPI
-        uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b  # v1.14.0
+        uses: pypa/gh-action-pypi-publish@dc37677b2e1c63e2034f94d8a5b11f265b73ba33  # v1.14.2
         with:
           repository-url: https://test.pypi.org/legacy/
 
@@ -310,7 +311,7 @@ jobs:
           ls -la dist
 
       - name: Publish to PyPI
-        uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b  # v1.14.0
+        uses: pypa/gh-action-pypi-publish@dc37677b2e1c63e2034f94d8a5b11f265b73ba33  # v1.14.2
 
   # --------------------------------------------------------------------------
   # Verify the PyPI package installs and imports correctly.
diff --git a/.github/workflows/release-upload.yml b/.github/workflows/release-upload.yml
index 77681096ed9..bd66b84ed76 100644
--- a/.github/workflows/release-upload.yml
+++ b/.github/workflows/release-upload.yml
@@ -46,7 +46,7 @@ jobs:
       ARCHIVE_NAME: ${{ github.event.repository.name }}-${{ inputs.git-tag }}
     steps:
       - name: Checkout Source
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           fetch-depth: 1
           ref: ${{ inputs.git-tag }}
diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
index 4f2c54f4509..4e915e02093 100644
--- a/.github/workflows/release.yml
+++ b/.github/workflows/release.yml
@@ -76,12 +76,13 @@ defaults:
 
 jobs:
   determine-run-id:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     outputs:
       run-id: ${{ steps.lookup-run-id.outputs.run-id }}
     steps:
       - name: Checkout Source
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # lookup-run-id resolves the git tag to a SHA; we need tags but not history.
           fetch-depth: 1
@@ -103,10 +104,11 @@ jobs:
           echo "run-id=$RUN_ID" >> "$GITHUB_OUTPUT"
 
   check-tag:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     steps:
       - name: Checkout Source
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # Dry-run validation resolves the requested tag locally; we need tags but not history.
           fetch-depth: 1
@@ -154,15 +156,16 @@ jobs:
           fi
 
   check-release-notes:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     steps:
       - name: Checkout Source
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           ref: ${{ inputs.git-tag }}
 
       - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           python-version: "3.12"
 
@@ -228,7 +231,7 @@ jobs:
       id-token: write
     steps:
       - name: Checkout Source
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Download component wheels
         env:
@@ -241,7 +244,7 @@ jobs:
           ./ci/tools/validate-release-wheels "${{ inputs.git-tag }}" "${{ inputs.component }}" "dist"
 
       - name: Publish package distributions to TestPyPI
-        uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b  # v1.14.0
+        uses: pypa/gh-action-pypi-publish@dc37677b2e1c63e2034f94d8a5b11f265b73ba33  # v1.14.2
         with:
           repository-url: https://test.pypi.org/legacy/
 
@@ -259,7 +262,7 @@ jobs:
       id-token: write
     steps:
       - name: Checkout Source
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Download component wheels
         env:
@@ -272,6 +275,6 @@ jobs:
           ./ci/tools/validate-release-wheels "${{ inputs.git-tag }}" "${{ inputs.component }}" "dist"
 
       - name: Publish package distributions to PyPI
-        uses: pypa/gh-action-pypi-publish@cef221092ed1bacb1cc03d23a2d87d1d172e277b  # v1.14.0
+        uses: pypa/gh-action-pypi-publish@dc37677b2e1c63e2034f94d8a5b11f265b73ba33  # v1.14.2
 
   # TODO: add another job to make the release leave the draft state?
diff --git a/.github/workflows/security-suite.yml b/.github/workflows/security-suite.yml
new file mode 100644
index 00000000000..64eb4846483
--- /dev/null
+++ b/.github/workflows/security-suite.yml
@@ -0,0 +1,50 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+#
+# CI security scanning via the NVIDIA/security-workflows suite: Pulse secret scan + CodeQL SAST.
+# Pulse runs on Linux nv-gha-runners (Docker image + OIDC/Vault) — Linux-only by design.
+# The local secret-scan-trufflehog pre-commit hook is cross-platform (Linux/macOS/Windows).
+# Pinned to a reviewed commit SHA.
+
+name: Security Suite (Pulse + CodeQL)
+
+on:
+  push:
+    branches:
+      - main
+      - ctk-next
+      - "pull-request/[0-9]+"
+  workflow_dispatch:
+
+concurrency:
+  group: ${{ github.workflow }}-on-${{ github.event_name }}-from-${{ github.ref_name }}
+  cancel-in-progress: true
+
+# Caller must grant every permission the reusable workflow declares, including scans it disables.
+permissions:
+  contents: read
+  id-token: write          # OIDC -> Vault -> nvcr.io image pull
+  security-events: write   # publish redacted SARIF to code scanning
+  actions: read
+
+jobs:
+  security-suite:
+    name: Security Suite
+    # Repository-specific workflow opt-ins use CI_CUSTOMIZATIONS_* Actions variables;
+    # see ci/README.md. Enable this only after the security-suite prerequisites exist.
+    if: >-
+      github.repository == 'NVIDIA/cuda-python' ||
+      vars.CI_CUSTOMIZATIONS_SECURITY_SUITE_ENABLED == 'true'
+    uses: NVIDIA/security-workflows/.github/workflows/security-suite.yml@c736f0454dc99764a66af6b906adfcdfbf621985  # v0.4.0
+    with:
+      enable-secret-scan: true
+      enable-sast-scan: true
+      secret-runs-on: linux-amd64-cpu4
+      # Set failure_policy explicitly so enforcement can't drift with upstream defaults.
+      #   unverified — fail on verified/live secrets (183); warn on unverified (185)  [default]
+      #   strict     — fail on any finding (verified or unverified)
+      #   all        — warn only; never fail the job on findings
+      secret-failure-policy: unverified
+      # Same analysis the retired codeql.yml performed: python, build-mode none, security-extended.
+      sast-languages: '["python"]'
diff --git a/.github/workflows/test-sdist-linux.yml b/.github/workflows/test-sdist-linux.yml
index cc00dfee680..8876ae102a4 100644
--- a/.github/workflows/test-sdist-linux.yml
+++ b/.github/workflows/test-sdist-linux.yml
@@ -11,26 +11,34 @@ on:
       cuda-version:
         required: true
         type: string
-      cuda-channel:
+      workplan:
+        description: JSON workplan. An empty value builds everything.
         required: false
+        default: ""
         type: string
-        default: stable
 
 defaults:
   run:
     shell: bash --noprofile --norc -xeuo pipefail {0}
 
 permissions:
+  actions: read  # This is required for actions/download-artifact
   contents: read  # This is required for actions/checkout
 
 jobs:
   test-sdist:
     name: Test sdist builds
+    if: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).jobs.sdist_tests }}
+    env:
+      BUILD_PATHFINDER: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.pathfinder.needs_build }}
+      BUILD_BINDINGS: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.bindings.needs_build }}
+      BUILD_CORE: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.core.needs_build }}
+      BUILD_PYTHON: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.python.needs_build }}
     timeout-minutes: 60
     runs-on: linux-amd64-cpu8
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # Treeless clone: setuptools-scm (invoked via `python -m build`) needs
           # the commit graph (`git describe`) but not historical blobs.
@@ -38,34 +46,55 @@ jobs:
           filter: blob:none
 
       - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           python-version: "3.12"
 
       - name: Install build tools
-        run: pip install build
+        run: python -m pip install "pip>=25.3" build
 
       # Pure Python packages -- no CTK needed.
       - name: Build cuda.pathfinder sdist and wheel-from-sdist
+        if: ${{ env.BUILD_PATHFINDER == 'true' }}
         run: |
           python -m build --sdist cuda_pathfinder/
           pip wheel --no-deps --wheel-dir cuda_pathfinder/dist cuda_pathfinder/dist/*.tar.gz
 
       - name: Build cuda-python sdist and wheel-from-sdist
+        if: ${{ env.BUILD_PYTHON == 'true' }}
         run: |
           python -m build --sdist cuda_python/
           pip wheel --no-deps --wheel-dir cuda_python/dist cuda_python/dist/*.tar.gz
 
+      - name: Download cuda.pathfinder wheel
+        if: ${{ env.BUILD_PATHFINDER != 'true' && (env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true') }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: cuda-pathfinder-wheel
+          path: cuda_pathfinder/dist
+
+      - name: Constrain builds to the local cuda.pathfinder wheel
+        if: ${{ env.BUILD_BINDINGS == 'true' }}
+        run: |
+          pathfinder_wheels=(cuda_pathfinder/dist/cuda_pathfinder-*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file://$(realpath "${pathfinder_wheels[0]}")"
+          printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}" | tee wheel-constraints/cuda-bindings.txt
+
       # Cython packages need CTK + sccache.
       # The env vars ACTIONS_CACHE_SERVICE_V2, ACTIONS_RESULTS_URL, and ACTIONS_RUNTIME_TOKEN
       # are exposed by this action.
       - name: Enable sccache
-        uses: mozilla-actions/sccache-action@9e7fa8a12102821edf02ca5dbea1acd0f89a2696  # 0.0.10
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' }}
+        uses: mozilla-actions/sccache-action@fc920bf0ec8de6ee65d409111f7ec508035751ba  # 0.0.11
         with:
           disable_annotations: 'true'
 
       # xref: https://github.com/orgs/community/discussions/42856#discussioncomment-7678867
       - name: Adding additional GHA cache-related env vars
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' }}
         uses: actions/github-script@v9
         with:
           script: |
@@ -73,43 +102,73 @@ jobs:
             core.exportVariable('ACTIONS_RUNTIME_URL', process.env['ACTIONS_RUNTIME_URL'])
 
       - name: Setup proxy cache
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' }}
         uses: nv-gha-runners/setup-proxy-cache@main
         continue-on-error: true
         with:
           enable-apt: true
 
       - name: Set up mini CTK
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' }}
         uses: ./.github/actions/fetch_ctk
         continue-on-error: false
         with:
           host-platform: ${{ inputs.host-platform }}
           cuda-version: ${{ inputs.cuda-version }}
-          cuda-channel: ${{ inputs.cuda-channel }}
 
       # cuda_bindings/setup.py parses CUDA headers at import time, so CUDA_PATH
       # (set by fetch_ctk) must be available for both sdist and wheel builds.
       - name: Build cuda.bindings sdist and wheel-from-sdist
+        if: ${{ env.BUILD_BINDINGS == 'true' }}
         run: |
           export CUDA_PYTHON_PARALLEL_LEVEL=$(nproc)
           export CC="sccache cc"
           export CXX="sccache c++"
-          export PIP_FIND_LINKS="$(pwd)/cuda_pathfinder/dist"
+          export PIP_BUILD_CONSTRAINT="$(pwd)/wheel-constraints/cuda-bindings.txt"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
           python -m build --sdist cuda_bindings/
           pip wheel --no-deps --wheel-dir cuda_bindings/dist cuda_bindings/dist/*.tar.gz
 
+      - name: Download cuda.bindings wheel
+        if: ${{ env.BUILD_BINDINGS != 'true' && env.BUILD_CORE == 'true' }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: cuda-bindings-python312-cuda${{ inputs.cuda-version }}-${{ inputs.host-platform }}-${{ github.sha }}
+          path: cuda_bindings/dist
+
+      - name: Constrain cuda.core to the local cuda.bindings wheel
+        if: ${{ env.BUILD_CORE == 'true' }}
+        run: |
+          CUDA_MAJOR="$(echo '${{ inputs.cuda-version }}' | cut -d. -f1)"
+          pathfinder_wheels=(cuda_pathfinder/dist/cuda_pathfinder-*.whl)
+          bindings_wheels=(cuda_bindings/dist/cuda_bindings-"${CUDA_MAJOR}".*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test "${#bindings_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          test -f "${bindings_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file://$(realpath "${pathfinder_wheels[0]}")"
+          bindings_uri="file://$(realpath "${bindings_wheels[0]}")"
+          {
+            printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}"
+            printf 'cuda-bindings @ %s\n' "${bindings_uri}"
+          } | tee wheel-constraints/cuda-core.txt
+
       # cuda_core sdist delegates to setuptools (no CTK needed), but
       # wheel-from-sdist needs CTK and cuda-bindings (dynamic build dep via
       # get_requires_for_build_wheel in build_hooks.py).
       - name: Build cuda.core sdist and wheel-from-sdist
+        if: ${{ env.BUILD_CORE == 'true' }}
         run: |
           export CUDA_PYTHON_PARALLEL_LEVEL=$(nproc)
           export CUDA_CORE_BUILD_MAJOR="$(echo '${{ inputs.cuda-version }}' | cut -d. -f1)"
           export CC="sccache cc"
           export CXX="sccache c++"
-          export PIP_FIND_LINKS="$(pwd)/cuda_bindings/dist $(pwd)/cuda_pathfinder/dist"
+          export PIP_BUILD_CONSTRAINT="$(pwd)/wheel-constraints/cuda-core.txt"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
           python -m build --sdist cuda_core/
           pip wheel --no-deps --wheel-dir cuda_core/dist cuda_core/dist/*.tar.gz
 
       - name: Show sccache stats
-        if: always()
+        if: ${{ always() && (env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true') }}
         run: sccache --show-stats
diff --git a/.github/workflows/test-sdist-windows.yml b/.github/workflows/test-sdist-windows.yml
index c0e4b2abc55..b35f80a2276 100644
--- a/.github/workflows/test-sdist-windows.yml
+++ b/.github/workflows/test-sdist-windows.yml
@@ -17,26 +17,34 @@ on:
       cuda-version:
         required: true
         type: string
-      cuda-channel:
+      workplan:
+        description: JSON workplan. An empty value builds everything.
         required: false
+        default: ""
         type: string
-        default: stable
 
 defaults:
   run:
     shell: bash --noprofile --norc -xeuo pipefail {0}
 
 permissions:
+  actions: read  # This is required for actions/download-artifact
   contents: read  # This is required for actions/checkout
 
 jobs:
   test-sdist:
     name: Test sdist builds
+    if: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).jobs.sdist_tests }}
+    env:
+      BUILD_PATHFINDER: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.pathfinder.needs_build }}
+      BUILD_BINDINGS: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.bindings.needs_build }}
+      BUILD_CORE: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.core.needs_build }}
+      BUILD_PYTHON: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.python.needs_build }}
     timeout-minutes: 60
     runs-on: windows-2022
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           # Treeless clone: setuptools-scm (invoked via `python -m build`) needs
           # the commit graph (`git describe`) but not historical blobs.
@@ -44,58 +52,105 @@ jobs:
           filter: blob:none
 
       - name: Set up Python
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
           python-version: "3.12"
 
       - name: Set up MSVC
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' }}
         uses: step-security/msvc-dev-cmd@22c98154b708dbd743e6f27a933cf6ceba3305c4  # v1.13.1
 
       - name: Install build tools
-        run: pip install build
+        run: python -m pip install "pip>=25.3" build
 
       # Pure Python packages -- no CTK needed.
       - name: Build cuda.pathfinder sdist and wheel-from-sdist
+        if: ${{ env.BUILD_PATHFINDER == 'true' }}
         run: |
           python -m build --sdist cuda_pathfinder/
           pip wheel --no-deps --wheel-dir cuda_pathfinder/dist cuda_pathfinder/dist/*.tar.gz
 
       - name: Build cuda-python sdist and wheel-from-sdist
+        if: ${{ env.BUILD_PYTHON == 'true' }}
         run: |
           python -m build --sdist cuda_python/
           pip wheel --no-deps --wheel-dir cuda_python/dist cuda_python/dist/*.tar.gz
 
+      - name: Download cuda.pathfinder wheel
+        if: ${{ env.BUILD_PATHFINDER != 'true' && (env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true') }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: cuda-pathfinder-wheel
+          path: cuda_pathfinder/dist
+
+      - name: Constrain builds to the local cuda.pathfinder wheel
+        if: ${{ env.BUILD_BINDINGS == 'true' }}
+        run: |
+          pathfinder_wheels=(cuda_pathfinder/dist/cuda_pathfinder-*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file:///$(cygpath -am "${pathfinder_wheels[0]}")"
+          printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}" | tee wheel-constraints/cuda-bindings.txt
+
       # Cython packages need CTK. No sccache on Windows (this is a correctness
       # smoke test, not a production build; see build-wheel.yml which also
       # limits sccache to Linux).
       - name: Set up mini CTK
+        if: ${{ env.BUILD_BINDINGS == 'true' || env.BUILD_CORE == 'true' }}
         uses: ./.github/actions/fetch_ctk
         continue-on-error: false
         with:
           host-platform: ${{ inputs.host-platform }}
           cuda-version: ${{ inputs.cuda-version }}
-          cuda-channel: ${{ inputs.cuda-channel }}
 
       # cuda_bindings/setup.py parses CUDA headers at import time, so CUDA_PATH
       # (set by fetch_ctk) must be available for both sdist and wheel builds.
-      # PIP_FIND_LINKS is passed as a native Windows path via cygpath because
-      # pip on Windows treats space-separated entries as separators and is
-      # picky about mixed path styles (see build-wheel.yml for the same
-      # convention).
+      # Constraint paths are passed as native Windows paths because the pip
+      # subprocesses run outside Git Bash.
       - name: Build cuda.bindings sdist and wheel-from-sdist
+        if: ${{ env.BUILD_BINDINGS == 'true' }}
         run: |
           export CUDA_PYTHON_PARALLEL_LEVEL=$(nproc)
-          export PIP_FIND_LINKS="$(cygpath -w "$(pwd)/cuda_pathfinder/dist")"
+          export PIP_BUILD_CONSTRAINT="$(cygpath -w "$(pwd)/wheel-constraints/cuda-bindings.txt")"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
           python -m build --sdist cuda_bindings/
           pip wheel --no-deps --wheel-dir cuda_bindings/dist cuda_bindings/dist/*.tar.gz
 
+      - name: Download cuda.bindings wheel
+        if: ${{ env.BUILD_BINDINGS != 'true' && env.BUILD_CORE == 'true' }}
+        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
+        with:
+          name: cuda-bindings-python312-cuda${{ inputs.cuda-version }}-${{ inputs.host-platform }}-${{ github.sha }}
+          path: cuda_bindings/dist
+
+      - name: Constrain cuda.core to the local cuda.bindings wheel
+        if: ${{ env.BUILD_CORE == 'true' }}
+        run: |
+          CUDA_MAJOR="$(echo '${{ inputs.cuda-version }}' | cut -d. -f1)"
+          pathfinder_wheels=(cuda_pathfinder/dist/cuda_pathfinder-*.whl)
+          bindings_wheels=(cuda_bindings/dist/cuda_bindings-"${CUDA_MAJOR}".*.whl)
+          test "${#pathfinder_wheels[@]}" -eq 1
+          test "${#bindings_wheels[@]}" -eq 1
+          test -f "${pathfinder_wheels[0]}"
+          test -f "${bindings_wheels[0]}"
+          mkdir -p wheel-constraints
+          pathfinder_uri="file:///$(cygpath -am "${pathfinder_wheels[0]}")"
+          bindings_uri="file:///$(cygpath -am "${bindings_wheels[0]}")"
+          {
+            printf 'cuda-pathfinder @ %s\n' "${pathfinder_uri}"
+            printf 'cuda-bindings @ %s\n' "${bindings_uri}"
+          } | tee wheel-constraints/cuda-core.txt
+
       # cuda_core sdist delegates to setuptools (no CTK needed), but
       # wheel-from-sdist needs CTK and cuda-bindings (dynamic build dep via
       # get_requires_for_build_wheel in build_hooks.py).
       - name: Build cuda.core sdist and wheel-from-sdist
+        if: ${{ env.BUILD_CORE == 'true' }}
         run: |
           export CUDA_PYTHON_PARALLEL_LEVEL=$(nproc)
           export CUDA_CORE_BUILD_MAJOR="$(echo '${{ inputs.cuda-version }}' | cut -d. -f1)"
-          export PIP_FIND_LINKS="$(cygpath -w "$(pwd)/cuda_bindings/dist") $(cygpath -w "$(pwd)/cuda_pathfinder/dist")"
+          export PIP_BUILD_CONSTRAINT="$(cygpath -w "$(pwd)/wheel-constraints/cuda-core.txt")"
+          export PIP_CONSTRAINT="${PIP_BUILD_CONSTRAINT}"
           python -m build --sdist cuda_core/
           pip wheel --no-deps --wheel-dir cuda_core/dist cuda_core/dist/*.tar.gz
diff --git a/.github/workflows/test-wheel-linux.yml b/.github/workflows/test-wheel-linux.yml
index 3bf53aff5fa..e36d45cb623 100644
--- a/.github/workflows/test-wheel-linux.yml
+++ b/.github/workflows/test-wheel-linux.yml
@@ -22,13 +22,10 @@ on:
       nruns:
         type: number
         default: 1
-      # When true, cuda.bindings tests (and the Cython tests that depend on
-      # them) are skipped even when CTK majors match. Callers set this based
-      # on the output of the detect-changes job in ci.yml so PRs that only
-      # touch unrelated modules avoid the expensive bindings test suite.
-      skip-bindings-test:
-        type: boolean
-        default: false
+      workplan:
+        description: JSON workplan. An empty value tests everything.
+        type: string
+        default: ""
       run-id:
         description: >
           Workflow run ID to download artifacts from.
@@ -65,7 +62,7 @@ jobs:
       OLD_BRANCH: ${{ steps.compute-matrix.outputs.OLD_BRANCH }}
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Validate Test Type
         run: |
@@ -101,6 +98,11 @@ jobs:
           echo "OLD_BRANCH=${OLD_BRANCH}" >> "$GITHUB_OUTPUT"
 
   test:
+    env:
+      TEST_PATHFINDER: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.pathfinder.needs_test }}
+      TEST_BINDINGS: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.bindings.needs_test }}
+      TEST_CORE: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.core.needs_test }}
+      TEST_PYTHON: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.python.needs_test }}
     name: Python ${{ matrix.PY_VER }}, CUDA ${{ matrix.CUDA_VER }} (${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}), GPU ${{ matrix.GPU }}${{ matrix.GPU_COUNT != '1' && format(' (x{0})', matrix.GPU_COUNT) || '' }}${{ matrix.FLAVOR && format(', {0}', matrix.FLAVOR) || '' }}${{ matrix.ENV.TORCH_VER && format(', {0}+{1}', matrix.ENV.TORCH_VER, matrix.ENV.TORCH_CUDA) || '' }}${{ matrix.ENV.MODE == 'nightly-numba-cuda' && ', latest' || '' }}
     timeout-minutes: 60
     needs: compute-matrix
@@ -125,7 +127,7 @@ jobs:
         PIP_CACHE_DIR: "/tmp/pip-cache"
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Setup proxy cache
         uses: nv-gha-runners/setup-proxy-cache@main
@@ -159,7 +161,7 @@ jobs:
           LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
           PY_VER: ${{ matrix.PY_VER }}
           SHA: ${{ inputs.sha || github.sha }}
-          SKIP_BINDINGS_TEST_OVERRIDE: ${{ inputs.skip-bindings-test && '1' || '0' }}
+          SKIP_BINDINGS_TEST_OVERRIDE: ${{ env.TEST_BINDINGS != 'true' && '1' || '0' }}
         run: ./ci/tools/env-vars test
 
       - name: Apply extra matrix environment variables
@@ -169,6 +171,7 @@ jobs:
         run: echo "$MATRIX_ENV" | jq -r 'to_entries[] | "\(.key)=\(.value)"' >> "$GITHUB_ENV"
 
       - name: Download cuda-pathfinder build artifacts
+        if: ${{ env.TEST_PATHFINDER == 'true' || env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: cuda-pathfinder-wheel
@@ -177,7 +180,7 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Download cuda-python build artifacts
-        if: ${{ env.BINDINGS_SOURCE == 'main' }}
+        if: ${{ env.TEST_PYTHON == 'true' && env.BINDINGS_SOURCE == 'main' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: cuda-python-wheel
@@ -186,7 +189,8 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Download cuda.bindings build artifacts
-        if: ${{ env.BINDINGS_SOURCE == 'main' }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                env.BINDINGS_SOURCE == 'main' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_BINDINGS_ARTIFACT_NAME }}
@@ -195,7 +199,8 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Download cuda-python & cuda.bindings build artifacts from the prior branch
-        if: ${{ env.BINDINGS_SOURCE == 'backport' }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                env.BINDINGS_SOURCE == 'backport' }}
         env:
           GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
@@ -210,35 +215,53 @@ jobs:
           && apt install gh -y
 
           OLD_BRANCH=${{ needs.compute-matrix.outputs.OLD_BRANCH }}
-          OLD_BASENAME="cuda-bindings-python${PYTHON_VERSION_FORMATTED}-cuda*-${{ inputs.host-platform }}*"
-          LATEST_PRIOR_RUN_ID=$(./ci/tools/lookup-run-id --branch "${OLD_BRANCH}" NVIDIA/cuda-python "CI")
-
-          gh run download $LATEST_PRIOR_RUN_ID -p ${OLD_BASENAME} -R NVIDIA/cuda-python
-          rm -rf ${OLD_BASENAME}-tests  # exclude cython test artifacts
-          ls -al $OLD_BASENAME
+          OLD_ARTIFACT_PATTERN="cuda-bindings-python${PYTHON_VERSION_FORMATTED}-cuda*-${{ inputs.host-platform }}-*[0-9a-f]"
+          LOOKUP_ARGS=(
+            --branch "${OLD_BRANCH}"
+            --artifact "${OLD_ARTIFACT_PATTERN}"
+          )
+          if ${{ env.TEST_PYTHON == 'true' }}; then
+            LOOKUP_ARGS+=(--artifact cuda-python-wheel)
+          fi
+          LATEST_PRIOR_RUN_ID=$(./ci/tools/lookup-run-id \
+            "${LOOKUP_ARGS[@]}" NVIDIA/cuda-python "CI")
+
+          gh run download \
+            "${LATEST_PRIOR_RUN_ID}" \
+            -p "${OLD_ARTIFACT_PATTERN}" \
+            -R NVIDIA/cuda-python
+          OLD_ARTIFACT_DIR=$(compgen -G "${OLD_ARTIFACT_PATTERN}")
+          test -d "${OLD_ARTIFACT_DIR}"
+          ls -al "${OLD_ARTIFACT_DIR}"
           mkdir -p "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"
-          mv $OLD_BASENAME/*.whl "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"/
-          rmdir $OLD_BASENAME
-
-          gh run download $LATEST_PRIOR_RUN_ID -p cuda-python-wheel -R NVIDIA/cuda-python
-          ls -al cuda-python-wheel
-          mv cuda-python-wheel/*.whl .
-          rmdir cuda-python-wheel
+          mv "${OLD_ARTIFACT_DIR}"/*.whl "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"/
+          rmdir "${OLD_ARTIFACT_DIR}"
+
+          if ${{ env.TEST_PYTHON == 'true' }}; then
+            gh run download \
+              "${LATEST_PRIOR_RUN_ID}" \
+              -p cuda-python-wheel \
+              -R NVIDIA/cuda-python
+            ls -al cuda-python-wheel
+            mv cuda-python-wheel/*.whl .
+            rmdir cuda-python-wheel
+          fi
 
       - name: Display structure of downloaded cuda-python artifacts
-        if: ${{ env.BINDINGS_SOURCE != 'published' }}
+        if: ${{ env.TEST_PYTHON == 'true' && env.BINDINGS_SOURCE != 'published' }}
         run: |
           pwd
           ls -lah cuda_python*.whl cuda_pathfinder/
 
       - name: Display structure of downloaded cuda.bindings artifacts
-        if: ${{ env.BINDINGS_SOURCE != 'published' }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                env.BINDINGS_SOURCE != 'published' }}
         run: |
           pwd
           ls -lahR $CUDA_BINDINGS_ARTIFACTS_DIR
 
       - name: Download cuda.bindings Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_BINDINGS == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_BINDINGS_ARTIFACT_NAME }}-tests
@@ -247,12 +270,13 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.bindings Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_BINDINGS == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         run: |
           pwd
           ls -lahR $CUDA_BINDINGS_CYTHON_TESTS_DIR
 
       - name: Download cuda.core build artifacts
+        if: ${{ env.TEST_CORE == 'true' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}
@@ -261,12 +285,13 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.core build artifacts
+        if: ${{ env.TEST_CORE == 'true' }}
         run: |
           pwd
           ls -lahR $CUDA_CORE_ARTIFACTS_DIR
 
       - name: Download cuda.core Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_CORE == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}-tests
@@ -275,12 +300,13 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.core Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_CORE == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         run: |
           pwd
           ls -lahR $CUDA_CORE_CYTHON_TESTS_DIR
 
       - name: Download cuda.core test binaries
+        if: ${{ env.TEST_CORE == 'true' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}-test-binaries
@@ -289,23 +315,28 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.core test binaries
+        if: ${{ env.TEST_CORE == 'true' }}
         run: |
           pwd
           ls -lahR $CUDA_CORE_TEST_BINARIES_DIR
 
       - name: Set up Python ${{ matrix.PY_VER }}
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
-          # TODO: Pin beta.2 precisely until cibuildwheel catches up (b4 broke ABI for Cython)
-          # this precise pin requires the explicit `freethreaded`.
-          # When 3.15 is officially supported we can also remove the `allow-prereleases` override.
-          python-version: ${{ startsWith(matrix.PY_VER, '3.15') && '3.15.0-beta.2' || matrix.PY_VER }}
-          freethreaded: ${{ endsWith(matrix.PY_VER, 't') }}
+          python-version: ${{ matrix.PY_VER }}
+          # TODO: remove allow-prereleases once 3.15 is officially supported
           allow-prereleases: ${{ startsWith(matrix.PY_VER, '3.15') }}
         env:
           # we use self-hosted runners on which setup-python behaves weirdly (Python include can't be found)...
           AGENT_TOOLSDIRECTORY: "/opt/hostedtoolcache"
 
+      - name: Enable Scientific Python Nightly Wheels for Python 3.15
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                startsWith(matrix.PY_VER, '3.15') }}
+        run: |
+          echo "PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple" >> "$GITHUB_ENV"
+          echo "PIP_ONLY_BINARY=numpy" >> "$GITHUB_ENV"
+
       - name: Set up mini CTK
         if: ${{ matrix.LOCAL_CTK == '1' }}
         uses: ./.github/actions/fetch_ctk
@@ -314,20 +345,8 @@ jobs:
           host-platform: ${{ inputs.host-platform }}
           cuda-version: ${{ matrix.CUDA_VER }}
 
-      # TODO: remove the numpy wheel steps once 3.15 is officially supported
-      - name: Download numpy wheel (pre-release Python)
-        if: ${{ startsWith(matrix.PY_VER, '3.15') }}
-        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
-        with:
-          name: numpy-python${{ env.PYTHON_VERSION_FORMATTED }}-${{ inputs.host-platform }}
-          path: numpy-wheel
-
-      - name: Install numpy wheel (pre-release Python)
-        if: ${{ startsWith(matrix.PY_VER, '3.15') }}
-        run: pip install numpy-wheel/*.whl
-
       - name: Set up latest cuda_sanitizer_api
-        if: ${{ env.SETUP_SANITIZER == '1' }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true') && env.SETUP_SANITIZER == '1' }}
         uses: ./.github/actions/fetch_ctk
         continue-on-error: false
         with:
@@ -336,6 +355,7 @@ jobs:
           cuda-components: "cuda_sanitizer_api"
 
       - name: Set up compute-sanitizer
+        if: ${{ env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' }}
         run: setup-sanitizer
 
       - name: Set up test repetition on nightly runs
@@ -343,7 +363,7 @@ jobs:
 
       # ── Standard test steps (skipped for nightly modes) ──
       - name: Run cuda.pathfinder tests with see_what_works
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PATHFINDER == 'true' }}
         env:
           CUDA_PATHFINDER_TEST_LOAD_NVIDIA_DYNAMIC_LIB_STRICTNESS: see_what_works
           CUDA_PATHFINDER_TEST_FIND_NVIDIA_HEADERS_STRICTNESS: see_what_works
@@ -351,17 +371,14 @@ jobs:
         run: run-tests pathfinder
 
       - name: Run cuda.bindings tests
-        if: ${{ inputs.test-mode == 'standard' && env.SKIP_CUDA_BINDINGS_TEST == '0' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_BINDINGS == 'true' && env.SKIP_CUDA_BINDINGS_TEST == '0' }}
         env:
           CUDA_VER: ${{ matrix.CUDA_VER }}
           LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
-          # #2299: BAR-size query returns CUDA_ERROR_NOT_SUPPORTED on G+H;
-          # skip the test on gh200 runners until upstream cufile guards it.
-          PYTEST_ADDOPTS: ${{ matrix.GPU == 'gh200' && '--deselect tests/test_cufile.py::test_get_bar_size_in_kb' || '' }}
         run: run-tests bindings
 
       - name: Run cuda.bindings benchmarks (smoke test)
-        if: ${{ inputs.test-mode == 'standard' && env.SKIP_CUDA_BINDINGS_TEST == '0' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_BINDINGS == 'true' && env.SKIP_CUDA_BINDINGS_TEST == '0' }}
         run: |
           pip install pyperf
           pushd benchmarks/cuda_bindings
@@ -369,25 +386,35 @@ jobs:
           popd
 
       - name: Run cuda.core tests
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_CORE == 'true' }}
         env:
           CUDA_VER: ${{ matrix.CUDA_VER }}
           LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
         run: run-tests core
 
       - name: Ensure cuda-python installable
-        if: ${{ inputs.test-mode == 'standard' && env.BINDINGS_SOURCE == 'main' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PYTHON == 'true' && env.BINDINGS_SOURCE == 'main' }}
         run: |
-          # Subpackages are already installed from CI artifacts; --no-deps keeps
-          # tag-release cuda-core wheels from being replaced by PyPI pins.
-          if [[ "${{ matrix.LOCAL_CTK }}" == 1 ]]; then
-            pip install --only-binary=:all: --no-deps cuda_python*.whl
+          # Package suites install their own dependencies. A metapackage-only
+          # run has no preceding suite, so install the exact local internal
+          # wheels in one transaction while resolving released dependencies
+          # such as cuda-core from the package index.
+          if ${{ env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' }}; then
+            dependency_args=(--no-deps)
           else
-            pip install --only-binary=:all: --no-deps $(ls cuda_python*.whl)[all]
+            dependency_args=(
+              ./cuda_pathfinder/cuda_pathfinder-*.whl
+              "${CUDA_BINDINGS_ARTIFACTS_DIR}"/cuda_bindings-*.whl
+            )
+          fi
+          python_requirements=(cuda_python*.whl)
+          if [[ "${{ matrix.LOCAL_CTK }}" != 1 ]]; then
+            python_requirements=("${python_requirements[@]/%/[all]}")
           fi
+          pip install --only-binary=:all: "${dependency_args[@]}" "${python_requirements[@]}"
 
       - name: Install cuda.pathfinder extra wheels for testing
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PATHFINDER == 'true' }}
         run: |
           set -euo pipefail
           pushd cuda_pathfinder
@@ -396,7 +423,7 @@ jobs:
           popd
 
       - name: Run cuda.pathfinder tests with all_must_work
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PATHFINDER == 'true' }}
         env:
           CUDA_PATHFINDER_TEST_LOAD_NVIDIA_DYNAMIC_LIB_STRICTNESS: all_must_work
           CUDA_PATHFINDER_TEST_FIND_NVIDIA_HEADERS_STRICTNESS: all_must_work
@@ -437,7 +464,7 @@ jobs:
         if: ${{ inputs.test-mode == 'nightly-pytorch' }}
         run: |
           pushd cuda_core
-          pytest -rxXs -v --durations=0 tests/test_utils.py tests/example_tests/
+          pytest -rxXs -v tests/test_utils.py tests/example_tests/
           popd
 
       - name: Run numba-cuda tests
@@ -446,7 +473,7 @@ jobs:
 
       - name: Checkout numba-cuda-mlir tests at matching tag
         if: ${{ inputs.test-mode == 'nightly-numba-cuda-mlir' && env.NUMBA_CUDA_MLIR_VER != '' }}
-        uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10  # v6.0.3
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           repository: NVIDIA/numba-cuda-mlir
           ref: v${{ env.NUMBA_CUDA_MLIR_VER }}
@@ -454,7 +481,13 @@ jobs:
 
       - name: Run numba-cuda-mlir tests
         if: ${{ inputs.test-mode == 'nightly-numba-cuda-mlir' && env.NUMBA_CUDA_MLIR_VER != '' }}
+        env:
+          LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
         run: |
+          if [[ "${LOCAL_CTK}" != 1 ]]; then
+            # Let numba-cuda-mlir skip inputs that require toolkit executables.
+            export NUMBA_CUDA_MLIR_TEST_WHEEL_ONLY=1
+          fi
           pushd numba-cuda-mlir-released
           # Install this tag's test deps (pytest + plugins + ml-dtypes + ...).
           pip install --upgrade "pip>=25.1"
@@ -462,51 +495,15 @@ jobs:
           # Skip tests/benchmarks/ and tests/doc_examples/ — they import the
           # numba package at collection time, which cuSIMT intentionally does
           # not depend on. See NVIDIA/numba-cuda-mlir#136.
-          #
-          # Version-gated deselects: when a newer numba-cuda-mlir release
-          # ships with the referenced fix, the guard evaluates false and the
-          # tests get run automatically. If they still fail on the newer
-          # version we hear about it loudly (rather than silently masking).
-          DESELECTS=()
-          if python -c "from packaging.version import Version; import sys; sys.exit(0 if Version('${NUMBA_CUDA_MLIR_VER}') <= Version('0.4.1') else 1)"; then
-            # NVIDIA/numba-cuda-mlir#135: serial-pytest contamination of
-            # numba_cuda_mlir.cuda.cudadrv from an xfailed test in
-            # test_nrt_comprehensive.py contaminates any later test that
-            # touches cuda.cudadrv.driver. Upstream CI hides it via
-            # `-n auto --dist loadscope`. Which specific tests fail depends
-            # on collection order (we saw different subsets on linux-64 vs
-            # win-64 across runs), so we deselect the union of all tests
-            # #135 lists as vulnerable + test_fortran_contiguous (observed
-            # to hit the same contamination in our runs).
-            #
-            # test_nvjitlink_jit_with_linkable_code_lto_dump_assembly_warn:
-            # subprocess-invokes `cuobjdump`, not on PATH in the base
-            # ubuntu:24.04 container. (Linux-only; Windows runners ship
-            # cuobjdump with the local CTK. No upstream fix yet — pending
-            # a skip-guard bug to be filed against NVIDIA/numba-cuda-mlir.)
-            DESELECTS+=(
-              --deselect 'tests/numba_cuda_tests/cudadrv/test_cuda_array_slicing.py::CudaArraySetting::test_no_sync_default_stream'
-              --deselect 'tests/numba_cuda_tests/cudadrv/test_cuda_array_slicing.py::CudaArraySetting::test_no_sync_supplied_stream'
-              --deselect 'tests/numba_cuda_tests/cudadrv/test_cuda_array_slicing.py::CudaArraySetting::test_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_consume_no_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_consume_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_launch_no_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_launch_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_launch_sync_two_streams'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_fortran_contiguous'
-              --deselect 'tests/numba_cuda_tests/cudadrv/test_nvjitlink.py::TestLinkerDumpAssembly::test_nvjitlink_jit_with_linkable_code_lto_dump_assembly_warn'
-            )
-          fi
-          pytest -rxXs -v --durations=0 \
+          pytest -rxXs -v \
             --ignore=tests/benchmarks \
             --ignore=tests/doc_examples \
-            "${DESELECTS[@]}" \
             tests/
           popd
 
       - name: Checkout released cuda-core tests at matching tag
         if: ${{ inputs.test-mode == 'nightly-cuda-core' && env.CUDA_CORE_RELEASED_VER != '' }}
-        uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10  # v6.0.3
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           ref: cuda-core-v${{ env.CUDA_CORE_RELEASED_VER }}
           path: cuda-core-released
@@ -534,7 +531,7 @@ jobs:
               --deselect 'tests/test_enum_coverage.py::test_wrapper_covers_all_binding_members[NvlinkVersion]'
             )
           fi
-          pytest -rxXs -v --durations=0 --randomly-dont-reorganize \
+          pytest -rxXs -v --randomly-dont-reorganize \
             "${DESELECTS[@]}" \
             tests/
           popd
diff --git a/.github/workflows/test-wheel-windows.yml b/.github/workflows/test-wheel-windows.yml
index 7f98a649f73..caa3767008f 100644
--- a/.github/workflows/test-wheel-windows.yml
+++ b/.github/workflows/test-wheel-windows.yml
@@ -22,13 +22,10 @@ on:
       nruns:
         type: number
         default: 1
-      # When true, cuda.bindings tests (and the Cython tests that depend on
-      # them) are skipped even when CTK majors match. Callers set this based
-      # on the output of the detect-changes job in ci.yml so PRs that only
-      # touch unrelated modules avoid the expensive bindings test suite.
-      skip-bindings-test:
-        type: boolean
-        default: false
+      workplan:
+        description: JSON workplan. An empty value tests everything.
+        type: string
+        default: ""
       run-id:
         description: >
           Workflow run ID to download artifacts from.
@@ -62,7 +59,7 @@ jobs:
       MATRIX: ${{ steps.compute-matrix.outputs.MATRIX }}
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Validate Test Type
         run: |
@@ -91,6 +88,11 @@ jobs:
           echo "MATRIX=${MATRIX}" | tee --append "${GITHUB_OUTPUT}"
 
   test:
+    env:
+      TEST_PATHFINDER: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.pathfinder.needs_test }}
+      TEST_BINDINGS: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.bindings.needs_test }}
+      TEST_CORE: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.core.needs_test }}
+      TEST_PYTHON: ${{ inputs.workplan == '' || fromJSON(inputs.workplan).modules.python.needs_test }}
     name: Python ${{ matrix.PY_VER }}, CUDA ${{ matrix.CUDA_VER }} (${{ (matrix.LOCAL_CTK == '1' && 'local') || 'wheels' }}), GPU ${{ matrix.GPU }}${{ matrix.GPU_COUNT != '1' && format(' (x{0})', matrix.GPU_COUNT) || '' }} (${{ matrix.DRIVER_MODE }})${{ matrix.ENV.TORCH_VER && format(', {0}+{1}', matrix.ENV.TORCH_VER, matrix.ENV.TORCH_CUDA) || '' }}${{ matrix.ENV.MODE == 'nightly-numba-cuda' && ', latest' || '' }}
     timeout-minutes: 60
     # The build stage could fail but we want the CI to keep moving.
@@ -104,7 +106,7 @@ jobs:
     runs-on: "windows-${{ matrix.ARCH }}-gpu-${{ matrix.GPU }}-${{ matrix.RUNNER_DRIVER }}-${{ matrix.GPU_COUNT }}"
     steps:
       - name: Checkout ${{ github.event.repository.name }}
-        uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0  # v7.0.0
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
 
       - name: Setup proxy cache
         uses: nv-gha-runners/setup-proxy-cache@main
@@ -146,7 +148,7 @@ jobs:
           LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
           PY_VER: ${{ matrix.PY_VER }}
           SHA: ${{ inputs.sha || github.sha }}
-          SKIP_BINDINGS_TEST_OVERRIDE: ${{ inputs.skip-bindings-test && '1' || '0' }}
+          SKIP_BINDINGS_TEST_OVERRIDE: ${{ env.TEST_BINDINGS != 'true' && '1' || '0' }}
         shell: bash --noprofile --norc -xeuo pipefail {0}
         run: ./ci/tools/env-vars test
 
@@ -158,6 +160,7 @@ jobs:
         run: echo "$MATRIX_ENV" | jq -r 'to_entries[] | "\(.key)=\(.value)"' >> "$GITHUB_ENV"
 
       - name: Download cuda-pathfinder build artifacts
+        if: ${{ env.TEST_PATHFINDER == 'true' || env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: cuda-pathfinder-wheel
@@ -166,7 +169,7 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Download cuda-python build artifacts
-        if: ${{ env.BINDINGS_SOURCE == 'main' }}
+        if: ${{ env.TEST_PYTHON == 'true' && env.BINDINGS_SOURCE == 'main' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: cuda-python-wheel
@@ -175,7 +178,8 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Download cuda.bindings build artifacts
-        if: ${{ env.BINDINGS_SOURCE == 'main' }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                env.BINDINGS_SOURCE == 'main' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_BINDINGS_ARTIFACT_NAME }}
@@ -184,41 +188,60 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Download cuda-python & cuda.bindings build artifacts from the prior branch
-        if: ${{ env.BINDINGS_SOURCE == 'backport' }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                env.BINDINGS_SOURCE == 'backport' }}
         env:
           GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         shell: bash --noprofile --norc -xeuo pipefail {0}
         run: |
           OLD_BRANCH=$(yq '.backport_branch' ci/versions.yml)
-          OLD_BASENAME="cuda-bindings-python${PYTHON_VERSION_FORMATTED}-cuda*-${{ inputs.host-platform }}*"
-          LATEST_PRIOR_RUN_ID=$(./ci/tools/lookup-run-id --branch "${OLD_BRANCH}" NVIDIA/cuda-python "CI")
-
-          gh run download $LATEST_PRIOR_RUN_ID -p ${OLD_BASENAME} -R NVIDIA/cuda-python
-          rm -rf ${OLD_BASENAME}-tests  # exclude cython test artifacts
-          ls -al $OLD_BASENAME
+          OLD_ARTIFACT_PATTERN="cuda-bindings-python${PYTHON_VERSION_FORMATTED}-cuda*-${{ inputs.host-platform }}-*[0-9a-f]"
+          LOOKUP_ARGS=(
+            --branch "${OLD_BRANCH}"
+            --artifact "${OLD_ARTIFACT_PATTERN}"
+          )
+          if ${{ env.TEST_PYTHON == 'true' }}; then
+            LOOKUP_ARGS+=(--artifact cuda-python-wheel)
+          fi
+          LATEST_PRIOR_RUN_ID=$(./ci/tools/lookup-run-id \
+            "${LOOKUP_ARGS[@]}" NVIDIA/cuda-python "CI")
+
+          gh run download \
+            "${LATEST_PRIOR_RUN_ID}" \
+            -p "${OLD_ARTIFACT_PATTERN}" \
+            -R NVIDIA/cuda-python
+          OLD_ARTIFACT_DIR=$(compgen -G "${OLD_ARTIFACT_PATTERN}")
+          test -d "${OLD_ARTIFACT_DIR}"
+          ls -al "${OLD_ARTIFACT_DIR}"
           mkdir -p "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"
-          mv $OLD_BASENAME/*.whl "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"/
-          rmdir $OLD_BASENAME
-
-          gh run download $LATEST_PRIOR_RUN_ID -p cuda-python-wheel -R NVIDIA/cuda-python
-          ls -al cuda-python-wheel
-          mv cuda-python-wheel/*.whl .
-          rmdir cuda-python-wheel
+          mv "${OLD_ARTIFACT_DIR}"/*.whl "${{ env.CUDA_BINDINGS_ARTIFACTS_DIR }}"/
+          rmdir "${OLD_ARTIFACT_DIR}"
+
+          if ${{ env.TEST_PYTHON == 'true' }}; then
+            gh run download \
+              "${LATEST_PRIOR_RUN_ID}" \
+              -p cuda-python-wheel \
+              -R NVIDIA/cuda-python
+            ls -al cuda-python-wheel
+            mv cuda-python-wheel/*.whl .
+            rmdir cuda-python-wheel
+          fi
 
       - name: Display structure of downloaded cuda-python artifacts
-        if: ${{ env.BINDINGS_SOURCE != 'published' }}
+        if: ${{ env.TEST_PYTHON == 'true' && env.BINDINGS_SOURCE != 'published' }}
         run: |
           Get-Location
           Get-ChildItem cuda_python*.whl | Select-Object Mode, LastWriteTime, Length, FullName
 
       - name: Display structure of downloaded cuda.bindings artifacts
-        if: ${{ env.BINDINGS_SOURCE != 'published' }}
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                env.BINDINGS_SOURCE != 'published' }}
         run: |
           Get-Location
           Get-ChildItem -Recurse -Force $env:CUDA_BINDINGS_ARTIFACTS_DIR | Select-Object Mode, LastWriteTime, Length, FullName
 
       - name: Download cuda.bindings Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_BINDINGS == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_BINDINGS_ARTIFACT_NAME }}-tests
@@ -227,12 +250,13 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.bindings Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_BINDINGS == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         run: |
           Get-Location
           Get-ChildItem -Recurse -Force $env:CUDA_BINDINGS_CYTHON_TESTS_DIR | Select-Object Mode, LastWriteTime, Length, FullName
 
       - name: Download cuda.core build artifacts
+        if: ${{ env.TEST_CORE == 'true' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}
@@ -241,12 +265,13 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.core build artifacts
+        if: ${{ env.TEST_CORE == 'true' }}
         run: |
           Get-Location
           Get-ChildItem -Recurse -Force $env:CUDA_CORE_ARTIFACTS_DIR | Select-Object Mode, LastWriteTime, Length, FullName
 
       - name: Download cuda.core Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_CORE == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}-tests
@@ -255,12 +280,13 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.core Cython tests
-        if: ${{ env.SKIP_CYTHON_TEST == '0' }}
+        if: ${{ env.TEST_CORE == 'true' && env.SKIP_CYTHON_TEST == '0' }}
         run: |
           Get-Location
           Get-ChildItem -Recurse -Force $env:CUDA_CORE_CYTHON_TESTS_DIR | Select-Object Mode, LastWriteTime, Length, FullName
 
       - name: Download cuda.core test binaries
+        if: ${{ env.TEST_CORE == 'true' }}
         uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
         with:
           name: ${{ env.CUDA_CORE_ARTIFACT_NAME }}-test-binaries
@@ -269,20 +295,26 @@ jobs:
           github-token: ${{ secrets.GITHUB_TOKEN }}
 
       - name: Display structure of downloaded cuda.core test binaries
+        if: ${{ env.TEST_CORE == 'true' }}
         run: |
           Get-Location
           Get-ChildItem -Recurse -Force $env:CUDA_CORE_TEST_BINARIES_DIR | Select-Object Mode, LastWriteTime, Length, FullName
 
       - name: Set up Python ${{ matrix.PY_VER }}
-        uses: actions/setup-python@ece7cb06caefa5fff74198d8649806c4678c61a1  # v6.3.0
+        uses: actions/setup-python@5fda3b95a4ea91299a34e894583c3862153e4b97  # v7.0.0
         with:
-          # TODO: Pin beta.2 precisely until cibuildwheel catches up (b4 broke ABI for Cython)
-          # this precise pin requires the explicit `freethreaded`.
-          # When 3.15 is officially supported we can also remove the `allow-prereleases` override.
-          python-version: ${{ startsWith(matrix.PY_VER, '3.15') && '3.15.0-beta.2' || matrix.PY_VER }}
-          freethreaded: ${{ endsWith(matrix.PY_VER, 't') }}
+          python-version: ${{ matrix.PY_VER }}
+          # TODO: remove allow-prereleases once 3.15 is officially supported
           allow-prereleases: ${{ startsWith(matrix.PY_VER, '3.15') }}
 
+      - name: Enable Scientific Python Nightly Wheels for Python 3.15
+        if: ${{ (env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' || env.TEST_PYTHON == 'true') &&
+                startsWith(matrix.PY_VER, '3.15') }}
+        shell: bash --noprofile --norc -xeuo pipefail {0}
+        run: |
+          echo "PIP_EXTRA_INDEX_URL=https://pypi.anaconda.org/scientific-python-nightly-wheels/simple" >> "$GITHUB_ENV"
+          echo "PIP_ONLY_BINARY=numpy" >> "$GITHUB_ENV"
+
       - name: Verify LongPathsEnabled
         run: |
           $val = (Get-ItemProperty -Path 'HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem' -Name 'LongPathsEnabled').LongPathsEnabled
@@ -300,26 +332,13 @@ jobs:
           host-platform: ${{ inputs.host-platform }}
           cuda-version: ${{ matrix.CUDA_VER }}
 
-      # TODO: remove the numpy wheel steps once 3.15 is officially supported
-      - name: Download numpy wheel (pre-release Python)
-        if: ${{ startsWith(matrix.PY_VER, '3.15') }}
-        uses: actions/download-artifact@3e5f45b2cfb9172054b4087a40e8e0b5a5461e7c  # v8.0.1
-        with:
-          name: numpy-python${{ env.PYTHON_VERSION_FORMATTED }}-${{ inputs.host-platform }}
-          path: numpy-wheel
-
-      - name: Install numpy wheel (pre-release Python)
-        if: ${{ startsWith(matrix.PY_VER, '3.15') }}
-        shell: bash --noprofile --norc -xeuo pipefail {0}
-        run: pip install numpy-wheel/*.whl
-
       - name: Set up test repetition on nightly runs
         shell: bash --noprofile --norc -xeuo pipefail {0}
         run: echo "PYTEST_ADDOPTS=\"--count=${{ inputs.nruns }}\"" >> "$GITHUB_ENV"
 
       # ── Standard test steps (skipped for nightly modes) ──
       - name: Run cuda.pathfinder tests with see_what_works
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PATHFINDER == 'true' }}
         env:
           CUDA_PATHFINDER_TEST_LOAD_NVIDIA_DYNAMIC_LIB_STRICTNESS: see_what_works
           CUDA_PATHFINDER_TEST_FIND_NVIDIA_HEADERS_STRICTNESS: see_what_works
@@ -328,7 +347,7 @@ jobs:
         run: run-tests pathfinder
 
       - name: Run cuda.bindings tests
-        if: ${{ inputs.test-mode == 'standard' && env.SKIP_CUDA_BINDINGS_TEST == '0' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_BINDINGS == 'true' && env.SKIP_CUDA_BINDINGS_TEST == '0' }}
         env:
           CUDA_VER: ${{ matrix.CUDA_VER }}
           LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
@@ -336,7 +355,7 @@ jobs:
         run: run-tests bindings
 
       - name: Run cuda.core tests
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_CORE == 'true' }}
         env:
           CUDA_VER: ${{ matrix.CUDA_VER }}
           LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
@@ -344,18 +363,28 @@ jobs:
         run: run-tests core
 
       - name: Ensure cuda-python installable
-        if: ${{ inputs.test-mode == 'standard' && env.BINDINGS_SOURCE == 'main' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PYTHON == 'true' && env.BINDINGS_SOURCE == 'main' }}
         run: |
-          # Subpackages are already installed from CI artifacts; --no-deps keeps
-          # tag-release cuda-core wheels from being replaced by PyPI pins.
-          if ('${{ matrix.LOCAL_CTK }}' -eq '1') {
-            pip install --only-binary=:all: --no-deps (Get-ChildItem -Filter cuda_python*.whl).FullName
+          # Package suites install their own dependencies. A metapackage-only
+          # run has no preceding suite, so install the exact local internal
+          # wheels in one transaction while resolving released dependencies
+          # such as cuda-core from the package index.
+          if ('${{ env.TEST_BINDINGS == 'true' || env.TEST_CORE == 'true' }}' -eq 'true') {
+            $dependencyArgs = @('--no-deps')
           } else {
-            pip install --only-binary=:all: --no-deps "$((Get-ChildItem -Filter cuda_python*.whl).FullName)[all]"
+            $dependencyArgs = @(
+              (Get-Item ./cuda_pathfinder/cuda_pathfinder-*.whl).FullName
+              (Get-Item "$env:CUDA_BINDINGS_ARTIFACTS_DIR/cuda_bindings-*.whl").FullName
+            )
           }
+          $pythonRequirements = @((Get-Item ./cuda_python*.whl).FullName)
+          if ('${{ matrix.LOCAL_CTK }}' -ne '1') {
+            $pythonRequirements = @($pythonRequirements | ForEach-Object { "$($_)[all]" })
+          }
+          pip install --only-binary=:all: @dependencyArgs @pythonRequirements
 
       - name: Install cuda.pathfinder extra wheels for testing
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PATHFINDER == 'true' }}
         shell: bash --noprofile --norc -xeuo pipefail {0}
         run: |
           pushd cuda_pathfinder
@@ -364,7 +393,7 @@ jobs:
           popd
 
       - name: Run cuda.pathfinder tests with all_must_work
-        if: ${{ inputs.test-mode == 'standard' }}
+        if: ${{ inputs.test-mode == 'standard' && env.TEST_PATHFINDER == 'true' }}
         env:
           CUDA_PATHFINDER_TEST_LOAD_NVIDIA_DYNAMIC_LIB_STRICTNESS: all_must_work
           CUDA_PATHFINDER_TEST_FIND_NVIDIA_HEADERS_STRICTNESS: all_must_work
@@ -418,7 +447,7 @@ jobs:
         shell: bash --noprofile --norc -xeuo pipefail {0}
         run: |
           pushd cuda_core
-          pytest -rxXs -v --durations=0 tests/test_utils.py tests/example_tests/
+          pytest -rxXs -v tests/test_utils.py tests/example_tests/
           popd
 
       - name: Run numba-cuda tests
@@ -428,7 +457,7 @@ jobs:
 
       - name: Checkout numba-cuda-mlir tests at matching tag
         if: ${{ inputs.test-mode == 'nightly-numba-cuda-mlir' && env.NUMBA_CUDA_MLIR_VER != '' }}
-        uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10  # v6.0.3
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           repository: NVIDIA/numba-cuda-mlir
           ref: v${{ env.NUMBA_CUDA_MLIR_VER }}
@@ -436,41 +465,26 @@ jobs:
 
       - name: Run numba-cuda-mlir tests
         if: ${{ inputs.test-mode == 'nightly-numba-cuda-mlir' && env.NUMBA_CUDA_MLIR_VER != '' }}
+        env:
+          LOCAL_CTK: ${{ matrix.LOCAL_CTK }}
         shell: bash --noprofile --norc -xeuo pipefail {0}
         run: |
+          if [[ "${LOCAL_CTK}" != 1 ]]; then
+            # Let numba-cuda-mlir skip inputs that require toolkit executables.
+            export NUMBA_CUDA_MLIR_TEST_WHEEL_ONLY=1
+          fi
           pushd numba-cuda-mlir-released
           pip install --upgrade "pip>=25.1"
           pip install --group test
-          # Version-gated deselects — dropped automatically when newer
-          # cuSIMT release ships. See linux step for full rationale.
-          # NVIDIA/numba-cuda-mlir#135 poisons a subset of tests that
-          # varies across runs based on collection order, so we deselect
-          # the full union rather than trying to enumerate what happened
-          # to fail on the most recent nightly.
-          DESELECTS=()
-          if python -c "from packaging.version import Version; import sys; sys.exit(0 if Version('${NUMBA_CUDA_MLIR_VER}') <= Version('0.4.1') else 1)"; then
-            DESELECTS+=(
-              --deselect 'tests/numba_cuda_tests/cudadrv/test_cuda_array_slicing.py::CudaArraySetting::test_no_sync_default_stream'
-              --deselect 'tests/numba_cuda_tests/cudadrv/test_cuda_array_slicing.py::CudaArraySetting::test_no_sync_supplied_stream'
-              --deselect 'tests/numba_cuda_tests/cudadrv/test_cuda_array_slicing.py::CudaArraySetting::test_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_consume_no_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_consume_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_launch_no_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_launch_sync'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_launch_sync_two_streams'
-              --deselect 'tests/numba_cuda_tests/cudapy/test_cuda_array_interface.py::TestCudaArrayInterface::test_fortran_contiguous'
-            )
-          fi
-          pytest -rxXs -v --durations=0 \
+          pytest -rxXs -v \
             --ignore=tests/benchmarks \
             --ignore=tests/doc_examples \
-            "${DESELECTS[@]}" \
             tests/
           popd
 
       - name: Checkout released cuda-core tests at matching tag
         if: ${{ inputs.test-mode == 'nightly-cuda-core' && env.CUDA_CORE_RELEASED_VER != '' }}
-        uses: actions/checkout@df4cb1c069e1874edd31b4311f1884172cec0e10  # v6.0.3
+        uses: actions/checkout@3d3c42e5aac5ba805825da76410c181273ba90b1  # v7.0.1
         with:
           ref: cuda-core-v${{ env.CUDA_CORE_RELEASED_VER }}
           path: cuda-core-released
@@ -503,7 +517,7 @@ jobs:
               --deselect 'tests/test_memory.py::test_non_managed_resources_report_not_managed[pinned]'
             )
           fi
-          pytest -rxXs -v --durations=0 --randomly-dont-reorganize \
+          pytest -rxXs -v --randomly-dont-reorganize \
             "${DESELECTS[@]}" \
             tests/
           popd
diff --git a/.github/workflows/triagelabel.yml b/.github/workflows/triagelabel.yml
index 300efad36a2..a1e7eafe190 100644
--- a/.github/workflows/triagelabel.yml
+++ b/.github/workflows/triagelabel.yml
@@ -12,6 +12,7 @@ on:
 
 jobs:
   triage:
+    if: ${{ github.repository_owner == 'nvidia' }}
     runs-on: ubuntu-latest
     permissions:
       issues: write
diff --git a/.gitignore b/.gitignore
index 6b6a7dfc0b5..91c3b74a105 100644
--- a/.gitignore
+++ b/.gitignore
@@ -142,7 +142,7 @@ celerybeat.pid
 
 # Environments
 .env
-.venv
+.venv*
 env/
 venv/
 ENV/
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 8a95d188070..451bb72fe8e 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -9,12 +9,20 @@ ci:
     autoupdate_branch: ''
     autoupdate_commit_msg: '[pre-commit.ci] pre-commit autoupdate'
     autoupdate_schedule: quarterly
-    skip: [lychee, check-precommit-installed]
+    skip: [lychee, check-precommit-installed, secret-scan-trufflehog]
     submodules: false
 
 # Please update the rev: SHAs below with this command:
 # pre-commit autoupdate --freeze
 repos:
+  # Runs first so a leaked credential blocks the commit before any formatter runs.
+  # Self-installing: the hook downloads a pinned, checksum-verified trufflehog on
+  # first use (no manual install). Skipped on pre-commit.ci; Pulse CI enforces server-side.
+  - repo: https://github.com/NVIDIA/security-workflows
+    rev: 711025b090f2aa728da576700750b195d1e816dc  # frozen: v0.3.0
+    hooks:
+      - id: secret-scan-trufflehog
+
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: c60c980e561ed3e73101667fe8365c609d19a438  # frozen: v0.15.9
     hooks:
@@ -50,6 +58,20 @@ repos:
         files: ^cuda_bindings/
         types: [text]
 
+      - id: check-pixi-cuda-version
+        name: Check pixi cuda-version pins track ci/versions.yml
+        entry: python ./ci/tools/check_pixi_cuda_version.py
+        language: python
+        additional_dependencies: [pyyaml==6.0.3]
+        files: '^(ci/versions\.yml|cuda_bindings/pixi\.toml|cuda_core/pixi\.toml)$'
+        pass_filenames: false
+
+      - id: check-mempool-hygiene
+        name: Check tests do not create uncapped memory pools
+        entry: python ./ci/tools/check_mempool_hygiene.py
+        language: python
+        files: '^cuda_core/tests/.*\.py$'
+
       - id: no-markdown-in-docs-source
         name: Prevent markdown files in docs/source directories
         entry: bash -c
@@ -61,13 +83,13 @@ repos:
 
       - id: stubgen-pyx-cuda-core
         name: Generate .pyi stubs for cuda_core
-        entry: stubgen-pyx cuda_core/cuda --continue-on-error --include-private
+        entry: python -X utf8 -m stubgen_pyx cuda_core/cuda --continue-on-error --include-private
         language: python
         files: ^cuda_core/cuda/.*\.(pyx|pxd)$
         pass_filenames: false
         additional_dependencies:
-          - stubgen-pyx==0.2.6
-          - Cython==3.2.4
+          - stubgen-pyx==0.2.22
+          - Cython==3.2.9
 
   # Link checking for authored documentation files
   - repo: https://github.com/lycheeverse/lychee
@@ -75,6 +97,7 @@ repos:
     hooks:
       - id: lychee
         args:
+          - LYCHEE_VERSION=0.24.2  # Must match the pinned rev above
           - --cache
           - --max-concurrency=4
           - --max-retries=3
@@ -96,7 +119,7 @@ repos:
     - id: check-yaml
     - id: debug-statements
     - id: end-of-file-fixer
-      exclude: &gen_exclude '^(?:cuda_python/README\.md|cuda_bindings/cuda/bindings/.*\.in?|cuda_bindings/docs/source/module/.*\.rst?|.*\.pyi)$'
+      exclude: &gen_exclude '^(?:cuda_python/README\.md|(?:.*/)?CLAUDE\.md|(?:.*/)?\.git_archival\.txt|cuda_bindings/cuda/bindings/.*\.in?|cuda_bindings/docs/source/module/.*\.rst?|.*\.pyi)$'
     - id: mixed-line-ending
     - id: trailing-whitespace
       exclude: |
@@ -146,6 +169,8 @@ repos:
       - id: cython-lint
         args: [--no-pycodestyle]
         exclude: ^cuda_bindings/
+        additional_dependencies:
+          - Cython==3.2.9
 
 
 default_language_version:
diff --git a/AGENTS.md b/AGENTS.md
index e66437159b0..05f4d9b780d 100644
--- a/AGENTS.md
+++ b/AGENTS.md
@@ -14,26 +14,30 @@ guide for package-specific conventions and workflows.
 
 # Pull requests
 
-**Never push branches or commits to the upstream repo (github.com/NVIDIA/cuda-python).
-Treat it as read-only.** All branch creation and pushes must go to the contributor's
-personal fork. Before pushing, confirm which remote points to the contributor's
-personal fork (not `upstream`) by running `git remote -v`, then push there
-(`git push <personal-fork-remote> <branch>`). Open the PR from that fork with
-`gh pr create`. Do not use `git push upstream` or any command that writes to
-the `upstream` remote.
-
-When creating pull requests with `gh pr create`, always assign at least one
-label and a milestone. CI enforces this via the `pr-metadata-check` workflow
-and will block PRs that are missing labels or a milestone. Use `--label` and
-`--milestone` flags, for example:
-
-```
-gh pr create --title "..." --body "..." --label "bug" --milestone "v1.0"
-```
-
-If you are unsure which label or milestone to use, check the existing labels
-and milestones on the repository with `gh label list` and `gh api
-repos/{owner}/{repo}/milestones --jq '.[].title'`, and pick the best match.
+Treat the canonical upstream repository as read-only by default. For normal
+pull-request work, push branches and commits to an approved fork associated
+with the contributor. The fork may be owned by the contributor's personal
+account or by an organization.
+
+Before any push, run `git remote -v` and verify the complete
+`OWNER/REPOSITORY` of the intended destination. For normal pull-request work,
+confirm that the destination is a fork of the pull-request base. Do not rely
+on remote names such as `origin` or `upstream`, or on the owner alone.
+
+An upstream push is allowed when the user explicitly requests it and provides
+a rationale for why the upstream repository is needed, such as testing
+`.github/workflows`, triggering CI from a designated upstream ref, or other
+infrastructure work.
+
+For an authorized upstream push, verify the exact source and destination refs
+against the user's request. If the repository and refspec are unambiguous,
+proceed; do not require the user to perform the push manually solely because
+the destination is upstream.
+
+Authorization is limited to the requested ref update. It does not authorize
+pushing to a default or protected branch, force-pushing, creating tags, or
+deleting refs unless the user separately and explicitly requests those
+operations.
 
 
 # General
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 012126cc842..d6810495dee 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -19,8 +19,13 @@ Thank you for your interest in contributing to CUDA Python! Based on the type of
 
 - [Contributing to CUDA Python](#contributing-to-cuda-python)
   - [Table of Contents](#table-of-contents)
+  - [Cloning the repository](#cloning-the-repository)
+    - [Recommended clone](#recommended-clone)
+    - [Fixing an existing clone](#fixing-an-existing-clone)
+    - [Symptoms of a bad clone](#symptoms-of-a-bad-clone)
   - [Type stubs for cuda.core](#type-stubs-for-cudacore)
   - [Pre-commit](#pre-commit)
+    - [Pre-commit on Windows](#pre-commit-on-windows)
   - [Signing Your Work](#signing-your-work)
   - [Code signing](#code-signing)
   - [Developer Certificate of Origin (DCO)](#developer-certificate-of-origin-dco)
@@ -34,6 +39,94 @@ Thank you for your interest in contributing to CUDA Python! Based on the type of
   - [Code coverage](#code-coverage)
 
 
+## Cloning the repository
+
+Every package in this repository derives its version from git tags using
+[`setuptools-scm`](https://setuptools-scm.readthedocs.io/), so **how you clone
+determines whether you can build at all, and whether the version you build is
+correct.** Each package matches its own tag prefix:
+
+| Package | Tag pattern |
+| --- | --- |
+| `cuda-bindings`, `cuda-python` | `v*` (e.g. `v13.4.1`) |
+| `cuda-core` | `cuda-core-v*` (e.g. `cuda-core-v1.1.0`) |
+| `cuda-pathfinder` | `cuda-pathfinder-v*` (e.g. `cuda-pathfinder-v1.6.0`) |
+
+Each package sets `root = ".."` in its `[tool.setuptools_scm]` table, meaning the
+version is read from the *repository root* rather than the package directory. A
+working build therefore needs all of the following:
+
+1. **A real git clone.** Source zips and GitHub "Download ZIP" archives have no
+   git metadata and the build fails outright. (Tarballs produced by
+   `git archive` do work, thanks to the `.git_archival.txt` substitutions
+   configured in `.gitattributes`.)
+2. **The full repository**, not just the package subdirectory, because the
+   version lookup walks up to the repository root.
+3. **Tags, reaching back at least as far as the most recent tag** matching the
+   package you are building. `git describe` needs to find that tag; the history
+   between it and your checkout must be present too.
+
+### Recommended clone
+
+The default `git clone` gives you everything you need:
+
+```console
+$ git clone https://github.com/NVIDIA/cuda-python.git
+```
+
+
+
+### Fixing an existing clone
+
+If you already have a shallow clone:
+
+```console
+$ git fetch --unshallow --tags
+```
+
+If you are working from a personal fork, your fork's tags stop tracking upstream
+the moment new releases are cut, which silently yields a stale version. Fetch
+tags from upstream directly:
+
+```console
+$ git remote add upstream https://github.com/NVIDIA/cuda-python.git
+$ git fetch --tags upstream
+```
+
+Keep doing this periodically — a fork that was correct when you created it will
+drift.
+
+### Symptoms of a bad clone
+
+Only case 3 below reports an error. The first two fail *silently*, producing a
+wrong version that surfaces much later as a confusing dependency-resolution or
+version-check failure:
+
+1. **No tags reachable.** The build succeeds and produces a version starting at
+   `0.1.dev`: a `--depth 1` clone yields `0.1.dev1+g0d22cb444`, a full clone made
+   with `--no-tags` yields `0.1.dev2114+g0d22cb444`. Installing `cuda-python`
+   built this way then fails, because its `install_requires` pins
+   `cuda-bindings` to that same bogus version.
+2. **Stale tags** (a fork that has not fetched upstream in a while): you get a
+   plausible-looking but wrong version, e.g. `13.0.4.dev650+g0d22cb44` when the
+   real latest tag is `v13.4.1`. Nothing warns you. Note there is no leading
+   `v` — the tag prefix is stripped by `tag_regex`.
+3. **No git metadata** (source zip): the build fails with
+   `LookupError: setuptools-scm was unable to detect version`.
+
+As a last resort — for example when building inside a container that has no git
+history — you can bypass the lookup entirely:
+
+```console
+$ SETUPTOOLS_SCM_PRETEND_VERSION_FOR_CUDA_CORE=1.1.0 pip install ./cuda_core
+```
+
+The environment variable is suffixed with the distribution name, uppercased with
+hyphens replaced by underscores: `..._FOR_CUDA_BINDINGS`, `..._FOR_CUDA_CORE`,
+`..._FOR_CUDA_PATHFINDER`, `..._FOR_CUDA_PYTHON`. Use this only when you
+genuinely cannot provide tags; it is not a substitute for a correct clone.
+
+
 ## Type stubs for cuda.core
 
 `cuda.core` is a PEP 561-compliant package: it ships a `py.typed` marker and
@@ -74,6 +167,22 @@ between commits, leaving stale headers or out-of-date stubs in the history.
 If the hook isn't installed, `pre-commit run` (and CI) will print a visible
 warning reminding you to run `pre-commit install`.
 
+### Pre-commit on Windows
+
+For development on Windows (not WSL), the `lychee` pre-commit task will not work
+when running `pre-commit run --all-files`.  This problem does not occur if you
+install the pre-commit hook and run it automatically as part of your `git
+commit` workflow.  To resolve this, you can either:
+
+1. Run `pre-commit` in Git Bash, rather than directly in PowerShell or cmd
+
+2. Skip it by setting the environment variable `SKIP` to `lychee`.  This would
+   be `$env:SKIP = "lychee"` in PowerShell or `set SKIP=lychee` in cmd.
+
+## Secret Scanning
+
+The `secret-scan-trufflehog` pre-commit hook scans staged files and installs TruffleHog into its own environment on first run, on Linux, macOS, and Windows. If it flags a secret, remove it before committing, or contact a maintainer if it's a false positive. Secrets are also scanned server-side in CI.
+
 
 ## Signing Your Work
 
diff --git a/LICENSE b/LICENSE
index d6f74778be8..f3fe76ecadf 100644
--- a/LICENSE
+++ b/LICENSE
@@ -176,3 +176,28 @@ Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
       of your accepting any such warranty or additional liability.
 
    END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
diff --git a/README.md b/README.md
index 782f04269ad..9c2955f6b7e 100644
--- a/README.md
+++ b/README.md
@@ -10,7 +10,7 @@ CUDA Python is the home for accessing NVIDIA’s CUDA platform from Python. It c
 * [numba.cuda](https://nvidia.github.io/numba-cuda/): A Python DSL that exposes CUDA **SIMT** programming model and compiles a restricted subset of Python code into CUDA kernels and device functions
 * [cuda.tile](https://docs.nvidia.com/cuda/cutile-python/): A new Python DSL that exposes CUDA **Tile** programming model and allows users to write NumPy-like code in CUDA kernels
 * [nvmath-python](https://docs.nvidia.com/cuda/nvmath-python/latest): Pythonic access to NVIDIA CPU & GPU Math Libraries, with [*host*](https://docs.nvidia.com/cuda/nvmath-python/latest/overview.html#host-apis), [*device*](https://docs.nvidia.com/cuda/nvmath-python/latest/overview.html#device-apis), and [*distributed*](https://docs.nvidia.com/cuda/nvmath-python/latest/distributed-apis/index.html) APIs. It also provides low-level Python bindings to host C APIs ([nvmath.bindings](https://docs.nvidia.com/cuda/nvmath-python/latest/bindings/index.html)).
-* [nvshmem4py](https://docs.nvidia.com/nvshmem/api/api/language_bindings/python/index.html): Pythonic interface to the NVSHMEM library, enabling Python applications to leverage NVSHMEM's high-performance PGAS (Partitioned Global Address Space) programming model for GPU-accelerated computing
+* [nvshmem4py](https://docs.nvidia.com/nvshmem/api/latest/api/language_bindings/python/index.html): Pythonic interface to the NVSHMEM library, enabling Python applications to leverage NVSHMEM's high-performance PGAS (Partitioned Global Address Space) programming model for GPU-accelerated computing
 * [Nsight Python](https://docs.nvidia.com/nsight-python/index.html): Python kernel profiling interface that automates performance analysis across multiple kernel configurations using NVIDIA Nsight Tools
 * [CUPTI Python](https://docs.nvidia.com/cupti-python/): Python APIs for creation of profiling tools that target CUDA Python applications via the CUDA Profiling Tools Interface (CUPTI)
 * [Accelerated Computing Hub](https://github.com/NVIDIA/accelerated-computing-hub): Open-source learning materials related to GPU computing. You will find user guides, tutorials, and other works freely available for all learners interested in GPU computing.
@@ -52,3 +52,14 @@ The list of available interfaces is:
 
 CUDA Python is licensed under the [Apache License 2.0](./LICENSE). Third-party
 attributions for `cuda.core` are listed in [`cuda_core/NOTICE`](./cuda_core/NOTICE).
+
+Each subproject is distributed as its own package and ships a copy of the same
+license alongside its sources, so that the license accompanies the built wheel.
+The root `LICENSE` governs the repository as a whole:
+
+| Subproject       | License    | License file                                             |
+| ---------------- | ---------- | -------------------------------------------------------- |
+| `cuda.bindings`  | Apache-2.0 | [`cuda_bindings/LICENSE`](./cuda_bindings/LICENSE)       |
+| `cuda.core`      | Apache-2.0 | [`cuda_core/LICENSE`](./cuda_core/LICENSE)               |
+| `cuda.pathfinder`| Apache-2.0 | [`cuda_pathfinder/LICENSE`](./cuda_pathfinder/LICENSE)   |
+| `cuda-python`    | Apache-2.0 | [`cuda_python/LICENSE`](./cuda_python/LICENSE)           |
diff --git a/benchmarks/cuda_bindings/runner/main.py b/benchmarks/cuda_bindings/runner/main.py
index 9c984c340d6..eb2bcdacaf0 100644
--- a/benchmarks/cuda_bindings/runner/main.py
+++ b/benchmarks/cuda_bindings/runner/main.py
@@ -232,11 +232,18 @@ def parse_args(argv: list[str], default_output: Path = DEFAULT_OUTPUT) -> tuple[
 
 def main(
     *,
-    bench_dir: Path = BENCH_DIR,
-    default_output: Path = DEFAULT_OUTPUT,
+    bench_dir: Path | None = None,
+    default_output: Path | None = None,
     module_name_prefix: str = DEFAULT_MODULE_NAME_PREFIX,
     bench_filter_env_var: str = DEFAULT_BENCH_FILTER_ENV_VAR,
 ) -> None:
+    # Resolve the defaults inside the call, for the same reason
+    # discover_benchmarks() does: a literal default would be bound at def-time
+    # and would ignore a later monkeypatch of the module-level constant.
+    if bench_dir is None:
+        bench_dir = BENCH_DIR
+    if default_output is None:
+        default_output = DEFAULT_OUTPUT
     parsed, remaining_argv = parse_args(sys.argv[1:], default_output=default_output)
 
     registry = discover_benchmarks(bench_dir=bench_dir, module_name_prefix=module_name_prefix)
diff --git a/benchmarks/cuda_bindings/tests/test_runner.py b/benchmarks/cuda_bindings/tests/test_runner.py
index 56d88444c9e..836653522a1 100644
--- a/benchmarks/cuda_bindings/tests/test_runner.py
+++ b/benchmarks/cuda_bindings/tests/test_runner.py
@@ -164,3 +164,24 @@ def test_bench_launch_initializes_on_first_use(monkeypatch):
 
     assert len(compile_calls) == 1
     assert len(launch_calls) == 2
+
+
+def test_main_honors_a_monkeypatched_bench_dir(monkeypatch, tmp_path, capsys):
+    """main() must resolve BENCH_DIR at call time, like discover_benchmarks() does.
+
+    A literal default would be bound at def-time and would silently ignore a
+    later patch of the module-level constant.
+    """
+    runner_main = load_runner_main(monkeypatch)
+
+    (tmp_path / "bench_patched.py").write_text(
+        "def bench_only_here(loops: int) -> float:\n    return loops + 0.5\n",
+        encoding="utf-8",
+    )
+    monkeypatch.setattr(runner_main, "BENCH_DIR", tmp_path)
+    runner_main._MODULE_CACHE.clear()
+    monkeypatch.setattr(sys, "argv", ["run_pyperf.py", "--list"])
+
+    runner_main.main()
+
+    assert capsys.readouterr().out.split() == ["patched.only_here"]
diff --git a/ci/README.md b/ci/README.md
new file mode 100644
index 00000000000..7a36fce9e29
--- /dev/null
+++ b/ci/README.md
@@ -0,0 +1,24 @@
+# Continuous Integration
+
+## Repository Customizations
+
+The workflows in this repository use the `CI_CUSTOMIZATIONS_*` namespace for
+GitHub Actions configuration variables that opt an alternative synchronized
+repository into repository-specific CI behavior. This keeps the workflow logic
+shared without hard-coding the names of private repositories into the public
+source tree.
+
+These variables are non-secret strings configured under
+**Settings > Secrets and variables > Actions > Variables**.
+An unset variable, or any value other than the literal string `true`, leaves
+the customization disabled. Do not store credentials or other secret values in
+these variables.
+
+| Variable | Default | Purpose |
+| --- | --- | --- |
+| `CI_CUSTOMIZATIONS_SECURITY_SUITE_ENABLED` | Disabled | Enables the NVIDIA Security Suite after its runner, Actions variables, and OIDC/Vault authorization have been provisioned for the repository. |
+
+The canonical `NVIDIA/cuda-python` repository does not need this variable
+because its standard workflow behavior is enabled directly. Before enabling a
+customization elsewhere, document the repository-specific prerequisites and
+verification procedure in that repository's own documentation.
diff --git a/ci/test-matrix.yml b/ci/test-matrix.yml
index 8e88525d0f7..7d6733084f6 100644
--- a/ci/test-matrix.yml
+++ b/ci/test-matrix.yml
@@ -32,57 +32,63 @@
 #           ENV: { CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM: '1' }
 #           ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu126' }
 
+# Host platforms that produce wheel artifacts in the main CI workflow.
+platforms:
+  - linux-64
+  - linux-aarch64
+  - win-64
+
 linux:
   pull-request:
     # linux-64
     - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'v100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     # disabled: compute-sanitizer install broken on CUDA 12.9.1 local CTK (TODO: re-enable once fixed)
     # - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest', ENV: { CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM: '1' } }
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'v100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: '610.43.02' }
+    - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: '610.43.02' }
     - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 't4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: '610.43.02' }
+    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: '610.43.02' }
     - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 't4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.15',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.15t', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.15',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.15t', CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     # linux-aarch64
     - { ARCH: 'arm64', PY_VER: '3.10',  CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.10',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'arm64', PY_VER: '3.10',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'arm64', PY_VER: '3.10',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.11',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.11',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'arm64', PY_VER: '3.11',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'arm64', PY_VER: '3.11',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     # disabled: compute-sanitizer install broken on CUDA 12.9.1 local CTK (TODO: re-enable once fixed)
     # - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.13',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.13',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'arm64', PY_VER: '3.13',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'arm64', PY_VER: '3.13',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     - { ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest' }
     # special runners
     - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'h100',       GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'h100',       GPU_COUNT: '1', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 't4',         GPU_COUNT: '2', DRIVER: 'latest' }
-    - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'h100',       GPU_COUNT: '2', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'h100',       GPU_COUNT: '1', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 't4',         GPU_COUNT: '2', DRIVER: 'latest' }
+    - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'h100',       GPU_COUNT: '2', DRIVER: 'latest' }
     - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 't4',         GPU_COUNT: '1', DRIVER: 'latest', FLAVOR: 'wsl' }
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'rtx4090',    GPU_COUNT: '1', DRIVER: 'latest', FLAVOR: 'wsl' }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'rtx4090',    GPU_COUNT: '1', DRIVER: 'latest', FLAVOR: 'wsl' }
   nightly:
     # nightly-pytorch
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu126' } }
@@ -95,44 +101,45 @@ linux:
     - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1',  TORCH_CUDA: 'cu130' } }
     # nightly-numba-cuda
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-numba-cuda' } }
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: '580.65.06',  ENV: { MODE: 'nightly-numba-cuda' } }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: '580.65.06',  ENV: { MODE: 'nightly-numba-cuda' } }
     - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-numba-cuda' } }
-    - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-numba-cuda' } }
+    - { ARCH: 'arm64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-numba-cuda' } }
     # nightly-numba-cuda-mlir (MLIR backend, linux-64 only)
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-numba-cuda-mlir' } }
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-numba-cuda-mlir' } }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-numba-cuda-mlir' } }
     # nightly-cuda-core (released cuda-core from PyPI against main pathfinder/bindings)
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-cuda-core' } }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-cuda-core' } }
     # nightly-standard (arm64 nightly-only runners — per runner team request)
-    - { ARCH: 'arm64', PY_VER: '3.13',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'gh200',      GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
-    - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'gb300',      GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
-    - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '2', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
-    - { ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '2', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
+    - { ARCH: 'arm64', PY_VER: '3.13',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'gh200',      GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
+    - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'gb300',      GPU_COUNT: '1', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
+    - { ARCH: 'arm64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '2', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
+    - { ARCH: 'arm64', PY_VER: '3.14t', CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '2', DRIVER: 'latest',     ENV: { MODE: 'nightly-standard' } }
 
 windows:
   pull-request:
     # win-64
     - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'rtx2080',    GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'WDDM' }
     - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
-    - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
+    - { ARCH: 'amd64', PY_VER: '3.10',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
     - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'v100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
     - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'rtx4090',    GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'WDDM' }
-    - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'rtx4090',    GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'WDDM' }
+    - { ARCH: 'amd64', PY_VER: '3.11',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'rtx4090',    GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'WDDM' }
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
     - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
     - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
-    - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM', ENV: { CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM: '1' } }
+    - { ARCH: 'amd64', PY_VER: '3.13',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM', ENV: { CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM: '1' } }
     - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'v100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
     - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.0.2', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
-    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
+    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
     - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '12.9.1', LOCAL_CTK: '1', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
     - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
-    - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
+    - { ARCH: 'amd64', PY_VER: '3.14t', CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
+    - { ARCH: 'amd64', PY_VER: '3.15',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
     # special runners
-    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '1', GPU: 't4',         GPU_COUNT: '2', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
-    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'h100',       GPU_COUNT: '2', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
+    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '1', GPU: 't4',         GPU_COUNT: '2', DRIVER: 'latest',  DRIVER_MODE: 'TCC' }
+    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'h100',       GPU_COUNT: '2', DRIVER: 'latest',  DRIVER_MODE: 'MCDM' }
   nightly:
     # nightly-pytorch
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.6.3', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC',  ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.12.1', TORCH_CUDA: 'cu126' } }
@@ -141,9 +148,9 @@ windows:
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.0.2', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC',  ENV: { MODE: 'nightly-pytorch', TORCH_VER: '2.9.1',  TORCH_CUDA: 'cu130' } }
     # nightly-numba-cuda
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'TCC',  ENV: { MODE: 'nightly-numba-cuda' } }
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: '596.36',  DRIVER_MODE: 'TCC',  ENV: { MODE: 'nightly-numba-cuda' } }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'l4',         GPU_COUNT: '1', DRIVER: '596.36',  DRIVER_MODE: 'TCC',  ENV: { MODE: 'nightly-numba-cuda' } }
     # nightly-numba-cuda-mlir (MLIR backend, win-64)
     - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '12.9.1', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM', ENV: { MODE: 'nightly-numba-cuda-mlir' } }
-    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM', ENV: { MODE: 'nightly-numba-cuda-mlir' } }
+    - { ARCH: 'amd64', PY_VER: '3.12',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'rtxpro6000', GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM', ENV: { MODE: 'nightly-numba-cuda-mlir' } }
     # nightly-cuda-core (released cuda-core from PyPI against main pathfinder/bindings)
-    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.3.0', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM', ENV: { MODE: 'nightly-cuda-core' } }
+    - { ARCH: 'amd64', PY_VER: '3.14',  CUDA_VER: '13.4.1', LOCAL_CTK: '0', GPU: 'a100',       GPU_COUNT: '1', DRIVER: 'latest',  DRIVER_MODE: 'MCDM', ENV: { MODE: 'nightly-cuda-core' } }
diff --git a/ci/tools/check_mempool_hygiene.py b/ci/tools/check_mempool_hygiene.py
new file mode 100644
index 00000000000..b200aba1ebb
--- /dev/null
+++ b/ci/tools/check_mempool_hygiene.py
@@ -0,0 +1,113 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Check that tests do not create uncapped CUDA memory pools.
+
+A pool created without ``max_size`` reserves an address-space window sized from
+installed device memory rather than from what the test allocates, and the whole
+cuda_core suite shares one process. Enough of those reservations exhaust the
+address space, after which the rest of the session fails with
+CUDA_ERROR_OUT_OF_MEMORY on a device with free physical memory.
+
+See cuda_core/tests/AGENTS.md for the rule this enforces.
+"""
+
+from __future__ import annotations
+
+import argparse
+import ast
+import sys
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[2]
+DEFAULT_TREE = ROOT / "cuda_core" / "tests"
+
+# Managed pools cannot be right-sized: cuMemPoolCreate requires maxSize == 0 for
+# managed pools, so ManagedMemoryResourceOptions has no max_size to set.
+CAPPABLE_OPTIONS = frozenset({"DeviceMemoryResourceOptions", "PinnedMemoryResourceOptions"})
+CAPPABLE_RESOURCES = frozenset({"DeviceMemoryResource", "PinnedMemoryResource"})
+
+OPT_OUT_MARKER = "uncapped-pool-ok"
+
+
+def _callee_name(node: ast.Call) -> str:
+    func = node.func
+    if isinstance(func, ast.Attribute):
+        return func.attr
+    if isinstance(func, ast.Name):
+        return func.id
+    return ""
+
+
+def _is_capped(node: ast.Call) -> bool:
+    # ``**kwargs`` (arg is None) may carry max_size; do not guess.
+    return any(kw.arg is None or kw.arg == "max_size" for kw in node.keywords)
+
+
+def _dict_is_capped(node: ast.Dict) -> bool:
+    for key in node.keys:
+        if key is None:  # ``**other`` inside the literal
+            return True
+        if isinstance(key, ast.Constant) and key.value == "max_size":
+            return True
+    return False
+
+
+def _opted_out(lines: list[str], node: ast.AST) -> bool:
+    """True if the call, or the line above it, carries the opt-out marker."""
+    start = max(node.lineno - 2, 0)  # -1 for 0-based, -1 more for a preceding comment
+    end = getattr(node, "end_lineno", node.lineno)
+    return any(OPT_OUT_MARKER in line for line in lines[start:end])
+
+
+def violations_in(path: Path) -> list[str]:
+    """Return one message per uncapped pool construction in ``path``."""
+    source = path.read_text(encoding="utf-8")
+    lines = source.splitlines()
+    found = []
+    for node in ast.walk(ast.parse(source, filename=str(path))):
+        if not isinstance(node, ast.Call):
+            continue
+        name = _callee_name(node)
+        if name in CAPPABLE_OPTIONS:
+            uncapped = not _is_capped(node)
+        elif name in CAPPABLE_RESOURCES:
+            # The options may also be given as a dict literal.
+            dicts = [arg for arg in [*node.args, *(kw.value for kw in node.keywords)] if isinstance(arg, ast.Dict)]
+            uncapped = any(not _dict_is_capped(d) for d in dicts)
+        else:
+            continue
+        if uncapped and not _opted_out(lines, node):
+            found.append(f"{path.as_posix()}:{node.lineno}: {name} without max_size")
+    return found
+
+
+def main(argv: list[str] | None = None) -> int:
+    parser = argparse.ArgumentParser(description=__doc__)
+    parser.add_argument(
+        "paths",
+        nargs="*",
+        type=Path,
+        help=f"Files to check. Defaults to every .py under {DEFAULT_TREE.relative_to(ROOT).as_posix()}.",
+    )
+    args = parser.parse_args(argv)
+
+    paths = args.paths or sorted(DEFAULT_TREE.rglob("*.py"))
+    violations = sorted(v for path in paths if path.suffix == ".py" for v in violations_in(path))
+    if not violations:
+        return 0
+
+    print("error: memory pools created by tests must set max_size:", file=sys.stderr)
+    for violation in violations:
+        print(f"  - {violation}", file=sys.stderr)
+    print(
+        f"Use the suite-wide POOL_SIZE from cuda_core/tests/helpers/constants.py, or annotate a\n"
+        f"deliberate exception with a '# {OPT_OUT_MARKER}: <reason>' comment.\n"
+        f"See cuda_core/tests/AGENTS.md.",
+        file=sys.stderr,
+    )
+    return 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/ci/tools/check_pixi_cuda_version.py b/ci/tools/check_pixi_cuda_version.py
new file mode 100644
index 00000000000..1ca931b9b48
--- /dev/null
+++ b/ci/tools/check_pixi_cuda_version.py
@@ -0,0 +1,91 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Check pixi cuda-version pins track ci/versions.yml (cuda.build.version)."""
+
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import tomllib
+import yaml
+
+ROOT = Path(__file__).resolve().parents[2]
+VERSIONS_FILE_PATH = ROOT / "ci" / "versions.yml"
+PIXI_FILES = [ROOT / d / "pixi.toml" for d in ("cuda_bindings", "cuda_core")]
+
+
+def main() -> int:
+    """Verify cuda_bindings/cuda_core pixi pins match ci/versions.yml."""
+    if not VERSIONS_FILE_PATH.is_file():
+        print(f"error: {VERSIONS_FILE_PATH} not found", file=sys.stderr)
+        return 2
+    try:
+        build_version = yaml.safe_load(VERSIONS_FILE_PATH.read_text(encoding="utf-8"))["cuda"]["build"]["version"]
+    except (KeyError, TypeError):
+        print(f"error: cuda.build.version not found in {VERSIONS_FILE_PATH}", file=sys.stderr)
+        return 2
+
+    major, minor, *_ = build_version.split(".")
+    expected = f"{major}.{minor}.*"
+    cuda_feature = f"cu{major}"
+
+    errors: list[str] = []
+    checked: list[str] = []
+    for path in PIXI_FILES:
+        if not path.is_file():
+            print(f"error: {path} not found", file=sys.stderr)
+            return 2
+        with path.open("rb") as f:
+            data = tomllib.load(f)
+        rel = path.relative_to(ROOT)
+        try:
+            variants = data["workspace"]["build-variants"]["cuda-version"]
+            cuda_pin = data["feature"][cuda_feature]["dependencies"]["cuda-version"]
+        except KeyError as exc:
+            print(
+                f"error: {rel} missing feature {cuda_feature!r} or cuda-version key: {exc}",
+                file=sys.stderr,
+            )
+            return 2
+        if expected not in variants:
+            errors.append(
+                f"{rel}: workspace.build-variants.cuda-version={variants!r} "
+                f"does not include {expected!r} "
+                f"(from ci/versions.yml cuda.build.version={build_version!r})"
+            )
+        if cuda_pin != expected:
+            errors.append(
+                f"{rel}: feature.{cuda_feature}.dependencies.cuda-version={cuda_pin!r} "
+                f"!= {expected!r} "
+                f"(from ci/versions.yml cuda.build.version={build_version!r})"
+            )
+
+        checked.append(
+            f"{rel} (workspace.build-variants.cuda-version={variants!r}, "
+            f"feature.{cuda_feature}.dependencies.cuda-version={cuda_pin!r})"
+        )
+
+    if errors:
+        print(
+            f"error: cuda_bindings/cuda_core pixi cuda-version pins out of sync with "
+            f"ci/versions.yml cuda.build.version={build_version!r} "
+            f"(expected pin {expected!r}):",
+            file=sys.stderr,
+        )
+        for err in errors:
+            print(f"  - {err}", file=sys.stderr)
+        return 1
+
+    print(
+        f"OK: pixi cuda-version pins match ci/versions.yml "
+        f"cuda.build.version={build_version!r} (expected pin {expected!r}):"
+    )
+    for item in checked:
+        print(f"  - {item}")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/ci/tools/check_release_notes.py b/ci/tools/check_release_notes.py
index 75d2c9871f0..1c99ddb019a 100644
--- a/ci/tools/check_release_notes.py
+++ b/ci/tools/check_release_notes.py
@@ -18,6 +18,7 @@
 import os
 import re
 import sys
+from pathlib import Path
 
 COMPONENT_TO_PACKAGE: dict[str, str] = {
     "cuda-core": "cuda_core",
@@ -62,8 +63,8 @@ def is_post_release(version: str) -> bool:
     return ".post" in version
 
 
-def load_backport_branch(repo_root: str = ".") -> str | None:
-    path = os.path.join(repo_root, "ci", "versions.yml")
+def load_backport_branch(repo_root: Path = Path(".")) -> str | None:
+    path = repo_root / "ci" / "versions.yml"
     try:
         with open(path, encoding="utf-8") as f:
             for line in f:
@@ -84,13 +85,16 @@ def is_backport_version(version: str, backport_branch: str) -> bool:
     return version == backport_branch
 
 
-def notes_path(package: str, version: str) -> str:
-    return os.path.join(package, "docs", "source", "release", f"{version}-notes.rst")
+def notes_path(package: str, version: str) -> Path:
+    return Path(package, "docs", "source", "release", f"{version}-notes.rst")
 
 
-def check_release_notes(git_tag: str, component: str, repo_root: str = ".") -> list[tuple[str, str]]:
+def check_release_notes(git_tag: str, component: str, repo_root: Path = Path(".")) -> list[tuple[str | Path, str]]:
     """Return a list of (path, reason) for missing or empty release notes.
 
+    ``path`` is the repo-relative notes path, or a ``<placeholder>`` naming the
+    offending argument when the tag or component itself is the problem.
+
     Returns an empty list when notes are present and non-empty, or when the
     tag is a .post release (no new notes required).
     """
@@ -105,10 +109,10 @@ def check_release_notes(git_tag: str, component: str, repo_root: str = ".") -> l
         return []
 
     path = notes_path(COMPONENT_TO_PACKAGE[component], version)
-    full = os.path.join(repo_root, path)
-    if not os.path.isfile(full):
+    full = repo_root / path
+    if not full.is_file():
         return [(path, "missing")]
-    if os.path.getsize(full) == 0:
+    if full.stat().st_size == 0:
         return [(path, "empty")]
     return []
 
@@ -123,7 +127,7 @@ def write_step_summary(message: str) -> None:
             f.write("\n")
 
 
-def warn_missing_backport_notes(git_tag: str, component: str, problems: list[tuple[str, str]]) -> None:
+def warn_missing_backport_notes(git_tag: str, component: str, problems: list[tuple[str | Path, str]]) -> None:
     print(f"WARNING: missing or empty release notes for backport tag {git_tag}:")
     summary_lines = [
         "## Release Notes Reminder",
@@ -147,8 +151,8 @@ def validate_backport_decision(
     version: str,
     backport_git_tag: str,
     backport_branch: str | None,
-    repo_root: str,
-) -> tuple[int | None, list[tuple[str, str]]]:
+    repo_root: Path,
+) -> tuple[int | None, list[tuple[str | Path, str]]]:
     if component not in BACKPORT_PLANNING_COMPONENTS or is_post_release(version):
         return None, []
 
@@ -205,7 +209,7 @@ def main(argv: list[str] | None = None) -> int:
     parser = argparse.ArgumentParser(description=__doc__)
     parser.add_argument("--git-tag", required=True)
     parser.add_argument("--component", required=True, choices=list(COMPONENT_TO_PACKAGE))
-    parser.add_argument("--repo-root", default=".")
+    parser.add_argument("--repo-root", default=Path("."), type=Path)
     parser.add_argument("--backport-git-tag", default="")
     parser.add_argument("--backport-branch", default="")
     args = parser.parse_args(argv)
diff --git a/ci/tools/compute_ci_plan.py b/ci/tools/compute_ci_plan.py
new file mode 100644
index 00000000000..9f94c67173d
--- /dev/null
+++ b/ci/tools/compute_ci_plan.py
@@ -0,0 +1,213 @@
+#!/usr/bin/env python3
+
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""Compute the CI build and test workplan for a pull request."""
+
+from __future__ import annotations
+
+import argparse
+import json
+import subprocess
+from pathlib import Path, PurePosixPath
+
+REPO_ROOT = Path(__file__).resolve().parents[2]
+MODULES = ("pathfinder", "bindings", "core", "python")
+PLATFORMS = ("linux", "windows")
+PACKAGE_MODULES = {f"cuda_{module}": module for module in MODULES}
+
+# Source changes have different build and test consumers. In particular,
+# cuda-python source needs a same-version bindings wheel, while a core-only
+# change can reuse the baseline cuda-python wheel.
+SOURCE_IMPACT = {
+    "pathfinder": (set(MODULES), set(MODULES)),
+    "bindings": ({"bindings", "core", "python"}, {"bindings", "core", "python"}),
+    "core": ({"core"}, {"core", "python"}),
+    "python": ({"bindings", "python"}, {"python"}),
+}
+
+IGNORED_BASENAMES = {"AGENTS.md", "CLAUDE.md", "pixi.lock", "pixi.toml"}
+IGNORED_SUFFIXES = {".md", ".svg"}
+IGNORED_PATHS = {
+    ".coveragerc",
+    ".gitignore",
+    ".pre-commit-config.yaml",
+    ".spdx-ignore",
+    "LICENSE",
+    "context7.json",
+    "greptile.json",
+    "ruff.toml",
+}
+IGNORED_PREFIXES = (".agents/", "toolshed/")
+
+# Only infrastructure exclusive to one OS belongs here; other CI paths force a full run.
+TEST_INFRA_PLATFORMS = {
+    ".github/workflows/test-wheel-linux.yml": "linux",
+    ".github/workflows/test-wheel-windows.yml": "windows",
+    "ci/tools/configure_driver_mode.ps1": "windows",
+    "ci/tools/guess_latest.sh": "linux",
+    "ci/tools/install_gpu_driver.ps1": "windows",
+    "ci/tools/install_gpu_driver.sh": "linux",
+    "ci/tools/setup-sanitizer": "linux",
+}
+
+
+def compute_workplan(
+    paths: list[str],
+    *,
+    merge_base: str,
+    baseline_run_id: str,
+    linked_paths: set[str] | None = None,
+) -> dict[str, object]:
+    """Return the final CI decisions for the supplied changed paths."""
+    linked_paths = linked_paths or set()
+    source_changes: set[str] = set()
+    test_changes: set[str] = set()
+    test_platforms: set[str] = set()
+    force_all = not merge_base or not baseline_run_id
+
+    if not force_all:
+        for path in paths:
+            path_parts = PurePosixPath(path).parts
+            if not path_parts:
+                continue
+
+            if platform := TEST_INFRA_PLATFORMS.get(path):
+                test_platforms.add(platform)
+                continue
+
+            if path_parts[0] == "ci" or (
+                len(path_parts) >= 2 and path_parts[:2] in {(".github", "actions"), (".github", "workflows")}
+            ):
+                force_all = True
+                break
+
+            if path_parts[0] == ".github" or path_parts[-1] in IGNORED_BASENAMES:
+                continue
+
+            module = PACKAGE_MODULES.get(path_parts[0])
+            if module is not None and len(path_parts) > 1:
+                relative = path_parts[1:]
+                if relative[0] == "docs":
+                    continue
+                if (
+                    any(part in {"test", "tests"} for part in relative[:-1])
+                    or relative[0] == "examples"
+                    or (module == "core" and relative == ("pytest.ini",))
+                ):
+                    test_changes.add(module)
+                elif PurePosixPath(path).suffix in IGNORED_SUFFIXES and path not in linked_paths:
+                    continue
+                else:
+                    source_changes.add(module)
+                continue
+
+            is_test_path = any(part in {"test", "tests"} for part in path_parts[:-1])
+            if is_test_path:
+                test_changes.update(MODULES)
+            elif (
+                path in IGNORED_PATHS
+                or PurePosixPath(path).suffix in IGNORED_SUFFIXES
+                or path.startswith(IGNORED_PREFIXES)
+            ):
+                continue
+            elif path_parts[0] in {"benchmarks", "cuda_python_test_helpers"}:
+                test_changes.update(MODULES)
+            else:
+                force_all = True
+                break
+
+    if force_all:
+        builds = set(MODULES)
+        tests = set(MODULES)
+        test_platforms = set(PLATFORMS)
+    else:
+        builds: set[str] = set()
+        tests = set(MODULES) if test_platforms else set(test_changes)
+        for module in source_changes:
+            build_impact, test_impact = SOURCE_IMPACT[module]
+            builds.update(build_impact)
+            tests.update(test_impact)
+        if source_changes or test_changes:
+            test_platforms.update(PLATFORMS)
+
+    modules = {
+        module: {
+            "needs_build": module in builds,
+            "needs_test": module in tests,
+        }
+        for module in MODULES
+    }
+    return {
+        "modules": modules,
+        "jobs": {
+            # These gates cover both optional artifact builds and wheel tests.
+            "platforms": {platform: platform in test_platforms for platform in PLATFORMS},
+            "sdist_tests": bool(builds),
+            "core_api_checks": force_all or "core" in source_changes,
+        },
+        "merge_base": merge_base,
+        "baseline": {
+            "run_id": baseline_run_id if not force_all else "",
+            "sha": merge_base if not force_all else "",
+        },
+    }
+
+
+def _git_output(*args: str) -> bytes:
+    return subprocess.check_output(  # noqa: S603 - argv is passed directly without a shell.
+        ["git", *args],  # noqa: S607
+        cwd=REPO_ROOT,
+    )
+
+
+def _changed_paths(merge_base: str) -> tuple[list[str], set[str]]:
+    output = _git_output("diff", "--no-renames", "--name-only", "-z", merge_base, "HEAD")
+    paths = [path.decode("utf-8", errors="surrogateescape") for path in output.split(b"\0") if path]
+    head_symlinks = _tracked_symlink_paths("HEAD")
+    # Base links preserve the packaging impact of deleted or replaced symlinks.
+    linked_paths = set(head_symlinks) | set(_tracked_symlink_paths(merge_base))
+    return _expand_linked_paths(paths, head_symlinks, root=REPO_ROOT), linked_paths
+
+
+def _tracked_symlink_paths(ref: str) -> list[str]:
+    output = _git_output("ls-tree", "--full-tree", "-r", "-z", ref)
+    return [
+        entry.partition(b"\t")[2].decode("utf-8", errors="surrogateescape")
+        for entry in output.split(b"\0")
+        if entry.startswith(b"120000 ")
+    ]
+
+
+def _expand_linked_paths(paths: list[str], symlink_paths: list[str], *, root: Path) -> list[str]:
+    """Include tracked symlinks whose resolved targets changed."""
+    resolved_paths = {(root / path).resolve(strict=False) for path in paths}
+    expanded = list(paths)
+    selected = set(paths)
+    expanded.extend(
+        path for path in symlink_paths if path not in selected and (root / path).resolve(strict=False) in resolved_paths
+    )
+    return expanded
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--merge-base", default="")
+    parser.add_argument("--baseline-run-id", default="")
+    args = parser.parse_args()
+
+    reusable_baseline = bool(args.merge_base and args.baseline_run_id)
+    paths, linked_paths = _changed_paths(args.merge_base) if reusable_baseline else ([], set())
+    plan = compute_workplan(
+        paths,
+        merge_base=args.merge_base,
+        baseline_run_id=args.baseline_run_id,
+        linked_paths=linked_paths,
+    )
+    print(json.dumps(plan, separators=(",", ":"), sort_keys=True))
+
+
+if __name__ == "__main__":
+    main()
diff --git a/ci/tools/env-vars b/ci/tools/env-vars
index 8ffbfa13472..118c7026ae3 100755
--- a/ci/tools/env-vars
+++ b/ci/tools/env-vars
@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # SPDX-License-Identifier: Apache-2.0
 
@@ -42,6 +42,12 @@ if [[ "${1}" == "build" ]]; then
   # platform is handled by the default value of platform (`auto`) in cibuildwheel
   # here we only need to specify the python version we want
   echo "CIBW_BUILD=cp${PYTHON_VERSION_FORMATTED}-*" >> $GITHUB_ENV
+  if [[ "${HOST_PLATFORM}" == "win-arm64" ]]; then
+    # cibuildwheel's `auto` architecture detection resolves to AMD64 on the
+    # windows-11-arm hosted runner (the Actions runner process itself reports
+    # AMD64 via emulation), so the target arch must be forced explicitly.
+    echo "CIBW_ARCHS=ARM64" >> $GITHUB_ENV
+  fi
   BUILD_CUDA_MAJOR="$(cut -d '.' -f 1 <<< ${CUDA_VER})"
   echo "BUILD_CUDA_MAJOR=${BUILD_CUDA_MAJOR}" >> $GITHUB_ENV
   echo "BUILD_PREV_CUDA_MAJOR=$((${BUILD_CUDA_MAJOR} - 1))" >> $GITHUB_ENV
diff --git a/ci/tools/fetch_ctk_redistrib.py b/ci/tools/fetch_ctk_redistrib.py
index af453c699a5..412dbc68a7c 100644
--- a/ci/tools/fetch_ctk_redistrib.py
+++ b/ci/tools/fetch_ctk_redistrib.py
@@ -4,18 +4,16 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-"""Resolve mini-CTK components and prerelease installers."""
+"""Resolve mini-CTK components from NVIDIA redistrib metadata."""
 
 from __future__ import annotations
 
 import argparse
 import json
-import shutil
 import sys
 import urllib.error
 import urllib.parse
 import urllib.request
-from dataclasses import dataclass
 from pathlib import Path
 from typing import Any
 
@@ -31,68 +29,6 @@
     "cuda_cccl": ("cccl",),
 }
 
-PREVIEW_COMPONENT_PACKAGES: dict[str, str] = {
-    "cuda_cccl": "cccl",
-    "cuda_crt": "cuda-crt",
-    "cuda_cudart": "cuda-cudart-dev",
-    "cuda_cupti": "cuda-cupti-dev",
-    "cuda_nvcc": "cuda-nvcc",
-    "cuda_nvrtc": "cuda-nvrtc-dev",
-    "cuda_profiler_api": "cuda-profiler-api",
-    "libcudla": "libcudla-dev",
-    "libcufile": "libcufile-dev",
-    "libnvfatbin": "libnvfatbin-dev",
-    "libnvjitlink": "libnvjitlink-dev",
-    "libnvvm": "libnvvm",
-}
-
-# Top-level directories inside the Windows local installer archive.
-PREVIEW_WINDOWS_ARCHIVE_DIRS: dict[str, str] = {
-    "cuda_cccl": "cccl",
-    "cuda_crt": "cuda_crt",
-    "cuda_cudart": "cuda_cudart",
-    "cuda_cupti": "cuda_cupti",
-    "cuda_nvcc": "cuda_nvcc",
-    "cuda_nvrtc": "cuda_nvrtc",
-    "cuda_profiler_api": "cuda_profiler_api",
-    "libnvfatbin": "libnvfatbin",
-    "libnvjitlink": "libnvjitlink",
-    "libnvvm": "libnvvm",
-}
-
-# Paths inside the extracted installer tree for each component.
-PREVIEW_WINDOWS_COMPONENT_ROOTS: dict[str, str] = {
-    "cuda_cccl": "cccl/cccl",
-    "cuda_crt": "cuda_crt/crt",
-    "cuda_cudart": "cuda_cudart/cudart",
-    "cuda_cupti": "cuda_cupti/cupti",
-    "cuda_nvcc": "cuda_nvcc/nvcc",
-    "cuda_nvrtc": "cuda_nvrtc",
-    "cuda_profiler_api": "cuda_profiler_api/cuda_profiler_api",
-    "libnvfatbin": "libnvfatbin/nvfatbin",
-    "libnvjitlink": "libnvjitlink/nvjitlink",
-    "libnvvm": "libnvvm/nvvm/nvvm",
-}
-
-
-@dataclass(frozen=True)
-class PreviewInstaller:
-    url: str
-    sha256: str
-
-
-# Source: https://packages.nvidia.com/prerelease/cuda/13.4.0/local_installers/sha256sum.txt
-PREVIEW_WINDOWS_INSTALLERS: dict[tuple[str, str], PreviewInstaller] = {
-    ("13.4.0", "win-64"): PreviewInstaller(
-        url=("https://packages.nvidia.com/prerelease/cuda/13.4.0/local_installers/cuda_13.4.0_windows_x86_64.exe"),
-        sha256="b743a3323116bf33404953ef58a9b9a3319368241f6352e933e9461409e9a759",
-    ),
-    ("13.4.0", "win-arm64"): PreviewInstaller(
-        url=("https://packages.nvidia.com/prerelease/cuda/13.4.0/local_installers/cuda_13.4.0_windows_arm64.exe"),
-        sha256="a1f68c81160b16d519c4087788b9c07de41306c3f1b872471ceee0996621374d",
-    ),
-}
-
 
 def host_platform_to_subdir(host_platform: str) -> str:
     try:
@@ -173,135 +109,6 @@ def filter_components(
     return filtered, skipped
 
 
-def get_preview_packages(*, host_platform: str, cuda_version: str, components: str) -> tuple[list[str], list[str]]:
-    if not host_platform.startswith("linux-"):
-        raise ValueError(f"CUDA prerelease packages are not supported for host-platform {host_platform!r}")
-
-    version_parts = cuda_version.split(".")
-    if len(version_parts) != 3 or not all(part.isdigit() for part in version_parts):
-        raise ValueError(f"invalid cuda-version: {cuda_version!r}")
-    package_suffix = "-".join(version_parts[:2])
-
-    packages = []
-    skipped = []
-    for component in filter_static_components(split_components(components), host_platform, cuda_version):
-        if component == "libcudla" and host_platform != "linux-aarch64":
-            skipped.append(component)
-            continue
-        try:
-            package_base = PREVIEW_COMPONENT_PACKAGES[component]
-        except KeyError as exc:
-            raise ValueError(f"unsupported CUDA prerelease component: {component!r}") from exc
-        package = f"{package_base}-{package_suffix}"
-        if package not in packages:
-            packages.append(package)
-    return packages, skipped
-
-
-def windows_arch_for_host_platform(host_platform: str) -> str:
-    if host_platform == "win-arm64":
-        return "arm64"
-    if host_platform == "win-64":
-        return "x64"
-    raise ValueError(f"unsupported Windows host-platform: {host_platform!r}")
-
-
-def get_preview_windows_archive_dirs(
-    *, host_platform: str, cuda_version: str, components: str
-) -> tuple[list[str], list[str]]:
-    if not host_platform.startswith("win-"):
-        raise ValueError(f"CUDA prerelease Windows installer is not supported for host-platform {host_platform!r}")
-
-    archive_dirs: list[str] = []
-    skipped: list[str] = []
-    for component in filter_static_components(split_components(components), host_platform, cuda_version):
-        if component == "libcudla":
-            skipped.append(component)
-            continue
-        try:
-            archive_dir = PREVIEW_WINDOWS_ARCHIVE_DIRS[component]
-        except KeyError as exc:
-            raise ValueError(f"unsupported CUDA prerelease component: {component!r}") from exc
-        if archive_dir not in archive_dirs:
-            archive_dirs.append(archive_dir)
-    return archive_dirs, skipped
-
-
-def _merge_tree(source: Path, destination: Path) -> None:
-    if not source.exists():
-        return
-    destination.mkdir(parents=True, exist_ok=True)
-    for item in source.iterdir():
-        target = destination / item.name
-        if item.is_dir():
-            _merge_tree(item, target)
-        elif target.exists():
-            target.unlink()
-            shutil.copy2(item, target)
-        else:
-            shutil.copy2(item, target)
-
-
-def merge_windows_preview_ctk(
-    *,
-    extract_root: Path,
-    destination: Path,
-    host_platform: str,
-    cuda_version: str,
-    components: str,
-) -> None:
-    arch = windows_arch_for_host_platform(host_platform)
-    if destination.exists():
-        shutil.rmtree(destination)
-    destination.mkdir(parents=True)
-
-    for component in filter_static_components(split_components(components), host_platform, cuda_version):
-        if component not in PREVIEW_WINDOWS_COMPONENT_ROOTS:
-            continue
-        component_root = extract_root / PREVIEW_WINDOWS_COMPONENT_ROOTS[component]
-        if not component_root.exists():
-            raise ValueError(f"CUDA prerelease installer did not provide {component_root}")
-
-        lib_dir = destination / "lib" / arch
-
-        if component == "cuda_nvrtc":
-            _merge_tree(component_root / "nvrtc_dev/include", destination / "include")
-            _merge_tree(component_root / "nvrtc_dev/lib" / arch, lib_dir)
-            _merge_tree(component_root / "nvrtc/bin" / arch, destination / "bin")
-            continue
-
-        if component == "cuda_cupti":
-            _merge_tree(component_root / "extras/CUPTI", destination / "extras/CUPTI")
-            continue
-
-        if component == "libnvvm":
-            _merge_tree(component_root, destination / "nvvm")
-            continue
-
-        _merge_tree(component_root / "include", destination / "include")
-        arch_bin = component_root / "bin" / arch
-        if arch_bin.exists():
-            _merge_tree(arch_bin, destination / "bin")
-        elif (component_root / "bin").exists():
-            _merge_tree(component_root / "bin", destination / "bin")
-        arch_lib = component_root / "lib" / arch
-        if arch_lib.exists():
-            _merge_tree(arch_lib, lib_dir)
-
-    if not (destination / "include").is_dir() or not (destination / "bin/nvcc.exe").is_file():
-        raise ValueError("CUDA prerelease installer did not provide the expected toolkit layout")
-
-
-def get_preview_installer(*, host_platform: str, cuda_version: str) -> PreviewInstaller:
-    try:
-        return PREVIEW_WINDOWS_INSTALLERS[(cuda_version, host_platform)]
-    except KeyError as exc:
-        raise ValueError(
-            f"CUDA prerelease installer is not supported for "
-            f"cuda-version {cuda_version!r}, host-platform {host_platform!r}"
-        ) from exc
-
-
 def get_component_relative_path(metadata: dict[str, Any], *, host_platform: str, component: str) -> str:
     ctk_subdir = host_platform_to_subdir(host_platform)
     component = resolve_component_name(metadata, component)
@@ -336,27 +143,6 @@ def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
     relpath_parser.add_argument("--metadata-path")
     relpath_parser.add_argument("--metadata-url")
 
-    preview_parser = subparsers.add_parser("preview-packages")
-    preview_parser.add_argument("--host-platform", required=True)
-    preview_parser.add_argument("--cuda-version", required=True)
-    preview_parser.add_argument("--components", required=True)
-
-    preview_installer_parser = subparsers.add_parser("preview-installer")
-    preview_installer_parser.add_argument("--host-platform", required=True)
-    preview_installer_parser.add_argument("--cuda-version", required=True)
-
-    preview_windows_archives_parser = subparsers.add_parser("preview-windows-archives")
-    preview_windows_archives_parser.add_argument("--host-platform", required=True)
-    preview_windows_archives_parser.add_argument("--cuda-version", required=True)
-    preview_windows_archives_parser.add_argument("--components", required=True)
-
-    merge_windows_preview_parser = subparsers.add_parser("merge-windows-preview")
-    merge_windows_preview_parser.add_argument("--host-platform", required=True)
-    merge_windows_preview_parser.add_argument("--cuda-version", required=True)
-    merge_windows_preview_parser.add_argument("--components", required=True)
-    merge_windows_preview_parser.add_argument("--extract-root", required=True)
-    merge_windows_preview_parser.add_argument("--destination", required=True)
-
     return parser.parse_args(argv)
 
 
@@ -364,55 +150,8 @@ def main(argv: list[str] | None = None) -> int:
     args = parse_args(argv)
 
     try:
-        if args.command == "preview-packages":
-            packages, skipped = get_preview_packages(
-                host_platform=args.host_platform,
-                cuda_version=args.cuda_version,
-                components=args.components,
-            )
-            for component in skipped:
-                print(
-                    f"Skipping unsupported CUDA prerelease component {component!r} "
-                    f"for host-platform {args.host_platform!r}",
-                    file=sys.stderr,
-                )
-            print(",".join(packages))
-            return 0
-
-        if args.command == "preview-installer":
-            installer = get_preview_installer(
-                host_platform=args.host_platform,
-                cuda_version=args.cuda_version,
-            )
-            print(f"{installer.url}\t{installer.sha256}")
-            return 0
-
-        if args.command == "preview-windows-archives":
-            archive_dirs, skipped = get_preview_windows_archive_dirs(
-                host_platform=args.host_platform,
-                cuda_version=args.cuda_version,
-                components=args.components,
-            )
-            for component in skipped:
-                print(
-                    f"Skipping unsupported CUDA prerelease component {component!r} "
-                    f"for host-platform {args.host_platform!r}",
-                    file=sys.stderr,
-                )
-            print(",".join(archive_dirs))
-            return 0
-
-        if args.command == "merge-windows-preview":
-            merge_windows_preview_ctk(
-                extract_root=Path(args.extract_root),
-                destination=Path(args.destination),
-                host_platform=args.host_platform,
-                cuda_version=args.cuda_version,
-                components=args.components,
-            )
-            return 0
-
         metadata = load_metadata(metadata_path=args.metadata_path, metadata_url=args.metadata_url)
+
         if args.command == "filter-components":
             filtered, skipped = filter_components(
                 metadata,
diff --git a/ci/tools/lookup-run-id b/ci/tools/lookup-run-id
index bd8ba413974..b177727cde5 100755
--- a/ci/tools/lookup-run-id
+++ b/ci/tools/lookup-run-id
@@ -8,7 +8,7 @@
 #
 # Two modes:
 #   --tag <tag>      Find the successful CI run triggered by a tag push.
-#   --branch <branch> Find the latest successful CI run on a branch.
+#   --branch <branch> Find the latest qualifying successful CI run on a branch.
 #
 # Outputs the run ID on stdout.  All diagnostic messages go to stderr.
 # When --head-sha is passed, a second line with the run's head SHA is printed.
@@ -24,11 +24,14 @@ Usage:
 Options:
   --tag <tag>        Find run by git tag (requires local git repo with the tag)
   --branch <branch>  Find latest successful run on the given branch
+  --artifact <glob>  Require an unexpired artifact matching this shell glob
+                     (repeatable; branch mode only)
   --head-sha         Also print the run's head commit SHA (second line)
 
 Examples:
   $0 --tag v13.0.1 NVIDIA/cuda-python
   $0 --branch main NVIDIA/cuda-python
+  $0 --branch 12.9.x --artifact 'cuda-bindings-python313-*' NVIDIA/cuda-python
   $0 --branch main --head-sha NVIDIA/cuda-python "CI"
 EOF
     exit 1
@@ -38,15 +41,21 @@ EOF
 MODE=""
 REF=""
 HEAD_SHA_FLAG=0
+ARTIFACT_PATTERNS=()
 
 while [[ $# -gt 0 ]]; do
     case "${1}" in
         --tag)
+            [[ $# -ge 2 ]] || usage
             [[ -n "${MODE}" && "${MODE}" != "tag" ]] && { echo "Error: --tag and --branch are mutually exclusive" >&2; exit 1; }
             MODE="tag"; REF="${2}"; shift 2 ;;
         --branch)
+            [[ $# -ge 2 ]] || usage
             [[ -n "${MODE}" && "${MODE}" != "branch" ]] && { echo "Error: --tag and --branch are mutually exclusive" >&2; exit 1; }
             MODE="branch"; REF="${2}"; shift 2 ;;
+        --artifact)
+            [[ $# -ge 2 ]] || usage
+            ARTIFACT_PATTERNS+=("${2}"); shift 2 ;;
         --head-sha)
             HEAD_SHA_FLAG=1; shift ;;
         -h|--help)
@@ -69,6 +78,11 @@ WORKFLOW_NAME="${1:-CI}"
 
 if [[ -z "${REPOSITORY}" ]]; then usage; fi
 
+if [[ "${MODE}" != "branch" && ${#ARTIFACT_PATTERNS[@]} -gt 0 ]]; then
+    echo "Error: --artifact is only supported with --branch" >&2
+    exit 1
+fi
+
 # ── Prerequisite checks ──
 if [[ -z "${GH_TOKEN:-}" ]]; then
     echo "Error: GH_TOKEN environment variable is required" >&2
@@ -86,17 +100,79 @@ done
 if [[ "${MODE}" == "branch" ]]; then
     echo "Looking up latest successful '${WORKFLOW_NAME}' run on branch: ${REF}" >&2
 
-    RUN_ID=$(gh run list \
-        -b "${REF}" \
-        -L 1 \
-        -w "${WORKFLOW_NAME}" \
-        -s success \
-        -R "${REPOSITORY}" \
-        --json databaseId \
-        | jq -r '.[0].databaseId // empty')
+    RUN_DATA=$(gh run list \
+        --repo "${REPOSITORY}" \
+        --branch "${REF}" \
+        --workflow "${WORKFLOW_NAME}" \
+        --status success \
+        --json databaseId,workflowName,status,conclusion,headSha,headBranch,createdAt,url \
+        --limit 100)
+
+    CANDIDATE_RUNS=$(echo "${RUN_DATA}" | jq -r \
+        --arg branch "${REF}" '
+        map(select(
+            .headBranch == $branch
+            and .conclusion == "success"
+        ))
+        | sort_by(.createdAt, .databaseId)
+        | reverse
+        | .[]
+        | [.databaseId, .headSha, .createdAt]
+        | @tsv
+    ')
+
+    if [[ -z "${CANDIDATE_RUNS}" ]]; then
+        echo "Error: No successful '${WORKFLOW_NAME}' run found on branch '${REF}'" >&2
+        exit 1
+    fi
+
+    if [[ ${#ARTIFACT_PATTERNS[@]} -gt 0 ]]; then
+        echo "Requiring unexpired artifacts matching:" >&2
+        printf '  - %s\n' "${ARTIFACT_PATTERNS[@]}" >&2
+    fi
+
+    RUN_ID=""
+    HEAD_SHA=""
+    while IFS= read -r candidate; do
+        IFS=$'\t' read -r candidate_id candidate_sha candidate_created_at <<< "${candidate}"
+
+        missing_patterns=()
+        if [[ ${#ARTIFACT_PATTERNS[@]} -gt 0 ]]; then
+            if ! ARTIFACT_NAMES=$(gh api --paginate \
+                "repos/${REPOSITORY}/actions/runs/${candidate_id}/artifacts?per_page=100" \
+                --jq '.artifacts[] | select(.expired == false) | .name'); then
+                echo "Error: Failed to list artifacts for run ${candidate_id}" >&2
+                exit 1
+            fi
+
+            for pattern in "${ARTIFACT_PATTERNS[@]}"; do
+                pattern_matched=0
+                while IFS= read -r artifact_name; do
+                    # The caller supplies a shell glob, so the RHS must remain unquoted.
+                    # shellcheck disable=SC2053
+                    if [[ -n "${artifact_name}" && "${artifact_name}" == ${pattern} ]]; then
+                        pattern_matched=1
+                        break
+                    fi
+                done <<< "${ARTIFACT_NAMES}"
+                if [[ ${pattern_matched} == 0 ]]; then
+                    missing_patterns+=("${pattern}")
+                fi
+            done
+        fi
+
+        if [[ ${#missing_patterns[@]} -gt 0 ]]; then
+            echo "Skipping run ${candidate_id} (${candidate_created_at}); missing unexpired artifact(s): ${missing_patterns[*]}" >&2
+            continue
+        fi
+
+        RUN_ID="${candidate_id}"
+        HEAD_SHA="${candidate_sha}"
+        break
+    done <<< "${CANDIDATE_RUNS}"
 
     if [[ -z "${RUN_ID}" ]]; then
-        echo "Error: No successful '${WORKFLOW_NAME}' run found on branch '${REF}'" >&2
+        echo "Error: No successful '${WORKFLOW_NAME}' run on branch '${REF}' has all required artifacts" >&2
         exit 1
     fi
 
@@ -104,10 +180,10 @@ if [[ "${MODE}" == "branch" ]]; then
     echo "${RUN_ID}"
 
     if [[ "${HEAD_SHA_FLAG}" == 1 ]]; then
-        HEAD_SHA=$(gh run view "${RUN_ID}" \
-            -R "${REPOSITORY}" \
-            --json headSha \
-            | jq -r '.headSha')
+        if [[ -z "${HEAD_SHA}" ]]; then
+            echo "Error: Run ${RUN_ID} has no head SHA" >&2
+            exit 1
+        fi
         echo "Head SHA: ${HEAD_SHA}" >&2
         echo "${HEAD_SHA}"
     fi
diff --git a/ci/tools/merge_cuda_core_wheels.py b/ci/tools/merge_cuda_core_wheels.py
index c66a1bfa2a8..23a8a21289f 100644
--- a/ci/tools/merge_cuda_core_wheels.py
+++ b/ci/tools/merge_cuda_core_wheels.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 
-# SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # SPDX-License-Identifier: Apache-2.0
 
@@ -27,10 +27,9 @@
 import tempfile
 import zipfile
 from pathlib import Path
-from typing import List
 
 
-def run_command(cmd: List[str], cwd: Path | None = None, env: dict = os.environ) -> subprocess.CompletedProcess:
+def run_command(cmd: list[str], cwd: Path | None = None, env: dict = os.environ) -> subprocess.CompletedProcess:
     """Run a command with error handling."""
     print(f"Running: {' '.join(cmd)}")
     if cwd:
@@ -78,7 +77,7 @@ def print_wheel_directory_structure(wheel_path: Path, filter_prefix: str = "cuda
         print(f"Warning: Could not list wheel contents: {e}", file=sys.stderr)
 
 
-def merge_wheels(wheels: List[Path], output_dir: Path, show_wheel_contents: bool = True) -> Path:
+def merge_wheels(wheels: list[Path], output_dir: Path, show_wheel_contents: bool = True) -> Path:
     """Merge multiple wheels into a single wheel with version-specific binaries."""
     print("\n=== Merging wheels ===", file=sys.stderr)
     print(f"Input wheels: {[w.name for w in wheels]}", file=sys.stderr)
diff --git a/ci/tools/run-tests b/ci/tools/run-tests
index c093ed9e4d2..b0ac372dd44 100755
--- a/ci/tools/run-tests
+++ b/ci/tools/run-tests
@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # SPDX-License-Identifier: Apache-2.0
 
@@ -20,13 +20,20 @@ fi
 
 test_module=${1}
 
+TEST_FT_GROUP=()
+PYTEST_PARALLEL_ARGS=()
+if python -c 'import sys; assert not sys._is_gil_enabled()' 2> /dev/null; then
+  TEST_FT_GROUP=(--group test-ft)
+  PYTEST_PARALLEL_ARGS=(--parallel-threads=4)
+fi
+
 # For standard modes, install pathfinder up front (it is a direct dependency
 # of bindings, and a transitive dependency of core).  Nightly modes install
 # all wheels together in a single pip call further below.
 if [[ "${test_module}" != nightly-* ]]; then
   pushd ./cuda_pathfinder
   echo "Installing pathfinder wheel"
-  pip install ./*.whl --group test
+  pip install ./*.whl --group test "${TEST_FT_GROUP[@]}"
   popd
 fi
 
@@ -36,7 +43,7 @@ if [[ "${test_module}" == "pathfinder" ]]; then
     "LD:${CUDA_PATHFINDER_TEST_LOAD_NVIDIA_DYNAMIC_LIB_STRICTNESS} " \
     "FH:${CUDA_PATHFINDER_TEST_FIND_NVIDIA_HEADERS_STRICTNESS} " \
     "BC:${CUDA_PATHFINDER_TEST_FIND_NVIDIA_BITCODE_LIB_STRICTNESS}"
-  pytest -ra -s -v --durations=0 tests/ |& tee /tmp/pathfinder_test_log.txt
+  pytest -ra -s -v "${PYTEST_PARALLEL_ARGS[@]}" tests/ |& tee /tmp/pathfinder_test_log.txt
   # Report the number of "INFO test_" lines (including zero)
   # to support quick validations based on GHA log archives.
   line_count=$(awk '/^INFO test_/ {count++} END {print count+0}' /tmp/pathfinder_test_log.txt)
@@ -46,14 +53,14 @@ elif [[ "${test_module}" == "bindings" ]]; then
   echo "Installing bindings wheel"
   pushd ./cuda_bindings
   if [[ "${LOCAL_CTK}" == 1 ]]; then
-    pip install "${CUDA_BINDINGS_ARTIFACTS_DIR}"/*.whl --group test
+    pip install "${CUDA_BINDINGS_ARTIFACTS_DIR}"/*.whl --group test "${TEST_FT_GROUP[@]}"
   else
-    pip install $(ls "${CUDA_BINDINGS_ARTIFACTS_DIR}"/*.whl)[all] --group test
+    pip install $(ls "${CUDA_BINDINGS_ARTIFACTS_DIR}"/*.whl)[all] --group test "${TEST_FT_GROUP[@]}"
   fi
   echo "Running bindings tests"
-  ${SANITIZER_CMD} pytest -rxXs -v --durations=0 --randomly-dont-reorganize tests/
+  ${SANITIZER_CMD} pytest -rxXs -v --randomly-dont-reorganize "${PYTEST_PARALLEL_ARGS[@]}" tests/
   if [[ "${SKIP_CYTHON_TEST}" == 0 ]]; then
-    ${SANITIZER_CMD} pytest -rxXs -v --durations=0 --randomly-dont-reorganize tests/cython
+    ${SANITIZER_CMD} pytest -rxXs -v --randomly-dont-reorganize "${PYTEST_PARALLEL_ARGS[@]}" tests/cython
   fi
   popd
 elif [[ "${test_module}" == "core" || "${test_module}" == nightly-* ]]; then
@@ -61,11 +68,6 @@ elif [[ "${test_module}" == "core" || "${test_module}" == nightly-* ]]; then
   TEST_CUDA_MAJOR="$(cut -d '.' -f 1 <<< ${CUDA_VER})"
   TEST_CUDA_MAJOR_MINOR="$(cut -d '.' -f 1-2 <<< "${CUDA_VER}")"
 
-  FREE_THREADING=""
-  if python -c 'import sys; assert not sys._is_gil_enabled()' 2> /dev/null; then
-    FREE_THREADING+="-ft"
-  fi
-
   # Resolve bindings based on BINDINGS_SOURCE (set by env-vars):
   #   main/backport → local wheel from artifacts dir
   #   published     → install from PyPI by version
@@ -101,15 +103,15 @@ elif [[ "${test_module}" == "core" || "${test_module}" == nightly-* ]]; then
     echo "Installing core wheel"
     # Constrain cuda-toolkit to the requested CTK version to avoid
     # pip pulling in a newer nvidia-cuda-runtime that conflicts with it.
-    pip install "${CORE_WHL[@]}" --group "test-cu${TEST_CUDA_MAJOR}${FREE_THREADING}" "cuda-toolkit==${TEST_CUDA_MAJOR_MINOR}.*"
+    pip install "${CORE_WHL[@]}" --group "test-cu${TEST_CUDA_MAJOR}" "${TEST_FT_GROUP[@]}" "cuda-toolkit==${TEST_CUDA_MAJOR_MINOR}.*"
     echo "Installed packages before core tests:"
     pip list
     echo "Running core tests"
-    ${SANITIZER_CMD} pytest -rxXs -v --durations=0 --randomly-dont-reorganize tests/
+    ${SANITIZER_CMD} pytest -rxXs -v --randomly-dont-reorganize "${PYTEST_PARALLEL_ARGS[@]}" tests/
     # Currently our CI always installs the latest bindings (from either major version).
     # This is not compatible with the test requirements.
     if [[ "${SKIP_CYTHON_TEST}" == 0 ]]; then
-      ${SANITIZER_CMD} pytest -rxXs -v --durations=0 --randomly-dont-reorganize tests/cython
+      ${SANITIZER_CMD} pytest -rxXs -v --randomly-dont-reorganize "${PYTEST_PARALLEL_ARGS[@]}" tests/cython
     fi
     popd
   elif [[ "${test_module}" == "nightly-cuda-core" ]]; then
@@ -123,7 +125,7 @@ elif [[ "${test_module}" == "core" || "${test_module}" == nightly-* ]]; then
     released_ver=$(pip show cuda-core | awk '/^Version:/{print $2}')
     if [[ -n "${GITHUB_ENV:-}" ]]; then
       echo "CUDA_CORE_RELEASED_VER=${released_ver}" >> "${GITHUB_ENV}"
-      echo "CUDA_CORE_TEST_GROUP=test-cu${TEST_CUDA_MAJOR}${FREE_THREADING}" >> "${GITHUB_ENV}"
+      echo "CUDA_CORE_TEST_GROUP=test-cu${TEST_CUDA_MAJOR}" >> "${GITHUB_ENV}"
     fi
     echo "Installed packages before released cuda-core tests:"
     pip list
@@ -137,7 +139,8 @@ elif [[ "${test_module}" == "core" || "${test_module}" == nightly-* ]]; then
       "${PATHFINDER_WHL[@]}"
       "${BINDINGS_ARGS[@]}"
       "${CORE_WHL[@]}"
-      --group "test-cu${TEST_CUDA_MAJOR}${FREE_THREADING}"
+      --group "test-cu${TEST_CUDA_MAJOR}"
+      "${TEST_FT_GROUP[@]}"
     )
 
     if [[ "${test_module}" == "nightly-pytorch" ]]; then
diff --git a/ci/tools/tests/test_check_mempool_hygiene.py b/ci/tools/tests/test_check_mempool_hygiene.py
new file mode 100644
index 00000000000..5ff3562059b
--- /dev/null
+++ b/ci/tools/tests/test_check_mempool_hygiene.py
@@ -0,0 +1,96 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+import os
+import sys
+
+import pytest
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+from check_mempool_hygiene import DEFAULT_TREE, main, violations_in
+
+
+def write(tmp_path, source):
+    path = tmp_path / "test_sample.py"
+    path.write_text(source, encoding="utf-8")
+    return path
+
+
+UNCAPPED = [
+    pytest.param("DeviceMemoryResource(dev, DeviceMemoryResourceOptions(ipc_enabled=True))", id="options-kwarg"),
+    pytest.param("PinnedMemoryResource(PinnedMemoryResourceOptions())", id="options-empty"),
+    pytest.param('DeviceMemoryResource(dev, {"ipc_enabled": True})', id="options-dict"),
+]
+
+CAPPED = [
+    pytest.param("DeviceMemoryResource(dev, DeviceMemoryResourceOptions(max_size=POOL_SIZE))", id="capped-kwarg"),
+    pytest.param('DeviceMemoryResource(dev, {"max_size": POOL_SIZE})', id="capped-dict"),
+    pytest.param("DeviceMemoryResource(dev, DeviceMemoryResourceOptions(**opts))", id="opaque-kwargs"),
+    # No options at all wraps the device's default pool and reserves nothing, so
+    # capping it would convert a free wrapper into a new pool.
+    pytest.param("DeviceMemoryResource(dev)", id="default-pool-wrapper"),
+    # cuMemPoolCreate requires maxSize == 0 for managed pools, so these have no
+    # max_size to set.
+    pytest.param("ManagedMemoryResource(ManagedMemoryResourceOptions(preferred_location=0))", id="managed-exempt"),
+]
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("source", UNCAPPED)
+def test_uncapped_pool_is_reported(tmp_path, source):
+    assert violations_in(write(tmp_path, source))
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("source", CAPPED)
+def test_acceptable_construction_is_not_reported(tmp_path, source):
+    assert violations_in(write(tmp_path, source)) == []
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("comment_line", [0, 1], ids=["marker-above", "marker-inline"])
+def test_marker_opts_a_call_out(tmp_path, comment_line):
+    # The escape hatch exists mainly for pytest.raises cases, where validation
+    # rejects the arguments before any pool is created.
+    call = "PinnedMemoryResource(PinnedMemoryResourceOptions())"
+    marker = "# uncapped-pool-ok: raises before the pool is created"
+    source = f"{marker}\n{call}" if comment_line == 0 else f"{call}  {marker}"
+
+    assert violations_in(write(tmp_path, source)) == []
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_reported_message_names_file_line_and_symbol(tmp_path):
+    path = write(tmp_path, "x = 1\nDeviceMemoryResource(dev, DeviceMemoryResourceOptions())\n")
+
+    (violation,) = violations_in(path)
+
+    assert violation.startswith(path.as_posix())
+    assert ":2:" in violation
+    assert "DeviceMemoryResourceOptions without max_size" in violation
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_main_reports_failure_for_the_files_it_is_given(tmp_path, capsys):
+    path = write(tmp_path, "DeviceMemoryResource(dev, DeviceMemoryResourceOptions())")
+
+    assert main([str(path)]) == 1
+    assert "must set max_size" in capsys.readouterr().err
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_main_ignores_non_python_files(tmp_path):
+    unrelated = tmp_path / "notes.txt"
+    unrelated.write_text("DeviceMemoryResourceOptions()", encoding="utf-8")
+
+    assert main([str(unrelated)]) == 0
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_the_live_test_suite_is_clean():
+    # Without a default the hook would only ever see changed files, so a
+    # violation could ride in on a rename or a merge.
+    assert DEFAULT_TREE.is_dir()
+    assert main([]) == 0
diff --git a/ci/tools/tests/test_check_release_notes.py b/ci/tools/tests/test_check_release_notes.py
index 4f65404eed5..e08eac6610d 100644
--- a/ci/tools/tests/test_check_release_notes.py
+++ b/ci/tools/tests/test_check_release_notes.py
@@ -3,10 +3,10 @@
 
 from __future__ import annotations
 
-import os
 import sys
+from pathlib import Path
 
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+sys.path.insert(0, str(Path(__file__).parent.parent))
 from check_release_notes import (
     check_release_notes,
     is_post_release,
@@ -87,43 +87,43 @@ def _make_notes(self, tmp_path, pkg, version, content="Release notes."):
 
     def test_present_and_nonempty(self, tmp_path):
         self._make_notes(tmp_path, "cuda_core", "0.7.0")
-        problems = check_release_notes("cuda-core-v0.7.0", "cuda-core", str(tmp_path))
+        problems = check_release_notes("cuda-core-v0.7.0", "cuda-core", tmp_path)
         assert problems == []
 
     def test_missing(self, tmp_path):
-        problems = check_release_notes("cuda-core-v0.7.0", "cuda-core", str(tmp_path))
+        problems = check_release_notes("cuda-core-v0.7.0", "cuda-core", tmp_path)
         assert len(problems) == 1
         assert problems[0][1] == "missing"
 
     def test_empty(self, tmp_path):
         self._make_notes(tmp_path, "cuda_core", "0.7.0", content="")
-        problems = check_release_notes("cuda-core-v0.7.0", "cuda-core", str(tmp_path))
+        problems = check_release_notes("cuda-core-v0.7.0", "cuda-core", tmp_path)
         assert len(problems) == 1
         assert problems[0][1] == "empty"
 
     def test_post_release_skipped(self, tmp_path):
-        problems = check_release_notes("v12.6.2.post1", "cuda-bindings", str(tmp_path))
+        problems = check_release_notes("v12.6.2.post1", "cuda-bindings", tmp_path)
         assert problems == []
 
     def test_invalid_tag(self, tmp_path):
-        problems = check_release_notes("not-a-tag", "cuda-core", str(tmp_path))
+        problems = check_release_notes("not-a-tag", "cuda-core", tmp_path)
         assert len(problems) == 1
         assert "cannot parse" in problems[0][1]
 
     def test_component_prefix_mismatch(self, tmp_path):
         # Pass a cuda-core tag with component=cuda-pathfinder; must be rejected.
-        problems = check_release_notes("cuda-core-v0.7.0", "cuda-pathfinder", str(tmp_path))
+        problems = check_release_notes("cuda-core-v0.7.0", "cuda-pathfinder", tmp_path)
         assert len(problems) == 1
         assert "cannot parse" in problems[0][1]
 
     def test_unknown_component(self, tmp_path):
-        problems = check_release_notes("v13.1.0", "bogus", str(tmp_path))
+        problems = check_release_notes("v13.1.0", "bogus", tmp_path)
         assert len(problems) == 1
         assert "unknown component" in problems[0][1]
 
     def test_plain_v_tag(self, tmp_path):
         self._make_notes(tmp_path, "cuda_python", "13.1.0")
-        problems = check_release_notes("v13.1.0", "cuda-python", str(tmp_path))
+        problems = check_release_notes("v13.1.0", "cuda-python", tmp_path)
         assert problems == []
 
 
@@ -133,17 +133,17 @@ def test_from_versions_yml(self, tmp_path):
         d.mkdir(parents=True)
         (d / "versions.yml").write_text('backport_branch: "12.9.x"\n')
 
-        assert load_backport_branch(str(tmp_path)) == "12.9.x"
+        assert load_backport_branch(tmp_path) == "12.9.x"
 
     def test_from_github_ref_name_for_legacy_backport_branch(self, tmp_path, monkeypatch):
         monkeypatch.setenv("GITHUB_REF_NAME", "12.9.x")
 
-        assert load_backport_branch(str(tmp_path)) == "12.9.x"
+        assert load_backport_branch(tmp_path) == "12.9.x"
 
     def test_ignores_non_backport_github_ref_name(self, tmp_path, monkeypatch):
         monkeypatch.setenv("GITHUB_REF_NAME", "main")
 
-        assert load_backport_branch(str(tmp_path)) is None
+        assert load_backport_branch(tmp_path) is None
 
 
 class TestMain:
diff --git a/ci/tools/tests/test_compute_ci_plan.py b/ci/tools/tests/test_compute_ci_plan.py
new file mode 100644
index 00000000000..79a83394dfa
--- /dev/null
+++ b/ci/tools/tests/test_compute_ci_plan.py
@@ -0,0 +1,181 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+import tempfile
+import unittest
+from pathlib import Path
+
+from ci.tools.compute_ci_plan import _expand_linked_paths, compute_workplan
+
+ALL_MODULES = {"pathfinder", "bindings", "core", "python"}
+ALL_PLATFORMS = {"linux", "windows"}
+
+
+def plan_for(
+    *paths: str,
+    baseline: bool = True,
+    linked_paths: set[str] | None = None,
+) -> dict[str, object]:
+    return compute_workplan(
+        list(paths),
+        merge_base="base",
+        baseline_run_id="123" if baseline else "",
+        linked_paths=linked_paths,
+    )
+
+
+def selected(plan: dict[str, object], key: str) -> set[str]:
+    modules = plan["modules"]
+    assert isinstance(modules, dict)
+    return {name for name, decision in modules.items() if decision[key]}
+
+
+def selected_platforms(plan: dict[str, object]) -> set[str]:
+    jobs = plan["jobs"]
+    assert isinstance(jobs, dict)
+    platforms = jobs["platforms"]
+    assert isinstance(platforms, dict)
+    assert set(platforms) == ALL_PLATFORMS
+    return {name for name, enabled in platforms.items() if enabled}
+
+
+class ComputeWorkplanTest(unittest.TestCase):
+    def test_path_impacts(self) -> None:
+        cases = {
+            "cuda_pathfinder/cuda/pathfinder/_loader.py": (ALL_MODULES, ALL_MODULES, False),
+            "cuda_bindings/cuda/bindings/driver.pyx": (
+                {"bindings", "core", "python"},
+                {"bindings", "core", "python"},
+                False,
+            ),
+            "cuda_core/cuda/core/_device.py": ({"core"}, {"core", "python"}, True),
+            "cuda_core/cuda/core/examples/demo.py": ({"core"}, {"core", "python"}, True),
+            "cuda_python/pyproject.toml": ({"bindings", "python"}, {"python"}, False),
+            "cuda_pathfinder/tests/test_loader.py": (set(), {"pathfinder"}, False),
+            "cuda_bindings/examples/0_Introduction/vectorAddDrv.py": (set(), {"bindings"}, False),
+            "cuda_bindings/tests/README.md": (set(), {"bindings"}, False),
+            "cuda_core/pytest.ini": (set(), {"core"}, False),
+            "cuda_python/tests/test_import.py": (set(), {"python"}, False),
+            "cuda_python_test_helpers/cuda_python_test_helpers/cuda_utils.py": (
+                set(),
+                ALL_MODULES,
+                False,
+            ),
+            "benchmarks/cuda_bindings/run_pyperf.py": (set(), ALL_MODULES, False),
+            "benchmarks/cuda_core/runner.py": (set(), ALL_MODULES, False),
+            "ci/tools/run-tests": (ALL_MODULES, ALL_MODULES, True),
+            "ci/versions.yml": (ALL_MODULES, ALL_MODULES, True),
+            "pytest.ini": (ALL_MODULES, ALL_MODULES, True),
+        }
+
+        for path, (builds, tests, core_api) in cases.items():
+            with self.subTest(path=path):
+                plan = plan_for(path)
+                assert selected(plan, "needs_build") == builds
+                assert selected(plan, "needs_test") == tests
+                assert selected_platforms(plan) == ALL_PLATFORMS
+                assert plan["jobs"]["sdist_tests"] == bool(builds)
+                assert plan["jobs"]["core_api_checks"] == core_api
+
+    def test_test_infrastructure_platforms(self) -> None:
+        cases = {
+            ".github/workflows/test-wheel-linux.yml": {"linux"},
+            ".github/workflows/test-wheel-windows.yml": {"windows"},
+            "ci/tools/configure_driver_mode.ps1": {"windows"},
+            "ci/tools/guess_latest.sh": {"linux"},
+            "ci/tools/install_gpu_driver.ps1": {"windows"},
+            "ci/tools/install_gpu_driver.sh": {"linux"},
+            "ci/tools/setup-sanitizer": {"linux"},
+        }
+
+        for path, platforms in cases.items():
+            with self.subTest(path=path):
+                plan = plan_for(path)
+                assert not selected(plan, "needs_build")
+                assert selected(plan, "needs_test") == ALL_MODULES
+                assert selected_platforms(plan) == platforms
+                assert not plan["jobs"]["sdist_tests"]
+                assert not plan["jobs"]["core_api_checks"]
+
+        mixed_plan = plan_for("ci/tools/install_gpu_driver.sh", "ci/tools/install_gpu_driver.ps1")
+        assert selected_platforms(mixed_plan) == ALL_PLATFORMS
+
+        source_plan = plan_for("ci/tools/install_gpu_driver.sh", "cuda_python/pyproject.toml")
+        assert selected_platforms(source_plan) == ALL_PLATFORMS
+
+    def test_ignored_paths_select_no_work(self) -> None:
+        for path in (
+            "cuda_core/docs/index.rst",
+            "cuda_core/pixi.toml",
+            "cuda_core/tests/fixtures/pixi.toml",
+            "benchmarks/cuda_bindings/pixi.toml",
+            "benchmarks/cuda_bindings/AGENTS.md",
+            "cuda_core/cuda/core/_cpp/DESIGN.md",
+            "cuda_bindings/README.md",
+            "cuda_core/README.md",
+            "new-area/pixi.toml",
+            "notes.md",
+            "diagram.svg",
+            ".github/labeler.yml",
+            ".github/ISSUE_TEMPLATE/bug.yml",
+        ):
+            with self.subTest(path=path):
+                plan = plan_for(path)
+                assert not selected(plan, "needs_build")
+                assert not selected(plan, "needs_test")
+                assert not selected_platforms(plan)
+
+    def test_unknown_path_and_missing_baseline_force_all(self) -> None:
+        for plan in (
+            plan_for("new-top-level-file"),
+            plan_for("new-area/config.toml"),
+            plan_for(".github/workflows/new-main-ci-workflow.yml"),
+            plan_for(".github/actions/doc_preview/action.yml"),
+            plan_for("ci/ci-pipeline.svg"),
+            plan_for("cuda_core/docs/index.rst", baseline=False),
+            compute_workplan([], merge_base="", baseline_run_id="123"),
+        ):
+            assert selected(plan, "needs_build") == ALL_MODULES
+            assert selected(plan, "needs_test") == ALL_MODULES
+            assert selected_platforms(plan) == ALL_PLATFORMS
+            assert plan["jobs"]["core_api_checks"]
+            assert plan["baseline"] == {"run_id": "", "sha": ""}
+
+    def test_mixed_changes_are_combined(self) -> None:
+        plan = plan_for("cuda_core/tests/test_device.py", "cuda_python/pyproject.toml")
+        assert selected(plan, "needs_build") == {"bindings", "python"}
+        assert selected(plan, "needs_test") == {"core", "python"}
+        assert selected_platforms(plan) == ALL_PLATFORMS
+        assert plan["jobs"]["sdist_tests"]
+        assert plan["baseline"] == {"run_id": "123", "sha": "base"}
+
+    def test_changed_symlink_targets_include_their_consumers(self) -> None:
+        with tempfile.TemporaryDirectory() as directory:
+            root = Path(directory)
+            (root / "cuda_python").mkdir()
+            (root / "cuda_core").mkdir()
+            (root / "README.md").write_text("readme", encoding="utf-8")
+            (root / "cuda_python" / "README.md").symlink_to("../README.md")
+            (root / "cuda_core" / "README.md").symlink_to("../README.md")
+
+            paths = _expand_linked_paths(
+                ["README.md"],
+                ["cuda_python/README.md"],
+                root=root,
+            )
+
+        assert paths == ["README.md", "cuda_python/README.md"]
+        plan = plan_for(*paths, linked_paths={"cuda_python/README.md"})
+        assert selected(plan, "needs_build") == {"bindings", "python"}
+        assert selected(plan, "needs_test") == {"python"}
+
+        removed_link = plan_for("cuda_python/README.md", linked_paths={"cuda_python/README.md"})
+        assert selected(removed_link, "needs_build") == {"bindings", "python"}
+        assert selected(removed_link, "needs_test") == {"python"}
+
+
+if __name__ == "__main__":
+    unittest.main()
diff --git a/ci/tools/tests/test_lookup_run_id.py b/ci/tools/tests/test_lookup_run_id.py
new file mode 100644
index 00000000000..cb972b24ed3
--- /dev/null
+++ b/ci/tools/tests/test_lookup_run_id.py
@@ -0,0 +1,239 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+import json
+import os
+import subprocess
+from pathlib import Path
+
+import pytest
+
+LOOKUP_RUN_ID = Path(__file__).parent.parent / "lookup-run-id"
+
+FAKE_GH = r"""#!/usr/bin/env python3
+import json
+import os
+import re
+import sys
+
+args = sys.argv[1:]
+if args[:2] == ["run", "list"]:
+    runs = json.loads(os.environ["FAKE_RUNS"])
+    try:
+        status = args[args.index("--status") + 1]
+        limit = int(args[args.index("--limit") + 1])
+    except (ValueError, IndexError):
+        print("run list requires --status and --limit", file=sys.stderr)
+        raise SystemExit(2)
+    if status == "success":
+        runs = [run for run in runs if run["conclusion"] == "success"]
+    elif status == "completed":
+        runs = [run for run in runs if run["status"] == "completed"]
+    else:
+        print(f"unsupported status filter: {status}", file=sys.stderr)
+        raise SystemExit(2)
+    print(json.dumps(runs[:limit]))
+    raise SystemExit(0)
+
+if args[:1] == ["api"]:
+    if "--paginate" not in args or "--jq" not in args:
+        print("artifact lookup must be paginated and filtered", file=sys.stderr)
+        raise SystemExit(2)
+    match = re.search(r"/runs/(\d+)/artifacts", " ".join(args))
+    if match is None:
+        print("could not determine run ID", file=sys.stderr)
+        raise SystemExit(2)
+    artifacts_by_run = json.loads(os.environ["FAKE_ARTIFACTS"])
+    artifacts = artifacts_by_run.get(match.group(1))
+    if artifacts is None:
+        print("simulated artifact API failure", file=sys.stderr)
+        raise SystemExit(3)
+    for artifact in artifacts:
+        if not artifact.get("expired", False):
+            print(artifact["name"])
+    raise SystemExit(0)
+
+print(f"unexpected gh arguments: {args!r}", file=sys.stderr)
+raise SystemExit(2)
+"""
+
+
+def _run(run_id, created_at, *, branch="12.9.x", workflow="CI", conclusion="success"):
+    return {
+        "databaseId": run_id,
+        "workflowName": workflow,
+        "status": "completed",
+        "conclusion": conclusion,
+        "headSha": f"sha-{run_id}",
+        "headBranch": branch,
+        "createdAt": created_at,
+        "url": f"https://example.invalid/runs/{run_id}",
+    }
+
+
+@pytest.fixture
+def fake_gh(tmp_path):
+    fake_bin = tmp_path / "bin"
+    fake_bin.mkdir()
+    gh = fake_bin / "gh"
+    gh.write_text(FAKE_GH, encoding="utf-8")
+    gh.chmod(0o755)
+    return fake_bin
+
+
+def _lookup(fake_gh, runs, artifacts, *args, workflow="CI"):
+    env = os.environ.copy()
+    env.update(
+        {
+            "FAKE_ARTIFACTS": json.dumps(artifacts),
+            "FAKE_RUNS": json.dumps(runs),
+            "GH_TOKEN": "test-token",
+            "PATH": f"{fake_gh}{os.pathsep}{env['PATH']}",
+        }
+    )
+    return subprocess.run(  # noqa: S603 - invokes the repository script under test
+        [str(LOOKUP_RUN_ID), *args, "NVIDIA/cuda-python", workflow],
+        check=False,
+        capture_output=True,
+        env=env,
+        text=True,
+    )
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+class TestBranchLookup:
+    def test_filters_successful_runs_before_applying_limit(self, fake_gh):
+        runs = [
+            _run(
+                run_id,
+                "2026-08-13T12:00:00Z",
+                conclusion="failure",
+            )
+            for run_id in range(200, 100, -1)
+        ]
+        runs.append(_run(50, "2026-08-12T12:00:00Z"))
+
+        result = _lookup(
+            fake_gh,
+            runs,
+            {},
+            "--branch",
+            "12.9.x",
+        )
+
+        assert result.returncode == 0, result.stderr
+        assert result.stdout.strip() == "50"
+
+    def test_selects_newest_run_with_filename_workflow_selector(self, fake_gh):
+        runs = [
+            _run(100, "2026-08-10T12:00:00Z"),
+            _run(400, "2026-08-13T12:00:00Z", conclusion="failure"),
+            _run(300, "2026-08-12T12:00:00Z", branch="other"),
+            _run(200, "2026-08-11T12:00:00Z"),
+        ]
+
+        result = _lookup(
+            fake_gh,
+            runs,
+            {},
+            "--branch",
+            "12.9.x",
+            "--head-sha",
+            workflow="ci.yml",
+        )
+
+        assert result.returncode == 0, result.stderr
+        assert result.stdout.splitlines() == ["200", "sha-200"]
+
+    def test_falls_back_until_all_required_artifacts_are_unexpired(self, fake_gh):
+        bindings_pattern = "cuda-bindings-python315-cuda*-linux-64*[0-9a-f]"
+        runs = [
+            _run(300, "2026-08-13T12:00:00Z"),
+            _run(200, "2026-08-12T12:00:00Z"),
+            _run(100, "2026-08-11T12:00:00Z"),
+        ]
+        artifacts = {
+            "300": [
+                {
+                    "name": "cuda-bindings-python315-cuda12.9.1-linux-64-abc123",
+                    "expired": True,
+                },
+                {
+                    "name": "cuda-bindings-python315-cuda12.9.1-linux-64-abc123-tests",
+                    "expired": False,
+                },
+                {"name": "cuda-python-wheel", "expired": False},
+            ],
+            "200": [
+                {
+                    "name": "cuda-bindings-python315-cuda12.9.1-linux-64-def456",
+                    "expired": False,
+                }
+            ],
+            "100": [
+                {
+                    "name": "cuda-bindings-python315-cuda12.9.1-linux-64-fedcba",
+                    "expired": False,
+                },
+                {"name": "cuda-python-wheel", "expired": False},
+            ],
+        }
+
+        result = _lookup(
+            fake_gh,
+            runs,
+            artifacts,
+            "--branch",
+            "12.9.x",
+            "--artifact",
+            bindings_pattern,
+            "--artifact",
+            "cuda-python-wheel",
+        )
+
+        assert result.returncode == 0, result.stderr
+        assert result.stdout.strip() == "100"
+        assert "Skipping run 300" in result.stderr
+        assert "Skipping run 200" in result.stderr
+
+    def test_reports_when_no_successful_run_has_required_artifacts(self, fake_gh):
+        runs = [_run(100, "2026-08-11T12:00:00Z")]
+        artifacts = {
+            "100": [
+                {
+                    "name": "cuda-bindings-python315-cuda12.9.1-linux-64-fedcba",
+                    "expired": True,
+                }
+            ]
+        }
+
+        result = _lookup(
+            fake_gh,
+            runs,
+            artifacts,
+            "--branch",
+            "12.9.x",
+            "--artifact",
+            "cuda-bindings-python315-cuda*-linux-64*[0-9a-f]",
+        )
+
+        assert result.returncode == 1
+        assert "has all required artifacts" in result.stderr
+
+    def test_propagates_artifact_api_failures(self, fake_gh):
+        runs = [_run(100, "2026-08-11T12:00:00Z")]
+
+        result = _lookup(
+            fake_gh,
+            runs,
+            {},
+            "--branch",
+            "12.9.x",
+            "--artifact",
+            "cuda-bindings-*",
+        )
+
+        assert result.returncode == 1
+        assert "Failed to list artifacts for run 100" in result.stderr
diff --git a/ci/versions.yml b/ci/versions.yml
index 4da77b95ef7..e6574847dd2 100644
--- a/ci/versions.yml
+++ b/ci/versions.yml
@@ -5,7 +5,6 @@ backport_branch: "12.9.x"  # keep in sync with target-branch in .github/dependab
 
 cuda:
   build:
-    version: "13.4.0"
-    channel: "prerelease"
+    version: "13.4.1"
   prev_build:
     version: "12.9.1"
diff --git a/cuda_bindings/LICENSE b/cuda_bindings/LICENSE
index d6f74778be8..f3fe76ecadf 100644
--- a/cuda_bindings/LICENSE
+++ b/cuda_bindings/LICENSE
@@ -176,3 +176,28 @@ Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
       of your accepting any such warranty or additional liability.
 
    END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
diff --git a/cuda_bindings/build_hooks.py b/cuda_bindings/build_hooks.py
index a50133f9777..63a371d125d 100644
--- a/cuda_bindings/build_hooks.py
+++ b/cuda_bindings/build_hooks.py
@@ -16,6 +16,7 @@
 import sys
 import sysconfig
 import tempfile
+from pathlib import Path
 from warnings import warn
 
 from setuptools import build_meta as _build_meta
@@ -50,9 +51,9 @@ def _import_get_cuda_path_or_home():
             cuda = None
 
         for p in sys.path:
-            sp_cuda = os.path.join(p, "cuda")
-            if os.path.isdir(os.path.join(sp_cuda, "pathfinder")):
-                cuda.__path__ = list(cuda.__path__) + [sp_cuda]
+            sp_cuda = Path(p) / "cuda"
+            if (sp_cuda / "pathfinder").is_dir():
+                cuda.__path__ = list(cuda.__path__) + [str(sp_cuda)]
                 break
         else:
             raise ModuleNotFoundError(
@@ -61,6 +62,11 @@ def _import_get_cuda_path_or_home():
             )
         import cuda.pathfinder
 
+    pathfinder_dir = Path(cuda.pathfinder.__file__).parent
+    print(
+        f"Using cuda-pathfinder {cuda.pathfinder.__version__} from {pathfinder_dir}",
+        file=sys.stderr,
+    )
     return cuda.pathfinder.get_cuda_path_or_home
 
 
@@ -131,6 +137,7 @@ def _build_cuda_bindings(debug=False):
     that metadata queries do not require a CUDA toolkit installation.
     """
     from Cython.Build import cythonize
+    from Cython.Compiler import Options as _CythonOptions
 
     global _extensions
 
@@ -224,6 +231,7 @@ def get_static_libraries(f):
         )
 
     # Cythonize
+    _CythonOptions.warning_errors = True
     cython_directives = {"language_level": 3, "embedsignature": True, "binding": True, "freethreading_compatible": True}
     if compile_for_coverage:
         cython_directives["linetrace"] = True
diff --git a/cuda_bindings/cuda/bindings/_internal/cudla.pxd b/cuda_bindings/cuda/bindings/_internal/cudla.pxd
index 2594bb88da9..52b1b777056 100644
--- a/cuda_bindings/cuda/bindings/_internal/cudla.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/cudla.pxd
@@ -1,10 +1,21 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated across versions from 1.5.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 1.5.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=6866708da9b12dc99b597cd56196b66a1f2645198821b572326bb0858b5906d3
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport (
+    uint32_t,
+    uint64_t,
+    uint8_t,
+)
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=496ca23b9a84c00538bab7ea91ea3789a1caece491349843387a706509454f43
 from ..cycudla cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/cudla_linux.pyx b/cuda_bindings/cuda/bindings/_internal/cudla_linux.pyx
index 284c90b15e1..b9cbb73a32e 100644
--- a/cuda_bindings/cuda/bindings/_internal/cudla_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/cudla_linux.pyx
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated across versions from 1.5.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=b11294791915840a6cb53811f7ce9d81a295c011e6d3c7585aa0c4d45be6bf43
+# This code was automatically generated across versions from 1.5.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=6d02d71c7a7ef7627a3dccc1514b8e1ea48ac7d738954a2259df71cfeaaca839
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -44,7 +43,12 @@ cdef extern from "<dlfcn.h>":
     void* _cyb_dlsym "dlsym"(void*, const char*) nogil
     const void * _cyb_RTLD_DEFAULT "RTLD_DEFAULT"
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+    uint64_t,
+    uint8_t,
+)
 
 import threading as _cyb_threading
 
@@ -193,43 +197,43 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_cudla()
     cdef dict data = {}
     global __cudlaGetVersion
-    data["__cudlaGetVersion"] = <_cyb_intptr_t>__cudlaGetVersion
+    data["__cudlaGetVersion"] = <intptr_t>__cudlaGetVersion
 
     global __cudlaDeviceGetCount
-    data["__cudlaDeviceGetCount"] = <_cyb_intptr_t>__cudlaDeviceGetCount
+    data["__cudlaDeviceGetCount"] = <intptr_t>__cudlaDeviceGetCount
 
     global __cudlaCreateDevice
-    data["__cudlaCreateDevice"] = <_cyb_intptr_t>__cudlaCreateDevice
+    data["__cudlaCreateDevice"] = <intptr_t>__cudlaCreateDevice
 
     global __cudlaMemRegister
-    data["__cudlaMemRegister"] = <_cyb_intptr_t>__cudlaMemRegister
+    data["__cudlaMemRegister"] = <intptr_t>__cudlaMemRegister
 
     global __cudlaModuleLoadFromMemory
-    data["__cudlaModuleLoadFromMemory"] = <_cyb_intptr_t>__cudlaModuleLoadFromMemory
+    data["__cudlaModuleLoadFromMemory"] = <intptr_t>__cudlaModuleLoadFromMemory
 
     global __cudlaModuleGetAttributes
-    data["__cudlaModuleGetAttributes"] = <_cyb_intptr_t>__cudlaModuleGetAttributes
+    data["__cudlaModuleGetAttributes"] = <intptr_t>__cudlaModuleGetAttributes
 
     global __cudlaModuleUnload
-    data["__cudlaModuleUnload"] = <_cyb_intptr_t>__cudlaModuleUnload
+    data["__cudlaModuleUnload"] = <intptr_t>__cudlaModuleUnload
 
     global __cudlaSubmitTask
-    data["__cudlaSubmitTask"] = <_cyb_intptr_t>__cudlaSubmitTask
+    data["__cudlaSubmitTask"] = <intptr_t>__cudlaSubmitTask
 
     global __cudlaDeviceGetAttribute
-    data["__cudlaDeviceGetAttribute"] = <_cyb_intptr_t>__cudlaDeviceGetAttribute
+    data["__cudlaDeviceGetAttribute"] = <intptr_t>__cudlaDeviceGetAttribute
 
     global __cudlaMemUnregister
-    data["__cudlaMemUnregister"] = <_cyb_intptr_t>__cudlaMemUnregister
+    data["__cudlaMemUnregister"] = <intptr_t>__cudlaMemUnregister
 
     global __cudlaGetLastError
-    data["__cudlaGetLastError"] = <_cyb_intptr_t>__cudlaGetLastError
+    data["__cudlaGetLastError"] = <intptr_t>__cudlaGetLastError
 
     global __cudlaDestroyDevice
-    data["__cudlaDestroyDevice"] = <_cyb_intptr_t>__cudlaDestroyDevice
+    data["__cudlaDestroyDevice"] = <intptr_t>__cudlaDestroyDevice
 
     global __cudlaSetTaskTimeoutInMs
-    data["__cudlaSetTaskTimeoutInMs"] = <_cyb_intptr_t>__cudlaSetTaskTimeoutInMs
+    data["__cudlaSetTaskTimeoutInMs"] = <intptr_t>__cudlaSetTaskTimeoutInMs
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/cudla_windows.pyx b/cuda_bindings/cuda/bindings/_internal/cudla_windows.pyx
index 09c20781d71..8e361068068 100644
--- a/cuda_bindings/cuda/bindings/_internal/cudla_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/cudla_windows.pyx
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated across versions from 1.5.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=e076e29e87500d2bdc0a65891978259cc1be746831c7b7177427daf7a970708e
+# This code was automatically generated across versions from 1.5.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=338d2b3b3dc670ce440660d6161d69bb61b7c2f0c03759fa8df5c91d45255d7d
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -44,7 +43,13 @@ cdef extern from "<windows.h>":
     ctypedef void* HMODULE
     void* _cyb_GetProcAddress "GetProcAddress"(HMODULE, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+    uint64_t,
+    uint8_t,
+    uintptr_t,
+)
 
 import threading as _cyb_threading
 
@@ -146,43 +151,43 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_cudla()
     cdef dict data = {}
     global __cudlaGetVersion
-    data["__cudlaGetVersion"] = <_cyb_intptr_t>__cudlaGetVersion
+    data["__cudlaGetVersion"] = <intptr_t>__cudlaGetVersion
 
     global __cudlaDeviceGetCount
-    data["__cudlaDeviceGetCount"] = <_cyb_intptr_t>__cudlaDeviceGetCount
+    data["__cudlaDeviceGetCount"] = <intptr_t>__cudlaDeviceGetCount
 
     global __cudlaCreateDevice
-    data["__cudlaCreateDevice"] = <_cyb_intptr_t>__cudlaCreateDevice
+    data["__cudlaCreateDevice"] = <intptr_t>__cudlaCreateDevice
 
     global __cudlaMemRegister
-    data["__cudlaMemRegister"] = <_cyb_intptr_t>__cudlaMemRegister
+    data["__cudlaMemRegister"] = <intptr_t>__cudlaMemRegister
 
     global __cudlaModuleLoadFromMemory
-    data["__cudlaModuleLoadFromMemory"] = <_cyb_intptr_t>__cudlaModuleLoadFromMemory
+    data["__cudlaModuleLoadFromMemory"] = <intptr_t>__cudlaModuleLoadFromMemory
 
     global __cudlaModuleGetAttributes
-    data["__cudlaModuleGetAttributes"] = <_cyb_intptr_t>__cudlaModuleGetAttributes
+    data["__cudlaModuleGetAttributes"] = <intptr_t>__cudlaModuleGetAttributes
 
     global __cudlaModuleUnload
-    data["__cudlaModuleUnload"] = <_cyb_intptr_t>__cudlaModuleUnload
+    data["__cudlaModuleUnload"] = <intptr_t>__cudlaModuleUnload
 
     global __cudlaSubmitTask
-    data["__cudlaSubmitTask"] = <_cyb_intptr_t>__cudlaSubmitTask
+    data["__cudlaSubmitTask"] = <intptr_t>__cudlaSubmitTask
 
     global __cudlaDeviceGetAttribute
-    data["__cudlaDeviceGetAttribute"] = <_cyb_intptr_t>__cudlaDeviceGetAttribute
+    data["__cudlaDeviceGetAttribute"] = <intptr_t>__cudlaDeviceGetAttribute
 
     global __cudlaMemUnregister
-    data["__cudlaMemUnregister"] = <_cyb_intptr_t>__cudlaMemUnregister
+    data["__cudlaMemUnregister"] = <intptr_t>__cudlaMemUnregister
 
     global __cudlaGetLastError
-    data["__cudlaGetLastError"] = <_cyb_intptr_t>__cudlaGetLastError
+    data["__cudlaGetLastError"] = <intptr_t>__cudlaGetLastError
 
     global __cudlaDestroyDevice
-    data["__cudlaDestroyDevice"] = <_cyb_intptr_t>__cudlaDestroyDevice
+    data["__cudlaDestroyDevice"] = <intptr_t>__cudlaDestroyDevice
 
     global __cudlaSetTaskTimeoutInMs
-    data["__cudlaSetTaskTimeoutInMs"] = <_cyb_intptr_t>__cudlaSetTaskTimeoutInMs
+    data["__cudlaSetTaskTimeoutInMs"] = <intptr_t>__cudlaSetTaskTimeoutInMs
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/cufile.pxd b/cuda_bindings/cuda/bindings/_internal/cufile.pxd
index b8c508e21de..9754670ed67 100644
--- a/cuda_bindings/cuda/bindings/_internal/cufile.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/cufile.pxd
@@ -2,10 +2,17 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=ce1a8b4cfbbc98d5a6e7975adbfa4e5be9f62da604eb3841691dc555b4b72e76
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libcpp cimport bool as _cyb_bool
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=aa4406f8a34fc4f1cf43294df5b80bcd84c0beb3b43dbcb66ecdbca3e17d439e
 from ..cycufile cimport *
 
 
@@ -24,7 +31,7 @@ cdef CUfileError_t _cuFileDriverClose() except?<CUfileError_t>CUFILE_LOADING_ERR
 cdef CUfileError_t _cuFileDriverClose_v2() except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef long _cuFileUseCount() except* nogil
 cdef CUfileError_t _cuFileDriverGetProperties(CUfileDrvProps_t* props) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
-cdef CUfileError_t _cuFileDriverSetPollMode(cpp_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
+cdef CUfileError_t _cuFileDriverSetPollMode(_cyb_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileDriverSetMaxDirectIOSize(size_t max_direct_io_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileDriverSetMaxCacheSize(size_t max_cache_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileDriverSetMaxPinnedMemSize(size_t max_pinned_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
@@ -39,10 +46,10 @@ cdef CUfileError_t _cuFileStreamRegister(CUstream stream, unsigned flags) except
 cdef CUfileError_t _cuFileStreamDeregister(CUstream stream) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileGetVersion(int* version) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileGetParameterSizeT(CUFileSizeTConfigParameter_t param, size_t* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
-cdef CUfileError_t _cuFileGetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
+cdef CUfileError_t _cuFileGetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileGetParameterString(CUFileStringConfigParameter_t param, char* desc_str, int len) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileSetParameterSizeT(CUFileSizeTConfigParameter_t param, size_t value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
-cdef CUfileError_t _cuFileSetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
+cdef CUfileError_t _cuFileSetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileSetParameterString(CUFileStringConfigParameter_t param, const char* desc_str) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileGetParameterMinMaxValue(CUFileSizeTConfigParameter_t param, size_t* min_value, size_t* max_value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t _cuFileSetStatsLevel(int level) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
diff --git a/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx b/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx
index baa2bd94858..03864ddd836 100644
--- a/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/cufile_linux.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=84741b6deffabec746bbb6a7efa6a638e72579f8eae7731380ae3c1718f1854b
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=20df7b33c9628ffefdce815bf9ffa31e635a9410ef0156145ced38a6e092d7f1
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -46,7 +45,8 @@ cdef extern from "<dlfcn.h>":
     const void * _cyb_RTLD_DEFAULT "RTLD_DEFAULT"
 
 cimport cython as _cyb_cython
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport intptr_t
+from libcpp cimport bool as _cyb_bool
 
 import threading as _cyb_threading
 
@@ -452,139 +452,139 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_cufile()
     cdef dict data = {}
     global __cuFileHandleRegister
-    data["__cuFileHandleRegister"] = <_cyb_intptr_t>__cuFileHandleRegister
+    data["__cuFileHandleRegister"] = <intptr_t>__cuFileHandleRegister
 
     global __cuFileHandleDeregister
-    data["__cuFileHandleDeregister"] = <_cyb_intptr_t>__cuFileHandleDeregister
+    data["__cuFileHandleDeregister"] = <intptr_t>__cuFileHandleDeregister
 
     global __cuFileBufRegister
-    data["__cuFileBufRegister"] = <_cyb_intptr_t>__cuFileBufRegister
+    data["__cuFileBufRegister"] = <intptr_t>__cuFileBufRegister
 
     global __cuFileBufDeregister
-    data["__cuFileBufDeregister"] = <_cyb_intptr_t>__cuFileBufDeregister
+    data["__cuFileBufDeregister"] = <intptr_t>__cuFileBufDeregister
 
     global __cuFileRead
-    data["__cuFileRead"] = <_cyb_intptr_t>__cuFileRead
+    data["__cuFileRead"] = <intptr_t>__cuFileRead
 
     global __cuFileWrite
-    data["__cuFileWrite"] = <_cyb_intptr_t>__cuFileWrite
+    data["__cuFileWrite"] = <intptr_t>__cuFileWrite
 
     global __cuFileDriverOpen
-    data["__cuFileDriverOpen"] = <_cyb_intptr_t>__cuFileDriverOpen
+    data["__cuFileDriverOpen"] = <intptr_t>__cuFileDriverOpen
 
     global __cuFileDriverClose
-    data["__cuFileDriverClose"] = <_cyb_intptr_t>__cuFileDriverClose
+    data["__cuFileDriverClose"] = <intptr_t>__cuFileDriverClose
 
     global __cuFileDriverClose_v2
-    data["__cuFileDriverClose_v2"] = <_cyb_intptr_t>__cuFileDriverClose_v2
+    data["__cuFileDriverClose_v2"] = <intptr_t>__cuFileDriverClose_v2
 
     global __cuFileUseCount
-    data["__cuFileUseCount"] = <_cyb_intptr_t>__cuFileUseCount
+    data["__cuFileUseCount"] = <intptr_t>__cuFileUseCount
 
     global __cuFileDriverGetProperties
-    data["__cuFileDriverGetProperties"] = <_cyb_intptr_t>__cuFileDriverGetProperties
+    data["__cuFileDriverGetProperties"] = <intptr_t>__cuFileDriverGetProperties
 
     global __cuFileDriverSetPollMode
-    data["__cuFileDriverSetPollMode"] = <_cyb_intptr_t>__cuFileDriverSetPollMode
+    data["__cuFileDriverSetPollMode"] = <intptr_t>__cuFileDriverSetPollMode
 
     global __cuFileDriverSetMaxDirectIOSize
-    data["__cuFileDriverSetMaxDirectIOSize"] = <_cyb_intptr_t>__cuFileDriverSetMaxDirectIOSize
+    data["__cuFileDriverSetMaxDirectIOSize"] = <intptr_t>__cuFileDriverSetMaxDirectIOSize
 
     global __cuFileDriverSetMaxCacheSize
-    data["__cuFileDriverSetMaxCacheSize"] = <_cyb_intptr_t>__cuFileDriverSetMaxCacheSize
+    data["__cuFileDriverSetMaxCacheSize"] = <intptr_t>__cuFileDriverSetMaxCacheSize
 
     global __cuFileDriverSetMaxPinnedMemSize
-    data["__cuFileDriverSetMaxPinnedMemSize"] = <_cyb_intptr_t>__cuFileDriverSetMaxPinnedMemSize
+    data["__cuFileDriverSetMaxPinnedMemSize"] = <intptr_t>__cuFileDriverSetMaxPinnedMemSize
 
     global __cuFileBatchIOSetUp
-    data["__cuFileBatchIOSetUp"] = <_cyb_intptr_t>__cuFileBatchIOSetUp
+    data["__cuFileBatchIOSetUp"] = <intptr_t>__cuFileBatchIOSetUp
 
     global __cuFileBatchIOSubmit
-    data["__cuFileBatchIOSubmit"] = <_cyb_intptr_t>__cuFileBatchIOSubmit
+    data["__cuFileBatchIOSubmit"] = <intptr_t>__cuFileBatchIOSubmit
 
     global __cuFileBatchIOGetStatus
-    data["__cuFileBatchIOGetStatus"] = <_cyb_intptr_t>__cuFileBatchIOGetStatus
+    data["__cuFileBatchIOGetStatus"] = <intptr_t>__cuFileBatchIOGetStatus
 
     global __cuFileBatchIOCancel
-    data["__cuFileBatchIOCancel"] = <_cyb_intptr_t>__cuFileBatchIOCancel
+    data["__cuFileBatchIOCancel"] = <intptr_t>__cuFileBatchIOCancel
 
     global __cuFileBatchIODestroy
-    data["__cuFileBatchIODestroy"] = <_cyb_intptr_t>__cuFileBatchIODestroy
+    data["__cuFileBatchIODestroy"] = <intptr_t>__cuFileBatchIODestroy
 
     global __cuFileReadAsync
-    data["__cuFileReadAsync"] = <_cyb_intptr_t>__cuFileReadAsync
+    data["__cuFileReadAsync"] = <intptr_t>__cuFileReadAsync
 
     global __cuFileWriteAsync
-    data["__cuFileWriteAsync"] = <_cyb_intptr_t>__cuFileWriteAsync
+    data["__cuFileWriteAsync"] = <intptr_t>__cuFileWriteAsync
 
     global __cuFileStreamRegister
-    data["__cuFileStreamRegister"] = <_cyb_intptr_t>__cuFileStreamRegister
+    data["__cuFileStreamRegister"] = <intptr_t>__cuFileStreamRegister
 
     global __cuFileStreamDeregister
-    data["__cuFileStreamDeregister"] = <_cyb_intptr_t>__cuFileStreamDeregister
+    data["__cuFileStreamDeregister"] = <intptr_t>__cuFileStreamDeregister
 
     global __cuFileGetVersion
-    data["__cuFileGetVersion"] = <_cyb_intptr_t>__cuFileGetVersion
+    data["__cuFileGetVersion"] = <intptr_t>__cuFileGetVersion
 
     global __cuFileGetParameterSizeT
-    data["__cuFileGetParameterSizeT"] = <_cyb_intptr_t>__cuFileGetParameterSizeT
+    data["__cuFileGetParameterSizeT"] = <intptr_t>__cuFileGetParameterSizeT
 
     global __cuFileGetParameterBool
-    data["__cuFileGetParameterBool"] = <_cyb_intptr_t>__cuFileGetParameterBool
+    data["__cuFileGetParameterBool"] = <intptr_t>__cuFileGetParameterBool
 
     global __cuFileGetParameterString
-    data["__cuFileGetParameterString"] = <_cyb_intptr_t>__cuFileGetParameterString
+    data["__cuFileGetParameterString"] = <intptr_t>__cuFileGetParameterString
 
     global __cuFileSetParameterSizeT
-    data["__cuFileSetParameterSizeT"] = <_cyb_intptr_t>__cuFileSetParameterSizeT
+    data["__cuFileSetParameterSizeT"] = <intptr_t>__cuFileSetParameterSizeT
 
     global __cuFileSetParameterBool
-    data["__cuFileSetParameterBool"] = <_cyb_intptr_t>__cuFileSetParameterBool
+    data["__cuFileSetParameterBool"] = <intptr_t>__cuFileSetParameterBool
 
     global __cuFileSetParameterString
-    data["__cuFileSetParameterString"] = <_cyb_intptr_t>__cuFileSetParameterString
+    data["__cuFileSetParameterString"] = <intptr_t>__cuFileSetParameterString
 
     global __cuFileGetParameterMinMaxValue
-    data["__cuFileGetParameterMinMaxValue"] = <_cyb_intptr_t>__cuFileGetParameterMinMaxValue
+    data["__cuFileGetParameterMinMaxValue"] = <intptr_t>__cuFileGetParameterMinMaxValue
 
     global __cuFileSetStatsLevel
-    data["__cuFileSetStatsLevel"] = <_cyb_intptr_t>__cuFileSetStatsLevel
+    data["__cuFileSetStatsLevel"] = <intptr_t>__cuFileSetStatsLevel
 
     global __cuFileGetStatsLevel
-    data["__cuFileGetStatsLevel"] = <_cyb_intptr_t>__cuFileGetStatsLevel
+    data["__cuFileGetStatsLevel"] = <intptr_t>__cuFileGetStatsLevel
 
     global __cuFileStatsStart
-    data["__cuFileStatsStart"] = <_cyb_intptr_t>__cuFileStatsStart
+    data["__cuFileStatsStart"] = <intptr_t>__cuFileStatsStart
 
     global __cuFileStatsStop
-    data["__cuFileStatsStop"] = <_cyb_intptr_t>__cuFileStatsStop
+    data["__cuFileStatsStop"] = <intptr_t>__cuFileStatsStop
 
     global __cuFileStatsReset
-    data["__cuFileStatsReset"] = <_cyb_intptr_t>__cuFileStatsReset
+    data["__cuFileStatsReset"] = <intptr_t>__cuFileStatsReset
 
     global __cuFileGetStatsL1
-    data["__cuFileGetStatsL1"] = <_cyb_intptr_t>__cuFileGetStatsL1
+    data["__cuFileGetStatsL1"] = <intptr_t>__cuFileGetStatsL1
 
     global __cuFileGetStatsL2
-    data["__cuFileGetStatsL2"] = <_cyb_intptr_t>__cuFileGetStatsL2
+    data["__cuFileGetStatsL2"] = <intptr_t>__cuFileGetStatsL2
 
     global __cuFileGetStatsL3
-    data["__cuFileGetStatsL3"] = <_cyb_intptr_t>__cuFileGetStatsL3
+    data["__cuFileGetStatsL3"] = <intptr_t>__cuFileGetStatsL3
 
     global __cuFileGetBARSizeInKB
-    data["__cuFileGetBARSizeInKB"] = <_cyb_intptr_t>__cuFileGetBARSizeInKB
+    data["__cuFileGetBARSizeInKB"] = <intptr_t>__cuFileGetBARSizeInKB
 
     global __cuFileSetParameterPosixPoolSlabArray
-    data["__cuFileSetParameterPosixPoolSlabArray"] = <_cyb_intptr_t>__cuFileSetParameterPosixPoolSlabArray
+    data["__cuFileSetParameterPosixPoolSlabArray"] = <intptr_t>__cuFileSetParameterPosixPoolSlabArray
 
     global __cuFileGetParameterPosixPoolSlabArray
-    data["__cuFileGetParameterPosixPoolSlabArray"] = <_cyb_intptr_t>__cuFileGetParameterPosixPoolSlabArray
+    data["__cuFileGetParameterPosixPoolSlabArray"] = <intptr_t>__cuFileGetParameterPosixPoolSlabArray
 
     global __cuFileReadv
-    data["__cuFileReadv"] = <_cyb_intptr_t>__cuFileReadv
+    data["__cuFileReadv"] = <intptr_t>__cuFileReadv
 
     global __cuFileWritev
-    data["__cuFileWritev"] = <_cyb_intptr_t>__cuFileWritev
+    data["__cuFileWritev"] = <intptr_t>__cuFileWritev
     _cyb_func_ptrs = data
     return data
 
@@ -717,13 +717,13 @@ cdef CUfileError_t _cuFileDriverGetProperties(CUfileDrvProps_t* props) except?<C
         props)
 
 
-cdef CUfileError_t _cuFileDriverSetPollMode(cpp_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
+cdef CUfileError_t _cuFileDriverSetPollMode(_cyb_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
     global __cuFileDriverSetPollMode
     _check_or_init_cufile()
     if __cuFileDriverSetPollMode == NULL:
         with gil:
             raise FunctionNotFoundError("function cuFileDriverSetPollMode is not found")
-    return (<CUfileError_t (*)(cpp_bool, size_t) noexcept nogil>__cuFileDriverSetPollMode)(
+    return (<CUfileError_t (*)(_cyb_bool, size_t) noexcept nogil>__cuFileDriverSetPollMode)(
         poll, poll_threshold_size)
 
 
@@ -868,13 +868,13 @@ cdef CUfileError_t _cuFileGetParameterSizeT(CUFileSizeTConfigParameter_t param,
         param, value)
 
 
-cdef CUfileError_t _cuFileGetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
+cdef CUfileError_t _cuFileGetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
     global __cuFileGetParameterBool
     _check_or_init_cufile()
     if __cuFileGetParameterBool == NULL:
         with gil:
             raise FunctionNotFoundError("function cuFileGetParameterBool is not found")
-    return (<CUfileError_t (*)(CUFileBoolConfigParameter_t, cpp_bool*) noexcept nogil>__cuFileGetParameterBool)(
+    return (<CUfileError_t (*)(CUFileBoolConfigParameter_t, _cyb_bool*) noexcept nogil>__cuFileGetParameterBool)(
         param, value)
 
 
@@ -898,13 +898,13 @@ cdef CUfileError_t _cuFileSetParameterSizeT(CUFileSizeTConfigParameter_t param,
         param, value)
 
 
-cdef CUfileError_t _cuFileSetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
+cdef CUfileError_t _cuFileSetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
     global __cuFileSetParameterBool
     _check_or_init_cufile()
     if __cuFileSetParameterBool == NULL:
         with gil:
             raise FunctionNotFoundError("function cuFileSetParameterBool is not found")
-    return (<CUfileError_t (*)(CUFileBoolConfigParameter_t, cpp_bool) noexcept nogil>__cuFileSetParameterBool)(
+    return (<CUfileError_t (*)(CUFileBoolConfigParameter_t, _cyb_bool) noexcept nogil>__cuFileSetParameterBool)(
         param, value)
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/driver.pxd b/cuda_bindings/cuda/bindings/_internal/driver.pxd
index 2996ff8d559..d44e4b612bb 100644
--- a/cuda_bindings/cuda/bindings/_internal/driver.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/driver.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=d0aeaada84c702fe1713aefa6074c6d8154cfe31f48f0371403d941c41205d6b
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=b45f017467bf91c9ba21a48072bd362bdf84509c674379435823618c2aebc954
 from ..cydriver cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/driver_linux.pyx b/cuda_bindings/cuda/bindings/_internal/driver_linux.pyx
index 9473f1d6afb..6fc1ca20c77 100644
--- a/cuda_bindings/cuda/bindings/_internal/driver_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/driver_linux.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1e5b152412ef388b8a785b8362155fef84faecf8a3575f95461cedb918b08fb0
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f23c5b6833163c19813f5a513216d2a4192b545a5ae8a47ffe7c95ebbc9bdbaf
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -44,7 +43,7 @@ cdef extern from * nogil:
 cdef extern from "<dlfcn.h>":
     void* _cyb_dlsym "dlsym"(void*, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport intptr_t
 
 from os import getenv as _cyb_getenv
 import threading as _cyb_threading
@@ -2164,25 +2163,25 @@ cdef int _init_driver() except -1 nogil:
         cuGetProcAddress_v2('cuStreamBeginRecaptureToGraph', <void **>&__cuStreamBeginRecaptureToGraph, 13030, ptds_mode, NULL)
 
         global __cuDeviceGetFabricClusterUuid
-        cuGetProcAddress_v2('cuDeviceGetFabricClusterUuid', <void **>&__cuDeviceGetFabricClusterUuid, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuDeviceGetFabricClusterUuid', <void **>&__cuDeviceGetFabricClusterUuid, 13041, ptds_mode, NULL)
 
         global __cuDeviceGetCliqueCount
-        cuGetProcAddress_v2('cuDeviceGetCliqueCount', <void **>&__cuDeviceGetCliqueCount, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuDeviceGetCliqueCount', <void **>&__cuDeviceGetCliqueCount, 13041, ptds_mode, NULL)
 
         global __cuDeviceGetCliqueInfo
-        cuGetProcAddress_v2('cuDeviceGetCliqueInfo', <void **>&__cuDeviceGetCliqueInfo, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuDeviceGetCliqueInfo', <void **>&__cuDeviceGetCliqueInfo, 13041, ptds_mode, NULL)
 
         global __cuMemGetLocationInfo
-        cuGetProcAddress_v2('cuMemGetLocationInfo', <void **>&__cuMemGetLocationInfo, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuMemGetLocationInfo', <void **>&__cuMemGetLocationInfo, 13041, ptds_mode, NULL)
 
         global __cuGraphAddNode_v3
-        cuGetProcAddress_v2('cuGraphAddNode', <void **>&__cuGraphAddNode_v3, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuGraphAddNode', <void **>&__cuGraphAddNode_v3, 13041, ptds_mode, NULL)
 
         global __cuGraphNodeSetParams_v2
-        cuGetProcAddress_v2('cuGraphNodeSetParams', <void **>&__cuGraphNodeSetParams_v2, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuGraphNodeSetParams', <void **>&__cuGraphNodeSetParams_v2, 13041, ptds_mode, NULL)
 
         global __cuCheckpointOperationComplete
-        cuGetProcAddress_v2('cuCheckpointOperationComplete', <void **>&__cuCheckpointOperationComplete, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuCheckpointOperationComplete', <void **>&__cuCheckpointOperationComplete, 13041, ptds_mode, NULL)
 
         _cyb_atomic_int_store(<int *>&_cyb___py_driver_init, 1)
         return 0
@@ -2202,1576 +2201,1576 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_driver()
     cdef dict data = {}
     global __cuGetErrorString
-    data["__cuGetErrorString"] = <_cyb_intptr_t>__cuGetErrorString
+    data["__cuGetErrorString"] = <intptr_t>__cuGetErrorString
 
     global __cuGetErrorName
-    data["__cuGetErrorName"] = <_cyb_intptr_t>__cuGetErrorName
+    data["__cuGetErrorName"] = <intptr_t>__cuGetErrorName
 
     global __cuInit
-    data["__cuInit"] = <_cyb_intptr_t>__cuInit
+    data["__cuInit"] = <intptr_t>__cuInit
 
     global __cuDriverGetVersion
-    data["__cuDriverGetVersion"] = <_cyb_intptr_t>__cuDriverGetVersion
+    data["__cuDriverGetVersion"] = <intptr_t>__cuDriverGetVersion
 
     global __cuDeviceGet
-    data["__cuDeviceGet"] = <_cyb_intptr_t>__cuDeviceGet
+    data["__cuDeviceGet"] = <intptr_t>__cuDeviceGet
 
     global __cuDeviceGetCount
-    data["__cuDeviceGetCount"] = <_cyb_intptr_t>__cuDeviceGetCount
+    data["__cuDeviceGetCount"] = <intptr_t>__cuDeviceGetCount
 
     global __cuDeviceGetName
-    data["__cuDeviceGetName"] = <_cyb_intptr_t>__cuDeviceGetName
+    data["__cuDeviceGetName"] = <intptr_t>__cuDeviceGetName
 
     global __cuDeviceGetUuid_v2
-    data["__cuDeviceGetUuid_v2"] = <_cyb_intptr_t>__cuDeviceGetUuid_v2
+    data["__cuDeviceGetUuid_v2"] = <intptr_t>__cuDeviceGetUuid_v2
 
     global __cuDeviceGetLuid
-    data["__cuDeviceGetLuid"] = <_cyb_intptr_t>__cuDeviceGetLuid
+    data["__cuDeviceGetLuid"] = <intptr_t>__cuDeviceGetLuid
 
     global __cuDeviceTotalMem_v2
-    data["__cuDeviceTotalMem_v2"] = <_cyb_intptr_t>__cuDeviceTotalMem_v2
+    data["__cuDeviceTotalMem_v2"] = <intptr_t>__cuDeviceTotalMem_v2
 
     global __cuDeviceGetTexture1DLinearMaxWidth
-    data["__cuDeviceGetTexture1DLinearMaxWidth"] = <_cyb_intptr_t>__cuDeviceGetTexture1DLinearMaxWidth
+    data["__cuDeviceGetTexture1DLinearMaxWidth"] = <intptr_t>__cuDeviceGetTexture1DLinearMaxWidth
 
     global __cuDeviceGetAttribute
-    data["__cuDeviceGetAttribute"] = <_cyb_intptr_t>__cuDeviceGetAttribute
+    data["__cuDeviceGetAttribute"] = <intptr_t>__cuDeviceGetAttribute
 
     global __cuDeviceGetNvSciSyncAttributes
-    data["__cuDeviceGetNvSciSyncAttributes"] = <_cyb_intptr_t>__cuDeviceGetNvSciSyncAttributes
+    data["__cuDeviceGetNvSciSyncAttributes"] = <intptr_t>__cuDeviceGetNvSciSyncAttributes
 
     global __cuDeviceSetMemPool
-    data["__cuDeviceSetMemPool"] = <_cyb_intptr_t>__cuDeviceSetMemPool
+    data["__cuDeviceSetMemPool"] = <intptr_t>__cuDeviceSetMemPool
 
     global __cuDeviceGetMemPool
-    data["__cuDeviceGetMemPool"] = <_cyb_intptr_t>__cuDeviceGetMemPool
+    data["__cuDeviceGetMemPool"] = <intptr_t>__cuDeviceGetMemPool
 
     global __cuDeviceGetDefaultMemPool
-    data["__cuDeviceGetDefaultMemPool"] = <_cyb_intptr_t>__cuDeviceGetDefaultMemPool
+    data["__cuDeviceGetDefaultMemPool"] = <intptr_t>__cuDeviceGetDefaultMemPool
 
     global __cuDeviceGetExecAffinitySupport
-    data["__cuDeviceGetExecAffinitySupport"] = <_cyb_intptr_t>__cuDeviceGetExecAffinitySupport
+    data["__cuDeviceGetExecAffinitySupport"] = <intptr_t>__cuDeviceGetExecAffinitySupport
 
     global __cuFlushGPUDirectRDMAWrites
-    data["__cuFlushGPUDirectRDMAWrites"] = <_cyb_intptr_t>__cuFlushGPUDirectRDMAWrites
+    data["__cuFlushGPUDirectRDMAWrites"] = <intptr_t>__cuFlushGPUDirectRDMAWrites
 
     global __cuDeviceGetProperties
-    data["__cuDeviceGetProperties"] = <_cyb_intptr_t>__cuDeviceGetProperties
+    data["__cuDeviceGetProperties"] = <intptr_t>__cuDeviceGetProperties
 
     global __cuDeviceComputeCapability
-    data["__cuDeviceComputeCapability"] = <_cyb_intptr_t>__cuDeviceComputeCapability
+    data["__cuDeviceComputeCapability"] = <intptr_t>__cuDeviceComputeCapability
 
     global __cuDevicePrimaryCtxRetain
-    data["__cuDevicePrimaryCtxRetain"] = <_cyb_intptr_t>__cuDevicePrimaryCtxRetain
+    data["__cuDevicePrimaryCtxRetain"] = <intptr_t>__cuDevicePrimaryCtxRetain
 
     global __cuDevicePrimaryCtxRelease_v2
-    data["__cuDevicePrimaryCtxRelease_v2"] = <_cyb_intptr_t>__cuDevicePrimaryCtxRelease_v2
+    data["__cuDevicePrimaryCtxRelease_v2"] = <intptr_t>__cuDevicePrimaryCtxRelease_v2
 
     global __cuDevicePrimaryCtxSetFlags_v2
-    data["__cuDevicePrimaryCtxSetFlags_v2"] = <_cyb_intptr_t>__cuDevicePrimaryCtxSetFlags_v2
+    data["__cuDevicePrimaryCtxSetFlags_v2"] = <intptr_t>__cuDevicePrimaryCtxSetFlags_v2
 
     global __cuDevicePrimaryCtxGetState
-    data["__cuDevicePrimaryCtxGetState"] = <_cyb_intptr_t>__cuDevicePrimaryCtxGetState
+    data["__cuDevicePrimaryCtxGetState"] = <intptr_t>__cuDevicePrimaryCtxGetState
 
     global __cuDevicePrimaryCtxReset_v2
-    data["__cuDevicePrimaryCtxReset_v2"] = <_cyb_intptr_t>__cuDevicePrimaryCtxReset_v2
+    data["__cuDevicePrimaryCtxReset_v2"] = <intptr_t>__cuDevicePrimaryCtxReset_v2
 
     global __cuCtxCreate_v2
-    data["__cuCtxCreate_v2"] = <_cyb_intptr_t>__cuCtxCreate_v2
+    data["__cuCtxCreate_v2"] = <intptr_t>__cuCtxCreate_v2
 
     global __cuCtxCreate_v3
-    data["__cuCtxCreate_v3"] = <_cyb_intptr_t>__cuCtxCreate_v3
+    data["__cuCtxCreate_v3"] = <intptr_t>__cuCtxCreate_v3
 
     global __cuCtxCreate_v4
-    data["__cuCtxCreate_v4"] = <_cyb_intptr_t>__cuCtxCreate_v4
+    data["__cuCtxCreate_v4"] = <intptr_t>__cuCtxCreate_v4
 
     global __cuCtxDestroy_v2
-    data["__cuCtxDestroy_v2"] = <_cyb_intptr_t>__cuCtxDestroy_v2
+    data["__cuCtxDestroy_v2"] = <intptr_t>__cuCtxDestroy_v2
 
     global __cuCtxPushCurrent_v2
-    data["__cuCtxPushCurrent_v2"] = <_cyb_intptr_t>__cuCtxPushCurrent_v2
+    data["__cuCtxPushCurrent_v2"] = <intptr_t>__cuCtxPushCurrent_v2
 
     global __cuCtxPopCurrent_v2
-    data["__cuCtxPopCurrent_v2"] = <_cyb_intptr_t>__cuCtxPopCurrent_v2
+    data["__cuCtxPopCurrent_v2"] = <intptr_t>__cuCtxPopCurrent_v2
 
     global __cuCtxSetCurrent
-    data["__cuCtxSetCurrent"] = <_cyb_intptr_t>__cuCtxSetCurrent
+    data["__cuCtxSetCurrent"] = <intptr_t>__cuCtxSetCurrent
 
     global __cuCtxGetCurrent
-    data["__cuCtxGetCurrent"] = <_cyb_intptr_t>__cuCtxGetCurrent
+    data["__cuCtxGetCurrent"] = <intptr_t>__cuCtxGetCurrent
 
     global __cuCtxGetDevice
-    data["__cuCtxGetDevice"] = <_cyb_intptr_t>__cuCtxGetDevice
+    data["__cuCtxGetDevice"] = <intptr_t>__cuCtxGetDevice
 
     global __cuCtxGetFlags
-    data["__cuCtxGetFlags"] = <_cyb_intptr_t>__cuCtxGetFlags
+    data["__cuCtxGetFlags"] = <intptr_t>__cuCtxGetFlags
 
     global __cuCtxSetFlags
-    data["__cuCtxSetFlags"] = <_cyb_intptr_t>__cuCtxSetFlags
+    data["__cuCtxSetFlags"] = <intptr_t>__cuCtxSetFlags
 
     global __cuCtxGetId
-    data["__cuCtxGetId"] = <_cyb_intptr_t>__cuCtxGetId
+    data["__cuCtxGetId"] = <intptr_t>__cuCtxGetId
 
     global __cuCtxSynchronize
-    data["__cuCtxSynchronize"] = <_cyb_intptr_t>__cuCtxSynchronize
+    data["__cuCtxSynchronize"] = <intptr_t>__cuCtxSynchronize
 
     global __cuCtxSetLimit
-    data["__cuCtxSetLimit"] = <_cyb_intptr_t>__cuCtxSetLimit
+    data["__cuCtxSetLimit"] = <intptr_t>__cuCtxSetLimit
 
     global __cuCtxGetLimit
-    data["__cuCtxGetLimit"] = <_cyb_intptr_t>__cuCtxGetLimit
+    data["__cuCtxGetLimit"] = <intptr_t>__cuCtxGetLimit
 
     global __cuCtxGetCacheConfig
-    data["__cuCtxGetCacheConfig"] = <_cyb_intptr_t>__cuCtxGetCacheConfig
+    data["__cuCtxGetCacheConfig"] = <intptr_t>__cuCtxGetCacheConfig
 
     global __cuCtxSetCacheConfig
-    data["__cuCtxSetCacheConfig"] = <_cyb_intptr_t>__cuCtxSetCacheConfig
+    data["__cuCtxSetCacheConfig"] = <intptr_t>__cuCtxSetCacheConfig
 
     global __cuCtxGetApiVersion
-    data["__cuCtxGetApiVersion"] = <_cyb_intptr_t>__cuCtxGetApiVersion
+    data["__cuCtxGetApiVersion"] = <intptr_t>__cuCtxGetApiVersion
 
     global __cuCtxGetStreamPriorityRange
-    data["__cuCtxGetStreamPriorityRange"] = <_cyb_intptr_t>__cuCtxGetStreamPriorityRange
+    data["__cuCtxGetStreamPriorityRange"] = <intptr_t>__cuCtxGetStreamPriorityRange
 
     global __cuCtxResetPersistingL2Cache
-    data["__cuCtxResetPersistingL2Cache"] = <_cyb_intptr_t>__cuCtxResetPersistingL2Cache
+    data["__cuCtxResetPersistingL2Cache"] = <intptr_t>__cuCtxResetPersistingL2Cache
 
     global __cuCtxGetExecAffinity
-    data["__cuCtxGetExecAffinity"] = <_cyb_intptr_t>__cuCtxGetExecAffinity
+    data["__cuCtxGetExecAffinity"] = <intptr_t>__cuCtxGetExecAffinity
 
     global __cuCtxRecordEvent
-    data["__cuCtxRecordEvent"] = <_cyb_intptr_t>__cuCtxRecordEvent
+    data["__cuCtxRecordEvent"] = <intptr_t>__cuCtxRecordEvent
 
     global __cuCtxWaitEvent
-    data["__cuCtxWaitEvent"] = <_cyb_intptr_t>__cuCtxWaitEvent
+    data["__cuCtxWaitEvent"] = <intptr_t>__cuCtxWaitEvent
 
     global __cuCtxAttach
-    data["__cuCtxAttach"] = <_cyb_intptr_t>__cuCtxAttach
+    data["__cuCtxAttach"] = <intptr_t>__cuCtxAttach
 
     global __cuCtxDetach
-    data["__cuCtxDetach"] = <_cyb_intptr_t>__cuCtxDetach
+    data["__cuCtxDetach"] = <intptr_t>__cuCtxDetach
 
     global __cuCtxGetSharedMemConfig
-    data["__cuCtxGetSharedMemConfig"] = <_cyb_intptr_t>__cuCtxGetSharedMemConfig
+    data["__cuCtxGetSharedMemConfig"] = <intptr_t>__cuCtxGetSharedMemConfig
 
     global __cuCtxSetSharedMemConfig
-    data["__cuCtxSetSharedMemConfig"] = <_cyb_intptr_t>__cuCtxSetSharedMemConfig
+    data["__cuCtxSetSharedMemConfig"] = <intptr_t>__cuCtxSetSharedMemConfig
 
     global __cuModuleLoad
-    data["__cuModuleLoad"] = <_cyb_intptr_t>__cuModuleLoad
+    data["__cuModuleLoad"] = <intptr_t>__cuModuleLoad
 
     global __cuModuleLoadData
-    data["__cuModuleLoadData"] = <_cyb_intptr_t>__cuModuleLoadData
+    data["__cuModuleLoadData"] = <intptr_t>__cuModuleLoadData
 
     global __cuModuleLoadDataEx
-    data["__cuModuleLoadDataEx"] = <_cyb_intptr_t>__cuModuleLoadDataEx
+    data["__cuModuleLoadDataEx"] = <intptr_t>__cuModuleLoadDataEx
 
     global __cuModuleLoadFatBinary
-    data["__cuModuleLoadFatBinary"] = <_cyb_intptr_t>__cuModuleLoadFatBinary
+    data["__cuModuleLoadFatBinary"] = <intptr_t>__cuModuleLoadFatBinary
 
     global __cuModuleUnload
-    data["__cuModuleUnload"] = <_cyb_intptr_t>__cuModuleUnload
+    data["__cuModuleUnload"] = <intptr_t>__cuModuleUnload
 
     global __cuModuleGetLoadingMode
-    data["__cuModuleGetLoadingMode"] = <_cyb_intptr_t>__cuModuleGetLoadingMode
+    data["__cuModuleGetLoadingMode"] = <intptr_t>__cuModuleGetLoadingMode
 
     global __cuModuleGetFunction
-    data["__cuModuleGetFunction"] = <_cyb_intptr_t>__cuModuleGetFunction
+    data["__cuModuleGetFunction"] = <intptr_t>__cuModuleGetFunction
 
     global __cuModuleGetFunctionCount
-    data["__cuModuleGetFunctionCount"] = <_cyb_intptr_t>__cuModuleGetFunctionCount
+    data["__cuModuleGetFunctionCount"] = <intptr_t>__cuModuleGetFunctionCount
 
     global __cuModuleEnumerateFunctions
-    data["__cuModuleEnumerateFunctions"] = <_cyb_intptr_t>__cuModuleEnumerateFunctions
+    data["__cuModuleEnumerateFunctions"] = <intptr_t>__cuModuleEnumerateFunctions
 
     global __cuModuleGetGlobal_v2
-    data["__cuModuleGetGlobal_v2"] = <_cyb_intptr_t>__cuModuleGetGlobal_v2
+    data["__cuModuleGetGlobal_v2"] = <intptr_t>__cuModuleGetGlobal_v2
 
     global __cuLinkCreate_v2
-    data["__cuLinkCreate_v2"] = <_cyb_intptr_t>__cuLinkCreate_v2
+    data["__cuLinkCreate_v2"] = <intptr_t>__cuLinkCreate_v2
 
     global __cuLinkAddData_v2
-    data["__cuLinkAddData_v2"] = <_cyb_intptr_t>__cuLinkAddData_v2
+    data["__cuLinkAddData_v2"] = <intptr_t>__cuLinkAddData_v2
 
     global __cuLinkAddFile_v2
-    data["__cuLinkAddFile_v2"] = <_cyb_intptr_t>__cuLinkAddFile_v2
+    data["__cuLinkAddFile_v2"] = <intptr_t>__cuLinkAddFile_v2
 
     global __cuLinkComplete
-    data["__cuLinkComplete"] = <_cyb_intptr_t>__cuLinkComplete
+    data["__cuLinkComplete"] = <intptr_t>__cuLinkComplete
 
     global __cuLinkDestroy
-    data["__cuLinkDestroy"] = <_cyb_intptr_t>__cuLinkDestroy
+    data["__cuLinkDestroy"] = <intptr_t>__cuLinkDestroy
 
     global __cuModuleGetTexRef
-    data["__cuModuleGetTexRef"] = <_cyb_intptr_t>__cuModuleGetTexRef
+    data["__cuModuleGetTexRef"] = <intptr_t>__cuModuleGetTexRef
 
     global __cuModuleGetSurfRef
-    data["__cuModuleGetSurfRef"] = <_cyb_intptr_t>__cuModuleGetSurfRef
+    data["__cuModuleGetSurfRef"] = <intptr_t>__cuModuleGetSurfRef
 
     global __cuLibraryLoadData
-    data["__cuLibraryLoadData"] = <_cyb_intptr_t>__cuLibraryLoadData
+    data["__cuLibraryLoadData"] = <intptr_t>__cuLibraryLoadData
 
     global __cuLibraryLoadFromFile
-    data["__cuLibraryLoadFromFile"] = <_cyb_intptr_t>__cuLibraryLoadFromFile
+    data["__cuLibraryLoadFromFile"] = <intptr_t>__cuLibraryLoadFromFile
 
     global __cuLibraryUnload
-    data["__cuLibraryUnload"] = <_cyb_intptr_t>__cuLibraryUnload
+    data["__cuLibraryUnload"] = <intptr_t>__cuLibraryUnload
 
     global __cuLibraryGetKernel
-    data["__cuLibraryGetKernel"] = <_cyb_intptr_t>__cuLibraryGetKernel
+    data["__cuLibraryGetKernel"] = <intptr_t>__cuLibraryGetKernel
 
     global __cuLibraryGetKernelCount
-    data["__cuLibraryGetKernelCount"] = <_cyb_intptr_t>__cuLibraryGetKernelCount
+    data["__cuLibraryGetKernelCount"] = <intptr_t>__cuLibraryGetKernelCount
 
     global __cuLibraryEnumerateKernels
-    data["__cuLibraryEnumerateKernels"] = <_cyb_intptr_t>__cuLibraryEnumerateKernels
+    data["__cuLibraryEnumerateKernels"] = <intptr_t>__cuLibraryEnumerateKernels
 
     global __cuLibraryGetModule
-    data["__cuLibraryGetModule"] = <_cyb_intptr_t>__cuLibraryGetModule
+    data["__cuLibraryGetModule"] = <intptr_t>__cuLibraryGetModule
 
     global __cuKernelGetFunction
-    data["__cuKernelGetFunction"] = <_cyb_intptr_t>__cuKernelGetFunction
+    data["__cuKernelGetFunction"] = <intptr_t>__cuKernelGetFunction
 
     global __cuKernelGetLibrary
-    data["__cuKernelGetLibrary"] = <_cyb_intptr_t>__cuKernelGetLibrary
+    data["__cuKernelGetLibrary"] = <intptr_t>__cuKernelGetLibrary
 
     global __cuLibraryGetGlobal
-    data["__cuLibraryGetGlobal"] = <_cyb_intptr_t>__cuLibraryGetGlobal
+    data["__cuLibraryGetGlobal"] = <intptr_t>__cuLibraryGetGlobal
 
     global __cuLibraryGetManaged
-    data["__cuLibraryGetManaged"] = <_cyb_intptr_t>__cuLibraryGetManaged
+    data["__cuLibraryGetManaged"] = <intptr_t>__cuLibraryGetManaged
 
     global __cuLibraryGetUnifiedFunction
-    data["__cuLibraryGetUnifiedFunction"] = <_cyb_intptr_t>__cuLibraryGetUnifiedFunction
+    data["__cuLibraryGetUnifiedFunction"] = <intptr_t>__cuLibraryGetUnifiedFunction
 
     global __cuKernelGetAttribute
-    data["__cuKernelGetAttribute"] = <_cyb_intptr_t>__cuKernelGetAttribute
+    data["__cuKernelGetAttribute"] = <intptr_t>__cuKernelGetAttribute
 
     global __cuKernelSetAttribute
-    data["__cuKernelSetAttribute"] = <_cyb_intptr_t>__cuKernelSetAttribute
+    data["__cuKernelSetAttribute"] = <intptr_t>__cuKernelSetAttribute
 
     global __cuKernelSetCacheConfig
-    data["__cuKernelSetCacheConfig"] = <_cyb_intptr_t>__cuKernelSetCacheConfig
+    data["__cuKernelSetCacheConfig"] = <intptr_t>__cuKernelSetCacheConfig
 
     global __cuKernelGetName
-    data["__cuKernelGetName"] = <_cyb_intptr_t>__cuKernelGetName
+    data["__cuKernelGetName"] = <intptr_t>__cuKernelGetName
 
     global __cuKernelGetParamInfo
-    data["__cuKernelGetParamInfo"] = <_cyb_intptr_t>__cuKernelGetParamInfo
+    data["__cuKernelGetParamInfo"] = <intptr_t>__cuKernelGetParamInfo
 
     global __cuMemGetInfo_v2
-    data["__cuMemGetInfo_v2"] = <_cyb_intptr_t>__cuMemGetInfo_v2
+    data["__cuMemGetInfo_v2"] = <intptr_t>__cuMemGetInfo_v2
 
     global __cuMemAlloc_v2
-    data["__cuMemAlloc_v2"] = <_cyb_intptr_t>__cuMemAlloc_v2
+    data["__cuMemAlloc_v2"] = <intptr_t>__cuMemAlloc_v2
 
     global __cuMemAllocPitch_v2
-    data["__cuMemAllocPitch_v2"] = <_cyb_intptr_t>__cuMemAllocPitch_v2
+    data["__cuMemAllocPitch_v2"] = <intptr_t>__cuMemAllocPitch_v2
 
     global __cuMemFree_v2
-    data["__cuMemFree_v2"] = <_cyb_intptr_t>__cuMemFree_v2
+    data["__cuMemFree_v2"] = <intptr_t>__cuMemFree_v2
 
     global __cuMemGetAddressRange_v2
-    data["__cuMemGetAddressRange_v2"] = <_cyb_intptr_t>__cuMemGetAddressRange_v2
+    data["__cuMemGetAddressRange_v2"] = <intptr_t>__cuMemGetAddressRange_v2
 
     global __cuMemAllocHost_v2
-    data["__cuMemAllocHost_v2"] = <_cyb_intptr_t>__cuMemAllocHost_v2
+    data["__cuMemAllocHost_v2"] = <intptr_t>__cuMemAllocHost_v2
 
     global __cuMemFreeHost
-    data["__cuMemFreeHost"] = <_cyb_intptr_t>__cuMemFreeHost
+    data["__cuMemFreeHost"] = <intptr_t>__cuMemFreeHost
 
     global __cuMemHostAlloc
-    data["__cuMemHostAlloc"] = <_cyb_intptr_t>__cuMemHostAlloc
+    data["__cuMemHostAlloc"] = <intptr_t>__cuMemHostAlloc
 
     global __cuMemHostGetDevicePointer_v2
-    data["__cuMemHostGetDevicePointer_v2"] = <_cyb_intptr_t>__cuMemHostGetDevicePointer_v2
+    data["__cuMemHostGetDevicePointer_v2"] = <intptr_t>__cuMemHostGetDevicePointer_v2
 
     global __cuMemHostGetFlags
-    data["__cuMemHostGetFlags"] = <_cyb_intptr_t>__cuMemHostGetFlags
+    data["__cuMemHostGetFlags"] = <intptr_t>__cuMemHostGetFlags
 
     global __cuMemAllocManaged
-    data["__cuMemAllocManaged"] = <_cyb_intptr_t>__cuMemAllocManaged
+    data["__cuMemAllocManaged"] = <intptr_t>__cuMemAllocManaged
 
     global __cuDeviceRegisterAsyncNotification
-    data["__cuDeviceRegisterAsyncNotification"] = <_cyb_intptr_t>__cuDeviceRegisterAsyncNotification
+    data["__cuDeviceRegisterAsyncNotification"] = <intptr_t>__cuDeviceRegisterAsyncNotification
 
     global __cuDeviceUnregisterAsyncNotification
-    data["__cuDeviceUnregisterAsyncNotification"] = <_cyb_intptr_t>__cuDeviceUnregisterAsyncNotification
+    data["__cuDeviceUnregisterAsyncNotification"] = <intptr_t>__cuDeviceUnregisterAsyncNotification
 
     global __cuDeviceGetByPCIBusId
-    data["__cuDeviceGetByPCIBusId"] = <_cyb_intptr_t>__cuDeviceGetByPCIBusId
+    data["__cuDeviceGetByPCIBusId"] = <intptr_t>__cuDeviceGetByPCIBusId
 
     global __cuDeviceGetPCIBusId
-    data["__cuDeviceGetPCIBusId"] = <_cyb_intptr_t>__cuDeviceGetPCIBusId
+    data["__cuDeviceGetPCIBusId"] = <intptr_t>__cuDeviceGetPCIBusId
 
     global __cuIpcGetEventHandle
-    data["__cuIpcGetEventHandle"] = <_cyb_intptr_t>__cuIpcGetEventHandle
+    data["__cuIpcGetEventHandle"] = <intptr_t>__cuIpcGetEventHandle
 
     global __cuIpcOpenEventHandle
-    data["__cuIpcOpenEventHandle"] = <_cyb_intptr_t>__cuIpcOpenEventHandle
+    data["__cuIpcOpenEventHandle"] = <intptr_t>__cuIpcOpenEventHandle
 
     global __cuIpcGetMemHandle
-    data["__cuIpcGetMemHandle"] = <_cyb_intptr_t>__cuIpcGetMemHandle
+    data["__cuIpcGetMemHandle"] = <intptr_t>__cuIpcGetMemHandle
 
     global __cuIpcOpenMemHandle_v2
-    data["__cuIpcOpenMemHandle_v2"] = <_cyb_intptr_t>__cuIpcOpenMemHandle_v2
+    data["__cuIpcOpenMemHandle_v2"] = <intptr_t>__cuIpcOpenMemHandle_v2
 
     global __cuIpcCloseMemHandle
-    data["__cuIpcCloseMemHandle"] = <_cyb_intptr_t>__cuIpcCloseMemHandle
+    data["__cuIpcCloseMemHandle"] = <intptr_t>__cuIpcCloseMemHandle
 
     global __cuMemHostRegister_v2
-    data["__cuMemHostRegister_v2"] = <_cyb_intptr_t>__cuMemHostRegister_v2
+    data["__cuMemHostRegister_v2"] = <intptr_t>__cuMemHostRegister_v2
 
     global __cuMemHostUnregister
-    data["__cuMemHostUnregister"] = <_cyb_intptr_t>__cuMemHostUnregister
+    data["__cuMemHostUnregister"] = <intptr_t>__cuMemHostUnregister
 
     global __cuMemcpy
-    data["__cuMemcpy"] = <_cyb_intptr_t>__cuMemcpy
+    data["__cuMemcpy"] = <intptr_t>__cuMemcpy
 
     global __cuMemcpyPeer
-    data["__cuMemcpyPeer"] = <_cyb_intptr_t>__cuMemcpyPeer
+    data["__cuMemcpyPeer"] = <intptr_t>__cuMemcpyPeer
 
     global __cuMemcpyHtoD_v2
-    data["__cuMemcpyHtoD_v2"] = <_cyb_intptr_t>__cuMemcpyHtoD_v2
+    data["__cuMemcpyHtoD_v2"] = <intptr_t>__cuMemcpyHtoD_v2
 
     global __cuMemcpyDtoH_v2
-    data["__cuMemcpyDtoH_v2"] = <_cyb_intptr_t>__cuMemcpyDtoH_v2
+    data["__cuMemcpyDtoH_v2"] = <intptr_t>__cuMemcpyDtoH_v2
 
     global __cuMemcpyDtoD_v2
-    data["__cuMemcpyDtoD_v2"] = <_cyb_intptr_t>__cuMemcpyDtoD_v2
+    data["__cuMemcpyDtoD_v2"] = <intptr_t>__cuMemcpyDtoD_v2
 
     global __cuMemcpyDtoA_v2
-    data["__cuMemcpyDtoA_v2"] = <_cyb_intptr_t>__cuMemcpyDtoA_v2
+    data["__cuMemcpyDtoA_v2"] = <intptr_t>__cuMemcpyDtoA_v2
 
     global __cuMemcpyAtoD_v2
-    data["__cuMemcpyAtoD_v2"] = <_cyb_intptr_t>__cuMemcpyAtoD_v2
+    data["__cuMemcpyAtoD_v2"] = <intptr_t>__cuMemcpyAtoD_v2
 
     global __cuMemcpyHtoA_v2
-    data["__cuMemcpyHtoA_v2"] = <_cyb_intptr_t>__cuMemcpyHtoA_v2
+    data["__cuMemcpyHtoA_v2"] = <intptr_t>__cuMemcpyHtoA_v2
 
     global __cuMemcpyAtoH_v2
-    data["__cuMemcpyAtoH_v2"] = <_cyb_intptr_t>__cuMemcpyAtoH_v2
+    data["__cuMemcpyAtoH_v2"] = <intptr_t>__cuMemcpyAtoH_v2
 
     global __cuMemcpyAtoA_v2
-    data["__cuMemcpyAtoA_v2"] = <_cyb_intptr_t>__cuMemcpyAtoA_v2
+    data["__cuMemcpyAtoA_v2"] = <intptr_t>__cuMemcpyAtoA_v2
 
     global __cuMemcpy2D_v2
-    data["__cuMemcpy2D_v2"] = <_cyb_intptr_t>__cuMemcpy2D_v2
+    data["__cuMemcpy2D_v2"] = <intptr_t>__cuMemcpy2D_v2
 
     global __cuMemcpy2DUnaligned_v2
-    data["__cuMemcpy2DUnaligned_v2"] = <_cyb_intptr_t>__cuMemcpy2DUnaligned_v2
+    data["__cuMemcpy2DUnaligned_v2"] = <intptr_t>__cuMemcpy2DUnaligned_v2
 
     global __cuMemcpy3D_v2
-    data["__cuMemcpy3D_v2"] = <_cyb_intptr_t>__cuMemcpy3D_v2
+    data["__cuMemcpy3D_v2"] = <intptr_t>__cuMemcpy3D_v2
 
     global __cuMemcpy3DPeer
-    data["__cuMemcpy3DPeer"] = <_cyb_intptr_t>__cuMemcpy3DPeer
+    data["__cuMemcpy3DPeer"] = <intptr_t>__cuMemcpy3DPeer
 
     global __cuMemcpyAsync
-    data["__cuMemcpyAsync"] = <_cyb_intptr_t>__cuMemcpyAsync
+    data["__cuMemcpyAsync"] = <intptr_t>__cuMemcpyAsync
 
     global __cuMemcpyPeerAsync
-    data["__cuMemcpyPeerAsync"] = <_cyb_intptr_t>__cuMemcpyPeerAsync
+    data["__cuMemcpyPeerAsync"] = <intptr_t>__cuMemcpyPeerAsync
 
     global __cuMemcpyHtoDAsync_v2
-    data["__cuMemcpyHtoDAsync_v2"] = <_cyb_intptr_t>__cuMemcpyHtoDAsync_v2
+    data["__cuMemcpyHtoDAsync_v2"] = <intptr_t>__cuMemcpyHtoDAsync_v2
 
     global __cuMemcpyDtoHAsync_v2
-    data["__cuMemcpyDtoHAsync_v2"] = <_cyb_intptr_t>__cuMemcpyDtoHAsync_v2
+    data["__cuMemcpyDtoHAsync_v2"] = <intptr_t>__cuMemcpyDtoHAsync_v2
 
     global __cuMemcpyDtoDAsync_v2
-    data["__cuMemcpyDtoDAsync_v2"] = <_cyb_intptr_t>__cuMemcpyDtoDAsync_v2
+    data["__cuMemcpyDtoDAsync_v2"] = <intptr_t>__cuMemcpyDtoDAsync_v2
 
     global __cuMemcpyHtoAAsync_v2
-    data["__cuMemcpyHtoAAsync_v2"] = <_cyb_intptr_t>__cuMemcpyHtoAAsync_v2
+    data["__cuMemcpyHtoAAsync_v2"] = <intptr_t>__cuMemcpyHtoAAsync_v2
 
     global __cuMemcpyAtoHAsync_v2
-    data["__cuMemcpyAtoHAsync_v2"] = <_cyb_intptr_t>__cuMemcpyAtoHAsync_v2
+    data["__cuMemcpyAtoHAsync_v2"] = <intptr_t>__cuMemcpyAtoHAsync_v2
 
     global __cuMemcpy2DAsync_v2
-    data["__cuMemcpy2DAsync_v2"] = <_cyb_intptr_t>__cuMemcpy2DAsync_v2
+    data["__cuMemcpy2DAsync_v2"] = <intptr_t>__cuMemcpy2DAsync_v2
 
     global __cuMemcpy3DAsync_v2
-    data["__cuMemcpy3DAsync_v2"] = <_cyb_intptr_t>__cuMemcpy3DAsync_v2
+    data["__cuMemcpy3DAsync_v2"] = <intptr_t>__cuMemcpy3DAsync_v2
 
     global __cuMemcpy3DPeerAsync
-    data["__cuMemcpy3DPeerAsync"] = <_cyb_intptr_t>__cuMemcpy3DPeerAsync
+    data["__cuMemcpy3DPeerAsync"] = <intptr_t>__cuMemcpy3DPeerAsync
 
     global __cuMemsetD8_v2
-    data["__cuMemsetD8_v2"] = <_cyb_intptr_t>__cuMemsetD8_v2
+    data["__cuMemsetD8_v2"] = <intptr_t>__cuMemsetD8_v2
 
     global __cuMemsetD16_v2
-    data["__cuMemsetD16_v2"] = <_cyb_intptr_t>__cuMemsetD16_v2
+    data["__cuMemsetD16_v2"] = <intptr_t>__cuMemsetD16_v2
 
     global __cuMemsetD32_v2
-    data["__cuMemsetD32_v2"] = <_cyb_intptr_t>__cuMemsetD32_v2
+    data["__cuMemsetD32_v2"] = <intptr_t>__cuMemsetD32_v2
 
     global __cuMemsetD2D8_v2
-    data["__cuMemsetD2D8_v2"] = <_cyb_intptr_t>__cuMemsetD2D8_v2
+    data["__cuMemsetD2D8_v2"] = <intptr_t>__cuMemsetD2D8_v2
 
     global __cuMemsetD2D16_v2
-    data["__cuMemsetD2D16_v2"] = <_cyb_intptr_t>__cuMemsetD2D16_v2
+    data["__cuMemsetD2D16_v2"] = <intptr_t>__cuMemsetD2D16_v2
 
     global __cuMemsetD2D32_v2
-    data["__cuMemsetD2D32_v2"] = <_cyb_intptr_t>__cuMemsetD2D32_v2
+    data["__cuMemsetD2D32_v2"] = <intptr_t>__cuMemsetD2D32_v2
 
     global __cuMemsetD8Async
-    data["__cuMemsetD8Async"] = <_cyb_intptr_t>__cuMemsetD8Async
+    data["__cuMemsetD8Async"] = <intptr_t>__cuMemsetD8Async
 
     global __cuMemsetD16Async
-    data["__cuMemsetD16Async"] = <_cyb_intptr_t>__cuMemsetD16Async
+    data["__cuMemsetD16Async"] = <intptr_t>__cuMemsetD16Async
 
     global __cuMemsetD32Async
-    data["__cuMemsetD32Async"] = <_cyb_intptr_t>__cuMemsetD32Async
+    data["__cuMemsetD32Async"] = <intptr_t>__cuMemsetD32Async
 
     global __cuMemsetD2D8Async
-    data["__cuMemsetD2D8Async"] = <_cyb_intptr_t>__cuMemsetD2D8Async
+    data["__cuMemsetD2D8Async"] = <intptr_t>__cuMemsetD2D8Async
 
     global __cuMemsetD2D16Async
-    data["__cuMemsetD2D16Async"] = <_cyb_intptr_t>__cuMemsetD2D16Async
+    data["__cuMemsetD2D16Async"] = <intptr_t>__cuMemsetD2D16Async
 
     global __cuMemsetD2D32Async
-    data["__cuMemsetD2D32Async"] = <_cyb_intptr_t>__cuMemsetD2D32Async
+    data["__cuMemsetD2D32Async"] = <intptr_t>__cuMemsetD2D32Async
 
     global __cuArrayCreate_v2
-    data["__cuArrayCreate_v2"] = <_cyb_intptr_t>__cuArrayCreate_v2
+    data["__cuArrayCreate_v2"] = <intptr_t>__cuArrayCreate_v2
 
     global __cuArrayGetDescriptor_v2
-    data["__cuArrayGetDescriptor_v2"] = <_cyb_intptr_t>__cuArrayGetDescriptor_v2
+    data["__cuArrayGetDescriptor_v2"] = <intptr_t>__cuArrayGetDescriptor_v2
 
     global __cuArrayGetSparseProperties
-    data["__cuArrayGetSparseProperties"] = <_cyb_intptr_t>__cuArrayGetSparseProperties
+    data["__cuArrayGetSparseProperties"] = <intptr_t>__cuArrayGetSparseProperties
 
     global __cuMipmappedArrayGetSparseProperties
-    data["__cuMipmappedArrayGetSparseProperties"] = <_cyb_intptr_t>__cuMipmappedArrayGetSparseProperties
+    data["__cuMipmappedArrayGetSparseProperties"] = <intptr_t>__cuMipmappedArrayGetSparseProperties
 
     global __cuArrayGetMemoryRequirements
-    data["__cuArrayGetMemoryRequirements"] = <_cyb_intptr_t>__cuArrayGetMemoryRequirements
+    data["__cuArrayGetMemoryRequirements"] = <intptr_t>__cuArrayGetMemoryRequirements
 
     global __cuMipmappedArrayGetMemoryRequirements
-    data["__cuMipmappedArrayGetMemoryRequirements"] = <_cyb_intptr_t>__cuMipmappedArrayGetMemoryRequirements
+    data["__cuMipmappedArrayGetMemoryRequirements"] = <intptr_t>__cuMipmappedArrayGetMemoryRequirements
 
     global __cuArrayGetPlane
-    data["__cuArrayGetPlane"] = <_cyb_intptr_t>__cuArrayGetPlane
+    data["__cuArrayGetPlane"] = <intptr_t>__cuArrayGetPlane
 
     global __cuArrayDestroy
-    data["__cuArrayDestroy"] = <_cyb_intptr_t>__cuArrayDestroy
+    data["__cuArrayDestroy"] = <intptr_t>__cuArrayDestroy
 
     global __cuArray3DCreate_v2
-    data["__cuArray3DCreate_v2"] = <_cyb_intptr_t>__cuArray3DCreate_v2
+    data["__cuArray3DCreate_v2"] = <intptr_t>__cuArray3DCreate_v2
 
     global __cuArray3DGetDescriptor_v2
-    data["__cuArray3DGetDescriptor_v2"] = <_cyb_intptr_t>__cuArray3DGetDescriptor_v2
+    data["__cuArray3DGetDescriptor_v2"] = <intptr_t>__cuArray3DGetDescriptor_v2
 
     global __cuMipmappedArrayCreate
-    data["__cuMipmappedArrayCreate"] = <_cyb_intptr_t>__cuMipmappedArrayCreate
+    data["__cuMipmappedArrayCreate"] = <intptr_t>__cuMipmappedArrayCreate
 
     global __cuMipmappedArrayGetLevel
-    data["__cuMipmappedArrayGetLevel"] = <_cyb_intptr_t>__cuMipmappedArrayGetLevel
+    data["__cuMipmappedArrayGetLevel"] = <intptr_t>__cuMipmappedArrayGetLevel
 
     global __cuMipmappedArrayDestroy
-    data["__cuMipmappedArrayDestroy"] = <_cyb_intptr_t>__cuMipmappedArrayDestroy
+    data["__cuMipmappedArrayDestroy"] = <intptr_t>__cuMipmappedArrayDestroy
 
     global __cuMemGetHandleForAddressRange
-    data["__cuMemGetHandleForAddressRange"] = <_cyb_intptr_t>__cuMemGetHandleForAddressRange
+    data["__cuMemGetHandleForAddressRange"] = <intptr_t>__cuMemGetHandleForAddressRange
 
     global __cuMemBatchDecompressAsync
-    data["__cuMemBatchDecompressAsync"] = <_cyb_intptr_t>__cuMemBatchDecompressAsync
+    data["__cuMemBatchDecompressAsync"] = <intptr_t>__cuMemBatchDecompressAsync
 
     global __cuMemAddressReserve
-    data["__cuMemAddressReserve"] = <_cyb_intptr_t>__cuMemAddressReserve
+    data["__cuMemAddressReserve"] = <intptr_t>__cuMemAddressReserve
 
     global __cuMemAddressFree
-    data["__cuMemAddressFree"] = <_cyb_intptr_t>__cuMemAddressFree
+    data["__cuMemAddressFree"] = <intptr_t>__cuMemAddressFree
 
     global __cuMemCreate
-    data["__cuMemCreate"] = <_cyb_intptr_t>__cuMemCreate
+    data["__cuMemCreate"] = <intptr_t>__cuMemCreate
 
     global __cuMemRelease
-    data["__cuMemRelease"] = <_cyb_intptr_t>__cuMemRelease
+    data["__cuMemRelease"] = <intptr_t>__cuMemRelease
 
     global __cuMemMap
-    data["__cuMemMap"] = <_cyb_intptr_t>__cuMemMap
+    data["__cuMemMap"] = <intptr_t>__cuMemMap
 
     global __cuMemMapArrayAsync
-    data["__cuMemMapArrayAsync"] = <_cyb_intptr_t>__cuMemMapArrayAsync
+    data["__cuMemMapArrayAsync"] = <intptr_t>__cuMemMapArrayAsync
 
     global __cuMemUnmap
-    data["__cuMemUnmap"] = <_cyb_intptr_t>__cuMemUnmap
+    data["__cuMemUnmap"] = <intptr_t>__cuMemUnmap
 
     global __cuMemSetAccess
-    data["__cuMemSetAccess"] = <_cyb_intptr_t>__cuMemSetAccess
+    data["__cuMemSetAccess"] = <intptr_t>__cuMemSetAccess
 
     global __cuMemGetAccess
-    data["__cuMemGetAccess"] = <_cyb_intptr_t>__cuMemGetAccess
+    data["__cuMemGetAccess"] = <intptr_t>__cuMemGetAccess
 
     global __cuMemExportToShareableHandle
-    data["__cuMemExportToShareableHandle"] = <_cyb_intptr_t>__cuMemExportToShareableHandle
+    data["__cuMemExportToShareableHandle"] = <intptr_t>__cuMemExportToShareableHandle
 
     global __cuMemImportFromShareableHandle
-    data["__cuMemImportFromShareableHandle"] = <_cyb_intptr_t>__cuMemImportFromShareableHandle
+    data["__cuMemImportFromShareableHandle"] = <intptr_t>__cuMemImportFromShareableHandle
 
     global __cuMemGetAllocationGranularity
-    data["__cuMemGetAllocationGranularity"] = <_cyb_intptr_t>__cuMemGetAllocationGranularity
+    data["__cuMemGetAllocationGranularity"] = <intptr_t>__cuMemGetAllocationGranularity
 
     global __cuMemGetAllocationPropertiesFromHandle
-    data["__cuMemGetAllocationPropertiesFromHandle"] = <_cyb_intptr_t>__cuMemGetAllocationPropertiesFromHandle
+    data["__cuMemGetAllocationPropertiesFromHandle"] = <intptr_t>__cuMemGetAllocationPropertiesFromHandle
 
     global __cuMemRetainAllocationHandle
-    data["__cuMemRetainAllocationHandle"] = <_cyb_intptr_t>__cuMemRetainAllocationHandle
+    data["__cuMemRetainAllocationHandle"] = <intptr_t>__cuMemRetainAllocationHandle
 
     global __cuMemFreeAsync
-    data["__cuMemFreeAsync"] = <_cyb_intptr_t>__cuMemFreeAsync
+    data["__cuMemFreeAsync"] = <intptr_t>__cuMemFreeAsync
 
     global __cuMemAllocAsync
-    data["__cuMemAllocAsync"] = <_cyb_intptr_t>__cuMemAllocAsync
+    data["__cuMemAllocAsync"] = <intptr_t>__cuMemAllocAsync
 
     global __cuMemPoolTrimTo
-    data["__cuMemPoolTrimTo"] = <_cyb_intptr_t>__cuMemPoolTrimTo
+    data["__cuMemPoolTrimTo"] = <intptr_t>__cuMemPoolTrimTo
 
     global __cuMemPoolSetAttribute
-    data["__cuMemPoolSetAttribute"] = <_cyb_intptr_t>__cuMemPoolSetAttribute
+    data["__cuMemPoolSetAttribute"] = <intptr_t>__cuMemPoolSetAttribute
 
     global __cuMemPoolGetAttribute
-    data["__cuMemPoolGetAttribute"] = <_cyb_intptr_t>__cuMemPoolGetAttribute
+    data["__cuMemPoolGetAttribute"] = <intptr_t>__cuMemPoolGetAttribute
 
     global __cuMemPoolSetAccess
-    data["__cuMemPoolSetAccess"] = <_cyb_intptr_t>__cuMemPoolSetAccess
+    data["__cuMemPoolSetAccess"] = <intptr_t>__cuMemPoolSetAccess
 
     global __cuMemPoolGetAccess
-    data["__cuMemPoolGetAccess"] = <_cyb_intptr_t>__cuMemPoolGetAccess
+    data["__cuMemPoolGetAccess"] = <intptr_t>__cuMemPoolGetAccess
 
     global __cuMemPoolCreate
-    data["__cuMemPoolCreate"] = <_cyb_intptr_t>__cuMemPoolCreate
+    data["__cuMemPoolCreate"] = <intptr_t>__cuMemPoolCreate
 
     global __cuMemPoolDestroy
-    data["__cuMemPoolDestroy"] = <_cyb_intptr_t>__cuMemPoolDestroy
+    data["__cuMemPoolDestroy"] = <intptr_t>__cuMemPoolDestroy
 
     global __cuMemAllocFromPoolAsync
-    data["__cuMemAllocFromPoolAsync"] = <_cyb_intptr_t>__cuMemAllocFromPoolAsync
+    data["__cuMemAllocFromPoolAsync"] = <intptr_t>__cuMemAllocFromPoolAsync
 
     global __cuMemPoolExportToShareableHandle
-    data["__cuMemPoolExportToShareableHandle"] = <_cyb_intptr_t>__cuMemPoolExportToShareableHandle
+    data["__cuMemPoolExportToShareableHandle"] = <intptr_t>__cuMemPoolExportToShareableHandle
 
     global __cuMemPoolImportFromShareableHandle
-    data["__cuMemPoolImportFromShareableHandle"] = <_cyb_intptr_t>__cuMemPoolImportFromShareableHandle
+    data["__cuMemPoolImportFromShareableHandle"] = <intptr_t>__cuMemPoolImportFromShareableHandle
 
     global __cuMemPoolExportPointer
-    data["__cuMemPoolExportPointer"] = <_cyb_intptr_t>__cuMemPoolExportPointer
+    data["__cuMemPoolExportPointer"] = <intptr_t>__cuMemPoolExportPointer
 
     global __cuMemPoolImportPointer
-    data["__cuMemPoolImportPointer"] = <_cyb_intptr_t>__cuMemPoolImportPointer
+    data["__cuMemPoolImportPointer"] = <intptr_t>__cuMemPoolImportPointer
 
     global __cuMulticastCreate
-    data["__cuMulticastCreate"] = <_cyb_intptr_t>__cuMulticastCreate
+    data["__cuMulticastCreate"] = <intptr_t>__cuMulticastCreate
 
     global __cuMulticastAddDevice
-    data["__cuMulticastAddDevice"] = <_cyb_intptr_t>__cuMulticastAddDevice
+    data["__cuMulticastAddDevice"] = <intptr_t>__cuMulticastAddDevice
 
     global __cuMulticastBindMem
-    data["__cuMulticastBindMem"] = <_cyb_intptr_t>__cuMulticastBindMem
+    data["__cuMulticastBindMem"] = <intptr_t>__cuMulticastBindMem
 
     global __cuMulticastBindAddr
-    data["__cuMulticastBindAddr"] = <_cyb_intptr_t>__cuMulticastBindAddr
+    data["__cuMulticastBindAddr"] = <intptr_t>__cuMulticastBindAddr
 
     global __cuMulticastUnbind
-    data["__cuMulticastUnbind"] = <_cyb_intptr_t>__cuMulticastUnbind
+    data["__cuMulticastUnbind"] = <intptr_t>__cuMulticastUnbind
 
     global __cuMulticastGetGranularity
-    data["__cuMulticastGetGranularity"] = <_cyb_intptr_t>__cuMulticastGetGranularity
+    data["__cuMulticastGetGranularity"] = <intptr_t>__cuMulticastGetGranularity
 
     global __cuPointerGetAttribute
-    data["__cuPointerGetAttribute"] = <_cyb_intptr_t>__cuPointerGetAttribute
+    data["__cuPointerGetAttribute"] = <intptr_t>__cuPointerGetAttribute
 
     global __cuMemPrefetchAsync_v2
-    data["__cuMemPrefetchAsync_v2"] = <_cyb_intptr_t>__cuMemPrefetchAsync_v2
+    data["__cuMemPrefetchAsync_v2"] = <intptr_t>__cuMemPrefetchAsync_v2
 
     global __cuMemAdvise_v2
-    data["__cuMemAdvise_v2"] = <_cyb_intptr_t>__cuMemAdvise_v2
+    data["__cuMemAdvise_v2"] = <intptr_t>__cuMemAdvise_v2
 
     global __cuMemRangeGetAttribute
-    data["__cuMemRangeGetAttribute"] = <_cyb_intptr_t>__cuMemRangeGetAttribute
+    data["__cuMemRangeGetAttribute"] = <intptr_t>__cuMemRangeGetAttribute
 
     global __cuMemRangeGetAttributes
-    data["__cuMemRangeGetAttributes"] = <_cyb_intptr_t>__cuMemRangeGetAttributes
+    data["__cuMemRangeGetAttributes"] = <intptr_t>__cuMemRangeGetAttributes
 
     global __cuPointerSetAttribute
-    data["__cuPointerSetAttribute"] = <_cyb_intptr_t>__cuPointerSetAttribute
+    data["__cuPointerSetAttribute"] = <intptr_t>__cuPointerSetAttribute
 
     global __cuPointerGetAttributes
-    data["__cuPointerGetAttributes"] = <_cyb_intptr_t>__cuPointerGetAttributes
+    data["__cuPointerGetAttributes"] = <intptr_t>__cuPointerGetAttributes
 
     global __cuStreamCreate
-    data["__cuStreamCreate"] = <_cyb_intptr_t>__cuStreamCreate
+    data["__cuStreamCreate"] = <intptr_t>__cuStreamCreate
 
     global __cuStreamCreateWithPriority
-    data["__cuStreamCreateWithPriority"] = <_cyb_intptr_t>__cuStreamCreateWithPriority
+    data["__cuStreamCreateWithPriority"] = <intptr_t>__cuStreamCreateWithPriority
 
     global __cuStreamGetPriority
-    data["__cuStreamGetPriority"] = <_cyb_intptr_t>__cuStreamGetPriority
+    data["__cuStreamGetPriority"] = <intptr_t>__cuStreamGetPriority
 
     global __cuStreamGetDevice
-    data["__cuStreamGetDevice"] = <_cyb_intptr_t>__cuStreamGetDevice
+    data["__cuStreamGetDevice"] = <intptr_t>__cuStreamGetDevice
 
     global __cuStreamGetFlags
-    data["__cuStreamGetFlags"] = <_cyb_intptr_t>__cuStreamGetFlags
+    data["__cuStreamGetFlags"] = <intptr_t>__cuStreamGetFlags
 
     global __cuStreamGetId
-    data["__cuStreamGetId"] = <_cyb_intptr_t>__cuStreamGetId
+    data["__cuStreamGetId"] = <intptr_t>__cuStreamGetId
 
     global __cuStreamGetCtx
-    data["__cuStreamGetCtx"] = <_cyb_intptr_t>__cuStreamGetCtx
+    data["__cuStreamGetCtx"] = <intptr_t>__cuStreamGetCtx
 
     global __cuStreamGetCtx_v2
-    data["__cuStreamGetCtx_v2"] = <_cyb_intptr_t>__cuStreamGetCtx_v2
+    data["__cuStreamGetCtx_v2"] = <intptr_t>__cuStreamGetCtx_v2
 
     global __cuStreamWaitEvent
-    data["__cuStreamWaitEvent"] = <_cyb_intptr_t>__cuStreamWaitEvent
+    data["__cuStreamWaitEvent"] = <intptr_t>__cuStreamWaitEvent
 
     global __cuStreamAddCallback
-    data["__cuStreamAddCallback"] = <_cyb_intptr_t>__cuStreamAddCallback
+    data["__cuStreamAddCallback"] = <intptr_t>__cuStreamAddCallback
 
     global __cuStreamBeginCapture_v2
-    data["__cuStreamBeginCapture_v2"] = <_cyb_intptr_t>__cuStreamBeginCapture_v2
+    data["__cuStreamBeginCapture_v2"] = <intptr_t>__cuStreamBeginCapture_v2
 
     global __cuStreamBeginCaptureToGraph
-    data["__cuStreamBeginCaptureToGraph"] = <_cyb_intptr_t>__cuStreamBeginCaptureToGraph
+    data["__cuStreamBeginCaptureToGraph"] = <intptr_t>__cuStreamBeginCaptureToGraph
 
     global __cuThreadExchangeStreamCaptureMode
-    data["__cuThreadExchangeStreamCaptureMode"] = <_cyb_intptr_t>__cuThreadExchangeStreamCaptureMode
+    data["__cuThreadExchangeStreamCaptureMode"] = <intptr_t>__cuThreadExchangeStreamCaptureMode
 
     global __cuStreamEndCapture
-    data["__cuStreamEndCapture"] = <_cyb_intptr_t>__cuStreamEndCapture
+    data["__cuStreamEndCapture"] = <intptr_t>__cuStreamEndCapture
 
     global __cuStreamIsCapturing
-    data["__cuStreamIsCapturing"] = <_cyb_intptr_t>__cuStreamIsCapturing
+    data["__cuStreamIsCapturing"] = <intptr_t>__cuStreamIsCapturing
 
     global __cuStreamGetCaptureInfo_v2
-    data["__cuStreamGetCaptureInfo_v2"] = <_cyb_intptr_t>__cuStreamGetCaptureInfo_v2
+    data["__cuStreamGetCaptureInfo_v2"] = <intptr_t>__cuStreamGetCaptureInfo_v2
 
     global __cuStreamGetCaptureInfo_v3
-    data["__cuStreamGetCaptureInfo_v3"] = <_cyb_intptr_t>__cuStreamGetCaptureInfo_v3
+    data["__cuStreamGetCaptureInfo_v3"] = <intptr_t>__cuStreamGetCaptureInfo_v3
 
     global __cuStreamUpdateCaptureDependencies_v2
-    data["__cuStreamUpdateCaptureDependencies_v2"] = <_cyb_intptr_t>__cuStreamUpdateCaptureDependencies_v2
+    data["__cuStreamUpdateCaptureDependencies_v2"] = <intptr_t>__cuStreamUpdateCaptureDependencies_v2
 
     global __cuStreamAttachMemAsync
-    data["__cuStreamAttachMemAsync"] = <_cyb_intptr_t>__cuStreamAttachMemAsync
+    data["__cuStreamAttachMemAsync"] = <intptr_t>__cuStreamAttachMemAsync
 
     global __cuStreamQuery
-    data["__cuStreamQuery"] = <_cyb_intptr_t>__cuStreamQuery
+    data["__cuStreamQuery"] = <intptr_t>__cuStreamQuery
 
     global __cuStreamSynchronize
-    data["__cuStreamSynchronize"] = <_cyb_intptr_t>__cuStreamSynchronize
+    data["__cuStreamSynchronize"] = <intptr_t>__cuStreamSynchronize
 
     global __cuStreamDestroy_v2
-    data["__cuStreamDestroy_v2"] = <_cyb_intptr_t>__cuStreamDestroy_v2
+    data["__cuStreamDestroy_v2"] = <intptr_t>__cuStreamDestroy_v2
 
     global __cuStreamCopyAttributes
-    data["__cuStreamCopyAttributes"] = <_cyb_intptr_t>__cuStreamCopyAttributes
+    data["__cuStreamCopyAttributes"] = <intptr_t>__cuStreamCopyAttributes
 
     global __cuStreamGetAttribute
-    data["__cuStreamGetAttribute"] = <_cyb_intptr_t>__cuStreamGetAttribute
+    data["__cuStreamGetAttribute"] = <intptr_t>__cuStreamGetAttribute
 
     global __cuStreamSetAttribute
-    data["__cuStreamSetAttribute"] = <_cyb_intptr_t>__cuStreamSetAttribute
+    data["__cuStreamSetAttribute"] = <intptr_t>__cuStreamSetAttribute
 
     global __cuEventCreate
-    data["__cuEventCreate"] = <_cyb_intptr_t>__cuEventCreate
+    data["__cuEventCreate"] = <intptr_t>__cuEventCreate
 
     global __cuEventRecord
-    data["__cuEventRecord"] = <_cyb_intptr_t>__cuEventRecord
+    data["__cuEventRecord"] = <intptr_t>__cuEventRecord
 
     global __cuEventRecordWithFlags
-    data["__cuEventRecordWithFlags"] = <_cyb_intptr_t>__cuEventRecordWithFlags
+    data["__cuEventRecordWithFlags"] = <intptr_t>__cuEventRecordWithFlags
 
     global __cuEventQuery
-    data["__cuEventQuery"] = <_cyb_intptr_t>__cuEventQuery
+    data["__cuEventQuery"] = <intptr_t>__cuEventQuery
 
     global __cuEventSynchronize
-    data["__cuEventSynchronize"] = <_cyb_intptr_t>__cuEventSynchronize
+    data["__cuEventSynchronize"] = <intptr_t>__cuEventSynchronize
 
     global __cuEventDestroy_v2
-    data["__cuEventDestroy_v2"] = <_cyb_intptr_t>__cuEventDestroy_v2
+    data["__cuEventDestroy_v2"] = <intptr_t>__cuEventDestroy_v2
 
     global __cuEventElapsedTime_v2
-    data["__cuEventElapsedTime_v2"] = <_cyb_intptr_t>__cuEventElapsedTime_v2
+    data["__cuEventElapsedTime_v2"] = <intptr_t>__cuEventElapsedTime_v2
 
     global __cuImportExternalMemory
-    data["__cuImportExternalMemory"] = <_cyb_intptr_t>__cuImportExternalMemory
+    data["__cuImportExternalMemory"] = <intptr_t>__cuImportExternalMemory
 
     global __cuExternalMemoryGetMappedBuffer
-    data["__cuExternalMemoryGetMappedBuffer"] = <_cyb_intptr_t>__cuExternalMemoryGetMappedBuffer
+    data["__cuExternalMemoryGetMappedBuffer"] = <intptr_t>__cuExternalMemoryGetMappedBuffer
 
     global __cuExternalMemoryGetMappedMipmappedArray
-    data["__cuExternalMemoryGetMappedMipmappedArray"] = <_cyb_intptr_t>__cuExternalMemoryGetMappedMipmappedArray
+    data["__cuExternalMemoryGetMappedMipmappedArray"] = <intptr_t>__cuExternalMemoryGetMappedMipmappedArray
 
     global __cuDestroyExternalMemory
-    data["__cuDestroyExternalMemory"] = <_cyb_intptr_t>__cuDestroyExternalMemory
+    data["__cuDestroyExternalMemory"] = <intptr_t>__cuDestroyExternalMemory
 
     global __cuImportExternalSemaphore
-    data["__cuImportExternalSemaphore"] = <_cyb_intptr_t>__cuImportExternalSemaphore
+    data["__cuImportExternalSemaphore"] = <intptr_t>__cuImportExternalSemaphore
 
     global __cuSignalExternalSemaphoresAsync
-    data["__cuSignalExternalSemaphoresAsync"] = <_cyb_intptr_t>__cuSignalExternalSemaphoresAsync
+    data["__cuSignalExternalSemaphoresAsync"] = <intptr_t>__cuSignalExternalSemaphoresAsync
 
     global __cuWaitExternalSemaphoresAsync
-    data["__cuWaitExternalSemaphoresAsync"] = <_cyb_intptr_t>__cuWaitExternalSemaphoresAsync
+    data["__cuWaitExternalSemaphoresAsync"] = <intptr_t>__cuWaitExternalSemaphoresAsync
 
     global __cuDestroyExternalSemaphore
-    data["__cuDestroyExternalSemaphore"] = <_cyb_intptr_t>__cuDestroyExternalSemaphore
+    data["__cuDestroyExternalSemaphore"] = <intptr_t>__cuDestroyExternalSemaphore
 
     global __cuStreamWaitValue32_v2
-    data["__cuStreamWaitValue32_v2"] = <_cyb_intptr_t>__cuStreamWaitValue32_v2
+    data["__cuStreamWaitValue32_v2"] = <intptr_t>__cuStreamWaitValue32_v2
 
     global __cuStreamWaitValue64_v2
-    data["__cuStreamWaitValue64_v2"] = <_cyb_intptr_t>__cuStreamWaitValue64_v2
+    data["__cuStreamWaitValue64_v2"] = <intptr_t>__cuStreamWaitValue64_v2
 
     global __cuStreamWriteValue32_v2
-    data["__cuStreamWriteValue32_v2"] = <_cyb_intptr_t>__cuStreamWriteValue32_v2
+    data["__cuStreamWriteValue32_v2"] = <intptr_t>__cuStreamWriteValue32_v2
 
     global __cuStreamWriteValue64_v2
-    data["__cuStreamWriteValue64_v2"] = <_cyb_intptr_t>__cuStreamWriteValue64_v2
+    data["__cuStreamWriteValue64_v2"] = <intptr_t>__cuStreamWriteValue64_v2
 
     global __cuStreamBatchMemOp_v2
-    data["__cuStreamBatchMemOp_v2"] = <_cyb_intptr_t>__cuStreamBatchMemOp_v2
+    data["__cuStreamBatchMemOp_v2"] = <intptr_t>__cuStreamBatchMemOp_v2
 
     global __cuFuncGetAttribute
-    data["__cuFuncGetAttribute"] = <_cyb_intptr_t>__cuFuncGetAttribute
+    data["__cuFuncGetAttribute"] = <intptr_t>__cuFuncGetAttribute
 
     global __cuFuncSetAttribute
-    data["__cuFuncSetAttribute"] = <_cyb_intptr_t>__cuFuncSetAttribute
+    data["__cuFuncSetAttribute"] = <intptr_t>__cuFuncSetAttribute
 
     global __cuFuncSetCacheConfig
-    data["__cuFuncSetCacheConfig"] = <_cyb_intptr_t>__cuFuncSetCacheConfig
+    data["__cuFuncSetCacheConfig"] = <intptr_t>__cuFuncSetCacheConfig
 
     global __cuFuncGetModule
-    data["__cuFuncGetModule"] = <_cyb_intptr_t>__cuFuncGetModule
+    data["__cuFuncGetModule"] = <intptr_t>__cuFuncGetModule
 
     global __cuFuncGetName
-    data["__cuFuncGetName"] = <_cyb_intptr_t>__cuFuncGetName
+    data["__cuFuncGetName"] = <intptr_t>__cuFuncGetName
 
     global __cuFuncGetParamInfo
-    data["__cuFuncGetParamInfo"] = <_cyb_intptr_t>__cuFuncGetParamInfo
+    data["__cuFuncGetParamInfo"] = <intptr_t>__cuFuncGetParamInfo
 
     global __cuFuncIsLoaded
-    data["__cuFuncIsLoaded"] = <_cyb_intptr_t>__cuFuncIsLoaded
+    data["__cuFuncIsLoaded"] = <intptr_t>__cuFuncIsLoaded
 
     global __cuFuncLoad
-    data["__cuFuncLoad"] = <_cyb_intptr_t>__cuFuncLoad
+    data["__cuFuncLoad"] = <intptr_t>__cuFuncLoad
 
     global __cuLaunchKernel
-    data["__cuLaunchKernel"] = <_cyb_intptr_t>__cuLaunchKernel
+    data["__cuLaunchKernel"] = <intptr_t>__cuLaunchKernel
 
     global __cuLaunchKernelEx
-    data["__cuLaunchKernelEx"] = <_cyb_intptr_t>__cuLaunchKernelEx
+    data["__cuLaunchKernelEx"] = <intptr_t>__cuLaunchKernelEx
 
     global __cuLaunchCooperativeKernel
-    data["__cuLaunchCooperativeKernel"] = <_cyb_intptr_t>__cuLaunchCooperativeKernel
+    data["__cuLaunchCooperativeKernel"] = <intptr_t>__cuLaunchCooperativeKernel
 
     global __cuLaunchCooperativeKernelMultiDevice
-    data["__cuLaunchCooperativeKernelMultiDevice"] = <_cyb_intptr_t>__cuLaunchCooperativeKernelMultiDevice
+    data["__cuLaunchCooperativeKernelMultiDevice"] = <intptr_t>__cuLaunchCooperativeKernelMultiDevice
 
     global __cuLaunchHostFunc
-    data["__cuLaunchHostFunc"] = <_cyb_intptr_t>__cuLaunchHostFunc
+    data["__cuLaunchHostFunc"] = <intptr_t>__cuLaunchHostFunc
 
     global __cuFuncSetBlockShape
-    data["__cuFuncSetBlockShape"] = <_cyb_intptr_t>__cuFuncSetBlockShape
+    data["__cuFuncSetBlockShape"] = <intptr_t>__cuFuncSetBlockShape
 
     global __cuFuncSetSharedSize
-    data["__cuFuncSetSharedSize"] = <_cyb_intptr_t>__cuFuncSetSharedSize
+    data["__cuFuncSetSharedSize"] = <intptr_t>__cuFuncSetSharedSize
 
     global __cuParamSetSize
-    data["__cuParamSetSize"] = <_cyb_intptr_t>__cuParamSetSize
+    data["__cuParamSetSize"] = <intptr_t>__cuParamSetSize
 
     global __cuParamSeti
-    data["__cuParamSeti"] = <_cyb_intptr_t>__cuParamSeti
+    data["__cuParamSeti"] = <intptr_t>__cuParamSeti
 
     global __cuParamSetf
-    data["__cuParamSetf"] = <_cyb_intptr_t>__cuParamSetf
+    data["__cuParamSetf"] = <intptr_t>__cuParamSetf
 
     global __cuParamSetv
-    data["__cuParamSetv"] = <_cyb_intptr_t>__cuParamSetv
+    data["__cuParamSetv"] = <intptr_t>__cuParamSetv
 
     global __cuLaunch
-    data["__cuLaunch"] = <_cyb_intptr_t>__cuLaunch
+    data["__cuLaunch"] = <intptr_t>__cuLaunch
 
     global __cuLaunchGrid
-    data["__cuLaunchGrid"] = <_cyb_intptr_t>__cuLaunchGrid
+    data["__cuLaunchGrid"] = <intptr_t>__cuLaunchGrid
 
     global __cuLaunchGridAsync
-    data["__cuLaunchGridAsync"] = <_cyb_intptr_t>__cuLaunchGridAsync
+    data["__cuLaunchGridAsync"] = <intptr_t>__cuLaunchGridAsync
 
     global __cuParamSetTexRef
-    data["__cuParamSetTexRef"] = <_cyb_intptr_t>__cuParamSetTexRef
+    data["__cuParamSetTexRef"] = <intptr_t>__cuParamSetTexRef
 
     global __cuFuncSetSharedMemConfig
-    data["__cuFuncSetSharedMemConfig"] = <_cyb_intptr_t>__cuFuncSetSharedMemConfig
+    data["__cuFuncSetSharedMemConfig"] = <intptr_t>__cuFuncSetSharedMemConfig
 
     global __cuGraphCreate
-    data["__cuGraphCreate"] = <_cyb_intptr_t>__cuGraphCreate
+    data["__cuGraphCreate"] = <intptr_t>__cuGraphCreate
 
     global __cuGraphAddKernelNode_v2
-    data["__cuGraphAddKernelNode_v2"] = <_cyb_intptr_t>__cuGraphAddKernelNode_v2
+    data["__cuGraphAddKernelNode_v2"] = <intptr_t>__cuGraphAddKernelNode_v2
 
     global __cuGraphKernelNodeGetParams_v2
-    data["__cuGraphKernelNodeGetParams_v2"] = <_cyb_intptr_t>__cuGraphKernelNodeGetParams_v2
+    data["__cuGraphKernelNodeGetParams_v2"] = <intptr_t>__cuGraphKernelNodeGetParams_v2
 
     global __cuGraphKernelNodeSetParams_v2
-    data["__cuGraphKernelNodeSetParams_v2"] = <_cyb_intptr_t>__cuGraphKernelNodeSetParams_v2
+    data["__cuGraphKernelNodeSetParams_v2"] = <intptr_t>__cuGraphKernelNodeSetParams_v2
 
     global __cuGraphAddMemcpyNode
-    data["__cuGraphAddMemcpyNode"] = <_cyb_intptr_t>__cuGraphAddMemcpyNode
+    data["__cuGraphAddMemcpyNode"] = <intptr_t>__cuGraphAddMemcpyNode
 
     global __cuGraphMemcpyNodeGetParams
-    data["__cuGraphMemcpyNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemcpyNodeGetParams
+    data["__cuGraphMemcpyNodeGetParams"] = <intptr_t>__cuGraphMemcpyNodeGetParams
 
     global __cuGraphMemcpyNodeSetParams
-    data["__cuGraphMemcpyNodeSetParams"] = <_cyb_intptr_t>__cuGraphMemcpyNodeSetParams
+    data["__cuGraphMemcpyNodeSetParams"] = <intptr_t>__cuGraphMemcpyNodeSetParams
 
     global __cuGraphAddMemsetNode
-    data["__cuGraphAddMemsetNode"] = <_cyb_intptr_t>__cuGraphAddMemsetNode
+    data["__cuGraphAddMemsetNode"] = <intptr_t>__cuGraphAddMemsetNode
 
     global __cuGraphMemsetNodeGetParams
-    data["__cuGraphMemsetNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemsetNodeGetParams
+    data["__cuGraphMemsetNodeGetParams"] = <intptr_t>__cuGraphMemsetNodeGetParams
 
     global __cuGraphMemsetNodeSetParams
-    data["__cuGraphMemsetNodeSetParams"] = <_cyb_intptr_t>__cuGraphMemsetNodeSetParams
+    data["__cuGraphMemsetNodeSetParams"] = <intptr_t>__cuGraphMemsetNodeSetParams
 
     global __cuGraphAddHostNode
-    data["__cuGraphAddHostNode"] = <_cyb_intptr_t>__cuGraphAddHostNode
+    data["__cuGraphAddHostNode"] = <intptr_t>__cuGraphAddHostNode
 
     global __cuGraphHostNodeGetParams
-    data["__cuGraphHostNodeGetParams"] = <_cyb_intptr_t>__cuGraphHostNodeGetParams
+    data["__cuGraphHostNodeGetParams"] = <intptr_t>__cuGraphHostNodeGetParams
 
     global __cuGraphHostNodeSetParams
-    data["__cuGraphHostNodeSetParams"] = <_cyb_intptr_t>__cuGraphHostNodeSetParams
+    data["__cuGraphHostNodeSetParams"] = <intptr_t>__cuGraphHostNodeSetParams
 
     global __cuGraphAddChildGraphNode
-    data["__cuGraphAddChildGraphNode"] = <_cyb_intptr_t>__cuGraphAddChildGraphNode
+    data["__cuGraphAddChildGraphNode"] = <intptr_t>__cuGraphAddChildGraphNode
 
     global __cuGraphChildGraphNodeGetGraph
-    data["__cuGraphChildGraphNodeGetGraph"] = <_cyb_intptr_t>__cuGraphChildGraphNodeGetGraph
+    data["__cuGraphChildGraphNodeGetGraph"] = <intptr_t>__cuGraphChildGraphNodeGetGraph
 
     global __cuGraphAddEmptyNode
-    data["__cuGraphAddEmptyNode"] = <_cyb_intptr_t>__cuGraphAddEmptyNode
+    data["__cuGraphAddEmptyNode"] = <intptr_t>__cuGraphAddEmptyNode
 
     global __cuGraphAddEventRecordNode
-    data["__cuGraphAddEventRecordNode"] = <_cyb_intptr_t>__cuGraphAddEventRecordNode
+    data["__cuGraphAddEventRecordNode"] = <intptr_t>__cuGraphAddEventRecordNode
 
     global __cuGraphEventRecordNodeGetEvent
-    data["__cuGraphEventRecordNodeGetEvent"] = <_cyb_intptr_t>__cuGraphEventRecordNodeGetEvent
+    data["__cuGraphEventRecordNodeGetEvent"] = <intptr_t>__cuGraphEventRecordNodeGetEvent
 
     global __cuGraphEventRecordNodeSetEvent
-    data["__cuGraphEventRecordNodeSetEvent"] = <_cyb_intptr_t>__cuGraphEventRecordNodeSetEvent
+    data["__cuGraphEventRecordNodeSetEvent"] = <intptr_t>__cuGraphEventRecordNodeSetEvent
 
     global __cuGraphAddEventWaitNode
-    data["__cuGraphAddEventWaitNode"] = <_cyb_intptr_t>__cuGraphAddEventWaitNode
+    data["__cuGraphAddEventWaitNode"] = <intptr_t>__cuGraphAddEventWaitNode
 
     global __cuGraphEventWaitNodeGetEvent
-    data["__cuGraphEventWaitNodeGetEvent"] = <_cyb_intptr_t>__cuGraphEventWaitNodeGetEvent
+    data["__cuGraphEventWaitNodeGetEvent"] = <intptr_t>__cuGraphEventWaitNodeGetEvent
 
     global __cuGraphEventWaitNodeSetEvent
-    data["__cuGraphEventWaitNodeSetEvent"] = <_cyb_intptr_t>__cuGraphEventWaitNodeSetEvent
+    data["__cuGraphEventWaitNodeSetEvent"] = <intptr_t>__cuGraphEventWaitNodeSetEvent
 
     global __cuGraphAddExternalSemaphoresSignalNode
-    data["__cuGraphAddExternalSemaphoresSignalNode"] = <_cyb_intptr_t>__cuGraphAddExternalSemaphoresSignalNode
+    data["__cuGraphAddExternalSemaphoresSignalNode"] = <intptr_t>__cuGraphAddExternalSemaphoresSignalNode
 
     global __cuGraphExternalSemaphoresSignalNodeGetParams
-    data["__cuGraphExternalSemaphoresSignalNodeGetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresSignalNodeGetParams
+    data["__cuGraphExternalSemaphoresSignalNodeGetParams"] = <intptr_t>__cuGraphExternalSemaphoresSignalNodeGetParams
 
     global __cuGraphExternalSemaphoresSignalNodeSetParams
-    data["__cuGraphExternalSemaphoresSignalNodeSetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresSignalNodeSetParams
+    data["__cuGraphExternalSemaphoresSignalNodeSetParams"] = <intptr_t>__cuGraphExternalSemaphoresSignalNodeSetParams
 
     global __cuGraphAddExternalSemaphoresWaitNode
-    data["__cuGraphAddExternalSemaphoresWaitNode"] = <_cyb_intptr_t>__cuGraphAddExternalSemaphoresWaitNode
+    data["__cuGraphAddExternalSemaphoresWaitNode"] = <intptr_t>__cuGraphAddExternalSemaphoresWaitNode
 
     global __cuGraphExternalSemaphoresWaitNodeGetParams
-    data["__cuGraphExternalSemaphoresWaitNodeGetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresWaitNodeGetParams
+    data["__cuGraphExternalSemaphoresWaitNodeGetParams"] = <intptr_t>__cuGraphExternalSemaphoresWaitNodeGetParams
 
     global __cuGraphExternalSemaphoresWaitNodeSetParams
-    data["__cuGraphExternalSemaphoresWaitNodeSetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresWaitNodeSetParams
+    data["__cuGraphExternalSemaphoresWaitNodeSetParams"] = <intptr_t>__cuGraphExternalSemaphoresWaitNodeSetParams
 
     global __cuGraphAddBatchMemOpNode
-    data["__cuGraphAddBatchMemOpNode"] = <_cyb_intptr_t>__cuGraphAddBatchMemOpNode
+    data["__cuGraphAddBatchMemOpNode"] = <intptr_t>__cuGraphAddBatchMemOpNode
 
     global __cuGraphBatchMemOpNodeGetParams
-    data["__cuGraphBatchMemOpNodeGetParams"] = <_cyb_intptr_t>__cuGraphBatchMemOpNodeGetParams
+    data["__cuGraphBatchMemOpNodeGetParams"] = <intptr_t>__cuGraphBatchMemOpNodeGetParams
 
     global __cuGraphBatchMemOpNodeSetParams
-    data["__cuGraphBatchMemOpNodeSetParams"] = <_cyb_intptr_t>__cuGraphBatchMemOpNodeSetParams
+    data["__cuGraphBatchMemOpNodeSetParams"] = <intptr_t>__cuGraphBatchMemOpNodeSetParams
 
     global __cuGraphExecBatchMemOpNodeSetParams
-    data["__cuGraphExecBatchMemOpNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecBatchMemOpNodeSetParams
+    data["__cuGraphExecBatchMemOpNodeSetParams"] = <intptr_t>__cuGraphExecBatchMemOpNodeSetParams
 
     global __cuGraphAddMemAllocNode
-    data["__cuGraphAddMemAllocNode"] = <_cyb_intptr_t>__cuGraphAddMemAllocNode
+    data["__cuGraphAddMemAllocNode"] = <intptr_t>__cuGraphAddMemAllocNode
 
     global __cuGraphMemAllocNodeGetParams
-    data["__cuGraphMemAllocNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemAllocNodeGetParams
+    data["__cuGraphMemAllocNodeGetParams"] = <intptr_t>__cuGraphMemAllocNodeGetParams
 
     global __cuGraphAddMemFreeNode
-    data["__cuGraphAddMemFreeNode"] = <_cyb_intptr_t>__cuGraphAddMemFreeNode
+    data["__cuGraphAddMemFreeNode"] = <intptr_t>__cuGraphAddMemFreeNode
 
     global __cuGraphMemFreeNodeGetParams
-    data["__cuGraphMemFreeNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemFreeNodeGetParams
+    data["__cuGraphMemFreeNodeGetParams"] = <intptr_t>__cuGraphMemFreeNodeGetParams
 
     global __cuDeviceGraphMemTrim
-    data["__cuDeviceGraphMemTrim"] = <_cyb_intptr_t>__cuDeviceGraphMemTrim
+    data["__cuDeviceGraphMemTrim"] = <intptr_t>__cuDeviceGraphMemTrim
 
     global __cuDeviceGetGraphMemAttribute
-    data["__cuDeviceGetGraphMemAttribute"] = <_cyb_intptr_t>__cuDeviceGetGraphMemAttribute
+    data["__cuDeviceGetGraphMemAttribute"] = <intptr_t>__cuDeviceGetGraphMemAttribute
 
     global __cuDeviceSetGraphMemAttribute
-    data["__cuDeviceSetGraphMemAttribute"] = <_cyb_intptr_t>__cuDeviceSetGraphMemAttribute
+    data["__cuDeviceSetGraphMemAttribute"] = <intptr_t>__cuDeviceSetGraphMemAttribute
 
     global __cuGraphClone
-    data["__cuGraphClone"] = <_cyb_intptr_t>__cuGraphClone
+    data["__cuGraphClone"] = <intptr_t>__cuGraphClone
 
     global __cuGraphNodeFindInClone
-    data["__cuGraphNodeFindInClone"] = <_cyb_intptr_t>__cuGraphNodeFindInClone
+    data["__cuGraphNodeFindInClone"] = <intptr_t>__cuGraphNodeFindInClone
 
     global __cuGraphNodeGetType
-    data["__cuGraphNodeGetType"] = <_cyb_intptr_t>__cuGraphNodeGetType
+    data["__cuGraphNodeGetType"] = <intptr_t>__cuGraphNodeGetType
 
     global __cuGraphGetNodes
-    data["__cuGraphGetNodes"] = <_cyb_intptr_t>__cuGraphGetNodes
+    data["__cuGraphGetNodes"] = <intptr_t>__cuGraphGetNodes
 
     global __cuGraphGetRootNodes
-    data["__cuGraphGetRootNodes"] = <_cyb_intptr_t>__cuGraphGetRootNodes
+    data["__cuGraphGetRootNodes"] = <intptr_t>__cuGraphGetRootNodes
 
     global __cuGraphGetEdges_v2
-    data["__cuGraphGetEdges_v2"] = <_cyb_intptr_t>__cuGraphGetEdges_v2
+    data["__cuGraphGetEdges_v2"] = <intptr_t>__cuGraphGetEdges_v2
 
     global __cuGraphNodeGetDependencies_v2
-    data["__cuGraphNodeGetDependencies_v2"] = <_cyb_intptr_t>__cuGraphNodeGetDependencies_v2
+    data["__cuGraphNodeGetDependencies_v2"] = <intptr_t>__cuGraphNodeGetDependencies_v2
 
     global __cuGraphNodeGetDependentNodes_v2
-    data["__cuGraphNodeGetDependentNodes_v2"] = <_cyb_intptr_t>__cuGraphNodeGetDependentNodes_v2
+    data["__cuGraphNodeGetDependentNodes_v2"] = <intptr_t>__cuGraphNodeGetDependentNodes_v2
 
     global __cuGraphAddDependencies_v2
-    data["__cuGraphAddDependencies_v2"] = <_cyb_intptr_t>__cuGraphAddDependencies_v2
+    data["__cuGraphAddDependencies_v2"] = <intptr_t>__cuGraphAddDependencies_v2
 
     global __cuGraphRemoveDependencies_v2
-    data["__cuGraphRemoveDependencies_v2"] = <_cyb_intptr_t>__cuGraphRemoveDependencies_v2
+    data["__cuGraphRemoveDependencies_v2"] = <intptr_t>__cuGraphRemoveDependencies_v2
 
     global __cuGraphDestroyNode
-    data["__cuGraphDestroyNode"] = <_cyb_intptr_t>__cuGraphDestroyNode
+    data["__cuGraphDestroyNode"] = <intptr_t>__cuGraphDestroyNode
 
     global __cuGraphInstantiateWithFlags
-    data["__cuGraphInstantiateWithFlags"] = <_cyb_intptr_t>__cuGraphInstantiateWithFlags
+    data["__cuGraphInstantiateWithFlags"] = <intptr_t>__cuGraphInstantiateWithFlags
 
     global __cuGraphInstantiateWithParams
-    data["__cuGraphInstantiateWithParams"] = <_cyb_intptr_t>__cuGraphInstantiateWithParams
+    data["__cuGraphInstantiateWithParams"] = <intptr_t>__cuGraphInstantiateWithParams
 
     global __cuGraphExecGetFlags
-    data["__cuGraphExecGetFlags"] = <_cyb_intptr_t>__cuGraphExecGetFlags
+    data["__cuGraphExecGetFlags"] = <intptr_t>__cuGraphExecGetFlags
 
     global __cuGraphExecKernelNodeSetParams_v2
-    data["__cuGraphExecKernelNodeSetParams_v2"] = <_cyb_intptr_t>__cuGraphExecKernelNodeSetParams_v2
+    data["__cuGraphExecKernelNodeSetParams_v2"] = <intptr_t>__cuGraphExecKernelNodeSetParams_v2
 
     global __cuGraphExecMemcpyNodeSetParams
-    data["__cuGraphExecMemcpyNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecMemcpyNodeSetParams
+    data["__cuGraphExecMemcpyNodeSetParams"] = <intptr_t>__cuGraphExecMemcpyNodeSetParams
 
     global __cuGraphExecMemsetNodeSetParams
-    data["__cuGraphExecMemsetNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecMemsetNodeSetParams
+    data["__cuGraphExecMemsetNodeSetParams"] = <intptr_t>__cuGraphExecMemsetNodeSetParams
 
     global __cuGraphExecHostNodeSetParams
-    data["__cuGraphExecHostNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecHostNodeSetParams
+    data["__cuGraphExecHostNodeSetParams"] = <intptr_t>__cuGraphExecHostNodeSetParams
 
     global __cuGraphExecChildGraphNodeSetParams
-    data["__cuGraphExecChildGraphNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecChildGraphNodeSetParams
+    data["__cuGraphExecChildGraphNodeSetParams"] = <intptr_t>__cuGraphExecChildGraphNodeSetParams
 
     global __cuGraphExecEventRecordNodeSetEvent
-    data["__cuGraphExecEventRecordNodeSetEvent"] = <_cyb_intptr_t>__cuGraphExecEventRecordNodeSetEvent
+    data["__cuGraphExecEventRecordNodeSetEvent"] = <intptr_t>__cuGraphExecEventRecordNodeSetEvent
 
     global __cuGraphExecEventWaitNodeSetEvent
-    data["__cuGraphExecEventWaitNodeSetEvent"] = <_cyb_intptr_t>__cuGraphExecEventWaitNodeSetEvent
+    data["__cuGraphExecEventWaitNodeSetEvent"] = <intptr_t>__cuGraphExecEventWaitNodeSetEvent
 
     global __cuGraphExecExternalSemaphoresSignalNodeSetParams
-    data["__cuGraphExecExternalSemaphoresSignalNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecExternalSemaphoresSignalNodeSetParams
+    data["__cuGraphExecExternalSemaphoresSignalNodeSetParams"] = <intptr_t>__cuGraphExecExternalSemaphoresSignalNodeSetParams
 
     global __cuGraphExecExternalSemaphoresWaitNodeSetParams
-    data["__cuGraphExecExternalSemaphoresWaitNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecExternalSemaphoresWaitNodeSetParams
+    data["__cuGraphExecExternalSemaphoresWaitNodeSetParams"] = <intptr_t>__cuGraphExecExternalSemaphoresWaitNodeSetParams
 
     global __cuGraphNodeSetEnabled
-    data["__cuGraphNodeSetEnabled"] = <_cyb_intptr_t>__cuGraphNodeSetEnabled
+    data["__cuGraphNodeSetEnabled"] = <intptr_t>__cuGraphNodeSetEnabled
 
     global __cuGraphNodeGetEnabled
-    data["__cuGraphNodeGetEnabled"] = <_cyb_intptr_t>__cuGraphNodeGetEnabled
+    data["__cuGraphNodeGetEnabled"] = <intptr_t>__cuGraphNodeGetEnabled
 
     global __cuGraphUpload
-    data["__cuGraphUpload"] = <_cyb_intptr_t>__cuGraphUpload
+    data["__cuGraphUpload"] = <intptr_t>__cuGraphUpload
 
     global __cuGraphLaunch
-    data["__cuGraphLaunch"] = <_cyb_intptr_t>__cuGraphLaunch
+    data["__cuGraphLaunch"] = <intptr_t>__cuGraphLaunch
 
     global __cuGraphExecDestroy
-    data["__cuGraphExecDestroy"] = <_cyb_intptr_t>__cuGraphExecDestroy
+    data["__cuGraphExecDestroy"] = <intptr_t>__cuGraphExecDestroy
 
     global __cuGraphDestroy
-    data["__cuGraphDestroy"] = <_cyb_intptr_t>__cuGraphDestroy
+    data["__cuGraphDestroy"] = <intptr_t>__cuGraphDestroy
 
     global __cuGraphExecUpdate_v2
-    data["__cuGraphExecUpdate_v2"] = <_cyb_intptr_t>__cuGraphExecUpdate_v2
+    data["__cuGraphExecUpdate_v2"] = <intptr_t>__cuGraphExecUpdate_v2
 
     global __cuGraphKernelNodeCopyAttributes
-    data["__cuGraphKernelNodeCopyAttributes"] = <_cyb_intptr_t>__cuGraphKernelNodeCopyAttributes
+    data["__cuGraphKernelNodeCopyAttributes"] = <intptr_t>__cuGraphKernelNodeCopyAttributes
 
     global __cuGraphKernelNodeGetAttribute
-    data["__cuGraphKernelNodeGetAttribute"] = <_cyb_intptr_t>__cuGraphKernelNodeGetAttribute
+    data["__cuGraphKernelNodeGetAttribute"] = <intptr_t>__cuGraphKernelNodeGetAttribute
 
     global __cuGraphKernelNodeSetAttribute
-    data["__cuGraphKernelNodeSetAttribute"] = <_cyb_intptr_t>__cuGraphKernelNodeSetAttribute
+    data["__cuGraphKernelNodeSetAttribute"] = <intptr_t>__cuGraphKernelNodeSetAttribute
 
     global __cuGraphDebugDotPrint
-    data["__cuGraphDebugDotPrint"] = <_cyb_intptr_t>__cuGraphDebugDotPrint
+    data["__cuGraphDebugDotPrint"] = <intptr_t>__cuGraphDebugDotPrint
 
     global __cuUserObjectCreate
-    data["__cuUserObjectCreate"] = <_cyb_intptr_t>__cuUserObjectCreate
+    data["__cuUserObjectCreate"] = <intptr_t>__cuUserObjectCreate
 
     global __cuUserObjectRetain
-    data["__cuUserObjectRetain"] = <_cyb_intptr_t>__cuUserObjectRetain
+    data["__cuUserObjectRetain"] = <intptr_t>__cuUserObjectRetain
 
     global __cuUserObjectRelease
-    data["__cuUserObjectRelease"] = <_cyb_intptr_t>__cuUserObjectRelease
+    data["__cuUserObjectRelease"] = <intptr_t>__cuUserObjectRelease
 
     global __cuGraphRetainUserObject
-    data["__cuGraphRetainUserObject"] = <_cyb_intptr_t>__cuGraphRetainUserObject
+    data["__cuGraphRetainUserObject"] = <intptr_t>__cuGraphRetainUserObject
 
     global __cuGraphReleaseUserObject
-    data["__cuGraphReleaseUserObject"] = <_cyb_intptr_t>__cuGraphReleaseUserObject
+    data["__cuGraphReleaseUserObject"] = <intptr_t>__cuGraphReleaseUserObject
 
     global __cuGraphAddNode_v2
-    data["__cuGraphAddNode_v2"] = <_cyb_intptr_t>__cuGraphAddNode_v2
+    data["__cuGraphAddNode_v2"] = <intptr_t>__cuGraphAddNode_v2
 
     global __cuGraphNodeSetParams
-    data["__cuGraphNodeSetParams"] = <_cyb_intptr_t>__cuGraphNodeSetParams
+    data["__cuGraphNodeSetParams"] = <intptr_t>__cuGraphNodeSetParams
 
     global __cuGraphExecNodeSetParams
-    data["__cuGraphExecNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecNodeSetParams
+    data["__cuGraphExecNodeSetParams"] = <intptr_t>__cuGraphExecNodeSetParams
 
     global __cuGraphConditionalHandleCreate
-    data["__cuGraphConditionalHandleCreate"] = <_cyb_intptr_t>__cuGraphConditionalHandleCreate
+    data["__cuGraphConditionalHandleCreate"] = <intptr_t>__cuGraphConditionalHandleCreate
 
     global __cuOccupancyMaxActiveBlocksPerMultiprocessor
-    data["__cuOccupancyMaxActiveBlocksPerMultiprocessor"] = <_cyb_intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessor
+    data["__cuOccupancyMaxActiveBlocksPerMultiprocessor"] = <intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessor
 
     global __cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
-    data["__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags"] = <_cyb_intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
+    data["__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags"] = <intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
 
     global __cuOccupancyMaxPotentialBlockSize
-    data["__cuOccupancyMaxPotentialBlockSize"] = <_cyb_intptr_t>__cuOccupancyMaxPotentialBlockSize
+    data["__cuOccupancyMaxPotentialBlockSize"] = <intptr_t>__cuOccupancyMaxPotentialBlockSize
 
     global __cuOccupancyMaxPotentialBlockSizeWithFlags
-    data["__cuOccupancyMaxPotentialBlockSizeWithFlags"] = <_cyb_intptr_t>__cuOccupancyMaxPotentialBlockSizeWithFlags
+    data["__cuOccupancyMaxPotentialBlockSizeWithFlags"] = <intptr_t>__cuOccupancyMaxPotentialBlockSizeWithFlags
 
     global __cuOccupancyAvailableDynamicSMemPerBlock
-    data["__cuOccupancyAvailableDynamicSMemPerBlock"] = <_cyb_intptr_t>__cuOccupancyAvailableDynamicSMemPerBlock
+    data["__cuOccupancyAvailableDynamicSMemPerBlock"] = <intptr_t>__cuOccupancyAvailableDynamicSMemPerBlock
 
     global __cuOccupancyMaxPotentialClusterSize
-    data["__cuOccupancyMaxPotentialClusterSize"] = <_cyb_intptr_t>__cuOccupancyMaxPotentialClusterSize
+    data["__cuOccupancyMaxPotentialClusterSize"] = <intptr_t>__cuOccupancyMaxPotentialClusterSize
 
     global __cuOccupancyMaxActiveClusters
-    data["__cuOccupancyMaxActiveClusters"] = <_cyb_intptr_t>__cuOccupancyMaxActiveClusters
+    data["__cuOccupancyMaxActiveClusters"] = <intptr_t>__cuOccupancyMaxActiveClusters
 
     global __cuTexRefSetArray
-    data["__cuTexRefSetArray"] = <_cyb_intptr_t>__cuTexRefSetArray
+    data["__cuTexRefSetArray"] = <intptr_t>__cuTexRefSetArray
 
     global __cuTexRefSetMipmappedArray
-    data["__cuTexRefSetMipmappedArray"] = <_cyb_intptr_t>__cuTexRefSetMipmappedArray
+    data["__cuTexRefSetMipmappedArray"] = <intptr_t>__cuTexRefSetMipmappedArray
 
     global __cuTexRefSetAddress_v2
-    data["__cuTexRefSetAddress_v2"] = <_cyb_intptr_t>__cuTexRefSetAddress_v2
+    data["__cuTexRefSetAddress_v2"] = <intptr_t>__cuTexRefSetAddress_v2
 
     global __cuTexRefSetAddress2D_v3
-    data["__cuTexRefSetAddress2D_v3"] = <_cyb_intptr_t>__cuTexRefSetAddress2D_v3
+    data["__cuTexRefSetAddress2D_v3"] = <intptr_t>__cuTexRefSetAddress2D_v3
 
     global __cuTexRefSetFormat
-    data["__cuTexRefSetFormat"] = <_cyb_intptr_t>__cuTexRefSetFormat
+    data["__cuTexRefSetFormat"] = <intptr_t>__cuTexRefSetFormat
 
     global __cuTexRefSetAddressMode
-    data["__cuTexRefSetAddressMode"] = <_cyb_intptr_t>__cuTexRefSetAddressMode
+    data["__cuTexRefSetAddressMode"] = <intptr_t>__cuTexRefSetAddressMode
 
     global __cuTexRefSetFilterMode
-    data["__cuTexRefSetFilterMode"] = <_cyb_intptr_t>__cuTexRefSetFilterMode
+    data["__cuTexRefSetFilterMode"] = <intptr_t>__cuTexRefSetFilterMode
 
     global __cuTexRefSetMipmapFilterMode
-    data["__cuTexRefSetMipmapFilterMode"] = <_cyb_intptr_t>__cuTexRefSetMipmapFilterMode
+    data["__cuTexRefSetMipmapFilterMode"] = <intptr_t>__cuTexRefSetMipmapFilterMode
 
     global __cuTexRefSetMipmapLevelBias
-    data["__cuTexRefSetMipmapLevelBias"] = <_cyb_intptr_t>__cuTexRefSetMipmapLevelBias
+    data["__cuTexRefSetMipmapLevelBias"] = <intptr_t>__cuTexRefSetMipmapLevelBias
 
     global __cuTexRefSetMipmapLevelClamp
-    data["__cuTexRefSetMipmapLevelClamp"] = <_cyb_intptr_t>__cuTexRefSetMipmapLevelClamp
+    data["__cuTexRefSetMipmapLevelClamp"] = <intptr_t>__cuTexRefSetMipmapLevelClamp
 
     global __cuTexRefSetMaxAnisotropy
-    data["__cuTexRefSetMaxAnisotropy"] = <_cyb_intptr_t>__cuTexRefSetMaxAnisotropy
+    data["__cuTexRefSetMaxAnisotropy"] = <intptr_t>__cuTexRefSetMaxAnisotropy
 
     global __cuTexRefSetBorderColor
-    data["__cuTexRefSetBorderColor"] = <_cyb_intptr_t>__cuTexRefSetBorderColor
+    data["__cuTexRefSetBorderColor"] = <intptr_t>__cuTexRefSetBorderColor
 
     global __cuTexRefSetFlags
-    data["__cuTexRefSetFlags"] = <_cyb_intptr_t>__cuTexRefSetFlags
+    data["__cuTexRefSetFlags"] = <intptr_t>__cuTexRefSetFlags
 
     global __cuTexRefGetAddress_v2
-    data["__cuTexRefGetAddress_v2"] = <_cyb_intptr_t>__cuTexRefGetAddress_v2
+    data["__cuTexRefGetAddress_v2"] = <intptr_t>__cuTexRefGetAddress_v2
 
     global __cuTexRefGetArray
-    data["__cuTexRefGetArray"] = <_cyb_intptr_t>__cuTexRefGetArray
+    data["__cuTexRefGetArray"] = <intptr_t>__cuTexRefGetArray
 
     global __cuTexRefGetMipmappedArray
-    data["__cuTexRefGetMipmappedArray"] = <_cyb_intptr_t>__cuTexRefGetMipmappedArray
+    data["__cuTexRefGetMipmappedArray"] = <intptr_t>__cuTexRefGetMipmappedArray
 
     global __cuTexRefGetAddressMode
-    data["__cuTexRefGetAddressMode"] = <_cyb_intptr_t>__cuTexRefGetAddressMode
+    data["__cuTexRefGetAddressMode"] = <intptr_t>__cuTexRefGetAddressMode
 
     global __cuTexRefGetFilterMode
-    data["__cuTexRefGetFilterMode"] = <_cyb_intptr_t>__cuTexRefGetFilterMode
+    data["__cuTexRefGetFilterMode"] = <intptr_t>__cuTexRefGetFilterMode
 
     global __cuTexRefGetFormat
-    data["__cuTexRefGetFormat"] = <_cyb_intptr_t>__cuTexRefGetFormat
+    data["__cuTexRefGetFormat"] = <intptr_t>__cuTexRefGetFormat
 
     global __cuTexRefGetMipmapFilterMode
-    data["__cuTexRefGetMipmapFilterMode"] = <_cyb_intptr_t>__cuTexRefGetMipmapFilterMode
+    data["__cuTexRefGetMipmapFilterMode"] = <intptr_t>__cuTexRefGetMipmapFilterMode
 
     global __cuTexRefGetMipmapLevelBias
-    data["__cuTexRefGetMipmapLevelBias"] = <_cyb_intptr_t>__cuTexRefGetMipmapLevelBias
+    data["__cuTexRefGetMipmapLevelBias"] = <intptr_t>__cuTexRefGetMipmapLevelBias
 
     global __cuTexRefGetMipmapLevelClamp
-    data["__cuTexRefGetMipmapLevelClamp"] = <_cyb_intptr_t>__cuTexRefGetMipmapLevelClamp
+    data["__cuTexRefGetMipmapLevelClamp"] = <intptr_t>__cuTexRefGetMipmapLevelClamp
 
     global __cuTexRefGetMaxAnisotropy
-    data["__cuTexRefGetMaxAnisotropy"] = <_cyb_intptr_t>__cuTexRefGetMaxAnisotropy
+    data["__cuTexRefGetMaxAnisotropy"] = <intptr_t>__cuTexRefGetMaxAnisotropy
 
     global __cuTexRefGetBorderColor
-    data["__cuTexRefGetBorderColor"] = <_cyb_intptr_t>__cuTexRefGetBorderColor
+    data["__cuTexRefGetBorderColor"] = <intptr_t>__cuTexRefGetBorderColor
 
     global __cuTexRefGetFlags
-    data["__cuTexRefGetFlags"] = <_cyb_intptr_t>__cuTexRefGetFlags
+    data["__cuTexRefGetFlags"] = <intptr_t>__cuTexRefGetFlags
 
     global __cuTexRefCreate
-    data["__cuTexRefCreate"] = <_cyb_intptr_t>__cuTexRefCreate
+    data["__cuTexRefCreate"] = <intptr_t>__cuTexRefCreate
 
     global __cuTexRefDestroy
-    data["__cuTexRefDestroy"] = <_cyb_intptr_t>__cuTexRefDestroy
+    data["__cuTexRefDestroy"] = <intptr_t>__cuTexRefDestroy
 
     global __cuSurfRefSetArray
-    data["__cuSurfRefSetArray"] = <_cyb_intptr_t>__cuSurfRefSetArray
+    data["__cuSurfRefSetArray"] = <intptr_t>__cuSurfRefSetArray
 
     global __cuSurfRefGetArray
-    data["__cuSurfRefGetArray"] = <_cyb_intptr_t>__cuSurfRefGetArray
+    data["__cuSurfRefGetArray"] = <intptr_t>__cuSurfRefGetArray
 
     global __cuTexObjectCreate
-    data["__cuTexObjectCreate"] = <_cyb_intptr_t>__cuTexObjectCreate
+    data["__cuTexObjectCreate"] = <intptr_t>__cuTexObjectCreate
 
     global __cuTexObjectDestroy
-    data["__cuTexObjectDestroy"] = <_cyb_intptr_t>__cuTexObjectDestroy
+    data["__cuTexObjectDestroy"] = <intptr_t>__cuTexObjectDestroy
 
     global __cuTexObjectGetResourceDesc
-    data["__cuTexObjectGetResourceDesc"] = <_cyb_intptr_t>__cuTexObjectGetResourceDesc
+    data["__cuTexObjectGetResourceDesc"] = <intptr_t>__cuTexObjectGetResourceDesc
 
     global __cuTexObjectGetTextureDesc
-    data["__cuTexObjectGetTextureDesc"] = <_cyb_intptr_t>__cuTexObjectGetTextureDesc
+    data["__cuTexObjectGetTextureDesc"] = <intptr_t>__cuTexObjectGetTextureDesc
 
     global __cuTexObjectGetResourceViewDesc
-    data["__cuTexObjectGetResourceViewDesc"] = <_cyb_intptr_t>__cuTexObjectGetResourceViewDesc
+    data["__cuTexObjectGetResourceViewDesc"] = <intptr_t>__cuTexObjectGetResourceViewDesc
 
     global __cuSurfObjectCreate
-    data["__cuSurfObjectCreate"] = <_cyb_intptr_t>__cuSurfObjectCreate
+    data["__cuSurfObjectCreate"] = <intptr_t>__cuSurfObjectCreate
 
     global __cuSurfObjectDestroy
-    data["__cuSurfObjectDestroy"] = <_cyb_intptr_t>__cuSurfObjectDestroy
+    data["__cuSurfObjectDestroy"] = <intptr_t>__cuSurfObjectDestroy
 
     global __cuSurfObjectGetResourceDesc
-    data["__cuSurfObjectGetResourceDesc"] = <_cyb_intptr_t>__cuSurfObjectGetResourceDesc
+    data["__cuSurfObjectGetResourceDesc"] = <intptr_t>__cuSurfObjectGetResourceDesc
 
     global __cuTensorMapEncodeTiled
-    data["__cuTensorMapEncodeTiled"] = <_cyb_intptr_t>__cuTensorMapEncodeTiled
+    data["__cuTensorMapEncodeTiled"] = <intptr_t>__cuTensorMapEncodeTiled
 
     global __cuTensorMapEncodeIm2col
-    data["__cuTensorMapEncodeIm2col"] = <_cyb_intptr_t>__cuTensorMapEncodeIm2col
+    data["__cuTensorMapEncodeIm2col"] = <intptr_t>__cuTensorMapEncodeIm2col
 
     global __cuTensorMapEncodeIm2colWide
-    data["__cuTensorMapEncodeIm2colWide"] = <_cyb_intptr_t>__cuTensorMapEncodeIm2colWide
+    data["__cuTensorMapEncodeIm2colWide"] = <intptr_t>__cuTensorMapEncodeIm2colWide
 
     global __cuTensorMapReplaceAddress
-    data["__cuTensorMapReplaceAddress"] = <_cyb_intptr_t>__cuTensorMapReplaceAddress
+    data["__cuTensorMapReplaceAddress"] = <intptr_t>__cuTensorMapReplaceAddress
 
     global __cuDeviceCanAccessPeer
-    data["__cuDeviceCanAccessPeer"] = <_cyb_intptr_t>__cuDeviceCanAccessPeer
+    data["__cuDeviceCanAccessPeer"] = <intptr_t>__cuDeviceCanAccessPeer
 
     global __cuCtxEnablePeerAccess
-    data["__cuCtxEnablePeerAccess"] = <_cyb_intptr_t>__cuCtxEnablePeerAccess
+    data["__cuCtxEnablePeerAccess"] = <intptr_t>__cuCtxEnablePeerAccess
 
     global __cuCtxDisablePeerAccess
-    data["__cuCtxDisablePeerAccess"] = <_cyb_intptr_t>__cuCtxDisablePeerAccess
+    data["__cuCtxDisablePeerAccess"] = <intptr_t>__cuCtxDisablePeerAccess
 
     global __cuDeviceGetP2PAttribute
-    data["__cuDeviceGetP2PAttribute"] = <_cyb_intptr_t>__cuDeviceGetP2PAttribute
+    data["__cuDeviceGetP2PAttribute"] = <intptr_t>__cuDeviceGetP2PAttribute
 
     global __cuGraphicsUnregisterResource
-    data["__cuGraphicsUnregisterResource"] = <_cyb_intptr_t>__cuGraphicsUnregisterResource
+    data["__cuGraphicsUnregisterResource"] = <intptr_t>__cuGraphicsUnregisterResource
 
     global __cuGraphicsSubResourceGetMappedArray
-    data["__cuGraphicsSubResourceGetMappedArray"] = <_cyb_intptr_t>__cuGraphicsSubResourceGetMappedArray
+    data["__cuGraphicsSubResourceGetMappedArray"] = <intptr_t>__cuGraphicsSubResourceGetMappedArray
 
     global __cuGraphicsResourceGetMappedMipmappedArray
-    data["__cuGraphicsResourceGetMappedMipmappedArray"] = <_cyb_intptr_t>__cuGraphicsResourceGetMappedMipmappedArray
+    data["__cuGraphicsResourceGetMappedMipmappedArray"] = <intptr_t>__cuGraphicsResourceGetMappedMipmappedArray
 
     global __cuGraphicsResourceGetMappedPointer_v2
-    data["__cuGraphicsResourceGetMappedPointer_v2"] = <_cyb_intptr_t>__cuGraphicsResourceGetMappedPointer_v2
+    data["__cuGraphicsResourceGetMappedPointer_v2"] = <intptr_t>__cuGraphicsResourceGetMappedPointer_v2
 
     global __cuGraphicsResourceSetMapFlags_v2
-    data["__cuGraphicsResourceSetMapFlags_v2"] = <_cyb_intptr_t>__cuGraphicsResourceSetMapFlags_v2
+    data["__cuGraphicsResourceSetMapFlags_v2"] = <intptr_t>__cuGraphicsResourceSetMapFlags_v2
 
     global __cuGraphicsMapResources
-    data["__cuGraphicsMapResources"] = <_cyb_intptr_t>__cuGraphicsMapResources
+    data["__cuGraphicsMapResources"] = <intptr_t>__cuGraphicsMapResources
 
     global __cuGraphicsUnmapResources
-    data["__cuGraphicsUnmapResources"] = <_cyb_intptr_t>__cuGraphicsUnmapResources
+    data["__cuGraphicsUnmapResources"] = <intptr_t>__cuGraphicsUnmapResources
 
     global __cuGetProcAddress_v2
-    data["__cuGetProcAddress_v2"] = <_cyb_intptr_t>__cuGetProcAddress_v2
+    data["__cuGetProcAddress_v2"] = <intptr_t>__cuGetProcAddress_v2
 
     global __cuCoredumpGetAttribute
-    data["__cuCoredumpGetAttribute"] = <_cyb_intptr_t>__cuCoredumpGetAttribute
+    data["__cuCoredumpGetAttribute"] = <intptr_t>__cuCoredumpGetAttribute
 
     global __cuCoredumpGetAttributeGlobal
-    data["__cuCoredumpGetAttributeGlobal"] = <_cyb_intptr_t>__cuCoredumpGetAttributeGlobal
+    data["__cuCoredumpGetAttributeGlobal"] = <intptr_t>__cuCoredumpGetAttributeGlobal
 
     global __cuCoredumpSetAttribute
-    data["__cuCoredumpSetAttribute"] = <_cyb_intptr_t>__cuCoredumpSetAttribute
+    data["__cuCoredumpSetAttribute"] = <intptr_t>__cuCoredumpSetAttribute
 
     global __cuCoredumpSetAttributeGlobal
-    data["__cuCoredumpSetAttributeGlobal"] = <_cyb_intptr_t>__cuCoredumpSetAttributeGlobal
+    data["__cuCoredumpSetAttributeGlobal"] = <intptr_t>__cuCoredumpSetAttributeGlobal
 
     global __cuGetExportTable
-    data["__cuGetExportTable"] = <_cyb_intptr_t>__cuGetExportTable
+    data["__cuGetExportTable"] = <intptr_t>__cuGetExportTable
 
     global __cuGreenCtxCreate
-    data["__cuGreenCtxCreate"] = <_cyb_intptr_t>__cuGreenCtxCreate
+    data["__cuGreenCtxCreate"] = <intptr_t>__cuGreenCtxCreate
 
     global __cuGreenCtxDestroy
-    data["__cuGreenCtxDestroy"] = <_cyb_intptr_t>__cuGreenCtxDestroy
+    data["__cuGreenCtxDestroy"] = <intptr_t>__cuGreenCtxDestroy
 
     global __cuCtxFromGreenCtx
-    data["__cuCtxFromGreenCtx"] = <_cyb_intptr_t>__cuCtxFromGreenCtx
+    data["__cuCtxFromGreenCtx"] = <intptr_t>__cuCtxFromGreenCtx
 
     global __cuDeviceGetDevResource
-    data["__cuDeviceGetDevResource"] = <_cyb_intptr_t>__cuDeviceGetDevResource
+    data["__cuDeviceGetDevResource"] = <intptr_t>__cuDeviceGetDevResource
 
     global __cuCtxGetDevResource
-    data["__cuCtxGetDevResource"] = <_cyb_intptr_t>__cuCtxGetDevResource
+    data["__cuCtxGetDevResource"] = <intptr_t>__cuCtxGetDevResource
 
     global __cuGreenCtxGetDevResource
-    data["__cuGreenCtxGetDevResource"] = <_cyb_intptr_t>__cuGreenCtxGetDevResource
+    data["__cuGreenCtxGetDevResource"] = <intptr_t>__cuGreenCtxGetDevResource
 
     global __cuDevSmResourceSplitByCount
-    data["__cuDevSmResourceSplitByCount"] = <_cyb_intptr_t>__cuDevSmResourceSplitByCount
+    data["__cuDevSmResourceSplitByCount"] = <intptr_t>__cuDevSmResourceSplitByCount
 
     global __cuDevResourceGenerateDesc
-    data["__cuDevResourceGenerateDesc"] = <_cyb_intptr_t>__cuDevResourceGenerateDesc
+    data["__cuDevResourceGenerateDesc"] = <intptr_t>__cuDevResourceGenerateDesc
 
     global __cuGreenCtxRecordEvent
-    data["__cuGreenCtxRecordEvent"] = <_cyb_intptr_t>__cuGreenCtxRecordEvent
+    data["__cuGreenCtxRecordEvent"] = <intptr_t>__cuGreenCtxRecordEvent
 
     global __cuGreenCtxWaitEvent
-    data["__cuGreenCtxWaitEvent"] = <_cyb_intptr_t>__cuGreenCtxWaitEvent
+    data["__cuGreenCtxWaitEvent"] = <intptr_t>__cuGreenCtxWaitEvent
 
     global __cuStreamGetGreenCtx
-    data["__cuStreamGetGreenCtx"] = <_cyb_intptr_t>__cuStreamGetGreenCtx
+    data["__cuStreamGetGreenCtx"] = <intptr_t>__cuStreamGetGreenCtx
 
     global __cuGreenCtxStreamCreate
-    data["__cuGreenCtxStreamCreate"] = <_cyb_intptr_t>__cuGreenCtxStreamCreate
+    data["__cuGreenCtxStreamCreate"] = <intptr_t>__cuGreenCtxStreamCreate
 
     global __cuLogsRegisterCallback
-    data["__cuLogsRegisterCallback"] = <_cyb_intptr_t>__cuLogsRegisterCallback
+    data["__cuLogsRegisterCallback"] = <intptr_t>__cuLogsRegisterCallback
 
     global __cuLogsUnregisterCallback
-    data["__cuLogsUnregisterCallback"] = <_cyb_intptr_t>__cuLogsUnregisterCallback
+    data["__cuLogsUnregisterCallback"] = <intptr_t>__cuLogsUnregisterCallback
 
     global __cuLogsCurrent
-    data["__cuLogsCurrent"] = <_cyb_intptr_t>__cuLogsCurrent
+    data["__cuLogsCurrent"] = <intptr_t>__cuLogsCurrent
 
     global __cuLogsDumpToFile
-    data["__cuLogsDumpToFile"] = <_cyb_intptr_t>__cuLogsDumpToFile
+    data["__cuLogsDumpToFile"] = <intptr_t>__cuLogsDumpToFile
 
     global __cuLogsDumpToMemory
-    data["__cuLogsDumpToMemory"] = <_cyb_intptr_t>__cuLogsDumpToMemory
+    data["__cuLogsDumpToMemory"] = <intptr_t>__cuLogsDumpToMemory
 
     global __cuCheckpointProcessGetRestoreThreadId
-    data["__cuCheckpointProcessGetRestoreThreadId"] = <_cyb_intptr_t>__cuCheckpointProcessGetRestoreThreadId
+    data["__cuCheckpointProcessGetRestoreThreadId"] = <intptr_t>__cuCheckpointProcessGetRestoreThreadId
 
     global __cuCheckpointProcessGetState
-    data["__cuCheckpointProcessGetState"] = <_cyb_intptr_t>__cuCheckpointProcessGetState
+    data["__cuCheckpointProcessGetState"] = <intptr_t>__cuCheckpointProcessGetState
 
     global __cuCheckpointProcessLock
-    data["__cuCheckpointProcessLock"] = <_cyb_intptr_t>__cuCheckpointProcessLock
+    data["__cuCheckpointProcessLock"] = <intptr_t>__cuCheckpointProcessLock
 
     global __cuCheckpointProcessCheckpoint
-    data["__cuCheckpointProcessCheckpoint"] = <_cyb_intptr_t>__cuCheckpointProcessCheckpoint
+    data["__cuCheckpointProcessCheckpoint"] = <intptr_t>__cuCheckpointProcessCheckpoint
 
     global __cuCheckpointProcessRestore
-    data["__cuCheckpointProcessRestore"] = <_cyb_intptr_t>__cuCheckpointProcessRestore
+    data["__cuCheckpointProcessRestore"] = <intptr_t>__cuCheckpointProcessRestore
 
     global __cuCheckpointProcessUnlock
-    data["__cuCheckpointProcessUnlock"] = <_cyb_intptr_t>__cuCheckpointProcessUnlock
+    data["__cuCheckpointProcessUnlock"] = <intptr_t>__cuCheckpointProcessUnlock
 
     global __cuGraphicsEGLRegisterImage
-    data["__cuGraphicsEGLRegisterImage"] = <_cyb_intptr_t>__cuGraphicsEGLRegisterImage
+    data["__cuGraphicsEGLRegisterImage"] = <intptr_t>__cuGraphicsEGLRegisterImage
 
     global __cuEGLStreamConsumerConnect
-    data["__cuEGLStreamConsumerConnect"] = <_cyb_intptr_t>__cuEGLStreamConsumerConnect
+    data["__cuEGLStreamConsumerConnect"] = <intptr_t>__cuEGLStreamConsumerConnect
 
     global __cuEGLStreamConsumerConnectWithFlags
-    data["__cuEGLStreamConsumerConnectWithFlags"] = <_cyb_intptr_t>__cuEGLStreamConsumerConnectWithFlags
+    data["__cuEGLStreamConsumerConnectWithFlags"] = <intptr_t>__cuEGLStreamConsumerConnectWithFlags
 
     global __cuEGLStreamConsumerDisconnect
-    data["__cuEGLStreamConsumerDisconnect"] = <_cyb_intptr_t>__cuEGLStreamConsumerDisconnect
+    data["__cuEGLStreamConsumerDisconnect"] = <intptr_t>__cuEGLStreamConsumerDisconnect
 
     global __cuEGLStreamConsumerAcquireFrame
-    data["__cuEGLStreamConsumerAcquireFrame"] = <_cyb_intptr_t>__cuEGLStreamConsumerAcquireFrame
+    data["__cuEGLStreamConsumerAcquireFrame"] = <intptr_t>__cuEGLStreamConsumerAcquireFrame
 
     global __cuEGLStreamConsumerReleaseFrame
-    data["__cuEGLStreamConsumerReleaseFrame"] = <_cyb_intptr_t>__cuEGLStreamConsumerReleaseFrame
+    data["__cuEGLStreamConsumerReleaseFrame"] = <intptr_t>__cuEGLStreamConsumerReleaseFrame
 
     global __cuEGLStreamProducerConnect
-    data["__cuEGLStreamProducerConnect"] = <_cyb_intptr_t>__cuEGLStreamProducerConnect
+    data["__cuEGLStreamProducerConnect"] = <intptr_t>__cuEGLStreamProducerConnect
 
     global __cuEGLStreamProducerDisconnect
-    data["__cuEGLStreamProducerDisconnect"] = <_cyb_intptr_t>__cuEGLStreamProducerDisconnect
+    data["__cuEGLStreamProducerDisconnect"] = <intptr_t>__cuEGLStreamProducerDisconnect
 
     global __cuEGLStreamProducerPresentFrame
-    data["__cuEGLStreamProducerPresentFrame"] = <_cyb_intptr_t>__cuEGLStreamProducerPresentFrame
+    data["__cuEGLStreamProducerPresentFrame"] = <intptr_t>__cuEGLStreamProducerPresentFrame
 
     global __cuEGLStreamProducerReturnFrame
-    data["__cuEGLStreamProducerReturnFrame"] = <_cyb_intptr_t>__cuEGLStreamProducerReturnFrame
+    data["__cuEGLStreamProducerReturnFrame"] = <intptr_t>__cuEGLStreamProducerReturnFrame
 
     global __cuGraphicsResourceGetMappedEglFrame
-    data["__cuGraphicsResourceGetMappedEglFrame"] = <_cyb_intptr_t>__cuGraphicsResourceGetMappedEglFrame
+    data["__cuGraphicsResourceGetMappedEglFrame"] = <intptr_t>__cuGraphicsResourceGetMappedEglFrame
 
     global __cuEventCreateFromEGLSync
-    data["__cuEventCreateFromEGLSync"] = <_cyb_intptr_t>__cuEventCreateFromEGLSync
+    data["__cuEventCreateFromEGLSync"] = <intptr_t>__cuEventCreateFromEGLSync
 
     global __cuGraphicsGLRegisterBuffer
-    data["__cuGraphicsGLRegisterBuffer"] = <_cyb_intptr_t>__cuGraphicsGLRegisterBuffer
+    data["__cuGraphicsGLRegisterBuffer"] = <intptr_t>__cuGraphicsGLRegisterBuffer
 
     global __cuGraphicsGLRegisterImage
-    data["__cuGraphicsGLRegisterImage"] = <_cyb_intptr_t>__cuGraphicsGLRegisterImage
+    data["__cuGraphicsGLRegisterImage"] = <intptr_t>__cuGraphicsGLRegisterImage
 
     global __cuGLGetDevices_v2
-    data["__cuGLGetDevices_v2"] = <_cyb_intptr_t>__cuGLGetDevices_v2
+    data["__cuGLGetDevices_v2"] = <intptr_t>__cuGLGetDevices_v2
 
     global __cuGLCtxCreate_v2
-    data["__cuGLCtxCreate_v2"] = <_cyb_intptr_t>__cuGLCtxCreate_v2
+    data["__cuGLCtxCreate_v2"] = <intptr_t>__cuGLCtxCreate_v2
 
     global __cuGLInit
-    data["__cuGLInit"] = <_cyb_intptr_t>__cuGLInit
+    data["__cuGLInit"] = <intptr_t>__cuGLInit
 
     global __cuGLRegisterBufferObject
-    data["__cuGLRegisterBufferObject"] = <_cyb_intptr_t>__cuGLRegisterBufferObject
+    data["__cuGLRegisterBufferObject"] = <intptr_t>__cuGLRegisterBufferObject
 
     global __cuGLMapBufferObject_v2
-    data["__cuGLMapBufferObject_v2"] = <_cyb_intptr_t>__cuGLMapBufferObject_v2
+    data["__cuGLMapBufferObject_v2"] = <intptr_t>__cuGLMapBufferObject_v2
 
     global __cuGLUnmapBufferObject
-    data["__cuGLUnmapBufferObject"] = <_cyb_intptr_t>__cuGLUnmapBufferObject
+    data["__cuGLUnmapBufferObject"] = <intptr_t>__cuGLUnmapBufferObject
 
     global __cuGLUnregisterBufferObject
-    data["__cuGLUnregisterBufferObject"] = <_cyb_intptr_t>__cuGLUnregisterBufferObject
+    data["__cuGLUnregisterBufferObject"] = <intptr_t>__cuGLUnregisterBufferObject
 
     global __cuGLSetBufferObjectMapFlags
-    data["__cuGLSetBufferObjectMapFlags"] = <_cyb_intptr_t>__cuGLSetBufferObjectMapFlags
+    data["__cuGLSetBufferObjectMapFlags"] = <intptr_t>__cuGLSetBufferObjectMapFlags
 
     global __cuGLMapBufferObjectAsync_v2
-    data["__cuGLMapBufferObjectAsync_v2"] = <_cyb_intptr_t>__cuGLMapBufferObjectAsync_v2
+    data["__cuGLMapBufferObjectAsync_v2"] = <intptr_t>__cuGLMapBufferObjectAsync_v2
 
     global __cuGLUnmapBufferObjectAsync
-    data["__cuGLUnmapBufferObjectAsync"] = <_cyb_intptr_t>__cuGLUnmapBufferObjectAsync
+    data["__cuGLUnmapBufferObjectAsync"] = <intptr_t>__cuGLUnmapBufferObjectAsync
 
     global __cuProfilerInitialize
-    data["__cuProfilerInitialize"] = <_cyb_intptr_t>__cuProfilerInitialize
+    data["__cuProfilerInitialize"] = <intptr_t>__cuProfilerInitialize
 
     global __cuProfilerStart
-    data["__cuProfilerStart"] = <_cyb_intptr_t>__cuProfilerStart
+    data["__cuProfilerStart"] = <intptr_t>__cuProfilerStart
 
     global __cuProfilerStop
-    data["__cuProfilerStop"] = <_cyb_intptr_t>__cuProfilerStop
+    data["__cuProfilerStop"] = <intptr_t>__cuProfilerStop
 
     global __cuVDPAUGetDevice
-    data["__cuVDPAUGetDevice"] = <_cyb_intptr_t>__cuVDPAUGetDevice
+    data["__cuVDPAUGetDevice"] = <intptr_t>__cuVDPAUGetDevice
 
     global __cuVDPAUCtxCreate_v2
-    data["__cuVDPAUCtxCreate_v2"] = <_cyb_intptr_t>__cuVDPAUCtxCreate_v2
+    data["__cuVDPAUCtxCreate_v2"] = <intptr_t>__cuVDPAUCtxCreate_v2
 
     global __cuGraphicsVDPAURegisterVideoSurface
-    data["__cuGraphicsVDPAURegisterVideoSurface"] = <_cyb_intptr_t>__cuGraphicsVDPAURegisterVideoSurface
+    data["__cuGraphicsVDPAURegisterVideoSurface"] = <intptr_t>__cuGraphicsVDPAURegisterVideoSurface
 
     global __cuGraphicsVDPAURegisterOutputSurface
-    data["__cuGraphicsVDPAURegisterOutputSurface"] = <_cyb_intptr_t>__cuGraphicsVDPAURegisterOutputSurface
+    data["__cuGraphicsVDPAURegisterOutputSurface"] = <intptr_t>__cuGraphicsVDPAURegisterOutputSurface
 
     global __cuDeviceGetHostAtomicCapabilities
-    data["__cuDeviceGetHostAtomicCapabilities"] = <_cyb_intptr_t>__cuDeviceGetHostAtomicCapabilities
+    data["__cuDeviceGetHostAtomicCapabilities"] = <intptr_t>__cuDeviceGetHostAtomicCapabilities
 
     global __cuCtxGetDevice_v2
-    data["__cuCtxGetDevice_v2"] = <_cyb_intptr_t>__cuCtxGetDevice_v2
+    data["__cuCtxGetDevice_v2"] = <intptr_t>__cuCtxGetDevice_v2
 
     global __cuCtxSynchronize_v2
-    data["__cuCtxSynchronize_v2"] = <_cyb_intptr_t>__cuCtxSynchronize_v2
+    data["__cuCtxSynchronize_v2"] = <intptr_t>__cuCtxSynchronize_v2
 
     global __cuMemcpyBatchAsync_v2
-    data["__cuMemcpyBatchAsync_v2"] = <_cyb_intptr_t>__cuMemcpyBatchAsync_v2
+    data["__cuMemcpyBatchAsync_v2"] = <intptr_t>__cuMemcpyBatchAsync_v2
 
     global __cuMemcpy3DBatchAsync_v2
-    data["__cuMemcpy3DBatchAsync_v2"] = <_cyb_intptr_t>__cuMemcpy3DBatchAsync_v2
+    data["__cuMemcpy3DBatchAsync_v2"] = <intptr_t>__cuMemcpy3DBatchAsync_v2
 
     global __cuMemGetDefaultMemPool
-    data["__cuMemGetDefaultMemPool"] = <_cyb_intptr_t>__cuMemGetDefaultMemPool
+    data["__cuMemGetDefaultMemPool"] = <intptr_t>__cuMemGetDefaultMemPool
 
     global __cuMemGetMemPool
-    data["__cuMemGetMemPool"] = <_cyb_intptr_t>__cuMemGetMemPool
+    data["__cuMemGetMemPool"] = <intptr_t>__cuMemGetMemPool
 
     global __cuMemSetMemPool
-    data["__cuMemSetMemPool"] = <_cyb_intptr_t>__cuMemSetMemPool
+    data["__cuMemSetMemPool"] = <intptr_t>__cuMemSetMemPool
 
     global __cuMemPrefetchBatchAsync
-    data["__cuMemPrefetchBatchAsync"] = <_cyb_intptr_t>__cuMemPrefetchBatchAsync
+    data["__cuMemPrefetchBatchAsync"] = <intptr_t>__cuMemPrefetchBatchAsync
 
     global __cuMemDiscardBatchAsync
-    data["__cuMemDiscardBatchAsync"] = <_cyb_intptr_t>__cuMemDiscardBatchAsync
+    data["__cuMemDiscardBatchAsync"] = <intptr_t>__cuMemDiscardBatchAsync
 
     global __cuMemDiscardAndPrefetchBatchAsync
-    data["__cuMemDiscardAndPrefetchBatchAsync"] = <_cyb_intptr_t>__cuMemDiscardAndPrefetchBatchAsync
+    data["__cuMemDiscardAndPrefetchBatchAsync"] = <intptr_t>__cuMemDiscardAndPrefetchBatchAsync
 
     global __cuDeviceGetP2PAtomicCapabilities
-    data["__cuDeviceGetP2PAtomicCapabilities"] = <_cyb_intptr_t>__cuDeviceGetP2PAtomicCapabilities
+    data["__cuDeviceGetP2PAtomicCapabilities"] = <intptr_t>__cuDeviceGetP2PAtomicCapabilities
 
     global __cuGreenCtxGetId
-    data["__cuGreenCtxGetId"] = <_cyb_intptr_t>__cuGreenCtxGetId
+    data["__cuGreenCtxGetId"] = <intptr_t>__cuGreenCtxGetId
 
     global __cuMulticastBindMem_v2
-    data["__cuMulticastBindMem_v2"] = <_cyb_intptr_t>__cuMulticastBindMem_v2
+    data["__cuMulticastBindMem_v2"] = <intptr_t>__cuMulticastBindMem_v2
 
     global __cuMulticastBindAddr_v2
-    data["__cuMulticastBindAddr_v2"] = <_cyb_intptr_t>__cuMulticastBindAddr_v2
+    data["__cuMulticastBindAddr_v2"] = <intptr_t>__cuMulticastBindAddr_v2
 
     global __cuGraphNodeGetContainingGraph
-    data["__cuGraphNodeGetContainingGraph"] = <_cyb_intptr_t>__cuGraphNodeGetContainingGraph
+    data["__cuGraphNodeGetContainingGraph"] = <intptr_t>__cuGraphNodeGetContainingGraph
 
     global __cuGraphNodeGetLocalId
-    data["__cuGraphNodeGetLocalId"] = <_cyb_intptr_t>__cuGraphNodeGetLocalId
+    data["__cuGraphNodeGetLocalId"] = <intptr_t>__cuGraphNodeGetLocalId
 
     global __cuGraphNodeGetToolsId
-    data["__cuGraphNodeGetToolsId"] = <_cyb_intptr_t>__cuGraphNodeGetToolsId
+    data["__cuGraphNodeGetToolsId"] = <intptr_t>__cuGraphNodeGetToolsId
 
     global __cuGraphGetId
-    data["__cuGraphGetId"] = <_cyb_intptr_t>__cuGraphGetId
+    data["__cuGraphGetId"] = <intptr_t>__cuGraphGetId
 
     global __cuGraphExecGetId
-    data["__cuGraphExecGetId"] = <_cyb_intptr_t>__cuGraphExecGetId
+    data["__cuGraphExecGetId"] = <intptr_t>__cuGraphExecGetId
 
     global __cuDevSmResourceSplit
-    data["__cuDevSmResourceSplit"] = <_cyb_intptr_t>__cuDevSmResourceSplit
+    data["__cuDevSmResourceSplit"] = <intptr_t>__cuDevSmResourceSplit
 
     global __cuStreamGetDevResource
-    data["__cuStreamGetDevResource"] = <_cyb_intptr_t>__cuStreamGetDevResource
+    data["__cuStreamGetDevResource"] = <intptr_t>__cuStreamGetDevResource
 
     global __cuKernelGetParamCount
-    data["__cuKernelGetParamCount"] = <_cyb_intptr_t>__cuKernelGetParamCount
+    data["__cuKernelGetParamCount"] = <intptr_t>__cuKernelGetParamCount
 
     global __cuMemcpyWithAttributesAsync
-    data["__cuMemcpyWithAttributesAsync"] = <_cyb_intptr_t>__cuMemcpyWithAttributesAsync
+    data["__cuMemcpyWithAttributesAsync"] = <intptr_t>__cuMemcpyWithAttributesAsync
 
     global __cuMemcpy3DWithAttributesAsync
-    data["__cuMemcpy3DWithAttributesAsync"] = <_cyb_intptr_t>__cuMemcpy3DWithAttributesAsync
+    data["__cuMemcpy3DWithAttributesAsync"] = <intptr_t>__cuMemcpy3DWithAttributesAsync
 
     global __cuStreamBeginCaptureToCig
-    data["__cuStreamBeginCaptureToCig"] = <_cyb_intptr_t>__cuStreamBeginCaptureToCig
+    data["__cuStreamBeginCaptureToCig"] = <intptr_t>__cuStreamBeginCaptureToCig
 
     global __cuStreamEndCaptureToCig
-    data["__cuStreamEndCaptureToCig"] = <_cyb_intptr_t>__cuStreamEndCaptureToCig
+    data["__cuStreamEndCaptureToCig"] = <intptr_t>__cuStreamEndCaptureToCig
 
     global __cuFuncGetParamCount
-    data["__cuFuncGetParamCount"] = <_cyb_intptr_t>__cuFuncGetParamCount
+    data["__cuFuncGetParamCount"] = <intptr_t>__cuFuncGetParamCount
 
     global __cuLaunchHostFunc_v2
-    data["__cuLaunchHostFunc_v2"] = <_cyb_intptr_t>__cuLaunchHostFunc_v2
+    data["__cuLaunchHostFunc_v2"] = <intptr_t>__cuLaunchHostFunc_v2
 
     global __cuGraphNodeGetParams
-    data["__cuGraphNodeGetParams"] = <_cyb_intptr_t>__cuGraphNodeGetParams
+    data["__cuGraphNodeGetParams"] = <intptr_t>__cuGraphNodeGetParams
 
     global __cuCoredumpRegisterStartCallback
-    data["__cuCoredumpRegisterStartCallback"] = <_cyb_intptr_t>__cuCoredumpRegisterStartCallback
+    data["__cuCoredumpRegisterStartCallback"] = <intptr_t>__cuCoredumpRegisterStartCallback
 
     global __cuCoredumpRegisterCompleteCallback
-    data["__cuCoredumpRegisterCompleteCallback"] = <_cyb_intptr_t>__cuCoredumpRegisterCompleteCallback
+    data["__cuCoredumpRegisterCompleteCallback"] = <intptr_t>__cuCoredumpRegisterCompleteCallback
 
     global __cuCoredumpDeregisterStartCallback
-    data["__cuCoredumpDeregisterStartCallback"] = <_cyb_intptr_t>__cuCoredumpDeregisterStartCallback
+    data["__cuCoredumpDeregisterStartCallback"] = <intptr_t>__cuCoredumpDeregisterStartCallback
 
     global __cuCoredumpDeregisterCompleteCallback
-    data["__cuCoredumpDeregisterCompleteCallback"] = <_cyb_intptr_t>__cuCoredumpDeregisterCompleteCallback
+    data["__cuCoredumpDeregisterCompleteCallback"] = <intptr_t>__cuCoredumpDeregisterCompleteCallback
 
     global __cuLogicalEndpointIdReserve
-    data["__cuLogicalEndpointIdReserve"] = <_cyb_intptr_t>__cuLogicalEndpointIdReserve
+    data["__cuLogicalEndpointIdReserve"] = <intptr_t>__cuLogicalEndpointIdReserve
 
     global __cuLogicalEndpointIdRelease
-    data["__cuLogicalEndpointIdRelease"] = <_cyb_intptr_t>__cuLogicalEndpointIdRelease
+    data["__cuLogicalEndpointIdRelease"] = <intptr_t>__cuLogicalEndpointIdRelease
 
     global __cuLogicalEndpointCreate
-    data["__cuLogicalEndpointCreate"] = <_cyb_intptr_t>__cuLogicalEndpointCreate
+    data["__cuLogicalEndpointCreate"] = <intptr_t>__cuLogicalEndpointCreate
 
     global __cuLogicalEndpointAddDevice
-    data["__cuLogicalEndpointAddDevice"] = <_cyb_intptr_t>__cuLogicalEndpointAddDevice
+    data["__cuLogicalEndpointAddDevice"] = <intptr_t>__cuLogicalEndpointAddDevice
 
     global __cuLogicalEndpointDestroy
-    data["__cuLogicalEndpointDestroy"] = <_cyb_intptr_t>__cuLogicalEndpointDestroy
+    data["__cuLogicalEndpointDestroy"] = <intptr_t>__cuLogicalEndpointDestroy
 
     global __cuLogicalEndpointBindAddr
-    data["__cuLogicalEndpointBindAddr"] = <_cyb_intptr_t>__cuLogicalEndpointBindAddr
+    data["__cuLogicalEndpointBindAddr"] = <intptr_t>__cuLogicalEndpointBindAddr
 
     global __cuLogicalEndpointBindMem
-    data["__cuLogicalEndpointBindMem"] = <_cyb_intptr_t>__cuLogicalEndpointBindMem
+    data["__cuLogicalEndpointBindMem"] = <intptr_t>__cuLogicalEndpointBindMem
 
     global __cuLogicalEndpointUnbind
-    data["__cuLogicalEndpointUnbind"] = <_cyb_intptr_t>__cuLogicalEndpointUnbind
+    data["__cuLogicalEndpointUnbind"] = <intptr_t>__cuLogicalEndpointUnbind
 
     global __cuLogicalEndpointExport
-    data["__cuLogicalEndpointExport"] = <_cyb_intptr_t>__cuLogicalEndpointExport
+    data["__cuLogicalEndpointExport"] = <intptr_t>__cuLogicalEndpointExport
 
     global __cuLogicalEndpointImport
-    data["__cuLogicalEndpointImport"] = <_cyb_intptr_t>__cuLogicalEndpointImport
+    data["__cuLogicalEndpointImport"] = <intptr_t>__cuLogicalEndpointImport
 
     global __cuLogicalEndpointGetLimits
-    data["__cuLogicalEndpointGetLimits"] = <_cyb_intptr_t>__cuLogicalEndpointGetLimits
+    data["__cuLogicalEndpointGetLimits"] = <intptr_t>__cuLogicalEndpointGetLimits
 
     global __cuLogicalEndpointQuery
-    data["__cuLogicalEndpointQuery"] = <_cyb_intptr_t>__cuLogicalEndpointQuery
+    data["__cuLogicalEndpointQuery"] = <intptr_t>__cuLogicalEndpointQuery
 
     global __cuStreamBeginRecaptureToGraph
-    data["__cuStreamBeginRecaptureToGraph"] = <_cyb_intptr_t>__cuStreamBeginRecaptureToGraph
+    data["__cuStreamBeginRecaptureToGraph"] = <intptr_t>__cuStreamBeginRecaptureToGraph
 
     global __cuDeviceGetFabricClusterUuid
-    data["__cuDeviceGetFabricClusterUuid"] = <_cyb_intptr_t>__cuDeviceGetFabricClusterUuid
+    data["__cuDeviceGetFabricClusterUuid"] = <intptr_t>__cuDeviceGetFabricClusterUuid
 
     global __cuDeviceGetCliqueCount
-    data["__cuDeviceGetCliqueCount"] = <_cyb_intptr_t>__cuDeviceGetCliqueCount
+    data["__cuDeviceGetCliqueCount"] = <intptr_t>__cuDeviceGetCliqueCount
 
     global __cuDeviceGetCliqueInfo
-    data["__cuDeviceGetCliqueInfo"] = <_cyb_intptr_t>__cuDeviceGetCliqueInfo
+    data["__cuDeviceGetCliqueInfo"] = <intptr_t>__cuDeviceGetCliqueInfo
 
     global __cuMemGetLocationInfo
-    data["__cuMemGetLocationInfo"] = <_cyb_intptr_t>__cuMemGetLocationInfo
+    data["__cuMemGetLocationInfo"] = <intptr_t>__cuMemGetLocationInfo
 
     global __cuGraphAddNode_v3
-    data["__cuGraphAddNode_v3"] = <_cyb_intptr_t>__cuGraphAddNode_v3
+    data["__cuGraphAddNode_v3"] = <intptr_t>__cuGraphAddNode_v3
 
     global __cuGraphNodeSetParams_v2
-    data["__cuGraphNodeSetParams_v2"] = <_cyb_intptr_t>__cuGraphNodeSetParams_v2
+    data["__cuGraphNodeSetParams_v2"] = <intptr_t>__cuGraphNodeSetParams_v2
 
     global __cuCheckpointOperationComplete
-    data["__cuCheckpointOperationComplete"] = <_cyb_intptr_t>__cuCheckpointOperationComplete
+    data["__cuCheckpointOperationComplete"] = <intptr_t>__cuCheckpointOperationComplete
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/driver_windows.pyx b/cuda_bindings/cuda/bindings/_internal/driver_windows.pyx
index 5bdc8edc360..729808ed432 100644
--- a/cuda_bindings/cuda/bindings/_internal/driver_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/driver_windows.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=56597b55df27ab42b4557879c383d53e0cff68853d1802c993db0e9eb8a449c7
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f49a90c93b3876714d90f8948fabc654d408ba6c8bc3a122503b1d1ef663f434
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,7 @@ cdef extern from "<windows.h>":
     ctypedef void* HMODULE
     void* _cyb_GetProcAddress "GetProcAddress"(HMODULE, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport intptr_t
 
 from os import getenv as _cyb_getenv
 import threading as _cyb_threading
@@ -2167,25 +2166,25 @@ cdef int _init_driver() except -1 nogil:
         cuGetProcAddress_v2('cuStreamBeginRecaptureToGraph', <void **>&__cuStreamBeginRecaptureToGraph, 13030, ptds_mode, NULL)
 
         global __cuDeviceGetFabricClusterUuid
-        cuGetProcAddress_v2('cuDeviceGetFabricClusterUuid', <void **>&__cuDeviceGetFabricClusterUuid, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuDeviceGetFabricClusterUuid', <void **>&__cuDeviceGetFabricClusterUuid, 13041, ptds_mode, NULL)
 
         global __cuDeviceGetCliqueCount
-        cuGetProcAddress_v2('cuDeviceGetCliqueCount', <void **>&__cuDeviceGetCliqueCount, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuDeviceGetCliqueCount', <void **>&__cuDeviceGetCliqueCount, 13041, ptds_mode, NULL)
 
         global __cuDeviceGetCliqueInfo
-        cuGetProcAddress_v2('cuDeviceGetCliqueInfo', <void **>&__cuDeviceGetCliqueInfo, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuDeviceGetCliqueInfo', <void **>&__cuDeviceGetCliqueInfo, 13041, ptds_mode, NULL)
 
         global __cuMemGetLocationInfo
-        cuGetProcAddress_v2('cuMemGetLocationInfo', <void **>&__cuMemGetLocationInfo, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuMemGetLocationInfo', <void **>&__cuMemGetLocationInfo, 13041, ptds_mode, NULL)
 
         global __cuGraphAddNode_v3
-        cuGetProcAddress_v2('cuGraphAddNode', <void **>&__cuGraphAddNode_v3, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuGraphAddNode', <void **>&__cuGraphAddNode_v3, 13041, ptds_mode, NULL)
 
         global __cuGraphNodeSetParams_v2
-        cuGetProcAddress_v2('cuGraphNodeSetParams', <void **>&__cuGraphNodeSetParams_v2, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuGraphNodeSetParams', <void **>&__cuGraphNodeSetParams_v2, 13041, ptds_mode, NULL)
 
         global __cuCheckpointOperationComplete
-        cuGetProcAddress_v2('cuCheckpointOperationComplete', <void **>&__cuCheckpointOperationComplete, 13040, ptds_mode, NULL)
+        cuGetProcAddress_v2('cuCheckpointOperationComplete', <void **>&__cuCheckpointOperationComplete, 13041, ptds_mode, NULL)
 
         _cyb_atomic_int_store(<int *>&_cyb___py_driver_init, 1)
         return 0
@@ -2205,1576 +2204,1576 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_driver()
     cdef dict data = {}
     global __cuGetErrorString
-    data["__cuGetErrorString"] = <_cyb_intptr_t>__cuGetErrorString
+    data["__cuGetErrorString"] = <intptr_t>__cuGetErrorString
 
     global __cuGetErrorName
-    data["__cuGetErrorName"] = <_cyb_intptr_t>__cuGetErrorName
+    data["__cuGetErrorName"] = <intptr_t>__cuGetErrorName
 
     global __cuInit
-    data["__cuInit"] = <_cyb_intptr_t>__cuInit
+    data["__cuInit"] = <intptr_t>__cuInit
 
     global __cuDriverGetVersion
-    data["__cuDriverGetVersion"] = <_cyb_intptr_t>__cuDriverGetVersion
+    data["__cuDriverGetVersion"] = <intptr_t>__cuDriverGetVersion
 
     global __cuDeviceGet
-    data["__cuDeviceGet"] = <_cyb_intptr_t>__cuDeviceGet
+    data["__cuDeviceGet"] = <intptr_t>__cuDeviceGet
 
     global __cuDeviceGetCount
-    data["__cuDeviceGetCount"] = <_cyb_intptr_t>__cuDeviceGetCount
+    data["__cuDeviceGetCount"] = <intptr_t>__cuDeviceGetCount
 
     global __cuDeviceGetName
-    data["__cuDeviceGetName"] = <_cyb_intptr_t>__cuDeviceGetName
+    data["__cuDeviceGetName"] = <intptr_t>__cuDeviceGetName
 
     global __cuDeviceGetUuid_v2
-    data["__cuDeviceGetUuid_v2"] = <_cyb_intptr_t>__cuDeviceGetUuid_v2
+    data["__cuDeviceGetUuid_v2"] = <intptr_t>__cuDeviceGetUuid_v2
 
     global __cuDeviceGetLuid
-    data["__cuDeviceGetLuid"] = <_cyb_intptr_t>__cuDeviceGetLuid
+    data["__cuDeviceGetLuid"] = <intptr_t>__cuDeviceGetLuid
 
     global __cuDeviceTotalMem_v2
-    data["__cuDeviceTotalMem_v2"] = <_cyb_intptr_t>__cuDeviceTotalMem_v2
+    data["__cuDeviceTotalMem_v2"] = <intptr_t>__cuDeviceTotalMem_v2
 
     global __cuDeviceGetTexture1DLinearMaxWidth
-    data["__cuDeviceGetTexture1DLinearMaxWidth"] = <_cyb_intptr_t>__cuDeviceGetTexture1DLinearMaxWidth
+    data["__cuDeviceGetTexture1DLinearMaxWidth"] = <intptr_t>__cuDeviceGetTexture1DLinearMaxWidth
 
     global __cuDeviceGetAttribute
-    data["__cuDeviceGetAttribute"] = <_cyb_intptr_t>__cuDeviceGetAttribute
+    data["__cuDeviceGetAttribute"] = <intptr_t>__cuDeviceGetAttribute
 
     global __cuDeviceGetNvSciSyncAttributes
-    data["__cuDeviceGetNvSciSyncAttributes"] = <_cyb_intptr_t>__cuDeviceGetNvSciSyncAttributes
+    data["__cuDeviceGetNvSciSyncAttributes"] = <intptr_t>__cuDeviceGetNvSciSyncAttributes
 
     global __cuDeviceSetMemPool
-    data["__cuDeviceSetMemPool"] = <_cyb_intptr_t>__cuDeviceSetMemPool
+    data["__cuDeviceSetMemPool"] = <intptr_t>__cuDeviceSetMemPool
 
     global __cuDeviceGetMemPool
-    data["__cuDeviceGetMemPool"] = <_cyb_intptr_t>__cuDeviceGetMemPool
+    data["__cuDeviceGetMemPool"] = <intptr_t>__cuDeviceGetMemPool
 
     global __cuDeviceGetDefaultMemPool
-    data["__cuDeviceGetDefaultMemPool"] = <_cyb_intptr_t>__cuDeviceGetDefaultMemPool
+    data["__cuDeviceGetDefaultMemPool"] = <intptr_t>__cuDeviceGetDefaultMemPool
 
     global __cuDeviceGetExecAffinitySupport
-    data["__cuDeviceGetExecAffinitySupport"] = <_cyb_intptr_t>__cuDeviceGetExecAffinitySupport
+    data["__cuDeviceGetExecAffinitySupport"] = <intptr_t>__cuDeviceGetExecAffinitySupport
 
     global __cuFlushGPUDirectRDMAWrites
-    data["__cuFlushGPUDirectRDMAWrites"] = <_cyb_intptr_t>__cuFlushGPUDirectRDMAWrites
+    data["__cuFlushGPUDirectRDMAWrites"] = <intptr_t>__cuFlushGPUDirectRDMAWrites
 
     global __cuDeviceGetProperties
-    data["__cuDeviceGetProperties"] = <_cyb_intptr_t>__cuDeviceGetProperties
+    data["__cuDeviceGetProperties"] = <intptr_t>__cuDeviceGetProperties
 
     global __cuDeviceComputeCapability
-    data["__cuDeviceComputeCapability"] = <_cyb_intptr_t>__cuDeviceComputeCapability
+    data["__cuDeviceComputeCapability"] = <intptr_t>__cuDeviceComputeCapability
 
     global __cuDevicePrimaryCtxRetain
-    data["__cuDevicePrimaryCtxRetain"] = <_cyb_intptr_t>__cuDevicePrimaryCtxRetain
+    data["__cuDevicePrimaryCtxRetain"] = <intptr_t>__cuDevicePrimaryCtxRetain
 
     global __cuDevicePrimaryCtxRelease_v2
-    data["__cuDevicePrimaryCtxRelease_v2"] = <_cyb_intptr_t>__cuDevicePrimaryCtxRelease_v2
+    data["__cuDevicePrimaryCtxRelease_v2"] = <intptr_t>__cuDevicePrimaryCtxRelease_v2
 
     global __cuDevicePrimaryCtxSetFlags_v2
-    data["__cuDevicePrimaryCtxSetFlags_v2"] = <_cyb_intptr_t>__cuDevicePrimaryCtxSetFlags_v2
+    data["__cuDevicePrimaryCtxSetFlags_v2"] = <intptr_t>__cuDevicePrimaryCtxSetFlags_v2
 
     global __cuDevicePrimaryCtxGetState
-    data["__cuDevicePrimaryCtxGetState"] = <_cyb_intptr_t>__cuDevicePrimaryCtxGetState
+    data["__cuDevicePrimaryCtxGetState"] = <intptr_t>__cuDevicePrimaryCtxGetState
 
     global __cuDevicePrimaryCtxReset_v2
-    data["__cuDevicePrimaryCtxReset_v2"] = <_cyb_intptr_t>__cuDevicePrimaryCtxReset_v2
+    data["__cuDevicePrimaryCtxReset_v2"] = <intptr_t>__cuDevicePrimaryCtxReset_v2
 
     global __cuCtxCreate_v2
-    data["__cuCtxCreate_v2"] = <_cyb_intptr_t>__cuCtxCreate_v2
+    data["__cuCtxCreate_v2"] = <intptr_t>__cuCtxCreate_v2
 
     global __cuCtxCreate_v3
-    data["__cuCtxCreate_v3"] = <_cyb_intptr_t>__cuCtxCreate_v3
+    data["__cuCtxCreate_v3"] = <intptr_t>__cuCtxCreate_v3
 
     global __cuCtxCreate_v4
-    data["__cuCtxCreate_v4"] = <_cyb_intptr_t>__cuCtxCreate_v4
+    data["__cuCtxCreate_v4"] = <intptr_t>__cuCtxCreate_v4
 
     global __cuCtxDestroy_v2
-    data["__cuCtxDestroy_v2"] = <_cyb_intptr_t>__cuCtxDestroy_v2
+    data["__cuCtxDestroy_v2"] = <intptr_t>__cuCtxDestroy_v2
 
     global __cuCtxPushCurrent_v2
-    data["__cuCtxPushCurrent_v2"] = <_cyb_intptr_t>__cuCtxPushCurrent_v2
+    data["__cuCtxPushCurrent_v2"] = <intptr_t>__cuCtxPushCurrent_v2
 
     global __cuCtxPopCurrent_v2
-    data["__cuCtxPopCurrent_v2"] = <_cyb_intptr_t>__cuCtxPopCurrent_v2
+    data["__cuCtxPopCurrent_v2"] = <intptr_t>__cuCtxPopCurrent_v2
 
     global __cuCtxSetCurrent
-    data["__cuCtxSetCurrent"] = <_cyb_intptr_t>__cuCtxSetCurrent
+    data["__cuCtxSetCurrent"] = <intptr_t>__cuCtxSetCurrent
 
     global __cuCtxGetCurrent
-    data["__cuCtxGetCurrent"] = <_cyb_intptr_t>__cuCtxGetCurrent
+    data["__cuCtxGetCurrent"] = <intptr_t>__cuCtxGetCurrent
 
     global __cuCtxGetDevice
-    data["__cuCtxGetDevice"] = <_cyb_intptr_t>__cuCtxGetDevice
+    data["__cuCtxGetDevice"] = <intptr_t>__cuCtxGetDevice
 
     global __cuCtxGetFlags
-    data["__cuCtxGetFlags"] = <_cyb_intptr_t>__cuCtxGetFlags
+    data["__cuCtxGetFlags"] = <intptr_t>__cuCtxGetFlags
 
     global __cuCtxSetFlags
-    data["__cuCtxSetFlags"] = <_cyb_intptr_t>__cuCtxSetFlags
+    data["__cuCtxSetFlags"] = <intptr_t>__cuCtxSetFlags
 
     global __cuCtxGetId
-    data["__cuCtxGetId"] = <_cyb_intptr_t>__cuCtxGetId
+    data["__cuCtxGetId"] = <intptr_t>__cuCtxGetId
 
     global __cuCtxSynchronize
-    data["__cuCtxSynchronize"] = <_cyb_intptr_t>__cuCtxSynchronize
+    data["__cuCtxSynchronize"] = <intptr_t>__cuCtxSynchronize
 
     global __cuCtxSetLimit
-    data["__cuCtxSetLimit"] = <_cyb_intptr_t>__cuCtxSetLimit
+    data["__cuCtxSetLimit"] = <intptr_t>__cuCtxSetLimit
 
     global __cuCtxGetLimit
-    data["__cuCtxGetLimit"] = <_cyb_intptr_t>__cuCtxGetLimit
+    data["__cuCtxGetLimit"] = <intptr_t>__cuCtxGetLimit
 
     global __cuCtxGetCacheConfig
-    data["__cuCtxGetCacheConfig"] = <_cyb_intptr_t>__cuCtxGetCacheConfig
+    data["__cuCtxGetCacheConfig"] = <intptr_t>__cuCtxGetCacheConfig
 
     global __cuCtxSetCacheConfig
-    data["__cuCtxSetCacheConfig"] = <_cyb_intptr_t>__cuCtxSetCacheConfig
+    data["__cuCtxSetCacheConfig"] = <intptr_t>__cuCtxSetCacheConfig
 
     global __cuCtxGetApiVersion
-    data["__cuCtxGetApiVersion"] = <_cyb_intptr_t>__cuCtxGetApiVersion
+    data["__cuCtxGetApiVersion"] = <intptr_t>__cuCtxGetApiVersion
 
     global __cuCtxGetStreamPriorityRange
-    data["__cuCtxGetStreamPriorityRange"] = <_cyb_intptr_t>__cuCtxGetStreamPriorityRange
+    data["__cuCtxGetStreamPriorityRange"] = <intptr_t>__cuCtxGetStreamPriorityRange
 
     global __cuCtxResetPersistingL2Cache
-    data["__cuCtxResetPersistingL2Cache"] = <_cyb_intptr_t>__cuCtxResetPersistingL2Cache
+    data["__cuCtxResetPersistingL2Cache"] = <intptr_t>__cuCtxResetPersistingL2Cache
 
     global __cuCtxGetExecAffinity
-    data["__cuCtxGetExecAffinity"] = <_cyb_intptr_t>__cuCtxGetExecAffinity
+    data["__cuCtxGetExecAffinity"] = <intptr_t>__cuCtxGetExecAffinity
 
     global __cuCtxRecordEvent
-    data["__cuCtxRecordEvent"] = <_cyb_intptr_t>__cuCtxRecordEvent
+    data["__cuCtxRecordEvent"] = <intptr_t>__cuCtxRecordEvent
 
     global __cuCtxWaitEvent
-    data["__cuCtxWaitEvent"] = <_cyb_intptr_t>__cuCtxWaitEvent
+    data["__cuCtxWaitEvent"] = <intptr_t>__cuCtxWaitEvent
 
     global __cuCtxAttach
-    data["__cuCtxAttach"] = <_cyb_intptr_t>__cuCtxAttach
+    data["__cuCtxAttach"] = <intptr_t>__cuCtxAttach
 
     global __cuCtxDetach
-    data["__cuCtxDetach"] = <_cyb_intptr_t>__cuCtxDetach
+    data["__cuCtxDetach"] = <intptr_t>__cuCtxDetach
 
     global __cuCtxGetSharedMemConfig
-    data["__cuCtxGetSharedMemConfig"] = <_cyb_intptr_t>__cuCtxGetSharedMemConfig
+    data["__cuCtxGetSharedMemConfig"] = <intptr_t>__cuCtxGetSharedMemConfig
 
     global __cuCtxSetSharedMemConfig
-    data["__cuCtxSetSharedMemConfig"] = <_cyb_intptr_t>__cuCtxSetSharedMemConfig
+    data["__cuCtxSetSharedMemConfig"] = <intptr_t>__cuCtxSetSharedMemConfig
 
     global __cuModuleLoad
-    data["__cuModuleLoad"] = <_cyb_intptr_t>__cuModuleLoad
+    data["__cuModuleLoad"] = <intptr_t>__cuModuleLoad
 
     global __cuModuleLoadData
-    data["__cuModuleLoadData"] = <_cyb_intptr_t>__cuModuleLoadData
+    data["__cuModuleLoadData"] = <intptr_t>__cuModuleLoadData
 
     global __cuModuleLoadDataEx
-    data["__cuModuleLoadDataEx"] = <_cyb_intptr_t>__cuModuleLoadDataEx
+    data["__cuModuleLoadDataEx"] = <intptr_t>__cuModuleLoadDataEx
 
     global __cuModuleLoadFatBinary
-    data["__cuModuleLoadFatBinary"] = <_cyb_intptr_t>__cuModuleLoadFatBinary
+    data["__cuModuleLoadFatBinary"] = <intptr_t>__cuModuleLoadFatBinary
 
     global __cuModuleUnload
-    data["__cuModuleUnload"] = <_cyb_intptr_t>__cuModuleUnload
+    data["__cuModuleUnload"] = <intptr_t>__cuModuleUnload
 
     global __cuModuleGetLoadingMode
-    data["__cuModuleGetLoadingMode"] = <_cyb_intptr_t>__cuModuleGetLoadingMode
+    data["__cuModuleGetLoadingMode"] = <intptr_t>__cuModuleGetLoadingMode
 
     global __cuModuleGetFunction
-    data["__cuModuleGetFunction"] = <_cyb_intptr_t>__cuModuleGetFunction
+    data["__cuModuleGetFunction"] = <intptr_t>__cuModuleGetFunction
 
     global __cuModuleGetFunctionCount
-    data["__cuModuleGetFunctionCount"] = <_cyb_intptr_t>__cuModuleGetFunctionCount
+    data["__cuModuleGetFunctionCount"] = <intptr_t>__cuModuleGetFunctionCount
 
     global __cuModuleEnumerateFunctions
-    data["__cuModuleEnumerateFunctions"] = <_cyb_intptr_t>__cuModuleEnumerateFunctions
+    data["__cuModuleEnumerateFunctions"] = <intptr_t>__cuModuleEnumerateFunctions
 
     global __cuModuleGetGlobal_v2
-    data["__cuModuleGetGlobal_v2"] = <_cyb_intptr_t>__cuModuleGetGlobal_v2
+    data["__cuModuleGetGlobal_v2"] = <intptr_t>__cuModuleGetGlobal_v2
 
     global __cuLinkCreate_v2
-    data["__cuLinkCreate_v2"] = <_cyb_intptr_t>__cuLinkCreate_v2
+    data["__cuLinkCreate_v2"] = <intptr_t>__cuLinkCreate_v2
 
     global __cuLinkAddData_v2
-    data["__cuLinkAddData_v2"] = <_cyb_intptr_t>__cuLinkAddData_v2
+    data["__cuLinkAddData_v2"] = <intptr_t>__cuLinkAddData_v2
 
     global __cuLinkAddFile_v2
-    data["__cuLinkAddFile_v2"] = <_cyb_intptr_t>__cuLinkAddFile_v2
+    data["__cuLinkAddFile_v2"] = <intptr_t>__cuLinkAddFile_v2
 
     global __cuLinkComplete
-    data["__cuLinkComplete"] = <_cyb_intptr_t>__cuLinkComplete
+    data["__cuLinkComplete"] = <intptr_t>__cuLinkComplete
 
     global __cuLinkDestroy
-    data["__cuLinkDestroy"] = <_cyb_intptr_t>__cuLinkDestroy
+    data["__cuLinkDestroy"] = <intptr_t>__cuLinkDestroy
 
     global __cuModuleGetTexRef
-    data["__cuModuleGetTexRef"] = <_cyb_intptr_t>__cuModuleGetTexRef
+    data["__cuModuleGetTexRef"] = <intptr_t>__cuModuleGetTexRef
 
     global __cuModuleGetSurfRef
-    data["__cuModuleGetSurfRef"] = <_cyb_intptr_t>__cuModuleGetSurfRef
+    data["__cuModuleGetSurfRef"] = <intptr_t>__cuModuleGetSurfRef
 
     global __cuLibraryLoadData
-    data["__cuLibraryLoadData"] = <_cyb_intptr_t>__cuLibraryLoadData
+    data["__cuLibraryLoadData"] = <intptr_t>__cuLibraryLoadData
 
     global __cuLibraryLoadFromFile
-    data["__cuLibraryLoadFromFile"] = <_cyb_intptr_t>__cuLibraryLoadFromFile
+    data["__cuLibraryLoadFromFile"] = <intptr_t>__cuLibraryLoadFromFile
 
     global __cuLibraryUnload
-    data["__cuLibraryUnload"] = <_cyb_intptr_t>__cuLibraryUnload
+    data["__cuLibraryUnload"] = <intptr_t>__cuLibraryUnload
 
     global __cuLibraryGetKernel
-    data["__cuLibraryGetKernel"] = <_cyb_intptr_t>__cuLibraryGetKernel
+    data["__cuLibraryGetKernel"] = <intptr_t>__cuLibraryGetKernel
 
     global __cuLibraryGetKernelCount
-    data["__cuLibraryGetKernelCount"] = <_cyb_intptr_t>__cuLibraryGetKernelCount
+    data["__cuLibraryGetKernelCount"] = <intptr_t>__cuLibraryGetKernelCount
 
     global __cuLibraryEnumerateKernels
-    data["__cuLibraryEnumerateKernels"] = <_cyb_intptr_t>__cuLibraryEnumerateKernels
+    data["__cuLibraryEnumerateKernels"] = <intptr_t>__cuLibraryEnumerateKernels
 
     global __cuLibraryGetModule
-    data["__cuLibraryGetModule"] = <_cyb_intptr_t>__cuLibraryGetModule
+    data["__cuLibraryGetModule"] = <intptr_t>__cuLibraryGetModule
 
     global __cuKernelGetFunction
-    data["__cuKernelGetFunction"] = <_cyb_intptr_t>__cuKernelGetFunction
+    data["__cuKernelGetFunction"] = <intptr_t>__cuKernelGetFunction
 
     global __cuKernelGetLibrary
-    data["__cuKernelGetLibrary"] = <_cyb_intptr_t>__cuKernelGetLibrary
+    data["__cuKernelGetLibrary"] = <intptr_t>__cuKernelGetLibrary
 
     global __cuLibraryGetGlobal
-    data["__cuLibraryGetGlobal"] = <_cyb_intptr_t>__cuLibraryGetGlobal
+    data["__cuLibraryGetGlobal"] = <intptr_t>__cuLibraryGetGlobal
 
     global __cuLibraryGetManaged
-    data["__cuLibraryGetManaged"] = <_cyb_intptr_t>__cuLibraryGetManaged
+    data["__cuLibraryGetManaged"] = <intptr_t>__cuLibraryGetManaged
 
     global __cuLibraryGetUnifiedFunction
-    data["__cuLibraryGetUnifiedFunction"] = <_cyb_intptr_t>__cuLibraryGetUnifiedFunction
+    data["__cuLibraryGetUnifiedFunction"] = <intptr_t>__cuLibraryGetUnifiedFunction
 
     global __cuKernelGetAttribute
-    data["__cuKernelGetAttribute"] = <_cyb_intptr_t>__cuKernelGetAttribute
+    data["__cuKernelGetAttribute"] = <intptr_t>__cuKernelGetAttribute
 
     global __cuKernelSetAttribute
-    data["__cuKernelSetAttribute"] = <_cyb_intptr_t>__cuKernelSetAttribute
+    data["__cuKernelSetAttribute"] = <intptr_t>__cuKernelSetAttribute
 
     global __cuKernelSetCacheConfig
-    data["__cuKernelSetCacheConfig"] = <_cyb_intptr_t>__cuKernelSetCacheConfig
+    data["__cuKernelSetCacheConfig"] = <intptr_t>__cuKernelSetCacheConfig
 
     global __cuKernelGetName
-    data["__cuKernelGetName"] = <_cyb_intptr_t>__cuKernelGetName
+    data["__cuKernelGetName"] = <intptr_t>__cuKernelGetName
 
     global __cuKernelGetParamInfo
-    data["__cuKernelGetParamInfo"] = <_cyb_intptr_t>__cuKernelGetParamInfo
+    data["__cuKernelGetParamInfo"] = <intptr_t>__cuKernelGetParamInfo
 
     global __cuMemGetInfo_v2
-    data["__cuMemGetInfo_v2"] = <_cyb_intptr_t>__cuMemGetInfo_v2
+    data["__cuMemGetInfo_v2"] = <intptr_t>__cuMemGetInfo_v2
 
     global __cuMemAlloc_v2
-    data["__cuMemAlloc_v2"] = <_cyb_intptr_t>__cuMemAlloc_v2
+    data["__cuMemAlloc_v2"] = <intptr_t>__cuMemAlloc_v2
 
     global __cuMemAllocPitch_v2
-    data["__cuMemAllocPitch_v2"] = <_cyb_intptr_t>__cuMemAllocPitch_v2
+    data["__cuMemAllocPitch_v2"] = <intptr_t>__cuMemAllocPitch_v2
 
     global __cuMemFree_v2
-    data["__cuMemFree_v2"] = <_cyb_intptr_t>__cuMemFree_v2
+    data["__cuMemFree_v2"] = <intptr_t>__cuMemFree_v2
 
     global __cuMemGetAddressRange_v2
-    data["__cuMemGetAddressRange_v2"] = <_cyb_intptr_t>__cuMemGetAddressRange_v2
+    data["__cuMemGetAddressRange_v2"] = <intptr_t>__cuMemGetAddressRange_v2
 
     global __cuMemAllocHost_v2
-    data["__cuMemAllocHost_v2"] = <_cyb_intptr_t>__cuMemAllocHost_v2
+    data["__cuMemAllocHost_v2"] = <intptr_t>__cuMemAllocHost_v2
 
     global __cuMemFreeHost
-    data["__cuMemFreeHost"] = <_cyb_intptr_t>__cuMemFreeHost
+    data["__cuMemFreeHost"] = <intptr_t>__cuMemFreeHost
 
     global __cuMemHostAlloc
-    data["__cuMemHostAlloc"] = <_cyb_intptr_t>__cuMemHostAlloc
+    data["__cuMemHostAlloc"] = <intptr_t>__cuMemHostAlloc
 
     global __cuMemHostGetDevicePointer_v2
-    data["__cuMemHostGetDevicePointer_v2"] = <_cyb_intptr_t>__cuMemHostGetDevicePointer_v2
+    data["__cuMemHostGetDevicePointer_v2"] = <intptr_t>__cuMemHostGetDevicePointer_v2
 
     global __cuMemHostGetFlags
-    data["__cuMemHostGetFlags"] = <_cyb_intptr_t>__cuMemHostGetFlags
+    data["__cuMemHostGetFlags"] = <intptr_t>__cuMemHostGetFlags
 
     global __cuMemAllocManaged
-    data["__cuMemAllocManaged"] = <_cyb_intptr_t>__cuMemAllocManaged
+    data["__cuMemAllocManaged"] = <intptr_t>__cuMemAllocManaged
 
     global __cuDeviceRegisterAsyncNotification
-    data["__cuDeviceRegisterAsyncNotification"] = <_cyb_intptr_t>__cuDeviceRegisterAsyncNotification
+    data["__cuDeviceRegisterAsyncNotification"] = <intptr_t>__cuDeviceRegisterAsyncNotification
 
     global __cuDeviceUnregisterAsyncNotification
-    data["__cuDeviceUnregisterAsyncNotification"] = <_cyb_intptr_t>__cuDeviceUnregisterAsyncNotification
+    data["__cuDeviceUnregisterAsyncNotification"] = <intptr_t>__cuDeviceUnregisterAsyncNotification
 
     global __cuDeviceGetByPCIBusId
-    data["__cuDeviceGetByPCIBusId"] = <_cyb_intptr_t>__cuDeviceGetByPCIBusId
+    data["__cuDeviceGetByPCIBusId"] = <intptr_t>__cuDeviceGetByPCIBusId
 
     global __cuDeviceGetPCIBusId
-    data["__cuDeviceGetPCIBusId"] = <_cyb_intptr_t>__cuDeviceGetPCIBusId
+    data["__cuDeviceGetPCIBusId"] = <intptr_t>__cuDeviceGetPCIBusId
 
     global __cuIpcGetEventHandle
-    data["__cuIpcGetEventHandle"] = <_cyb_intptr_t>__cuIpcGetEventHandle
+    data["__cuIpcGetEventHandle"] = <intptr_t>__cuIpcGetEventHandle
 
     global __cuIpcOpenEventHandle
-    data["__cuIpcOpenEventHandle"] = <_cyb_intptr_t>__cuIpcOpenEventHandle
+    data["__cuIpcOpenEventHandle"] = <intptr_t>__cuIpcOpenEventHandle
 
     global __cuIpcGetMemHandle
-    data["__cuIpcGetMemHandle"] = <_cyb_intptr_t>__cuIpcGetMemHandle
+    data["__cuIpcGetMemHandle"] = <intptr_t>__cuIpcGetMemHandle
 
     global __cuIpcOpenMemHandle_v2
-    data["__cuIpcOpenMemHandle_v2"] = <_cyb_intptr_t>__cuIpcOpenMemHandle_v2
+    data["__cuIpcOpenMemHandle_v2"] = <intptr_t>__cuIpcOpenMemHandle_v2
 
     global __cuIpcCloseMemHandle
-    data["__cuIpcCloseMemHandle"] = <_cyb_intptr_t>__cuIpcCloseMemHandle
+    data["__cuIpcCloseMemHandle"] = <intptr_t>__cuIpcCloseMemHandle
 
     global __cuMemHostRegister_v2
-    data["__cuMemHostRegister_v2"] = <_cyb_intptr_t>__cuMemHostRegister_v2
+    data["__cuMemHostRegister_v2"] = <intptr_t>__cuMemHostRegister_v2
 
     global __cuMemHostUnregister
-    data["__cuMemHostUnregister"] = <_cyb_intptr_t>__cuMemHostUnregister
+    data["__cuMemHostUnregister"] = <intptr_t>__cuMemHostUnregister
 
     global __cuMemcpy
-    data["__cuMemcpy"] = <_cyb_intptr_t>__cuMemcpy
+    data["__cuMemcpy"] = <intptr_t>__cuMemcpy
 
     global __cuMemcpyPeer
-    data["__cuMemcpyPeer"] = <_cyb_intptr_t>__cuMemcpyPeer
+    data["__cuMemcpyPeer"] = <intptr_t>__cuMemcpyPeer
 
     global __cuMemcpyHtoD_v2
-    data["__cuMemcpyHtoD_v2"] = <_cyb_intptr_t>__cuMemcpyHtoD_v2
+    data["__cuMemcpyHtoD_v2"] = <intptr_t>__cuMemcpyHtoD_v2
 
     global __cuMemcpyDtoH_v2
-    data["__cuMemcpyDtoH_v2"] = <_cyb_intptr_t>__cuMemcpyDtoH_v2
+    data["__cuMemcpyDtoH_v2"] = <intptr_t>__cuMemcpyDtoH_v2
 
     global __cuMemcpyDtoD_v2
-    data["__cuMemcpyDtoD_v2"] = <_cyb_intptr_t>__cuMemcpyDtoD_v2
+    data["__cuMemcpyDtoD_v2"] = <intptr_t>__cuMemcpyDtoD_v2
 
     global __cuMemcpyDtoA_v2
-    data["__cuMemcpyDtoA_v2"] = <_cyb_intptr_t>__cuMemcpyDtoA_v2
+    data["__cuMemcpyDtoA_v2"] = <intptr_t>__cuMemcpyDtoA_v2
 
     global __cuMemcpyAtoD_v2
-    data["__cuMemcpyAtoD_v2"] = <_cyb_intptr_t>__cuMemcpyAtoD_v2
+    data["__cuMemcpyAtoD_v2"] = <intptr_t>__cuMemcpyAtoD_v2
 
     global __cuMemcpyHtoA_v2
-    data["__cuMemcpyHtoA_v2"] = <_cyb_intptr_t>__cuMemcpyHtoA_v2
+    data["__cuMemcpyHtoA_v2"] = <intptr_t>__cuMemcpyHtoA_v2
 
     global __cuMemcpyAtoH_v2
-    data["__cuMemcpyAtoH_v2"] = <_cyb_intptr_t>__cuMemcpyAtoH_v2
+    data["__cuMemcpyAtoH_v2"] = <intptr_t>__cuMemcpyAtoH_v2
 
     global __cuMemcpyAtoA_v2
-    data["__cuMemcpyAtoA_v2"] = <_cyb_intptr_t>__cuMemcpyAtoA_v2
+    data["__cuMemcpyAtoA_v2"] = <intptr_t>__cuMemcpyAtoA_v2
 
     global __cuMemcpy2D_v2
-    data["__cuMemcpy2D_v2"] = <_cyb_intptr_t>__cuMemcpy2D_v2
+    data["__cuMemcpy2D_v2"] = <intptr_t>__cuMemcpy2D_v2
 
     global __cuMemcpy2DUnaligned_v2
-    data["__cuMemcpy2DUnaligned_v2"] = <_cyb_intptr_t>__cuMemcpy2DUnaligned_v2
+    data["__cuMemcpy2DUnaligned_v2"] = <intptr_t>__cuMemcpy2DUnaligned_v2
 
     global __cuMemcpy3D_v2
-    data["__cuMemcpy3D_v2"] = <_cyb_intptr_t>__cuMemcpy3D_v2
+    data["__cuMemcpy3D_v2"] = <intptr_t>__cuMemcpy3D_v2
 
     global __cuMemcpy3DPeer
-    data["__cuMemcpy3DPeer"] = <_cyb_intptr_t>__cuMemcpy3DPeer
+    data["__cuMemcpy3DPeer"] = <intptr_t>__cuMemcpy3DPeer
 
     global __cuMemcpyAsync
-    data["__cuMemcpyAsync"] = <_cyb_intptr_t>__cuMemcpyAsync
+    data["__cuMemcpyAsync"] = <intptr_t>__cuMemcpyAsync
 
     global __cuMemcpyPeerAsync
-    data["__cuMemcpyPeerAsync"] = <_cyb_intptr_t>__cuMemcpyPeerAsync
+    data["__cuMemcpyPeerAsync"] = <intptr_t>__cuMemcpyPeerAsync
 
     global __cuMemcpyHtoDAsync_v2
-    data["__cuMemcpyHtoDAsync_v2"] = <_cyb_intptr_t>__cuMemcpyHtoDAsync_v2
+    data["__cuMemcpyHtoDAsync_v2"] = <intptr_t>__cuMemcpyHtoDAsync_v2
 
     global __cuMemcpyDtoHAsync_v2
-    data["__cuMemcpyDtoHAsync_v2"] = <_cyb_intptr_t>__cuMemcpyDtoHAsync_v2
+    data["__cuMemcpyDtoHAsync_v2"] = <intptr_t>__cuMemcpyDtoHAsync_v2
 
     global __cuMemcpyDtoDAsync_v2
-    data["__cuMemcpyDtoDAsync_v2"] = <_cyb_intptr_t>__cuMemcpyDtoDAsync_v2
+    data["__cuMemcpyDtoDAsync_v2"] = <intptr_t>__cuMemcpyDtoDAsync_v2
 
     global __cuMemcpyHtoAAsync_v2
-    data["__cuMemcpyHtoAAsync_v2"] = <_cyb_intptr_t>__cuMemcpyHtoAAsync_v2
+    data["__cuMemcpyHtoAAsync_v2"] = <intptr_t>__cuMemcpyHtoAAsync_v2
 
     global __cuMemcpyAtoHAsync_v2
-    data["__cuMemcpyAtoHAsync_v2"] = <_cyb_intptr_t>__cuMemcpyAtoHAsync_v2
+    data["__cuMemcpyAtoHAsync_v2"] = <intptr_t>__cuMemcpyAtoHAsync_v2
 
     global __cuMemcpy2DAsync_v2
-    data["__cuMemcpy2DAsync_v2"] = <_cyb_intptr_t>__cuMemcpy2DAsync_v2
+    data["__cuMemcpy2DAsync_v2"] = <intptr_t>__cuMemcpy2DAsync_v2
 
     global __cuMemcpy3DAsync_v2
-    data["__cuMemcpy3DAsync_v2"] = <_cyb_intptr_t>__cuMemcpy3DAsync_v2
+    data["__cuMemcpy3DAsync_v2"] = <intptr_t>__cuMemcpy3DAsync_v2
 
     global __cuMemcpy3DPeerAsync
-    data["__cuMemcpy3DPeerAsync"] = <_cyb_intptr_t>__cuMemcpy3DPeerAsync
+    data["__cuMemcpy3DPeerAsync"] = <intptr_t>__cuMemcpy3DPeerAsync
 
     global __cuMemsetD8_v2
-    data["__cuMemsetD8_v2"] = <_cyb_intptr_t>__cuMemsetD8_v2
+    data["__cuMemsetD8_v2"] = <intptr_t>__cuMemsetD8_v2
 
     global __cuMemsetD16_v2
-    data["__cuMemsetD16_v2"] = <_cyb_intptr_t>__cuMemsetD16_v2
+    data["__cuMemsetD16_v2"] = <intptr_t>__cuMemsetD16_v2
 
     global __cuMemsetD32_v2
-    data["__cuMemsetD32_v2"] = <_cyb_intptr_t>__cuMemsetD32_v2
+    data["__cuMemsetD32_v2"] = <intptr_t>__cuMemsetD32_v2
 
     global __cuMemsetD2D8_v2
-    data["__cuMemsetD2D8_v2"] = <_cyb_intptr_t>__cuMemsetD2D8_v2
+    data["__cuMemsetD2D8_v2"] = <intptr_t>__cuMemsetD2D8_v2
 
     global __cuMemsetD2D16_v2
-    data["__cuMemsetD2D16_v2"] = <_cyb_intptr_t>__cuMemsetD2D16_v2
+    data["__cuMemsetD2D16_v2"] = <intptr_t>__cuMemsetD2D16_v2
 
     global __cuMemsetD2D32_v2
-    data["__cuMemsetD2D32_v2"] = <_cyb_intptr_t>__cuMemsetD2D32_v2
+    data["__cuMemsetD2D32_v2"] = <intptr_t>__cuMemsetD2D32_v2
 
     global __cuMemsetD8Async
-    data["__cuMemsetD8Async"] = <_cyb_intptr_t>__cuMemsetD8Async
+    data["__cuMemsetD8Async"] = <intptr_t>__cuMemsetD8Async
 
     global __cuMemsetD16Async
-    data["__cuMemsetD16Async"] = <_cyb_intptr_t>__cuMemsetD16Async
+    data["__cuMemsetD16Async"] = <intptr_t>__cuMemsetD16Async
 
     global __cuMemsetD32Async
-    data["__cuMemsetD32Async"] = <_cyb_intptr_t>__cuMemsetD32Async
+    data["__cuMemsetD32Async"] = <intptr_t>__cuMemsetD32Async
 
     global __cuMemsetD2D8Async
-    data["__cuMemsetD2D8Async"] = <_cyb_intptr_t>__cuMemsetD2D8Async
+    data["__cuMemsetD2D8Async"] = <intptr_t>__cuMemsetD2D8Async
 
     global __cuMemsetD2D16Async
-    data["__cuMemsetD2D16Async"] = <_cyb_intptr_t>__cuMemsetD2D16Async
+    data["__cuMemsetD2D16Async"] = <intptr_t>__cuMemsetD2D16Async
 
     global __cuMemsetD2D32Async
-    data["__cuMemsetD2D32Async"] = <_cyb_intptr_t>__cuMemsetD2D32Async
+    data["__cuMemsetD2D32Async"] = <intptr_t>__cuMemsetD2D32Async
 
     global __cuArrayCreate_v2
-    data["__cuArrayCreate_v2"] = <_cyb_intptr_t>__cuArrayCreate_v2
+    data["__cuArrayCreate_v2"] = <intptr_t>__cuArrayCreate_v2
 
     global __cuArrayGetDescriptor_v2
-    data["__cuArrayGetDescriptor_v2"] = <_cyb_intptr_t>__cuArrayGetDescriptor_v2
+    data["__cuArrayGetDescriptor_v2"] = <intptr_t>__cuArrayGetDescriptor_v2
 
     global __cuArrayGetSparseProperties
-    data["__cuArrayGetSparseProperties"] = <_cyb_intptr_t>__cuArrayGetSparseProperties
+    data["__cuArrayGetSparseProperties"] = <intptr_t>__cuArrayGetSparseProperties
 
     global __cuMipmappedArrayGetSparseProperties
-    data["__cuMipmappedArrayGetSparseProperties"] = <_cyb_intptr_t>__cuMipmappedArrayGetSparseProperties
+    data["__cuMipmappedArrayGetSparseProperties"] = <intptr_t>__cuMipmappedArrayGetSparseProperties
 
     global __cuArrayGetMemoryRequirements
-    data["__cuArrayGetMemoryRequirements"] = <_cyb_intptr_t>__cuArrayGetMemoryRequirements
+    data["__cuArrayGetMemoryRequirements"] = <intptr_t>__cuArrayGetMemoryRequirements
 
     global __cuMipmappedArrayGetMemoryRequirements
-    data["__cuMipmappedArrayGetMemoryRequirements"] = <_cyb_intptr_t>__cuMipmappedArrayGetMemoryRequirements
+    data["__cuMipmappedArrayGetMemoryRequirements"] = <intptr_t>__cuMipmappedArrayGetMemoryRequirements
 
     global __cuArrayGetPlane
-    data["__cuArrayGetPlane"] = <_cyb_intptr_t>__cuArrayGetPlane
+    data["__cuArrayGetPlane"] = <intptr_t>__cuArrayGetPlane
 
     global __cuArrayDestroy
-    data["__cuArrayDestroy"] = <_cyb_intptr_t>__cuArrayDestroy
+    data["__cuArrayDestroy"] = <intptr_t>__cuArrayDestroy
 
     global __cuArray3DCreate_v2
-    data["__cuArray3DCreate_v2"] = <_cyb_intptr_t>__cuArray3DCreate_v2
+    data["__cuArray3DCreate_v2"] = <intptr_t>__cuArray3DCreate_v2
 
     global __cuArray3DGetDescriptor_v2
-    data["__cuArray3DGetDescriptor_v2"] = <_cyb_intptr_t>__cuArray3DGetDescriptor_v2
+    data["__cuArray3DGetDescriptor_v2"] = <intptr_t>__cuArray3DGetDescriptor_v2
 
     global __cuMipmappedArrayCreate
-    data["__cuMipmappedArrayCreate"] = <_cyb_intptr_t>__cuMipmappedArrayCreate
+    data["__cuMipmappedArrayCreate"] = <intptr_t>__cuMipmappedArrayCreate
 
     global __cuMipmappedArrayGetLevel
-    data["__cuMipmappedArrayGetLevel"] = <_cyb_intptr_t>__cuMipmappedArrayGetLevel
+    data["__cuMipmappedArrayGetLevel"] = <intptr_t>__cuMipmappedArrayGetLevel
 
     global __cuMipmappedArrayDestroy
-    data["__cuMipmappedArrayDestroy"] = <_cyb_intptr_t>__cuMipmappedArrayDestroy
+    data["__cuMipmappedArrayDestroy"] = <intptr_t>__cuMipmappedArrayDestroy
 
     global __cuMemGetHandleForAddressRange
-    data["__cuMemGetHandleForAddressRange"] = <_cyb_intptr_t>__cuMemGetHandleForAddressRange
+    data["__cuMemGetHandleForAddressRange"] = <intptr_t>__cuMemGetHandleForAddressRange
 
     global __cuMemBatchDecompressAsync
-    data["__cuMemBatchDecompressAsync"] = <_cyb_intptr_t>__cuMemBatchDecompressAsync
+    data["__cuMemBatchDecompressAsync"] = <intptr_t>__cuMemBatchDecompressAsync
 
     global __cuMemAddressReserve
-    data["__cuMemAddressReserve"] = <_cyb_intptr_t>__cuMemAddressReserve
+    data["__cuMemAddressReserve"] = <intptr_t>__cuMemAddressReserve
 
     global __cuMemAddressFree
-    data["__cuMemAddressFree"] = <_cyb_intptr_t>__cuMemAddressFree
+    data["__cuMemAddressFree"] = <intptr_t>__cuMemAddressFree
 
     global __cuMemCreate
-    data["__cuMemCreate"] = <_cyb_intptr_t>__cuMemCreate
+    data["__cuMemCreate"] = <intptr_t>__cuMemCreate
 
     global __cuMemRelease
-    data["__cuMemRelease"] = <_cyb_intptr_t>__cuMemRelease
+    data["__cuMemRelease"] = <intptr_t>__cuMemRelease
 
     global __cuMemMap
-    data["__cuMemMap"] = <_cyb_intptr_t>__cuMemMap
+    data["__cuMemMap"] = <intptr_t>__cuMemMap
 
     global __cuMemMapArrayAsync
-    data["__cuMemMapArrayAsync"] = <_cyb_intptr_t>__cuMemMapArrayAsync
+    data["__cuMemMapArrayAsync"] = <intptr_t>__cuMemMapArrayAsync
 
     global __cuMemUnmap
-    data["__cuMemUnmap"] = <_cyb_intptr_t>__cuMemUnmap
+    data["__cuMemUnmap"] = <intptr_t>__cuMemUnmap
 
     global __cuMemSetAccess
-    data["__cuMemSetAccess"] = <_cyb_intptr_t>__cuMemSetAccess
+    data["__cuMemSetAccess"] = <intptr_t>__cuMemSetAccess
 
     global __cuMemGetAccess
-    data["__cuMemGetAccess"] = <_cyb_intptr_t>__cuMemGetAccess
+    data["__cuMemGetAccess"] = <intptr_t>__cuMemGetAccess
 
     global __cuMemExportToShareableHandle
-    data["__cuMemExportToShareableHandle"] = <_cyb_intptr_t>__cuMemExportToShareableHandle
+    data["__cuMemExportToShareableHandle"] = <intptr_t>__cuMemExportToShareableHandle
 
     global __cuMemImportFromShareableHandle
-    data["__cuMemImportFromShareableHandle"] = <_cyb_intptr_t>__cuMemImportFromShareableHandle
+    data["__cuMemImportFromShareableHandle"] = <intptr_t>__cuMemImportFromShareableHandle
 
     global __cuMemGetAllocationGranularity
-    data["__cuMemGetAllocationGranularity"] = <_cyb_intptr_t>__cuMemGetAllocationGranularity
+    data["__cuMemGetAllocationGranularity"] = <intptr_t>__cuMemGetAllocationGranularity
 
     global __cuMemGetAllocationPropertiesFromHandle
-    data["__cuMemGetAllocationPropertiesFromHandle"] = <_cyb_intptr_t>__cuMemGetAllocationPropertiesFromHandle
+    data["__cuMemGetAllocationPropertiesFromHandle"] = <intptr_t>__cuMemGetAllocationPropertiesFromHandle
 
     global __cuMemRetainAllocationHandle
-    data["__cuMemRetainAllocationHandle"] = <_cyb_intptr_t>__cuMemRetainAllocationHandle
+    data["__cuMemRetainAllocationHandle"] = <intptr_t>__cuMemRetainAllocationHandle
 
     global __cuMemFreeAsync
-    data["__cuMemFreeAsync"] = <_cyb_intptr_t>__cuMemFreeAsync
+    data["__cuMemFreeAsync"] = <intptr_t>__cuMemFreeAsync
 
     global __cuMemAllocAsync
-    data["__cuMemAllocAsync"] = <_cyb_intptr_t>__cuMemAllocAsync
+    data["__cuMemAllocAsync"] = <intptr_t>__cuMemAllocAsync
 
     global __cuMemPoolTrimTo
-    data["__cuMemPoolTrimTo"] = <_cyb_intptr_t>__cuMemPoolTrimTo
+    data["__cuMemPoolTrimTo"] = <intptr_t>__cuMemPoolTrimTo
 
     global __cuMemPoolSetAttribute
-    data["__cuMemPoolSetAttribute"] = <_cyb_intptr_t>__cuMemPoolSetAttribute
+    data["__cuMemPoolSetAttribute"] = <intptr_t>__cuMemPoolSetAttribute
 
     global __cuMemPoolGetAttribute
-    data["__cuMemPoolGetAttribute"] = <_cyb_intptr_t>__cuMemPoolGetAttribute
+    data["__cuMemPoolGetAttribute"] = <intptr_t>__cuMemPoolGetAttribute
 
     global __cuMemPoolSetAccess
-    data["__cuMemPoolSetAccess"] = <_cyb_intptr_t>__cuMemPoolSetAccess
+    data["__cuMemPoolSetAccess"] = <intptr_t>__cuMemPoolSetAccess
 
     global __cuMemPoolGetAccess
-    data["__cuMemPoolGetAccess"] = <_cyb_intptr_t>__cuMemPoolGetAccess
+    data["__cuMemPoolGetAccess"] = <intptr_t>__cuMemPoolGetAccess
 
     global __cuMemPoolCreate
-    data["__cuMemPoolCreate"] = <_cyb_intptr_t>__cuMemPoolCreate
+    data["__cuMemPoolCreate"] = <intptr_t>__cuMemPoolCreate
 
     global __cuMemPoolDestroy
-    data["__cuMemPoolDestroy"] = <_cyb_intptr_t>__cuMemPoolDestroy
+    data["__cuMemPoolDestroy"] = <intptr_t>__cuMemPoolDestroy
 
     global __cuMemAllocFromPoolAsync
-    data["__cuMemAllocFromPoolAsync"] = <_cyb_intptr_t>__cuMemAllocFromPoolAsync
+    data["__cuMemAllocFromPoolAsync"] = <intptr_t>__cuMemAllocFromPoolAsync
 
     global __cuMemPoolExportToShareableHandle
-    data["__cuMemPoolExportToShareableHandle"] = <_cyb_intptr_t>__cuMemPoolExportToShareableHandle
+    data["__cuMemPoolExportToShareableHandle"] = <intptr_t>__cuMemPoolExportToShareableHandle
 
     global __cuMemPoolImportFromShareableHandle
-    data["__cuMemPoolImportFromShareableHandle"] = <_cyb_intptr_t>__cuMemPoolImportFromShareableHandle
+    data["__cuMemPoolImportFromShareableHandle"] = <intptr_t>__cuMemPoolImportFromShareableHandle
 
     global __cuMemPoolExportPointer
-    data["__cuMemPoolExportPointer"] = <_cyb_intptr_t>__cuMemPoolExportPointer
+    data["__cuMemPoolExportPointer"] = <intptr_t>__cuMemPoolExportPointer
 
     global __cuMemPoolImportPointer
-    data["__cuMemPoolImportPointer"] = <_cyb_intptr_t>__cuMemPoolImportPointer
+    data["__cuMemPoolImportPointer"] = <intptr_t>__cuMemPoolImportPointer
 
     global __cuMulticastCreate
-    data["__cuMulticastCreate"] = <_cyb_intptr_t>__cuMulticastCreate
+    data["__cuMulticastCreate"] = <intptr_t>__cuMulticastCreate
 
     global __cuMulticastAddDevice
-    data["__cuMulticastAddDevice"] = <_cyb_intptr_t>__cuMulticastAddDevice
+    data["__cuMulticastAddDevice"] = <intptr_t>__cuMulticastAddDevice
 
     global __cuMulticastBindMem
-    data["__cuMulticastBindMem"] = <_cyb_intptr_t>__cuMulticastBindMem
+    data["__cuMulticastBindMem"] = <intptr_t>__cuMulticastBindMem
 
     global __cuMulticastBindAddr
-    data["__cuMulticastBindAddr"] = <_cyb_intptr_t>__cuMulticastBindAddr
+    data["__cuMulticastBindAddr"] = <intptr_t>__cuMulticastBindAddr
 
     global __cuMulticastUnbind
-    data["__cuMulticastUnbind"] = <_cyb_intptr_t>__cuMulticastUnbind
+    data["__cuMulticastUnbind"] = <intptr_t>__cuMulticastUnbind
 
     global __cuMulticastGetGranularity
-    data["__cuMulticastGetGranularity"] = <_cyb_intptr_t>__cuMulticastGetGranularity
+    data["__cuMulticastGetGranularity"] = <intptr_t>__cuMulticastGetGranularity
 
     global __cuPointerGetAttribute
-    data["__cuPointerGetAttribute"] = <_cyb_intptr_t>__cuPointerGetAttribute
+    data["__cuPointerGetAttribute"] = <intptr_t>__cuPointerGetAttribute
 
     global __cuMemPrefetchAsync_v2
-    data["__cuMemPrefetchAsync_v2"] = <_cyb_intptr_t>__cuMemPrefetchAsync_v2
+    data["__cuMemPrefetchAsync_v2"] = <intptr_t>__cuMemPrefetchAsync_v2
 
     global __cuMemAdvise_v2
-    data["__cuMemAdvise_v2"] = <_cyb_intptr_t>__cuMemAdvise_v2
+    data["__cuMemAdvise_v2"] = <intptr_t>__cuMemAdvise_v2
 
     global __cuMemRangeGetAttribute
-    data["__cuMemRangeGetAttribute"] = <_cyb_intptr_t>__cuMemRangeGetAttribute
+    data["__cuMemRangeGetAttribute"] = <intptr_t>__cuMemRangeGetAttribute
 
     global __cuMemRangeGetAttributes
-    data["__cuMemRangeGetAttributes"] = <_cyb_intptr_t>__cuMemRangeGetAttributes
+    data["__cuMemRangeGetAttributes"] = <intptr_t>__cuMemRangeGetAttributes
 
     global __cuPointerSetAttribute
-    data["__cuPointerSetAttribute"] = <_cyb_intptr_t>__cuPointerSetAttribute
+    data["__cuPointerSetAttribute"] = <intptr_t>__cuPointerSetAttribute
 
     global __cuPointerGetAttributes
-    data["__cuPointerGetAttributes"] = <_cyb_intptr_t>__cuPointerGetAttributes
+    data["__cuPointerGetAttributes"] = <intptr_t>__cuPointerGetAttributes
 
     global __cuStreamCreate
-    data["__cuStreamCreate"] = <_cyb_intptr_t>__cuStreamCreate
+    data["__cuStreamCreate"] = <intptr_t>__cuStreamCreate
 
     global __cuStreamCreateWithPriority
-    data["__cuStreamCreateWithPriority"] = <_cyb_intptr_t>__cuStreamCreateWithPriority
+    data["__cuStreamCreateWithPriority"] = <intptr_t>__cuStreamCreateWithPriority
 
     global __cuStreamGetPriority
-    data["__cuStreamGetPriority"] = <_cyb_intptr_t>__cuStreamGetPriority
+    data["__cuStreamGetPriority"] = <intptr_t>__cuStreamGetPriority
 
     global __cuStreamGetDevice
-    data["__cuStreamGetDevice"] = <_cyb_intptr_t>__cuStreamGetDevice
+    data["__cuStreamGetDevice"] = <intptr_t>__cuStreamGetDevice
 
     global __cuStreamGetFlags
-    data["__cuStreamGetFlags"] = <_cyb_intptr_t>__cuStreamGetFlags
+    data["__cuStreamGetFlags"] = <intptr_t>__cuStreamGetFlags
 
     global __cuStreamGetId
-    data["__cuStreamGetId"] = <_cyb_intptr_t>__cuStreamGetId
+    data["__cuStreamGetId"] = <intptr_t>__cuStreamGetId
 
     global __cuStreamGetCtx
-    data["__cuStreamGetCtx"] = <_cyb_intptr_t>__cuStreamGetCtx
+    data["__cuStreamGetCtx"] = <intptr_t>__cuStreamGetCtx
 
     global __cuStreamGetCtx_v2
-    data["__cuStreamGetCtx_v2"] = <_cyb_intptr_t>__cuStreamGetCtx_v2
+    data["__cuStreamGetCtx_v2"] = <intptr_t>__cuStreamGetCtx_v2
 
     global __cuStreamWaitEvent
-    data["__cuStreamWaitEvent"] = <_cyb_intptr_t>__cuStreamWaitEvent
+    data["__cuStreamWaitEvent"] = <intptr_t>__cuStreamWaitEvent
 
     global __cuStreamAddCallback
-    data["__cuStreamAddCallback"] = <_cyb_intptr_t>__cuStreamAddCallback
+    data["__cuStreamAddCallback"] = <intptr_t>__cuStreamAddCallback
 
     global __cuStreamBeginCapture_v2
-    data["__cuStreamBeginCapture_v2"] = <_cyb_intptr_t>__cuStreamBeginCapture_v2
+    data["__cuStreamBeginCapture_v2"] = <intptr_t>__cuStreamBeginCapture_v2
 
     global __cuStreamBeginCaptureToGraph
-    data["__cuStreamBeginCaptureToGraph"] = <_cyb_intptr_t>__cuStreamBeginCaptureToGraph
+    data["__cuStreamBeginCaptureToGraph"] = <intptr_t>__cuStreamBeginCaptureToGraph
 
     global __cuThreadExchangeStreamCaptureMode
-    data["__cuThreadExchangeStreamCaptureMode"] = <_cyb_intptr_t>__cuThreadExchangeStreamCaptureMode
+    data["__cuThreadExchangeStreamCaptureMode"] = <intptr_t>__cuThreadExchangeStreamCaptureMode
 
     global __cuStreamEndCapture
-    data["__cuStreamEndCapture"] = <_cyb_intptr_t>__cuStreamEndCapture
+    data["__cuStreamEndCapture"] = <intptr_t>__cuStreamEndCapture
 
     global __cuStreamIsCapturing
-    data["__cuStreamIsCapturing"] = <_cyb_intptr_t>__cuStreamIsCapturing
+    data["__cuStreamIsCapturing"] = <intptr_t>__cuStreamIsCapturing
 
     global __cuStreamGetCaptureInfo_v2
-    data["__cuStreamGetCaptureInfo_v2"] = <_cyb_intptr_t>__cuStreamGetCaptureInfo_v2
+    data["__cuStreamGetCaptureInfo_v2"] = <intptr_t>__cuStreamGetCaptureInfo_v2
 
     global __cuStreamGetCaptureInfo_v3
-    data["__cuStreamGetCaptureInfo_v3"] = <_cyb_intptr_t>__cuStreamGetCaptureInfo_v3
+    data["__cuStreamGetCaptureInfo_v3"] = <intptr_t>__cuStreamGetCaptureInfo_v3
 
     global __cuStreamUpdateCaptureDependencies_v2
-    data["__cuStreamUpdateCaptureDependencies_v2"] = <_cyb_intptr_t>__cuStreamUpdateCaptureDependencies_v2
+    data["__cuStreamUpdateCaptureDependencies_v2"] = <intptr_t>__cuStreamUpdateCaptureDependencies_v2
 
     global __cuStreamAttachMemAsync
-    data["__cuStreamAttachMemAsync"] = <_cyb_intptr_t>__cuStreamAttachMemAsync
+    data["__cuStreamAttachMemAsync"] = <intptr_t>__cuStreamAttachMemAsync
 
     global __cuStreamQuery
-    data["__cuStreamQuery"] = <_cyb_intptr_t>__cuStreamQuery
+    data["__cuStreamQuery"] = <intptr_t>__cuStreamQuery
 
     global __cuStreamSynchronize
-    data["__cuStreamSynchronize"] = <_cyb_intptr_t>__cuStreamSynchronize
+    data["__cuStreamSynchronize"] = <intptr_t>__cuStreamSynchronize
 
     global __cuStreamDestroy_v2
-    data["__cuStreamDestroy_v2"] = <_cyb_intptr_t>__cuStreamDestroy_v2
+    data["__cuStreamDestroy_v2"] = <intptr_t>__cuStreamDestroy_v2
 
     global __cuStreamCopyAttributes
-    data["__cuStreamCopyAttributes"] = <_cyb_intptr_t>__cuStreamCopyAttributes
+    data["__cuStreamCopyAttributes"] = <intptr_t>__cuStreamCopyAttributes
 
     global __cuStreamGetAttribute
-    data["__cuStreamGetAttribute"] = <_cyb_intptr_t>__cuStreamGetAttribute
+    data["__cuStreamGetAttribute"] = <intptr_t>__cuStreamGetAttribute
 
     global __cuStreamSetAttribute
-    data["__cuStreamSetAttribute"] = <_cyb_intptr_t>__cuStreamSetAttribute
+    data["__cuStreamSetAttribute"] = <intptr_t>__cuStreamSetAttribute
 
     global __cuEventCreate
-    data["__cuEventCreate"] = <_cyb_intptr_t>__cuEventCreate
+    data["__cuEventCreate"] = <intptr_t>__cuEventCreate
 
     global __cuEventRecord
-    data["__cuEventRecord"] = <_cyb_intptr_t>__cuEventRecord
+    data["__cuEventRecord"] = <intptr_t>__cuEventRecord
 
     global __cuEventRecordWithFlags
-    data["__cuEventRecordWithFlags"] = <_cyb_intptr_t>__cuEventRecordWithFlags
+    data["__cuEventRecordWithFlags"] = <intptr_t>__cuEventRecordWithFlags
 
     global __cuEventQuery
-    data["__cuEventQuery"] = <_cyb_intptr_t>__cuEventQuery
+    data["__cuEventQuery"] = <intptr_t>__cuEventQuery
 
     global __cuEventSynchronize
-    data["__cuEventSynchronize"] = <_cyb_intptr_t>__cuEventSynchronize
+    data["__cuEventSynchronize"] = <intptr_t>__cuEventSynchronize
 
     global __cuEventDestroy_v2
-    data["__cuEventDestroy_v2"] = <_cyb_intptr_t>__cuEventDestroy_v2
+    data["__cuEventDestroy_v2"] = <intptr_t>__cuEventDestroy_v2
 
     global __cuEventElapsedTime_v2
-    data["__cuEventElapsedTime_v2"] = <_cyb_intptr_t>__cuEventElapsedTime_v2
+    data["__cuEventElapsedTime_v2"] = <intptr_t>__cuEventElapsedTime_v2
 
     global __cuImportExternalMemory
-    data["__cuImportExternalMemory"] = <_cyb_intptr_t>__cuImportExternalMemory
+    data["__cuImportExternalMemory"] = <intptr_t>__cuImportExternalMemory
 
     global __cuExternalMemoryGetMappedBuffer
-    data["__cuExternalMemoryGetMappedBuffer"] = <_cyb_intptr_t>__cuExternalMemoryGetMappedBuffer
+    data["__cuExternalMemoryGetMappedBuffer"] = <intptr_t>__cuExternalMemoryGetMappedBuffer
 
     global __cuExternalMemoryGetMappedMipmappedArray
-    data["__cuExternalMemoryGetMappedMipmappedArray"] = <_cyb_intptr_t>__cuExternalMemoryGetMappedMipmappedArray
+    data["__cuExternalMemoryGetMappedMipmappedArray"] = <intptr_t>__cuExternalMemoryGetMappedMipmappedArray
 
     global __cuDestroyExternalMemory
-    data["__cuDestroyExternalMemory"] = <_cyb_intptr_t>__cuDestroyExternalMemory
+    data["__cuDestroyExternalMemory"] = <intptr_t>__cuDestroyExternalMemory
 
     global __cuImportExternalSemaphore
-    data["__cuImportExternalSemaphore"] = <_cyb_intptr_t>__cuImportExternalSemaphore
+    data["__cuImportExternalSemaphore"] = <intptr_t>__cuImportExternalSemaphore
 
     global __cuSignalExternalSemaphoresAsync
-    data["__cuSignalExternalSemaphoresAsync"] = <_cyb_intptr_t>__cuSignalExternalSemaphoresAsync
+    data["__cuSignalExternalSemaphoresAsync"] = <intptr_t>__cuSignalExternalSemaphoresAsync
 
     global __cuWaitExternalSemaphoresAsync
-    data["__cuWaitExternalSemaphoresAsync"] = <_cyb_intptr_t>__cuWaitExternalSemaphoresAsync
+    data["__cuWaitExternalSemaphoresAsync"] = <intptr_t>__cuWaitExternalSemaphoresAsync
 
     global __cuDestroyExternalSemaphore
-    data["__cuDestroyExternalSemaphore"] = <_cyb_intptr_t>__cuDestroyExternalSemaphore
+    data["__cuDestroyExternalSemaphore"] = <intptr_t>__cuDestroyExternalSemaphore
 
     global __cuStreamWaitValue32_v2
-    data["__cuStreamWaitValue32_v2"] = <_cyb_intptr_t>__cuStreamWaitValue32_v2
+    data["__cuStreamWaitValue32_v2"] = <intptr_t>__cuStreamWaitValue32_v2
 
     global __cuStreamWaitValue64_v2
-    data["__cuStreamWaitValue64_v2"] = <_cyb_intptr_t>__cuStreamWaitValue64_v2
+    data["__cuStreamWaitValue64_v2"] = <intptr_t>__cuStreamWaitValue64_v2
 
     global __cuStreamWriteValue32_v2
-    data["__cuStreamWriteValue32_v2"] = <_cyb_intptr_t>__cuStreamWriteValue32_v2
+    data["__cuStreamWriteValue32_v2"] = <intptr_t>__cuStreamWriteValue32_v2
 
     global __cuStreamWriteValue64_v2
-    data["__cuStreamWriteValue64_v2"] = <_cyb_intptr_t>__cuStreamWriteValue64_v2
+    data["__cuStreamWriteValue64_v2"] = <intptr_t>__cuStreamWriteValue64_v2
 
     global __cuStreamBatchMemOp_v2
-    data["__cuStreamBatchMemOp_v2"] = <_cyb_intptr_t>__cuStreamBatchMemOp_v2
+    data["__cuStreamBatchMemOp_v2"] = <intptr_t>__cuStreamBatchMemOp_v2
 
     global __cuFuncGetAttribute
-    data["__cuFuncGetAttribute"] = <_cyb_intptr_t>__cuFuncGetAttribute
+    data["__cuFuncGetAttribute"] = <intptr_t>__cuFuncGetAttribute
 
     global __cuFuncSetAttribute
-    data["__cuFuncSetAttribute"] = <_cyb_intptr_t>__cuFuncSetAttribute
+    data["__cuFuncSetAttribute"] = <intptr_t>__cuFuncSetAttribute
 
     global __cuFuncSetCacheConfig
-    data["__cuFuncSetCacheConfig"] = <_cyb_intptr_t>__cuFuncSetCacheConfig
+    data["__cuFuncSetCacheConfig"] = <intptr_t>__cuFuncSetCacheConfig
 
     global __cuFuncGetModule
-    data["__cuFuncGetModule"] = <_cyb_intptr_t>__cuFuncGetModule
+    data["__cuFuncGetModule"] = <intptr_t>__cuFuncGetModule
 
     global __cuFuncGetName
-    data["__cuFuncGetName"] = <_cyb_intptr_t>__cuFuncGetName
+    data["__cuFuncGetName"] = <intptr_t>__cuFuncGetName
 
     global __cuFuncGetParamInfo
-    data["__cuFuncGetParamInfo"] = <_cyb_intptr_t>__cuFuncGetParamInfo
+    data["__cuFuncGetParamInfo"] = <intptr_t>__cuFuncGetParamInfo
 
     global __cuFuncIsLoaded
-    data["__cuFuncIsLoaded"] = <_cyb_intptr_t>__cuFuncIsLoaded
+    data["__cuFuncIsLoaded"] = <intptr_t>__cuFuncIsLoaded
 
     global __cuFuncLoad
-    data["__cuFuncLoad"] = <_cyb_intptr_t>__cuFuncLoad
+    data["__cuFuncLoad"] = <intptr_t>__cuFuncLoad
 
     global __cuLaunchKernel
-    data["__cuLaunchKernel"] = <_cyb_intptr_t>__cuLaunchKernel
+    data["__cuLaunchKernel"] = <intptr_t>__cuLaunchKernel
 
     global __cuLaunchKernelEx
-    data["__cuLaunchKernelEx"] = <_cyb_intptr_t>__cuLaunchKernelEx
+    data["__cuLaunchKernelEx"] = <intptr_t>__cuLaunchKernelEx
 
     global __cuLaunchCooperativeKernel
-    data["__cuLaunchCooperativeKernel"] = <_cyb_intptr_t>__cuLaunchCooperativeKernel
+    data["__cuLaunchCooperativeKernel"] = <intptr_t>__cuLaunchCooperativeKernel
 
     global __cuLaunchCooperativeKernelMultiDevice
-    data["__cuLaunchCooperativeKernelMultiDevice"] = <_cyb_intptr_t>__cuLaunchCooperativeKernelMultiDevice
+    data["__cuLaunchCooperativeKernelMultiDevice"] = <intptr_t>__cuLaunchCooperativeKernelMultiDevice
 
     global __cuLaunchHostFunc
-    data["__cuLaunchHostFunc"] = <_cyb_intptr_t>__cuLaunchHostFunc
+    data["__cuLaunchHostFunc"] = <intptr_t>__cuLaunchHostFunc
 
     global __cuFuncSetBlockShape
-    data["__cuFuncSetBlockShape"] = <_cyb_intptr_t>__cuFuncSetBlockShape
+    data["__cuFuncSetBlockShape"] = <intptr_t>__cuFuncSetBlockShape
 
     global __cuFuncSetSharedSize
-    data["__cuFuncSetSharedSize"] = <_cyb_intptr_t>__cuFuncSetSharedSize
+    data["__cuFuncSetSharedSize"] = <intptr_t>__cuFuncSetSharedSize
 
     global __cuParamSetSize
-    data["__cuParamSetSize"] = <_cyb_intptr_t>__cuParamSetSize
+    data["__cuParamSetSize"] = <intptr_t>__cuParamSetSize
 
     global __cuParamSeti
-    data["__cuParamSeti"] = <_cyb_intptr_t>__cuParamSeti
+    data["__cuParamSeti"] = <intptr_t>__cuParamSeti
 
     global __cuParamSetf
-    data["__cuParamSetf"] = <_cyb_intptr_t>__cuParamSetf
+    data["__cuParamSetf"] = <intptr_t>__cuParamSetf
 
     global __cuParamSetv
-    data["__cuParamSetv"] = <_cyb_intptr_t>__cuParamSetv
+    data["__cuParamSetv"] = <intptr_t>__cuParamSetv
 
     global __cuLaunch
-    data["__cuLaunch"] = <_cyb_intptr_t>__cuLaunch
+    data["__cuLaunch"] = <intptr_t>__cuLaunch
 
     global __cuLaunchGrid
-    data["__cuLaunchGrid"] = <_cyb_intptr_t>__cuLaunchGrid
+    data["__cuLaunchGrid"] = <intptr_t>__cuLaunchGrid
 
     global __cuLaunchGridAsync
-    data["__cuLaunchGridAsync"] = <_cyb_intptr_t>__cuLaunchGridAsync
+    data["__cuLaunchGridAsync"] = <intptr_t>__cuLaunchGridAsync
 
     global __cuParamSetTexRef
-    data["__cuParamSetTexRef"] = <_cyb_intptr_t>__cuParamSetTexRef
+    data["__cuParamSetTexRef"] = <intptr_t>__cuParamSetTexRef
 
     global __cuFuncSetSharedMemConfig
-    data["__cuFuncSetSharedMemConfig"] = <_cyb_intptr_t>__cuFuncSetSharedMemConfig
+    data["__cuFuncSetSharedMemConfig"] = <intptr_t>__cuFuncSetSharedMemConfig
 
     global __cuGraphCreate
-    data["__cuGraphCreate"] = <_cyb_intptr_t>__cuGraphCreate
+    data["__cuGraphCreate"] = <intptr_t>__cuGraphCreate
 
     global __cuGraphAddKernelNode_v2
-    data["__cuGraphAddKernelNode_v2"] = <_cyb_intptr_t>__cuGraphAddKernelNode_v2
+    data["__cuGraphAddKernelNode_v2"] = <intptr_t>__cuGraphAddKernelNode_v2
 
     global __cuGraphKernelNodeGetParams_v2
-    data["__cuGraphKernelNodeGetParams_v2"] = <_cyb_intptr_t>__cuGraphKernelNodeGetParams_v2
+    data["__cuGraphKernelNodeGetParams_v2"] = <intptr_t>__cuGraphKernelNodeGetParams_v2
 
     global __cuGraphKernelNodeSetParams_v2
-    data["__cuGraphKernelNodeSetParams_v2"] = <_cyb_intptr_t>__cuGraphKernelNodeSetParams_v2
+    data["__cuGraphKernelNodeSetParams_v2"] = <intptr_t>__cuGraphKernelNodeSetParams_v2
 
     global __cuGraphAddMemcpyNode
-    data["__cuGraphAddMemcpyNode"] = <_cyb_intptr_t>__cuGraphAddMemcpyNode
+    data["__cuGraphAddMemcpyNode"] = <intptr_t>__cuGraphAddMemcpyNode
 
     global __cuGraphMemcpyNodeGetParams
-    data["__cuGraphMemcpyNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemcpyNodeGetParams
+    data["__cuGraphMemcpyNodeGetParams"] = <intptr_t>__cuGraphMemcpyNodeGetParams
 
     global __cuGraphMemcpyNodeSetParams
-    data["__cuGraphMemcpyNodeSetParams"] = <_cyb_intptr_t>__cuGraphMemcpyNodeSetParams
+    data["__cuGraphMemcpyNodeSetParams"] = <intptr_t>__cuGraphMemcpyNodeSetParams
 
     global __cuGraphAddMemsetNode
-    data["__cuGraphAddMemsetNode"] = <_cyb_intptr_t>__cuGraphAddMemsetNode
+    data["__cuGraphAddMemsetNode"] = <intptr_t>__cuGraphAddMemsetNode
 
     global __cuGraphMemsetNodeGetParams
-    data["__cuGraphMemsetNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemsetNodeGetParams
+    data["__cuGraphMemsetNodeGetParams"] = <intptr_t>__cuGraphMemsetNodeGetParams
 
     global __cuGraphMemsetNodeSetParams
-    data["__cuGraphMemsetNodeSetParams"] = <_cyb_intptr_t>__cuGraphMemsetNodeSetParams
+    data["__cuGraphMemsetNodeSetParams"] = <intptr_t>__cuGraphMemsetNodeSetParams
 
     global __cuGraphAddHostNode
-    data["__cuGraphAddHostNode"] = <_cyb_intptr_t>__cuGraphAddHostNode
+    data["__cuGraphAddHostNode"] = <intptr_t>__cuGraphAddHostNode
 
     global __cuGraphHostNodeGetParams
-    data["__cuGraphHostNodeGetParams"] = <_cyb_intptr_t>__cuGraphHostNodeGetParams
+    data["__cuGraphHostNodeGetParams"] = <intptr_t>__cuGraphHostNodeGetParams
 
     global __cuGraphHostNodeSetParams
-    data["__cuGraphHostNodeSetParams"] = <_cyb_intptr_t>__cuGraphHostNodeSetParams
+    data["__cuGraphHostNodeSetParams"] = <intptr_t>__cuGraphHostNodeSetParams
 
     global __cuGraphAddChildGraphNode
-    data["__cuGraphAddChildGraphNode"] = <_cyb_intptr_t>__cuGraphAddChildGraphNode
+    data["__cuGraphAddChildGraphNode"] = <intptr_t>__cuGraphAddChildGraphNode
 
     global __cuGraphChildGraphNodeGetGraph
-    data["__cuGraphChildGraphNodeGetGraph"] = <_cyb_intptr_t>__cuGraphChildGraphNodeGetGraph
+    data["__cuGraphChildGraphNodeGetGraph"] = <intptr_t>__cuGraphChildGraphNodeGetGraph
 
     global __cuGraphAddEmptyNode
-    data["__cuGraphAddEmptyNode"] = <_cyb_intptr_t>__cuGraphAddEmptyNode
+    data["__cuGraphAddEmptyNode"] = <intptr_t>__cuGraphAddEmptyNode
 
     global __cuGraphAddEventRecordNode
-    data["__cuGraphAddEventRecordNode"] = <_cyb_intptr_t>__cuGraphAddEventRecordNode
+    data["__cuGraphAddEventRecordNode"] = <intptr_t>__cuGraphAddEventRecordNode
 
     global __cuGraphEventRecordNodeGetEvent
-    data["__cuGraphEventRecordNodeGetEvent"] = <_cyb_intptr_t>__cuGraphEventRecordNodeGetEvent
+    data["__cuGraphEventRecordNodeGetEvent"] = <intptr_t>__cuGraphEventRecordNodeGetEvent
 
     global __cuGraphEventRecordNodeSetEvent
-    data["__cuGraphEventRecordNodeSetEvent"] = <_cyb_intptr_t>__cuGraphEventRecordNodeSetEvent
+    data["__cuGraphEventRecordNodeSetEvent"] = <intptr_t>__cuGraphEventRecordNodeSetEvent
 
     global __cuGraphAddEventWaitNode
-    data["__cuGraphAddEventWaitNode"] = <_cyb_intptr_t>__cuGraphAddEventWaitNode
+    data["__cuGraphAddEventWaitNode"] = <intptr_t>__cuGraphAddEventWaitNode
 
     global __cuGraphEventWaitNodeGetEvent
-    data["__cuGraphEventWaitNodeGetEvent"] = <_cyb_intptr_t>__cuGraphEventWaitNodeGetEvent
+    data["__cuGraphEventWaitNodeGetEvent"] = <intptr_t>__cuGraphEventWaitNodeGetEvent
 
     global __cuGraphEventWaitNodeSetEvent
-    data["__cuGraphEventWaitNodeSetEvent"] = <_cyb_intptr_t>__cuGraphEventWaitNodeSetEvent
+    data["__cuGraphEventWaitNodeSetEvent"] = <intptr_t>__cuGraphEventWaitNodeSetEvent
 
     global __cuGraphAddExternalSemaphoresSignalNode
-    data["__cuGraphAddExternalSemaphoresSignalNode"] = <_cyb_intptr_t>__cuGraphAddExternalSemaphoresSignalNode
+    data["__cuGraphAddExternalSemaphoresSignalNode"] = <intptr_t>__cuGraphAddExternalSemaphoresSignalNode
 
     global __cuGraphExternalSemaphoresSignalNodeGetParams
-    data["__cuGraphExternalSemaphoresSignalNodeGetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresSignalNodeGetParams
+    data["__cuGraphExternalSemaphoresSignalNodeGetParams"] = <intptr_t>__cuGraphExternalSemaphoresSignalNodeGetParams
 
     global __cuGraphExternalSemaphoresSignalNodeSetParams
-    data["__cuGraphExternalSemaphoresSignalNodeSetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresSignalNodeSetParams
+    data["__cuGraphExternalSemaphoresSignalNodeSetParams"] = <intptr_t>__cuGraphExternalSemaphoresSignalNodeSetParams
 
     global __cuGraphAddExternalSemaphoresWaitNode
-    data["__cuGraphAddExternalSemaphoresWaitNode"] = <_cyb_intptr_t>__cuGraphAddExternalSemaphoresWaitNode
+    data["__cuGraphAddExternalSemaphoresWaitNode"] = <intptr_t>__cuGraphAddExternalSemaphoresWaitNode
 
     global __cuGraphExternalSemaphoresWaitNodeGetParams
-    data["__cuGraphExternalSemaphoresWaitNodeGetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresWaitNodeGetParams
+    data["__cuGraphExternalSemaphoresWaitNodeGetParams"] = <intptr_t>__cuGraphExternalSemaphoresWaitNodeGetParams
 
     global __cuGraphExternalSemaphoresWaitNodeSetParams
-    data["__cuGraphExternalSemaphoresWaitNodeSetParams"] = <_cyb_intptr_t>__cuGraphExternalSemaphoresWaitNodeSetParams
+    data["__cuGraphExternalSemaphoresWaitNodeSetParams"] = <intptr_t>__cuGraphExternalSemaphoresWaitNodeSetParams
 
     global __cuGraphAddBatchMemOpNode
-    data["__cuGraphAddBatchMemOpNode"] = <_cyb_intptr_t>__cuGraphAddBatchMemOpNode
+    data["__cuGraphAddBatchMemOpNode"] = <intptr_t>__cuGraphAddBatchMemOpNode
 
     global __cuGraphBatchMemOpNodeGetParams
-    data["__cuGraphBatchMemOpNodeGetParams"] = <_cyb_intptr_t>__cuGraphBatchMemOpNodeGetParams
+    data["__cuGraphBatchMemOpNodeGetParams"] = <intptr_t>__cuGraphBatchMemOpNodeGetParams
 
     global __cuGraphBatchMemOpNodeSetParams
-    data["__cuGraphBatchMemOpNodeSetParams"] = <_cyb_intptr_t>__cuGraphBatchMemOpNodeSetParams
+    data["__cuGraphBatchMemOpNodeSetParams"] = <intptr_t>__cuGraphBatchMemOpNodeSetParams
 
     global __cuGraphExecBatchMemOpNodeSetParams
-    data["__cuGraphExecBatchMemOpNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecBatchMemOpNodeSetParams
+    data["__cuGraphExecBatchMemOpNodeSetParams"] = <intptr_t>__cuGraphExecBatchMemOpNodeSetParams
 
     global __cuGraphAddMemAllocNode
-    data["__cuGraphAddMemAllocNode"] = <_cyb_intptr_t>__cuGraphAddMemAllocNode
+    data["__cuGraphAddMemAllocNode"] = <intptr_t>__cuGraphAddMemAllocNode
 
     global __cuGraphMemAllocNodeGetParams
-    data["__cuGraphMemAllocNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemAllocNodeGetParams
+    data["__cuGraphMemAllocNodeGetParams"] = <intptr_t>__cuGraphMemAllocNodeGetParams
 
     global __cuGraphAddMemFreeNode
-    data["__cuGraphAddMemFreeNode"] = <_cyb_intptr_t>__cuGraphAddMemFreeNode
+    data["__cuGraphAddMemFreeNode"] = <intptr_t>__cuGraphAddMemFreeNode
 
     global __cuGraphMemFreeNodeGetParams
-    data["__cuGraphMemFreeNodeGetParams"] = <_cyb_intptr_t>__cuGraphMemFreeNodeGetParams
+    data["__cuGraphMemFreeNodeGetParams"] = <intptr_t>__cuGraphMemFreeNodeGetParams
 
     global __cuDeviceGraphMemTrim
-    data["__cuDeviceGraphMemTrim"] = <_cyb_intptr_t>__cuDeviceGraphMemTrim
+    data["__cuDeviceGraphMemTrim"] = <intptr_t>__cuDeviceGraphMemTrim
 
     global __cuDeviceGetGraphMemAttribute
-    data["__cuDeviceGetGraphMemAttribute"] = <_cyb_intptr_t>__cuDeviceGetGraphMemAttribute
+    data["__cuDeviceGetGraphMemAttribute"] = <intptr_t>__cuDeviceGetGraphMemAttribute
 
     global __cuDeviceSetGraphMemAttribute
-    data["__cuDeviceSetGraphMemAttribute"] = <_cyb_intptr_t>__cuDeviceSetGraphMemAttribute
+    data["__cuDeviceSetGraphMemAttribute"] = <intptr_t>__cuDeviceSetGraphMemAttribute
 
     global __cuGraphClone
-    data["__cuGraphClone"] = <_cyb_intptr_t>__cuGraphClone
+    data["__cuGraphClone"] = <intptr_t>__cuGraphClone
 
     global __cuGraphNodeFindInClone
-    data["__cuGraphNodeFindInClone"] = <_cyb_intptr_t>__cuGraphNodeFindInClone
+    data["__cuGraphNodeFindInClone"] = <intptr_t>__cuGraphNodeFindInClone
 
     global __cuGraphNodeGetType
-    data["__cuGraphNodeGetType"] = <_cyb_intptr_t>__cuGraphNodeGetType
+    data["__cuGraphNodeGetType"] = <intptr_t>__cuGraphNodeGetType
 
     global __cuGraphGetNodes
-    data["__cuGraphGetNodes"] = <_cyb_intptr_t>__cuGraphGetNodes
+    data["__cuGraphGetNodes"] = <intptr_t>__cuGraphGetNodes
 
     global __cuGraphGetRootNodes
-    data["__cuGraphGetRootNodes"] = <_cyb_intptr_t>__cuGraphGetRootNodes
+    data["__cuGraphGetRootNodes"] = <intptr_t>__cuGraphGetRootNodes
 
     global __cuGraphGetEdges_v2
-    data["__cuGraphGetEdges_v2"] = <_cyb_intptr_t>__cuGraphGetEdges_v2
+    data["__cuGraphGetEdges_v2"] = <intptr_t>__cuGraphGetEdges_v2
 
     global __cuGraphNodeGetDependencies_v2
-    data["__cuGraphNodeGetDependencies_v2"] = <_cyb_intptr_t>__cuGraphNodeGetDependencies_v2
+    data["__cuGraphNodeGetDependencies_v2"] = <intptr_t>__cuGraphNodeGetDependencies_v2
 
     global __cuGraphNodeGetDependentNodes_v2
-    data["__cuGraphNodeGetDependentNodes_v2"] = <_cyb_intptr_t>__cuGraphNodeGetDependentNodes_v2
+    data["__cuGraphNodeGetDependentNodes_v2"] = <intptr_t>__cuGraphNodeGetDependentNodes_v2
 
     global __cuGraphAddDependencies_v2
-    data["__cuGraphAddDependencies_v2"] = <_cyb_intptr_t>__cuGraphAddDependencies_v2
+    data["__cuGraphAddDependencies_v2"] = <intptr_t>__cuGraphAddDependencies_v2
 
     global __cuGraphRemoveDependencies_v2
-    data["__cuGraphRemoveDependencies_v2"] = <_cyb_intptr_t>__cuGraphRemoveDependencies_v2
+    data["__cuGraphRemoveDependencies_v2"] = <intptr_t>__cuGraphRemoveDependencies_v2
 
     global __cuGraphDestroyNode
-    data["__cuGraphDestroyNode"] = <_cyb_intptr_t>__cuGraphDestroyNode
+    data["__cuGraphDestroyNode"] = <intptr_t>__cuGraphDestroyNode
 
     global __cuGraphInstantiateWithFlags
-    data["__cuGraphInstantiateWithFlags"] = <_cyb_intptr_t>__cuGraphInstantiateWithFlags
+    data["__cuGraphInstantiateWithFlags"] = <intptr_t>__cuGraphInstantiateWithFlags
 
     global __cuGraphInstantiateWithParams
-    data["__cuGraphInstantiateWithParams"] = <_cyb_intptr_t>__cuGraphInstantiateWithParams
+    data["__cuGraphInstantiateWithParams"] = <intptr_t>__cuGraphInstantiateWithParams
 
     global __cuGraphExecGetFlags
-    data["__cuGraphExecGetFlags"] = <_cyb_intptr_t>__cuGraphExecGetFlags
+    data["__cuGraphExecGetFlags"] = <intptr_t>__cuGraphExecGetFlags
 
     global __cuGraphExecKernelNodeSetParams_v2
-    data["__cuGraphExecKernelNodeSetParams_v2"] = <_cyb_intptr_t>__cuGraphExecKernelNodeSetParams_v2
+    data["__cuGraphExecKernelNodeSetParams_v2"] = <intptr_t>__cuGraphExecKernelNodeSetParams_v2
 
     global __cuGraphExecMemcpyNodeSetParams
-    data["__cuGraphExecMemcpyNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecMemcpyNodeSetParams
+    data["__cuGraphExecMemcpyNodeSetParams"] = <intptr_t>__cuGraphExecMemcpyNodeSetParams
 
     global __cuGraphExecMemsetNodeSetParams
-    data["__cuGraphExecMemsetNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecMemsetNodeSetParams
+    data["__cuGraphExecMemsetNodeSetParams"] = <intptr_t>__cuGraphExecMemsetNodeSetParams
 
     global __cuGraphExecHostNodeSetParams
-    data["__cuGraphExecHostNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecHostNodeSetParams
+    data["__cuGraphExecHostNodeSetParams"] = <intptr_t>__cuGraphExecHostNodeSetParams
 
     global __cuGraphExecChildGraphNodeSetParams
-    data["__cuGraphExecChildGraphNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecChildGraphNodeSetParams
+    data["__cuGraphExecChildGraphNodeSetParams"] = <intptr_t>__cuGraphExecChildGraphNodeSetParams
 
     global __cuGraphExecEventRecordNodeSetEvent
-    data["__cuGraphExecEventRecordNodeSetEvent"] = <_cyb_intptr_t>__cuGraphExecEventRecordNodeSetEvent
+    data["__cuGraphExecEventRecordNodeSetEvent"] = <intptr_t>__cuGraphExecEventRecordNodeSetEvent
 
     global __cuGraphExecEventWaitNodeSetEvent
-    data["__cuGraphExecEventWaitNodeSetEvent"] = <_cyb_intptr_t>__cuGraphExecEventWaitNodeSetEvent
+    data["__cuGraphExecEventWaitNodeSetEvent"] = <intptr_t>__cuGraphExecEventWaitNodeSetEvent
 
     global __cuGraphExecExternalSemaphoresSignalNodeSetParams
-    data["__cuGraphExecExternalSemaphoresSignalNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecExternalSemaphoresSignalNodeSetParams
+    data["__cuGraphExecExternalSemaphoresSignalNodeSetParams"] = <intptr_t>__cuGraphExecExternalSemaphoresSignalNodeSetParams
 
     global __cuGraphExecExternalSemaphoresWaitNodeSetParams
-    data["__cuGraphExecExternalSemaphoresWaitNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecExternalSemaphoresWaitNodeSetParams
+    data["__cuGraphExecExternalSemaphoresWaitNodeSetParams"] = <intptr_t>__cuGraphExecExternalSemaphoresWaitNodeSetParams
 
     global __cuGraphNodeSetEnabled
-    data["__cuGraphNodeSetEnabled"] = <_cyb_intptr_t>__cuGraphNodeSetEnabled
+    data["__cuGraphNodeSetEnabled"] = <intptr_t>__cuGraphNodeSetEnabled
 
     global __cuGraphNodeGetEnabled
-    data["__cuGraphNodeGetEnabled"] = <_cyb_intptr_t>__cuGraphNodeGetEnabled
+    data["__cuGraphNodeGetEnabled"] = <intptr_t>__cuGraphNodeGetEnabled
 
     global __cuGraphUpload
-    data["__cuGraphUpload"] = <_cyb_intptr_t>__cuGraphUpload
+    data["__cuGraphUpload"] = <intptr_t>__cuGraphUpload
 
     global __cuGraphLaunch
-    data["__cuGraphLaunch"] = <_cyb_intptr_t>__cuGraphLaunch
+    data["__cuGraphLaunch"] = <intptr_t>__cuGraphLaunch
 
     global __cuGraphExecDestroy
-    data["__cuGraphExecDestroy"] = <_cyb_intptr_t>__cuGraphExecDestroy
+    data["__cuGraphExecDestroy"] = <intptr_t>__cuGraphExecDestroy
 
     global __cuGraphDestroy
-    data["__cuGraphDestroy"] = <_cyb_intptr_t>__cuGraphDestroy
+    data["__cuGraphDestroy"] = <intptr_t>__cuGraphDestroy
 
     global __cuGraphExecUpdate_v2
-    data["__cuGraphExecUpdate_v2"] = <_cyb_intptr_t>__cuGraphExecUpdate_v2
+    data["__cuGraphExecUpdate_v2"] = <intptr_t>__cuGraphExecUpdate_v2
 
     global __cuGraphKernelNodeCopyAttributes
-    data["__cuGraphKernelNodeCopyAttributes"] = <_cyb_intptr_t>__cuGraphKernelNodeCopyAttributes
+    data["__cuGraphKernelNodeCopyAttributes"] = <intptr_t>__cuGraphKernelNodeCopyAttributes
 
     global __cuGraphKernelNodeGetAttribute
-    data["__cuGraphKernelNodeGetAttribute"] = <_cyb_intptr_t>__cuGraphKernelNodeGetAttribute
+    data["__cuGraphKernelNodeGetAttribute"] = <intptr_t>__cuGraphKernelNodeGetAttribute
 
     global __cuGraphKernelNodeSetAttribute
-    data["__cuGraphKernelNodeSetAttribute"] = <_cyb_intptr_t>__cuGraphKernelNodeSetAttribute
+    data["__cuGraphKernelNodeSetAttribute"] = <intptr_t>__cuGraphKernelNodeSetAttribute
 
     global __cuGraphDebugDotPrint
-    data["__cuGraphDebugDotPrint"] = <_cyb_intptr_t>__cuGraphDebugDotPrint
+    data["__cuGraphDebugDotPrint"] = <intptr_t>__cuGraphDebugDotPrint
 
     global __cuUserObjectCreate
-    data["__cuUserObjectCreate"] = <_cyb_intptr_t>__cuUserObjectCreate
+    data["__cuUserObjectCreate"] = <intptr_t>__cuUserObjectCreate
 
     global __cuUserObjectRetain
-    data["__cuUserObjectRetain"] = <_cyb_intptr_t>__cuUserObjectRetain
+    data["__cuUserObjectRetain"] = <intptr_t>__cuUserObjectRetain
 
     global __cuUserObjectRelease
-    data["__cuUserObjectRelease"] = <_cyb_intptr_t>__cuUserObjectRelease
+    data["__cuUserObjectRelease"] = <intptr_t>__cuUserObjectRelease
 
     global __cuGraphRetainUserObject
-    data["__cuGraphRetainUserObject"] = <_cyb_intptr_t>__cuGraphRetainUserObject
+    data["__cuGraphRetainUserObject"] = <intptr_t>__cuGraphRetainUserObject
 
     global __cuGraphReleaseUserObject
-    data["__cuGraphReleaseUserObject"] = <_cyb_intptr_t>__cuGraphReleaseUserObject
+    data["__cuGraphReleaseUserObject"] = <intptr_t>__cuGraphReleaseUserObject
 
     global __cuGraphAddNode_v2
-    data["__cuGraphAddNode_v2"] = <_cyb_intptr_t>__cuGraphAddNode_v2
+    data["__cuGraphAddNode_v2"] = <intptr_t>__cuGraphAddNode_v2
 
     global __cuGraphNodeSetParams
-    data["__cuGraphNodeSetParams"] = <_cyb_intptr_t>__cuGraphNodeSetParams
+    data["__cuGraphNodeSetParams"] = <intptr_t>__cuGraphNodeSetParams
 
     global __cuGraphExecNodeSetParams
-    data["__cuGraphExecNodeSetParams"] = <_cyb_intptr_t>__cuGraphExecNodeSetParams
+    data["__cuGraphExecNodeSetParams"] = <intptr_t>__cuGraphExecNodeSetParams
 
     global __cuGraphConditionalHandleCreate
-    data["__cuGraphConditionalHandleCreate"] = <_cyb_intptr_t>__cuGraphConditionalHandleCreate
+    data["__cuGraphConditionalHandleCreate"] = <intptr_t>__cuGraphConditionalHandleCreate
 
     global __cuOccupancyMaxActiveBlocksPerMultiprocessor
-    data["__cuOccupancyMaxActiveBlocksPerMultiprocessor"] = <_cyb_intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessor
+    data["__cuOccupancyMaxActiveBlocksPerMultiprocessor"] = <intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessor
 
     global __cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
-    data["__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags"] = <_cyb_intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
+    data["__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags"] = <intptr_t>__cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags
 
     global __cuOccupancyMaxPotentialBlockSize
-    data["__cuOccupancyMaxPotentialBlockSize"] = <_cyb_intptr_t>__cuOccupancyMaxPotentialBlockSize
+    data["__cuOccupancyMaxPotentialBlockSize"] = <intptr_t>__cuOccupancyMaxPotentialBlockSize
 
     global __cuOccupancyMaxPotentialBlockSizeWithFlags
-    data["__cuOccupancyMaxPotentialBlockSizeWithFlags"] = <_cyb_intptr_t>__cuOccupancyMaxPotentialBlockSizeWithFlags
+    data["__cuOccupancyMaxPotentialBlockSizeWithFlags"] = <intptr_t>__cuOccupancyMaxPotentialBlockSizeWithFlags
 
     global __cuOccupancyAvailableDynamicSMemPerBlock
-    data["__cuOccupancyAvailableDynamicSMemPerBlock"] = <_cyb_intptr_t>__cuOccupancyAvailableDynamicSMemPerBlock
+    data["__cuOccupancyAvailableDynamicSMemPerBlock"] = <intptr_t>__cuOccupancyAvailableDynamicSMemPerBlock
 
     global __cuOccupancyMaxPotentialClusterSize
-    data["__cuOccupancyMaxPotentialClusterSize"] = <_cyb_intptr_t>__cuOccupancyMaxPotentialClusterSize
+    data["__cuOccupancyMaxPotentialClusterSize"] = <intptr_t>__cuOccupancyMaxPotentialClusterSize
 
     global __cuOccupancyMaxActiveClusters
-    data["__cuOccupancyMaxActiveClusters"] = <_cyb_intptr_t>__cuOccupancyMaxActiveClusters
+    data["__cuOccupancyMaxActiveClusters"] = <intptr_t>__cuOccupancyMaxActiveClusters
 
     global __cuTexRefSetArray
-    data["__cuTexRefSetArray"] = <_cyb_intptr_t>__cuTexRefSetArray
+    data["__cuTexRefSetArray"] = <intptr_t>__cuTexRefSetArray
 
     global __cuTexRefSetMipmappedArray
-    data["__cuTexRefSetMipmappedArray"] = <_cyb_intptr_t>__cuTexRefSetMipmappedArray
+    data["__cuTexRefSetMipmappedArray"] = <intptr_t>__cuTexRefSetMipmappedArray
 
     global __cuTexRefSetAddress_v2
-    data["__cuTexRefSetAddress_v2"] = <_cyb_intptr_t>__cuTexRefSetAddress_v2
+    data["__cuTexRefSetAddress_v2"] = <intptr_t>__cuTexRefSetAddress_v2
 
     global __cuTexRefSetAddress2D_v3
-    data["__cuTexRefSetAddress2D_v3"] = <_cyb_intptr_t>__cuTexRefSetAddress2D_v3
+    data["__cuTexRefSetAddress2D_v3"] = <intptr_t>__cuTexRefSetAddress2D_v3
 
     global __cuTexRefSetFormat
-    data["__cuTexRefSetFormat"] = <_cyb_intptr_t>__cuTexRefSetFormat
+    data["__cuTexRefSetFormat"] = <intptr_t>__cuTexRefSetFormat
 
     global __cuTexRefSetAddressMode
-    data["__cuTexRefSetAddressMode"] = <_cyb_intptr_t>__cuTexRefSetAddressMode
+    data["__cuTexRefSetAddressMode"] = <intptr_t>__cuTexRefSetAddressMode
 
     global __cuTexRefSetFilterMode
-    data["__cuTexRefSetFilterMode"] = <_cyb_intptr_t>__cuTexRefSetFilterMode
+    data["__cuTexRefSetFilterMode"] = <intptr_t>__cuTexRefSetFilterMode
 
     global __cuTexRefSetMipmapFilterMode
-    data["__cuTexRefSetMipmapFilterMode"] = <_cyb_intptr_t>__cuTexRefSetMipmapFilterMode
+    data["__cuTexRefSetMipmapFilterMode"] = <intptr_t>__cuTexRefSetMipmapFilterMode
 
     global __cuTexRefSetMipmapLevelBias
-    data["__cuTexRefSetMipmapLevelBias"] = <_cyb_intptr_t>__cuTexRefSetMipmapLevelBias
+    data["__cuTexRefSetMipmapLevelBias"] = <intptr_t>__cuTexRefSetMipmapLevelBias
 
     global __cuTexRefSetMipmapLevelClamp
-    data["__cuTexRefSetMipmapLevelClamp"] = <_cyb_intptr_t>__cuTexRefSetMipmapLevelClamp
+    data["__cuTexRefSetMipmapLevelClamp"] = <intptr_t>__cuTexRefSetMipmapLevelClamp
 
     global __cuTexRefSetMaxAnisotropy
-    data["__cuTexRefSetMaxAnisotropy"] = <_cyb_intptr_t>__cuTexRefSetMaxAnisotropy
+    data["__cuTexRefSetMaxAnisotropy"] = <intptr_t>__cuTexRefSetMaxAnisotropy
 
     global __cuTexRefSetBorderColor
-    data["__cuTexRefSetBorderColor"] = <_cyb_intptr_t>__cuTexRefSetBorderColor
+    data["__cuTexRefSetBorderColor"] = <intptr_t>__cuTexRefSetBorderColor
 
     global __cuTexRefSetFlags
-    data["__cuTexRefSetFlags"] = <_cyb_intptr_t>__cuTexRefSetFlags
+    data["__cuTexRefSetFlags"] = <intptr_t>__cuTexRefSetFlags
 
     global __cuTexRefGetAddress_v2
-    data["__cuTexRefGetAddress_v2"] = <_cyb_intptr_t>__cuTexRefGetAddress_v2
+    data["__cuTexRefGetAddress_v2"] = <intptr_t>__cuTexRefGetAddress_v2
 
     global __cuTexRefGetArray
-    data["__cuTexRefGetArray"] = <_cyb_intptr_t>__cuTexRefGetArray
+    data["__cuTexRefGetArray"] = <intptr_t>__cuTexRefGetArray
 
     global __cuTexRefGetMipmappedArray
-    data["__cuTexRefGetMipmappedArray"] = <_cyb_intptr_t>__cuTexRefGetMipmappedArray
+    data["__cuTexRefGetMipmappedArray"] = <intptr_t>__cuTexRefGetMipmappedArray
 
     global __cuTexRefGetAddressMode
-    data["__cuTexRefGetAddressMode"] = <_cyb_intptr_t>__cuTexRefGetAddressMode
+    data["__cuTexRefGetAddressMode"] = <intptr_t>__cuTexRefGetAddressMode
 
     global __cuTexRefGetFilterMode
-    data["__cuTexRefGetFilterMode"] = <_cyb_intptr_t>__cuTexRefGetFilterMode
+    data["__cuTexRefGetFilterMode"] = <intptr_t>__cuTexRefGetFilterMode
 
     global __cuTexRefGetFormat
-    data["__cuTexRefGetFormat"] = <_cyb_intptr_t>__cuTexRefGetFormat
+    data["__cuTexRefGetFormat"] = <intptr_t>__cuTexRefGetFormat
 
     global __cuTexRefGetMipmapFilterMode
-    data["__cuTexRefGetMipmapFilterMode"] = <_cyb_intptr_t>__cuTexRefGetMipmapFilterMode
+    data["__cuTexRefGetMipmapFilterMode"] = <intptr_t>__cuTexRefGetMipmapFilterMode
 
     global __cuTexRefGetMipmapLevelBias
-    data["__cuTexRefGetMipmapLevelBias"] = <_cyb_intptr_t>__cuTexRefGetMipmapLevelBias
+    data["__cuTexRefGetMipmapLevelBias"] = <intptr_t>__cuTexRefGetMipmapLevelBias
 
     global __cuTexRefGetMipmapLevelClamp
-    data["__cuTexRefGetMipmapLevelClamp"] = <_cyb_intptr_t>__cuTexRefGetMipmapLevelClamp
+    data["__cuTexRefGetMipmapLevelClamp"] = <intptr_t>__cuTexRefGetMipmapLevelClamp
 
     global __cuTexRefGetMaxAnisotropy
-    data["__cuTexRefGetMaxAnisotropy"] = <_cyb_intptr_t>__cuTexRefGetMaxAnisotropy
+    data["__cuTexRefGetMaxAnisotropy"] = <intptr_t>__cuTexRefGetMaxAnisotropy
 
     global __cuTexRefGetBorderColor
-    data["__cuTexRefGetBorderColor"] = <_cyb_intptr_t>__cuTexRefGetBorderColor
+    data["__cuTexRefGetBorderColor"] = <intptr_t>__cuTexRefGetBorderColor
 
     global __cuTexRefGetFlags
-    data["__cuTexRefGetFlags"] = <_cyb_intptr_t>__cuTexRefGetFlags
+    data["__cuTexRefGetFlags"] = <intptr_t>__cuTexRefGetFlags
 
     global __cuTexRefCreate
-    data["__cuTexRefCreate"] = <_cyb_intptr_t>__cuTexRefCreate
+    data["__cuTexRefCreate"] = <intptr_t>__cuTexRefCreate
 
     global __cuTexRefDestroy
-    data["__cuTexRefDestroy"] = <_cyb_intptr_t>__cuTexRefDestroy
+    data["__cuTexRefDestroy"] = <intptr_t>__cuTexRefDestroy
 
     global __cuSurfRefSetArray
-    data["__cuSurfRefSetArray"] = <_cyb_intptr_t>__cuSurfRefSetArray
+    data["__cuSurfRefSetArray"] = <intptr_t>__cuSurfRefSetArray
 
     global __cuSurfRefGetArray
-    data["__cuSurfRefGetArray"] = <_cyb_intptr_t>__cuSurfRefGetArray
+    data["__cuSurfRefGetArray"] = <intptr_t>__cuSurfRefGetArray
 
     global __cuTexObjectCreate
-    data["__cuTexObjectCreate"] = <_cyb_intptr_t>__cuTexObjectCreate
+    data["__cuTexObjectCreate"] = <intptr_t>__cuTexObjectCreate
 
     global __cuTexObjectDestroy
-    data["__cuTexObjectDestroy"] = <_cyb_intptr_t>__cuTexObjectDestroy
+    data["__cuTexObjectDestroy"] = <intptr_t>__cuTexObjectDestroy
 
     global __cuTexObjectGetResourceDesc
-    data["__cuTexObjectGetResourceDesc"] = <_cyb_intptr_t>__cuTexObjectGetResourceDesc
+    data["__cuTexObjectGetResourceDesc"] = <intptr_t>__cuTexObjectGetResourceDesc
 
     global __cuTexObjectGetTextureDesc
-    data["__cuTexObjectGetTextureDesc"] = <_cyb_intptr_t>__cuTexObjectGetTextureDesc
+    data["__cuTexObjectGetTextureDesc"] = <intptr_t>__cuTexObjectGetTextureDesc
 
     global __cuTexObjectGetResourceViewDesc
-    data["__cuTexObjectGetResourceViewDesc"] = <_cyb_intptr_t>__cuTexObjectGetResourceViewDesc
+    data["__cuTexObjectGetResourceViewDesc"] = <intptr_t>__cuTexObjectGetResourceViewDesc
 
     global __cuSurfObjectCreate
-    data["__cuSurfObjectCreate"] = <_cyb_intptr_t>__cuSurfObjectCreate
+    data["__cuSurfObjectCreate"] = <intptr_t>__cuSurfObjectCreate
 
     global __cuSurfObjectDestroy
-    data["__cuSurfObjectDestroy"] = <_cyb_intptr_t>__cuSurfObjectDestroy
+    data["__cuSurfObjectDestroy"] = <intptr_t>__cuSurfObjectDestroy
 
     global __cuSurfObjectGetResourceDesc
-    data["__cuSurfObjectGetResourceDesc"] = <_cyb_intptr_t>__cuSurfObjectGetResourceDesc
+    data["__cuSurfObjectGetResourceDesc"] = <intptr_t>__cuSurfObjectGetResourceDesc
 
     global __cuTensorMapEncodeTiled
-    data["__cuTensorMapEncodeTiled"] = <_cyb_intptr_t>__cuTensorMapEncodeTiled
+    data["__cuTensorMapEncodeTiled"] = <intptr_t>__cuTensorMapEncodeTiled
 
     global __cuTensorMapEncodeIm2col
-    data["__cuTensorMapEncodeIm2col"] = <_cyb_intptr_t>__cuTensorMapEncodeIm2col
+    data["__cuTensorMapEncodeIm2col"] = <intptr_t>__cuTensorMapEncodeIm2col
 
     global __cuTensorMapEncodeIm2colWide
-    data["__cuTensorMapEncodeIm2colWide"] = <_cyb_intptr_t>__cuTensorMapEncodeIm2colWide
+    data["__cuTensorMapEncodeIm2colWide"] = <intptr_t>__cuTensorMapEncodeIm2colWide
 
     global __cuTensorMapReplaceAddress
-    data["__cuTensorMapReplaceAddress"] = <_cyb_intptr_t>__cuTensorMapReplaceAddress
+    data["__cuTensorMapReplaceAddress"] = <intptr_t>__cuTensorMapReplaceAddress
 
     global __cuDeviceCanAccessPeer
-    data["__cuDeviceCanAccessPeer"] = <_cyb_intptr_t>__cuDeviceCanAccessPeer
+    data["__cuDeviceCanAccessPeer"] = <intptr_t>__cuDeviceCanAccessPeer
 
     global __cuCtxEnablePeerAccess
-    data["__cuCtxEnablePeerAccess"] = <_cyb_intptr_t>__cuCtxEnablePeerAccess
+    data["__cuCtxEnablePeerAccess"] = <intptr_t>__cuCtxEnablePeerAccess
 
     global __cuCtxDisablePeerAccess
-    data["__cuCtxDisablePeerAccess"] = <_cyb_intptr_t>__cuCtxDisablePeerAccess
+    data["__cuCtxDisablePeerAccess"] = <intptr_t>__cuCtxDisablePeerAccess
 
     global __cuDeviceGetP2PAttribute
-    data["__cuDeviceGetP2PAttribute"] = <_cyb_intptr_t>__cuDeviceGetP2PAttribute
+    data["__cuDeviceGetP2PAttribute"] = <intptr_t>__cuDeviceGetP2PAttribute
 
     global __cuGraphicsUnregisterResource
-    data["__cuGraphicsUnregisterResource"] = <_cyb_intptr_t>__cuGraphicsUnregisterResource
+    data["__cuGraphicsUnregisterResource"] = <intptr_t>__cuGraphicsUnregisterResource
 
     global __cuGraphicsSubResourceGetMappedArray
-    data["__cuGraphicsSubResourceGetMappedArray"] = <_cyb_intptr_t>__cuGraphicsSubResourceGetMappedArray
+    data["__cuGraphicsSubResourceGetMappedArray"] = <intptr_t>__cuGraphicsSubResourceGetMappedArray
 
     global __cuGraphicsResourceGetMappedMipmappedArray
-    data["__cuGraphicsResourceGetMappedMipmappedArray"] = <_cyb_intptr_t>__cuGraphicsResourceGetMappedMipmappedArray
+    data["__cuGraphicsResourceGetMappedMipmappedArray"] = <intptr_t>__cuGraphicsResourceGetMappedMipmappedArray
 
     global __cuGraphicsResourceGetMappedPointer_v2
-    data["__cuGraphicsResourceGetMappedPointer_v2"] = <_cyb_intptr_t>__cuGraphicsResourceGetMappedPointer_v2
+    data["__cuGraphicsResourceGetMappedPointer_v2"] = <intptr_t>__cuGraphicsResourceGetMappedPointer_v2
 
     global __cuGraphicsResourceSetMapFlags_v2
-    data["__cuGraphicsResourceSetMapFlags_v2"] = <_cyb_intptr_t>__cuGraphicsResourceSetMapFlags_v2
+    data["__cuGraphicsResourceSetMapFlags_v2"] = <intptr_t>__cuGraphicsResourceSetMapFlags_v2
 
     global __cuGraphicsMapResources
-    data["__cuGraphicsMapResources"] = <_cyb_intptr_t>__cuGraphicsMapResources
+    data["__cuGraphicsMapResources"] = <intptr_t>__cuGraphicsMapResources
 
     global __cuGraphicsUnmapResources
-    data["__cuGraphicsUnmapResources"] = <_cyb_intptr_t>__cuGraphicsUnmapResources
+    data["__cuGraphicsUnmapResources"] = <intptr_t>__cuGraphicsUnmapResources
 
     global __cuGetProcAddress_v2
-    data["__cuGetProcAddress_v2"] = <_cyb_intptr_t>__cuGetProcAddress_v2
+    data["__cuGetProcAddress_v2"] = <intptr_t>__cuGetProcAddress_v2
 
     global __cuCoredumpGetAttribute
-    data["__cuCoredumpGetAttribute"] = <_cyb_intptr_t>__cuCoredumpGetAttribute
+    data["__cuCoredumpGetAttribute"] = <intptr_t>__cuCoredumpGetAttribute
 
     global __cuCoredumpGetAttributeGlobal
-    data["__cuCoredumpGetAttributeGlobal"] = <_cyb_intptr_t>__cuCoredumpGetAttributeGlobal
+    data["__cuCoredumpGetAttributeGlobal"] = <intptr_t>__cuCoredumpGetAttributeGlobal
 
     global __cuCoredumpSetAttribute
-    data["__cuCoredumpSetAttribute"] = <_cyb_intptr_t>__cuCoredumpSetAttribute
+    data["__cuCoredumpSetAttribute"] = <intptr_t>__cuCoredumpSetAttribute
 
     global __cuCoredumpSetAttributeGlobal
-    data["__cuCoredumpSetAttributeGlobal"] = <_cyb_intptr_t>__cuCoredumpSetAttributeGlobal
+    data["__cuCoredumpSetAttributeGlobal"] = <intptr_t>__cuCoredumpSetAttributeGlobal
 
     global __cuGetExportTable
-    data["__cuGetExportTable"] = <_cyb_intptr_t>__cuGetExportTable
+    data["__cuGetExportTable"] = <intptr_t>__cuGetExportTable
 
     global __cuGreenCtxCreate
-    data["__cuGreenCtxCreate"] = <_cyb_intptr_t>__cuGreenCtxCreate
+    data["__cuGreenCtxCreate"] = <intptr_t>__cuGreenCtxCreate
 
     global __cuGreenCtxDestroy
-    data["__cuGreenCtxDestroy"] = <_cyb_intptr_t>__cuGreenCtxDestroy
+    data["__cuGreenCtxDestroy"] = <intptr_t>__cuGreenCtxDestroy
 
     global __cuCtxFromGreenCtx
-    data["__cuCtxFromGreenCtx"] = <_cyb_intptr_t>__cuCtxFromGreenCtx
+    data["__cuCtxFromGreenCtx"] = <intptr_t>__cuCtxFromGreenCtx
 
     global __cuDeviceGetDevResource
-    data["__cuDeviceGetDevResource"] = <_cyb_intptr_t>__cuDeviceGetDevResource
+    data["__cuDeviceGetDevResource"] = <intptr_t>__cuDeviceGetDevResource
 
     global __cuCtxGetDevResource
-    data["__cuCtxGetDevResource"] = <_cyb_intptr_t>__cuCtxGetDevResource
+    data["__cuCtxGetDevResource"] = <intptr_t>__cuCtxGetDevResource
 
     global __cuGreenCtxGetDevResource
-    data["__cuGreenCtxGetDevResource"] = <_cyb_intptr_t>__cuGreenCtxGetDevResource
+    data["__cuGreenCtxGetDevResource"] = <intptr_t>__cuGreenCtxGetDevResource
 
     global __cuDevSmResourceSplitByCount
-    data["__cuDevSmResourceSplitByCount"] = <_cyb_intptr_t>__cuDevSmResourceSplitByCount
+    data["__cuDevSmResourceSplitByCount"] = <intptr_t>__cuDevSmResourceSplitByCount
 
     global __cuDevResourceGenerateDesc
-    data["__cuDevResourceGenerateDesc"] = <_cyb_intptr_t>__cuDevResourceGenerateDesc
+    data["__cuDevResourceGenerateDesc"] = <intptr_t>__cuDevResourceGenerateDesc
 
     global __cuGreenCtxRecordEvent
-    data["__cuGreenCtxRecordEvent"] = <_cyb_intptr_t>__cuGreenCtxRecordEvent
+    data["__cuGreenCtxRecordEvent"] = <intptr_t>__cuGreenCtxRecordEvent
 
     global __cuGreenCtxWaitEvent
-    data["__cuGreenCtxWaitEvent"] = <_cyb_intptr_t>__cuGreenCtxWaitEvent
+    data["__cuGreenCtxWaitEvent"] = <intptr_t>__cuGreenCtxWaitEvent
 
     global __cuStreamGetGreenCtx
-    data["__cuStreamGetGreenCtx"] = <_cyb_intptr_t>__cuStreamGetGreenCtx
+    data["__cuStreamGetGreenCtx"] = <intptr_t>__cuStreamGetGreenCtx
 
     global __cuGreenCtxStreamCreate
-    data["__cuGreenCtxStreamCreate"] = <_cyb_intptr_t>__cuGreenCtxStreamCreate
+    data["__cuGreenCtxStreamCreate"] = <intptr_t>__cuGreenCtxStreamCreate
 
     global __cuLogsRegisterCallback
-    data["__cuLogsRegisterCallback"] = <_cyb_intptr_t>__cuLogsRegisterCallback
+    data["__cuLogsRegisterCallback"] = <intptr_t>__cuLogsRegisterCallback
 
     global __cuLogsUnregisterCallback
-    data["__cuLogsUnregisterCallback"] = <_cyb_intptr_t>__cuLogsUnregisterCallback
+    data["__cuLogsUnregisterCallback"] = <intptr_t>__cuLogsUnregisterCallback
 
     global __cuLogsCurrent
-    data["__cuLogsCurrent"] = <_cyb_intptr_t>__cuLogsCurrent
+    data["__cuLogsCurrent"] = <intptr_t>__cuLogsCurrent
 
     global __cuLogsDumpToFile
-    data["__cuLogsDumpToFile"] = <_cyb_intptr_t>__cuLogsDumpToFile
+    data["__cuLogsDumpToFile"] = <intptr_t>__cuLogsDumpToFile
 
     global __cuLogsDumpToMemory
-    data["__cuLogsDumpToMemory"] = <_cyb_intptr_t>__cuLogsDumpToMemory
+    data["__cuLogsDumpToMemory"] = <intptr_t>__cuLogsDumpToMemory
 
     global __cuCheckpointProcessGetRestoreThreadId
-    data["__cuCheckpointProcessGetRestoreThreadId"] = <_cyb_intptr_t>__cuCheckpointProcessGetRestoreThreadId
+    data["__cuCheckpointProcessGetRestoreThreadId"] = <intptr_t>__cuCheckpointProcessGetRestoreThreadId
 
     global __cuCheckpointProcessGetState
-    data["__cuCheckpointProcessGetState"] = <_cyb_intptr_t>__cuCheckpointProcessGetState
+    data["__cuCheckpointProcessGetState"] = <intptr_t>__cuCheckpointProcessGetState
 
     global __cuCheckpointProcessLock
-    data["__cuCheckpointProcessLock"] = <_cyb_intptr_t>__cuCheckpointProcessLock
+    data["__cuCheckpointProcessLock"] = <intptr_t>__cuCheckpointProcessLock
 
     global __cuCheckpointProcessCheckpoint
-    data["__cuCheckpointProcessCheckpoint"] = <_cyb_intptr_t>__cuCheckpointProcessCheckpoint
+    data["__cuCheckpointProcessCheckpoint"] = <intptr_t>__cuCheckpointProcessCheckpoint
 
     global __cuCheckpointProcessRestore
-    data["__cuCheckpointProcessRestore"] = <_cyb_intptr_t>__cuCheckpointProcessRestore
+    data["__cuCheckpointProcessRestore"] = <intptr_t>__cuCheckpointProcessRestore
 
     global __cuCheckpointProcessUnlock
-    data["__cuCheckpointProcessUnlock"] = <_cyb_intptr_t>__cuCheckpointProcessUnlock
+    data["__cuCheckpointProcessUnlock"] = <intptr_t>__cuCheckpointProcessUnlock
 
     global __cuGraphicsEGLRegisterImage
-    data["__cuGraphicsEGLRegisterImage"] = <_cyb_intptr_t>__cuGraphicsEGLRegisterImage
+    data["__cuGraphicsEGLRegisterImage"] = <intptr_t>__cuGraphicsEGLRegisterImage
 
     global __cuEGLStreamConsumerConnect
-    data["__cuEGLStreamConsumerConnect"] = <_cyb_intptr_t>__cuEGLStreamConsumerConnect
+    data["__cuEGLStreamConsumerConnect"] = <intptr_t>__cuEGLStreamConsumerConnect
 
     global __cuEGLStreamConsumerConnectWithFlags
-    data["__cuEGLStreamConsumerConnectWithFlags"] = <_cyb_intptr_t>__cuEGLStreamConsumerConnectWithFlags
+    data["__cuEGLStreamConsumerConnectWithFlags"] = <intptr_t>__cuEGLStreamConsumerConnectWithFlags
 
     global __cuEGLStreamConsumerDisconnect
-    data["__cuEGLStreamConsumerDisconnect"] = <_cyb_intptr_t>__cuEGLStreamConsumerDisconnect
+    data["__cuEGLStreamConsumerDisconnect"] = <intptr_t>__cuEGLStreamConsumerDisconnect
 
     global __cuEGLStreamConsumerAcquireFrame
-    data["__cuEGLStreamConsumerAcquireFrame"] = <_cyb_intptr_t>__cuEGLStreamConsumerAcquireFrame
+    data["__cuEGLStreamConsumerAcquireFrame"] = <intptr_t>__cuEGLStreamConsumerAcquireFrame
 
     global __cuEGLStreamConsumerReleaseFrame
-    data["__cuEGLStreamConsumerReleaseFrame"] = <_cyb_intptr_t>__cuEGLStreamConsumerReleaseFrame
+    data["__cuEGLStreamConsumerReleaseFrame"] = <intptr_t>__cuEGLStreamConsumerReleaseFrame
 
     global __cuEGLStreamProducerConnect
-    data["__cuEGLStreamProducerConnect"] = <_cyb_intptr_t>__cuEGLStreamProducerConnect
+    data["__cuEGLStreamProducerConnect"] = <intptr_t>__cuEGLStreamProducerConnect
 
     global __cuEGLStreamProducerDisconnect
-    data["__cuEGLStreamProducerDisconnect"] = <_cyb_intptr_t>__cuEGLStreamProducerDisconnect
+    data["__cuEGLStreamProducerDisconnect"] = <intptr_t>__cuEGLStreamProducerDisconnect
 
     global __cuEGLStreamProducerPresentFrame
-    data["__cuEGLStreamProducerPresentFrame"] = <_cyb_intptr_t>__cuEGLStreamProducerPresentFrame
+    data["__cuEGLStreamProducerPresentFrame"] = <intptr_t>__cuEGLStreamProducerPresentFrame
 
     global __cuEGLStreamProducerReturnFrame
-    data["__cuEGLStreamProducerReturnFrame"] = <_cyb_intptr_t>__cuEGLStreamProducerReturnFrame
+    data["__cuEGLStreamProducerReturnFrame"] = <intptr_t>__cuEGLStreamProducerReturnFrame
 
     global __cuGraphicsResourceGetMappedEglFrame
-    data["__cuGraphicsResourceGetMappedEglFrame"] = <_cyb_intptr_t>__cuGraphicsResourceGetMappedEglFrame
+    data["__cuGraphicsResourceGetMappedEglFrame"] = <intptr_t>__cuGraphicsResourceGetMappedEglFrame
 
     global __cuEventCreateFromEGLSync
-    data["__cuEventCreateFromEGLSync"] = <_cyb_intptr_t>__cuEventCreateFromEGLSync
+    data["__cuEventCreateFromEGLSync"] = <intptr_t>__cuEventCreateFromEGLSync
 
     global __cuGraphicsGLRegisterBuffer
-    data["__cuGraphicsGLRegisterBuffer"] = <_cyb_intptr_t>__cuGraphicsGLRegisterBuffer
+    data["__cuGraphicsGLRegisterBuffer"] = <intptr_t>__cuGraphicsGLRegisterBuffer
 
     global __cuGraphicsGLRegisterImage
-    data["__cuGraphicsGLRegisterImage"] = <_cyb_intptr_t>__cuGraphicsGLRegisterImage
+    data["__cuGraphicsGLRegisterImage"] = <intptr_t>__cuGraphicsGLRegisterImage
 
     global __cuGLGetDevices_v2
-    data["__cuGLGetDevices_v2"] = <_cyb_intptr_t>__cuGLGetDevices_v2
+    data["__cuGLGetDevices_v2"] = <intptr_t>__cuGLGetDevices_v2
 
     global __cuGLCtxCreate_v2
-    data["__cuGLCtxCreate_v2"] = <_cyb_intptr_t>__cuGLCtxCreate_v2
+    data["__cuGLCtxCreate_v2"] = <intptr_t>__cuGLCtxCreate_v2
 
     global __cuGLInit
-    data["__cuGLInit"] = <_cyb_intptr_t>__cuGLInit
+    data["__cuGLInit"] = <intptr_t>__cuGLInit
 
     global __cuGLRegisterBufferObject
-    data["__cuGLRegisterBufferObject"] = <_cyb_intptr_t>__cuGLRegisterBufferObject
+    data["__cuGLRegisterBufferObject"] = <intptr_t>__cuGLRegisterBufferObject
 
     global __cuGLMapBufferObject_v2
-    data["__cuGLMapBufferObject_v2"] = <_cyb_intptr_t>__cuGLMapBufferObject_v2
+    data["__cuGLMapBufferObject_v2"] = <intptr_t>__cuGLMapBufferObject_v2
 
     global __cuGLUnmapBufferObject
-    data["__cuGLUnmapBufferObject"] = <_cyb_intptr_t>__cuGLUnmapBufferObject
+    data["__cuGLUnmapBufferObject"] = <intptr_t>__cuGLUnmapBufferObject
 
     global __cuGLUnregisterBufferObject
-    data["__cuGLUnregisterBufferObject"] = <_cyb_intptr_t>__cuGLUnregisterBufferObject
+    data["__cuGLUnregisterBufferObject"] = <intptr_t>__cuGLUnregisterBufferObject
 
     global __cuGLSetBufferObjectMapFlags
-    data["__cuGLSetBufferObjectMapFlags"] = <_cyb_intptr_t>__cuGLSetBufferObjectMapFlags
+    data["__cuGLSetBufferObjectMapFlags"] = <intptr_t>__cuGLSetBufferObjectMapFlags
 
     global __cuGLMapBufferObjectAsync_v2
-    data["__cuGLMapBufferObjectAsync_v2"] = <_cyb_intptr_t>__cuGLMapBufferObjectAsync_v2
+    data["__cuGLMapBufferObjectAsync_v2"] = <intptr_t>__cuGLMapBufferObjectAsync_v2
 
     global __cuGLUnmapBufferObjectAsync
-    data["__cuGLUnmapBufferObjectAsync"] = <_cyb_intptr_t>__cuGLUnmapBufferObjectAsync
+    data["__cuGLUnmapBufferObjectAsync"] = <intptr_t>__cuGLUnmapBufferObjectAsync
 
     global __cuProfilerInitialize
-    data["__cuProfilerInitialize"] = <_cyb_intptr_t>__cuProfilerInitialize
+    data["__cuProfilerInitialize"] = <intptr_t>__cuProfilerInitialize
 
     global __cuProfilerStart
-    data["__cuProfilerStart"] = <_cyb_intptr_t>__cuProfilerStart
+    data["__cuProfilerStart"] = <intptr_t>__cuProfilerStart
 
     global __cuProfilerStop
-    data["__cuProfilerStop"] = <_cyb_intptr_t>__cuProfilerStop
+    data["__cuProfilerStop"] = <intptr_t>__cuProfilerStop
 
     global __cuVDPAUGetDevice
-    data["__cuVDPAUGetDevice"] = <_cyb_intptr_t>__cuVDPAUGetDevice
+    data["__cuVDPAUGetDevice"] = <intptr_t>__cuVDPAUGetDevice
 
     global __cuVDPAUCtxCreate_v2
-    data["__cuVDPAUCtxCreate_v2"] = <_cyb_intptr_t>__cuVDPAUCtxCreate_v2
+    data["__cuVDPAUCtxCreate_v2"] = <intptr_t>__cuVDPAUCtxCreate_v2
 
     global __cuGraphicsVDPAURegisterVideoSurface
-    data["__cuGraphicsVDPAURegisterVideoSurface"] = <_cyb_intptr_t>__cuGraphicsVDPAURegisterVideoSurface
+    data["__cuGraphicsVDPAURegisterVideoSurface"] = <intptr_t>__cuGraphicsVDPAURegisterVideoSurface
 
     global __cuGraphicsVDPAURegisterOutputSurface
-    data["__cuGraphicsVDPAURegisterOutputSurface"] = <_cyb_intptr_t>__cuGraphicsVDPAURegisterOutputSurface
+    data["__cuGraphicsVDPAURegisterOutputSurface"] = <intptr_t>__cuGraphicsVDPAURegisterOutputSurface
 
     global __cuDeviceGetHostAtomicCapabilities
-    data["__cuDeviceGetHostAtomicCapabilities"] = <_cyb_intptr_t>__cuDeviceGetHostAtomicCapabilities
+    data["__cuDeviceGetHostAtomicCapabilities"] = <intptr_t>__cuDeviceGetHostAtomicCapabilities
 
     global __cuCtxGetDevice_v2
-    data["__cuCtxGetDevice_v2"] = <_cyb_intptr_t>__cuCtxGetDevice_v2
+    data["__cuCtxGetDevice_v2"] = <intptr_t>__cuCtxGetDevice_v2
 
     global __cuCtxSynchronize_v2
-    data["__cuCtxSynchronize_v2"] = <_cyb_intptr_t>__cuCtxSynchronize_v2
+    data["__cuCtxSynchronize_v2"] = <intptr_t>__cuCtxSynchronize_v2
 
     global __cuMemcpyBatchAsync_v2
-    data["__cuMemcpyBatchAsync_v2"] = <_cyb_intptr_t>__cuMemcpyBatchAsync_v2
+    data["__cuMemcpyBatchAsync_v2"] = <intptr_t>__cuMemcpyBatchAsync_v2
 
     global __cuMemcpy3DBatchAsync_v2
-    data["__cuMemcpy3DBatchAsync_v2"] = <_cyb_intptr_t>__cuMemcpy3DBatchAsync_v2
+    data["__cuMemcpy3DBatchAsync_v2"] = <intptr_t>__cuMemcpy3DBatchAsync_v2
 
     global __cuMemGetDefaultMemPool
-    data["__cuMemGetDefaultMemPool"] = <_cyb_intptr_t>__cuMemGetDefaultMemPool
+    data["__cuMemGetDefaultMemPool"] = <intptr_t>__cuMemGetDefaultMemPool
 
     global __cuMemGetMemPool
-    data["__cuMemGetMemPool"] = <_cyb_intptr_t>__cuMemGetMemPool
+    data["__cuMemGetMemPool"] = <intptr_t>__cuMemGetMemPool
 
     global __cuMemSetMemPool
-    data["__cuMemSetMemPool"] = <_cyb_intptr_t>__cuMemSetMemPool
+    data["__cuMemSetMemPool"] = <intptr_t>__cuMemSetMemPool
 
     global __cuMemPrefetchBatchAsync
-    data["__cuMemPrefetchBatchAsync"] = <_cyb_intptr_t>__cuMemPrefetchBatchAsync
+    data["__cuMemPrefetchBatchAsync"] = <intptr_t>__cuMemPrefetchBatchAsync
 
     global __cuMemDiscardBatchAsync
-    data["__cuMemDiscardBatchAsync"] = <_cyb_intptr_t>__cuMemDiscardBatchAsync
+    data["__cuMemDiscardBatchAsync"] = <intptr_t>__cuMemDiscardBatchAsync
 
     global __cuMemDiscardAndPrefetchBatchAsync
-    data["__cuMemDiscardAndPrefetchBatchAsync"] = <_cyb_intptr_t>__cuMemDiscardAndPrefetchBatchAsync
+    data["__cuMemDiscardAndPrefetchBatchAsync"] = <intptr_t>__cuMemDiscardAndPrefetchBatchAsync
 
     global __cuDeviceGetP2PAtomicCapabilities
-    data["__cuDeviceGetP2PAtomicCapabilities"] = <_cyb_intptr_t>__cuDeviceGetP2PAtomicCapabilities
+    data["__cuDeviceGetP2PAtomicCapabilities"] = <intptr_t>__cuDeviceGetP2PAtomicCapabilities
 
     global __cuGreenCtxGetId
-    data["__cuGreenCtxGetId"] = <_cyb_intptr_t>__cuGreenCtxGetId
+    data["__cuGreenCtxGetId"] = <intptr_t>__cuGreenCtxGetId
 
     global __cuMulticastBindMem_v2
-    data["__cuMulticastBindMem_v2"] = <_cyb_intptr_t>__cuMulticastBindMem_v2
+    data["__cuMulticastBindMem_v2"] = <intptr_t>__cuMulticastBindMem_v2
 
     global __cuMulticastBindAddr_v2
-    data["__cuMulticastBindAddr_v2"] = <_cyb_intptr_t>__cuMulticastBindAddr_v2
+    data["__cuMulticastBindAddr_v2"] = <intptr_t>__cuMulticastBindAddr_v2
 
     global __cuGraphNodeGetContainingGraph
-    data["__cuGraphNodeGetContainingGraph"] = <_cyb_intptr_t>__cuGraphNodeGetContainingGraph
+    data["__cuGraphNodeGetContainingGraph"] = <intptr_t>__cuGraphNodeGetContainingGraph
 
     global __cuGraphNodeGetLocalId
-    data["__cuGraphNodeGetLocalId"] = <_cyb_intptr_t>__cuGraphNodeGetLocalId
+    data["__cuGraphNodeGetLocalId"] = <intptr_t>__cuGraphNodeGetLocalId
 
     global __cuGraphNodeGetToolsId
-    data["__cuGraphNodeGetToolsId"] = <_cyb_intptr_t>__cuGraphNodeGetToolsId
+    data["__cuGraphNodeGetToolsId"] = <intptr_t>__cuGraphNodeGetToolsId
 
     global __cuGraphGetId
-    data["__cuGraphGetId"] = <_cyb_intptr_t>__cuGraphGetId
+    data["__cuGraphGetId"] = <intptr_t>__cuGraphGetId
 
     global __cuGraphExecGetId
-    data["__cuGraphExecGetId"] = <_cyb_intptr_t>__cuGraphExecGetId
+    data["__cuGraphExecGetId"] = <intptr_t>__cuGraphExecGetId
 
     global __cuDevSmResourceSplit
-    data["__cuDevSmResourceSplit"] = <_cyb_intptr_t>__cuDevSmResourceSplit
+    data["__cuDevSmResourceSplit"] = <intptr_t>__cuDevSmResourceSplit
 
     global __cuStreamGetDevResource
-    data["__cuStreamGetDevResource"] = <_cyb_intptr_t>__cuStreamGetDevResource
+    data["__cuStreamGetDevResource"] = <intptr_t>__cuStreamGetDevResource
 
     global __cuKernelGetParamCount
-    data["__cuKernelGetParamCount"] = <_cyb_intptr_t>__cuKernelGetParamCount
+    data["__cuKernelGetParamCount"] = <intptr_t>__cuKernelGetParamCount
 
     global __cuMemcpyWithAttributesAsync
-    data["__cuMemcpyWithAttributesAsync"] = <_cyb_intptr_t>__cuMemcpyWithAttributesAsync
+    data["__cuMemcpyWithAttributesAsync"] = <intptr_t>__cuMemcpyWithAttributesAsync
 
     global __cuMemcpy3DWithAttributesAsync
-    data["__cuMemcpy3DWithAttributesAsync"] = <_cyb_intptr_t>__cuMemcpy3DWithAttributesAsync
+    data["__cuMemcpy3DWithAttributesAsync"] = <intptr_t>__cuMemcpy3DWithAttributesAsync
 
     global __cuStreamBeginCaptureToCig
-    data["__cuStreamBeginCaptureToCig"] = <_cyb_intptr_t>__cuStreamBeginCaptureToCig
+    data["__cuStreamBeginCaptureToCig"] = <intptr_t>__cuStreamBeginCaptureToCig
 
     global __cuStreamEndCaptureToCig
-    data["__cuStreamEndCaptureToCig"] = <_cyb_intptr_t>__cuStreamEndCaptureToCig
+    data["__cuStreamEndCaptureToCig"] = <intptr_t>__cuStreamEndCaptureToCig
 
     global __cuFuncGetParamCount
-    data["__cuFuncGetParamCount"] = <_cyb_intptr_t>__cuFuncGetParamCount
+    data["__cuFuncGetParamCount"] = <intptr_t>__cuFuncGetParamCount
 
     global __cuLaunchHostFunc_v2
-    data["__cuLaunchHostFunc_v2"] = <_cyb_intptr_t>__cuLaunchHostFunc_v2
+    data["__cuLaunchHostFunc_v2"] = <intptr_t>__cuLaunchHostFunc_v2
 
     global __cuGraphNodeGetParams
-    data["__cuGraphNodeGetParams"] = <_cyb_intptr_t>__cuGraphNodeGetParams
+    data["__cuGraphNodeGetParams"] = <intptr_t>__cuGraphNodeGetParams
 
     global __cuCoredumpRegisterStartCallback
-    data["__cuCoredumpRegisterStartCallback"] = <_cyb_intptr_t>__cuCoredumpRegisterStartCallback
+    data["__cuCoredumpRegisterStartCallback"] = <intptr_t>__cuCoredumpRegisterStartCallback
 
     global __cuCoredumpRegisterCompleteCallback
-    data["__cuCoredumpRegisterCompleteCallback"] = <_cyb_intptr_t>__cuCoredumpRegisterCompleteCallback
+    data["__cuCoredumpRegisterCompleteCallback"] = <intptr_t>__cuCoredumpRegisterCompleteCallback
 
     global __cuCoredumpDeregisterStartCallback
-    data["__cuCoredumpDeregisterStartCallback"] = <_cyb_intptr_t>__cuCoredumpDeregisterStartCallback
+    data["__cuCoredumpDeregisterStartCallback"] = <intptr_t>__cuCoredumpDeregisterStartCallback
 
     global __cuCoredumpDeregisterCompleteCallback
-    data["__cuCoredumpDeregisterCompleteCallback"] = <_cyb_intptr_t>__cuCoredumpDeregisterCompleteCallback
+    data["__cuCoredumpDeregisterCompleteCallback"] = <intptr_t>__cuCoredumpDeregisterCompleteCallback
 
     global __cuLogicalEndpointIdReserve
-    data["__cuLogicalEndpointIdReserve"] = <_cyb_intptr_t>__cuLogicalEndpointIdReserve
+    data["__cuLogicalEndpointIdReserve"] = <intptr_t>__cuLogicalEndpointIdReserve
 
     global __cuLogicalEndpointIdRelease
-    data["__cuLogicalEndpointIdRelease"] = <_cyb_intptr_t>__cuLogicalEndpointIdRelease
+    data["__cuLogicalEndpointIdRelease"] = <intptr_t>__cuLogicalEndpointIdRelease
 
     global __cuLogicalEndpointCreate
-    data["__cuLogicalEndpointCreate"] = <_cyb_intptr_t>__cuLogicalEndpointCreate
+    data["__cuLogicalEndpointCreate"] = <intptr_t>__cuLogicalEndpointCreate
 
     global __cuLogicalEndpointAddDevice
-    data["__cuLogicalEndpointAddDevice"] = <_cyb_intptr_t>__cuLogicalEndpointAddDevice
+    data["__cuLogicalEndpointAddDevice"] = <intptr_t>__cuLogicalEndpointAddDevice
 
     global __cuLogicalEndpointDestroy
-    data["__cuLogicalEndpointDestroy"] = <_cyb_intptr_t>__cuLogicalEndpointDestroy
+    data["__cuLogicalEndpointDestroy"] = <intptr_t>__cuLogicalEndpointDestroy
 
     global __cuLogicalEndpointBindAddr
-    data["__cuLogicalEndpointBindAddr"] = <_cyb_intptr_t>__cuLogicalEndpointBindAddr
+    data["__cuLogicalEndpointBindAddr"] = <intptr_t>__cuLogicalEndpointBindAddr
 
     global __cuLogicalEndpointBindMem
-    data["__cuLogicalEndpointBindMem"] = <_cyb_intptr_t>__cuLogicalEndpointBindMem
+    data["__cuLogicalEndpointBindMem"] = <intptr_t>__cuLogicalEndpointBindMem
 
     global __cuLogicalEndpointUnbind
-    data["__cuLogicalEndpointUnbind"] = <_cyb_intptr_t>__cuLogicalEndpointUnbind
+    data["__cuLogicalEndpointUnbind"] = <intptr_t>__cuLogicalEndpointUnbind
 
     global __cuLogicalEndpointExport
-    data["__cuLogicalEndpointExport"] = <_cyb_intptr_t>__cuLogicalEndpointExport
+    data["__cuLogicalEndpointExport"] = <intptr_t>__cuLogicalEndpointExport
 
     global __cuLogicalEndpointImport
-    data["__cuLogicalEndpointImport"] = <_cyb_intptr_t>__cuLogicalEndpointImport
+    data["__cuLogicalEndpointImport"] = <intptr_t>__cuLogicalEndpointImport
 
     global __cuLogicalEndpointGetLimits
-    data["__cuLogicalEndpointGetLimits"] = <_cyb_intptr_t>__cuLogicalEndpointGetLimits
+    data["__cuLogicalEndpointGetLimits"] = <intptr_t>__cuLogicalEndpointGetLimits
 
     global __cuLogicalEndpointQuery
-    data["__cuLogicalEndpointQuery"] = <_cyb_intptr_t>__cuLogicalEndpointQuery
+    data["__cuLogicalEndpointQuery"] = <intptr_t>__cuLogicalEndpointQuery
 
     global __cuStreamBeginRecaptureToGraph
-    data["__cuStreamBeginRecaptureToGraph"] = <_cyb_intptr_t>__cuStreamBeginRecaptureToGraph
+    data["__cuStreamBeginRecaptureToGraph"] = <intptr_t>__cuStreamBeginRecaptureToGraph
 
     global __cuDeviceGetFabricClusterUuid
-    data["__cuDeviceGetFabricClusterUuid"] = <_cyb_intptr_t>__cuDeviceGetFabricClusterUuid
+    data["__cuDeviceGetFabricClusterUuid"] = <intptr_t>__cuDeviceGetFabricClusterUuid
 
     global __cuDeviceGetCliqueCount
-    data["__cuDeviceGetCliqueCount"] = <_cyb_intptr_t>__cuDeviceGetCliqueCount
+    data["__cuDeviceGetCliqueCount"] = <intptr_t>__cuDeviceGetCliqueCount
 
     global __cuDeviceGetCliqueInfo
-    data["__cuDeviceGetCliqueInfo"] = <_cyb_intptr_t>__cuDeviceGetCliqueInfo
+    data["__cuDeviceGetCliqueInfo"] = <intptr_t>__cuDeviceGetCliqueInfo
 
     global __cuMemGetLocationInfo
-    data["__cuMemGetLocationInfo"] = <_cyb_intptr_t>__cuMemGetLocationInfo
+    data["__cuMemGetLocationInfo"] = <intptr_t>__cuMemGetLocationInfo
 
     global __cuGraphAddNode_v3
-    data["__cuGraphAddNode_v3"] = <_cyb_intptr_t>__cuGraphAddNode_v3
+    data["__cuGraphAddNode_v3"] = <intptr_t>__cuGraphAddNode_v3
 
     global __cuGraphNodeSetParams_v2
-    data["__cuGraphNodeSetParams_v2"] = <_cyb_intptr_t>__cuGraphNodeSetParams_v2
+    data["__cuGraphNodeSetParams_v2"] = <intptr_t>__cuGraphNodeSetParams_v2
 
     global __cuCheckpointOperationComplete
-    data["__cuCheckpointOperationComplete"] = <_cyb_intptr_t>__cuCheckpointOperationComplete
+    data["__cuCheckpointOperationComplete"] = <intptr_t>__cuCheckpointOperationComplete
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvfatbin.pxd b/cuda_bindings/cuda/bindings/_internal/nvfatbin.pxd
index d8f087af7fb..4eadeab01c8 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvfatbin.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/nvfatbin.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.4.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.4.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=4176ab61d2c088c30ef453fdc5aee9f5f66e0cf76732826ab900fd211c143e14
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=4fc8b05be8a1a25737a1940a53339f6af3b7a1d4e513558109aaac48b3222681
 from ..cynvfatbin cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvfatbin_linux.pyx b/cuda_bindings/cuda/bindings/_internal/nvfatbin_linux.pyx
index 09cefc0c8f9..937878b5a15 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvfatbin_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvfatbin_linux.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.4.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=5351e00f0cca82ccf833f27a4729a538b46110830393e49526539505d0fbe1e9
+# This code was automatically generated across versions from 12.4.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=6b42b70b945f3898a53f87261fcdb5a688cb9ab93476427781e1838a3ffffaf9
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,7 @@ cdef extern from "<dlfcn.h>":
     void* _cyb_dlsym "dlsym"(void*, const char*) nogil
     const void * _cyb_RTLD_DEFAULT "RTLD_DEFAULT"
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport intptr_t
 
 import threading as _cyb_threading
 
@@ -186,40 +185,40 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvfatbin()
     cdef dict data = {}
     global __nvFatbinGetErrorString
-    data["__nvFatbinGetErrorString"] = <_cyb_intptr_t>__nvFatbinGetErrorString
+    data["__nvFatbinGetErrorString"] = <intptr_t>__nvFatbinGetErrorString
 
     global __nvFatbinCreate
-    data["__nvFatbinCreate"] = <_cyb_intptr_t>__nvFatbinCreate
+    data["__nvFatbinCreate"] = <intptr_t>__nvFatbinCreate
 
     global __nvFatbinDestroy
-    data["__nvFatbinDestroy"] = <_cyb_intptr_t>__nvFatbinDestroy
+    data["__nvFatbinDestroy"] = <intptr_t>__nvFatbinDestroy
 
     global __nvFatbinAddPTX
-    data["__nvFatbinAddPTX"] = <_cyb_intptr_t>__nvFatbinAddPTX
+    data["__nvFatbinAddPTX"] = <intptr_t>__nvFatbinAddPTX
 
     global __nvFatbinAddCubin
-    data["__nvFatbinAddCubin"] = <_cyb_intptr_t>__nvFatbinAddCubin
+    data["__nvFatbinAddCubin"] = <intptr_t>__nvFatbinAddCubin
 
     global __nvFatbinAddLTOIR
-    data["__nvFatbinAddLTOIR"] = <_cyb_intptr_t>__nvFatbinAddLTOIR
+    data["__nvFatbinAddLTOIR"] = <intptr_t>__nvFatbinAddLTOIR
 
     global __nvFatbinSize
-    data["__nvFatbinSize"] = <_cyb_intptr_t>__nvFatbinSize
+    data["__nvFatbinSize"] = <intptr_t>__nvFatbinSize
 
     global __nvFatbinGet
-    data["__nvFatbinGet"] = <_cyb_intptr_t>__nvFatbinGet
+    data["__nvFatbinGet"] = <intptr_t>__nvFatbinGet
 
     global __nvFatbinVersion
-    data["__nvFatbinVersion"] = <_cyb_intptr_t>__nvFatbinVersion
+    data["__nvFatbinVersion"] = <intptr_t>__nvFatbinVersion
 
     global __nvFatbinAddIndex
-    data["__nvFatbinAddIndex"] = <_cyb_intptr_t>__nvFatbinAddIndex
+    data["__nvFatbinAddIndex"] = <intptr_t>__nvFatbinAddIndex
 
     global __nvFatbinAddReloc
-    data["__nvFatbinAddReloc"] = <_cyb_intptr_t>__nvFatbinAddReloc
+    data["__nvFatbinAddReloc"] = <intptr_t>__nvFatbinAddReloc
 
     global __nvFatbinAddTileIR
-    data["__nvFatbinAddTileIR"] = <_cyb_intptr_t>__nvFatbinAddTileIR
+    data["__nvFatbinAddTileIR"] = <intptr_t>__nvFatbinAddTileIR
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvfatbin_windows.pyx b/cuda_bindings/cuda/bindings/_internal/nvfatbin_windows.pyx
index e0abd202bbe..03453560c4e 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvfatbin_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvfatbin_windows.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.4.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=91a09cd316df7848a0f2c3fba5e516a6e94749e3259b0fbd6f57e9b9873fce55
+# This code was automatically generated across versions from 12.4.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=4f4711d1bf4600663e9a7958c75666ad7c7785248afdef1c701d58c78ce81bfe
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,10 @@ cdef extern from "<windows.h>":
     ctypedef void* HMODULE
     void* _cyb_GetProcAddress "GetProcAddress"(HMODULE, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uintptr_t,
+)
 
 import threading as _cyb_threading
 
@@ -138,40 +140,40 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvfatbin()
     cdef dict data = {}
     global __nvFatbinGetErrorString
-    data["__nvFatbinGetErrorString"] = <_cyb_intptr_t>__nvFatbinGetErrorString
+    data["__nvFatbinGetErrorString"] = <intptr_t>__nvFatbinGetErrorString
 
     global __nvFatbinCreate
-    data["__nvFatbinCreate"] = <_cyb_intptr_t>__nvFatbinCreate
+    data["__nvFatbinCreate"] = <intptr_t>__nvFatbinCreate
 
     global __nvFatbinDestroy
-    data["__nvFatbinDestroy"] = <_cyb_intptr_t>__nvFatbinDestroy
+    data["__nvFatbinDestroy"] = <intptr_t>__nvFatbinDestroy
 
     global __nvFatbinAddPTX
-    data["__nvFatbinAddPTX"] = <_cyb_intptr_t>__nvFatbinAddPTX
+    data["__nvFatbinAddPTX"] = <intptr_t>__nvFatbinAddPTX
 
     global __nvFatbinAddCubin
-    data["__nvFatbinAddCubin"] = <_cyb_intptr_t>__nvFatbinAddCubin
+    data["__nvFatbinAddCubin"] = <intptr_t>__nvFatbinAddCubin
 
     global __nvFatbinAddLTOIR
-    data["__nvFatbinAddLTOIR"] = <_cyb_intptr_t>__nvFatbinAddLTOIR
+    data["__nvFatbinAddLTOIR"] = <intptr_t>__nvFatbinAddLTOIR
 
     global __nvFatbinSize
-    data["__nvFatbinSize"] = <_cyb_intptr_t>__nvFatbinSize
+    data["__nvFatbinSize"] = <intptr_t>__nvFatbinSize
 
     global __nvFatbinGet
-    data["__nvFatbinGet"] = <_cyb_intptr_t>__nvFatbinGet
+    data["__nvFatbinGet"] = <intptr_t>__nvFatbinGet
 
     global __nvFatbinVersion
-    data["__nvFatbinVersion"] = <_cyb_intptr_t>__nvFatbinVersion
+    data["__nvFatbinVersion"] = <intptr_t>__nvFatbinVersion
 
     global __nvFatbinAddIndex
-    data["__nvFatbinAddIndex"] = <_cyb_intptr_t>__nvFatbinAddIndex
+    data["__nvFatbinAddIndex"] = <intptr_t>__nvFatbinAddIndex
 
     global __nvFatbinAddReloc
-    data["__nvFatbinAddReloc"] = <_cyb_intptr_t>__nvFatbinAddReloc
+    data["__nvFatbinAddReloc"] = <intptr_t>__nvFatbinAddReloc
 
     global __nvFatbinAddTileIR
-    data["__nvFatbinAddTileIR"] = <_cyb_intptr_t>__nvFatbinAddTileIR
+    data["__nvFatbinAddTileIR"] = <intptr_t>__nvFatbinAddTileIR
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvjitlink.pxd b/cuda_bindings/cuda/bindings/_internal/nvjitlink.pxd
index 21d527a3c16..bb1419ae946 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvjitlink.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/nvjitlink.pxd
@@ -2,10 +2,17 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f54caf5830f0b76772ca6e06487bc94eef354c725f6e6f3c908b993860ba6787
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport uint32_t
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=05522f152eb6cf5e4b8fc2c0bd25362366a36c9d3c976321ba0155ba330c6209
 from ..cynvjitlink cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx b/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx
index 7458f5b88e8..4c21693caf7 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvjitlink_linux.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=539829faeb71eb1d20a60f5e4ad835826eee873b96694b6db8809b9b904bc7b8
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a286ec6ed7fcdd0d82d6624d68c700cc3678e1e26f3ba1243df518cdeea5a992
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,10 @@ cdef extern from "<dlfcn.h>":
     void* _cyb_dlsym "dlsym"(void*, const char*) nogil
     const void * _cyb_RTLD_DEFAULT "RTLD_DEFAULT"
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+)
 
 import threading as _cyb_threading
 
@@ -218,52 +220,52 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvjitlink()
     cdef dict data = {}
     global __nvJitLinkCreate
-    data["__nvJitLinkCreate"] = <_cyb_intptr_t>__nvJitLinkCreate
+    data["__nvJitLinkCreate"] = <intptr_t>__nvJitLinkCreate
 
     global __nvJitLinkDestroy
-    data["__nvJitLinkDestroy"] = <_cyb_intptr_t>__nvJitLinkDestroy
+    data["__nvJitLinkDestroy"] = <intptr_t>__nvJitLinkDestroy
 
     global __nvJitLinkAddData
-    data["__nvJitLinkAddData"] = <_cyb_intptr_t>__nvJitLinkAddData
+    data["__nvJitLinkAddData"] = <intptr_t>__nvJitLinkAddData
 
     global __nvJitLinkAddFile
-    data["__nvJitLinkAddFile"] = <_cyb_intptr_t>__nvJitLinkAddFile
+    data["__nvJitLinkAddFile"] = <intptr_t>__nvJitLinkAddFile
 
     global __nvJitLinkComplete
-    data["__nvJitLinkComplete"] = <_cyb_intptr_t>__nvJitLinkComplete
+    data["__nvJitLinkComplete"] = <intptr_t>__nvJitLinkComplete
 
     global __nvJitLinkGetLinkedCubinSize
-    data["__nvJitLinkGetLinkedCubinSize"] = <_cyb_intptr_t>__nvJitLinkGetLinkedCubinSize
+    data["__nvJitLinkGetLinkedCubinSize"] = <intptr_t>__nvJitLinkGetLinkedCubinSize
 
     global __nvJitLinkGetLinkedCubin
-    data["__nvJitLinkGetLinkedCubin"] = <_cyb_intptr_t>__nvJitLinkGetLinkedCubin
+    data["__nvJitLinkGetLinkedCubin"] = <intptr_t>__nvJitLinkGetLinkedCubin
 
     global __nvJitLinkGetLinkedPtxSize
-    data["__nvJitLinkGetLinkedPtxSize"] = <_cyb_intptr_t>__nvJitLinkGetLinkedPtxSize
+    data["__nvJitLinkGetLinkedPtxSize"] = <intptr_t>__nvJitLinkGetLinkedPtxSize
 
     global __nvJitLinkGetLinkedPtx
-    data["__nvJitLinkGetLinkedPtx"] = <_cyb_intptr_t>__nvJitLinkGetLinkedPtx
+    data["__nvJitLinkGetLinkedPtx"] = <intptr_t>__nvJitLinkGetLinkedPtx
 
     global __nvJitLinkGetErrorLogSize
-    data["__nvJitLinkGetErrorLogSize"] = <_cyb_intptr_t>__nvJitLinkGetErrorLogSize
+    data["__nvJitLinkGetErrorLogSize"] = <intptr_t>__nvJitLinkGetErrorLogSize
 
     global __nvJitLinkGetErrorLog
-    data["__nvJitLinkGetErrorLog"] = <_cyb_intptr_t>__nvJitLinkGetErrorLog
+    data["__nvJitLinkGetErrorLog"] = <intptr_t>__nvJitLinkGetErrorLog
 
     global __nvJitLinkGetInfoLogSize
-    data["__nvJitLinkGetInfoLogSize"] = <_cyb_intptr_t>__nvJitLinkGetInfoLogSize
+    data["__nvJitLinkGetInfoLogSize"] = <intptr_t>__nvJitLinkGetInfoLogSize
 
     global __nvJitLinkGetInfoLog
-    data["__nvJitLinkGetInfoLog"] = <_cyb_intptr_t>__nvJitLinkGetInfoLog
+    data["__nvJitLinkGetInfoLog"] = <intptr_t>__nvJitLinkGetInfoLog
 
     global __nvJitLinkVersion
-    data["__nvJitLinkVersion"] = <_cyb_intptr_t>__nvJitLinkVersion
+    data["__nvJitLinkVersion"] = <intptr_t>__nvJitLinkVersion
 
     global __nvJitLinkGetLinkedLTOIRSize
-    data["__nvJitLinkGetLinkedLTOIRSize"] = <_cyb_intptr_t>__nvJitLinkGetLinkedLTOIRSize
+    data["__nvJitLinkGetLinkedLTOIRSize"] = <intptr_t>__nvJitLinkGetLinkedLTOIRSize
 
     global __nvJitLinkGetLinkedLTOIR
-    data["__nvJitLinkGetLinkedLTOIR"] = <_cyb_intptr_t>__nvJitLinkGetLinkedLTOIR
+    data["__nvJitLinkGetLinkedLTOIR"] = <intptr_t>__nvJitLinkGetLinkedLTOIR
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx b/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx
index 9e279570c8d..9ce2fc111be 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvjitlink_windows.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=d90e50b8ffd6f1d66aa26e5a0d38b9e3a3c7a801114de8feabe626d622d50f81
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=eef6c33c425f24828307c7fc62c45dcdd8b98e5dd47be467709f64eadfd432b2
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,11 @@ cdef extern from "<windows.h>":
     ctypedef void* HMODULE
     void* _cyb_GetProcAddress "GetProcAddress"(HMODULE, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+    uintptr_t,
+)
 
 import threading as _cyb_threading
 
@@ -154,52 +157,52 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvjitlink()
     cdef dict data = {}
     global __nvJitLinkCreate
-    data["__nvJitLinkCreate"] = <_cyb_intptr_t>__nvJitLinkCreate
+    data["__nvJitLinkCreate"] = <intptr_t>__nvJitLinkCreate
 
     global __nvJitLinkDestroy
-    data["__nvJitLinkDestroy"] = <_cyb_intptr_t>__nvJitLinkDestroy
+    data["__nvJitLinkDestroy"] = <intptr_t>__nvJitLinkDestroy
 
     global __nvJitLinkAddData
-    data["__nvJitLinkAddData"] = <_cyb_intptr_t>__nvJitLinkAddData
+    data["__nvJitLinkAddData"] = <intptr_t>__nvJitLinkAddData
 
     global __nvJitLinkAddFile
-    data["__nvJitLinkAddFile"] = <_cyb_intptr_t>__nvJitLinkAddFile
+    data["__nvJitLinkAddFile"] = <intptr_t>__nvJitLinkAddFile
 
     global __nvJitLinkComplete
-    data["__nvJitLinkComplete"] = <_cyb_intptr_t>__nvJitLinkComplete
+    data["__nvJitLinkComplete"] = <intptr_t>__nvJitLinkComplete
 
     global __nvJitLinkGetLinkedCubinSize
-    data["__nvJitLinkGetLinkedCubinSize"] = <_cyb_intptr_t>__nvJitLinkGetLinkedCubinSize
+    data["__nvJitLinkGetLinkedCubinSize"] = <intptr_t>__nvJitLinkGetLinkedCubinSize
 
     global __nvJitLinkGetLinkedCubin
-    data["__nvJitLinkGetLinkedCubin"] = <_cyb_intptr_t>__nvJitLinkGetLinkedCubin
+    data["__nvJitLinkGetLinkedCubin"] = <intptr_t>__nvJitLinkGetLinkedCubin
 
     global __nvJitLinkGetLinkedPtxSize
-    data["__nvJitLinkGetLinkedPtxSize"] = <_cyb_intptr_t>__nvJitLinkGetLinkedPtxSize
+    data["__nvJitLinkGetLinkedPtxSize"] = <intptr_t>__nvJitLinkGetLinkedPtxSize
 
     global __nvJitLinkGetLinkedPtx
-    data["__nvJitLinkGetLinkedPtx"] = <_cyb_intptr_t>__nvJitLinkGetLinkedPtx
+    data["__nvJitLinkGetLinkedPtx"] = <intptr_t>__nvJitLinkGetLinkedPtx
 
     global __nvJitLinkGetErrorLogSize
-    data["__nvJitLinkGetErrorLogSize"] = <_cyb_intptr_t>__nvJitLinkGetErrorLogSize
+    data["__nvJitLinkGetErrorLogSize"] = <intptr_t>__nvJitLinkGetErrorLogSize
 
     global __nvJitLinkGetErrorLog
-    data["__nvJitLinkGetErrorLog"] = <_cyb_intptr_t>__nvJitLinkGetErrorLog
+    data["__nvJitLinkGetErrorLog"] = <intptr_t>__nvJitLinkGetErrorLog
 
     global __nvJitLinkGetInfoLogSize
-    data["__nvJitLinkGetInfoLogSize"] = <_cyb_intptr_t>__nvJitLinkGetInfoLogSize
+    data["__nvJitLinkGetInfoLogSize"] = <intptr_t>__nvJitLinkGetInfoLogSize
 
     global __nvJitLinkGetInfoLog
-    data["__nvJitLinkGetInfoLog"] = <_cyb_intptr_t>__nvJitLinkGetInfoLog
+    data["__nvJitLinkGetInfoLog"] = <intptr_t>__nvJitLinkGetInfoLog
 
     global __nvJitLinkVersion
-    data["__nvJitLinkVersion"] = <_cyb_intptr_t>__nvJitLinkVersion
+    data["__nvJitLinkVersion"] = <intptr_t>__nvJitLinkVersion
 
     global __nvJitLinkGetLinkedLTOIRSize
-    data["__nvJitLinkGetLinkedLTOIRSize"] = <_cyb_intptr_t>__nvJitLinkGetLinkedLTOIRSize
+    data["__nvJitLinkGetLinkedLTOIRSize"] = <intptr_t>__nvJitLinkGetLinkedLTOIRSize
 
     global __nvJitLinkGetLinkedLTOIR
-    data["__nvJitLinkGetLinkedLTOIR"] = <_cyb_intptr_t>__nvJitLinkGetLinkedLTOIR
+    data["__nvJitLinkGetLinkedLTOIR"] = <intptr_t>__nvJitLinkGetLinkedLTOIR
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvml.pxd b/cuda_bindings/cuda/bindings/_internal/nvml.pxd
index d8addb4612e..11504e0f41d 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvml.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/nvml.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=11f3b1735ed60584030439236109205020cc620c548d63cce0c15615e6334e4a
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=25a9a64fc7aed96ba4ab9be2bd7b2c8c2b464e7d8fb7dab7b2dd85b32da0efe3
 from ..cynvml cimport *
 
 
@@ -377,9 +376,9 @@ cdef nvmlReturn_t _nvmlDevicePerfMetricsGetSamples_v1(nvmlDevice_t device, nvmlP
 cdef nvmlReturn_t _nvmlDeviceSetNvlinkBwModeAsync_v1(nvmlDevice_t device, nvmlNvlinkSetBwModeAsync_v1_t* setBwModeAsync) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
 cdef nvmlReturn_t _nvmlDeviceGetNvLinkTelemetrySamples_v1(nvmlDevice_t device, nvmlNvlinkTelemetrySamples_v1_t* samples) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
 cdef nvmlReturn_t _nvmlEventSetRegisterGpuOperationalEvents_v1(nvmlEventSet_t eventSet, const nvmlGpuOperationalEventConfig_v1_t* config) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t _nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventData_v2_t* data, unsigned int timeoutms) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t _nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, unsigned int* count) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t _nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, unsigned int index, nvmlOperationalEventContextInfo_v1_t* info) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t _nvmlEventSetGetContextData_v1(nvmlEventSet_t set, unsigned int index, void* data, unsigned int* dataSize) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t _nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, unsigned int index, nvmlGpuOperationalEventContextLegacyXid_v1_t* xid) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t _nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventSetWait_v3_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t _nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, nvmlEventSetGetContextCount_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t _nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, nvmlEventSetGetContextInfo_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t _nvmlEventSetGetContextData_v1(nvmlEventSet_t set, nvmlEventSetGetContextData_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t _nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
 cdef nvmlReturn_t _nvmlDeviceGetBankRemapperStatus_v1(nvmlDevice_t device, nvmlEccBankRemapperStatus_v1_t* pBankRemapperStatus) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
diff --git a/cuda_bindings/cuda/bindings/_internal/nvml_linux.pyx b/cuda_bindings/cuda/bindings/_internal/nvml_linux.pyx
index c61714f77dd..ab251a57fe1 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvml_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvml_linux.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=735d5128e04ed65d3517e4315b5c05f9f1731c2f4dd00460925bb30f7090f6f5
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=77c516adfddaab32e14f7d0bf80b78c33d928198af0be5ea18ec7b880c9c09c9
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,7 @@ cdef extern from "<dlfcn.h>":
     void* _cyb_dlsym "dlsym"(void*, const char*) nogil
     const void * _cyb_RTLD_DEFAULT "RTLD_DEFAULT"
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport intptr_t
 
 import threading as _cyb_threading
 
@@ -3050,1114 +3049,1114 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvml()
     cdef dict data = {}
     global __nvmlInit_v2
-    data["__nvmlInit_v2"] = <_cyb_intptr_t>__nvmlInit_v2
+    data["__nvmlInit_v2"] = <intptr_t>__nvmlInit_v2
 
     global __nvmlInitWithFlags
-    data["__nvmlInitWithFlags"] = <_cyb_intptr_t>__nvmlInitWithFlags
+    data["__nvmlInitWithFlags"] = <intptr_t>__nvmlInitWithFlags
 
     global __nvmlShutdown
-    data["__nvmlShutdown"] = <_cyb_intptr_t>__nvmlShutdown
+    data["__nvmlShutdown"] = <intptr_t>__nvmlShutdown
 
     global __nvmlErrorString
-    data["__nvmlErrorString"] = <_cyb_intptr_t>__nvmlErrorString
+    data["__nvmlErrorString"] = <intptr_t>__nvmlErrorString
 
     global __nvmlSystemGetDriverVersion
-    data["__nvmlSystemGetDriverVersion"] = <_cyb_intptr_t>__nvmlSystemGetDriverVersion
+    data["__nvmlSystemGetDriverVersion"] = <intptr_t>__nvmlSystemGetDriverVersion
 
     global __nvmlSystemGetNVMLVersion
-    data["__nvmlSystemGetNVMLVersion"] = <_cyb_intptr_t>__nvmlSystemGetNVMLVersion
+    data["__nvmlSystemGetNVMLVersion"] = <intptr_t>__nvmlSystemGetNVMLVersion
 
     global __nvmlSystemGetCudaDriverVersion
-    data["__nvmlSystemGetCudaDriverVersion"] = <_cyb_intptr_t>__nvmlSystemGetCudaDriverVersion
+    data["__nvmlSystemGetCudaDriverVersion"] = <intptr_t>__nvmlSystemGetCudaDriverVersion
 
     global __nvmlSystemGetCudaDriverVersion_v2
-    data["__nvmlSystemGetCudaDriverVersion_v2"] = <_cyb_intptr_t>__nvmlSystemGetCudaDriverVersion_v2
+    data["__nvmlSystemGetCudaDriverVersion_v2"] = <intptr_t>__nvmlSystemGetCudaDriverVersion_v2
 
     global __nvmlSystemGetProcessName
-    data["__nvmlSystemGetProcessName"] = <_cyb_intptr_t>__nvmlSystemGetProcessName
+    data["__nvmlSystemGetProcessName"] = <intptr_t>__nvmlSystemGetProcessName
 
     global __nvmlSystemGetHicVersion
-    data["__nvmlSystemGetHicVersion"] = <_cyb_intptr_t>__nvmlSystemGetHicVersion
+    data["__nvmlSystemGetHicVersion"] = <intptr_t>__nvmlSystemGetHicVersion
 
     global __nvmlSystemGetTopologyGpuSet
-    data["__nvmlSystemGetTopologyGpuSet"] = <_cyb_intptr_t>__nvmlSystemGetTopologyGpuSet
+    data["__nvmlSystemGetTopologyGpuSet"] = <intptr_t>__nvmlSystemGetTopologyGpuSet
 
     global __nvmlSystemGetDriverBranch
-    data["__nvmlSystemGetDriverBranch"] = <_cyb_intptr_t>__nvmlSystemGetDriverBranch
+    data["__nvmlSystemGetDriverBranch"] = <intptr_t>__nvmlSystemGetDriverBranch
 
     global __nvmlUnitGetCount
-    data["__nvmlUnitGetCount"] = <_cyb_intptr_t>__nvmlUnitGetCount
+    data["__nvmlUnitGetCount"] = <intptr_t>__nvmlUnitGetCount
 
     global __nvmlUnitGetHandleByIndex
-    data["__nvmlUnitGetHandleByIndex"] = <_cyb_intptr_t>__nvmlUnitGetHandleByIndex
+    data["__nvmlUnitGetHandleByIndex"] = <intptr_t>__nvmlUnitGetHandleByIndex
 
     global __nvmlUnitGetUnitInfo
-    data["__nvmlUnitGetUnitInfo"] = <_cyb_intptr_t>__nvmlUnitGetUnitInfo
+    data["__nvmlUnitGetUnitInfo"] = <intptr_t>__nvmlUnitGetUnitInfo
 
     global __nvmlUnitGetLedState
-    data["__nvmlUnitGetLedState"] = <_cyb_intptr_t>__nvmlUnitGetLedState
+    data["__nvmlUnitGetLedState"] = <intptr_t>__nvmlUnitGetLedState
 
     global __nvmlUnitGetPsuInfo
-    data["__nvmlUnitGetPsuInfo"] = <_cyb_intptr_t>__nvmlUnitGetPsuInfo
+    data["__nvmlUnitGetPsuInfo"] = <intptr_t>__nvmlUnitGetPsuInfo
 
     global __nvmlUnitGetTemperature
-    data["__nvmlUnitGetTemperature"] = <_cyb_intptr_t>__nvmlUnitGetTemperature
+    data["__nvmlUnitGetTemperature"] = <intptr_t>__nvmlUnitGetTemperature
 
     global __nvmlUnitGetFanSpeedInfo
-    data["__nvmlUnitGetFanSpeedInfo"] = <_cyb_intptr_t>__nvmlUnitGetFanSpeedInfo
+    data["__nvmlUnitGetFanSpeedInfo"] = <intptr_t>__nvmlUnitGetFanSpeedInfo
 
     global __nvmlUnitGetDevices
-    data["__nvmlUnitGetDevices"] = <_cyb_intptr_t>__nvmlUnitGetDevices
+    data["__nvmlUnitGetDevices"] = <intptr_t>__nvmlUnitGetDevices
 
     global __nvmlDeviceGetCount_v2
-    data["__nvmlDeviceGetCount_v2"] = <_cyb_intptr_t>__nvmlDeviceGetCount_v2
+    data["__nvmlDeviceGetCount_v2"] = <intptr_t>__nvmlDeviceGetCount_v2
 
     global __nvmlDeviceGetAttributes_v2
-    data["__nvmlDeviceGetAttributes_v2"] = <_cyb_intptr_t>__nvmlDeviceGetAttributes_v2
+    data["__nvmlDeviceGetAttributes_v2"] = <intptr_t>__nvmlDeviceGetAttributes_v2
 
     global __nvmlDeviceGetHandleByIndex_v2
-    data["__nvmlDeviceGetHandleByIndex_v2"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByIndex_v2
+    data["__nvmlDeviceGetHandleByIndex_v2"] = <intptr_t>__nvmlDeviceGetHandleByIndex_v2
 
     global __nvmlDeviceGetHandleBySerial
-    data["__nvmlDeviceGetHandleBySerial"] = <_cyb_intptr_t>__nvmlDeviceGetHandleBySerial
+    data["__nvmlDeviceGetHandleBySerial"] = <intptr_t>__nvmlDeviceGetHandleBySerial
 
     global __nvmlDeviceGetHandleByUUID
-    data["__nvmlDeviceGetHandleByUUID"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByUUID
+    data["__nvmlDeviceGetHandleByUUID"] = <intptr_t>__nvmlDeviceGetHandleByUUID
 
     global __nvmlDeviceGetHandleByUUIDV
-    data["__nvmlDeviceGetHandleByUUIDV"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByUUIDV
+    data["__nvmlDeviceGetHandleByUUIDV"] = <intptr_t>__nvmlDeviceGetHandleByUUIDV
 
     global __nvmlDeviceGetHandleByPciBusId_v2
-    data["__nvmlDeviceGetHandleByPciBusId_v2"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByPciBusId_v2
+    data["__nvmlDeviceGetHandleByPciBusId_v2"] = <intptr_t>__nvmlDeviceGetHandleByPciBusId_v2
 
     global __nvmlDeviceGetName
-    data["__nvmlDeviceGetName"] = <_cyb_intptr_t>__nvmlDeviceGetName
+    data["__nvmlDeviceGetName"] = <intptr_t>__nvmlDeviceGetName
 
     global __nvmlDeviceGetBrand
-    data["__nvmlDeviceGetBrand"] = <_cyb_intptr_t>__nvmlDeviceGetBrand
+    data["__nvmlDeviceGetBrand"] = <intptr_t>__nvmlDeviceGetBrand
 
     global __nvmlDeviceGetIndex
-    data["__nvmlDeviceGetIndex"] = <_cyb_intptr_t>__nvmlDeviceGetIndex
+    data["__nvmlDeviceGetIndex"] = <intptr_t>__nvmlDeviceGetIndex
 
     global __nvmlDeviceGetSerial
-    data["__nvmlDeviceGetSerial"] = <_cyb_intptr_t>__nvmlDeviceGetSerial
+    data["__nvmlDeviceGetSerial"] = <intptr_t>__nvmlDeviceGetSerial
 
     global __nvmlDeviceGetModuleId
-    data["__nvmlDeviceGetModuleId"] = <_cyb_intptr_t>__nvmlDeviceGetModuleId
+    data["__nvmlDeviceGetModuleId"] = <intptr_t>__nvmlDeviceGetModuleId
 
     global __nvmlDeviceGetC2cModeInfoV
-    data["__nvmlDeviceGetC2cModeInfoV"] = <_cyb_intptr_t>__nvmlDeviceGetC2cModeInfoV
+    data["__nvmlDeviceGetC2cModeInfoV"] = <intptr_t>__nvmlDeviceGetC2cModeInfoV
 
     global __nvmlDeviceGetMemoryAffinity
-    data["__nvmlDeviceGetMemoryAffinity"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryAffinity
+    data["__nvmlDeviceGetMemoryAffinity"] = <intptr_t>__nvmlDeviceGetMemoryAffinity
 
     global __nvmlDeviceGetCpuAffinityWithinScope
-    data["__nvmlDeviceGetCpuAffinityWithinScope"] = <_cyb_intptr_t>__nvmlDeviceGetCpuAffinityWithinScope
+    data["__nvmlDeviceGetCpuAffinityWithinScope"] = <intptr_t>__nvmlDeviceGetCpuAffinityWithinScope
 
     global __nvmlDeviceGetCpuAffinity
-    data["__nvmlDeviceGetCpuAffinity"] = <_cyb_intptr_t>__nvmlDeviceGetCpuAffinity
+    data["__nvmlDeviceGetCpuAffinity"] = <intptr_t>__nvmlDeviceGetCpuAffinity
 
     global __nvmlDeviceSetCpuAffinity
-    data["__nvmlDeviceSetCpuAffinity"] = <_cyb_intptr_t>__nvmlDeviceSetCpuAffinity
+    data["__nvmlDeviceSetCpuAffinity"] = <intptr_t>__nvmlDeviceSetCpuAffinity
 
     global __nvmlDeviceClearCpuAffinity
-    data["__nvmlDeviceClearCpuAffinity"] = <_cyb_intptr_t>__nvmlDeviceClearCpuAffinity
+    data["__nvmlDeviceClearCpuAffinity"] = <intptr_t>__nvmlDeviceClearCpuAffinity
 
     global __nvmlDeviceGetNumaNodeId
-    data["__nvmlDeviceGetNumaNodeId"] = <_cyb_intptr_t>__nvmlDeviceGetNumaNodeId
+    data["__nvmlDeviceGetNumaNodeId"] = <intptr_t>__nvmlDeviceGetNumaNodeId
 
     global __nvmlDeviceGetTopologyCommonAncestor
-    data["__nvmlDeviceGetTopologyCommonAncestor"] = <_cyb_intptr_t>__nvmlDeviceGetTopologyCommonAncestor
+    data["__nvmlDeviceGetTopologyCommonAncestor"] = <intptr_t>__nvmlDeviceGetTopologyCommonAncestor
 
     global __nvmlDeviceGetTopologyNearestGpus
-    data["__nvmlDeviceGetTopologyNearestGpus"] = <_cyb_intptr_t>__nvmlDeviceGetTopologyNearestGpus
+    data["__nvmlDeviceGetTopologyNearestGpus"] = <intptr_t>__nvmlDeviceGetTopologyNearestGpus
 
     global __nvmlDeviceGetP2PStatus
-    data["__nvmlDeviceGetP2PStatus"] = <_cyb_intptr_t>__nvmlDeviceGetP2PStatus
+    data["__nvmlDeviceGetP2PStatus"] = <intptr_t>__nvmlDeviceGetP2PStatus
 
     global __nvmlDeviceGetUUID
-    data["__nvmlDeviceGetUUID"] = <_cyb_intptr_t>__nvmlDeviceGetUUID
+    data["__nvmlDeviceGetUUID"] = <intptr_t>__nvmlDeviceGetUUID
 
     global __nvmlDeviceGetMinorNumber
-    data["__nvmlDeviceGetMinorNumber"] = <_cyb_intptr_t>__nvmlDeviceGetMinorNumber
+    data["__nvmlDeviceGetMinorNumber"] = <intptr_t>__nvmlDeviceGetMinorNumber
 
     global __nvmlDeviceGetBoardPartNumber
-    data["__nvmlDeviceGetBoardPartNumber"] = <_cyb_intptr_t>__nvmlDeviceGetBoardPartNumber
+    data["__nvmlDeviceGetBoardPartNumber"] = <intptr_t>__nvmlDeviceGetBoardPartNumber
 
     global __nvmlDeviceGetInforomVersion
-    data["__nvmlDeviceGetInforomVersion"] = <_cyb_intptr_t>__nvmlDeviceGetInforomVersion
+    data["__nvmlDeviceGetInforomVersion"] = <intptr_t>__nvmlDeviceGetInforomVersion
 
     global __nvmlDeviceGetInforomImageVersion
-    data["__nvmlDeviceGetInforomImageVersion"] = <_cyb_intptr_t>__nvmlDeviceGetInforomImageVersion
+    data["__nvmlDeviceGetInforomImageVersion"] = <intptr_t>__nvmlDeviceGetInforomImageVersion
 
     global __nvmlDeviceGetInforomConfigurationChecksum
-    data["__nvmlDeviceGetInforomConfigurationChecksum"] = <_cyb_intptr_t>__nvmlDeviceGetInforomConfigurationChecksum
+    data["__nvmlDeviceGetInforomConfigurationChecksum"] = <intptr_t>__nvmlDeviceGetInforomConfigurationChecksum
 
     global __nvmlDeviceValidateInforom
-    data["__nvmlDeviceValidateInforom"] = <_cyb_intptr_t>__nvmlDeviceValidateInforom
+    data["__nvmlDeviceValidateInforom"] = <intptr_t>__nvmlDeviceValidateInforom
 
     global __nvmlDeviceGetLastBBXFlushTime
-    data["__nvmlDeviceGetLastBBXFlushTime"] = <_cyb_intptr_t>__nvmlDeviceGetLastBBXFlushTime
+    data["__nvmlDeviceGetLastBBXFlushTime"] = <intptr_t>__nvmlDeviceGetLastBBXFlushTime
 
     global __nvmlDeviceGetDisplayMode
-    data["__nvmlDeviceGetDisplayMode"] = <_cyb_intptr_t>__nvmlDeviceGetDisplayMode
+    data["__nvmlDeviceGetDisplayMode"] = <intptr_t>__nvmlDeviceGetDisplayMode
 
     global __nvmlDeviceGetDisplayActive
-    data["__nvmlDeviceGetDisplayActive"] = <_cyb_intptr_t>__nvmlDeviceGetDisplayActive
+    data["__nvmlDeviceGetDisplayActive"] = <intptr_t>__nvmlDeviceGetDisplayActive
 
     global __nvmlDeviceGetPersistenceMode
-    data["__nvmlDeviceGetPersistenceMode"] = <_cyb_intptr_t>__nvmlDeviceGetPersistenceMode
+    data["__nvmlDeviceGetPersistenceMode"] = <intptr_t>__nvmlDeviceGetPersistenceMode
 
     global __nvmlDeviceGetPciInfoExt
-    data["__nvmlDeviceGetPciInfoExt"] = <_cyb_intptr_t>__nvmlDeviceGetPciInfoExt
+    data["__nvmlDeviceGetPciInfoExt"] = <intptr_t>__nvmlDeviceGetPciInfoExt
 
     global __nvmlDeviceGetPciInfo_v3
-    data["__nvmlDeviceGetPciInfo_v3"] = <_cyb_intptr_t>__nvmlDeviceGetPciInfo_v3
+    data["__nvmlDeviceGetPciInfo_v3"] = <intptr_t>__nvmlDeviceGetPciInfo_v3
 
     global __nvmlDeviceGetMaxPcieLinkGeneration
-    data["__nvmlDeviceGetMaxPcieLinkGeneration"] = <_cyb_intptr_t>__nvmlDeviceGetMaxPcieLinkGeneration
+    data["__nvmlDeviceGetMaxPcieLinkGeneration"] = <intptr_t>__nvmlDeviceGetMaxPcieLinkGeneration
 
     global __nvmlDeviceGetGpuMaxPcieLinkGeneration
-    data["__nvmlDeviceGetGpuMaxPcieLinkGeneration"] = <_cyb_intptr_t>__nvmlDeviceGetGpuMaxPcieLinkGeneration
+    data["__nvmlDeviceGetGpuMaxPcieLinkGeneration"] = <intptr_t>__nvmlDeviceGetGpuMaxPcieLinkGeneration
 
     global __nvmlDeviceGetMaxPcieLinkWidth
-    data["__nvmlDeviceGetMaxPcieLinkWidth"] = <_cyb_intptr_t>__nvmlDeviceGetMaxPcieLinkWidth
+    data["__nvmlDeviceGetMaxPcieLinkWidth"] = <intptr_t>__nvmlDeviceGetMaxPcieLinkWidth
 
     global __nvmlDeviceGetCurrPcieLinkGeneration
-    data["__nvmlDeviceGetCurrPcieLinkGeneration"] = <_cyb_intptr_t>__nvmlDeviceGetCurrPcieLinkGeneration
+    data["__nvmlDeviceGetCurrPcieLinkGeneration"] = <intptr_t>__nvmlDeviceGetCurrPcieLinkGeneration
 
     global __nvmlDeviceGetCurrPcieLinkWidth
-    data["__nvmlDeviceGetCurrPcieLinkWidth"] = <_cyb_intptr_t>__nvmlDeviceGetCurrPcieLinkWidth
+    data["__nvmlDeviceGetCurrPcieLinkWidth"] = <intptr_t>__nvmlDeviceGetCurrPcieLinkWidth
 
     global __nvmlDeviceGetPcieThroughput
-    data["__nvmlDeviceGetPcieThroughput"] = <_cyb_intptr_t>__nvmlDeviceGetPcieThroughput
+    data["__nvmlDeviceGetPcieThroughput"] = <intptr_t>__nvmlDeviceGetPcieThroughput
 
     global __nvmlDeviceGetPcieReplayCounter
-    data["__nvmlDeviceGetPcieReplayCounter"] = <_cyb_intptr_t>__nvmlDeviceGetPcieReplayCounter
+    data["__nvmlDeviceGetPcieReplayCounter"] = <intptr_t>__nvmlDeviceGetPcieReplayCounter
 
     global __nvmlDeviceGetClockInfo
-    data["__nvmlDeviceGetClockInfo"] = <_cyb_intptr_t>__nvmlDeviceGetClockInfo
+    data["__nvmlDeviceGetClockInfo"] = <intptr_t>__nvmlDeviceGetClockInfo
 
     global __nvmlDeviceGetMaxClockInfo
-    data["__nvmlDeviceGetMaxClockInfo"] = <_cyb_intptr_t>__nvmlDeviceGetMaxClockInfo
+    data["__nvmlDeviceGetMaxClockInfo"] = <intptr_t>__nvmlDeviceGetMaxClockInfo
 
     global __nvmlDeviceGetGpcClkVfOffset
-    data["__nvmlDeviceGetGpcClkVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetGpcClkVfOffset
+    data["__nvmlDeviceGetGpcClkVfOffset"] = <intptr_t>__nvmlDeviceGetGpcClkVfOffset
 
     global __nvmlDeviceGetClock
-    data["__nvmlDeviceGetClock"] = <_cyb_intptr_t>__nvmlDeviceGetClock
+    data["__nvmlDeviceGetClock"] = <intptr_t>__nvmlDeviceGetClock
 
     global __nvmlDeviceGetMaxCustomerBoostClock
-    data["__nvmlDeviceGetMaxCustomerBoostClock"] = <_cyb_intptr_t>__nvmlDeviceGetMaxCustomerBoostClock
+    data["__nvmlDeviceGetMaxCustomerBoostClock"] = <intptr_t>__nvmlDeviceGetMaxCustomerBoostClock
 
     global __nvmlDeviceGetSupportedMemoryClocks
-    data["__nvmlDeviceGetSupportedMemoryClocks"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedMemoryClocks
+    data["__nvmlDeviceGetSupportedMemoryClocks"] = <intptr_t>__nvmlDeviceGetSupportedMemoryClocks
 
     global __nvmlDeviceGetSupportedGraphicsClocks
-    data["__nvmlDeviceGetSupportedGraphicsClocks"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedGraphicsClocks
+    data["__nvmlDeviceGetSupportedGraphicsClocks"] = <intptr_t>__nvmlDeviceGetSupportedGraphicsClocks
 
     global __nvmlDeviceGetAutoBoostedClocksEnabled
-    data["__nvmlDeviceGetAutoBoostedClocksEnabled"] = <_cyb_intptr_t>__nvmlDeviceGetAutoBoostedClocksEnabled
+    data["__nvmlDeviceGetAutoBoostedClocksEnabled"] = <intptr_t>__nvmlDeviceGetAutoBoostedClocksEnabled
 
     global __nvmlDeviceGetFanSpeed
-    data["__nvmlDeviceGetFanSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetFanSpeed
+    data["__nvmlDeviceGetFanSpeed"] = <intptr_t>__nvmlDeviceGetFanSpeed
 
     global __nvmlDeviceGetFanSpeed_v2
-    data["__nvmlDeviceGetFanSpeed_v2"] = <_cyb_intptr_t>__nvmlDeviceGetFanSpeed_v2
+    data["__nvmlDeviceGetFanSpeed_v2"] = <intptr_t>__nvmlDeviceGetFanSpeed_v2
 
     global __nvmlDeviceGetFanSpeedRPM
-    data["__nvmlDeviceGetFanSpeedRPM"] = <_cyb_intptr_t>__nvmlDeviceGetFanSpeedRPM
+    data["__nvmlDeviceGetFanSpeedRPM"] = <intptr_t>__nvmlDeviceGetFanSpeedRPM
 
     global __nvmlDeviceGetTargetFanSpeed
-    data["__nvmlDeviceGetTargetFanSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetTargetFanSpeed
+    data["__nvmlDeviceGetTargetFanSpeed"] = <intptr_t>__nvmlDeviceGetTargetFanSpeed
 
     global __nvmlDeviceGetMinMaxFanSpeed
-    data["__nvmlDeviceGetMinMaxFanSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetMinMaxFanSpeed
+    data["__nvmlDeviceGetMinMaxFanSpeed"] = <intptr_t>__nvmlDeviceGetMinMaxFanSpeed
 
     global __nvmlDeviceGetFanControlPolicy_v2
-    data["__nvmlDeviceGetFanControlPolicy_v2"] = <_cyb_intptr_t>__nvmlDeviceGetFanControlPolicy_v2
+    data["__nvmlDeviceGetFanControlPolicy_v2"] = <intptr_t>__nvmlDeviceGetFanControlPolicy_v2
 
     global __nvmlDeviceGetNumFans
-    data["__nvmlDeviceGetNumFans"] = <_cyb_intptr_t>__nvmlDeviceGetNumFans
+    data["__nvmlDeviceGetNumFans"] = <intptr_t>__nvmlDeviceGetNumFans
 
     global __nvmlDeviceGetCoolerInfo
-    data["__nvmlDeviceGetCoolerInfo"] = <_cyb_intptr_t>__nvmlDeviceGetCoolerInfo
+    data["__nvmlDeviceGetCoolerInfo"] = <intptr_t>__nvmlDeviceGetCoolerInfo
 
     global __nvmlDeviceGetTemperatureV
-    data["__nvmlDeviceGetTemperatureV"] = <_cyb_intptr_t>__nvmlDeviceGetTemperatureV
+    data["__nvmlDeviceGetTemperatureV"] = <intptr_t>__nvmlDeviceGetTemperatureV
 
     global __nvmlDeviceGetTemperatureThreshold
-    data["__nvmlDeviceGetTemperatureThreshold"] = <_cyb_intptr_t>__nvmlDeviceGetTemperatureThreshold
+    data["__nvmlDeviceGetTemperatureThreshold"] = <intptr_t>__nvmlDeviceGetTemperatureThreshold
 
     global __nvmlDeviceGetMarginTemperature
-    data["__nvmlDeviceGetMarginTemperature"] = <_cyb_intptr_t>__nvmlDeviceGetMarginTemperature
+    data["__nvmlDeviceGetMarginTemperature"] = <intptr_t>__nvmlDeviceGetMarginTemperature
 
     global __nvmlDeviceGetThermalSettings
-    data["__nvmlDeviceGetThermalSettings"] = <_cyb_intptr_t>__nvmlDeviceGetThermalSettings
+    data["__nvmlDeviceGetThermalSettings"] = <intptr_t>__nvmlDeviceGetThermalSettings
 
     global __nvmlDeviceGetPerformanceState
-    data["__nvmlDeviceGetPerformanceState"] = <_cyb_intptr_t>__nvmlDeviceGetPerformanceState
+    data["__nvmlDeviceGetPerformanceState"] = <intptr_t>__nvmlDeviceGetPerformanceState
 
     global __nvmlDeviceGetCurrentClocksEventReasons
-    data["__nvmlDeviceGetCurrentClocksEventReasons"] = <_cyb_intptr_t>__nvmlDeviceGetCurrentClocksEventReasons
+    data["__nvmlDeviceGetCurrentClocksEventReasons"] = <intptr_t>__nvmlDeviceGetCurrentClocksEventReasons
 
     global __nvmlDeviceGetSupportedClocksEventReasons
-    data["__nvmlDeviceGetSupportedClocksEventReasons"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedClocksEventReasons
+    data["__nvmlDeviceGetSupportedClocksEventReasons"] = <intptr_t>__nvmlDeviceGetSupportedClocksEventReasons
 
     global __nvmlDeviceGetPowerState
-    data["__nvmlDeviceGetPowerState"] = <_cyb_intptr_t>__nvmlDeviceGetPowerState
+    data["__nvmlDeviceGetPowerState"] = <intptr_t>__nvmlDeviceGetPowerState
 
     global __nvmlDeviceGetDynamicPstatesInfo
-    data["__nvmlDeviceGetDynamicPstatesInfo"] = <_cyb_intptr_t>__nvmlDeviceGetDynamicPstatesInfo
+    data["__nvmlDeviceGetDynamicPstatesInfo"] = <intptr_t>__nvmlDeviceGetDynamicPstatesInfo
 
     global __nvmlDeviceGetMemClkVfOffset
-    data["__nvmlDeviceGetMemClkVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetMemClkVfOffset
+    data["__nvmlDeviceGetMemClkVfOffset"] = <intptr_t>__nvmlDeviceGetMemClkVfOffset
 
     global __nvmlDeviceGetMinMaxClockOfPState
-    data["__nvmlDeviceGetMinMaxClockOfPState"] = <_cyb_intptr_t>__nvmlDeviceGetMinMaxClockOfPState
+    data["__nvmlDeviceGetMinMaxClockOfPState"] = <intptr_t>__nvmlDeviceGetMinMaxClockOfPState
 
     global __nvmlDeviceGetSupportedPerformanceStates
-    data["__nvmlDeviceGetSupportedPerformanceStates"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedPerformanceStates
+    data["__nvmlDeviceGetSupportedPerformanceStates"] = <intptr_t>__nvmlDeviceGetSupportedPerformanceStates
 
     global __nvmlDeviceGetGpcClkMinMaxVfOffset
-    data["__nvmlDeviceGetGpcClkMinMaxVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetGpcClkMinMaxVfOffset
+    data["__nvmlDeviceGetGpcClkMinMaxVfOffset"] = <intptr_t>__nvmlDeviceGetGpcClkMinMaxVfOffset
 
     global __nvmlDeviceGetMemClkMinMaxVfOffset
-    data["__nvmlDeviceGetMemClkMinMaxVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetMemClkMinMaxVfOffset
+    data["__nvmlDeviceGetMemClkMinMaxVfOffset"] = <intptr_t>__nvmlDeviceGetMemClkMinMaxVfOffset
 
     global __nvmlDeviceGetClockOffsets
-    data["__nvmlDeviceGetClockOffsets"] = <_cyb_intptr_t>__nvmlDeviceGetClockOffsets
+    data["__nvmlDeviceGetClockOffsets"] = <intptr_t>__nvmlDeviceGetClockOffsets
 
     global __nvmlDeviceSetClockOffsets
-    data["__nvmlDeviceSetClockOffsets"] = <_cyb_intptr_t>__nvmlDeviceSetClockOffsets
+    data["__nvmlDeviceSetClockOffsets"] = <intptr_t>__nvmlDeviceSetClockOffsets
 
     global __nvmlDeviceGetPerformanceModes
-    data["__nvmlDeviceGetPerformanceModes"] = <_cyb_intptr_t>__nvmlDeviceGetPerformanceModes
+    data["__nvmlDeviceGetPerformanceModes"] = <intptr_t>__nvmlDeviceGetPerformanceModes
 
     global __nvmlDeviceGetCurrentClockFreqs
-    data["__nvmlDeviceGetCurrentClockFreqs"] = <_cyb_intptr_t>__nvmlDeviceGetCurrentClockFreqs
+    data["__nvmlDeviceGetCurrentClockFreqs"] = <intptr_t>__nvmlDeviceGetCurrentClockFreqs
 
     global __nvmlDeviceGetPowerManagementLimit
-    data["__nvmlDeviceGetPowerManagementLimit"] = <_cyb_intptr_t>__nvmlDeviceGetPowerManagementLimit
+    data["__nvmlDeviceGetPowerManagementLimit"] = <intptr_t>__nvmlDeviceGetPowerManagementLimit
 
     global __nvmlDeviceGetPowerManagementLimitConstraints
-    data["__nvmlDeviceGetPowerManagementLimitConstraints"] = <_cyb_intptr_t>__nvmlDeviceGetPowerManagementLimitConstraints
+    data["__nvmlDeviceGetPowerManagementLimitConstraints"] = <intptr_t>__nvmlDeviceGetPowerManagementLimitConstraints
 
     global __nvmlDeviceGetPowerManagementDefaultLimit
-    data["__nvmlDeviceGetPowerManagementDefaultLimit"] = <_cyb_intptr_t>__nvmlDeviceGetPowerManagementDefaultLimit
+    data["__nvmlDeviceGetPowerManagementDefaultLimit"] = <intptr_t>__nvmlDeviceGetPowerManagementDefaultLimit
 
     global __nvmlDeviceGetPowerUsage
-    data["__nvmlDeviceGetPowerUsage"] = <_cyb_intptr_t>__nvmlDeviceGetPowerUsage
+    data["__nvmlDeviceGetPowerUsage"] = <intptr_t>__nvmlDeviceGetPowerUsage
 
     global __nvmlDeviceGetTotalEnergyConsumption
-    data["__nvmlDeviceGetTotalEnergyConsumption"] = <_cyb_intptr_t>__nvmlDeviceGetTotalEnergyConsumption
+    data["__nvmlDeviceGetTotalEnergyConsumption"] = <intptr_t>__nvmlDeviceGetTotalEnergyConsumption
 
     global __nvmlDeviceGetEnforcedPowerLimit
-    data["__nvmlDeviceGetEnforcedPowerLimit"] = <_cyb_intptr_t>__nvmlDeviceGetEnforcedPowerLimit
+    data["__nvmlDeviceGetEnforcedPowerLimit"] = <intptr_t>__nvmlDeviceGetEnforcedPowerLimit
 
     global __nvmlDeviceGetGpuOperationMode
-    data["__nvmlDeviceGetGpuOperationMode"] = <_cyb_intptr_t>__nvmlDeviceGetGpuOperationMode
+    data["__nvmlDeviceGetGpuOperationMode"] = <intptr_t>__nvmlDeviceGetGpuOperationMode
 
     global __nvmlDeviceGetMemoryInfo_v2
-    data["__nvmlDeviceGetMemoryInfo_v2"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryInfo_v2
+    data["__nvmlDeviceGetMemoryInfo_v2"] = <intptr_t>__nvmlDeviceGetMemoryInfo_v2
 
     global __nvmlDeviceGetComputeMode
-    data["__nvmlDeviceGetComputeMode"] = <_cyb_intptr_t>__nvmlDeviceGetComputeMode
+    data["__nvmlDeviceGetComputeMode"] = <intptr_t>__nvmlDeviceGetComputeMode
 
     global __nvmlDeviceGetCudaComputeCapability
-    data["__nvmlDeviceGetCudaComputeCapability"] = <_cyb_intptr_t>__nvmlDeviceGetCudaComputeCapability
+    data["__nvmlDeviceGetCudaComputeCapability"] = <intptr_t>__nvmlDeviceGetCudaComputeCapability
 
     global __nvmlDeviceGetDramEncryptionMode
-    data["__nvmlDeviceGetDramEncryptionMode"] = <_cyb_intptr_t>__nvmlDeviceGetDramEncryptionMode
+    data["__nvmlDeviceGetDramEncryptionMode"] = <intptr_t>__nvmlDeviceGetDramEncryptionMode
 
     global __nvmlDeviceSetDramEncryptionMode
-    data["__nvmlDeviceSetDramEncryptionMode"] = <_cyb_intptr_t>__nvmlDeviceSetDramEncryptionMode
+    data["__nvmlDeviceSetDramEncryptionMode"] = <intptr_t>__nvmlDeviceSetDramEncryptionMode
 
     global __nvmlDeviceGetEccMode
-    data["__nvmlDeviceGetEccMode"] = <_cyb_intptr_t>__nvmlDeviceGetEccMode
+    data["__nvmlDeviceGetEccMode"] = <intptr_t>__nvmlDeviceGetEccMode
 
     global __nvmlDeviceGetDefaultEccMode
-    data["__nvmlDeviceGetDefaultEccMode"] = <_cyb_intptr_t>__nvmlDeviceGetDefaultEccMode
+    data["__nvmlDeviceGetDefaultEccMode"] = <intptr_t>__nvmlDeviceGetDefaultEccMode
 
     global __nvmlDeviceGetBoardId
-    data["__nvmlDeviceGetBoardId"] = <_cyb_intptr_t>__nvmlDeviceGetBoardId
+    data["__nvmlDeviceGetBoardId"] = <intptr_t>__nvmlDeviceGetBoardId
 
     global __nvmlDeviceGetMultiGpuBoard
-    data["__nvmlDeviceGetMultiGpuBoard"] = <_cyb_intptr_t>__nvmlDeviceGetMultiGpuBoard
+    data["__nvmlDeviceGetMultiGpuBoard"] = <intptr_t>__nvmlDeviceGetMultiGpuBoard
 
     global __nvmlDeviceGetTotalEccErrors
-    data["__nvmlDeviceGetTotalEccErrors"] = <_cyb_intptr_t>__nvmlDeviceGetTotalEccErrors
+    data["__nvmlDeviceGetTotalEccErrors"] = <intptr_t>__nvmlDeviceGetTotalEccErrors
 
     global __nvmlDeviceGetMemoryErrorCounter
-    data["__nvmlDeviceGetMemoryErrorCounter"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryErrorCounter
+    data["__nvmlDeviceGetMemoryErrorCounter"] = <intptr_t>__nvmlDeviceGetMemoryErrorCounter
 
     global __nvmlDeviceGetUtilizationRates
-    data["__nvmlDeviceGetUtilizationRates"] = <_cyb_intptr_t>__nvmlDeviceGetUtilizationRates
+    data["__nvmlDeviceGetUtilizationRates"] = <intptr_t>__nvmlDeviceGetUtilizationRates
 
     global __nvmlDeviceGetEncoderUtilization
-    data["__nvmlDeviceGetEncoderUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderUtilization
+    data["__nvmlDeviceGetEncoderUtilization"] = <intptr_t>__nvmlDeviceGetEncoderUtilization
 
     global __nvmlDeviceGetEncoderCapacity
-    data["__nvmlDeviceGetEncoderCapacity"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderCapacity
+    data["__nvmlDeviceGetEncoderCapacity"] = <intptr_t>__nvmlDeviceGetEncoderCapacity
 
     global __nvmlDeviceGetEncoderStats
-    data["__nvmlDeviceGetEncoderStats"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderStats
+    data["__nvmlDeviceGetEncoderStats"] = <intptr_t>__nvmlDeviceGetEncoderStats
 
     global __nvmlDeviceGetEncoderSessions
-    data["__nvmlDeviceGetEncoderSessions"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderSessions
+    data["__nvmlDeviceGetEncoderSessions"] = <intptr_t>__nvmlDeviceGetEncoderSessions
 
     global __nvmlDeviceGetDecoderUtilization
-    data["__nvmlDeviceGetDecoderUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetDecoderUtilization
+    data["__nvmlDeviceGetDecoderUtilization"] = <intptr_t>__nvmlDeviceGetDecoderUtilization
 
     global __nvmlDeviceGetJpgUtilization
-    data["__nvmlDeviceGetJpgUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetJpgUtilization
+    data["__nvmlDeviceGetJpgUtilization"] = <intptr_t>__nvmlDeviceGetJpgUtilization
 
     global __nvmlDeviceGetOfaUtilization
-    data["__nvmlDeviceGetOfaUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetOfaUtilization
+    data["__nvmlDeviceGetOfaUtilization"] = <intptr_t>__nvmlDeviceGetOfaUtilization
 
     global __nvmlDeviceGetFBCStats
-    data["__nvmlDeviceGetFBCStats"] = <_cyb_intptr_t>__nvmlDeviceGetFBCStats
+    data["__nvmlDeviceGetFBCStats"] = <intptr_t>__nvmlDeviceGetFBCStats
 
     global __nvmlDeviceGetFBCSessions
-    data["__nvmlDeviceGetFBCSessions"] = <_cyb_intptr_t>__nvmlDeviceGetFBCSessions
+    data["__nvmlDeviceGetFBCSessions"] = <intptr_t>__nvmlDeviceGetFBCSessions
 
     global __nvmlDeviceGetDriverModel_v2
-    data["__nvmlDeviceGetDriverModel_v2"] = <_cyb_intptr_t>__nvmlDeviceGetDriverModel_v2
+    data["__nvmlDeviceGetDriverModel_v2"] = <intptr_t>__nvmlDeviceGetDriverModel_v2
 
     global __nvmlDeviceGetVbiosVersion
-    data["__nvmlDeviceGetVbiosVersion"] = <_cyb_intptr_t>__nvmlDeviceGetVbiosVersion
+    data["__nvmlDeviceGetVbiosVersion"] = <intptr_t>__nvmlDeviceGetVbiosVersion
 
     global __nvmlDeviceGetBridgeChipInfo
-    data["__nvmlDeviceGetBridgeChipInfo"] = <_cyb_intptr_t>__nvmlDeviceGetBridgeChipInfo
+    data["__nvmlDeviceGetBridgeChipInfo"] = <intptr_t>__nvmlDeviceGetBridgeChipInfo
 
     global __nvmlDeviceGetComputeRunningProcesses_v3
-    data["__nvmlDeviceGetComputeRunningProcesses_v3"] = <_cyb_intptr_t>__nvmlDeviceGetComputeRunningProcesses_v3
+    data["__nvmlDeviceGetComputeRunningProcesses_v3"] = <intptr_t>__nvmlDeviceGetComputeRunningProcesses_v3
 
     global __nvmlDeviceGetGraphicsRunningProcesses_v3
-    data["__nvmlDeviceGetGraphicsRunningProcesses_v3"] = <_cyb_intptr_t>__nvmlDeviceGetGraphicsRunningProcesses_v3
+    data["__nvmlDeviceGetGraphicsRunningProcesses_v3"] = <intptr_t>__nvmlDeviceGetGraphicsRunningProcesses_v3
 
     global __nvmlDeviceGetMPSComputeRunningProcesses_v3
-    data["__nvmlDeviceGetMPSComputeRunningProcesses_v3"] = <_cyb_intptr_t>__nvmlDeviceGetMPSComputeRunningProcesses_v3
+    data["__nvmlDeviceGetMPSComputeRunningProcesses_v3"] = <intptr_t>__nvmlDeviceGetMPSComputeRunningProcesses_v3
 
     global __nvmlDeviceGetRunningProcessDetailList
-    data["__nvmlDeviceGetRunningProcessDetailList"] = <_cyb_intptr_t>__nvmlDeviceGetRunningProcessDetailList
+    data["__nvmlDeviceGetRunningProcessDetailList"] = <intptr_t>__nvmlDeviceGetRunningProcessDetailList
 
     global __nvmlDeviceOnSameBoard
-    data["__nvmlDeviceOnSameBoard"] = <_cyb_intptr_t>__nvmlDeviceOnSameBoard
+    data["__nvmlDeviceOnSameBoard"] = <intptr_t>__nvmlDeviceOnSameBoard
 
     global __nvmlDeviceGetAPIRestriction
-    data["__nvmlDeviceGetAPIRestriction"] = <_cyb_intptr_t>__nvmlDeviceGetAPIRestriction
+    data["__nvmlDeviceGetAPIRestriction"] = <intptr_t>__nvmlDeviceGetAPIRestriction
 
     global __nvmlDeviceGetSamples
-    data["__nvmlDeviceGetSamples"] = <_cyb_intptr_t>__nvmlDeviceGetSamples
+    data["__nvmlDeviceGetSamples"] = <intptr_t>__nvmlDeviceGetSamples
 
     global __nvmlDeviceGetBAR1MemoryInfo
-    data["__nvmlDeviceGetBAR1MemoryInfo"] = <_cyb_intptr_t>__nvmlDeviceGetBAR1MemoryInfo
+    data["__nvmlDeviceGetBAR1MemoryInfo"] = <intptr_t>__nvmlDeviceGetBAR1MemoryInfo
 
     global __nvmlDeviceGetIrqNum
-    data["__nvmlDeviceGetIrqNum"] = <_cyb_intptr_t>__nvmlDeviceGetIrqNum
+    data["__nvmlDeviceGetIrqNum"] = <intptr_t>__nvmlDeviceGetIrqNum
 
     global __nvmlDeviceGetNumGpuCores
-    data["__nvmlDeviceGetNumGpuCores"] = <_cyb_intptr_t>__nvmlDeviceGetNumGpuCores
+    data["__nvmlDeviceGetNumGpuCores"] = <intptr_t>__nvmlDeviceGetNumGpuCores
 
     global __nvmlDeviceGetPowerSource
-    data["__nvmlDeviceGetPowerSource"] = <_cyb_intptr_t>__nvmlDeviceGetPowerSource
+    data["__nvmlDeviceGetPowerSource"] = <intptr_t>__nvmlDeviceGetPowerSource
 
     global __nvmlDeviceGetMemoryBusWidth
-    data["__nvmlDeviceGetMemoryBusWidth"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryBusWidth
+    data["__nvmlDeviceGetMemoryBusWidth"] = <intptr_t>__nvmlDeviceGetMemoryBusWidth
 
     global __nvmlDeviceGetPcieLinkMaxSpeed
-    data["__nvmlDeviceGetPcieLinkMaxSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetPcieLinkMaxSpeed
+    data["__nvmlDeviceGetPcieLinkMaxSpeed"] = <intptr_t>__nvmlDeviceGetPcieLinkMaxSpeed
 
     global __nvmlDeviceGetPcieSpeed
-    data["__nvmlDeviceGetPcieSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetPcieSpeed
+    data["__nvmlDeviceGetPcieSpeed"] = <intptr_t>__nvmlDeviceGetPcieSpeed
 
     global __nvmlDeviceGetAdaptiveClockInfoStatus
-    data["__nvmlDeviceGetAdaptiveClockInfoStatus"] = <_cyb_intptr_t>__nvmlDeviceGetAdaptiveClockInfoStatus
+    data["__nvmlDeviceGetAdaptiveClockInfoStatus"] = <intptr_t>__nvmlDeviceGetAdaptiveClockInfoStatus
 
     global __nvmlDeviceGetBusType
-    data["__nvmlDeviceGetBusType"] = <_cyb_intptr_t>__nvmlDeviceGetBusType
+    data["__nvmlDeviceGetBusType"] = <intptr_t>__nvmlDeviceGetBusType
 
     global __nvmlDeviceGetGpuFabricInfoV
-    data["__nvmlDeviceGetGpuFabricInfoV"] = <_cyb_intptr_t>__nvmlDeviceGetGpuFabricInfoV
+    data["__nvmlDeviceGetGpuFabricInfoV"] = <intptr_t>__nvmlDeviceGetGpuFabricInfoV
 
     global __nvmlSystemGetConfComputeCapabilities
-    data["__nvmlSystemGetConfComputeCapabilities"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeCapabilities
+    data["__nvmlSystemGetConfComputeCapabilities"] = <intptr_t>__nvmlSystemGetConfComputeCapabilities
 
     global __nvmlSystemGetConfComputeState
-    data["__nvmlSystemGetConfComputeState"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeState
+    data["__nvmlSystemGetConfComputeState"] = <intptr_t>__nvmlSystemGetConfComputeState
 
     global __nvmlDeviceGetConfComputeMemSizeInfo
-    data["__nvmlDeviceGetConfComputeMemSizeInfo"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeMemSizeInfo
+    data["__nvmlDeviceGetConfComputeMemSizeInfo"] = <intptr_t>__nvmlDeviceGetConfComputeMemSizeInfo
 
     global __nvmlSystemGetConfComputeGpusReadyState
-    data["__nvmlSystemGetConfComputeGpusReadyState"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeGpusReadyState
+    data["__nvmlSystemGetConfComputeGpusReadyState"] = <intptr_t>__nvmlSystemGetConfComputeGpusReadyState
 
     global __nvmlDeviceGetConfComputeProtectedMemoryUsage
-    data["__nvmlDeviceGetConfComputeProtectedMemoryUsage"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeProtectedMemoryUsage
+    data["__nvmlDeviceGetConfComputeProtectedMemoryUsage"] = <intptr_t>__nvmlDeviceGetConfComputeProtectedMemoryUsage
 
     global __nvmlDeviceGetConfComputeGpuCertificate
-    data["__nvmlDeviceGetConfComputeGpuCertificate"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeGpuCertificate
+    data["__nvmlDeviceGetConfComputeGpuCertificate"] = <intptr_t>__nvmlDeviceGetConfComputeGpuCertificate
 
     global __nvmlDeviceGetConfComputeGpuAttestationReport
-    data["__nvmlDeviceGetConfComputeGpuAttestationReport"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeGpuAttestationReport
+    data["__nvmlDeviceGetConfComputeGpuAttestationReport"] = <intptr_t>__nvmlDeviceGetConfComputeGpuAttestationReport
 
     global __nvmlSystemGetConfComputeKeyRotationThresholdInfo
-    data["__nvmlSystemGetConfComputeKeyRotationThresholdInfo"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeKeyRotationThresholdInfo
+    data["__nvmlSystemGetConfComputeKeyRotationThresholdInfo"] = <intptr_t>__nvmlSystemGetConfComputeKeyRotationThresholdInfo
 
     global __nvmlDeviceSetConfComputeUnprotectedMemSize
-    data["__nvmlDeviceSetConfComputeUnprotectedMemSize"] = <_cyb_intptr_t>__nvmlDeviceSetConfComputeUnprotectedMemSize
+    data["__nvmlDeviceSetConfComputeUnprotectedMemSize"] = <intptr_t>__nvmlDeviceSetConfComputeUnprotectedMemSize
 
     global __nvmlSystemSetConfComputeGpusReadyState
-    data["__nvmlSystemSetConfComputeGpusReadyState"] = <_cyb_intptr_t>__nvmlSystemSetConfComputeGpusReadyState
+    data["__nvmlSystemSetConfComputeGpusReadyState"] = <intptr_t>__nvmlSystemSetConfComputeGpusReadyState
 
     global __nvmlSystemSetConfComputeKeyRotationThresholdInfo
-    data["__nvmlSystemSetConfComputeKeyRotationThresholdInfo"] = <_cyb_intptr_t>__nvmlSystemSetConfComputeKeyRotationThresholdInfo
+    data["__nvmlSystemSetConfComputeKeyRotationThresholdInfo"] = <intptr_t>__nvmlSystemSetConfComputeKeyRotationThresholdInfo
 
     global __nvmlSystemGetConfComputeSettings
-    data["__nvmlSystemGetConfComputeSettings"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeSettings
+    data["__nvmlSystemGetConfComputeSettings"] = <intptr_t>__nvmlSystemGetConfComputeSettings
 
     global __nvmlDeviceGetGspFirmwareVersion
-    data["__nvmlDeviceGetGspFirmwareVersion"] = <_cyb_intptr_t>__nvmlDeviceGetGspFirmwareVersion
+    data["__nvmlDeviceGetGspFirmwareVersion"] = <intptr_t>__nvmlDeviceGetGspFirmwareVersion
 
     global __nvmlDeviceGetGspFirmwareMode
-    data["__nvmlDeviceGetGspFirmwareMode"] = <_cyb_intptr_t>__nvmlDeviceGetGspFirmwareMode
+    data["__nvmlDeviceGetGspFirmwareMode"] = <intptr_t>__nvmlDeviceGetGspFirmwareMode
 
     global __nvmlDeviceGetSramEccErrorStatus
-    data["__nvmlDeviceGetSramEccErrorStatus"] = <_cyb_intptr_t>__nvmlDeviceGetSramEccErrorStatus
+    data["__nvmlDeviceGetSramEccErrorStatus"] = <intptr_t>__nvmlDeviceGetSramEccErrorStatus
 
     global __nvmlDeviceGetAccountingMode
-    data["__nvmlDeviceGetAccountingMode"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingMode
+    data["__nvmlDeviceGetAccountingMode"] = <intptr_t>__nvmlDeviceGetAccountingMode
 
     global __nvmlDeviceGetAccountingStats
-    data["__nvmlDeviceGetAccountingStats"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingStats
+    data["__nvmlDeviceGetAccountingStats"] = <intptr_t>__nvmlDeviceGetAccountingStats
 
     global __nvmlDeviceGetAccountingPids
-    data["__nvmlDeviceGetAccountingPids"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingPids
+    data["__nvmlDeviceGetAccountingPids"] = <intptr_t>__nvmlDeviceGetAccountingPids
 
     global __nvmlDeviceGetAccountingBufferSize
-    data["__nvmlDeviceGetAccountingBufferSize"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingBufferSize
+    data["__nvmlDeviceGetAccountingBufferSize"] = <intptr_t>__nvmlDeviceGetAccountingBufferSize
 
     global __nvmlDeviceGetRetiredPages
-    data["__nvmlDeviceGetRetiredPages"] = <_cyb_intptr_t>__nvmlDeviceGetRetiredPages
+    data["__nvmlDeviceGetRetiredPages"] = <intptr_t>__nvmlDeviceGetRetiredPages
 
     global __nvmlDeviceGetRetiredPages_v2
-    data["__nvmlDeviceGetRetiredPages_v2"] = <_cyb_intptr_t>__nvmlDeviceGetRetiredPages_v2
+    data["__nvmlDeviceGetRetiredPages_v2"] = <intptr_t>__nvmlDeviceGetRetiredPages_v2
 
     global __nvmlDeviceGetRetiredPagesPendingStatus
-    data["__nvmlDeviceGetRetiredPagesPendingStatus"] = <_cyb_intptr_t>__nvmlDeviceGetRetiredPagesPendingStatus
+    data["__nvmlDeviceGetRetiredPagesPendingStatus"] = <intptr_t>__nvmlDeviceGetRetiredPagesPendingStatus
 
     global __nvmlDeviceGetRemappedRows
-    data["__nvmlDeviceGetRemappedRows"] = <_cyb_intptr_t>__nvmlDeviceGetRemappedRows
+    data["__nvmlDeviceGetRemappedRows"] = <intptr_t>__nvmlDeviceGetRemappedRows
 
     global __nvmlDeviceGetRowRemapperHistogram
-    data["__nvmlDeviceGetRowRemapperHistogram"] = <_cyb_intptr_t>__nvmlDeviceGetRowRemapperHistogram
+    data["__nvmlDeviceGetRowRemapperHistogram"] = <intptr_t>__nvmlDeviceGetRowRemapperHistogram
 
     global __nvmlDeviceGetArchitecture
-    data["__nvmlDeviceGetArchitecture"] = <_cyb_intptr_t>__nvmlDeviceGetArchitecture
+    data["__nvmlDeviceGetArchitecture"] = <intptr_t>__nvmlDeviceGetArchitecture
 
     global __nvmlDeviceGetClkMonStatus
-    data["__nvmlDeviceGetClkMonStatus"] = <_cyb_intptr_t>__nvmlDeviceGetClkMonStatus
+    data["__nvmlDeviceGetClkMonStatus"] = <intptr_t>__nvmlDeviceGetClkMonStatus
 
     global __nvmlDeviceGetProcessUtilization
-    data["__nvmlDeviceGetProcessUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetProcessUtilization
+    data["__nvmlDeviceGetProcessUtilization"] = <intptr_t>__nvmlDeviceGetProcessUtilization
 
     global __nvmlDeviceGetProcessesUtilizationInfo
-    data["__nvmlDeviceGetProcessesUtilizationInfo"] = <_cyb_intptr_t>__nvmlDeviceGetProcessesUtilizationInfo
+    data["__nvmlDeviceGetProcessesUtilizationInfo"] = <intptr_t>__nvmlDeviceGetProcessesUtilizationInfo
 
     global __nvmlDeviceGetPlatformInfo
-    data["__nvmlDeviceGetPlatformInfo"] = <_cyb_intptr_t>__nvmlDeviceGetPlatformInfo
+    data["__nvmlDeviceGetPlatformInfo"] = <intptr_t>__nvmlDeviceGetPlatformInfo
 
     global __nvmlUnitSetLedState
-    data["__nvmlUnitSetLedState"] = <_cyb_intptr_t>__nvmlUnitSetLedState
+    data["__nvmlUnitSetLedState"] = <intptr_t>__nvmlUnitSetLedState
 
     global __nvmlDeviceSetPersistenceMode
-    data["__nvmlDeviceSetPersistenceMode"] = <_cyb_intptr_t>__nvmlDeviceSetPersistenceMode
+    data["__nvmlDeviceSetPersistenceMode"] = <intptr_t>__nvmlDeviceSetPersistenceMode
 
     global __nvmlDeviceSetComputeMode
-    data["__nvmlDeviceSetComputeMode"] = <_cyb_intptr_t>__nvmlDeviceSetComputeMode
+    data["__nvmlDeviceSetComputeMode"] = <intptr_t>__nvmlDeviceSetComputeMode
 
     global __nvmlDeviceSetEccMode
-    data["__nvmlDeviceSetEccMode"] = <_cyb_intptr_t>__nvmlDeviceSetEccMode
+    data["__nvmlDeviceSetEccMode"] = <intptr_t>__nvmlDeviceSetEccMode
 
     global __nvmlDeviceClearEccErrorCounts
-    data["__nvmlDeviceClearEccErrorCounts"] = <_cyb_intptr_t>__nvmlDeviceClearEccErrorCounts
+    data["__nvmlDeviceClearEccErrorCounts"] = <intptr_t>__nvmlDeviceClearEccErrorCounts
 
     global __nvmlDeviceSetDriverModel
-    data["__nvmlDeviceSetDriverModel"] = <_cyb_intptr_t>__nvmlDeviceSetDriverModel
+    data["__nvmlDeviceSetDriverModel"] = <intptr_t>__nvmlDeviceSetDriverModel
 
     global __nvmlDeviceSetGpuLockedClocks
-    data["__nvmlDeviceSetGpuLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceSetGpuLockedClocks
+    data["__nvmlDeviceSetGpuLockedClocks"] = <intptr_t>__nvmlDeviceSetGpuLockedClocks
 
     global __nvmlDeviceResetGpuLockedClocks
-    data["__nvmlDeviceResetGpuLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceResetGpuLockedClocks
+    data["__nvmlDeviceResetGpuLockedClocks"] = <intptr_t>__nvmlDeviceResetGpuLockedClocks
 
     global __nvmlDeviceSetMemoryLockedClocks
-    data["__nvmlDeviceSetMemoryLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceSetMemoryLockedClocks
+    data["__nvmlDeviceSetMemoryLockedClocks"] = <intptr_t>__nvmlDeviceSetMemoryLockedClocks
 
     global __nvmlDeviceResetMemoryLockedClocks
-    data["__nvmlDeviceResetMemoryLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceResetMemoryLockedClocks
+    data["__nvmlDeviceResetMemoryLockedClocks"] = <intptr_t>__nvmlDeviceResetMemoryLockedClocks
 
     global __nvmlDeviceSetAutoBoostedClocksEnabled
-    data["__nvmlDeviceSetAutoBoostedClocksEnabled"] = <_cyb_intptr_t>__nvmlDeviceSetAutoBoostedClocksEnabled
+    data["__nvmlDeviceSetAutoBoostedClocksEnabled"] = <intptr_t>__nvmlDeviceSetAutoBoostedClocksEnabled
 
     global __nvmlDeviceSetDefaultAutoBoostedClocksEnabled
-    data["__nvmlDeviceSetDefaultAutoBoostedClocksEnabled"] = <_cyb_intptr_t>__nvmlDeviceSetDefaultAutoBoostedClocksEnabled
+    data["__nvmlDeviceSetDefaultAutoBoostedClocksEnabled"] = <intptr_t>__nvmlDeviceSetDefaultAutoBoostedClocksEnabled
 
     global __nvmlDeviceSetDefaultFanSpeed_v2
-    data["__nvmlDeviceSetDefaultFanSpeed_v2"] = <_cyb_intptr_t>__nvmlDeviceSetDefaultFanSpeed_v2
+    data["__nvmlDeviceSetDefaultFanSpeed_v2"] = <intptr_t>__nvmlDeviceSetDefaultFanSpeed_v2
 
     global __nvmlDeviceSetFanControlPolicy
-    data["__nvmlDeviceSetFanControlPolicy"] = <_cyb_intptr_t>__nvmlDeviceSetFanControlPolicy
+    data["__nvmlDeviceSetFanControlPolicy"] = <intptr_t>__nvmlDeviceSetFanControlPolicy
 
     global __nvmlDeviceSetTemperatureThreshold
-    data["__nvmlDeviceSetTemperatureThreshold"] = <_cyb_intptr_t>__nvmlDeviceSetTemperatureThreshold
+    data["__nvmlDeviceSetTemperatureThreshold"] = <intptr_t>__nvmlDeviceSetTemperatureThreshold
 
     global __nvmlDeviceSetGpuOperationMode
-    data["__nvmlDeviceSetGpuOperationMode"] = <_cyb_intptr_t>__nvmlDeviceSetGpuOperationMode
+    data["__nvmlDeviceSetGpuOperationMode"] = <intptr_t>__nvmlDeviceSetGpuOperationMode
 
     global __nvmlDeviceSetAPIRestriction
-    data["__nvmlDeviceSetAPIRestriction"] = <_cyb_intptr_t>__nvmlDeviceSetAPIRestriction
+    data["__nvmlDeviceSetAPIRestriction"] = <intptr_t>__nvmlDeviceSetAPIRestriction
 
     global __nvmlDeviceSetFanSpeed_v2
-    data["__nvmlDeviceSetFanSpeed_v2"] = <_cyb_intptr_t>__nvmlDeviceSetFanSpeed_v2
+    data["__nvmlDeviceSetFanSpeed_v2"] = <intptr_t>__nvmlDeviceSetFanSpeed_v2
 
     global __nvmlDeviceSetAccountingMode
-    data["__nvmlDeviceSetAccountingMode"] = <_cyb_intptr_t>__nvmlDeviceSetAccountingMode
+    data["__nvmlDeviceSetAccountingMode"] = <intptr_t>__nvmlDeviceSetAccountingMode
 
     global __nvmlDeviceClearAccountingPids
-    data["__nvmlDeviceClearAccountingPids"] = <_cyb_intptr_t>__nvmlDeviceClearAccountingPids
+    data["__nvmlDeviceClearAccountingPids"] = <intptr_t>__nvmlDeviceClearAccountingPids
 
     global __nvmlDeviceSetPowerManagementLimit_v2
-    data["__nvmlDeviceSetPowerManagementLimit_v2"] = <_cyb_intptr_t>__nvmlDeviceSetPowerManagementLimit_v2
+    data["__nvmlDeviceSetPowerManagementLimit_v2"] = <intptr_t>__nvmlDeviceSetPowerManagementLimit_v2
 
     global __nvmlDeviceGetNvLinkState
-    data["__nvmlDeviceGetNvLinkState"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkState
+    data["__nvmlDeviceGetNvLinkState"] = <intptr_t>__nvmlDeviceGetNvLinkState
 
     global __nvmlDeviceGetNvLinkVersion
-    data["__nvmlDeviceGetNvLinkVersion"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkVersion
+    data["__nvmlDeviceGetNvLinkVersion"] = <intptr_t>__nvmlDeviceGetNvLinkVersion
 
     global __nvmlDeviceGetNvLinkCapability
-    data["__nvmlDeviceGetNvLinkCapability"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkCapability
+    data["__nvmlDeviceGetNvLinkCapability"] = <intptr_t>__nvmlDeviceGetNvLinkCapability
 
     global __nvmlDeviceGetNvLinkRemotePciInfo_v2
-    data["__nvmlDeviceGetNvLinkRemotePciInfo_v2"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkRemotePciInfo_v2
+    data["__nvmlDeviceGetNvLinkRemotePciInfo_v2"] = <intptr_t>__nvmlDeviceGetNvLinkRemotePciInfo_v2
 
     global __nvmlDeviceGetNvLinkErrorCounter
-    data["__nvmlDeviceGetNvLinkErrorCounter"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkErrorCounter
+    data["__nvmlDeviceGetNvLinkErrorCounter"] = <intptr_t>__nvmlDeviceGetNvLinkErrorCounter
 
     global __nvmlDeviceResetNvLinkErrorCounters
-    data["__nvmlDeviceResetNvLinkErrorCounters"] = <_cyb_intptr_t>__nvmlDeviceResetNvLinkErrorCounters
+    data["__nvmlDeviceResetNvLinkErrorCounters"] = <intptr_t>__nvmlDeviceResetNvLinkErrorCounters
 
     global __nvmlDeviceGetNvLinkRemoteDeviceType
-    data["__nvmlDeviceGetNvLinkRemoteDeviceType"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkRemoteDeviceType
+    data["__nvmlDeviceGetNvLinkRemoteDeviceType"] = <intptr_t>__nvmlDeviceGetNvLinkRemoteDeviceType
 
     global __nvmlDeviceSetNvLinkDeviceLowPowerThreshold
-    data["__nvmlDeviceSetNvLinkDeviceLowPowerThreshold"] = <_cyb_intptr_t>__nvmlDeviceSetNvLinkDeviceLowPowerThreshold
+    data["__nvmlDeviceSetNvLinkDeviceLowPowerThreshold"] = <intptr_t>__nvmlDeviceSetNvLinkDeviceLowPowerThreshold
 
     global __nvmlSystemSetNvlinkBwMode
-    data["__nvmlSystemSetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlSystemSetNvlinkBwMode
+    data["__nvmlSystemSetNvlinkBwMode"] = <intptr_t>__nvmlSystemSetNvlinkBwMode
 
     global __nvmlSystemGetNvlinkBwMode
-    data["__nvmlSystemGetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlSystemGetNvlinkBwMode
+    data["__nvmlSystemGetNvlinkBwMode"] = <intptr_t>__nvmlSystemGetNvlinkBwMode
 
     global __nvmlDeviceGetNvlinkSupportedBwModes
-    data["__nvmlDeviceGetNvlinkSupportedBwModes"] = <_cyb_intptr_t>__nvmlDeviceGetNvlinkSupportedBwModes
+    data["__nvmlDeviceGetNvlinkSupportedBwModes"] = <intptr_t>__nvmlDeviceGetNvlinkSupportedBwModes
 
     global __nvmlDeviceGetNvlinkBwMode
-    data["__nvmlDeviceGetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlDeviceGetNvlinkBwMode
+    data["__nvmlDeviceGetNvlinkBwMode"] = <intptr_t>__nvmlDeviceGetNvlinkBwMode
 
     global __nvmlDeviceSetNvlinkBwMode
-    data["__nvmlDeviceSetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlDeviceSetNvlinkBwMode
+    data["__nvmlDeviceSetNvlinkBwMode"] = <intptr_t>__nvmlDeviceSetNvlinkBwMode
 
     global __nvmlEventSetCreate
-    data["__nvmlEventSetCreate"] = <_cyb_intptr_t>__nvmlEventSetCreate
+    data["__nvmlEventSetCreate"] = <intptr_t>__nvmlEventSetCreate
 
     global __nvmlDeviceRegisterEvents
-    data["__nvmlDeviceRegisterEvents"] = <_cyb_intptr_t>__nvmlDeviceRegisterEvents
+    data["__nvmlDeviceRegisterEvents"] = <intptr_t>__nvmlDeviceRegisterEvents
 
     global __nvmlDeviceGetSupportedEventTypes
-    data["__nvmlDeviceGetSupportedEventTypes"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedEventTypes
+    data["__nvmlDeviceGetSupportedEventTypes"] = <intptr_t>__nvmlDeviceGetSupportedEventTypes
 
     global __nvmlEventSetWait_v2
-    data["__nvmlEventSetWait_v2"] = <_cyb_intptr_t>__nvmlEventSetWait_v2
+    data["__nvmlEventSetWait_v2"] = <intptr_t>__nvmlEventSetWait_v2
 
     global __nvmlEventSetFree
-    data["__nvmlEventSetFree"] = <_cyb_intptr_t>__nvmlEventSetFree
+    data["__nvmlEventSetFree"] = <intptr_t>__nvmlEventSetFree
 
     global __nvmlSystemEventSetCreate
-    data["__nvmlSystemEventSetCreate"] = <_cyb_intptr_t>__nvmlSystemEventSetCreate
+    data["__nvmlSystemEventSetCreate"] = <intptr_t>__nvmlSystemEventSetCreate
 
     global __nvmlSystemEventSetFree
-    data["__nvmlSystemEventSetFree"] = <_cyb_intptr_t>__nvmlSystemEventSetFree
+    data["__nvmlSystemEventSetFree"] = <intptr_t>__nvmlSystemEventSetFree
 
     global __nvmlSystemRegisterEvents
-    data["__nvmlSystemRegisterEvents"] = <_cyb_intptr_t>__nvmlSystemRegisterEvents
+    data["__nvmlSystemRegisterEvents"] = <intptr_t>__nvmlSystemRegisterEvents
 
     global __nvmlSystemEventSetWait
-    data["__nvmlSystemEventSetWait"] = <_cyb_intptr_t>__nvmlSystemEventSetWait
+    data["__nvmlSystemEventSetWait"] = <intptr_t>__nvmlSystemEventSetWait
 
     global __nvmlDeviceModifyDrainState
-    data["__nvmlDeviceModifyDrainState"] = <_cyb_intptr_t>__nvmlDeviceModifyDrainState
+    data["__nvmlDeviceModifyDrainState"] = <intptr_t>__nvmlDeviceModifyDrainState
 
     global __nvmlDeviceQueryDrainState
-    data["__nvmlDeviceQueryDrainState"] = <_cyb_intptr_t>__nvmlDeviceQueryDrainState
+    data["__nvmlDeviceQueryDrainState"] = <intptr_t>__nvmlDeviceQueryDrainState
 
     global __nvmlDeviceRemoveGpu_v2
-    data["__nvmlDeviceRemoveGpu_v2"] = <_cyb_intptr_t>__nvmlDeviceRemoveGpu_v2
+    data["__nvmlDeviceRemoveGpu_v2"] = <intptr_t>__nvmlDeviceRemoveGpu_v2
 
     global __nvmlDeviceDiscoverGpus
-    data["__nvmlDeviceDiscoverGpus"] = <_cyb_intptr_t>__nvmlDeviceDiscoverGpus
+    data["__nvmlDeviceDiscoverGpus"] = <intptr_t>__nvmlDeviceDiscoverGpus
 
     global __nvmlDeviceGetFieldValues
-    data["__nvmlDeviceGetFieldValues"] = <_cyb_intptr_t>__nvmlDeviceGetFieldValues
+    data["__nvmlDeviceGetFieldValues"] = <intptr_t>__nvmlDeviceGetFieldValues
 
     global __nvmlDeviceClearFieldValues
-    data["__nvmlDeviceClearFieldValues"] = <_cyb_intptr_t>__nvmlDeviceClearFieldValues
+    data["__nvmlDeviceClearFieldValues"] = <intptr_t>__nvmlDeviceClearFieldValues
 
     global __nvmlDeviceGetVirtualizationMode
-    data["__nvmlDeviceGetVirtualizationMode"] = <_cyb_intptr_t>__nvmlDeviceGetVirtualizationMode
+    data["__nvmlDeviceGetVirtualizationMode"] = <intptr_t>__nvmlDeviceGetVirtualizationMode
 
     global __nvmlDeviceGetHostVgpuMode
-    data["__nvmlDeviceGetHostVgpuMode"] = <_cyb_intptr_t>__nvmlDeviceGetHostVgpuMode
+    data["__nvmlDeviceGetHostVgpuMode"] = <intptr_t>__nvmlDeviceGetHostVgpuMode
 
     global __nvmlDeviceSetVirtualizationMode
-    data["__nvmlDeviceSetVirtualizationMode"] = <_cyb_intptr_t>__nvmlDeviceSetVirtualizationMode
+    data["__nvmlDeviceSetVirtualizationMode"] = <intptr_t>__nvmlDeviceSetVirtualizationMode
 
     global __nvmlDeviceGetVgpuHeterogeneousMode
-    data["__nvmlDeviceGetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuHeterogeneousMode
+    data["__nvmlDeviceGetVgpuHeterogeneousMode"] = <intptr_t>__nvmlDeviceGetVgpuHeterogeneousMode
 
     global __nvmlDeviceSetVgpuHeterogeneousMode
-    data["__nvmlDeviceSetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuHeterogeneousMode
+    data["__nvmlDeviceSetVgpuHeterogeneousMode"] = <intptr_t>__nvmlDeviceSetVgpuHeterogeneousMode
 
     global __nvmlVgpuInstanceGetPlacementId
-    data["__nvmlVgpuInstanceGetPlacementId"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetPlacementId
+    data["__nvmlVgpuInstanceGetPlacementId"] = <intptr_t>__nvmlVgpuInstanceGetPlacementId
 
     global __nvmlDeviceGetVgpuTypeSupportedPlacements
-    data["__nvmlDeviceGetVgpuTypeSupportedPlacements"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuTypeSupportedPlacements
+    data["__nvmlDeviceGetVgpuTypeSupportedPlacements"] = <intptr_t>__nvmlDeviceGetVgpuTypeSupportedPlacements
 
     global __nvmlDeviceGetVgpuTypeCreatablePlacements
-    data["__nvmlDeviceGetVgpuTypeCreatablePlacements"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuTypeCreatablePlacements
+    data["__nvmlDeviceGetVgpuTypeCreatablePlacements"] = <intptr_t>__nvmlDeviceGetVgpuTypeCreatablePlacements
 
     global __nvmlVgpuTypeGetGspHeapSize
-    data["__nvmlVgpuTypeGetGspHeapSize"] = <_cyb_intptr_t>__nvmlVgpuTypeGetGspHeapSize
+    data["__nvmlVgpuTypeGetGspHeapSize"] = <intptr_t>__nvmlVgpuTypeGetGspHeapSize
 
     global __nvmlVgpuTypeGetFbReservation
-    data["__nvmlVgpuTypeGetFbReservation"] = <_cyb_intptr_t>__nvmlVgpuTypeGetFbReservation
+    data["__nvmlVgpuTypeGetFbReservation"] = <intptr_t>__nvmlVgpuTypeGetFbReservation
 
     global __nvmlVgpuInstanceGetRuntimeStateSize
-    data["__nvmlVgpuInstanceGetRuntimeStateSize"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetRuntimeStateSize
+    data["__nvmlVgpuInstanceGetRuntimeStateSize"] = <intptr_t>__nvmlVgpuInstanceGetRuntimeStateSize
 
     global __nvmlDeviceSetVgpuCapabilities
-    data["__nvmlDeviceSetVgpuCapabilities"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuCapabilities
+    data["__nvmlDeviceSetVgpuCapabilities"] = <intptr_t>__nvmlDeviceSetVgpuCapabilities
 
     global __nvmlDeviceGetGridLicensableFeatures_v4
-    data["__nvmlDeviceGetGridLicensableFeatures_v4"] = <_cyb_intptr_t>__nvmlDeviceGetGridLicensableFeatures_v4
+    data["__nvmlDeviceGetGridLicensableFeatures_v4"] = <intptr_t>__nvmlDeviceGetGridLicensableFeatures_v4
 
     global __nvmlGetVgpuDriverCapabilities
-    data["__nvmlGetVgpuDriverCapabilities"] = <_cyb_intptr_t>__nvmlGetVgpuDriverCapabilities
+    data["__nvmlGetVgpuDriverCapabilities"] = <intptr_t>__nvmlGetVgpuDriverCapabilities
 
     global __nvmlDeviceGetVgpuCapabilities
-    data["__nvmlDeviceGetVgpuCapabilities"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuCapabilities
+    data["__nvmlDeviceGetVgpuCapabilities"] = <intptr_t>__nvmlDeviceGetVgpuCapabilities
 
     global __nvmlDeviceGetSupportedVgpus
-    data["__nvmlDeviceGetSupportedVgpus"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedVgpus
+    data["__nvmlDeviceGetSupportedVgpus"] = <intptr_t>__nvmlDeviceGetSupportedVgpus
 
     global __nvmlDeviceGetCreatableVgpus
-    data["__nvmlDeviceGetCreatableVgpus"] = <_cyb_intptr_t>__nvmlDeviceGetCreatableVgpus
+    data["__nvmlDeviceGetCreatableVgpus"] = <intptr_t>__nvmlDeviceGetCreatableVgpus
 
     global __nvmlVgpuTypeGetClass
-    data["__nvmlVgpuTypeGetClass"] = <_cyb_intptr_t>__nvmlVgpuTypeGetClass
+    data["__nvmlVgpuTypeGetClass"] = <intptr_t>__nvmlVgpuTypeGetClass
 
     global __nvmlVgpuTypeGetName
-    data["__nvmlVgpuTypeGetName"] = <_cyb_intptr_t>__nvmlVgpuTypeGetName
+    data["__nvmlVgpuTypeGetName"] = <intptr_t>__nvmlVgpuTypeGetName
 
     global __nvmlVgpuTypeGetGpuInstanceProfileId
-    data["__nvmlVgpuTypeGetGpuInstanceProfileId"] = <_cyb_intptr_t>__nvmlVgpuTypeGetGpuInstanceProfileId
+    data["__nvmlVgpuTypeGetGpuInstanceProfileId"] = <intptr_t>__nvmlVgpuTypeGetGpuInstanceProfileId
 
     global __nvmlVgpuTypeGetDeviceID
-    data["__nvmlVgpuTypeGetDeviceID"] = <_cyb_intptr_t>__nvmlVgpuTypeGetDeviceID
+    data["__nvmlVgpuTypeGetDeviceID"] = <intptr_t>__nvmlVgpuTypeGetDeviceID
 
     global __nvmlVgpuTypeGetFramebufferSize
-    data["__nvmlVgpuTypeGetFramebufferSize"] = <_cyb_intptr_t>__nvmlVgpuTypeGetFramebufferSize
+    data["__nvmlVgpuTypeGetFramebufferSize"] = <intptr_t>__nvmlVgpuTypeGetFramebufferSize
 
     global __nvmlVgpuTypeGetNumDisplayHeads
-    data["__nvmlVgpuTypeGetNumDisplayHeads"] = <_cyb_intptr_t>__nvmlVgpuTypeGetNumDisplayHeads
+    data["__nvmlVgpuTypeGetNumDisplayHeads"] = <intptr_t>__nvmlVgpuTypeGetNumDisplayHeads
 
     global __nvmlVgpuTypeGetResolution
-    data["__nvmlVgpuTypeGetResolution"] = <_cyb_intptr_t>__nvmlVgpuTypeGetResolution
+    data["__nvmlVgpuTypeGetResolution"] = <intptr_t>__nvmlVgpuTypeGetResolution
 
     global __nvmlVgpuTypeGetLicense
-    data["__nvmlVgpuTypeGetLicense"] = <_cyb_intptr_t>__nvmlVgpuTypeGetLicense
+    data["__nvmlVgpuTypeGetLicense"] = <intptr_t>__nvmlVgpuTypeGetLicense
 
     global __nvmlVgpuTypeGetFrameRateLimit
-    data["__nvmlVgpuTypeGetFrameRateLimit"] = <_cyb_intptr_t>__nvmlVgpuTypeGetFrameRateLimit
+    data["__nvmlVgpuTypeGetFrameRateLimit"] = <intptr_t>__nvmlVgpuTypeGetFrameRateLimit
 
     global __nvmlVgpuTypeGetMaxInstances
-    data["__nvmlVgpuTypeGetMaxInstances"] = <_cyb_intptr_t>__nvmlVgpuTypeGetMaxInstances
+    data["__nvmlVgpuTypeGetMaxInstances"] = <intptr_t>__nvmlVgpuTypeGetMaxInstances
 
     global __nvmlVgpuTypeGetMaxInstancesPerVm
-    data["__nvmlVgpuTypeGetMaxInstancesPerVm"] = <_cyb_intptr_t>__nvmlVgpuTypeGetMaxInstancesPerVm
+    data["__nvmlVgpuTypeGetMaxInstancesPerVm"] = <intptr_t>__nvmlVgpuTypeGetMaxInstancesPerVm
 
     global __nvmlVgpuTypeGetBAR1Info
-    data["__nvmlVgpuTypeGetBAR1Info"] = <_cyb_intptr_t>__nvmlVgpuTypeGetBAR1Info
+    data["__nvmlVgpuTypeGetBAR1Info"] = <intptr_t>__nvmlVgpuTypeGetBAR1Info
 
     global __nvmlDeviceGetActiveVgpus
-    data["__nvmlDeviceGetActiveVgpus"] = <_cyb_intptr_t>__nvmlDeviceGetActiveVgpus
+    data["__nvmlDeviceGetActiveVgpus"] = <intptr_t>__nvmlDeviceGetActiveVgpus
 
     global __nvmlVgpuInstanceGetVmID
-    data["__nvmlVgpuInstanceGetVmID"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetVmID
+    data["__nvmlVgpuInstanceGetVmID"] = <intptr_t>__nvmlVgpuInstanceGetVmID
 
     global __nvmlVgpuInstanceGetUUID
-    data["__nvmlVgpuInstanceGetUUID"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetUUID
+    data["__nvmlVgpuInstanceGetUUID"] = <intptr_t>__nvmlVgpuInstanceGetUUID
 
     global __nvmlVgpuInstanceGetVmDriverVersion
-    data["__nvmlVgpuInstanceGetVmDriverVersion"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetVmDriverVersion
+    data["__nvmlVgpuInstanceGetVmDriverVersion"] = <intptr_t>__nvmlVgpuInstanceGetVmDriverVersion
 
     global __nvmlVgpuInstanceGetFbUsage
-    data["__nvmlVgpuInstanceGetFbUsage"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFbUsage
+    data["__nvmlVgpuInstanceGetFbUsage"] = <intptr_t>__nvmlVgpuInstanceGetFbUsage
 
     global __nvmlVgpuInstanceGetLicenseStatus
-    data["__nvmlVgpuInstanceGetLicenseStatus"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetLicenseStatus
+    data["__nvmlVgpuInstanceGetLicenseStatus"] = <intptr_t>__nvmlVgpuInstanceGetLicenseStatus
 
     global __nvmlVgpuInstanceGetType
-    data["__nvmlVgpuInstanceGetType"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetType
+    data["__nvmlVgpuInstanceGetType"] = <intptr_t>__nvmlVgpuInstanceGetType
 
     global __nvmlVgpuInstanceGetFrameRateLimit
-    data["__nvmlVgpuInstanceGetFrameRateLimit"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFrameRateLimit
+    data["__nvmlVgpuInstanceGetFrameRateLimit"] = <intptr_t>__nvmlVgpuInstanceGetFrameRateLimit
 
     global __nvmlVgpuInstanceGetEccMode
-    data["__nvmlVgpuInstanceGetEccMode"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEccMode
+    data["__nvmlVgpuInstanceGetEccMode"] = <intptr_t>__nvmlVgpuInstanceGetEccMode
 
     global __nvmlVgpuInstanceGetEncoderCapacity
-    data["__nvmlVgpuInstanceGetEncoderCapacity"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEncoderCapacity
+    data["__nvmlVgpuInstanceGetEncoderCapacity"] = <intptr_t>__nvmlVgpuInstanceGetEncoderCapacity
 
     global __nvmlVgpuInstanceSetEncoderCapacity
-    data["__nvmlVgpuInstanceSetEncoderCapacity"] = <_cyb_intptr_t>__nvmlVgpuInstanceSetEncoderCapacity
+    data["__nvmlVgpuInstanceSetEncoderCapacity"] = <intptr_t>__nvmlVgpuInstanceSetEncoderCapacity
 
     global __nvmlVgpuInstanceGetEncoderStats
-    data["__nvmlVgpuInstanceGetEncoderStats"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEncoderStats
+    data["__nvmlVgpuInstanceGetEncoderStats"] = <intptr_t>__nvmlVgpuInstanceGetEncoderStats
 
     global __nvmlVgpuInstanceGetEncoderSessions
-    data["__nvmlVgpuInstanceGetEncoderSessions"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEncoderSessions
+    data["__nvmlVgpuInstanceGetEncoderSessions"] = <intptr_t>__nvmlVgpuInstanceGetEncoderSessions
 
     global __nvmlVgpuInstanceGetFBCStats
-    data["__nvmlVgpuInstanceGetFBCStats"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFBCStats
+    data["__nvmlVgpuInstanceGetFBCStats"] = <intptr_t>__nvmlVgpuInstanceGetFBCStats
 
     global __nvmlVgpuInstanceGetFBCSessions
-    data["__nvmlVgpuInstanceGetFBCSessions"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFBCSessions
+    data["__nvmlVgpuInstanceGetFBCSessions"] = <intptr_t>__nvmlVgpuInstanceGetFBCSessions
 
     global __nvmlVgpuInstanceGetGpuInstanceId
-    data["__nvmlVgpuInstanceGetGpuInstanceId"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetGpuInstanceId
+    data["__nvmlVgpuInstanceGetGpuInstanceId"] = <intptr_t>__nvmlVgpuInstanceGetGpuInstanceId
 
     global __nvmlVgpuInstanceGetGpuPciId
-    data["__nvmlVgpuInstanceGetGpuPciId"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetGpuPciId
+    data["__nvmlVgpuInstanceGetGpuPciId"] = <intptr_t>__nvmlVgpuInstanceGetGpuPciId
 
     global __nvmlVgpuTypeGetCapabilities
-    data["__nvmlVgpuTypeGetCapabilities"] = <_cyb_intptr_t>__nvmlVgpuTypeGetCapabilities
+    data["__nvmlVgpuTypeGetCapabilities"] = <intptr_t>__nvmlVgpuTypeGetCapabilities
 
     global __nvmlVgpuInstanceGetMdevUUID
-    data["__nvmlVgpuInstanceGetMdevUUID"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetMdevUUID
+    data["__nvmlVgpuInstanceGetMdevUUID"] = <intptr_t>__nvmlVgpuInstanceGetMdevUUID
 
     global __nvmlGpuInstanceGetCreatableVgpus
-    data["__nvmlGpuInstanceGetCreatableVgpus"] = <_cyb_intptr_t>__nvmlGpuInstanceGetCreatableVgpus
+    data["__nvmlGpuInstanceGetCreatableVgpus"] = <intptr_t>__nvmlGpuInstanceGetCreatableVgpus
 
     global __nvmlVgpuTypeGetMaxInstancesPerGpuInstance
-    data["__nvmlVgpuTypeGetMaxInstancesPerGpuInstance"] = <_cyb_intptr_t>__nvmlVgpuTypeGetMaxInstancesPerGpuInstance
+    data["__nvmlVgpuTypeGetMaxInstancesPerGpuInstance"] = <intptr_t>__nvmlVgpuTypeGetMaxInstancesPerGpuInstance
 
     global __nvmlGpuInstanceGetActiveVgpus
-    data["__nvmlGpuInstanceGetActiveVgpus"] = <_cyb_intptr_t>__nvmlGpuInstanceGetActiveVgpus
+    data["__nvmlGpuInstanceGetActiveVgpus"] = <intptr_t>__nvmlGpuInstanceGetActiveVgpus
 
     global __nvmlGpuInstanceSetVgpuSchedulerState
-    data["__nvmlGpuInstanceSetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState
+    data["__nvmlGpuInstanceSetVgpuSchedulerState"] = <intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState
 
     global __nvmlGpuInstanceGetVgpuSchedulerState
-    data["__nvmlGpuInstanceGetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState
+    data["__nvmlGpuInstanceGetVgpuSchedulerState"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState
 
     global __nvmlGpuInstanceGetVgpuSchedulerLog
-    data["__nvmlGpuInstanceGetVgpuSchedulerLog"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog
+    data["__nvmlGpuInstanceGetVgpuSchedulerLog"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog
 
     global __nvmlGpuInstanceGetVgpuTypeCreatablePlacements
-    data["__nvmlGpuInstanceGetVgpuTypeCreatablePlacements"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuTypeCreatablePlacements
+    data["__nvmlGpuInstanceGetVgpuTypeCreatablePlacements"] = <intptr_t>__nvmlGpuInstanceGetVgpuTypeCreatablePlacements
 
     global __nvmlGpuInstanceGetVgpuHeterogeneousMode
-    data["__nvmlGpuInstanceGetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuHeterogeneousMode
+    data["__nvmlGpuInstanceGetVgpuHeterogeneousMode"] = <intptr_t>__nvmlGpuInstanceGetVgpuHeterogeneousMode
 
     global __nvmlGpuInstanceSetVgpuHeterogeneousMode
-    data["__nvmlGpuInstanceSetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlGpuInstanceSetVgpuHeterogeneousMode
+    data["__nvmlGpuInstanceSetVgpuHeterogeneousMode"] = <intptr_t>__nvmlGpuInstanceSetVgpuHeterogeneousMode
 
     global __nvmlVgpuInstanceGetMetadata
-    data["__nvmlVgpuInstanceGetMetadata"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetMetadata
+    data["__nvmlVgpuInstanceGetMetadata"] = <intptr_t>__nvmlVgpuInstanceGetMetadata
 
     global __nvmlDeviceGetVgpuMetadata
-    data["__nvmlDeviceGetVgpuMetadata"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuMetadata
+    data["__nvmlDeviceGetVgpuMetadata"] = <intptr_t>__nvmlDeviceGetVgpuMetadata
 
     global __nvmlGetVgpuCompatibility
-    data["__nvmlGetVgpuCompatibility"] = <_cyb_intptr_t>__nvmlGetVgpuCompatibility
+    data["__nvmlGetVgpuCompatibility"] = <intptr_t>__nvmlGetVgpuCompatibility
 
     global __nvmlDeviceGetPgpuMetadataString
-    data["__nvmlDeviceGetPgpuMetadataString"] = <_cyb_intptr_t>__nvmlDeviceGetPgpuMetadataString
+    data["__nvmlDeviceGetPgpuMetadataString"] = <intptr_t>__nvmlDeviceGetPgpuMetadataString
 
     global __nvmlDeviceGetVgpuSchedulerLog
-    data["__nvmlDeviceGetVgpuSchedulerLog"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerLog
+    data["__nvmlDeviceGetVgpuSchedulerLog"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerLog
 
     global __nvmlDeviceGetVgpuSchedulerState
-    data["__nvmlDeviceGetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerState
+    data["__nvmlDeviceGetVgpuSchedulerState"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerState
 
     global __nvmlDeviceGetVgpuSchedulerCapabilities
-    data["__nvmlDeviceGetVgpuSchedulerCapabilities"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerCapabilities
+    data["__nvmlDeviceGetVgpuSchedulerCapabilities"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerCapabilities
 
     global __nvmlDeviceSetVgpuSchedulerState
-    data["__nvmlDeviceSetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuSchedulerState
+    data["__nvmlDeviceSetVgpuSchedulerState"] = <intptr_t>__nvmlDeviceSetVgpuSchedulerState
 
     global __nvmlGetVgpuVersion
-    data["__nvmlGetVgpuVersion"] = <_cyb_intptr_t>__nvmlGetVgpuVersion
+    data["__nvmlGetVgpuVersion"] = <intptr_t>__nvmlGetVgpuVersion
 
     global __nvmlSetVgpuVersion
-    data["__nvmlSetVgpuVersion"] = <_cyb_intptr_t>__nvmlSetVgpuVersion
+    data["__nvmlSetVgpuVersion"] = <intptr_t>__nvmlSetVgpuVersion
 
     global __nvmlDeviceGetVgpuUtilization
-    data["__nvmlDeviceGetVgpuUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuUtilization
+    data["__nvmlDeviceGetVgpuUtilization"] = <intptr_t>__nvmlDeviceGetVgpuUtilization
 
     global __nvmlDeviceGetVgpuInstancesUtilizationInfo
-    data["__nvmlDeviceGetVgpuInstancesUtilizationInfo"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuInstancesUtilizationInfo
+    data["__nvmlDeviceGetVgpuInstancesUtilizationInfo"] = <intptr_t>__nvmlDeviceGetVgpuInstancesUtilizationInfo
 
     global __nvmlDeviceGetVgpuProcessUtilization
-    data["__nvmlDeviceGetVgpuProcessUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuProcessUtilization
+    data["__nvmlDeviceGetVgpuProcessUtilization"] = <intptr_t>__nvmlDeviceGetVgpuProcessUtilization
 
     global __nvmlDeviceGetVgpuProcessesUtilizationInfo
-    data["__nvmlDeviceGetVgpuProcessesUtilizationInfo"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuProcessesUtilizationInfo
+    data["__nvmlDeviceGetVgpuProcessesUtilizationInfo"] = <intptr_t>__nvmlDeviceGetVgpuProcessesUtilizationInfo
 
     global __nvmlVgpuInstanceGetAccountingMode
-    data["__nvmlVgpuInstanceGetAccountingMode"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetAccountingMode
+    data["__nvmlVgpuInstanceGetAccountingMode"] = <intptr_t>__nvmlVgpuInstanceGetAccountingMode
 
     global __nvmlVgpuInstanceGetAccountingPids
-    data["__nvmlVgpuInstanceGetAccountingPids"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetAccountingPids
+    data["__nvmlVgpuInstanceGetAccountingPids"] = <intptr_t>__nvmlVgpuInstanceGetAccountingPids
 
     global __nvmlVgpuInstanceGetAccountingStats
-    data["__nvmlVgpuInstanceGetAccountingStats"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetAccountingStats
+    data["__nvmlVgpuInstanceGetAccountingStats"] = <intptr_t>__nvmlVgpuInstanceGetAccountingStats
 
     global __nvmlVgpuInstanceClearAccountingPids
-    data["__nvmlVgpuInstanceClearAccountingPids"] = <_cyb_intptr_t>__nvmlVgpuInstanceClearAccountingPids
+    data["__nvmlVgpuInstanceClearAccountingPids"] = <intptr_t>__nvmlVgpuInstanceClearAccountingPids
 
     global __nvmlVgpuInstanceGetLicenseInfo_v2
-    data["__nvmlVgpuInstanceGetLicenseInfo_v2"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetLicenseInfo_v2
+    data["__nvmlVgpuInstanceGetLicenseInfo_v2"] = <intptr_t>__nvmlVgpuInstanceGetLicenseInfo_v2
 
     global __nvmlGetExcludedDeviceCount
-    data["__nvmlGetExcludedDeviceCount"] = <_cyb_intptr_t>__nvmlGetExcludedDeviceCount
+    data["__nvmlGetExcludedDeviceCount"] = <intptr_t>__nvmlGetExcludedDeviceCount
 
     global __nvmlGetExcludedDeviceInfoByIndex
-    data["__nvmlGetExcludedDeviceInfoByIndex"] = <_cyb_intptr_t>__nvmlGetExcludedDeviceInfoByIndex
+    data["__nvmlGetExcludedDeviceInfoByIndex"] = <intptr_t>__nvmlGetExcludedDeviceInfoByIndex
 
     global __nvmlDeviceSetMigMode
-    data["__nvmlDeviceSetMigMode"] = <_cyb_intptr_t>__nvmlDeviceSetMigMode
+    data["__nvmlDeviceSetMigMode"] = <intptr_t>__nvmlDeviceSetMigMode
 
     global __nvmlDeviceGetMigMode
-    data["__nvmlDeviceGetMigMode"] = <_cyb_intptr_t>__nvmlDeviceGetMigMode
+    data["__nvmlDeviceGetMigMode"] = <intptr_t>__nvmlDeviceGetMigMode
 
     global __nvmlDeviceGetGpuInstanceProfileInfoV
-    data["__nvmlDeviceGetGpuInstanceProfileInfoV"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoV
+    data["__nvmlDeviceGetGpuInstanceProfileInfoV"] = <intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoV
 
     global __nvmlDeviceGetGpuInstancePossiblePlacements_v2
-    data["__nvmlDeviceGetGpuInstancePossiblePlacements_v2"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstancePossiblePlacements_v2
+    data["__nvmlDeviceGetGpuInstancePossiblePlacements_v2"] = <intptr_t>__nvmlDeviceGetGpuInstancePossiblePlacements_v2
 
     global __nvmlDeviceGetGpuInstanceRemainingCapacity
-    data["__nvmlDeviceGetGpuInstanceRemainingCapacity"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceRemainingCapacity
+    data["__nvmlDeviceGetGpuInstanceRemainingCapacity"] = <intptr_t>__nvmlDeviceGetGpuInstanceRemainingCapacity
 
     global __nvmlDeviceCreateGpuInstance
-    data["__nvmlDeviceCreateGpuInstance"] = <_cyb_intptr_t>__nvmlDeviceCreateGpuInstance
+    data["__nvmlDeviceCreateGpuInstance"] = <intptr_t>__nvmlDeviceCreateGpuInstance
 
     global __nvmlDeviceCreateGpuInstanceWithPlacement
-    data["__nvmlDeviceCreateGpuInstanceWithPlacement"] = <_cyb_intptr_t>__nvmlDeviceCreateGpuInstanceWithPlacement
+    data["__nvmlDeviceCreateGpuInstanceWithPlacement"] = <intptr_t>__nvmlDeviceCreateGpuInstanceWithPlacement
 
     global __nvmlGpuInstanceDestroy
-    data["__nvmlGpuInstanceDestroy"] = <_cyb_intptr_t>__nvmlGpuInstanceDestroy
+    data["__nvmlGpuInstanceDestroy"] = <intptr_t>__nvmlGpuInstanceDestroy
 
     global __nvmlDeviceGetGpuInstances
-    data["__nvmlDeviceGetGpuInstances"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstances
+    data["__nvmlDeviceGetGpuInstances"] = <intptr_t>__nvmlDeviceGetGpuInstances
 
     global __nvmlDeviceGetGpuInstanceById
-    data["__nvmlDeviceGetGpuInstanceById"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceById
+    data["__nvmlDeviceGetGpuInstanceById"] = <intptr_t>__nvmlDeviceGetGpuInstanceById
 
     global __nvmlGpuInstanceGetInfo
-    data["__nvmlGpuInstanceGetInfo"] = <_cyb_intptr_t>__nvmlGpuInstanceGetInfo
+    data["__nvmlGpuInstanceGetInfo"] = <intptr_t>__nvmlGpuInstanceGetInfo
 
     global __nvmlGpuInstanceGetComputeInstanceProfileInfoV
-    data["__nvmlGpuInstanceGetComputeInstanceProfileInfoV"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstanceProfileInfoV
+    data["__nvmlGpuInstanceGetComputeInstanceProfileInfoV"] = <intptr_t>__nvmlGpuInstanceGetComputeInstanceProfileInfoV
 
     global __nvmlGpuInstanceGetComputeInstanceRemainingCapacity
-    data["__nvmlGpuInstanceGetComputeInstanceRemainingCapacity"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstanceRemainingCapacity
+    data["__nvmlGpuInstanceGetComputeInstanceRemainingCapacity"] = <intptr_t>__nvmlGpuInstanceGetComputeInstanceRemainingCapacity
 
     global __nvmlGpuInstanceGetComputeInstancePossiblePlacements
-    data["__nvmlGpuInstanceGetComputeInstancePossiblePlacements"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstancePossiblePlacements
+    data["__nvmlGpuInstanceGetComputeInstancePossiblePlacements"] = <intptr_t>__nvmlGpuInstanceGetComputeInstancePossiblePlacements
 
     global __nvmlGpuInstanceCreateComputeInstance
-    data["__nvmlGpuInstanceCreateComputeInstance"] = <_cyb_intptr_t>__nvmlGpuInstanceCreateComputeInstance
+    data["__nvmlGpuInstanceCreateComputeInstance"] = <intptr_t>__nvmlGpuInstanceCreateComputeInstance
 
     global __nvmlGpuInstanceCreateComputeInstanceWithPlacement
-    data["__nvmlGpuInstanceCreateComputeInstanceWithPlacement"] = <_cyb_intptr_t>__nvmlGpuInstanceCreateComputeInstanceWithPlacement
+    data["__nvmlGpuInstanceCreateComputeInstanceWithPlacement"] = <intptr_t>__nvmlGpuInstanceCreateComputeInstanceWithPlacement
 
     global __nvmlComputeInstanceDestroy
-    data["__nvmlComputeInstanceDestroy"] = <_cyb_intptr_t>__nvmlComputeInstanceDestroy
+    data["__nvmlComputeInstanceDestroy"] = <intptr_t>__nvmlComputeInstanceDestroy
 
     global __nvmlGpuInstanceGetComputeInstances
-    data["__nvmlGpuInstanceGetComputeInstances"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstances
+    data["__nvmlGpuInstanceGetComputeInstances"] = <intptr_t>__nvmlGpuInstanceGetComputeInstances
 
     global __nvmlGpuInstanceGetComputeInstanceById
-    data["__nvmlGpuInstanceGetComputeInstanceById"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstanceById
+    data["__nvmlGpuInstanceGetComputeInstanceById"] = <intptr_t>__nvmlGpuInstanceGetComputeInstanceById
 
     global __nvmlComputeInstanceGetInfo_v2
-    data["__nvmlComputeInstanceGetInfo_v2"] = <_cyb_intptr_t>__nvmlComputeInstanceGetInfo_v2
+    data["__nvmlComputeInstanceGetInfo_v2"] = <intptr_t>__nvmlComputeInstanceGetInfo_v2
 
     global __nvmlDeviceIsMigDeviceHandle
-    data["__nvmlDeviceIsMigDeviceHandle"] = <_cyb_intptr_t>__nvmlDeviceIsMigDeviceHandle
+    data["__nvmlDeviceIsMigDeviceHandle"] = <intptr_t>__nvmlDeviceIsMigDeviceHandle
 
     global __nvmlDeviceGetGpuInstanceId
-    data["__nvmlDeviceGetGpuInstanceId"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceId
+    data["__nvmlDeviceGetGpuInstanceId"] = <intptr_t>__nvmlDeviceGetGpuInstanceId
 
     global __nvmlDeviceGetComputeInstanceId
-    data["__nvmlDeviceGetComputeInstanceId"] = <_cyb_intptr_t>__nvmlDeviceGetComputeInstanceId
+    data["__nvmlDeviceGetComputeInstanceId"] = <intptr_t>__nvmlDeviceGetComputeInstanceId
 
     global __nvmlDeviceGetMaxMigDeviceCount
-    data["__nvmlDeviceGetMaxMigDeviceCount"] = <_cyb_intptr_t>__nvmlDeviceGetMaxMigDeviceCount
+    data["__nvmlDeviceGetMaxMigDeviceCount"] = <intptr_t>__nvmlDeviceGetMaxMigDeviceCount
 
     global __nvmlDeviceGetMigDeviceHandleByIndex
-    data["__nvmlDeviceGetMigDeviceHandleByIndex"] = <_cyb_intptr_t>__nvmlDeviceGetMigDeviceHandleByIndex
+    data["__nvmlDeviceGetMigDeviceHandleByIndex"] = <intptr_t>__nvmlDeviceGetMigDeviceHandleByIndex
 
     global __nvmlDeviceGetDeviceHandleFromMigDeviceHandle
-    data["__nvmlDeviceGetDeviceHandleFromMigDeviceHandle"] = <_cyb_intptr_t>__nvmlDeviceGetDeviceHandleFromMigDeviceHandle
+    data["__nvmlDeviceGetDeviceHandleFromMigDeviceHandle"] = <intptr_t>__nvmlDeviceGetDeviceHandleFromMigDeviceHandle
 
     global __nvmlDeviceGetCapabilities
-    data["__nvmlDeviceGetCapabilities"] = <_cyb_intptr_t>__nvmlDeviceGetCapabilities
+    data["__nvmlDeviceGetCapabilities"] = <intptr_t>__nvmlDeviceGetCapabilities
 
     global __nvmlDevicePowerSmoothingActivatePresetProfile
-    data["__nvmlDevicePowerSmoothingActivatePresetProfile"] = <_cyb_intptr_t>__nvmlDevicePowerSmoothingActivatePresetProfile
+    data["__nvmlDevicePowerSmoothingActivatePresetProfile"] = <intptr_t>__nvmlDevicePowerSmoothingActivatePresetProfile
 
     global __nvmlDevicePowerSmoothingUpdatePresetProfileParam
-    data["__nvmlDevicePowerSmoothingUpdatePresetProfileParam"] = <_cyb_intptr_t>__nvmlDevicePowerSmoothingUpdatePresetProfileParam
+    data["__nvmlDevicePowerSmoothingUpdatePresetProfileParam"] = <intptr_t>__nvmlDevicePowerSmoothingUpdatePresetProfileParam
 
     global __nvmlDevicePowerSmoothingSetState
-    data["__nvmlDevicePowerSmoothingSetState"] = <_cyb_intptr_t>__nvmlDevicePowerSmoothingSetState
+    data["__nvmlDevicePowerSmoothingSetState"] = <intptr_t>__nvmlDevicePowerSmoothingSetState
 
     global __nvmlDeviceGetAddressingMode
-    data["__nvmlDeviceGetAddressingMode"] = <_cyb_intptr_t>__nvmlDeviceGetAddressingMode
+    data["__nvmlDeviceGetAddressingMode"] = <intptr_t>__nvmlDeviceGetAddressingMode
 
     global __nvmlDeviceGetRepairStatus
-    data["__nvmlDeviceGetRepairStatus"] = <_cyb_intptr_t>__nvmlDeviceGetRepairStatus
+    data["__nvmlDeviceGetRepairStatus"] = <intptr_t>__nvmlDeviceGetRepairStatus
 
     global __nvmlDeviceGetPowerMizerMode_v1
-    data["__nvmlDeviceGetPowerMizerMode_v1"] = <_cyb_intptr_t>__nvmlDeviceGetPowerMizerMode_v1
+    data["__nvmlDeviceGetPowerMizerMode_v1"] = <intptr_t>__nvmlDeviceGetPowerMizerMode_v1
 
     global __nvmlDeviceSetPowerMizerMode_v1
-    data["__nvmlDeviceSetPowerMizerMode_v1"] = <_cyb_intptr_t>__nvmlDeviceSetPowerMizerMode_v1
+    data["__nvmlDeviceSetPowerMizerMode_v1"] = <intptr_t>__nvmlDeviceSetPowerMizerMode_v1
 
     global __nvmlDeviceGetPdi
-    data["__nvmlDeviceGetPdi"] = <_cyb_intptr_t>__nvmlDeviceGetPdi
+    data["__nvmlDeviceGetPdi"] = <intptr_t>__nvmlDeviceGetPdi
 
     global __nvmlDeviceSetHostname_v1
-    data["__nvmlDeviceSetHostname_v1"] = <_cyb_intptr_t>__nvmlDeviceSetHostname_v1
+    data["__nvmlDeviceSetHostname_v1"] = <intptr_t>__nvmlDeviceSetHostname_v1
 
     global __nvmlDeviceGetHostname_v1
-    data["__nvmlDeviceGetHostname_v1"] = <_cyb_intptr_t>__nvmlDeviceGetHostname_v1
+    data["__nvmlDeviceGetHostname_v1"] = <intptr_t>__nvmlDeviceGetHostname_v1
 
     global __nvmlDeviceGetNvLinkInfo
-    data["__nvmlDeviceGetNvLinkInfo"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkInfo
+    data["__nvmlDeviceGetNvLinkInfo"] = <intptr_t>__nvmlDeviceGetNvLinkInfo
 
     global __nvmlDeviceReadWritePRM_v1
-    data["__nvmlDeviceReadWritePRM_v1"] = <_cyb_intptr_t>__nvmlDeviceReadWritePRM_v1
+    data["__nvmlDeviceReadWritePRM_v1"] = <intptr_t>__nvmlDeviceReadWritePRM_v1
 
     global __nvmlDeviceGetGpuInstanceProfileInfoByIdV
-    data["__nvmlDeviceGetGpuInstanceProfileInfoByIdV"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoByIdV
+    data["__nvmlDeviceGetGpuInstanceProfileInfoByIdV"] = <intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoByIdV
 
     global __nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts
-    data["__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts"] = <_cyb_intptr_t>__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts
+    data["__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts"] = <intptr_t>__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts
 
     global __nvmlDeviceGetUnrepairableMemoryFlag_v1
-    data["__nvmlDeviceGetUnrepairableMemoryFlag_v1"] = <_cyb_intptr_t>__nvmlDeviceGetUnrepairableMemoryFlag_v1
+    data["__nvmlDeviceGetUnrepairableMemoryFlag_v1"] = <intptr_t>__nvmlDeviceGetUnrepairableMemoryFlag_v1
 
     global __nvmlDeviceReadPRMCounters_v1
-    data["__nvmlDeviceReadPRMCounters_v1"] = <_cyb_intptr_t>__nvmlDeviceReadPRMCounters_v1
+    data["__nvmlDeviceReadPRMCounters_v1"] = <intptr_t>__nvmlDeviceReadPRMCounters_v1
 
     global __nvmlDeviceSetRusdSettings_v1
-    data["__nvmlDeviceSetRusdSettings_v1"] = <_cyb_intptr_t>__nvmlDeviceSetRusdSettings_v1
+    data["__nvmlDeviceSetRusdSettings_v1"] = <intptr_t>__nvmlDeviceSetRusdSettings_v1
 
     global __nvmlDeviceVgpuForceGspUnload
-    data["__nvmlDeviceVgpuForceGspUnload"] = <_cyb_intptr_t>__nvmlDeviceVgpuForceGspUnload
+    data["__nvmlDeviceVgpuForceGspUnload"] = <intptr_t>__nvmlDeviceVgpuForceGspUnload
 
     global __nvmlDeviceGetVgpuSchedulerState_v2
-    data["__nvmlDeviceGetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerState_v2
+    data["__nvmlDeviceGetVgpuSchedulerState_v2"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerState_v2
 
     global __nvmlGpuInstanceGetVgpuSchedulerState_v2
-    data["__nvmlGpuInstanceGetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState_v2
+    data["__nvmlGpuInstanceGetVgpuSchedulerState_v2"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState_v2
 
     global __nvmlDeviceGetVgpuSchedulerLog_v2
-    data["__nvmlDeviceGetVgpuSchedulerLog_v2"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerLog_v2
+    data["__nvmlDeviceGetVgpuSchedulerLog_v2"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerLog_v2
 
     global __nvmlGpuInstanceGetVgpuSchedulerLog_v2
-    data["__nvmlGpuInstanceGetVgpuSchedulerLog_v2"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog_v2
+    data["__nvmlGpuInstanceGetVgpuSchedulerLog_v2"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog_v2
 
     global __nvmlDeviceSetVgpuSchedulerState_v2
-    data["__nvmlDeviceSetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuSchedulerState_v2
+    data["__nvmlDeviceSetVgpuSchedulerState_v2"] = <intptr_t>__nvmlDeviceSetVgpuSchedulerState_v2
 
     global __nvmlGpuInstanceSetVgpuSchedulerState_v2
-    data["__nvmlGpuInstanceSetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState_v2
+    data["__nvmlGpuInstanceSetVgpuSchedulerState_v2"] = <intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState_v2
 
     global __nvmlSystemGetCPER_v1
-    data["__nvmlSystemGetCPER_v1"] = <_cyb_intptr_t>__nvmlSystemGetCPER_v1
+    data["__nvmlSystemGetCPER_v1"] = <intptr_t>__nvmlSystemGetCPER_v1
 
     global __nvmlDeviceGetBBXTimeData_v1
-    data["__nvmlDeviceGetBBXTimeData_v1"] = <_cyb_intptr_t>__nvmlDeviceGetBBXTimeData_v1
+    data["__nvmlDeviceGetBBXTimeData_v1"] = <intptr_t>__nvmlDeviceGetBBXTimeData_v1
 
     global __nvmlDeviceGetAccountingStats_v2
-    data["__nvmlDeviceGetAccountingStats_v2"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingStats_v2
+    data["__nvmlDeviceGetAccountingStats_v2"] = <intptr_t>__nvmlDeviceGetAccountingStats_v2
 
     global __nvmlDeviceGetRemappedRows_v2
-    data["__nvmlDeviceGetRemappedRows_v2"] = <_cyb_intptr_t>__nvmlDeviceGetRemappedRows_v2
+    data["__nvmlDeviceGetRemappedRows_v2"] = <intptr_t>__nvmlDeviceGetRemappedRows_v2
 
     global __nvmlDeviceSetAdaptiveTgpMode_v1
-    data["__nvmlDeviceSetAdaptiveTgpMode_v1"] = <_cyb_intptr_t>__nvmlDeviceSetAdaptiveTgpMode_v1
+    data["__nvmlDeviceSetAdaptiveTgpMode_v1"] = <intptr_t>__nvmlDeviceSetAdaptiveTgpMode_v1
 
     global __nvmlDeviceGetAdaptiveTgpModeInfo_v1
-    data["__nvmlDeviceGetAdaptiveTgpModeInfo_v1"] = <_cyb_intptr_t>__nvmlDeviceGetAdaptiveTgpModeInfo_v1
+    data["__nvmlDeviceGetAdaptiveTgpModeInfo_v1"] = <intptr_t>__nvmlDeviceGetAdaptiveTgpModeInfo_v1
 
     global __nvmlDeviceSetMemoryLimits_v1
-    data["__nvmlDeviceSetMemoryLimits_v1"] = <_cyb_intptr_t>__nvmlDeviceSetMemoryLimits_v1
+    data["__nvmlDeviceSetMemoryLimits_v1"] = <intptr_t>__nvmlDeviceSetMemoryLimits_v1
 
     global __nvmlDeviceGetMemoryLimits_v1
-    data["__nvmlDeviceGetMemoryLimits_v1"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryLimits_v1
+    data["__nvmlDeviceGetMemoryLimits_v1"] = <intptr_t>__nvmlDeviceGetMemoryLimits_v1
 
     global __nvmlDeviceGetGpuFabricInfo_v4
-    data["__nvmlDeviceGetGpuFabricInfo_v4"] = <_cyb_intptr_t>__nvmlDeviceGetGpuFabricInfo_v4
+    data["__nvmlDeviceGetGpuFabricInfo_v4"] = <intptr_t>__nvmlDeviceGetGpuFabricInfo_v4
 
     global __nvmlDevicePerfMetricsGetSamples_v1
-    data["__nvmlDevicePerfMetricsGetSamples_v1"] = <_cyb_intptr_t>__nvmlDevicePerfMetricsGetSamples_v1
+    data["__nvmlDevicePerfMetricsGetSamples_v1"] = <intptr_t>__nvmlDevicePerfMetricsGetSamples_v1
 
     global __nvmlDeviceSetNvlinkBwModeAsync_v1
-    data["__nvmlDeviceSetNvlinkBwModeAsync_v1"] = <_cyb_intptr_t>__nvmlDeviceSetNvlinkBwModeAsync_v1
+    data["__nvmlDeviceSetNvlinkBwModeAsync_v1"] = <intptr_t>__nvmlDeviceSetNvlinkBwModeAsync_v1
 
     global __nvmlDeviceGetNvLinkTelemetrySamples_v1
-    data["__nvmlDeviceGetNvLinkTelemetrySamples_v1"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkTelemetrySamples_v1
+    data["__nvmlDeviceGetNvLinkTelemetrySamples_v1"] = <intptr_t>__nvmlDeviceGetNvLinkTelemetrySamples_v1
 
     global __nvmlEventSetRegisterGpuOperationalEvents_v1
-    data["__nvmlEventSetRegisterGpuOperationalEvents_v1"] = <_cyb_intptr_t>__nvmlEventSetRegisterGpuOperationalEvents_v1
+    data["__nvmlEventSetRegisterGpuOperationalEvents_v1"] = <intptr_t>__nvmlEventSetRegisterGpuOperationalEvents_v1
 
     global __nvmlEventSetWait_v3
-    data["__nvmlEventSetWait_v3"] = <_cyb_intptr_t>__nvmlEventSetWait_v3
+    data["__nvmlEventSetWait_v3"] = <intptr_t>__nvmlEventSetWait_v3
 
     global __nvmlEventSetGetContextCount_v1
-    data["__nvmlEventSetGetContextCount_v1"] = <_cyb_intptr_t>__nvmlEventSetGetContextCount_v1
+    data["__nvmlEventSetGetContextCount_v1"] = <intptr_t>__nvmlEventSetGetContextCount_v1
 
     global __nvmlEventSetGetContextInfo_v1
-    data["__nvmlEventSetGetContextInfo_v1"] = <_cyb_intptr_t>__nvmlEventSetGetContextInfo_v1
+    data["__nvmlEventSetGetContextInfo_v1"] = <intptr_t>__nvmlEventSetGetContextInfo_v1
 
     global __nvmlEventSetGetContextData_v1
-    data["__nvmlEventSetGetContextData_v1"] = <_cyb_intptr_t>__nvmlEventSetGetContextData_v1
+    data["__nvmlEventSetGetContextData_v1"] = <intptr_t>__nvmlEventSetGetContextData_v1
 
     global __nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
-    data["__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1"] = <_cyb_intptr_t>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
+    data["__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1"] = <intptr_t>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
 
     global __nvmlDeviceGetBankRemapperStatus_v1
-    data["__nvmlDeviceGetBankRemapperStatus_v1"] = <_cyb_intptr_t>__nvmlDeviceGetBankRemapperStatus_v1
+    data["__nvmlDeviceGetBankRemapperStatus_v1"] = <intptr_t>__nvmlDeviceGetBankRemapperStatus_v1
     _cyb_func_ptrs = data
     return data
 
@@ -7820,54 +7819,54 @@ cdef nvmlReturn_t _nvmlEventSetRegisterGpuOperationalEvents_v1(nvmlEventSet_t ev
         eventSet, config)
 
 
-cdef nvmlReturn_t _nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventData_v2_t* data, unsigned int timeoutms) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventSetWait_v3_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetWait_v3
     _check_or_init_nvml()
     if __nvmlEventSetWait_v3 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetWait_v3 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventData_v2_t*, unsigned int) noexcept nogil>__nvmlEventSetWait_v3)(
-        set, data, timeoutms)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetWait_v3_t*) noexcept nogil>__nvmlEventSetWait_v3)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, unsigned int* count) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, nvmlEventSetGetContextCount_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetContextCount_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetContextCount_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetContextCount_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int*) noexcept nogil>__nvmlEventSetGetContextCount_v1)(
-        set, count)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetContextCount_v1_t*) noexcept nogil>__nvmlEventSetGetContextCount_v1)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, unsigned int index, nvmlOperationalEventContextInfo_v1_t* info) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, nvmlEventSetGetContextInfo_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetContextInfo_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetContextInfo_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetContextInfo_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int, nvmlOperationalEventContextInfo_v1_t*) noexcept nogil>__nvmlEventSetGetContextInfo_v1)(
-        set, index, info)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetContextInfo_v1_t*) noexcept nogil>__nvmlEventSetGetContextInfo_v1)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetContextData_v1(nvmlEventSet_t set, unsigned int index, void* data, unsigned int* dataSize) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetContextData_v1(nvmlEventSet_t set, nvmlEventSetGetContextData_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetContextData_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetContextData_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetContextData_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int, void*, unsigned int*) noexcept nogil>__nvmlEventSetGetContextData_v1)(
-        set, index, data, dataSize)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetContextData_v1_t*) noexcept nogil>__nvmlEventSetGetContextData_v1)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, unsigned int index, nvmlGpuOperationalEventContextLegacyXid_v1_t* xid) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int, nvmlGpuOperationalEventContextLegacyXid_v1_t*) noexcept nogil>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1)(
-        set, index, xid)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t*) noexcept nogil>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1)(
+        set, params)
 
 
 cdef nvmlReturn_t _nvmlDeviceGetBankRemapperStatus_v1(nvmlDevice_t device, nvmlEccBankRemapperStatus_v1_t* pBankRemapperStatus) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
diff --git a/cuda_bindings/cuda/bindings/_internal/nvml_windows.pyx b/cuda_bindings/cuda/bindings/_internal/nvml_windows.pyx
index 7b851e1aa4e..e5a7cf53a78 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvml_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvml_windows.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=10e6cb1d192514ece92e863cbebdde5c60b94cdc58d27a8c2e4cf9af1a27c968
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=5e4dabf79550bbf99149a55b67542f1b6bf20a48f3dbfd922848c16115418f5e
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,10 @@ cdef extern from "<windows.h>":
     ctypedef void* HMODULE
     void* _cyb_GetProcAddress "GetProcAddress"(HMODULE, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uintptr_t,
+)
 
 import threading as _cyb_threading
 
@@ -1570,1114 +1572,1114 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvml()
     cdef dict data = {}
     global __nvmlInit_v2
-    data["__nvmlInit_v2"] = <_cyb_intptr_t>__nvmlInit_v2
+    data["__nvmlInit_v2"] = <intptr_t>__nvmlInit_v2
 
     global __nvmlInitWithFlags
-    data["__nvmlInitWithFlags"] = <_cyb_intptr_t>__nvmlInitWithFlags
+    data["__nvmlInitWithFlags"] = <intptr_t>__nvmlInitWithFlags
 
     global __nvmlShutdown
-    data["__nvmlShutdown"] = <_cyb_intptr_t>__nvmlShutdown
+    data["__nvmlShutdown"] = <intptr_t>__nvmlShutdown
 
     global __nvmlErrorString
-    data["__nvmlErrorString"] = <_cyb_intptr_t>__nvmlErrorString
+    data["__nvmlErrorString"] = <intptr_t>__nvmlErrorString
 
     global __nvmlSystemGetDriverVersion
-    data["__nvmlSystemGetDriverVersion"] = <_cyb_intptr_t>__nvmlSystemGetDriverVersion
+    data["__nvmlSystemGetDriverVersion"] = <intptr_t>__nvmlSystemGetDriverVersion
 
     global __nvmlSystemGetNVMLVersion
-    data["__nvmlSystemGetNVMLVersion"] = <_cyb_intptr_t>__nvmlSystemGetNVMLVersion
+    data["__nvmlSystemGetNVMLVersion"] = <intptr_t>__nvmlSystemGetNVMLVersion
 
     global __nvmlSystemGetCudaDriverVersion
-    data["__nvmlSystemGetCudaDriverVersion"] = <_cyb_intptr_t>__nvmlSystemGetCudaDriverVersion
+    data["__nvmlSystemGetCudaDriverVersion"] = <intptr_t>__nvmlSystemGetCudaDriverVersion
 
     global __nvmlSystemGetCudaDriverVersion_v2
-    data["__nvmlSystemGetCudaDriverVersion_v2"] = <_cyb_intptr_t>__nvmlSystemGetCudaDriverVersion_v2
+    data["__nvmlSystemGetCudaDriverVersion_v2"] = <intptr_t>__nvmlSystemGetCudaDriverVersion_v2
 
     global __nvmlSystemGetProcessName
-    data["__nvmlSystemGetProcessName"] = <_cyb_intptr_t>__nvmlSystemGetProcessName
+    data["__nvmlSystemGetProcessName"] = <intptr_t>__nvmlSystemGetProcessName
 
     global __nvmlSystemGetHicVersion
-    data["__nvmlSystemGetHicVersion"] = <_cyb_intptr_t>__nvmlSystemGetHicVersion
+    data["__nvmlSystemGetHicVersion"] = <intptr_t>__nvmlSystemGetHicVersion
 
     global __nvmlSystemGetTopologyGpuSet
-    data["__nvmlSystemGetTopologyGpuSet"] = <_cyb_intptr_t>__nvmlSystemGetTopologyGpuSet
+    data["__nvmlSystemGetTopologyGpuSet"] = <intptr_t>__nvmlSystemGetTopologyGpuSet
 
     global __nvmlSystemGetDriverBranch
-    data["__nvmlSystemGetDriverBranch"] = <_cyb_intptr_t>__nvmlSystemGetDriverBranch
+    data["__nvmlSystemGetDriverBranch"] = <intptr_t>__nvmlSystemGetDriverBranch
 
     global __nvmlUnitGetCount
-    data["__nvmlUnitGetCount"] = <_cyb_intptr_t>__nvmlUnitGetCount
+    data["__nvmlUnitGetCount"] = <intptr_t>__nvmlUnitGetCount
 
     global __nvmlUnitGetHandleByIndex
-    data["__nvmlUnitGetHandleByIndex"] = <_cyb_intptr_t>__nvmlUnitGetHandleByIndex
+    data["__nvmlUnitGetHandleByIndex"] = <intptr_t>__nvmlUnitGetHandleByIndex
 
     global __nvmlUnitGetUnitInfo
-    data["__nvmlUnitGetUnitInfo"] = <_cyb_intptr_t>__nvmlUnitGetUnitInfo
+    data["__nvmlUnitGetUnitInfo"] = <intptr_t>__nvmlUnitGetUnitInfo
 
     global __nvmlUnitGetLedState
-    data["__nvmlUnitGetLedState"] = <_cyb_intptr_t>__nvmlUnitGetLedState
+    data["__nvmlUnitGetLedState"] = <intptr_t>__nvmlUnitGetLedState
 
     global __nvmlUnitGetPsuInfo
-    data["__nvmlUnitGetPsuInfo"] = <_cyb_intptr_t>__nvmlUnitGetPsuInfo
+    data["__nvmlUnitGetPsuInfo"] = <intptr_t>__nvmlUnitGetPsuInfo
 
     global __nvmlUnitGetTemperature
-    data["__nvmlUnitGetTemperature"] = <_cyb_intptr_t>__nvmlUnitGetTemperature
+    data["__nvmlUnitGetTemperature"] = <intptr_t>__nvmlUnitGetTemperature
 
     global __nvmlUnitGetFanSpeedInfo
-    data["__nvmlUnitGetFanSpeedInfo"] = <_cyb_intptr_t>__nvmlUnitGetFanSpeedInfo
+    data["__nvmlUnitGetFanSpeedInfo"] = <intptr_t>__nvmlUnitGetFanSpeedInfo
 
     global __nvmlUnitGetDevices
-    data["__nvmlUnitGetDevices"] = <_cyb_intptr_t>__nvmlUnitGetDevices
+    data["__nvmlUnitGetDevices"] = <intptr_t>__nvmlUnitGetDevices
 
     global __nvmlDeviceGetCount_v2
-    data["__nvmlDeviceGetCount_v2"] = <_cyb_intptr_t>__nvmlDeviceGetCount_v2
+    data["__nvmlDeviceGetCount_v2"] = <intptr_t>__nvmlDeviceGetCount_v2
 
     global __nvmlDeviceGetAttributes_v2
-    data["__nvmlDeviceGetAttributes_v2"] = <_cyb_intptr_t>__nvmlDeviceGetAttributes_v2
+    data["__nvmlDeviceGetAttributes_v2"] = <intptr_t>__nvmlDeviceGetAttributes_v2
 
     global __nvmlDeviceGetHandleByIndex_v2
-    data["__nvmlDeviceGetHandleByIndex_v2"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByIndex_v2
+    data["__nvmlDeviceGetHandleByIndex_v2"] = <intptr_t>__nvmlDeviceGetHandleByIndex_v2
 
     global __nvmlDeviceGetHandleBySerial
-    data["__nvmlDeviceGetHandleBySerial"] = <_cyb_intptr_t>__nvmlDeviceGetHandleBySerial
+    data["__nvmlDeviceGetHandleBySerial"] = <intptr_t>__nvmlDeviceGetHandleBySerial
 
     global __nvmlDeviceGetHandleByUUID
-    data["__nvmlDeviceGetHandleByUUID"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByUUID
+    data["__nvmlDeviceGetHandleByUUID"] = <intptr_t>__nvmlDeviceGetHandleByUUID
 
     global __nvmlDeviceGetHandleByUUIDV
-    data["__nvmlDeviceGetHandleByUUIDV"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByUUIDV
+    data["__nvmlDeviceGetHandleByUUIDV"] = <intptr_t>__nvmlDeviceGetHandleByUUIDV
 
     global __nvmlDeviceGetHandleByPciBusId_v2
-    data["__nvmlDeviceGetHandleByPciBusId_v2"] = <_cyb_intptr_t>__nvmlDeviceGetHandleByPciBusId_v2
+    data["__nvmlDeviceGetHandleByPciBusId_v2"] = <intptr_t>__nvmlDeviceGetHandleByPciBusId_v2
 
     global __nvmlDeviceGetName
-    data["__nvmlDeviceGetName"] = <_cyb_intptr_t>__nvmlDeviceGetName
+    data["__nvmlDeviceGetName"] = <intptr_t>__nvmlDeviceGetName
 
     global __nvmlDeviceGetBrand
-    data["__nvmlDeviceGetBrand"] = <_cyb_intptr_t>__nvmlDeviceGetBrand
+    data["__nvmlDeviceGetBrand"] = <intptr_t>__nvmlDeviceGetBrand
 
     global __nvmlDeviceGetIndex
-    data["__nvmlDeviceGetIndex"] = <_cyb_intptr_t>__nvmlDeviceGetIndex
+    data["__nvmlDeviceGetIndex"] = <intptr_t>__nvmlDeviceGetIndex
 
     global __nvmlDeviceGetSerial
-    data["__nvmlDeviceGetSerial"] = <_cyb_intptr_t>__nvmlDeviceGetSerial
+    data["__nvmlDeviceGetSerial"] = <intptr_t>__nvmlDeviceGetSerial
 
     global __nvmlDeviceGetModuleId
-    data["__nvmlDeviceGetModuleId"] = <_cyb_intptr_t>__nvmlDeviceGetModuleId
+    data["__nvmlDeviceGetModuleId"] = <intptr_t>__nvmlDeviceGetModuleId
 
     global __nvmlDeviceGetC2cModeInfoV
-    data["__nvmlDeviceGetC2cModeInfoV"] = <_cyb_intptr_t>__nvmlDeviceGetC2cModeInfoV
+    data["__nvmlDeviceGetC2cModeInfoV"] = <intptr_t>__nvmlDeviceGetC2cModeInfoV
 
     global __nvmlDeviceGetMemoryAffinity
-    data["__nvmlDeviceGetMemoryAffinity"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryAffinity
+    data["__nvmlDeviceGetMemoryAffinity"] = <intptr_t>__nvmlDeviceGetMemoryAffinity
 
     global __nvmlDeviceGetCpuAffinityWithinScope
-    data["__nvmlDeviceGetCpuAffinityWithinScope"] = <_cyb_intptr_t>__nvmlDeviceGetCpuAffinityWithinScope
+    data["__nvmlDeviceGetCpuAffinityWithinScope"] = <intptr_t>__nvmlDeviceGetCpuAffinityWithinScope
 
     global __nvmlDeviceGetCpuAffinity
-    data["__nvmlDeviceGetCpuAffinity"] = <_cyb_intptr_t>__nvmlDeviceGetCpuAffinity
+    data["__nvmlDeviceGetCpuAffinity"] = <intptr_t>__nvmlDeviceGetCpuAffinity
 
     global __nvmlDeviceSetCpuAffinity
-    data["__nvmlDeviceSetCpuAffinity"] = <_cyb_intptr_t>__nvmlDeviceSetCpuAffinity
+    data["__nvmlDeviceSetCpuAffinity"] = <intptr_t>__nvmlDeviceSetCpuAffinity
 
     global __nvmlDeviceClearCpuAffinity
-    data["__nvmlDeviceClearCpuAffinity"] = <_cyb_intptr_t>__nvmlDeviceClearCpuAffinity
+    data["__nvmlDeviceClearCpuAffinity"] = <intptr_t>__nvmlDeviceClearCpuAffinity
 
     global __nvmlDeviceGetNumaNodeId
-    data["__nvmlDeviceGetNumaNodeId"] = <_cyb_intptr_t>__nvmlDeviceGetNumaNodeId
+    data["__nvmlDeviceGetNumaNodeId"] = <intptr_t>__nvmlDeviceGetNumaNodeId
 
     global __nvmlDeviceGetTopologyCommonAncestor
-    data["__nvmlDeviceGetTopologyCommonAncestor"] = <_cyb_intptr_t>__nvmlDeviceGetTopologyCommonAncestor
+    data["__nvmlDeviceGetTopologyCommonAncestor"] = <intptr_t>__nvmlDeviceGetTopologyCommonAncestor
 
     global __nvmlDeviceGetTopologyNearestGpus
-    data["__nvmlDeviceGetTopologyNearestGpus"] = <_cyb_intptr_t>__nvmlDeviceGetTopologyNearestGpus
+    data["__nvmlDeviceGetTopologyNearestGpus"] = <intptr_t>__nvmlDeviceGetTopologyNearestGpus
 
     global __nvmlDeviceGetP2PStatus
-    data["__nvmlDeviceGetP2PStatus"] = <_cyb_intptr_t>__nvmlDeviceGetP2PStatus
+    data["__nvmlDeviceGetP2PStatus"] = <intptr_t>__nvmlDeviceGetP2PStatus
 
     global __nvmlDeviceGetUUID
-    data["__nvmlDeviceGetUUID"] = <_cyb_intptr_t>__nvmlDeviceGetUUID
+    data["__nvmlDeviceGetUUID"] = <intptr_t>__nvmlDeviceGetUUID
 
     global __nvmlDeviceGetMinorNumber
-    data["__nvmlDeviceGetMinorNumber"] = <_cyb_intptr_t>__nvmlDeviceGetMinorNumber
+    data["__nvmlDeviceGetMinorNumber"] = <intptr_t>__nvmlDeviceGetMinorNumber
 
     global __nvmlDeviceGetBoardPartNumber
-    data["__nvmlDeviceGetBoardPartNumber"] = <_cyb_intptr_t>__nvmlDeviceGetBoardPartNumber
+    data["__nvmlDeviceGetBoardPartNumber"] = <intptr_t>__nvmlDeviceGetBoardPartNumber
 
     global __nvmlDeviceGetInforomVersion
-    data["__nvmlDeviceGetInforomVersion"] = <_cyb_intptr_t>__nvmlDeviceGetInforomVersion
+    data["__nvmlDeviceGetInforomVersion"] = <intptr_t>__nvmlDeviceGetInforomVersion
 
     global __nvmlDeviceGetInforomImageVersion
-    data["__nvmlDeviceGetInforomImageVersion"] = <_cyb_intptr_t>__nvmlDeviceGetInforomImageVersion
+    data["__nvmlDeviceGetInforomImageVersion"] = <intptr_t>__nvmlDeviceGetInforomImageVersion
 
     global __nvmlDeviceGetInforomConfigurationChecksum
-    data["__nvmlDeviceGetInforomConfigurationChecksum"] = <_cyb_intptr_t>__nvmlDeviceGetInforomConfigurationChecksum
+    data["__nvmlDeviceGetInforomConfigurationChecksum"] = <intptr_t>__nvmlDeviceGetInforomConfigurationChecksum
 
     global __nvmlDeviceValidateInforom
-    data["__nvmlDeviceValidateInforom"] = <_cyb_intptr_t>__nvmlDeviceValidateInforom
+    data["__nvmlDeviceValidateInforom"] = <intptr_t>__nvmlDeviceValidateInforom
 
     global __nvmlDeviceGetLastBBXFlushTime
-    data["__nvmlDeviceGetLastBBXFlushTime"] = <_cyb_intptr_t>__nvmlDeviceGetLastBBXFlushTime
+    data["__nvmlDeviceGetLastBBXFlushTime"] = <intptr_t>__nvmlDeviceGetLastBBXFlushTime
 
     global __nvmlDeviceGetDisplayMode
-    data["__nvmlDeviceGetDisplayMode"] = <_cyb_intptr_t>__nvmlDeviceGetDisplayMode
+    data["__nvmlDeviceGetDisplayMode"] = <intptr_t>__nvmlDeviceGetDisplayMode
 
     global __nvmlDeviceGetDisplayActive
-    data["__nvmlDeviceGetDisplayActive"] = <_cyb_intptr_t>__nvmlDeviceGetDisplayActive
+    data["__nvmlDeviceGetDisplayActive"] = <intptr_t>__nvmlDeviceGetDisplayActive
 
     global __nvmlDeviceGetPersistenceMode
-    data["__nvmlDeviceGetPersistenceMode"] = <_cyb_intptr_t>__nvmlDeviceGetPersistenceMode
+    data["__nvmlDeviceGetPersistenceMode"] = <intptr_t>__nvmlDeviceGetPersistenceMode
 
     global __nvmlDeviceGetPciInfoExt
-    data["__nvmlDeviceGetPciInfoExt"] = <_cyb_intptr_t>__nvmlDeviceGetPciInfoExt
+    data["__nvmlDeviceGetPciInfoExt"] = <intptr_t>__nvmlDeviceGetPciInfoExt
 
     global __nvmlDeviceGetPciInfo_v3
-    data["__nvmlDeviceGetPciInfo_v3"] = <_cyb_intptr_t>__nvmlDeviceGetPciInfo_v3
+    data["__nvmlDeviceGetPciInfo_v3"] = <intptr_t>__nvmlDeviceGetPciInfo_v3
 
     global __nvmlDeviceGetMaxPcieLinkGeneration
-    data["__nvmlDeviceGetMaxPcieLinkGeneration"] = <_cyb_intptr_t>__nvmlDeviceGetMaxPcieLinkGeneration
+    data["__nvmlDeviceGetMaxPcieLinkGeneration"] = <intptr_t>__nvmlDeviceGetMaxPcieLinkGeneration
 
     global __nvmlDeviceGetGpuMaxPcieLinkGeneration
-    data["__nvmlDeviceGetGpuMaxPcieLinkGeneration"] = <_cyb_intptr_t>__nvmlDeviceGetGpuMaxPcieLinkGeneration
+    data["__nvmlDeviceGetGpuMaxPcieLinkGeneration"] = <intptr_t>__nvmlDeviceGetGpuMaxPcieLinkGeneration
 
     global __nvmlDeviceGetMaxPcieLinkWidth
-    data["__nvmlDeviceGetMaxPcieLinkWidth"] = <_cyb_intptr_t>__nvmlDeviceGetMaxPcieLinkWidth
+    data["__nvmlDeviceGetMaxPcieLinkWidth"] = <intptr_t>__nvmlDeviceGetMaxPcieLinkWidth
 
     global __nvmlDeviceGetCurrPcieLinkGeneration
-    data["__nvmlDeviceGetCurrPcieLinkGeneration"] = <_cyb_intptr_t>__nvmlDeviceGetCurrPcieLinkGeneration
+    data["__nvmlDeviceGetCurrPcieLinkGeneration"] = <intptr_t>__nvmlDeviceGetCurrPcieLinkGeneration
 
     global __nvmlDeviceGetCurrPcieLinkWidth
-    data["__nvmlDeviceGetCurrPcieLinkWidth"] = <_cyb_intptr_t>__nvmlDeviceGetCurrPcieLinkWidth
+    data["__nvmlDeviceGetCurrPcieLinkWidth"] = <intptr_t>__nvmlDeviceGetCurrPcieLinkWidth
 
     global __nvmlDeviceGetPcieThroughput
-    data["__nvmlDeviceGetPcieThroughput"] = <_cyb_intptr_t>__nvmlDeviceGetPcieThroughput
+    data["__nvmlDeviceGetPcieThroughput"] = <intptr_t>__nvmlDeviceGetPcieThroughput
 
     global __nvmlDeviceGetPcieReplayCounter
-    data["__nvmlDeviceGetPcieReplayCounter"] = <_cyb_intptr_t>__nvmlDeviceGetPcieReplayCounter
+    data["__nvmlDeviceGetPcieReplayCounter"] = <intptr_t>__nvmlDeviceGetPcieReplayCounter
 
     global __nvmlDeviceGetClockInfo
-    data["__nvmlDeviceGetClockInfo"] = <_cyb_intptr_t>__nvmlDeviceGetClockInfo
+    data["__nvmlDeviceGetClockInfo"] = <intptr_t>__nvmlDeviceGetClockInfo
 
     global __nvmlDeviceGetMaxClockInfo
-    data["__nvmlDeviceGetMaxClockInfo"] = <_cyb_intptr_t>__nvmlDeviceGetMaxClockInfo
+    data["__nvmlDeviceGetMaxClockInfo"] = <intptr_t>__nvmlDeviceGetMaxClockInfo
 
     global __nvmlDeviceGetGpcClkVfOffset
-    data["__nvmlDeviceGetGpcClkVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetGpcClkVfOffset
+    data["__nvmlDeviceGetGpcClkVfOffset"] = <intptr_t>__nvmlDeviceGetGpcClkVfOffset
 
     global __nvmlDeviceGetClock
-    data["__nvmlDeviceGetClock"] = <_cyb_intptr_t>__nvmlDeviceGetClock
+    data["__nvmlDeviceGetClock"] = <intptr_t>__nvmlDeviceGetClock
 
     global __nvmlDeviceGetMaxCustomerBoostClock
-    data["__nvmlDeviceGetMaxCustomerBoostClock"] = <_cyb_intptr_t>__nvmlDeviceGetMaxCustomerBoostClock
+    data["__nvmlDeviceGetMaxCustomerBoostClock"] = <intptr_t>__nvmlDeviceGetMaxCustomerBoostClock
 
     global __nvmlDeviceGetSupportedMemoryClocks
-    data["__nvmlDeviceGetSupportedMemoryClocks"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedMemoryClocks
+    data["__nvmlDeviceGetSupportedMemoryClocks"] = <intptr_t>__nvmlDeviceGetSupportedMemoryClocks
 
     global __nvmlDeviceGetSupportedGraphicsClocks
-    data["__nvmlDeviceGetSupportedGraphicsClocks"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedGraphicsClocks
+    data["__nvmlDeviceGetSupportedGraphicsClocks"] = <intptr_t>__nvmlDeviceGetSupportedGraphicsClocks
 
     global __nvmlDeviceGetAutoBoostedClocksEnabled
-    data["__nvmlDeviceGetAutoBoostedClocksEnabled"] = <_cyb_intptr_t>__nvmlDeviceGetAutoBoostedClocksEnabled
+    data["__nvmlDeviceGetAutoBoostedClocksEnabled"] = <intptr_t>__nvmlDeviceGetAutoBoostedClocksEnabled
 
     global __nvmlDeviceGetFanSpeed
-    data["__nvmlDeviceGetFanSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetFanSpeed
+    data["__nvmlDeviceGetFanSpeed"] = <intptr_t>__nvmlDeviceGetFanSpeed
 
     global __nvmlDeviceGetFanSpeed_v2
-    data["__nvmlDeviceGetFanSpeed_v2"] = <_cyb_intptr_t>__nvmlDeviceGetFanSpeed_v2
+    data["__nvmlDeviceGetFanSpeed_v2"] = <intptr_t>__nvmlDeviceGetFanSpeed_v2
 
     global __nvmlDeviceGetFanSpeedRPM
-    data["__nvmlDeviceGetFanSpeedRPM"] = <_cyb_intptr_t>__nvmlDeviceGetFanSpeedRPM
+    data["__nvmlDeviceGetFanSpeedRPM"] = <intptr_t>__nvmlDeviceGetFanSpeedRPM
 
     global __nvmlDeviceGetTargetFanSpeed
-    data["__nvmlDeviceGetTargetFanSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetTargetFanSpeed
+    data["__nvmlDeviceGetTargetFanSpeed"] = <intptr_t>__nvmlDeviceGetTargetFanSpeed
 
     global __nvmlDeviceGetMinMaxFanSpeed
-    data["__nvmlDeviceGetMinMaxFanSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetMinMaxFanSpeed
+    data["__nvmlDeviceGetMinMaxFanSpeed"] = <intptr_t>__nvmlDeviceGetMinMaxFanSpeed
 
     global __nvmlDeviceGetFanControlPolicy_v2
-    data["__nvmlDeviceGetFanControlPolicy_v2"] = <_cyb_intptr_t>__nvmlDeviceGetFanControlPolicy_v2
+    data["__nvmlDeviceGetFanControlPolicy_v2"] = <intptr_t>__nvmlDeviceGetFanControlPolicy_v2
 
     global __nvmlDeviceGetNumFans
-    data["__nvmlDeviceGetNumFans"] = <_cyb_intptr_t>__nvmlDeviceGetNumFans
+    data["__nvmlDeviceGetNumFans"] = <intptr_t>__nvmlDeviceGetNumFans
 
     global __nvmlDeviceGetCoolerInfo
-    data["__nvmlDeviceGetCoolerInfo"] = <_cyb_intptr_t>__nvmlDeviceGetCoolerInfo
+    data["__nvmlDeviceGetCoolerInfo"] = <intptr_t>__nvmlDeviceGetCoolerInfo
 
     global __nvmlDeviceGetTemperatureV
-    data["__nvmlDeviceGetTemperatureV"] = <_cyb_intptr_t>__nvmlDeviceGetTemperatureV
+    data["__nvmlDeviceGetTemperatureV"] = <intptr_t>__nvmlDeviceGetTemperatureV
 
     global __nvmlDeviceGetTemperatureThreshold
-    data["__nvmlDeviceGetTemperatureThreshold"] = <_cyb_intptr_t>__nvmlDeviceGetTemperatureThreshold
+    data["__nvmlDeviceGetTemperatureThreshold"] = <intptr_t>__nvmlDeviceGetTemperatureThreshold
 
     global __nvmlDeviceGetMarginTemperature
-    data["__nvmlDeviceGetMarginTemperature"] = <_cyb_intptr_t>__nvmlDeviceGetMarginTemperature
+    data["__nvmlDeviceGetMarginTemperature"] = <intptr_t>__nvmlDeviceGetMarginTemperature
 
     global __nvmlDeviceGetThermalSettings
-    data["__nvmlDeviceGetThermalSettings"] = <_cyb_intptr_t>__nvmlDeviceGetThermalSettings
+    data["__nvmlDeviceGetThermalSettings"] = <intptr_t>__nvmlDeviceGetThermalSettings
 
     global __nvmlDeviceGetPerformanceState
-    data["__nvmlDeviceGetPerformanceState"] = <_cyb_intptr_t>__nvmlDeviceGetPerformanceState
+    data["__nvmlDeviceGetPerformanceState"] = <intptr_t>__nvmlDeviceGetPerformanceState
 
     global __nvmlDeviceGetCurrentClocksEventReasons
-    data["__nvmlDeviceGetCurrentClocksEventReasons"] = <_cyb_intptr_t>__nvmlDeviceGetCurrentClocksEventReasons
+    data["__nvmlDeviceGetCurrentClocksEventReasons"] = <intptr_t>__nvmlDeviceGetCurrentClocksEventReasons
 
     global __nvmlDeviceGetSupportedClocksEventReasons
-    data["__nvmlDeviceGetSupportedClocksEventReasons"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedClocksEventReasons
+    data["__nvmlDeviceGetSupportedClocksEventReasons"] = <intptr_t>__nvmlDeviceGetSupportedClocksEventReasons
 
     global __nvmlDeviceGetPowerState
-    data["__nvmlDeviceGetPowerState"] = <_cyb_intptr_t>__nvmlDeviceGetPowerState
+    data["__nvmlDeviceGetPowerState"] = <intptr_t>__nvmlDeviceGetPowerState
 
     global __nvmlDeviceGetDynamicPstatesInfo
-    data["__nvmlDeviceGetDynamicPstatesInfo"] = <_cyb_intptr_t>__nvmlDeviceGetDynamicPstatesInfo
+    data["__nvmlDeviceGetDynamicPstatesInfo"] = <intptr_t>__nvmlDeviceGetDynamicPstatesInfo
 
     global __nvmlDeviceGetMemClkVfOffset
-    data["__nvmlDeviceGetMemClkVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetMemClkVfOffset
+    data["__nvmlDeviceGetMemClkVfOffset"] = <intptr_t>__nvmlDeviceGetMemClkVfOffset
 
     global __nvmlDeviceGetMinMaxClockOfPState
-    data["__nvmlDeviceGetMinMaxClockOfPState"] = <_cyb_intptr_t>__nvmlDeviceGetMinMaxClockOfPState
+    data["__nvmlDeviceGetMinMaxClockOfPState"] = <intptr_t>__nvmlDeviceGetMinMaxClockOfPState
 
     global __nvmlDeviceGetSupportedPerformanceStates
-    data["__nvmlDeviceGetSupportedPerformanceStates"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedPerformanceStates
+    data["__nvmlDeviceGetSupportedPerformanceStates"] = <intptr_t>__nvmlDeviceGetSupportedPerformanceStates
 
     global __nvmlDeviceGetGpcClkMinMaxVfOffset
-    data["__nvmlDeviceGetGpcClkMinMaxVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetGpcClkMinMaxVfOffset
+    data["__nvmlDeviceGetGpcClkMinMaxVfOffset"] = <intptr_t>__nvmlDeviceGetGpcClkMinMaxVfOffset
 
     global __nvmlDeviceGetMemClkMinMaxVfOffset
-    data["__nvmlDeviceGetMemClkMinMaxVfOffset"] = <_cyb_intptr_t>__nvmlDeviceGetMemClkMinMaxVfOffset
+    data["__nvmlDeviceGetMemClkMinMaxVfOffset"] = <intptr_t>__nvmlDeviceGetMemClkMinMaxVfOffset
 
     global __nvmlDeviceGetClockOffsets
-    data["__nvmlDeviceGetClockOffsets"] = <_cyb_intptr_t>__nvmlDeviceGetClockOffsets
+    data["__nvmlDeviceGetClockOffsets"] = <intptr_t>__nvmlDeviceGetClockOffsets
 
     global __nvmlDeviceSetClockOffsets
-    data["__nvmlDeviceSetClockOffsets"] = <_cyb_intptr_t>__nvmlDeviceSetClockOffsets
+    data["__nvmlDeviceSetClockOffsets"] = <intptr_t>__nvmlDeviceSetClockOffsets
 
     global __nvmlDeviceGetPerformanceModes
-    data["__nvmlDeviceGetPerformanceModes"] = <_cyb_intptr_t>__nvmlDeviceGetPerformanceModes
+    data["__nvmlDeviceGetPerformanceModes"] = <intptr_t>__nvmlDeviceGetPerformanceModes
 
     global __nvmlDeviceGetCurrentClockFreqs
-    data["__nvmlDeviceGetCurrentClockFreqs"] = <_cyb_intptr_t>__nvmlDeviceGetCurrentClockFreqs
+    data["__nvmlDeviceGetCurrentClockFreqs"] = <intptr_t>__nvmlDeviceGetCurrentClockFreqs
 
     global __nvmlDeviceGetPowerManagementLimit
-    data["__nvmlDeviceGetPowerManagementLimit"] = <_cyb_intptr_t>__nvmlDeviceGetPowerManagementLimit
+    data["__nvmlDeviceGetPowerManagementLimit"] = <intptr_t>__nvmlDeviceGetPowerManagementLimit
 
     global __nvmlDeviceGetPowerManagementLimitConstraints
-    data["__nvmlDeviceGetPowerManagementLimitConstraints"] = <_cyb_intptr_t>__nvmlDeviceGetPowerManagementLimitConstraints
+    data["__nvmlDeviceGetPowerManagementLimitConstraints"] = <intptr_t>__nvmlDeviceGetPowerManagementLimitConstraints
 
     global __nvmlDeviceGetPowerManagementDefaultLimit
-    data["__nvmlDeviceGetPowerManagementDefaultLimit"] = <_cyb_intptr_t>__nvmlDeviceGetPowerManagementDefaultLimit
+    data["__nvmlDeviceGetPowerManagementDefaultLimit"] = <intptr_t>__nvmlDeviceGetPowerManagementDefaultLimit
 
     global __nvmlDeviceGetPowerUsage
-    data["__nvmlDeviceGetPowerUsage"] = <_cyb_intptr_t>__nvmlDeviceGetPowerUsage
+    data["__nvmlDeviceGetPowerUsage"] = <intptr_t>__nvmlDeviceGetPowerUsage
 
     global __nvmlDeviceGetTotalEnergyConsumption
-    data["__nvmlDeviceGetTotalEnergyConsumption"] = <_cyb_intptr_t>__nvmlDeviceGetTotalEnergyConsumption
+    data["__nvmlDeviceGetTotalEnergyConsumption"] = <intptr_t>__nvmlDeviceGetTotalEnergyConsumption
 
     global __nvmlDeviceGetEnforcedPowerLimit
-    data["__nvmlDeviceGetEnforcedPowerLimit"] = <_cyb_intptr_t>__nvmlDeviceGetEnforcedPowerLimit
+    data["__nvmlDeviceGetEnforcedPowerLimit"] = <intptr_t>__nvmlDeviceGetEnforcedPowerLimit
 
     global __nvmlDeviceGetGpuOperationMode
-    data["__nvmlDeviceGetGpuOperationMode"] = <_cyb_intptr_t>__nvmlDeviceGetGpuOperationMode
+    data["__nvmlDeviceGetGpuOperationMode"] = <intptr_t>__nvmlDeviceGetGpuOperationMode
 
     global __nvmlDeviceGetMemoryInfo_v2
-    data["__nvmlDeviceGetMemoryInfo_v2"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryInfo_v2
+    data["__nvmlDeviceGetMemoryInfo_v2"] = <intptr_t>__nvmlDeviceGetMemoryInfo_v2
 
     global __nvmlDeviceGetComputeMode
-    data["__nvmlDeviceGetComputeMode"] = <_cyb_intptr_t>__nvmlDeviceGetComputeMode
+    data["__nvmlDeviceGetComputeMode"] = <intptr_t>__nvmlDeviceGetComputeMode
 
     global __nvmlDeviceGetCudaComputeCapability
-    data["__nvmlDeviceGetCudaComputeCapability"] = <_cyb_intptr_t>__nvmlDeviceGetCudaComputeCapability
+    data["__nvmlDeviceGetCudaComputeCapability"] = <intptr_t>__nvmlDeviceGetCudaComputeCapability
 
     global __nvmlDeviceGetDramEncryptionMode
-    data["__nvmlDeviceGetDramEncryptionMode"] = <_cyb_intptr_t>__nvmlDeviceGetDramEncryptionMode
+    data["__nvmlDeviceGetDramEncryptionMode"] = <intptr_t>__nvmlDeviceGetDramEncryptionMode
 
     global __nvmlDeviceSetDramEncryptionMode
-    data["__nvmlDeviceSetDramEncryptionMode"] = <_cyb_intptr_t>__nvmlDeviceSetDramEncryptionMode
+    data["__nvmlDeviceSetDramEncryptionMode"] = <intptr_t>__nvmlDeviceSetDramEncryptionMode
 
     global __nvmlDeviceGetEccMode
-    data["__nvmlDeviceGetEccMode"] = <_cyb_intptr_t>__nvmlDeviceGetEccMode
+    data["__nvmlDeviceGetEccMode"] = <intptr_t>__nvmlDeviceGetEccMode
 
     global __nvmlDeviceGetDefaultEccMode
-    data["__nvmlDeviceGetDefaultEccMode"] = <_cyb_intptr_t>__nvmlDeviceGetDefaultEccMode
+    data["__nvmlDeviceGetDefaultEccMode"] = <intptr_t>__nvmlDeviceGetDefaultEccMode
 
     global __nvmlDeviceGetBoardId
-    data["__nvmlDeviceGetBoardId"] = <_cyb_intptr_t>__nvmlDeviceGetBoardId
+    data["__nvmlDeviceGetBoardId"] = <intptr_t>__nvmlDeviceGetBoardId
 
     global __nvmlDeviceGetMultiGpuBoard
-    data["__nvmlDeviceGetMultiGpuBoard"] = <_cyb_intptr_t>__nvmlDeviceGetMultiGpuBoard
+    data["__nvmlDeviceGetMultiGpuBoard"] = <intptr_t>__nvmlDeviceGetMultiGpuBoard
 
     global __nvmlDeviceGetTotalEccErrors
-    data["__nvmlDeviceGetTotalEccErrors"] = <_cyb_intptr_t>__nvmlDeviceGetTotalEccErrors
+    data["__nvmlDeviceGetTotalEccErrors"] = <intptr_t>__nvmlDeviceGetTotalEccErrors
 
     global __nvmlDeviceGetMemoryErrorCounter
-    data["__nvmlDeviceGetMemoryErrorCounter"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryErrorCounter
+    data["__nvmlDeviceGetMemoryErrorCounter"] = <intptr_t>__nvmlDeviceGetMemoryErrorCounter
 
     global __nvmlDeviceGetUtilizationRates
-    data["__nvmlDeviceGetUtilizationRates"] = <_cyb_intptr_t>__nvmlDeviceGetUtilizationRates
+    data["__nvmlDeviceGetUtilizationRates"] = <intptr_t>__nvmlDeviceGetUtilizationRates
 
     global __nvmlDeviceGetEncoderUtilization
-    data["__nvmlDeviceGetEncoderUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderUtilization
+    data["__nvmlDeviceGetEncoderUtilization"] = <intptr_t>__nvmlDeviceGetEncoderUtilization
 
     global __nvmlDeviceGetEncoderCapacity
-    data["__nvmlDeviceGetEncoderCapacity"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderCapacity
+    data["__nvmlDeviceGetEncoderCapacity"] = <intptr_t>__nvmlDeviceGetEncoderCapacity
 
     global __nvmlDeviceGetEncoderStats
-    data["__nvmlDeviceGetEncoderStats"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderStats
+    data["__nvmlDeviceGetEncoderStats"] = <intptr_t>__nvmlDeviceGetEncoderStats
 
     global __nvmlDeviceGetEncoderSessions
-    data["__nvmlDeviceGetEncoderSessions"] = <_cyb_intptr_t>__nvmlDeviceGetEncoderSessions
+    data["__nvmlDeviceGetEncoderSessions"] = <intptr_t>__nvmlDeviceGetEncoderSessions
 
     global __nvmlDeviceGetDecoderUtilization
-    data["__nvmlDeviceGetDecoderUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetDecoderUtilization
+    data["__nvmlDeviceGetDecoderUtilization"] = <intptr_t>__nvmlDeviceGetDecoderUtilization
 
     global __nvmlDeviceGetJpgUtilization
-    data["__nvmlDeviceGetJpgUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetJpgUtilization
+    data["__nvmlDeviceGetJpgUtilization"] = <intptr_t>__nvmlDeviceGetJpgUtilization
 
     global __nvmlDeviceGetOfaUtilization
-    data["__nvmlDeviceGetOfaUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetOfaUtilization
+    data["__nvmlDeviceGetOfaUtilization"] = <intptr_t>__nvmlDeviceGetOfaUtilization
 
     global __nvmlDeviceGetFBCStats
-    data["__nvmlDeviceGetFBCStats"] = <_cyb_intptr_t>__nvmlDeviceGetFBCStats
+    data["__nvmlDeviceGetFBCStats"] = <intptr_t>__nvmlDeviceGetFBCStats
 
     global __nvmlDeviceGetFBCSessions
-    data["__nvmlDeviceGetFBCSessions"] = <_cyb_intptr_t>__nvmlDeviceGetFBCSessions
+    data["__nvmlDeviceGetFBCSessions"] = <intptr_t>__nvmlDeviceGetFBCSessions
 
     global __nvmlDeviceGetDriverModel_v2
-    data["__nvmlDeviceGetDriverModel_v2"] = <_cyb_intptr_t>__nvmlDeviceGetDriverModel_v2
+    data["__nvmlDeviceGetDriverModel_v2"] = <intptr_t>__nvmlDeviceGetDriverModel_v2
 
     global __nvmlDeviceGetVbiosVersion
-    data["__nvmlDeviceGetVbiosVersion"] = <_cyb_intptr_t>__nvmlDeviceGetVbiosVersion
+    data["__nvmlDeviceGetVbiosVersion"] = <intptr_t>__nvmlDeviceGetVbiosVersion
 
     global __nvmlDeviceGetBridgeChipInfo
-    data["__nvmlDeviceGetBridgeChipInfo"] = <_cyb_intptr_t>__nvmlDeviceGetBridgeChipInfo
+    data["__nvmlDeviceGetBridgeChipInfo"] = <intptr_t>__nvmlDeviceGetBridgeChipInfo
 
     global __nvmlDeviceGetComputeRunningProcesses_v3
-    data["__nvmlDeviceGetComputeRunningProcesses_v3"] = <_cyb_intptr_t>__nvmlDeviceGetComputeRunningProcesses_v3
+    data["__nvmlDeviceGetComputeRunningProcesses_v3"] = <intptr_t>__nvmlDeviceGetComputeRunningProcesses_v3
 
     global __nvmlDeviceGetGraphicsRunningProcesses_v3
-    data["__nvmlDeviceGetGraphicsRunningProcesses_v3"] = <_cyb_intptr_t>__nvmlDeviceGetGraphicsRunningProcesses_v3
+    data["__nvmlDeviceGetGraphicsRunningProcesses_v3"] = <intptr_t>__nvmlDeviceGetGraphicsRunningProcesses_v3
 
     global __nvmlDeviceGetMPSComputeRunningProcesses_v3
-    data["__nvmlDeviceGetMPSComputeRunningProcesses_v3"] = <_cyb_intptr_t>__nvmlDeviceGetMPSComputeRunningProcesses_v3
+    data["__nvmlDeviceGetMPSComputeRunningProcesses_v3"] = <intptr_t>__nvmlDeviceGetMPSComputeRunningProcesses_v3
 
     global __nvmlDeviceGetRunningProcessDetailList
-    data["__nvmlDeviceGetRunningProcessDetailList"] = <_cyb_intptr_t>__nvmlDeviceGetRunningProcessDetailList
+    data["__nvmlDeviceGetRunningProcessDetailList"] = <intptr_t>__nvmlDeviceGetRunningProcessDetailList
 
     global __nvmlDeviceOnSameBoard
-    data["__nvmlDeviceOnSameBoard"] = <_cyb_intptr_t>__nvmlDeviceOnSameBoard
+    data["__nvmlDeviceOnSameBoard"] = <intptr_t>__nvmlDeviceOnSameBoard
 
     global __nvmlDeviceGetAPIRestriction
-    data["__nvmlDeviceGetAPIRestriction"] = <_cyb_intptr_t>__nvmlDeviceGetAPIRestriction
+    data["__nvmlDeviceGetAPIRestriction"] = <intptr_t>__nvmlDeviceGetAPIRestriction
 
     global __nvmlDeviceGetSamples
-    data["__nvmlDeviceGetSamples"] = <_cyb_intptr_t>__nvmlDeviceGetSamples
+    data["__nvmlDeviceGetSamples"] = <intptr_t>__nvmlDeviceGetSamples
 
     global __nvmlDeviceGetBAR1MemoryInfo
-    data["__nvmlDeviceGetBAR1MemoryInfo"] = <_cyb_intptr_t>__nvmlDeviceGetBAR1MemoryInfo
+    data["__nvmlDeviceGetBAR1MemoryInfo"] = <intptr_t>__nvmlDeviceGetBAR1MemoryInfo
 
     global __nvmlDeviceGetIrqNum
-    data["__nvmlDeviceGetIrqNum"] = <_cyb_intptr_t>__nvmlDeviceGetIrqNum
+    data["__nvmlDeviceGetIrqNum"] = <intptr_t>__nvmlDeviceGetIrqNum
 
     global __nvmlDeviceGetNumGpuCores
-    data["__nvmlDeviceGetNumGpuCores"] = <_cyb_intptr_t>__nvmlDeviceGetNumGpuCores
+    data["__nvmlDeviceGetNumGpuCores"] = <intptr_t>__nvmlDeviceGetNumGpuCores
 
     global __nvmlDeviceGetPowerSource
-    data["__nvmlDeviceGetPowerSource"] = <_cyb_intptr_t>__nvmlDeviceGetPowerSource
+    data["__nvmlDeviceGetPowerSource"] = <intptr_t>__nvmlDeviceGetPowerSource
 
     global __nvmlDeviceGetMemoryBusWidth
-    data["__nvmlDeviceGetMemoryBusWidth"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryBusWidth
+    data["__nvmlDeviceGetMemoryBusWidth"] = <intptr_t>__nvmlDeviceGetMemoryBusWidth
 
     global __nvmlDeviceGetPcieLinkMaxSpeed
-    data["__nvmlDeviceGetPcieLinkMaxSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetPcieLinkMaxSpeed
+    data["__nvmlDeviceGetPcieLinkMaxSpeed"] = <intptr_t>__nvmlDeviceGetPcieLinkMaxSpeed
 
     global __nvmlDeviceGetPcieSpeed
-    data["__nvmlDeviceGetPcieSpeed"] = <_cyb_intptr_t>__nvmlDeviceGetPcieSpeed
+    data["__nvmlDeviceGetPcieSpeed"] = <intptr_t>__nvmlDeviceGetPcieSpeed
 
     global __nvmlDeviceGetAdaptiveClockInfoStatus
-    data["__nvmlDeviceGetAdaptiveClockInfoStatus"] = <_cyb_intptr_t>__nvmlDeviceGetAdaptiveClockInfoStatus
+    data["__nvmlDeviceGetAdaptiveClockInfoStatus"] = <intptr_t>__nvmlDeviceGetAdaptiveClockInfoStatus
 
     global __nvmlDeviceGetBusType
-    data["__nvmlDeviceGetBusType"] = <_cyb_intptr_t>__nvmlDeviceGetBusType
+    data["__nvmlDeviceGetBusType"] = <intptr_t>__nvmlDeviceGetBusType
 
     global __nvmlDeviceGetGpuFabricInfoV
-    data["__nvmlDeviceGetGpuFabricInfoV"] = <_cyb_intptr_t>__nvmlDeviceGetGpuFabricInfoV
+    data["__nvmlDeviceGetGpuFabricInfoV"] = <intptr_t>__nvmlDeviceGetGpuFabricInfoV
 
     global __nvmlSystemGetConfComputeCapabilities
-    data["__nvmlSystemGetConfComputeCapabilities"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeCapabilities
+    data["__nvmlSystemGetConfComputeCapabilities"] = <intptr_t>__nvmlSystemGetConfComputeCapabilities
 
     global __nvmlSystemGetConfComputeState
-    data["__nvmlSystemGetConfComputeState"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeState
+    data["__nvmlSystemGetConfComputeState"] = <intptr_t>__nvmlSystemGetConfComputeState
 
     global __nvmlDeviceGetConfComputeMemSizeInfo
-    data["__nvmlDeviceGetConfComputeMemSizeInfo"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeMemSizeInfo
+    data["__nvmlDeviceGetConfComputeMemSizeInfo"] = <intptr_t>__nvmlDeviceGetConfComputeMemSizeInfo
 
     global __nvmlSystemGetConfComputeGpusReadyState
-    data["__nvmlSystemGetConfComputeGpusReadyState"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeGpusReadyState
+    data["__nvmlSystemGetConfComputeGpusReadyState"] = <intptr_t>__nvmlSystemGetConfComputeGpusReadyState
 
     global __nvmlDeviceGetConfComputeProtectedMemoryUsage
-    data["__nvmlDeviceGetConfComputeProtectedMemoryUsage"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeProtectedMemoryUsage
+    data["__nvmlDeviceGetConfComputeProtectedMemoryUsage"] = <intptr_t>__nvmlDeviceGetConfComputeProtectedMemoryUsage
 
     global __nvmlDeviceGetConfComputeGpuCertificate
-    data["__nvmlDeviceGetConfComputeGpuCertificate"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeGpuCertificate
+    data["__nvmlDeviceGetConfComputeGpuCertificate"] = <intptr_t>__nvmlDeviceGetConfComputeGpuCertificate
 
     global __nvmlDeviceGetConfComputeGpuAttestationReport
-    data["__nvmlDeviceGetConfComputeGpuAttestationReport"] = <_cyb_intptr_t>__nvmlDeviceGetConfComputeGpuAttestationReport
+    data["__nvmlDeviceGetConfComputeGpuAttestationReport"] = <intptr_t>__nvmlDeviceGetConfComputeGpuAttestationReport
 
     global __nvmlSystemGetConfComputeKeyRotationThresholdInfo
-    data["__nvmlSystemGetConfComputeKeyRotationThresholdInfo"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeKeyRotationThresholdInfo
+    data["__nvmlSystemGetConfComputeKeyRotationThresholdInfo"] = <intptr_t>__nvmlSystemGetConfComputeKeyRotationThresholdInfo
 
     global __nvmlDeviceSetConfComputeUnprotectedMemSize
-    data["__nvmlDeviceSetConfComputeUnprotectedMemSize"] = <_cyb_intptr_t>__nvmlDeviceSetConfComputeUnprotectedMemSize
+    data["__nvmlDeviceSetConfComputeUnprotectedMemSize"] = <intptr_t>__nvmlDeviceSetConfComputeUnprotectedMemSize
 
     global __nvmlSystemSetConfComputeGpusReadyState
-    data["__nvmlSystemSetConfComputeGpusReadyState"] = <_cyb_intptr_t>__nvmlSystemSetConfComputeGpusReadyState
+    data["__nvmlSystemSetConfComputeGpusReadyState"] = <intptr_t>__nvmlSystemSetConfComputeGpusReadyState
 
     global __nvmlSystemSetConfComputeKeyRotationThresholdInfo
-    data["__nvmlSystemSetConfComputeKeyRotationThresholdInfo"] = <_cyb_intptr_t>__nvmlSystemSetConfComputeKeyRotationThresholdInfo
+    data["__nvmlSystemSetConfComputeKeyRotationThresholdInfo"] = <intptr_t>__nvmlSystemSetConfComputeKeyRotationThresholdInfo
 
     global __nvmlSystemGetConfComputeSettings
-    data["__nvmlSystemGetConfComputeSettings"] = <_cyb_intptr_t>__nvmlSystemGetConfComputeSettings
+    data["__nvmlSystemGetConfComputeSettings"] = <intptr_t>__nvmlSystemGetConfComputeSettings
 
     global __nvmlDeviceGetGspFirmwareVersion
-    data["__nvmlDeviceGetGspFirmwareVersion"] = <_cyb_intptr_t>__nvmlDeviceGetGspFirmwareVersion
+    data["__nvmlDeviceGetGspFirmwareVersion"] = <intptr_t>__nvmlDeviceGetGspFirmwareVersion
 
     global __nvmlDeviceGetGspFirmwareMode
-    data["__nvmlDeviceGetGspFirmwareMode"] = <_cyb_intptr_t>__nvmlDeviceGetGspFirmwareMode
+    data["__nvmlDeviceGetGspFirmwareMode"] = <intptr_t>__nvmlDeviceGetGspFirmwareMode
 
     global __nvmlDeviceGetSramEccErrorStatus
-    data["__nvmlDeviceGetSramEccErrorStatus"] = <_cyb_intptr_t>__nvmlDeviceGetSramEccErrorStatus
+    data["__nvmlDeviceGetSramEccErrorStatus"] = <intptr_t>__nvmlDeviceGetSramEccErrorStatus
 
     global __nvmlDeviceGetAccountingMode
-    data["__nvmlDeviceGetAccountingMode"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingMode
+    data["__nvmlDeviceGetAccountingMode"] = <intptr_t>__nvmlDeviceGetAccountingMode
 
     global __nvmlDeviceGetAccountingStats
-    data["__nvmlDeviceGetAccountingStats"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingStats
+    data["__nvmlDeviceGetAccountingStats"] = <intptr_t>__nvmlDeviceGetAccountingStats
 
     global __nvmlDeviceGetAccountingPids
-    data["__nvmlDeviceGetAccountingPids"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingPids
+    data["__nvmlDeviceGetAccountingPids"] = <intptr_t>__nvmlDeviceGetAccountingPids
 
     global __nvmlDeviceGetAccountingBufferSize
-    data["__nvmlDeviceGetAccountingBufferSize"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingBufferSize
+    data["__nvmlDeviceGetAccountingBufferSize"] = <intptr_t>__nvmlDeviceGetAccountingBufferSize
 
     global __nvmlDeviceGetRetiredPages
-    data["__nvmlDeviceGetRetiredPages"] = <_cyb_intptr_t>__nvmlDeviceGetRetiredPages
+    data["__nvmlDeviceGetRetiredPages"] = <intptr_t>__nvmlDeviceGetRetiredPages
 
     global __nvmlDeviceGetRetiredPages_v2
-    data["__nvmlDeviceGetRetiredPages_v2"] = <_cyb_intptr_t>__nvmlDeviceGetRetiredPages_v2
+    data["__nvmlDeviceGetRetiredPages_v2"] = <intptr_t>__nvmlDeviceGetRetiredPages_v2
 
     global __nvmlDeviceGetRetiredPagesPendingStatus
-    data["__nvmlDeviceGetRetiredPagesPendingStatus"] = <_cyb_intptr_t>__nvmlDeviceGetRetiredPagesPendingStatus
+    data["__nvmlDeviceGetRetiredPagesPendingStatus"] = <intptr_t>__nvmlDeviceGetRetiredPagesPendingStatus
 
     global __nvmlDeviceGetRemappedRows
-    data["__nvmlDeviceGetRemappedRows"] = <_cyb_intptr_t>__nvmlDeviceGetRemappedRows
+    data["__nvmlDeviceGetRemappedRows"] = <intptr_t>__nvmlDeviceGetRemappedRows
 
     global __nvmlDeviceGetRowRemapperHistogram
-    data["__nvmlDeviceGetRowRemapperHistogram"] = <_cyb_intptr_t>__nvmlDeviceGetRowRemapperHistogram
+    data["__nvmlDeviceGetRowRemapperHistogram"] = <intptr_t>__nvmlDeviceGetRowRemapperHistogram
 
     global __nvmlDeviceGetArchitecture
-    data["__nvmlDeviceGetArchitecture"] = <_cyb_intptr_t>__nvmlDeviceGetArchitecture
+    data["__nvmlDeviceGetArchitecture"] = <intptr_t>__nvmlDeviceGetArchitecture
 
     global __nvmlDeviceGetClkMonStatus
-    data["__nvmlDeviceGetClkMonStatus"] = <_cyb_intptr_t>__nvmlDeviceGetClkMonStatus
+    data["__nvmlDeviceGetClkMonStatus"] = <intptr_t>__nvmlDeviceGetClkMonStatus
 
     global __nvmlDeviceGetProcessUtilization
-    data["__nvmlDeviceGetProcessUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetProcessUtilization
+    data["__nvmlDeviceGetProcessUtilization"] = <intptr_t>__nvmlDeviceGetProcessUtilization
 
     global __nvmlDeviceGetProcessesUtilizationInfo
-    data["__nvmlDeviceGetProcessesUtilizationInfo"] = <_cyb_intptr_t>__nvmlDeviceGetProcessesUtilizationInfo
+    data["__nvmlDeviceGetProcessesUtilizationInfo"] = <intptr_t>__nvmlDeviceGetProcessesUtilizationInfo
 
     global __nvmlDeviceGetPlatformInfo
-    data["__nvmlDeviceGetPlatformInfo"] = <_cyb_intptr_t>__nvmlDeviceGetPlatformInfo
+    data["__nvmlDeviceGetPlatformInfo"] = <intptr_t>__nvmlDeviceGetPlatformInfo
 
     global __nvmlUnitSetLedState
-    data["__nvmlUnitSetLedState"] = <_cyb_intptr_t>__nvmlUnitSetLedState
+    data["__nvmlUnitSetLedState"] = <intptr_t>__nvmlUnitSetLedState
 
     global __nvmlDeviceSetPersistenceMode
-    data["__nvmlDeviceSetPersistenceMode"] = <_cyb_intptr_t>__nvmlDeviceSetPersistenceMode
+    data["__nvmlDeviceSetPersistenceMode"] = <intptr_t>__nvmlDeviceSetPersistenceMode
 
     global __nvmlDeviceSetComputeMode
-    data["__nvmlDeviceSetComputeMode"] = <_cyb_intptr_t>__nvmlDeviceSetComputeMode
+    data["__nvmlDeviceSetComputeMode"] = <intptr_t>__nvmlDeviceSetComputeMode
 
     global __nvmlDeviceSetEccMode
-    data["__nvmlDeviceSetEccMode"] = <_cyb_intptr_t>__nvmlDeviceSetEccMode
+    data["__nvmlDeviceSetEccMode"] = <intptr_t>__nvmlDeviceSetEccMode
 
     global __nvmlDeviceClearEccErrorCounts
-    data["__nvmlDeviceClearEccErrorCounts"] = <_cyb_intptr_t>__nvmlDeviceClearEccErrorCounts
+    data["__nvmlDeviceClearEccErrorCounts"] = <intptr_t>__nvmlDeviceClearEccErrorCounts
 
     global __nvmlDeviceSetDriverModel
-    data["__nvmlDeviceSetDriverModel"] = <_cyb_intptr_t>__nvmlDeviceSetDriverModel
+    data["__nvmlDeviceSetDriverModel"] = <intptr_t>__nvmlDeviceSetDriverModel
 
     global __nvmlDeviceSetGpuLockedClocks
-    data["__nvmlDeviceSetGpuLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceSetGpuLockedClocks
+    data["__nvmlDeviceSetGpuLockedClocks"] = <intptr_t>__nvmlDeviceSetGpuLockedClocks
 
     global __nvmlDeviceResetGpuLockedClocks
-    data["__nvmlDeviceResetGpuLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceResetGpuLockedClocks
+    data["__nvmlDeviceResetGpuLockedClocks"] = <intptr_t>__nvmlDeviceResetGpuLockedClocks
 
     global __nvmlDeviceSetMemoryLockedClocks
-    data["__nvmlDeviceSetMemoryLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceSetMemoryLockedClocks
+    data["__nvmlDeviceSetMemoryLockedClocks"] = <intptr_t>__nvmlDeviceSetMemoryLockedClocks
 
     global __nvmlDeviceResetMemoryLockedClocks
-    data["__nvmlDeviceResetMemoryLockedClocks"] = <_cyb_intptr_t>__nvmlDeviceResetMemoryLockedClocks
+    data["__nvmlDeviceResetMemoryLockedClocks"] = <intptr_t>__nvmlDeviceResetMemoryLockedClocks
 
     global __nvmlDeviceSetAutoBoostedClocksEnabled
-    data["__nvmlDeviceSetAutoBoostedClocksEnabled"] = <_cyb_intptr_t>__nvmlDeviceSetAutoBoostedClocksEnabled
+    data["__nvmlDeviceSetAutoBoostedClocksEnabled"] = <intptr_t>__nvmlDeviceSetAutoBoostedClocksEnabled
 
     global __nvmlDeviceSetDefaultAutoBoostedClocksEnabled
-    data["__nvmlDeviceSetDefaultAutoBoostedClocksEnabled"] = <_cyb_intptr_t>__nvmlDeviceSetDefaultAutoBoostedClocksEnabled
+    data["__nvmlDeviceSetDefaultAutoBoostedClocksEnabled"] = <intptr_t>__nvmlDeviceSetDefaultAutoBoostedClocksEnabled
 
     global __nvmlDeviceSetDefaultFanSpeed_v2
-    data["__nvmlDeviceSetDefaultFanSpeed_v2"] = <_cyb_intptr_t>__nvmlDeviceSetDefaultFanSpeed_v2
+    data["__nvmlDeviceSetDefaultFanSpeed_v2"] = <intptr_t>__nvmlDeviceSetDefaultFanSpeed_v2
 
     global __nvmlDeviceSetFanControlPolicy
-    data["__nvmlDeviceSetFanControlPolicy"] = <_cyb_intptr_t>__nvmlDeviceSetFanControlPolicy
+    data["__nvmlDeviceSetFanControlPolicy"] = <intptr_t>__nvmlDeviceSetFanControlPolicy
 
     global __nvmlDeviceSetTemperatureThreshold
-    data["__nvmlDeviceSetTemperatureThreshold"] = <_cyb_intptr_t>__nvmlDeviceSetTemperatureThreshold
+    data["__nvmlDeviceSetTemperatureThreshold"] = <intptr_t>__nvmlDeviceSetTemperatureThreshold
 
     global __nvmlDeviceSetGpuOperationMode
-    data["__nvmlDeviceSetGpuOperationMode"] = <_cyb_intptr_t>__nvmlDeviceSetGpuOperationMode
+    data["__nvmlDeviceSetGpuOperationMode"] = <intptr_t>__nvmlDeviceSetGpuOperationMode
 
     global __nvmlDeviceSetAPIRestriction
-    data["__nvmlDeviceSetAPIRestriction"] = <_cyb_intptr_t>__nvmlDeviceSetAPIRestriction
+    data["__nvmlDeviceSetAPIRestriction"] = <intptr_t>__nvmlDeviceSetAPIRestriction
 
     global __nvmlDeviceSetFanSpeed_v2
-    data["__nvmlDeviceSetFanSpeed_v2"] = <_cyb_intptr_t>__nvmlDeviceSetFanSpeed_v2
+    data["__nvmlDeviceSetFanSpeed_v2"] = <intptr_t>__nvmlDeviceSetFanSpeed_v2
 
     global __nvmlDeviceSetAccountingMode
-    data["__nvmlDeviceSetAccountingMode"] = <_cyb_intptr_t>__nvmlDeviceSetAccountingMode
+    data["__nvmlDeviceSetAccountingMode"] = <intptr_t>__nvmlDeviceSetAccountingMode
 
     global __nvmlDeviceClearAccountingPids
-    data["__nvmlDeviceClearAccountingPids"] = <_cyb_intptr_t>__nvmlDeviceClearAccountingPids
+    data["__nvmlDeviceClearAccountingPids"] = <intptr_t>__nvmlDeviceClearAccountingPids
 
     global __nvmlDeviceSetPowerManagementLimit_v2
-    data["__nvmlDeviceSetPowerManagementLimit_v2"] = <_cyb_intptr_t>__nvmlDeviceSetPowerManagementLimit_v2
+    data["__nvmlDeviceSetPowerManagementLimit_v2"] = <intptr_t>__nvmlDeviceSetPowerManagementLimit_v2
 
     global __nvmlDeviceGetNvLinkState
-    data["__nvmlDeviceGetNvLinkState"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkState
+    data["__nvmlDeviceGetNvLinkState"] = <intptr_t>__nvmlDeviceGetNvLinkState
 
     global __nvmlDeviceGetNvLinkVersion
-    data["__nvmlDeviceGetNvLinkVersion"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkVersion
+    data["__nvmlDeviceGetNvLinkVersion"] = <intptr_t>__nvmlDeviceGetNvLinkVersion
 
     global __nvmlDeviceGetNvLinkCapability
-    data["__nvmlDeviceGetNvLinkCapability"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkCapability
+    data["__nvmlDeviceGetNvLinkCapability"] = <intptr_t>__nvmlDeviceGetNvLinkCapability
 
     global __nvmlDeviceGetNvLinkRemotePciInfo_v2
-    data["__nvmlDeviceGetNvLinkRemotePciInfo_v2"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkRemotePciInfo_v2
+    data["__nvmlDeviceGetNvLinkRemotePciInfo_v2"] = <intptr_t>__nvmlDeviceGetNvLinkRemotePciInfo_v2
 
     global __nvmlDeviceGetNvLinkErrorCounter
-    data["__nvmlDeviceGetNvLinkErrorCounter"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkErrorCounter
+    data["__nvmlDeviceGetNvLinkErrorCounter"] = <intptr_t>__nvmlDeviceGetNvLinkErrorCounter
 
     global __nvmlDeviceResetNvLinkErrorCounters
-    data["__nvmlDeviceResetNvLinkErrorCounters"] = <_cyb_intptr_t>__nvmlDeviceResetNvLinkErrorCounters
+    data["__nvmlDeviceResetNvLinkErrorCounters"] = <intptr_t>__nvmlDeviceResetNvLinkErrorCounters
 
     global __nvmlDeviceGetNvLinkRemoteDeviceType
-    data["__nvmlDeviceGetNvLinkRemoteDeviceType"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkRemoteDeviceType
+    data["__nvmlDeviceGetNvLinkRemoteDeviceType"] = <intptr_t>__nvmlDeviceGetNvLinkRemoteDeviceType
 
     global __nvmlDeviceSetNvLinkDeviceLowPowerThreshold
-    data["__nvmlDeviceSetNvLinkDeviceLowPowerThreshold"] = <_cyb_intptr_t>__nvmlDeviceSetNvLinkDeviceLowPowerThreshold
+    data["__nvmlDeviceSetNvLinkDeviceLowPowerThreshold"] = <intptr_t>__nvmlDeviceSetNvLinkDeviceLowPowerThreshold
 
     global __nvmlSystemSetNvlinkBwMode
-    data["__nvmlSystemSetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlSystemSetNvlinkBwMode
+    data["__nvmlSystemSetNvlinkBwMode"] = <intptr_t>__nvmlSystemSetNvlinkBwMode
 
     global __nvmlSystemGetNvlinkBwMode
-    data["__nvmlSystemGetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlSystemGetNvlinkBwMode
+    data["__nvmlSystemGetNvlinkBwMode"] = <intptr_t>__nvmlSystemGetNvlinkBwMode
 
     global __nvmlDeviceGetNvlinkSupportedBwModes
-    data["__nvmlDeviceGetNvlinkSupportedBwModes"] = <_cyb_intptr_t>__nvmlDeviceGetNvlinkSupportedBwModes
+    data["__nvmlDeviceGetNvlinkSupportedBwModes"] = <intptr_t>__nvmlDeviceGetNvlinkSupportedBwModes
 
     global __nvmlDeviceGetNvlinkBwMode
-    data["__nvmlDeviceGetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlDeviceGetNvlinkBwMode
+    data["__nvmlDeviceGetNvlinkBwMode"] = <intptr_t>__nvmlDeviceGetNvlinkBwMode
 
     global __nvmlDeviceSetNvlinkBwMode
-    data["__nvmlDeviceSetNvlinkBwMode"] = <_cyb_intptr_t>__nvmlDeviceSetNvlinkBwMode
+    data["__nvmlDeviceSetNvlinkBwMode"] = <intptr_t>__nvmlDeviceSetNvlinkBwMode
 
     global __nvmlEventSetCreate
-    data["__nvmlEventSetCreate"] = <_cyb_intptr_t>__nvmlEventSetCreate
+    data["__nvmlEventSetCreate"] = <intptr_t>__nvmlEventSetCreate
 
     global __nvmlDeviceRegisterEvents
-    data["__nvmlDeviceRegisterEvents"] = <_cyb_intptr_t>__nvmlDeviceRegisterEvents
+    data["__nvmlDeviceRegisterEvents"] = <intptr_t>__nvmlDeviceRegisterEvents
 
     global __nvmlDeviceGetSupportedEventTypes
-    data["__nvmlDeviceGetSupportedEventTypes"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedEventTypes
+    data["__nvmlDeviceGetSupportedEventTypes"] = <intptr_t>__nvmlDeviceGetSupportedEventTypes
 
     global __nvmlEventSetWait_v2
-    data["__nvmlEventSetWait_v2"] = <_cyb_intptr_t>__nvmlEventSetWait_v2
+    data["__nvmlEventSetWait_v2"] = <intptr_t>__nvmlEventSetWait_v2
 
     global __nvmlEventSetFree
-    data["__nvmlEventSetFree"] = <_cyb_intptr_t>__nvmlEventSetFree
+    data["__nvmlEventSetFree"] = <intptr_t>__nvmlEventSetFree
 
     global __nvmlSystemEventSetCreate
-    data["__nvmlSystemEventSetCreate"] = <_cyb_intptr_t>__nvmlSystemEventSetCreate
+    data["__nvmlSystemEventSetCreate"] = <intptr_t>__nvmlSystemEventSetCreate
 
     global __nvmlSystemEventSetFree
-    data["__nvmlSystemEventSetFree"] = <_cyb_intptr_t>__nvmlSystemEventSetFree
+    data["__nvmlSystemEventSetFree"] = <intptr_t>__nvmlSystemEventSetFree
 
     global __nvmlSystemRegisterEvents
-    data["__nvmlSystemRegisterEvents"] = <_cyb_intptr_t>__nvmlSystemRegisterEvents
+    data["__nvmlSystemRegisterEvents"] = <intptr_t>__nvmlSystemRegisterEvents
 
     global __nvmlSystemEventSetWait
-    data["__nvmlSystemEventSetWait"] = <_cyb_intptr_t>__nvmlSystemEventSetWait
+    data["__nvmlSystemEventSetWait"] = <intptr_t>__nvmlSystemEventSetWait
 
     global __nvmlDeviceModifyDrainState
-    data["__nvmlDeviceModifyDrainState"] = <_cyb_intptr_t>__nvmlDeviceModifyDrainState
+    data["__nvmlDeviceModifyDrainState"] = <intptr_t>__nvmlDeviceModifyDrainState
 
     global __nvmlDeviceQueryDrainState
-    data["__nvmlDeviceQueryDrainState"] = <_cyb_intptr_t>__nvmlDeviceQueryDrainState
+    data["__nvmlDeviceQueryDrainState"] = <intptr_t>__nvmlDeviceQueryDrainState
 
     global __nvmlDeviceRemoveGpu_v2
-    data["__nvmlDeviceRemoveGpu_v2"] = <_cyb_intptr_t>__nvmlDeviceRemoveGpu_v2
+    data["__nvmlDeviceRemoveGpu_v2"] = <intptr_t>__nvmlDeviceRemoveGpu_v2
 
     global __nvmlDeviceDiscoverGpus
-    data["__nvmlDeviceDiscoverGpus"] = <_cyb_intptr_t>__nvmlDeviceDiscoverGpus
+    data["__nvmlDeviceDiscoverGpus"] = <intptr_t>__nvmlDeviceDiscoverGpus
 
     global __nvmlDeviceGetFieldValues
-    data["__nvmlDeviceGetFieldValues"] = <_cyb_intptr_t>__nvmlDeviceGetFieldValues
+    data["__nvmlDeviceGetFieldValues"] = <intptr_t>__nvmlDeviceGetFieldValues
 
     global __nvmlDeviceClearFieldValues
-    data["__nvmlDeviceClearFieldValues"] = <_cyb_intptr_t>__nvmlDeviceClearFieldValues
+    data["__nvmlDeviceClearFieldValues"] = <intptr_t>__nvmlDeviceClearFieldValues
 
     global __nvmlDeviceGetVirtualizationMode
-    data["__nvmlDeviceGetVirtualizationMode"] = <_cyb_intptr_t>__nvmlDeviceGetVirtualizationMode
+    data["__nvmlDeviceGetVirtualizationMode"] = <intptr_t>__nvmlDeviceGetVirtualizationMode
 
     global __nvmlDeviceGetHostVgpuMode
-    data["__nvmlDeviceGetHostVgpuMode"] = <_cyb_intptr_t>__nvmlDeviceGetHostVgpuMode
+    data["__nvmlDeviceGetHostVgpuMode"] = <intptr_t>__nvmlDeviceGetHostVgpuMode
 
     global __nvmlDeviceSetVirtualizationMode
-    data["__nvmlDeviceSetVirtualizationMode"] = <_cyb_intptr_t>__nvmlDeviceSetVirtualizationMode
+    data["__nvmlDeviceSetVirtualizationMode"] = <intptr_t>__nvmlDeviceSetVirtualizationMode
 
     global __nvmlDeviceGetVgpuHeterogeneousMode
-    data["__nvmlDeviceGetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuHeterogeneousMode
+    data["__nvmlDeviceGetVgpuHeterogeneousMode"] = <intptr_t>__nvmlDeviceGetVgpuHeterogeneousMode
 
     global __nvmlDeviceSetVgpuHeterogeneousMode
-    data["__nvmlDeviceSetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuHeterogeneousMode
+    data["__nvmlDeviceSetVgpuHeterogeneousMode"] = <intptr_t>__nvmlDeviceSetVgpuHeterogeneousMode
 
     global __nvmlVgpuInstanceGetPlacementId
-    data["__nvmlVgpuInstanceGetPlacementId"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetPlacementId
+    data["__nvmlVgpuInstanceGetPlacementId"] = <intptr_t>__nvmlVgpuInstanceGetPlacementId
 
     global __nvmlDeviceGetVgpuTypeSupportedPlacements
-    data["__nvmlDeviceGetVgpuTypeSupportedPlacements"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuTypeSupportedPlacements
+    data["__nvmlDeviceGetVgpuTypeSupportedPlacements"] = <intptr_t>__nvmlDeviceGetVgpuTypeSupportedPlacements
 
     global __nvmlDeviceGetVgpuTypeCreatablePlacements
-    data["__nvmlDeviceGetVgpuTypeCreatablePlacements"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuTypeCreatablePlacements
+    data["__nvmlDeviceGetVgpuTypeCreatablePlacements"] = <intptr_t>__nvmlDeviceGetVgpuTypeCreatablePlacements
 
     global __nvmlVgpuTypeGetGspHeapSize
-    data["__nvmlVgpuTypeGetGspHeapSize"] = <_cyb_intptr_t>__nvmlVgpuTypeGetGspHeapSize
+    data["__nvmlVgpuTypeGetGspHeapSize"] = <intptr_t>__nvmlVgpuTypeGetGspHeapSize
 
     global __nvmlVgpuTypeGetFbReservation
-    data["__nvmlVgpuTypeGetFbReservation"] = <_cyb_intptr_t>__nvmlVgpuTypeGetFbReservation
+    data["__nvmlVgpuTypeGetFbReservation"] = <intptr_t>__nvmlVgpuTypeGetFbReservation
 
     global __nvmlVgpuInstanceGetRuntimeStateSize
-    data["__nvmlVgpuInstanceGetRuntimeStateSize"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetRuntimeStateSize
+    data["__nvmlVgpuInstanceGetRuntimeStateSize"] = <intptr_t>__nvmlVgpuInstanceGetRuntimeStateSize
 
     global __nvmlDeviceSetVgpuCapabilities
-    data["__nvmlDeviceSetVgpuCapabilities"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuCapabilities
+    data["__nvmlDeviceSetVgpuCapabilities"] = <intptr_t>__nvmlDeviceSetVgpuCapabilities
 
     global __nvmlDeviceGetGridLicensableFeatures_v4
-    data["__nvmlDeviceGetGridLicensableFeatures_v4"] = <_cyb_intptr_t>__nvmlDeviceGetGridLicensableFeatures_v4
+    data["__nvmlDeviceGetGridLicensableFeatures_v4"] = <intptr_t>__nvmlDeviceGetGridLicensableFeatures_v4
 
     global __nvmlGetVgpuDriverCapabilities
-    data["__nvmlGetVgpuDriverCapabilities"] = <_cyb_intptr_t>__nvmlGetVgpuDriverCapabilities
+    data["__nvmlGetVgpuDriverCapabilities"] = <intptr_t>__nvmlGetVgpuDriverCapabilities
 
     global __nvmlDeviceGetVgpuCapabilities
-    data["__nvmlDeviceGetVgpuCapabilities"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuCapabilities
+    data["__nvmlDeviceGetVgpuCapabilities"] = <intptr_t>__nvmlDeviceGetVgpuCapabilities
 
     global __nvmlDeviceGetSupportedVgpus
-    data["__nvmlDeviceGetSupportedVgpus"] = <_cyb_intptr_t>__nvmlDeviceGetSupportedVgpus
+    data["__nvmlDeviceGetSupportedVgpus"] = <intptr_t>__nvmlDeviceGetSupportedVgpus
 
     global __nvmlDeviceGetCreatableVgpus
-    data["__nvmlDeviceGetCreatableVgpus"] = <_cyb_intptr_t>__nvmlDeviceGetCreatableVgpus
+    data["__nvmlDeviceGetCreatableVgpus"] = <intptr_t>__nvmlDeviceGetCreatableVgpus
 
     global __nvmlVgpuTypeGetClass
-    data["__nvmlVgpuTypeGetClass"] = <_cyb_intptr_t>__nvmlVgpuTypeGetClass
+    data["__nvmlVgpuTypeGetClass"] = <intptr_t>__nvmlVgpuTypeGetClass
 
     global __nvmlVgpuTypeGetName
-    data["__nvmlVgpuTypeGetName"] = <_cyb_intptr_t>__nvmlVgpuTypeGetName
+    data["__nvmlVgpuTypeGetName"] = <intptr_t>__nvmlVgpuTypeGetName
 
     global __nvmlVgpuTypeGetGpuInstanceProfileId
-    data["__nvmlVgpuTypeGetGpuInstanceProfileId"] = <_cyb_intptr_t>__nvmlVgpuTypeGetGpuInstanceProfileId
+    data["__nvmlVgpuTypeGetGpuInstanceProfileId"] = <intptr_t>__nvmlVgpuTypeGetGpuInstanceProfileId
 
     global __nvmlVgpuTypeGetDeviceID
-    data["__nvmlVgpuTypeGetDeviceID"] = <_cyb_intptr_t>__nvmlVgpuTypeGetDeviceID
+    data["__nvmlVgpuTypeGetDeviceID"] = <intptr_t>__nvmlVgpuTypeGetDeviceID
 
     global __nvmlVgpuTypeGetFramebufferSize
-    data["__nvmlVgpuTypeGetFramebufferSize"] = <_cyb_intptr_t>__nvmlVgpuTypeGetFramebufferSize
+    data["__nvmlVgpuTypeGetFramebufferSize"] = <intptr_t>__nvmlVgpuTypeGetFramebufferSize
 
     global __nvmlVgpuTypeGetNumDisplayHeads
-    data["__nvmlVgpuTypeGetNumDisplayHeads"] = <_cyb_intptr_t>__nvmlVgpuTypeGetNumDisplayHeads
+    data["__nvmlVgpuTypeGetNumDisplayHeads"] = <intptr_t>__nvmlVgpuTypeGetNumDisplayHeads
 
     global __nvmlVgpuTypeGetResolution
-    data["__nvmlVgpuTypeGetResolution"] = <_cyb_intptr_t>__nvmlVgpuTypeGetResolution
+    data["__nvmlVgpuTypeGetResolution"] = <intptr_t>__nvmlVgpuTypeGetResolution
 
     global __nvmlVgpuTypeGetLicense
-    data["__nvmlVgpuTypeGetLicense"] = <_cyb_intptr_t>__nvmlVgpuTypeGetLicense
+    data["__nvmlVgpuTypeGetLicense"] = <intptr_t>__nvmlVgpuTypeGetLicense
 
     global __nvmlVgpuTypeGetFrameRateLimit
-    data["__nvmlVgpuTypeGetFrameRateLimit"] = <_cyb_intptr_t>__nvmlVgpuTypeGetFrameRateLimit
+    data["__nvmlVgpuTypeGetFrameRateLimit"] = <intptr_t>__nvmlVgpuTypeGetFrameRateLimit
 
     global __nvmlVgpuTypeGetMaxInstances
-    data["__nvmlVgpuTypeGetMaxInstances"] = <_cyb_intptr_t>__nvmlVgpuTypeGetMaxInstances
+    data["__nvmlVgpuTypeGetMaxInstances"] = <intptr_t>__nvmlVgpuTypeGetMaxInstances
 
     global __nvmlVgpuTypeGetMaxInstancesPerVm
-    data["__nvmlVgpuTypeGetMaxInstancesPerVm"] = <_cyb_intptr_t>__nvmlVgpuTypeGetMaxInstancesPerVm
+    data["__nvmlVgpuTypeGetMaxInstancesPerVm"] = <intptr_t>__nvmlVgpuTypeGetMaxInstancesPerVm
 
     global __nvmlVgpuTypeGetBAR1Info
-    data["__nvmlVgpuTypeGetBAR1Info"] = <_cyb_intptr_t>__nvmlVgpuTypeGetBAR1Info
+    data["__nvmlVgpuTypeGetBAR1Info"] = <intptr_t>__nvmlVgpuTypeGetBAR1Info
 
     global __nvmlDeviceGetActiveVgpus
-    data["__nvmlDeviceGetActiveVgpus"] = <_cyb_intptr_t>__nvmlDeviceGetActiveVgpus
+    data["__nvmlDeviceGetActiveVgpus"] = <intptr_t>__nvmlDeviceGetActiveVgpus
 
     global __nvmlVgpuInstanceGetVmID
-    data["__nvmlVgpuInstanceGetVmID"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetVmID
+    data["__nvmlVgpuInstanceGetVmID"] = <intptr_t>__nvmlVgpuInstanceGetVmID
 
     global __nvmlVgpuInstanceGetUUID
-    data["__nvmlVgpuInstanceGetUUID"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetUUID
+    data["__nvmlVgpuInstanceGetUUID"] = <intptr_t>__nvmlVgpuInstanceGetUUID
 
     global __nvmlVgpuInstanceGetVmDriverVersion
-    data["__nvmlVgpuInstanceGetVmDriverVersion"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetVmDriverVersion
+    data["__nvmlVgpuInstanceGetVmDriverVersion"] = <intptr_t>__nvmlVgpuInstanceGetVmDriverVersion
 
     global __nvmlVgpuInstanceGetFbUsage
-    data["__nvmlVgpuInstanceGetFbUsage"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFbUsage
+    data["__nvmlVgpuInstanceGetFbUsage"] = <intptr_t>__nvmlVgpuInstanceGetFbUsage
 
     global __nvmlVgpuInstanceGetLicenseStatus
-    data["__nvmlVgpuInstanceGetLicenseStatus"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetLicenseStatus
+    data["__nvmlVgpuInstanceGetLicenseStatus"] = <intptr_t>__nvmlVgpuInstanceGetLicenseStatus
 
     global __nvmlVgpuInstanceGetType
-    data["__nvmlVgpuInstanceGetType"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetType
+    data["__nvmlVgpuInstanceGetType"] = <intptr_t>__nvmlVgpuInstanceGetType
 
     global __nvmlVgpuInstanceGetFrameRateLimit
-    data["__nvmlVgpuInstanceGetFrameRateLimit"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFrameRateLimit
+    data["__nvmlVgpuInstanceGetFrameRateLimit"] = <intptr_t>__nvmlVgpuInstanceGetFrameRateLimit
 
     global __nvmlVgpuInstanceGetEccMode
-    data["__nvmlVgpuInstanceGetEccMode"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEccMode
+    data["__nvmlVgpuInstanceGetEccMode"] = <intptr_t>__nvmlVgpuInstanceGetEccMode
 
     global __nvmlVgpuInstanceGetEncoderCapacity
-    data["__nvmlVgpuInstanceGetEncoderCapacity"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEncoderCapacity
+    data["__nvmlVgpuInstanceGetEncoderCapacity"] = <intptr_t>__nvmlVgpuInstanceGetEncoderCapacity
 
     global __nvmlVgpuInstanceSetEncoderCapacity
-    data["__nvmlVgpuInstanceSetEncoderCapacity"] = <_cyb_intptr_t>__nvmlVgpuInstanceSetEncoderCapacity
+    data["__nvmlVgpuInstanceSetEncoderCapacity"] = <intptr_t>__nvmlVgpuInstanceSetEncoderCapacity
 
     global __nvmlVgpuInstanceGetEncoderStats
-    data["__nvmlVgpuInstanceGetEncoderStats"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEncoderStats
+    data["__nvmlVgpuInstanceGetEncoderStats"] = <intptr_t>__nvmlVgpuInstanceGetEncoderStats
 
     global __nvmlVgpuInstanceGetEncoderSessions
-    data["__nvmlVgpuInstanceGetEncoderSessions"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetEncoderSessions
+    data["__nvmlVgpuInstanceGetEncoderSessions"] = <intptr_t>__nvmlVgpuInstanceGetEncoderSessions
 
     global __nvmlVgpuInstanceGetFBCStats
-    data["__nvmlVgpuInstanceGetFBCStats"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFBCStats
+    data["__nvmlVgpuInstanceGetFBCStats"] = <intptr_t>__nvmlVgpuInstanceGetFBCStats
 
     global __nvmlVgpuInstanceGetFBCSessions
-    data["__nvmlVgpuInstanceGetFBCSessions"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetFBCSessions
+    data["__nvmlVgpuInstanceGetFBCSessions"] = <intptr_t>__nvmlVgpuInstanceGetFBCSessions
 
     global __nvmlVgpuInstanceGetGpuInstanceId
-    data["__nvmlVgpuInstanceGetGpuInstanceId"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetGpuInstanceId
+    data["__nvmlVgpuInstanceGetGpuInstanceId"] = <intptr_t>__nvmlVgpuInstanceGetGpuInstanceId
 
     global __nvmlVgpuInstanceGetGpuPciId
-    data["__nvmlVgpuInstanceGetGpuPciId"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetGpuPciId
+    data["__nvmlVgpuInstanceGetGpuPciId"] = <intptr_t>__nvmlVgpuInstanceGetGpuPciId
 
     global __nvmlVgpuTypeGetCapabilities
-    data["__nvmlVgpuTypeGetCapabilities"] = <_cyb_intptr_t>__nvmlVgpuTypeGetCapabilities
+    data["__nvmlVgpuTypeGetCapabilities"] = <intptr_t>__nvmlVgpuTypeGetCapabilities
 
     global __nvmlVgpuInstanceGetMdevUUID
-    data["__nvmlVgpuInstanceGetMdevUUID"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetMdevUUID
+    data["__nvmlVgpuInstanceGetMdevUUID"] = <intptr_t>__nvmlVgpuInstanceGetMdevUUID
 
     global __nvmlGpuInstanceGetCreatableVgpus
-    data["__nvmlGpuInstanceGetCreatableVgpus"] = <_cyb_intptr_t>__nvmlGpuInstanceGetCreatableVgpus
+    data["__nvmlGpuInstanceGetCreatableVgpus"] = <intptr_t>__nvmlGpuInstanceGetCreatableVgpus
 
     global __nvmlVgpuTypeGetMaxInstancesPerGpuInstance
-    data["__nvmlVgpuTypeGetMaxInstancesPerGpuInstance"] = <_cyb_intptr_t>__nvmlVgpuTypeGetMaxInstancesPerGpuInstance
+    data["__nvmlVgpuTypeGetMaxInstancesPerGpuInstance"] = <intptr_t>__nvmlVgpuTypeGetMaxInstancesPerGpuInstance
 
     global __nvmlGpuInstanceGetActiveVgpus
-    data["__nvmlGpuInstanceGetActiveVgpus"] = <_cyb_intptr_t>__nvmlGpuInstanceGetActiveVgpus
+    data["__nvmlGpuInstanceGetActiveVgpus"] = <intptr_t>__nvmlGpuInstanceGetActiveVgpus
 
     global __nvmlGpuInstanceSetVgpuSchedulerState
-    data["__nvmlGpuInstanceSetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState
+    data["__nvmlGpuInstanceSetVgpuSchedulerState"] = <intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState
 
     global __nvmlGpuInstanceGetVgpuSchedulerState
-    data["__nvmlGpuInstanceGetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState
+    data["__nvmlGpuInstanceGetVgpuSchedulerState"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState
 
     global __nvmlGpuInstanceGetVgpuSchedulerLog
-    data["__nvmlGpuInstanceGetVgpuSchedulerLog"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog
+    data["__nvmlGpuInstanceGetVgpuSchedulerLog"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog
 
     global __nvmlGpuInstanceGetVgpuTypeCreatablePlacements
-    data["__nvmlGpuInstanceGetVgpuTypeCreatablePlacements"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuTypeCreatablePlacements
+    data["__nvmlGpuInstanceGetVgpuTypeCreatablePlacements"] = <intptr_t>__nvmlGpuInstanceGetVgpuTypeCreatablePlacements
 
     global __nvmlGpuInstanceGetVgpuHeterogeneousMode
-    data["__nvmlGpuInstanceGetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuHeterogeneousMode
+    data["__nvmlGpuInstanceGetVgpuHeterogeneousMode"] = <intptr_t>__nvmlGpuInstanceGetVgpuHeterogeneousMode
 
     global __nvmlGpuInstanceSetVgpuHeterogeneousMode
-    data["__nvmlGpuInstanceSetVgpuHeterogeneousMode"] = <_cyb_intptr_t>__nvmlGpuInstanceSetVgpuHeterogeneousMode
+    data["__nvmlGpuInstanceSetVgpuHeterogeneousMode"] = <intptr_t>__nvmlGpuInstanceSetVgpuHeterogeneousMode
 
     global __nvmlVgpuInstanceGetMetadata
-    data["__nvmlVgpuInstanceGetMetadata"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetMetadata
+    data["__nvmlVgpuInstanceGetMetadata"] = <intptr_t>__nvmlVgpuInstanceGetMetadata
 
     global __nvmlDeviceGetVgpuMetadata
-    data["__nvmlDeviceGetVgpuMetadata"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuMetadata
+    data["__nvmlDeviceGetVgpuMetadata"] = <intptr_t>__nvmlDeviceGetVgpuMetadata
 
     global __nvmlGetVgpuCompatibility
-    data["__nvmlGetVgpuCompatibility"] = <_cyb_intptr_t>__nvmlGetVgpuCompatibility
+    data["__nvmlGetVgpuCompatibility"] = <intptr_t>__nvmlGetVgpuCompatibility
 
     global __nvmlDeviceGetPgpuMetadataString
-    data["__nvmlDeviceGetPgpuMetadataString"] = <_cyb_intptr_t>__nvmlDeviceGetPgpuMetadataString
+    data["__nvmlDeviceGetPgpuMetadataString"] = <intptr_t>__nvmlDeviceGetPgpuMetadataString
 
     global __nvmlDeviceGetVgpuSchedulerLog
-    data["__nvmlDeviceGetVgpuSchedulerLog"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerLog
+    data["__nvmlDeviceGetVgpuSchedulerLog"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerLog
 
     global __nvmlDeviceGetVgpuSchedulerState
-    data["__nvmlDeviceGetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerState
+    data["__nvmlDeviceGetVgpuSchedulerState"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerState
 
     global __nvmlDeviceGetVgpuSchedulerCapabilities
-    data["__nvmlDeviceGetVgpuSchedulerCapabilities"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerCapabilities
+    data["__nvmlDeviceGetVgpuSchedulerCapabilities"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerCapabilities
 
     global __nvmlDeviceSetVgpuSchedulerState
-    data["__nvmlDeviceSetVgpuSchedulerState"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuSchedulerState
+    data["__nvmlDeviceSetVgpuSchedulerState"] = <intptr_t>__nvmlDeviceSetVgpuSchedulerState
 
     global __nvmlGetVgpuVersion
-    data["__nvmlGetVgpuVersion"] = <_cyb_intptr_t>__nvmlGetVgpuVersion
+    data["__nvmlGetVgpuVersion"] = <intptr_t>__nvmlGetVgpuVersion
 
     global __nvmlSetVgpuVersion
-    data["__nvmlSetVgpuVersion"] = <_cyb_intptr_t>__nvmlSetVgpuVersion
+    data["__nvmlSetVgpuVersion"] = <intptr_t>__nvmlSetVgpuVersion
 
     global __nvmlDeviceGetVgpuUtilization
-    data["__nvmlDeviceGetVgpuUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuUtilization
+    data["__nvmlDeviceGetVgpuUtilization"] = <intptr_t>__nvmlDeviceGetVgpuUtilization
 
     global __nvmlDeviceGetVgpuInstancesUtilizationInfo
-    data["__nvmlDeviceGetVgpuInstancesUtilizationInfo"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuInstancesUtilizationInfo
+    data["__nvmlDeviceGetVgpuInstancesUtilizationInfo"] = <intptr_t>__nvmlDeviceGetVgpuInstancesUtilizationInfo
 
     global __nvmlDeviceGetVgpuProcessUtilization
-    data["__nvmlDeviceGetVgpuProcessUtilization"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuProcessUtilization
+    data["__nvmlDeviceGetVgpuProcessUtilization"] = <intptr_t>__nvmlDeviceGetVgpuProcessUtilization
 
     global __nvmlDeviceGetVgpuProcessesUtilizationInfo
-    data["__nvmlDeviceGetVgpuProcessesUtilizationInfo"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuProcessesUtilizationInfo
+    data["__nvmlDeviceGetVgpuProcessesUtilizationInfo"] = <intptr_t>__nvmlDeviceGetVgpuProcessesUtilizationInfo
 
     global __nvmlVgpuInstanceGetAccountingMode
-    data["__nvmlVgpuInstanceGetAccountingMode"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetAccountingMode
+    data["__nvmlVgpuInstanceGetAccountingMode"] = <intptr_t>__nvmlVgpuInstanceGetAccountingMode
 
     global __nvmlVgpuInstanceGetAccountingPids
-    data["__nvmlVgpuInstanceGetAccountingPids"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetAccountingPids
+    data["__nvmlVgpuInstanceGetAccountingPids"] = <intptr_t>__nvmlVgpuInstanceGetAccountingPids
 
     global __nvmlVgpuInstanceGetAccountingStats
-    data["__nvmlVgpuInstanceGetAccountingStats"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetAccountingStats
+    data["__nvmlVgpuInstanceGetAccountingStats"] = <intptr_t>__nvmlVgpuInstanceGetAccountingStats
 
     global __nvmlVgpuInstanceClearAccountingPids
-    data["__nvmlVgpuInstanceClearAccountingPids"] = <_cyb_intptr_t>__nvmlVgpuInstanceClearAccountingPids
+    data["__nvmlVgpuInstanceClearAccountingPids"] = <intptr_t>__nvmlVgpuInstanceClearAccountingPids
 
     global __nvmlVgpuInstanceGetLicenseInfo_v2
-    data["__nvmlVgpuInstanceGetLicenseInfo_v2"] = <_cyb_intptr_t>__nvmlVgpuInstanceGetLicenseInfo_v2
+    data["__nvmlVgpuInstanceGetLicenseInfo_v2"] = <intptr_t>__nvmlVgpuInstanceGetLicenseInfo_v2
 
     global __nvmlGetExcludedDeviceCount
-    data["__nvmlGetExcludedDeviceCount"] = <_cyb_intptr_t>__nvmlGetExcludedDeviceCount
+    data["__nvmlGetExcludedDeviceCount"] = <intptr_t>__nvmlGetExcludedDeviceCount
 
     global __nvmlGetExcludedDeviceInfoByIndex
-    data["__nvmlGetExcludedDeviceInfoByIndex"] = <_cyb_intptr_t>__nvmlGetExcludedDeviceInfoByIndex
+    data["__nvmlGetExcludedDeviceInfoByIndex"] = <intptr_t>__nvmlGetExcludedDeviceInfoByIndex
 
     global __nvmlDeviceSetMigMode
-    data["__nvmlDeviceSetMigMode"] = <_cyb_intptr_t>__nvmlDeviceSetMigMode
+    data["__nvmlDeviceSetMigMode"] = <intptr_t>__nvmlDeviceSetMigMode
 
     global __nvmlDeviceGetMigMode
-    data["__nvmlDeviceGetMigMode"] = <_cyb_intptr_t>__nvmlDeviceGetMigMode
+    data["__nvmlDeviceGetMigMode"] = <intptr_t>__nvmlDeviceGetMigMode
 
     global __nvmlDeviceGetGpuInstanceProfileInfoV
-    data["__nvmlDeviceGetGpuInstanceProfileInfoV"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoV
+    data["__nvmlDeviceGetGpuInstanceProfileInfoV"] = <intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoV
 
     global __nvmlDeviceGetGpuInstancePossiblePlacements_v2
-    data["__nvmlDeviceGetGpuInstancePossiblePlacements_v2"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstancePossiblePlacements_v2
+    data["__nvmlDeviceGetGpuInstancePossiblePlacements_v2"] = <intptr_t>__nvmlDeviceGetGpuInstancePossiblePlacements_v2
 
     global __nvmlDeviceGetGpuInstanceRemainingCapacity
-    data["__nvmlDeviceGetGpuInstanceRemainingCapacity"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceRemainingCapacity
+    data["__nvmlDeviceGetGpuInstanceRemainingCapacity"] = <intptr_t>__nvmlDeviceGetGpuInstanceRemainingCapacity
 
     global __nvmlDeviceCreateGpuInstance
-    data["__nvmlDeviceCreateGpuInstance"] = <_cyb_intptr_t>__nvmlDeviceCreateGpuInstance
+    data["__nvmlDeviceCreateGpuInstance"] = <intptr_t>__nvmlDeviceCreateGpuInstance
 
     global __nvmlDeviceCreateGpuInstanceWithPlacement
-    data["__nvmlDeviceCreateGpuInstanceWithPlacement"] = <_cyb_intptr_t>__nvmlDeviceCreateGpuInstanceWithPlacement
+    data["__nvmlDeviceCreateGpuInstanceWithPlacement"] = <intptr_t>__nvmlDeviceCreateGpuInstanceWithPlacement
 
     global __nvmlGpuInstanceDestroy
-    data["__nvmlGpuInstanceDestroy"] = <_cyb_intptr_t>__nvmlGpuInstanceDestroy
+    data["__nvmlGpuInstanceDestroy"] = <intptr_t>__nvmlGpuInstanceDestroy
 
     global __nvmlDeviceGetGpuInstances
-    data["__nvmlDeviceGetGpuInstances"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstances
+    data["__nvmlDeviceGetGpuInstances"] = <intptr_t>__nvmlDeviceGetGpuInstances
 
     global __nvmlDeviceGetGpuInstanceById
-    data["__nvmlDeviceGetGpuInstanceById"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceById
+    data["__nvmlDeviceGetGpuInstanceById"] = <intptr_t>__nvmlDeviceGetGpuInstanceById
 
     global __nvmlGpuInstanceGetInfo
-    data["__nvmlGpuInstanceGetInfo"] = <_cyb_intptr_t>__nvmlGpuInstanceGetInfo
+    data["__nvmlGpuInstanceGetInfo"] = <intptr_t>__nvmlGpuInstanceGetInfo
 
     global __nvmlGpuInstanceGetComputeInstanceProfileInfoV
-    data["__nvmlGpuInstanceGetComputeInstanceProfileInfoV"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstanceProfileInfoV
+    data["__nvmlGpuInstanceGetComputeInstanceProfileInfoV"] = <intptr_t>__nvmlGpuInstanceGetComputeInstanceProfileInfoV
 
     global __nvmlGpuInstanceGetComputeInstanceRemainingCapacity
-    data["__nvmlGpuInstanceGetComputeInstanceRemainingCapacity"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstanceRemainingCapacity
+    data["__nvmlGpuInstanceGetComputeInstanceRemainingCapacity"] = <intptr_t>__nvmlGpuInstanceGetComputeInstanceRemainingCapacity
 
     global __nvmlGpuInstanceGetComputeInstancePossiblePlacements
-    data["__nvmlGpuInstanceGetComputeInstancePossiblePlacements"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstancePossiblePlacements
+    data["__nvmlGpuInstanceGetComputeInstancePossiblePlacements"] = <intptr_t>__nvmlGpuInstanceGetComputeInstancePossiblePlacements
 
     global __nvmlGpuInstanceCreateComputeInstance
-    data["__nvmlGpuInstanceCreateComputeInstance"] = <_cyb_intptr_t>__nvmlGpuInstanceCreateComputeInstance
+    data["__nvmlGpuInstanceCreateComputeInstance"] = <intptr_t>__nvmlGpuInstanceCreateComputeInstance
 
     global __nvmlGpuInstanceCreateComputeInstanceWithPlacement
-    data["__nvmlGpuInstanceCreateComputeInstanceWithPlacement"] = <_cyb_intptr_t>__nvmlGpuInstanceCreateComputeInstanceWithPlacement
+    data["__nvmlGpuInstanceCreateComputeInstanceWithPlacement"] = <intptr_t>__nvmlGpuInstanceCreateComputeInstanceWithPlacement
 
     global __nvmlComputeInstanceDestroy
-    data["__nvmlComputeInstanceDestroy"] = <_cyb_intptr_t>__nvmlComputeInstanceDestroy
+    data["__nvmlComputeInstanceDestroy"] = <intptr_t>__nvmlComputeInstanceDestroy
 
     global __nvmlGpuInstanceGetComputeInstances
-    data["__nvmlGpuInstanceGetComputeInstances"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstances
+    data["__nvmlGpuInstanceGetComputeInstances"] = <intptr_t>__nvmlGpuInstanceGetComputeInstances
 
     global __nvmlGpuInstanceGetComputeInstanceById
-    data["__nvmlGpuInstanceGetComputeInstanceById"] = <_cyb_intptr_t>__nvmlGpuInstanceGetComputeInstanceById
+    data["__nvmlGpuInstanceGetComputeInstanceById"] = <intptr_t>__nvmlGpuInstanceGetComputeInstanceById
 
     global __nvmlComputeInstanceGetInfo_v2
-    data["__nvmlComputeInstanceGetInfo_v2"] = <_cyb_intptr_t>__nvmlComputeInstanceGetInfo_v2
+    data["__nvmlComputeInstanceGetInfo_v2"] = <intptr_t>__nvmlComputeInstanceGetInfo_v2
 
     global __nvmlDeviceIsMigDeviceHandle
-    data["__nvmlDeviceIsMigDeviceHandle"] = <_cyb_intptr_t>__nvmlDeviceIsMigDeviceHandle
+    data["__nvmlDeviceIsMigDeviceHandle"] = <intptr_t>__nvmlDeviceIsMigDeviceHandle
 
     global __nvmlDeviceGetGpuInstanceId
-    data["__nvmlDeviceGetGpuInstanceId"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceId
+    data["__nvmlDeviceGetGpuInstanceId"] = <intptr_t>__nvmlDeviceGetGpuInstanceId
 
     global __nvmlDeviceGetComputeInstanceId
-    data["__nvmlDeviceGetComputeInstanceId"] = <_cyb_intptr_t>__nvmlDeviceGetComputeInstanceId
+    data["__nvmlDeviceGetComputeInstanceId"] = <intptr_t>__nvmlDeviceGetComputeInstanceId
 
     global __nvmlDeviceGetMaxMigDeviceCount
-    data["__nvmlDeviceGetMaxMigDeviceCount"] = <_cyb_intptr_t>__nvmlDeviceGetMaxMigDeviceCount
+    data["__nvmlDeviceGetMaxMigDeviceCount"] = <intptr_t>__nvmlDeviceGetMaxMigDeviceCount
 
     global __nvmlDeviceGetMigDeviceHandleByIndex
-    data["__nvmlDeviceGetMigDeviceHandleByIndex"] = <_cyb_intptr_t>__nvmlDeviceGetMigDeviceHandleByIndex
+    data["__nvmlDeviceGetMigDeviceHandleByIndex"] = <intptr_t>__nvmlDeviceGetMigDeviceHandleByIndex
 
     global __nvmlDeviceGetDeviceHandleFromMigDeviceHandle
-    data["__nvmlDeviceGetDeviceHandleFromMigDeviceHandle"] = <_cyb_intptr_t>__nvmlDeviceGetDeviceHandleFromMigDeviceHandle
+    data["__nvmlDeviceGetDeviceHandleFromMigDeviceHandle"] = <intptr_t>__nvmlDeviceGetDeviceHandleFromMigDeviceHandle
 
     global __nvmlDeviceGetCapabilities
-    data["__nvmlDeviceGetCapabilities"] = <_cyb_intptr_t>__nvmlDeviceGetCapabilities
+    data["__nvmlDeviceGetCapabilities"] = <intptr_t>__nvmlDeviceGetCapabilities
 
     global __nvmlDevicePowerSmoothingActivatePresetProfile
-    data["__nvmlDevicePowerSmoothingActivatePresetProfile"] = <_cyb_intptr_t>__nvmlDevicePowerSmoothingActivatePresetProfile
+    data["__nvmlDevicePowerSmoothingActivatePresetProfile"] = <intptr_t>__nvmlDevicePowerSmoothingActivatePresetProfile
 
     global __nvmlDevicePowerSmoothingUpdatePresetProfileParam
-    data["__nvmlDevicePowerSmoothingUpdatePresetProfileParam"] = <_cyb_intptr_t>__nvmlDevicePowerSmoothingUpdatePresetProfileParam
+    data["__nvmlDevicePowerSmoothingUpdatePresetProfileParam"] = <intptr_t>__nvmlDevicePowerSmoothingUpdatePresetProfileParam
 
     global __nvmlDevicePowerSmoothingSetState
-    data["__nvmlDevicePowerSmoothingSetState"] = <_cyb_intptr_t>__nvmlDevicePowerSmoothingSetState
+    data["__nvmlDevicePowerSmoothingSetState"] = <intptr_t>__nvmlDevicePowerSmoothingSetState
 
     global __nvmlDeviceGetAddressingMode
-    data["__nvmlDeviceGetAddressingMode"] = <_cyb_intptr_t>__nvmlDeviceGetAddressingMode
+    data["__nvmlDeviceGetAddressingMode"] = <intptr_t>__nvmlDeviceGetAddressingMode
 
     global __nvmlDeviceGetRepairStatus
-    data["__nvmlDeviceGetRepairStatus"] = <_cyb_intptr_t>__nvmlDeviceGetRepairStatus
+    data["__nvmlDeviceGetRepairStatus"] = <intptr_t>__nvmlDeviceGetRepairStatus
 
     global __nvmlDeviceGetPowerMizerMode_v1
-    data["__nvmlDeviceGetPowerMizerMode_v1"] = <_cyb_intptr_t>__nvmlDeviceGetPowerMizerMode_v1
+    data["__nvmlDeviceGetPowerMizerMode_v1"] = <intptr_t>__nvmlDeviceGetPowerMizerMode_v1
 
     global __nvmlDeviceSetPowerMizerMode_v1
-    data["__nvmlDeviceSetPowerMizerMode_v1"] = <_cyb_intptr_t>__nvmlDeviceSetPowerMizerMode_v1
+    data["__nvmlDeviceSetPowerMizerMode_v1"] = <intptr_t>__nvmlDeviceSetPowerMizerMode_v1
 
     global __nvmlDeviceGetPdi
-    data["__nvmlDeviceGetPdi"] = <_cyb_intptr_t>__nvmlDeviceGetPdi
+    data["__nvmlDeviceGetPdi"] = <intptr_t>__nvmlDeviceGetPdi
 
     global __nvmlDeviceSetHostname_v1
-    data["__nvmlDeviceSetHostname_v1"] = <_cyb_intptr_t>__nvmlDeviceSetHostname_v1
+    data["__nvmlDeviceSetHostname_v1"] = <intptr_t>__nvmlDeviceSetHostname_v1
 
     global __nvmlDeviceGetHostname_v1
-    data["__nvmlDeviceGetHostname_v1"] = <_cyb_intptr_t>__nvmlDeviceGetHostname_v1
+    data["__nvmlDeviceGetHostname_v1"] = <intptr_t>__nvmlDeviceGetHostname_v1
 
     global __nvmlDeviceGetNvLinkInfo
-    data["__nvmlDeviceGetNvLinkInfo"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkInfo
+    data["__nvmlDeviceGetNvLinkInfo"] = <intptr_t>__nvmlDeviceGetNvLinkInfo
 
     global __nvmlDeviceReadWritePRM_v1
-    data["__nvmlDeviceReadWritePRM_v1"] = <_cyb_intptr_t>__nvmlDeviceReadWritePRM_v1
+    data["__nvmlDeviceReadWritePRM_v1"] = <intptr_t>__nvmlDeviceReadWritePRM_v1
 
     global __nvmlDeviceGetGpuInstanceProfileInfoByIdV
-    data["__nvmlDeviceGetGpuInstanceProfileInfoByIdV"] = <_cyb_intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoByIdV
+    data["__nvmlDeviceGetGpuInstanceProfileInfoByIdV"] = <intptr_t>__nvmlDeviceGetGpuInstanceProfileInfoByIdV
 
     global __nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts
-    data["__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts"] = <_cyb_intptr_t>__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts
+    data["__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts"] = <intptr_t>__nvmlDeviceGetSramUniqueUncorrectedEccErrorCounts
 
     global __nvmlDeviceGetUnrepairableMemoryFlag_v1
-    data["__nvmlDeviceGetUnrepairableMemoryFlag_v1"] = <_cyb_intptr_t>__nvmlDeviceGetUnrepairableMemoryFlag_v1
+    data["__nvmlDeviceGetUnrepairableMemoryFlag_v1"] = <intptr_t>__nvmlDeviceGetUnrepairableMemoryFlag_v1
 
     global __nvmlDeviceReadPRMCounters_v1
-    data["__nvmlDeviceReadPRMCounters_v1"] = <_cyb_intptr_t>__nvmlDeviceReadPRMCounters_v1
+    data["__nvmlDeviceReadPRMCounters_v1"] = <intptr_t>__nvmlDeviceReadPRMCounters_v1
 
     global __nvmlDeviceSetRusdSettings_v1
-    data["__nvmlDeviceSetRusdSettings_v1"] = <_cyb_intptr_t>__nvmlDeviceSetRusdSettings_v1
+    data["__nvmlDeviceSetRusdSettings_v1"] = <intptr_t>__nvmlDeviceSetRusdSettings_v1
 
     global __nvmlDeviceVgpuForceGspUnload
-    data["__nvmlDeviceVgpuForceGspUnload"] = <_cyb_intptr_t>__nvmlDeviceVgpuForceGspUnload
+    data["__nvmlDeviceVgpuForceGspUnload"] = <intptr_t>__nvmlDeviceVgpuForceGspUnload
 
     global __nvmlDeviceGetVgpuSchedulerState_v2
-    data["__nvmlDeviceGetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerState_v2
+    data["__nvmlDeviceGetVgpuSchedulerState_v2"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerState_v2
 
     global __nvmlGpuInstanceGetVgpuSchedulerState_v2
-    data["__nvmlGpuInstanceGetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState_v2
+    data["__nvmlGpuInstanceGetVgpuSchedulerState_v2"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerState_v2
 
     global __nvmlDeviceGetVgpuSchedulerLog_v2
-    data["__nvmlDeviceGetVgpuSchedulerLog_v2"] = <_cyb_intptr_t>__nvmlDeviceGetVgpuSchedulerLog_v2
+    data["__nvmlDeviceGetVgpuSchedulerLog_v2"] = <intptr_t>__nvmlDeviceGetVgpuSchedulerLog_v2
 
     global __nvmlGpuInstanceGetVgpuSchedulerLog_v2
-    data["__nvmlGpuInstanceGetVgpuSchedulerLog_v2"] = <_cyb_intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog_v2
+    data["__nvmlGpuInstanceGetVgpuSchedulerLog_v2"] = <intptr_t>__nvmlGpuInstanceGetVgpuSchedulerLog_v2
 
     global __nvmlDeviceSetVgpuSchedulerState_v2
-    data["__nvmlDeviceSetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlDeviceSetVgpuSchedulerState_v2
+    data["__nvmlDeviceSetVgpuSchedulerState_v2"] = <intptr_t>__nvmlDeviceSetVgpuSchedulerState_v2
 
     global __nvmlGpuInstanceSetVgpuSchedulerState_v2
-    data["__nvmlGpuInstanceSetVgpuSchedulerState_v2"] = <_cyb_intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState_v2
+    data["__nvmlGpuInstanceSetVgpuSchedulerState_v2"] = <intptr_t>__nvmlGpuInstanceSetVgpuSchedulerState_v2
 
     global __nvmlSystemGetCPER_v1
-    data["__nvmlSystemGetCPER_v1"] = <_cyb_intptr_t>__nvmlSystemGetCPER_v1
+    data["__nvmlSystemGetCPER_v1"] = <intptr_t>__nvmlSystemGetCPER_v1
 
     global __nvmlDeviceGetBBXTimeData_v1
-    data["__nvmlDeviceGetBBXTimeData_v1"] = <_cyb_intptr_t>__nvmlDeviceGetBBXTimeData_v1
+    data["__nvmlDeviceGetBBXTimeData_v1"] = <intptr_t>__nvmlDeviceGetBBXTimeData_v1
 
     global __nvmlDeviceGetAccountingStats_v2
-    data["__nvmlDeviceGetAccountingStats_v2"] = <_cyb_intptr_t>__nvmlDeviceGetAccountingStats_v2
+    data["__nvmlDeviceGetAccountingStats_v2"] = <intptr_t>__nvmlDeviceGetAccountingStats_v2
 
     global __nvmlDeviceGetRemappedRows_v2
-    data["__nvmlDeviceGetRemappedRows_v2"] = <_cyb_intptr_t>__nvmlDeviceGetRemappedRows_v2
+    data["__nvmlDeviceGetRemappedRows_v2"] = <intptr_t>__nvmlDeviceGetRemappedRows_v2
 
     global __nvmlDeviceSetAdaptiveTgpMode_v1
-    data["__nvmlDeviceSetAdaptiveTgpMode_v1"] = <_cyb_intptr_t>__nvmlDeviceSetAdaptiveTgpMode_v1
+    data["__nvmlDeviceSetAdaptiveTgpMode_v1"] = <intptr_t>__nvmlDeviceSetAdaptiveTgpMode_v1
 
     global __nvmlDeviceGetAdaptiveTgpModeInfo_v1
-    data["__nvmlDeviceGetAdaptiveTgpModeInfo_v1"] = <_cyb_intptr_t>__nvmlDeviceGetAdaptiveTgpModeInfo_v1
+    data["__nvmlDeviceGetAdaptiveTgpModeInfo_v1"] = <intptr_t>__nvmlDeviceGetAdaptiveTgpModeInfo_v1
 
     global __nvmlDeviceSetMemoryLimits_v1
-    data["__nvmlDeviceSetMemoryLimits_v1"] = <_cyb_intptr_t>__nvmlDeviceSetMemoryLimits_v1
+    data["__nvmlDeviceSetMemoryLimits_v1"] = <intptr_t>__nvmlDeviceSetMemoryLimits_v1
 
     global __nvmlDeviceGetMemoryLimits_v1
-    data["__nvmlDeviceGetMemoryLimits_v1"] = <_cyb_intptr_t>__nvmlDeviceGetMemoryLimits_v1
+    data["__nvmlDeviceGetMemoryLimits_v1"] = <intptr_t>__nvmlDeviceGetMemoryLimits_v1
 
     global __nvmlDeviceGetGpuFabricInfo_v4
-    data["__nvmlDeviceGetGpuFabricInfo_v4"] = <_cyb_intptr_t>__nvmlDeviceGetGpuFabricInfo_v4
+    data["__nvmlDeviceGetGpuFabricInfo_v4"] = <intptr_t>__nvmlDeviceGetGpuFabricInfo_v4
 
     global __nvmlDevicePerfMetricsGetSamples_v1
-    data["__nvmlDevicePerfMetricsGetSamples_v1"] = <_cyb_intptr_t>__nvmlDevicePerfMetricsGetSamples_v1
+    data["__nvmlDevicePerfMetricsGetSamples_v1"] = <intptr_t>__nvmlDevicePerfMetricsGetSamples_v1
 
     global __nvmlDeviceSetNvlinkBwModeAsync_v1
-    data["__nvmlDeviceSetNvlinkBwModeAsync_v1"] = <_cyb_intptr_t>__nvmlDeviceSetNvlinkBwModeAsync_v1
+    data["__nvmlDeviceSetNvlinkBwModeAsync_v1"] = <intptr_t>__nvmlDeviceSetNvlinkBwModeAsync_v1
 
     global __nvmlDeviceGetNvLinkTelemetrySamples_v1
-    data["__nvmlDeviceGetNvLinkTelemetrySamples_v1"] = <_cyb_intptr_t>__nvmlDeviceGetNvLinkTelemetrySamples_v1
+    data["__nvmlDeviceGetNvLinkTelemetrySamples_v1"] = <intptr_t>__nvmlDeviceGetNvLinkTelemetrySamples_v1
 
     global __nvmlEventSetRegisterGpuOperationalEvents_v1
-    data["__nvmlEventSetRegisterGpuOperationalEvents_v1"] = <_cyb_intptr_t>__nvmlEventSetRegisterGpuOperationalEvents_v1
+    data["__nvmlEventSetRegisterGpuOperationalEvents_v1"] = <intptr_t>__nvmlEventSetRegisterGpuOperationalEvents_v1
 
     global __nvmlEventSetWait_v3
-    data["__nvmlEventSetWait_v3"] = <_cyb_intptr_t>__nvmlEventSetWait_v3
+    data["__nvmlEventSetWait_v3"] = <intptr_t>__nvmlEventSetWait_v3
 
     global __nvmlEventSetGetContextCount_v1
-    data["__nvmlEventSetGetContextCount_v1"] = <_cyb_intptr_t>__nvmlEventSetGetContextCount_v1
+    data["__nvmlEventSetGetContextCount_v1"] = <intptr_t>__nvmlEventSetGetContextCount_v1
 
     global __nvmlEventSetGetContextInfo_v1
-    data["__nvmlEventSetGetContextInfo_v1"] = <_cyb_intptr_t>__nvmlEventSetGetContextInfo_v1
+    data["__nvmlEventSetGetContextInfo_v1"] = <intptr_t>__nvmlEventSetGetContextInfo_v1
 
     global __nvmlEventSetGetContextData_v1
-    data["__nvmlEventSetGetContextData_v1"] = <_cyb_intptr_t>__nvmlEventSetGetContextData_v1
+    data["__nvmlEventSetGetContextData_v1"] = <intptr_t>__nvmlEventSetGetContextData_v1
 
     global __nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
-    data["__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1"] = <_cyb_intptr_t>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
+    data["__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1"] = <intptr_t>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
 
     global __nvmlDeviceGetBankRemapperStatus_v1
-    data["__nvmlDeviceGetBankRemapperStatus_v1"] = <_cyb_intptr_t>__nvmlDeviceGetBankRemapperStatus_v1
+    data["__nvmlDeviceGetBankRemapperStatus_v1"] = <intptr_t>__nvmlDeviceGetBankRemapperStatus_v1
     _cyb_func_ptrs = data
     return data
 
@@ -6339,54 +6341,54 @@ cdef nvmlReturn_t _nvmlEventSetRegisterGpuOperationalEvents_v1(nvmlEventSet_t ev
         eventSet, config)
 
 
-cdef nvmlReturn_t _nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventData_v2_t* data, unsigned int timeoutms) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventSetWait_v3_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetWait_v3
     _check_or_init_nvml()
     if __nvmlEventSetWait_v3 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetWait_v3 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventData_v2_t*, unsigned int) noexcept nogil>__nvmlEventSetWait_v3)(
-        set, data, timeoutms)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetWait_v3_t*) noexcept nogil>__nvmlEventSetWait_v3)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, unsigned int* count) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, nvmlEventSetGetContextCount_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetContextCount_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetContextCount_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetContextCount_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int*) noexcept nogil>__nvmlEventSetGetContextCount_v1)(
-        set, count)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetContextCount_v1_t*) noexcept nogil>__nvmlEventSetGetContextCount_v1)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, unsigned int index, nvmlOperationalEventContextInfo_v1_t* info) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, nvmlEventSetGetContextInfo_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetContextInfo_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetContextInfo_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetContextInfo_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int, nvmlOperationalEventContextInfo_v1_t*) noexcept nogil>__nvmlEventSetGetContextInfo_v1)(
-        set, index, info)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetContextInfo_v1_t*) noexcept nogil>__nvmlEventSetGetContextInfo_v1)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetContextData_v1(nvmlEventSet_t set, unsigned int index, void* data, unsigned int* dataSize) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetContextData_v1(nvmlEventSet_t set, nvmlEventSetGetContextData_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetContextData_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetContextData_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetContextData_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int, void*, unsigned int*) noexcept nogil>__nvmlEventSetGetContextData_v1)(
-        set, index, data, dataSize)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetContextData_v1_t*) noexcept nogil>__nvmlEventSetGetContextData_v1)(
+        set, params)
 
 
-cdef nvmlReturn_t _nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, unsigned int index, nvmlGpuOperationalEventContextLegacyXid_v1_t* xid) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+cdef nvmlReturn_t _nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
     global __nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1
     _check_or_init_nvml()
     if __nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1 == NULL:
         with gil:
             raise FunctionNotFoundError("function nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1 is not found")
-    return (<nvmlReturn_t (*)(nvmlEventSet_t, unsigned int, nvmlGpuOperationalEventContextLegacyXid_v1_t*) noexcept nogil>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1)(
-        set, index, xid)
+    return (<nvmlReturn_t (*)(nvmlEventSet_t, nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t*) noexcept nogil>__nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1)(
+        set, params)
 
 
 cdef nvmlReturn_t _nvmlDeviceGetBankRemapperStatus_v1(nvmlDevice_t device, nvmlEccBankRemapperStatus_v1_t* pBankRemapperStatus) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
diff --git a/cuda_bindings/cuda/bindings/_internal/nvrtc.pxd b/cuda_bindings/cuda/bindings/_internal/nvrtc.pxd
index 68f4cc772fd..1da9da1cdcf 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvrtc.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/nvrtc.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=8d4e35dd6b1a5b4d4138b57d889d92501da4c91fc6c3d38c050bb2359e033589
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1710f2e6f38e8023555cf41d7faf7c3aba487689e58eddac250903cc33d6d4fe
 from ..cynvrtc cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvrtc_linux.pyx b/cuda_bindings/cuda/bindings/_internal/nvrtc_linux.pyx
index 06a6277d829..861fc42e34b 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvrtc_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvrtc_linux.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=3d6013b99cb59aaab8ae661d838401b123ed27efda53268eab153c7add7ca3a8
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=d8397f8100cfd6d26ff1c1f4ea795dd81e92f4beb60d304b5306733152305760
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,7 @@ cdef extern from "<dlfcn.h>":
     void* _cyb_dlsym "dlsym"(void*, const char*) nogil
     const void * _cyb_RTLD_DEFAULT "RTLD_DEFAULT"
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport intptr_t
 
 import threading as _cyb_threading
 
@@ -322,91 +321,91 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvrtc()
     cdef dict data = {}
     global __nvrtcGetErrorString
-    data["__nvrtcGetErrorString"] = <_cyb_intptr_t>__nvrtcGetErrorString
+    data["__nvrtcGetErrorString"] = <intptr_t>__nvrtcGetErrorString
 
     global __nvrtcVersion
-    data["__nvrtcVersion"] = <_cyb_intptr_t>__nvrtcVersion
+    data["__nvrtcVersion"] = <intptr_t>__nvrtcVersion
 
     global __nvrtcGetNumSupportedArchs
-    data["__nvrtcGetNumSupportedArchs"] = <_cyb_intptr_t>__nvrtcGetNumSupportedArchs
+    data["__nvrtcGetNumSupportedArchs"] = <intptr_t>__nvrtcGetNumSupportedArchs
 
     global __nvrtcGetSupportedArchs
-    data["__nvrtcGetSupportedArchs"] = <_cyb_intptr_t>__nvrtcGetSupportedArchs
+    data["__nvrtcGetSupportedArchs"] = <intptr_t>__nvrtcGetSupportedArchs
 
     global __nvrtcCreateProgram
-    data["__nvrtcCreateProgram"] = <_cyb_intptr_t>__nvrtcCreateProgram
+    data["__nvrtcCreateProgram"] = <intptr_t>__nvrtcCreateProgram
 
     global __nvrtcDestroyProgram
-    data["__nvrtcDestroyProgram"] = <_cyb_intptr_t>__nvrtcDestroyProgram
+    data["__nvrtcDestroyProgram"] = <intptr_t>__nvrtcDestroyProgram
 
     global __nvrtcCompileProgram
-    data["__nvrtcCompileProgram"] = <_cyb_intptr_t>__nvrtcCompileProgram
+    data["__nvrtcCompileProgram"] = <intptr_t>__nvrtcCompileProgram
 
     global __nvrtcGetPTXSize
-    data["__nvrtcGetPTXSize"] = <_cyb_intptr_t>__nvrtcGetPTXSize
+    data["__nvrtcGetPTXSize"] = <intptr_t>__nvrtcGetPTXSize
 
     global __nvrtcGetPTX
-    data["__nvrtcGetPTX"] = <_cyb_intptr_t>__nvrtcGetPTX
+    data["__nvrtcGetPTX"] = <intptr_t>__nvrtcGetPTX
 
     global __nvrtcGetCUBINSize
-    data["__nvrtcGetCUBINSize"] = <_cyb_intptr_t>__nvrtcGetCUBINSize
+    data["__nvrtcGetCUBINSize"] = <intptr_t>__nvrtcGetCUBINSize
 
     global __nvrtcGetCUBIN
-    data["__nvrtcGetCUBIN"] = <_cyb_intptr_t>__nvrtcGetCUBIN
+    data["__nvrtcGetCUBIN"] = <intptr_t>__nvrtcGetCUBIN
 
     global __nvrtcGetLTOIRSize
-    data["__nvrtcGetLTOIRSize"] = <_cyb_intptr_t>__nvrtcGetLTOIRSize
+    data["__nvrtcGetLTOIRSize"] = <intptr_t>__nvrtcGetLTOIRSize
 
     global __nvrtcGetLTOIR
-    data["__nvrtcGetLTOIR"] = <_cyb_intptr_t>__nvrtcGetLTOIR
+    data["__nvrtcGetLTOIR"] = <intptr_t>__nvrtcGetLTOIR
 
     global __nvrtcGetOptiXIRSize
-    data["__nvrtcGetOptiXIRSize"] = <_cyb_intptr_t>__nvrtcGetOptiXIRSize
+    data["__nvrtcGetOptiXIRSize"] = <intptr_t>__nvrtcGetOptiXIRSize
 
     global __nvrtcGetOptiXIR
-    data["__nvrtcGetOptiXIR"] = <_cyb_intptr_t>__nvrtcGetOptiXIR
+    data["__nvrtcGetOptiXIR"] = <intptr_t>__nvrtcGetOptiXIR
 
     global __nvrtcGetProgramLogSize
-    data["__nvrtcGetProgramLogSize"] = <_cyb_intptr_t>__nvrtcGetProgramLogSize
+    data["__nvrtcGetProgramLogSize"] = <intptr_t>__nvrtcGetProgramLogSize
 
     global __nvrtcGetProgramLog
-    data["__nvrtcGetProgramLog"] = <_cyb_intptr_t>__nvrtcGetProgramLog
+    data["__nvrtcGetProgramLog"] = <intptr_t>__nvrtcGetProgramLog
 
     global __nvrtcAddNameExpression
-    data["__nvrtcAddNameExpression"] = <_cyb_intptr_t>__nvrtcAddNameExpression
+    data["__nvrtcAddNameExpression"] = <intptr_t>__nvrtcAddNameExpression
 
     global __nvrtcGetLoweredName
-    data["__nvrtcGetLoweredName"] = <_cyb_intptr_t>__nvrtcGetLoweredName
+    data["__nvrtcGetLoweredName"] = <intptr_t>__nvrtcGetLoweredName
 
     global __nvrtcGetPCHHeapSize
-    data["__nvrtcGetPCHHeapSize"] = <_cyb_intptr_t>__nvrtcGetPCHHeapSize
+    data["__nvrtcGetPCHHeapSize"] = <intptr_t>__nvrtcGetPCHHeapSize
 
     global __nvrtcSetPCHHeapSize
-    data["__nvrtcSetPCHHeapSize"] = <_cyb_intptr_t>__nvrtcSetPCHHeapSize
+    data["__nvrtcSetPCHHeapSize"] = <intptr_t>__nvrtcSetPCHHeapSize
 
     global __nvrtcGetPCHCreateStatus
-    data["__nvrtcGetPCHCreateStatus"] = <_cyb_intptr_t>__nvrtcGetPCHCreateStatus
+    data["__nvrtcGetPCHCreateStatus"] = <intptr_t>__nvrtcGetPCHCreateStatus
 
     global __nvrtcGetPCHHeapSizeRequired
-    data["__nvrtcGetPCHHeapSizeRequired"] = <_cyb_intptr_t>__nvrtcGetPCHHeapSizeRequired
+    data["__nvrtcGetPCHHeapSizeRequired"] = <intptr_t>__nvrtcGetPCHHeapSizeRequired
 
     global __nvrtcSetFlowCallback
-    data["__nvrtcSetFlowCallback"] = <_cyb_intptr_t>__nvrtcSetFlowCallback
+    data["__nvrtcSetFlowCallback"] = <intptr_t>__nvrtcSetFlowCallback
 
     global __nvrtcGetTileIRSize
-    data["__nvrtcGetTileIRSize"] = <_cyb_intptr_t>__nvrtcGetTileIRSize
+    data["__nvrtcGetTileIRSize"] = <intptr_t>__nvrtcGetTileIRSize
 
     global __nvrtcGetTileIR
-    data["__nvrtcGetTileIR"] = <_cyb_intptr_t>__nvrtcGetTileIR
+    data["__nvrtcGetTileIR"] = <intptr_t>__nvrtcGetTileIR
 
     global __nvrtcInstallBundledHeaders
-    data["__nvrtcInstallBundledHeaders"] = <_cyb_intptr_t>__nvrtcInstallBundledHeaders
+    data["__nvrtcInstallBundledHeaders"] = <intptr_t>__nvrtcInstallBundledHeaders
 
     global __nvrtcGetBundledHeadersInfo
-    data["__nvrtcGetBundledHeadersInfo"] = <_cyb_intptr_t>__nvrtcGetBundledHeadersInfo
+    data["__nvrtcGetBundledHeadersInfo"] = <intptr_t>__nvrtcGetBundledHeadersInfo
 
     global __nvrtcRemoveBundledHeaders
-    data["__nvrtcRemoveBundledHeaders"] = <_cyb_intptr_t>__nvrtcRemoveBundledHeaders
+    data["__nvrtcRemoveBundledHeaders"] = <intptr_t>__nvrtcRemoveBundledHeaders
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvrtc_windows.pyx b/cuda_bindings/cuda/bindings/_internal/nvrtc_windows.pyx
index 752c659677f..917f6c45dd6 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvrtc_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvrtc_windows.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=574a59b0c82321fb7c287f06c11dd873715e47bea253df57466f0cfc29d8f5de
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=b324edc3b551146f59d4df5588a6f5d1f06ec91d193333dcda5c35ca49dc251d
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,10 @@ cdef extern from "<windows.h>":
     ctypedef void* HMODULE
     void* _cyb_GetProcAddress "GetProcAddress"(HMODULE, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uintptr_t,
+)
 
 import threading as _cyb_threading
 
@@ -206,91 +208,91 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvrtc()
     cdef dict data = {}
     global __nvrtcGetErrorString
-    data["__nvrtcGetErrorString"] = <_cyb_intptr_t>__nvrtcGetErrorString
+    data["__nvrtcGetErrorString"] = <intptr_t>__nvrtcGetErrorString
 
     global __nvrtcVersion
-    data["__nvrtcVersion"] = <_cyb_intptr_t>__nvrtcVersion
+    data["__nvrtcVersion"] = <intptr_t>__nvrtcVersion
 
     global __nvrtcGetNumSupportedArchs
-    data["__nvrtcGetNumSupportedArchs"] = <_cyb_intptr_t>__nvrtcGetNumSupportedArchs
+    data["__nvrtcGetNumSupportedArchs"] = <intptr_t>__nvrtcGetNumSupportedArchs
 
     global __nvrtcGetSupportedArchs
-    data["__nvrtcGetSupportedArchs"] = <_cyb_intptr_t>__nvrtcGetSupportedArchs
+    data["__nvrtcGetSupportedArchs"] = <intptr_t>__nvrtcGetSupportedArchs
 
     global __nvrtcCreateProgram
-    data["__nvrtcCreateProgram"] = <_cyb_intptr_t>__nvrtcCreateProgram
+    data["__nvrtcCreateProgram"] = <intptr_t>__nvrtcCreateProgram
 
     global __nvrtcDestroyProgram
-    data["__nvrtcDestroyProgram"] = <_cyb_intptr_t>__nvrtcDestroyProgram
+    data["__nvrtcDestroyProgram"] = <intptr_t>__nvrtcDestroyProgram
 
     global __nvrtcCompileProgram
-    data["__nvrtcCompileProgram"] = <_cyb_intptr_t>__nvrtcCompileProgram
+    data["__nvrtcCompileProgram"] = <intptr_t>__nvrtcCompileProgram
 
     global __nvrtcGetPTXSize
-    data["__nvrtcGetPTXSize"] = <_cyb_intptr_t>__nvrtcGetPTXSize
+    data["__nvrtcGetPTXSize"] = <intptr_t>__nvrtcGetPTXSize
 
     global __nvrtcGetPTX
-    data["__nvrtcGetPTX"] = <_cyb_intptr_t>__nvrtcGetPTX
+    data["__nvrtcGetPTX"] = <intptr_t>__nvrtcGetPTX
 
     global __nvrtcGetCUBINSize
-    data["__nvrtcGetCUBINSize"] = <_cyb_intptr_t>__nvrtcGetCUBINSize
+    data["__nvrtcGetCUBINSize"] = <intptr_t>__nvrtcGetCUBINSize
 
     global __nvrtcGetCUBIN
-    data["__nvrtcGetCUBIN"] = <_cyb_intptr_t>__nvrtcGetCUBIN
+    data["__nvrtcGetCUBIN"] = <intptr_t>__nvrtcGetCUBIN
 
     global __nvrtcGetLTOIRSize
-    data["__nvrtcGetLTOIRSize"] = <_cyb_intptr_t>__nvrtcGetLTOIRSize
+    data["__nvrtcGetLTOIRSize"] = <intptr_t>__nvrtcGetLTOIRSize
 
     global __nvrtcGetLTOIR
-    data["__nvrtcGetLTOIR"] = <_cyb_intptr_t>__nvrtcGetLTOIR
+    data["__nvrtcGetLTOIR"] = <intptr_t>__nvrtcGetLTOIR
 
     global __nvrtcGetOptiXIRSize
-    data["__nvrtcGetOptiXIRSize"] = <_cyb_intptr_t>__nvrtcGetOptiXIRSize
+    data["__nvrtcGetOptiXIRSize"] = <intptr_t>__nvrtcGetOptiXIRSize
 
     global __nvrtcGetOptiXIR
-    data["__nvrtcGetOptiXIR"] = <_cyb_intptr_t>__nvrtcGetOptiXIR
+    data["__nvrtcGetOptiXIR"] = <intptr_t>__nvrtcGetOptiXIR
 
     global __nvrtcGetProgramLogSize
-    data["__nvrtcGetProgramLogSize"] = <_cyb_intptr_t>__nvrtcGetProgramLogSize
+    data["__nvrtcGetProgramLogSize"] = <intptr_t>__nvrtcGetProgramLogSize
 
     global __nvrtcGetProgramLog
-    data["__nvrtcGetProgramLog"] = <_cyb_intptr_t>__nvrtcGetProgramLog
+    data["__nvrtcGetProgramLog"] = <intptr_t>__nvrtcGetProgramLog
 
     global __nvrtcAddNameExpression
-    data["__nvrtcAddNameExpression"] = <_cyb_intptr_t>__nvrtcAddNameExpression
+    data["__nvrtcAddNameExpression"] = <intptr_t>__nvrtcAddNameExpression
 
     global __nvrtcGetLoweredName
-    data["__nvrtcGetLoweredName"] = <_cyb_intptr_t>__nvrtcGetLoweredName
+    data["__nvrtcGetLoweredName"] = <intptr_t>__nvrtcGetLoweredName
 
     global __nvrtcGetPCHHeapSize
-    data["__nvrtcGetPCHHeapSize"] = <_cyb_intptr_t>__nvrtcGetPCHHeapSize
+    data["__nvrtcGetPCHHeapSize"] = <intptr_t>__nvrtcGetPCHHeapSize
 
     global __nvrtcSetPCHHeapSize
-    data["__nvrtcSetPCHHeapSize"] = <_cyb_intptr_t>__nvrtcSetPCHHeapSize
+    data["__nvrtcSetPCHHeapSize"] = <intptr_t>__nvrtcSetPCHHeapSize
 
     global __nvrtcGetPCHCreateStatus
-    data["__nvrtcGetPCHCreateStatus"] = <_cyb_intptr_t>__nvrtcGetPCHCreateStatus
+    data["__nvrtcGetPCHCreateStatus"] = <intptr_t>__nvrtcGetPCHCreateStatus
 
     global __nvrtcGetPCHHeapSizeRequired
-    data["__nvrtcGetPCHHeapSizeRequired"] = <_cyb_intptr_t>__nvrtcGetPCHHeapSizeRequired
+    data["__nvrtcGetPCHHeapSizeRequired"] = <intptr_t>__nvrtcGetPCHHeapSizeRequired
 
     global __nvrtcSetFlowCallback
-    data["__nvrtcSetFlowCallback"] = <_cyb_intptr_t>__nvrtcSetFlowCallback
+    data["__nvrtcSetFlowCallback"] = <intptr_t>__nvrtcSetFlowCallback
 
     global __nvrtcGetTileIRSize
-    data["__nvrtcGetTileIRSize"] = <_cyb_intptr_t>__nvrtcGetTileIRSize
+    data["__nvrtcGetTileIRSize"] = <intptr_t>__nvrtcGetTileIRSize
 
     global __nvrtcGetTileIR
-    data["__nvrtcGetTileIR"] = <_cyb_intptr_t>__nvrtcGetTileIR
+    data["__nvrtcGetTileIR"] = <intptr_t>__nvrtcGetTileIR
 
     global __nvrtcInstallBundledHeaders
-    data["__nvrtcInstallBundledHeaders"] = <_cyb_intptr_t>__nvrtcInstallBundledHeaders
+    data["__nvrtcInstallBundledHeaders"] = <intptr_t>__nvrtcInstallBundledHeaders
 
     global __nvrtcGetBundledHeadersInfo
-    data["__nvrtcGetBundledHeadersInfo"] = <_cyb_intptr_t>__nvrtcGetBundledHeadersInfo
+    data["__nvrtcGetBundledHeadersInfo"] = <intptr_t>__nvrtcGetBundledHeadersInfo
 
     global __nvrtcRemoveBundledHeaders
-    data["__nvrtcRemoveBundledHeaders"] = <_cyb_intptr_t>__nvrtcRemoveBundledHeaders
+    data["__nvrtcRemoveBundledHeaders"] = <intptr_t>__nvrtcRemoveBundledHeaders
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvvm.pxd b/cuda_bindings/cuda/bindings/_internal/nvvm.pxd
index 205bf7a658f..5b9abafa5df 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvvm.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/nvvm.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1bb383561fd7ffa5411d336ed9df7dbd5d59ed0a9215e82c9938dd54266f9106
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=6be47c668a3a1086937075cb5f4798941232ec81027841b98ee6ca66c277ff0c
 from ..cynvvm cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx b/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx
index 08f74faa61b..39329bc9b64 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvvm_linux.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=b8fe65feec44ce979fc981ea49fefa1b8bdd487092159d597ba5b18b427cc74d
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=cf645e79d2d72cd4c10d5f4fcd6bab245f292559ac432180554c0d944aa03dae
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,7 @@ cdef extern from "<dlfcn.h>":
     void* _cyb_dlsym "dlsym"(void*, const char*) nogil
     const void * _cyb_RTLD_DEFAULT "RTLD_DEFAULT"
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport intptr_t
 
 import threading as _cyb_threading
 
@@ -202,46 +201,46 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvvm()
     cdef dict data = {}
     global __nvvmGetErrorString
-    data["__nvvmGetErrorString"] = <_cyb_intptr_t>__nvvmGetErrorString
+    data["__nvvmGetErrorString"] = <intptr_t>__nvvmGetErrorString
 
     global __nvvmVersion
-    data["__nvvmVersion"] = <_cyb_intptr_t>__nvvmVersion
+    data["__nvvmVersion"] = <intptr_t>__nvvmVersion
 
     global __nvvmIRVersion
-    data["__nvvmIRVersion"] = <_cyb_intptr_t>__nvvmIRVersion
+    data["__nvvmIRVersion"] = <intptr_t>__nvvmIRVersion
 
     global __nvvmCreateProgram
-    data["__nvvmCreateProgram"] = <_cyb_intptr_t>__nvvmCreateProgram
+    data["__nvvmCreateProgram"] = <intptr_t>__nvvmCreateProgram
 
     global __nvvmDestroyProgram
-    data["__nvvmDestroyProgram"] = <_cyb_intptr_t>__nvvmDestroyProgram
+    data["__nvvmDestroyProgram"] = <intptr_t>__nvvmDestroyProgram
 
     global __nvvmAddModuleToProgram
-    data["__nvvmAddModuleToProgram"] = <_cyb_intptr_t>__nvvmAddModuleToProgram
+    data["__nvvmAddModuleToProgram"] = <intptr_t>__nvvmAddModuleToProgram
 
     global __nvvmLazyAddModuleToProgram
-    data["__nvvmLazyAddModuleToProgram"] = <_cyb_intptr_t>__nvvmLazyAddModuleToProgram
+    data["__nvvmLazyAddModuleToProgram"] = <intptr_t>__nvvmLazyAddModuleToProgram
 
     global __nvvmCompileProgram
-    data["__nvvmCompileProgram"] = <_cyb_intptr_t>__nvvmCompileProgram
+    data["__nvvmCompileProgram"] = <intptr_t>__nvvmCompileProgram
 
     global __nvvmVerifyProgram
-    data["__nvvmVerifyProgram"] = <_cyb_intptr_t>__nvvmVerifyProgram
+    data["__nvvmVerifyProgram"] = <intptr_t>__nvvmVerifyProgram
 
     global __nvvmGetCompiledResultSize
-    data["__nvvmGetCompiledResultSize"] = <_cyb_intptr_t>__nvvmGetCompiledResultSize
+    data["__nvvmGetCompiledResultSize"] = <intptr_t>__nvvmGetCompiledResultSize
 
     global __nvvmGetCompiledResult
-    data["__nvvmGetCompiledResult"] = <_cyb_intptr_t>__nvvmGetCompiledResult
+    data["__nvvmGetCompiledResult"] = <intptr_t>__nvvmGetCompiledResult
 
     global __nvvmGetProgramLogSize
-    data["__nvvmGetProgramLogSize"] = <_cyb_intptr_t>__nvvmGetProgramLogSize
+    data["__nvvmGetProgramLogSize"] = <intptr_t>__nvvmGetProgramLogSize
 
     global __nvvmGetProgramLog
-    data["__nvvmGetProgramLog"] = <_cyb_intptr_t>__nvvmGetProgramLog
+    data["__nvvmGetProgramLog"] = <intptr_t>__nvvmGetProgramLog
 
     global __nvvmLLVMVersion
-    data["__nvvmLLVMVersion"] = <_cyb_intptr_t>__nvvmLLVMVersion
+    data["__nvvmLLVMVersion"] = <intptr_t>__nvvmLLVMVersion
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx b/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx
index 2a6754f0450..047c99f2b9f 100644
--- a/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/nvvm_windows.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1a8d9ee78bc417c85345caf1dd580ac660ab437cd874a89d6924786f4ad7aade
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=d826369ce197164240eae2ca22bc88bb193a3ec936946b9d3b5b906b503fb446
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -45,7 +44,10 @@ cdef extern from "<windows.h>":
     ctypedef void* HMODULE
     void* _cyb_GetProcAddress "GetProcAddress"(HMODULE, const char*) nogil
 
-from libc.stdint cimport intptr_t as _cyb_intptr_t
+from libc.stdint cimport (
+    intptr_t,
+    uintptr_t,
+)
 
 import threading as _cyb_threading
 
@@ -146,46 +148,46 @@ cpdef dict _inspect_function_pointers():
     _check_or_init_nvvm()
     cdef dict data = {}
     global __nvvmGetErrorString
-    data["__nvvmGetErrorString"] = <_cyb_intptr_t>__nvvmGetErrorString
+    data["__nvvmGetErrorString"] = <intptr_t>__nvvmGetErrorString
 
     global __nvvmVersion
-    data["__nvvmVersion"] = <_cyb_intptr_t>__nvvmVersion
+    data["__nvvmVersion"] = <intptr_t>__nvvmVersion
 
     global __nvvmIRVersion
-    data["__nvvmIRVersion"] = <_cyb_intptr_t>__nvvmIRVersion
+    data["__nvvmIRVersion"] = <intptr_t>__nvvmIRVersion
 
     global __nvvmCreateProgram
-    data["__nvvmCreateProgram"] = <_cyb_intptr_t>__nvvmCreateProgram
+    data["__nvvmCreateProgram"] = <intptr_t>__nvvmCreateProgram
 
     global __nvvmDestroyProgram
-    data["__nvvmDestroyProgram"] = <_cyb_intptr_t>__nvvmDestroyProgram
+    data["__nvvmDestroyProgram"] = <intptr_t>__nvvmDestroyProgram
 
     global __nvvmAddModuleToProgram
-    data["__nvvmAddModuleToProgram"] = <_cyb_intptr_t>__nvvmAddModuleToProgram
+    data["__nvvmAddModuleToProgram"] = <intptr_t>__nvvmAddModuleToProgram
 
     global __nvvmLazyAddModuleToProgram
-    data["__nvvmLazyAddModuleToProgram"] = <_cyb_intptr_t>__nvvmLazyAddModuleToProgram
+    data["__nvvmLazyAddModuleToProgram"] = <intptr_t>__nvvmLazyAddModuleToProgram
 
     global __nvvmCompileProgram
-    data["__nvvmCompileProgram"] = <_cyb_intptr_t>__nvvmCompileProgram
+    data["__nvvmCompileProgram"] = <intptr_t>__nvvmCompileProgram
 
     global __nvvmVerifyProgram
-    data["__nvvmVerifyProgram"] = <_cyb_intptr_t>__nvvmVerifyProgram
+    data["__nvvmVerifyProgram"] = <intptr_t>__nvvmVerifyProgram
 
     global __nvvmGetCompiledResultSize
-    data["__nvvmGetCompiledResultSize"] = <_cyb_intptr_t>__nvvmGetCompiledResultSize
+    data["__nvvmGetCompiledResultSize"] = <intptr_t>__nvvmGetCompiledResultSize
 
     global __nvvmGetCompiledResult
-    data["__nvvmGetCompiledResult"] = <_cyb_intptr_t>__nvvmGetCompiledResult
+    data["__nvvmGetCompiledResult"] = <intptr_t>__nvvmGetCompiledResult
 
     global __nvvmGetProgramLogSize
-    data["__nvvmGetProgramLogSize"] = <_cyb_intptr_t>__nvvmGetProgramLogSize
+    data["__nvvmGetProgramLogSize"] = <intptr_t>__nvvmGetProgramLogSize
 
     global __nvvmGetProgramLog
-    data["__nvvmGetProgramLog"] = <_cyb_intptr_t>__nvvmGetProgramLog
+    data["__nvvmGetProgramLog"] = <intptr_t>__nvvmGetProgramLog
 
     global __nvvmLLVMVersion
-    data["__nvvmLLVMVersion"] = <_cyb_intptr_t>__nvvmLLVMVersion
+    data["__nvvmLLVMVersion"] = <intptr_t>__nvvmLLVMVersion
     _cyb_func_ptrs = data
     return data
 
diff --git a/cuda_bindings/cuda/bindings/_internal/runtime.pxd b/cuda_bindings/cuda/bindings/_internal/runtime.pxd
index 6714704a175..f7f47c97856 100644
--- a/cuda_bindings/cuda/bindings/_internal/runtime.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/runtime.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=cd46e65c8b1ec45ff0541a157eeb974a3258f0540645a5616759d23b17e1bc10
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=0ffe9d8d30b5d068a7a7a368d66ca9f4904fbc62224f8617c3968dd73f017e25
 from ..cyruntime cimport *
 
 # EGL/GL/VDPAU helper declarations (implementations included in runtime_linux/windows.pyx)
diff --git a/cuda_bindings/cuda/bindings/_internal/runtime_linux.pyx b/cuda_bindings/cuda/bindings/_internal/runtime_linux.pyx
index 86a17c1f8ff..1ae37127bd1 100644
--- a/cuda_bindings/cuda/bindings/_internal/runtime_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/runtime_linux.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1b990290e2d956f48a0006dfe6341c78d6198aecf0a1a20d2e71c7044869d220
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=8a9a7693abb19d9b8586773190de738ea06eff697d16683a49ce67bfa4426788
 import os
 
 from libc.stdint cimport uintptr_t
diff --git a/cuda_bindings/cuda/bindings/_internal/runtime_ptds.pxd b/cuda_bindings/cuda/bindings/_internal/runtime_ptds.pxd
index cd7d433a2c1..322ecce25ce 100644
--- a/cuda_bindings/cuda/bindings/_internal/runtime_ptds.pxd
+++ b/cuda_bindings/cuda/bindings/_internal/runtime_ptds.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=7bcf08853dcfdf191a306446ddac7774147d679de81aad4209c5fd6c74e82ccc
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=997d3bde508f97fcb58d0bfe138041c865c8c738f43dec215826d8498ad73cf2
 from ..cyruntime cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/_internal/runtime_ptds_linux.pyx b/cuda_bindings/cuda/bindings/_internal/runtime_ptds_linux.pyx
index af100599378..730bd35b917 100644
--- a/cuda_bindings/cuda/bindings/_internal/runtime_ptds_linux.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/runtime_ptds_linux.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=35dccf403acb6cffa9cbefc4f90d1e05f20f86060d1eadd0342aff3de3bfdaca
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=0a50966ff0481d081895f8a962cedc08239c3637de07e4a554eec0cdf08d6670
 cdef extern from "":
     """
     #define CUDA_API_PER_THREAD_DEFAULT_STREAM
diff --git a/cuda_bindings/cuda/bindings/_internal/runtime_ptds_windows.pyx b/cuda_bindings/cuda/bindings/_internal/runtime_ptds_windows.pyx
index af100599378..730bd35b917 100644
--- a/cuda_bindings/cuda/bindings/_internal/runtime_ptds_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/runtime_ptds_windows.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=35dccf403acb6cffa9cbefc4f90d1e05f20f86060d1eadd0342aff3de3bfdaca
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=0a50966ff0481d081895f8a962cedc08239c3637de07e4a554eec0cdf08d6670
 cdef extern from "":
     """
     #define CUDA_API_PER_THREAD_DEFAULT_STREAM
diff --git a/cuda_bindings/cuda/bindings/_internal/runtime_windows.pyx b/cuda_bindings/cuda/bindings/_internal/runtime_windows.pyx
index 45161adb0c1..01a9d803c50 100644
--- a/cuda_bindings/cuda/bindings/_internal/runtime_windows.pyx
+++ b/cuda_bindings/cuda/bindings/_internal/runtime_windows.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=bbe09320a5e5a688b4b633aa016d3326deb51e3e02ed380b34b94556bc22b421
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=ea5305267da9d9a72f329179f57a5ba85d5ba93f7dbb80eb6deb188f735f3d68
 import os
 
 from libc.stdint cimport uintptr_t
diff --git a/cuda_bindings/cuda/bindings/_lib/param_packer.h b/cuda_bindings/cuda/bindings/_lib/param_packer.h
index 8d4833bb200..b11c26dfb92 100644
--- a/cuda_bindings/cuda/bindings/_lib/param_packer.h
+++ b/cuda_bindings/cuda/bindings/_lib/param_packer.h
@@ -5,8 +5,6 @@
 
 #include <map>
 #include <functional>
-#include <stdexcept>
-#include <string>
 #include <climits>
 #include <cstdint>
 
@@ -30,7 +28,10 @@ PyLong_AsInt(PyObject *obj)
 }
 #endif
 
-static PyObject* ctypes_module = nullptr;
+// Statics must be initialized at Python import time via init_param_packer()
+// which happens when including utils.pxi.
+// This includes the m_feeders maps as it must not be mutated from threads.
+static bool param_packer_initialized = false;
 
 static PyTypeObject* ctypes_c_char = nullptr;
 static PyTypeObject* ctypes_c_bool = nullptr;
@@ -50,138 +51,118 @@ static PyTypeObject* ctypes_c_float = nullptr;
 static PyTypeObject* ctypes_c_double = nullptr;
 static PyTypeObject* ctypes_c_void_p = nullptr;
 
-static void fetch_ctypes()
+// (target type, source type)
+static std::map<std::pair<PyTypeObject*,PyTypeObject*>, std::function<int(void*, PyObject*)>> m_feeders;
+
+// Helper to fetch a strong reference of the ctypes type.
+static PyTypeObject* fetch_ctypes_type(PyObject* ctypes_module, const char* name)
 {
-    ctypes_module = PyImport_ImportModule("ctypes");
-    if (ctypes_module == nullptr)
-        throw std::runtime_error("Cannot import ctypes module");
-    // get method addressof
-    PyObject* ctypes_dict = PyModule_GetDict(ctypes_module);
-    if (ctypes_dict == nullptr)
-        throw std::runtime_error(std::string("FAILURE @ ") + std::string(__FILE__) + " : " + std::to_string(__LINE__));
-    // supportedtypes
-    ctypes_c_char = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_char");
-    ctypes_c_bool = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_bool");
-    ctypes_c_wchar = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_wchar");
-    ctypes_c_byte = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_byte");
-    ctypes_c_ubyte = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_ubyte");
-    ctypes_c_short = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_short");
-    ctypes_c_ushort = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_ushort");
-    ctypes_c_int = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_int");
-    ctypes_c_uint = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_uint");
-    ctypes_c_long = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_long");
-    ctypes_c_ulong = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_ulong");
-    ctypes_c_longlong = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_longlong");
-    ctypes_c_ulonglong = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_ulonglong");
-    ctypes_c_size_t = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_size_t");
-    ctypes_c_float = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_float");
-    ctypes_c_double = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_double");
-    ctypes_c_void_p = (PyTypeObject*) PyDict_GetItemString(ctypes_dict, "c_void_p"); // == c_voidp
+    return (PyTypeObject*)PyObject_GetAttrString(ctypes_module, name);
 }
 
+static bool fetch_ctypes()
+{
+    PyObject* ctypes_module = PyImport_ImportModule("ctypes");
+    if (ctypes_module == nullptr) return false;
+    // Parenthesize each assignment: `=` binds looser than `&&`.
+    bool success = (
+        (ctypes_c_char = fetch_ctypes_type(ctypes_module, "c_char")) &&
+        (ctypes_c_bool = fetch_ctypes_type(ctypes_module, "c_bool")) &&
+        (ctypes_c_wchar = fetch_ctypes_type(ctypes_module, "c_wchar")) &&
+        (ctypes_c_byte = fetch_ctypes_type(ctypes_module, "c_byte")) &&
+        (ctypes_c_ubyte = fetch_ctypes_type(ctypes_module, "c_ubyte")) &&
+        (ctypes_c_short = fetch_ctypes_type(ctypes_module, "c_short")) &&
+        (ctypes_c_ushort = fetch_ctypes_type(ctypes_module, "c_ushort")) &&
+        (ctypes_c_int = fetch_ctypes_type(ctypes_module, "c_int")) &&
+        (ctypes_c_uint = fetch_ctypes_type(ctypes_module, "c_uint")) &&
+        (ctypes_c_long = fetch_ctypes_type(ctypes_module, "c_long")) &&
+        (ctypes_c_ulong = fetch_ctypes_type(ctypes_module, "c_ulong")) &&
+        (ctypes_c_longlong = fetch_ctypes_type(ctypes_module, "c_longlong")) &&
+        (ctypes_c_ulonglong = fetch_ctypes_type(ctypes_module, "c_ulonglong")) &&
+        (ctypes_c_size_t = fetch_ctypes_type(ctypes_module, "c_size_t")) &&
+        (ctypes_c_float = fetch_ctypes_type(ctypes_module, "c_float")) &&
+        (ctypes_c_double = fetch_ctypes_type(ctypes_module, "c_double")) &&
+        (ctypes_c_void_p = fetch_ctypes_type(ctypes_module, "c_void_p"))  // == c_voidp
+    );
+    Py_DECREF(ctypes_module);
+    return success;
+}
 
-// (target type, source type)
-static std::map<std::pair<PyTypeObject*,PyTypeObject*>, std::function<int(void*, PyObject*)>> m_feeders;
 
-static void populate_feeders(PyTypeObject* target_t, PyTypeObject* source_t)
+// Initialize common (target_type, Python type) pairs for fast argument feeding.
+static void populate_feeders()
 {
-    if (target_t == ctypes_c_int)
+    m_feeders[{ctypes_c_int, &PyLong_Type}] = [](void* ptr, PyObject* value) -> int
     {
-        if (source_t == &PyLong_Type)
-        {
-            m_feeders[{target_t,source_t}] = [](void* ptr, PyObject* value) -> int
-            {
-                // PyLong_AsInt range-checks against the 32-bit int slot and raises
-                // OverflowError itself, so an out-of-range value is rejected rather
-                // than silently truncated.
-                int v = PyLong_AsInt(value);
-                if (v == -1 && PyErr_Occurred())
-                    return -1;
-                *((int*)ptr) = v;
-                return sizeof(int);
-            };
-            return;
-        }
-    } else if (target_t == ctypes_c_bool) {
-        if (source_t == &PyBool_Type)
-        {
-            m_feeders[{target_t,source_t}] = [](void* ptr, PyObject* value) -> int
-            {
-                *((bool*)ptr) = (value == Py_True);
-                return sizeof(bool);
-            };
-            return;
-        }
-    } else if (target_t == ctypes_c_byte) {
-        if (source_t == &PyLong_Type)
-        {
-            m_feeders[{target_t,source_t}] = [](void* ptr, PyObject* value) -> int
-            {
-                // c_byte is an 8-bit slot with no dedicated CPython converter, so
-                // range-check explicitly against INT8_MIN/INT8_MAX. AsLongAndOverflow's
-                // `overflow` only flags values outside `long` (64-bit on LP64), so a
-                // value in that range would be silently truncated by (int8_t)v without
-                // the explicit bounds check. When overflow!=0, v is the -1 sentinel
-                // (not the real value), so that case must be caught before trusting v.
-                int overflow = 0;
-                long v = PyLong_AsLongAndOverflow(value, &overflow);
-                if (overflow == 0 && v == -1 && PyErr_Occurred())
-                    return -1;  // non-overflow conversion error; exception already set
-                if (overflow != 0 || v < INT8_MIN || v > INT8_MAX)
-                {
-                    PyErr_SetString(PyExc_OverflowError,
-                        "Python int is out of range for a c_byte (8-bit) kernel argument");
-                    return -1;
-                }
-                *((int8_t*)ptr) = (int8_t)v;
-                return sizeof(int8_t);
-            };
-            return;
-        }
-    } else if (target_t == ctypes_c_double) {
-        if (source_t == &PyFloat_Type)
-        {
-            m_feeders[{target_t,source_t}] = [](void* ptr, PyObject* value) -> int
-            {
-                *((double*)ptr) = (double)PyFloat_AsDouble(value);
-                return sizeof(double);
-            };
-            return;
-        }
-    } else if (target_t == ctypes_c_float) {
-        if (source_t == &PyFloat_Type)
-        {
-            m_feeders[{target_t,source_t}] = [](void* ptr, PyObject* value) -> int
-            {
-                *((float*)ptr) = (float)PyFloat_AsDouble(value);
-                return sizeof(float);
-            };
-            return;
-        }
-    } else if (target_t == ctypes_c_longlong) {
-        if (source_t == &PyLong_Type)
+        // PyLong_AsInt range-checks against the 32-bit int slot and raises
+        // OverflowError itself, so an out-of-range value is rejected rather
+        // than silently truncated.
+        int v = PyLong_AsInt(value);
+        if (v == -1 && PyErr_Occurred())
+            return -1;
+        *((int*)ptr) = v;
+        return sizeof(int);
+    };
+    m_feeders[{ctypes_c_bool, &PyBool_Type}] = [](void* ptr, PyObject* value) -> int
+    {
+        *((bool*)ptr) = (value == Py_True);
+        return sizeof(bool);
+    };
+    m_feeders[{ctypes_c_byte, &PyLong_Type}] = [](void* ptr, PyObject* value) -> int
+    {
+        // c_byte is an 8-bit slot with no dedicated CPython converter, so
+        // range-check explicitly against INT8_MIN/INT8_MAX. AsLongAndOverflow's
+        // `overflow` only flags values outside `long` (64-bit on LP64), so a
+        // value in that range would be silently truncated by (int8_t)v without
+        // the explicit bounds check. When overflow!=0, v is the -1 sentinel
+        // (not the real value), so that case must be caught before trusting v.
+        int overflow = 0;
+        long v = PyLong_AsLongAndOverflow(value, &overflow);
+        if (overflow == 0 && v == -1 && PyErr_Occurred())
+            return -1;  // non-overflow conversion error; exception already set
+        if (overflow != 0 || v < INT8_MIN || v > INT8_MAX)
         {
-            m_feeders[{target_t,source_t}] = [](void* ptr, PyObject* value) -> int
-            {
-                *((long long*)ptr) = (long long)PyLong_AsLongLong(value);
-                return sizeof(long long);
-            };
-            return;
+            PyErr_SetString(PyExc_OverflowError,
+                "Python int is out of range for a c_byte (8-bit) kernel argument");
+            return -1;
         }
-    }
+        *((int8_t*)ptr) = (int8_t)v;
+        return sizeof(int8_t);
+    };
+    m_feeders[{ctypes_c_double, &PyFloat_Type}] = [](void* ptr, PyObject* value) -> int
+    {
+        *((double*)ptr) = (double)PyFloat_AsDouble(value);
+        return sizeof(double);
+    };
+    m_feeders[{ctypes_c_float, &PyFloat_Type}] = [](void* ptr, PyObject* value) -> int
+    {
+        *((float*)ptr) = (float)PyFloat_AsDouble(value);
+        return sizeof(float);
+    };
+    m_feeders[{ctypes_c_longlong, &PyLong_Type}] = [](void* ptr, PyObject* value) -> int
+    {
+        long long v = PyLong_AsLongLong(value);
+        if (v == -1 && PyErr_Occurred())
+            return -1;
+        *((long long*)ptr) = v;
+        return sizeof(long long);
+    };
 }
 
+// Call once from each consuming module body (import, single-threaded).
+static void init_param_packer()
+{
+    if (param_packer_initialized)
+        return;
+    if (!fetch_ctypes()) return;
+    populate_feeders();
+    param_packer_initialized = true;
+}
+
+// Never-mutated lookup. 0 -> ctypes fallback; -1 -> exception already set.
 static int feed(void* ptr, PyObject* value, PyObject* type)
 {
-    PyTypeObject* pto = (PyTypeObject*)type;
-    if (ctypes_c_int == nullptr)
-        fetch_ctypes();
-    auto found = m_feeders.find({pto,value->ob_type});
-    if (found == m_feeders.end())
-    {
-        populate_feeders(pto, value->ob_type);
-        found = m_feeders.find({pto,value->ob_type});
-    }
+    auto found = m_feeders.find({(PyTypeObject*)type, Py_TYPE(value)});
     if (found != m_feeders.end())
     {
         return found->second(ptr, value);
diff --git a/cuda_bindings/cuda/bindings/_lib/param_packer.pxd b/cuda_bindings/cuda/bindings/_lib/param_packer.pxd
index d1f84059db1..cf0c37be768 100644
--- a/cuda_bindings/cuda/bindings/_lib/param_packer.pxd
+++ b/cuda_bindings/cuda/bindings/_lib/param_packer.pxd
@@ -2,6 +2,10 @@
 # SPDX-License-Identifier: Apache-2.0
 
 # Include "param_packer.h" so its contents get compiled into every
-# Cython extension module that depends on param_packer.pxd.
+# Cython extension module that depends on param_packer.pxd. Each such module
+# owns a copy of the header statics and must call init_param_packer().
 cdef extern from "param_packer.h":
-    int feed(void* ptr, object o, object ct) except? -1
+    # except +* so a C++ throw or pending ImportError become Python exceptions.
+    void init_param_packer() except +*
+    # -1 is a feeder rejection; 0 means no feeder (ctypes fallback).
+    int feed(void* ptr, object o, object ct) except -1
diff --git a/cuda_bindings/cuda/bindings/_lib/utils.pxi b/cuda_bindings/cuda/bindings/_lib/utils.pxi
index 2796f910798..7783afed97c 100644
--- a/cuda_bindings/cuda/bindings/_lib/utils.pxi
+++ b/cuda_bindings/cuda/bindings/_lib/utils.pxi
@@ -11,6 +11,9 @@ import ctypes as _ctypes
 cimport cuda.bindings.cydriver as cydriver
 cimport cuda.bindings._lib.param_packer as param_packer
 
+# Import-time init so feed() is a pure read under free threading.
+param_packer.init_param_packer()
+
 cdef void* _callocWrapper(length, size):
     cdef void* out = calloc(length, size)
     if out is NULL:
diff --git a/cuda_bindings/cuda/bindings/_lib/windll.pxd b/cuda_bindings/cuda/bindings/_lib/windll.pxd
index 294a1a9fd90..b5fd5c4db90 100644
--- a/cuda_bindings/cuda/bindings/_lib/windll.pxd
+++ b/cuda_bindings/cuda/bindings/_lib/windll.pxd
@@ -14,7 +14,7 @@ cdef extern from "windows.h" nogil:
     ctypedef const char *LPCSTR
     ctypedef int BOOL
 
-    cdef DWORD LOAD_LIBRARY_SEARCH_SYSTEM32 = 0x00000800
+    const DWORD LOAD_LIBRARY_SEARCH_SYSTEM32
 
     HMODULE _LoadLibraryExW "LoadLibraryExW"(
         LPCWSTR lpLibFileName,
diff --git a/cuda_bindings/cuda/bindings/_test_helpers/__init__.py b/cuda_bindings/cuda/bindings/_test_helpers/__init__.py
deleted file mode 100644
index 2cfab242d2a..00000000000
--- a/cuda_bindings/cuda/bindings/_test_helpers/__init__.py
+++ /dev/null
@@ -1,6 +0,0 @@
-# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-# SPDX-License-Identifier: Apache-2.0
-
-
-# This package contains test helper utilities that may also be useful for other libraries outside of `cuda.bindings`,
-# such as `cuda.core`. These utilities are not part of the public API of `cuda.bindings` and may change without notice.
diff --git a/cuda_bindings/cuda/bindings/_test_helpers/arch_check.py b/cuda_bindings/cuda/bindings/_test_helpers/arch_check.py
deleted file mode 100644
index 7f35f006c36..00000000000
--- a/cuda_bindings/cuda/bindings/_test_helpers/arch_check.py
+++ /dev/null
@@ -1,71 +0,0 @@
-# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-# SPDX-License-Identifier: Apache-2.0
-
-
-from contextlib import contextmanager
-from functools import cache
-
-import pytest
-
-from cuda.bindings import nvml
-from cuda.bindings._internal.utils import FunctionNotFoundError as NvmlSymbolNotFoundError
-
-
-@cache
-def hardware_supports_nvml():
-    """
-    Tries to call the simplest NVML API possible to see if just the basics
-    works.  If not we are probably on one of the platforms where NVML is not
-    supported at all (e.g. Jetson Orin).
-    """
-    nvml.init_v2()
-    try:
-        nvml.system_get_driver_branch()
-    except (nvml.NotSupportedError, nvml.UnknownError):
-        return False
-    else:
-        return True
-    finally:
-        nvml.shutdown()
-
-
-@contextmanager
-def unsupported_before(device: int, expected_device_arch: nvml.DeviceArch | str | None):
-    device_arch = nvml.device_get_architecture(device)
-
-    if isinstance(expected_device_arch, nvml.DeviceArch):
-        expected_device_arch_int = int(expected_device_arch)
-    elif expected_device_arch == "FERMI":
-        expected_device_arch_int = 1
-    else:
-        expected_device_arch_int = 0
-
-    if expected_device_arch is None or expected_device_arch == "HAS_INFOROM" or device_arch == nvml.DeviceArch.UNKNOWN:
-        # In this case, we don't /know/ if it will fail, but we are ok if it
-        # does or does not.
-
-        # TODO: There are APIs that are documented as supported only if the
-        # device has an InfoROM, but I couldn't find a way to detect that.  For
-        # now, they are just handled as "possibly failing".
-
-        try:
-            yield
-        except (nvml.NotSupportedError, nvml.FunctionNotFoundError, NvmlSymbolNotFoundError):
-            # The API call raised NotSupportedError, NVML status FunctionNotFoundError,
-            # or NvmlSymbolNotFoundError (symbol absent from the loaded NVML DLL), so we
-            # skip the test but don't fail it
-            try:
-                name = nvml.DeviceArch(device_arch).name
-            except ValueError:
-                name = f"UNKNOWN({device_arch})"
-            pytest.skip(f"Unsupported call for device architecture {name} on device '{nvml.device_get_name(device)}'")
-        # If the API call worked, just continue
-    elif int(device_arch) < expected_device_arch_int:
-        # In this case, we /know/ if will fail, and we want to assert that it does.
-        with pytest.raises(nvml.NotSupportedError):
-            yield
-        # The above call was unsupported, so the rest of the test is skipped
-        pytest.skip(f"Unsupported before {expected_device_arch.name}, got {nvml.device_get_name(device)}")
-    else:
-        # In this case, we /know/ it should work, and if it fails, the test should fail.
-        yield
diff --git a/cuda_bindings/cuda/bindings/_v2/nvrtc.pxd b/cuda_bindings/cuda/bindings/_v2/nvrtc.pxd
index 3e8aa8a3675..9c5978e5474 100644
--- a/cuda_bindings/cuda/bindings/_v2/nvrtc.pxd
+++ b/cuda_bindings/cuda/bindings/_v2/nvrtc.pxd
@@ -2,10 +2,17 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=5c7c24ae0ae5a6032e23f801fe9c3151a434eebd3b3429fbfd799985f87b184c
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport intptr_t
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=632bbedaee3acec49d09764a74b02343ada9ddc14f52c6fe00843d62e147006b
 from libc.stdint cimport intptr_t
 
 from ..cynvrtc cimport *
diff --git a/cuda_bindings/cuda/bindings/_v2/nvrtc.pyx b/cuda_bindings/cuda/bindings/_v2/nvrtc.pyx
index 4e267b1bd47..9cc508aeef6 100644
--- a/cuda_bindings/cuda/bindings/_v2/nvrtc.pyx
+++ b/cuda_bindings/cuda/bindings/_v2/nvrtc.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=b919b9cb09a71e4b2f6ad7dd1f76c7e3bf92b5cb1dd51c0d83087d2ce0cab581
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=3b41a6e66b9064266d04521a6cc9b9a4f715c453d21323ab9741f9e34e6f2d80
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -12,6 +11,7 @@
 cimport cpython as _cyb_cpython
 cimport cpython.buffer as _cyb_cpython_buffer
 from cython cimport view as _cyb_view
+from libc.stdint cimport intptr_t
 from libc.stdlib cimport (
     calloc as _cyb_calloc,
     free as _cyb_free,
diff --git a/cuda_bindings/cuda/bindings/cudla.pxd b/cuda_bindings/cuda/bindings/cudla.pxd
index 97ecfb1bf25..90cddb7e342 100644
--- a/cuda_bindings/cuda/bindings/cudla.pxd
+++ b/cuda_bindings/cuda/bindings/cudla.pxd
@@ -1,10 +1,21 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated across versions from 1.5.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 1.5.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f6b70193e4ca3c62bd5749b3d19d305f0e268225bf1a6dcf6b95091cb0511791
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+    uint64_t,
+)
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=436984a783ea5e6bef13945d0b6d60b4143aa08131c82cdea619337233b15737
 from libc.stdint cimport intptr_t
 
 from .cycudla cimport *
@@ -32,6 +43,7 @@ ctypedef cudlaModuleLoadFlags _ModuleLoadFlags
 ctypedef cudlaSubmissionFlags _SubmissionFlags
 ctypedef cudlaAccessPermissionFlags _AccessPermissionFlags
 ctypedef cudlaDevAttributeType _DevAttributeType
+ctypedef cudlaScratchMemoryConfig _ScratchMemoryConfig
 
 
 ###############################################################################
@@ -45,10 +57,10 @@ cpdef intptr_t mem_register(intptr_t dev_handle, intptr_t ptr, size_t size, uint
 cpdef intptr_t module_load_from_memory(intptr_t dev_handle, p_module, size_t module_size, uint32_t flags) except *
 cpdef module_unload(intptr_t h_module, uint32_t flags)
 cpdef submit_task(intptr_t dev_handle, intptr_t ptr_to_tasks, uint32_t num_tasks, intptr_t stream, uint32_t flags)
-cpdef object device_get_attribute(intptr_t dev_handle, int attrib) except *
+cpdef object device_get_attribute(intptr_t dev_handle, int attrib)
 cpdef mem_unregister(intptr_t dev_handle, intptr_t dev_ptr)
 cpdef int get_last_error(intptr_t dev_handle) except? 0
 cpdef destroy_device(intptr_t dev_handle)
 cpdef set_task_timeout_in_ms(intptr_t dev_handle, uint32_t timeout)
 
-cpdef module_get_attributes(intptr_t h_module, int attr_type) except *
+cpdef module_get_attributes(intptr_t h_module, int attr_type)
diff --git a/cuda_bindings/cuda/bindings/cudla.pyx b/cuda_bindings/cuda/bindings/cudla.pyx
index 4532ebaeb97..9d04eb6013d 100644
--- a/cuda_bindings/cuda/bindings/cudla.pyx
+++ b/cuda_bindings/cuda/bindings/cudla.pyx
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated across versions from 1.5.0 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=37c4218155319e18c12093c50fd40d05d05035b9625c2aaf8c111b0ab26d3c8c
+# This code was automatically generated across versions from 1.5.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=27847299a8355597d74d78c538539764838b579ac5331197a0773132e9c1fc18
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -11,6 +10,12 @@
 cimport cpython as _cyb_cpython
 cimport cpython.buffer as _cyb_cpython_buffer
 from cython cimport view as _cyb_view
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+    uint64_t,
+    uint8_t,
+)
 from libc.stdlib cimport (
     calloc as _cyb_calloc,
     free as _cyb_free,
@@ -63,6 +68,35 @@ cdef _cyb_from_data(data, dtype_name, expected_dtype, lowpp_type):
         raise ValueError(f"data array must be of dtype {dtype_name}")
     return lowpp_type.from_ptr(data.ctypes.data, not data.flags.writeable, data)
 
+cdef intptr_t _cyb_get_buffer_pointer(buf, Py_ssize_t size, readonly=True) except?-1:
+    cdef intptr_t ptr
+    cdef int flags = _cyb_cpython.PyBUF_ANY_CONTIGUOUS
+    if not readonly:
+        flags |= _cyb_cpython.PyBUF_WRITABLE
+    cdef int status = -1
+    cdef _cyb_cpython.Py_buffer view
+    if isinstance(buf, int):
+        ptr = <intptr_t>buf
+    else:
+        try:
+            status = _cyb_cpython.PyObject_GetBuffer(buf, &view, flags)
+            if size != -1:
+                assert view.len == size
+            assert view.ndim == 1
+        except Exception as e:
+            adj = "writable " if not readonly else ""
+            raise ValueError(
+                "buf must be either a Python int representing the pointer "
+                f"address to a valid buffer, or a 1D contiguous {adj}"
+                f"buffer, of size {size}"
+            ) from e
+        else:
+            ptr = <intptr_t>view.buf
+        finally:
+            if status == 0:
+                _cyb_cpython.PyBuffer_Release(&view)
+    return ptr
+
 
 # <<<< END OF PREAMBLE CONTENT >>>>
 
@@ -70,7 +104,6 @@ cimport cython  # NOQA
 from libc.stdint cimport intptr_t, uintptr_t
 from libc.stdlib cimport malloc, free
 
-from ._internal.utils cimport get_buffer_pointer
 
 
 
@@ -1695,6 +1728,14 @@ class DevAttributeType(_cyb_IntEnum):
     UNIFIED_ADDRESSING = CUDLA_UNIFIED_ADDRESSING
     DEVICE_VERSION = CUDLA_DEVICE_VERSION
 
+class ScratchMemoryConfig(_cyb_IntEnum):
+    """
+    See `cudlaScratchMemoryConfig`.
+    """
+    SCRATCH_MEMORY_DEFAULT = CUDLA_SCRATCH_MEMORY_DEFAULT
+    SCRATCH_MEMORY_SHARED_STATIC = CUDLA_SCRATCH_MEMORY_SHARED_STATIC
+    MAX = CUDLA_SCRATCH_MEMORY_CONFIG_MAX
+
 
 ###############################################################################
 # Error handling
@@ -1740,7 +1781,7 @@ cpdef uint64_t device_get_count() except? -1:
 
 cpdef intptr_t create_device(uint64_t device, uint32_t flags) except *:
     cdef DevHandle dev_handle
-    if flags == CUDLA_STANDALONE:
+    if flags & CUDLA_STANDALONE:
         raise CudlaError(cudlaErrorUnsupportedOperation)
     with nogil:
         __status__ = cudlaCreateDevice(<const uint64_t>device, &dev_handle, <const uint32_t>flags)
@@ -1757,7 +1798,7 @@ cpdef intptr_t mem_register(intptr_t dev_handle, intptr_t ptr, size_t size, uint
 
 
 cpdef intptr_t module_load_from_memory(intptr_t dev_handle, p_module, size_t module_size, uint32_t flags) except *:
-    cdef void* _p_module_ = get_buffer_pointer(p_module, module_size, readonly=True)
+    cdef void* _p_module_ = <void *>_cyb_get_buffer_pointer(p_module, module_size, readonly=True)
     cdef Module h_module
     with nogil:
         __status__ = cudlaModuleLoadFromMemory(<const DevHandle>dev_handle, <const uint8_t* const>_p_module_, <const size_t>module_size, &h_module, <const uint32_t>flags)
@@ -1777,7 +1818,7 @@ cpdef submit_task(intptr_t dev_handle, intptr_t ptr_to_tasks, uint32_t num_tasks
     check_status(__status__)
 
 
-cpdef object device_get_attribute(intptr_t dev_handle, int attrib) except *:
+cpdef object device_get_attribute(intptr_t dev_handle, int attrib):
     cdef DevAttribute p_attribute_py = DevAttribute()
     cdef cudlaDevAttribute *p_attribute = <cudlaDevAttribute *><intptr_t>(p_attribute_py._get_ptr())
     with nogil:
@@ -1811,7 +1852,7 @@ cpdef set_task_timeout_in_ms(intptr_t dev_handle, uint32_t timeout):
     check_status(__status__)
 
 
-cpdef module_get_attributes(intptr_t h_module, int attr_type) except *:
+cpdef module_get_attributes(intptr_t h_module, int attr_type):
     """Query module attributes, interpreting the cudlaModuleAttribute union
     based on the requested attribute type.
 
diff --git a/cuda_bindings/cuda/bindings/cufile.pxd b/cuda_bindings/cuda/bindings/cufile.pxd
index 35b6271e529..1970c4f614a 100644
--- a/cuda_bindings/cuda/bindings/cufile.pxd
+++ b/cuda_bindings/cuda/bindings/cufile.pxd
@@ -2,11 +2,18 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=616e51ad15aa071792eceba5db17a6fb2b845b219395e2fdcc6278d3621f52de
+
+
+
+# <<<< PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1d85ffab055c92f1ea96fc186f7ede91090e0d65388d2a03591d374f74937209
 from libc.stdint cimport intptr_t
+from libcpp cimport bool as _cyb_bool
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
 from .cycufile cimport *
 
diff --git a/cuda_bindings/cuda/bindings/cufile.pyx b/cuda_bindings/cuda/bindings/cufile.pyx
index 15eedf9708f..7365ed4b62b 100644
--- a/cuda_bindings/cuda/bindings/cufile.pyx
+++ b/cuda_bindings/cuda/bindings/cufile.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=9bb12d58d34130a4d23007783ff3b16344fd90af5d0977196234ced1b9e6574d
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=99d6a9660bb3015680d55d4d2da20861cecfd836de22a90892eeb64a480acafa
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -13,6 +12,10 @@ cimport cpython as _cyb_cpython
 cimport cpython.buffer as _cyb_cpython_buffer
 cimport cpython.memoryview as _cyb_cpython_memoryview
 from cython cimport view as _cyb_view
+from libc.stdint cimport (
+    intptr_t,
+    uint64_t,
+)
 from libc.stdlib cimport (
     calloc as _cyb_calloc,
     free as _cyb_free,
@@ -22,6 +25,7 @@ from libc.string cimport (
     memcmp as _cyb_memcmp,
     memcpy as _cyb_memcpy,
 )
+from libcpp cimport bool as _cyb_bool
 
 from cuda.bindings._internal._fast_enum import FastEnum as _cyb_FastEnum
 
@@ -70,7 +74,7 @@ cdef _cyb_from_data(data, dtype_name, expected_dtype, lowpp_type):
 
 cimport cython  # NOQA
 from libc cimport errno
-from ._internal.utils cimport (get_buffer_pointer, get_nested_resource_ptr,
+from ._internal.utils cimport (get_nested_resource_ptr,
                                nested_resource)
 
 import cython
@@ -3302,9 +3306,12 @@ class cuFileError(Exception):
 @cython.profile(False)
 cdef int check_status(ReturnT status) except 1 nogil:
     if ReturnT is CUfileError_t:
-        if status.err != 0 or status.cu_err != 0:
+        if IS_CUDA_ERR(status):
             with gil:
                 raise cuFileError(status.err, status.cu_err)
+        elif IS_CUFILE_ERR(status.err):
+            with gil:
+                raise cuFileError(status.err)
     elif ReturnT is ssize_t:
         if status == -1:
             # note: this assumes cuFile already properly resets errno in each API
@@ -3423,7 +3430,7 @@ cpdef driver_set_poll_mode(bint poll, size_t poll_threshold_size):
     .. seealso:: `cuFileDriverSetPollMode`
     """
     with nogil:
-        __status__ = cuFileDriverSetPollMode(<cpp_bool>poll, poll_threshold_size)
+        __status__ = cuFileDriverSetPollMode(<_cyb_bool>poll, poll_threshold_size)
     check_status(__status__)
 
 
@@ -3548,7 +3555,7 @@ cpdef size_t get_parameter_size_t(int param) except? 0:
 
 
 cpdef bint get_parameter_bool(int param) except? 0:
-    cdef cpp_bool value
+    cdef _cyb_bool value
     with nogil:
         __status__ = cuFileGetParameterBool(<_BoolConfigParameter>param, &value)
     check_status(__status__)
@@ -3572,7 +3579,7 @@ cpdef set_parameter_size_t(int param, size_t value):
 
 cpdef set_parameter_bool(int param, bint value):
     with nogil:
-        __status__ = cuFileSetParameterBool(<_BoolConfigParameter>param, <cpp_bool>value)
+        __status__ = cuFileSetParameterBool(<_BoolConfigParameter>param, <_cyb_bool>value)
     check_status(__status__)
 
 
diff --git a/cuda_bindings/cuda/bindings/cycudla.pxd b/cuda_bindings/cuda/bindings/cycudla.pxd
index 5f42abe0de5..bd47c37e1c6 100644
--- a/cuda_bindings/cuda/bindings/cycudla.pxd
+++ b/cuda_bindings/cuda/bindings/cycudla.pxd
@@ -1,14 +1,22 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated across versions from 1.5.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 1.5.0 to 13.4.1. Do not modify it directly.
 # This layer exposes the C header to Cython as-is.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f769acaca3dada01ba364b7053e43bcc2439f912fee376ebf3f2139fd8786203
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport (
+    uint32_t,
+    uint64_t,
+    uint8_t,
+)
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f24f3dc6fe7d137fe1753e5eb4ebb613d631f984996f6dbb859befed8211c73b
-from libc.stdint cimport int8_t, int16_t, int32_t, int64_t
-from libc.stdint cimport uint8_t, uint16_t, uint32_t, uint64_t
-from libc.stdint cimport intptr_t, uintptr_t
 from libc.stddef cimport size_t
 
 
@@ -80,6 +88,11 @@ ctypedef enum cudlaDevAttributeType "cudlaDevAttributeType":
     CUDLA_UNIFIED_ADDRESSING "CUDLA_UNIFIED_ADDRESSING" = 0
     CUDLA_DEVICE_VERSION "CUDLA_DEVICE_VERSION" = 1
 
+ctypedef enum cudlaScratchMemoryConfig "cudlaScratchMemoryConfig":
+    CUDLA_SCRATCH_MEMORY_DEFAULT "CUDLA_SCRATCH_MEMORY_DEFAULT" = (0U << 1)
+    CUDLA_SCRATCH_MEMORY_SHARED_STATIC "CUDLA_SCRATCH_MEMORY_SHARED_STATIC" = (1U << 1)
+    CUDLA_SCRATCH_MEMORY_CONFIG_MAX "CUDLA_SCRATCH_MEMORY_CONFIG_MAX" = 0x7FFFFFFF
+
 # types
 ctypedef void* cudlaDevHandle 'cudlaDevHandle'
 
diff --git a/cuda_bindings/cuda/bindings/cycudla.pyx b/cuda_bindings/cuda/bindings/cycudla.pyx
index df23650e881..7249bd7135c 100644
--- a/cuda_bindings/cuda/bindings/cycudla.pyx
+++ b/cuda_bindings/cuda/bindings/cycudla.pyx
@@ -1,10 +1,21 @@
 # SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated across versions from 1.5.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 1.5.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=ef5d2f05cc1ae1fe20b8f9133f0e88a82406c97909ee9327fe4ed0645dae6ecb
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport (
+    uint32_t,
+    uint64_t,
+    uint8_t,
+)
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=71bfc67b64e7e78ba54303e68d8df46f44f73c601c5d303926a46e261b3fd042
 from ._internal cimport cudla as _cudla
 
 
diff --git a/cuda_bindings/cuda/bindings/cycufile.pxd b/cuda_bindings/cuda/bindings/cycufile.pxd
index 47aa51465fe..3196f6a5eab 100644
--- a/cuda_bindings/cuda/bindings/cycufile.pxd
+++ b/cuda_bindings/cuda/bindings/cycufile.pxd
@@ -2,13 +2,22 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=ee9acc9a7052fdb1b1eddc639c1fbe72ac5f3b2a9179cd832240c916edce8d74
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport (
+    uint32_t,
+    uint64_t,
+)
+from libcpp cimport bool as _cyb_bool
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=7961eb9a31b8ad5274ddd2a6357f2f75c1004c44ee4a5edeadf22674f1833d3e
-from libc.stdint cimport uint32_t, uint64_t
 from libc.time cimport time_t
-from libcpp cimport bool as cpp_bool
 from posix.types cimport off_t
 
 cimport cuda.bindings.cydriver
@@ -393,6 +402,13 @@ cdef extern from 'cufile.h':
         CUfilePerGpuStats_t per_gpu_stats[16]
 
 
+# Error-inspection macros from cufile.h (declared as functions so Cython
+# emits calls that the C preprocessor expands).
+cdef extern from 'cufile.h' nogil:
+    bint IS_CUDA_ERR(CUfileError_t status)
+    bint IS_CUFILE_ERR(CUfileOpError err)
+
+
 cdef extern from *:
     """
     // This is the missing piece we need to supply to help Cython & C++ compilers.
@@ -422,7 +438,7 @@ cdef CUfileError_t cuFileDriverClose() except?<CUfileError_t>CUFILE_LOADING_ERRO
 cdef CUfileError_t cuFileDriverClose_v2() except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef long cuFileUseCount() except* nogil
 cdef CUfileError_t cuFileDriverGetProperties(CUfileDrvProps_t* props) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
-cdef CUfileError_t cuFileDriverSetPollMode(cpp_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
+cdef CUfileError_t cuFileDriverSetPollMode(_cyb_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileDriverSetMaxDirectIOSize(size_t max_direct_io_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileDriverSetMaxCacheSize(size_t max_cache_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileDriverSetMaxPinnedMemSize(size_t max_pinned_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
@@ -437,10 +453,10 @@ cdef CUfileError_t cuFileStreamRegister(CUstream stream, unsigned flags) except?
 cdef CUfileError_t cuFileStreamDeregister(CUstream stream) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileGetVersion(int* version) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileGetParameterSizeT(CUFileSizeTConfigParameter_t param, size_t* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
-cdef CUfileError_t cuFileGetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
+cdef CUfileError_t cuFileGetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileGetParameterString(CUFileStringConfigParameter_t param, char* desc_str, int len) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileSetParameterSizeT(CUFileSizeTConfigParameter_t param, size_t value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
-cdef CUfileError_t cuFileSetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
+cdef CUfileError_t cuFileSetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileSetParameterString(CUFileStringConfigParameter_t param, const char* desc_str) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileGetParameterMinMaxValue(CUFileSizeTConfigParameter_t param, size_t* min_value, size_t* max_value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
 cdef CUfileError_t cuFileSetStatsLevel(int level) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil
diff --git a/cuda_bindings/cuda/bindings/cycufile.pyx b/cuda_bindings/cuda/bindings/cycufile.pyx
index 5c6ac42c8cd..71e499b791d 100644
--- a/cuda_bindings/cuda/bindings/cycufile.pyx
+++ b/cuda_bindings/cuda/bindings/cycufile.pyx
@@ -2,14 +2,14 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f665ca316ab6166959a5f3338c901e698617b31146000a9d99422dcf9849d3fc
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=331732354093d8b2560607ca720e2d2a8a4531704b11582ac7c5811f14261273
 
 
 # <<<< PREAMBLE CONTENT >>>>
 
 cimport cython as _cyb_cython
+from libcpp cimport bool as _cyb_bool
 
 
 # <<<< END OF PREAMBLE CONTENT >>>>
@@ -67,7 +67,7 @@ cdef CUfileError_t cuFileDriverGetProperties(CUfileDrvProps_t* props) except?<CU
     return _cufile._cuFileDriverGetProperties(props)
 
 
-cdef CUfileError_t cuFileDriverSetPollMode(cpp_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
+cdef CUfileError_t cuFileDriverSetPollMode(_cyb_bool poll, size_t poll_threshold_size) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
     return _cufile._cuFileDriverSetPollMode(poll, poll_threshold_size)
 
 
@@ -128,7 +128,7 @@ cdef CUfileError_t cuFileGetParameterSizeT(CUFileSizeTConfigParameter_t param, s
     return _cufile._cuFileGetParameterSizeT(param, value)
 
 
-cdef CUfileError_t cuFileGetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
+cdef CUfileError_t cuFileGetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool* value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
     return _cufile._cuFileGetParameterBool(param, value)
 
 
@@ -140,7 +140,7 @@ cdef CUfileError_t cuFileSetParameterSizeT(CUFileSizeTConfigParameter_t param, s
     return _cufile._cuFileSetParameterSizeT(param, value)
 
 
-cdef CUfileError_t cuFileSetParameterBool(CUFileBoolConfigParameter_t param, cpp_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
+cdef CUfileError_t cuFileSetParameterBool(CUFileBoolConfigParameter_t param, _cyb_bool value) except?<CUfileError_t>CUFILE_LOADING_ERROR nogil:
     return _cufile._cuFileSetParameterBool(param, value)
 
 
diff --git a/cuda_bindings/cuda/bindings/cydriver.pxd b/cuda_bindings/cuda/bindings/cydriver.pxd
index da6754e7af2..db2e3f3bdb4 100644
--- a/cuda_bindings/cuda/bindings/cydriver.pxd
+++ b/cuda_bindings/cuda/bindings/cydriver.pxd
@@ -2,10 +2,20 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=26d9c23bcf10595e40a03f65b7b7491e2fa5d7161458b6183c53353665bf6f52
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport (
+    uint32_t,
+    uint64_t,
+)
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=9e145065ec8a0e7780c0d8e38d0cec7a9b4bf2512e8a745f32593531bbb64676
 from libc.stdint cimport uint32_t, uint64_t
 
 
diff --git a/cuda_bindings/cuda/bindings/cydriver.pyx b/cuda_bindings/cuda/bindings/cydriver.pyx
index af647d36913..82676152c39 100644
--- a/cuda_bindings/cuda/bindings/cydriver.pyx
+++ b/cuda_bindings/cuda/bindings/cydriver.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=66aba9b58abd5c5ae210ca5ca8ac01676cb64b9f4059c17623b68146e30381ac
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=99b0dd6a5b631fb108b5d2422c62f8fd4660630dda543978357a03d96c5dc201
 from ._internal cimport driver as _driver
 
 cdef CUresult cuGetErrorString(CUresult error, const char** pStr) except ?CUDA_ERROR_NOT_FOUND nogil:
diff --git a/cuda_bindings/cuda/bindings/cynvfatbin.pxd b/cuda_bindings/cuda/bindings/cynvfatbin.pxd
index c9d844c6da9..b61707a47c8 100644
--- a/cuda_bindings/cuda/bindings/cynvfatbin.pxd
+++ b/cuda_bindings/cuda/bindings/cynvfatbin.pxd
@@ -2,11 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.4.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.4.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=350ce092394c88b497887fcb76999a31e960cb7c395fbc50aadd7d5ce174ffc7
-from libc.stdint cimport intptr_t, uint32_t
 
 
 ###############################################################################
@@ -14,6 +11,7 @@ from libc.stdint cimport intptr_t, uint32_t
 ###############################################################################
 
 # enums
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=4eaac7021af14308210cbd9dd8bf938f0b09d395ef079368750627da493fa06e
 ctypedef enum nvFatbinResult "nvFatbinResult":
     NVFATBIN_SUCCESS "NVFATBIN_SUCCESS" = 0
     NVFATBIN_ERROR_INTERNAL "NVFATBIN_ERROR_INTERNAL"
diff --git a/cuda_bindings/cuda/bindings/cynvfatbin.pyx b/cuda_bindings/cuda/bindings/cynvfatbin.pyx
index 45c539c5ac8..a943e7bbf01 100644
--- a/cuda_bindings/cuda/bindings/cynvfatbin.pyx
+++ b/cuda_bindings/cuda/bindings/cynvfatbin.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.4.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.4.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a68125034d3e119ba0ef4b2b9d490cee4a84ffc773465379588b86d515dfa022
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=ac4e507008fec5a9a6963e6539b4a783ca1908452fc4bdb300119af7a1312ff0
 from ._internal cimport nvfatbin as _nvfatbin
 
 
diff --git a/cuda_bindings/cuda/bindings/cynvjitlink.pxd b/cuda_bindings/cuda/bindings/cynvjitlink.pxd
index b6bc62c1d7b..1c240342c91 100644
--- a/cuda_bindings/cuda/bindings/cynvjitlink.pxd
+++ b/cuda_bindings/cuda/bindings/cynvjitlink.pxd
@@ -2,11 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=19b54696d673ac6a15251d0a9fb4d23d19a3ed87a31a38a1727cf89a4a1a8383
-from libc.stdint cimport intptr_t, uint32_t
 
 
 ###############################################################################
@@ -14,6 +11,15 @@ from libc.stdint cimport intptr_t, uint32_t
 ###############################################################################
 
 # enums
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=7bd3a5876758225a37a98b496a1423047d3a446a4a0956ebc11b17f0abe2128a
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport uint32_t
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
+
 ctypedef enum nvJitLinkResult "nvJitLinkResult":
     NVJITLINK_SUCCESS "NVJITLINK_SUCCESS" = 0
     NVJITLINK_ERROR_UNRECOGNIZED_OPTION "NVJITLINK_ERROR_UNRECOGNIZED_OPTION"
diff --git a/cuda_bindings/cuda/bindings/cynvjitlink.pyx b/cuda_bindings/cuda/bindings/cynvjitlink.pyx
index fd20bfee10f..0359f23f216 100644
--- a/cuda_bindings/cuda/bindings/cynvjitlink.pyx
+++ b/cuda_bindings/cuda/bindings/cynvjitlink.pyx
@@ -2,10 +2,17 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=3abd933ead70f75181084a0ac8ea01c523839c18b93820a2c560e9b945de6d3e
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport uint32_t
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f91e9f01600d3933b3489ae1d9963b33f8095779168d3b27949645eb41926ec3
 from ._internal cimport nvjitlink as _nvjitlink
 
 
diff --git a/cuda_bindings/cuda/bindings/cynvml.pxd b/cuda_bindings/cuda/bindings/cynvml.pxd
index be3ab2da3ae..780241c5a3a 100644
--- a/cuda_bindings/cuda/bindings/cynvml.pxd
+++ b/cuda_bindings/cuda/bindings/cynvml.pxd
@@ -2,11 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=6cd5217ee9e8afc03e6cce40801c8b2ad5f105d1fb2a1528910955e91e3cc570
-from libc.stdint cimport int64_t
 
 
 ###############################################################################
@@ -14,6 +11,7 @@ from libc.stdint cimport int64_t
 ###############################################################################
 
 # enums
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=60a5b20aeb8f2f1b807c72675995ed6bf5943e58f3b9ab24933f51d4a7246f6f
 ctypedef enum nvmlBridgeChipType_t "nvmlBridgeChipType_t":
     NVML_BRIDGE_CHIP_PLX "NVML_BRIDGE_CHIP_PLX" = 0
     NVML_BRIDGE_CHIP_BRO4 "NVML_BRIDGE_CHIP_BRO4" = 1
@@ -1742,13 +1740,23 @@ ctypedef struct nvmlAdaptiveTgpModeInfo_v1_t 'nvmlAdaptiveTgpModeInfo_v1_t':
     nvmlEnableState_t enablementStatus
     unsigned int adjustedLimitMw
 
-ctypedef struct nvmlOperationalEventContextInfo_v1_t 'nvmlOperationalEventContextInfo_v1_t':
+ctypedef struct nvmlEventSetGetContextCount_v1_t 'nvmlEventSetGetContextCount_v1_t':
+    unsigned int count
+
+ctypedef struct nvmlEventSetGetContextInfo_v1_t 'nvmlEventSetGetContextInfo_v1_t':
+    unsigned int index
     unsigned int nvmlGpuOperationalEventContextType
     unsigned int sourceEventContextType
     unsigned int dataSize
     unsigned short dataFormatVersion
 
-ctypedef struct nvmlGpuOperationalEventContextLegacyXid_v1_t 'nvmlGpuOperationalEventContextLegacyXid_v1_t':
+ctypedef struct nvmlEventSetGetContextData_v1_t 'nvmlEventSetGetContextData_v1_t':
+    void* data
+    unsigned int index
+    unsigned int dataSize
+
+ctypedef struct nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t 'nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t':
+    unsigned int index
     unsigned int xidCode
 
 ctypedef struct nvmlGpuFabricClique_v1_t 'nvmlGpuFabricClique_v1_t':
@@ -1760,7 +1768,9 @@ ctypedef struct nvmlGpuOperationalEventConfig_v1_t 'nvmlGpuOperationalEventConfi
     unsigned int minLogLevel
     unsigned int minSeverity
 
-ctypedef struct nvmlEventData_v2_t 'nvmlEventData_v2_t':
+ctypedef struct nvmlEventSetWait_v3_t 'nvmlEventSetWait_v3_t':
+    unsigned int timeoutMs
+    unsigned int dataType
     char uuid[96]
     char sourceModule[16]
     unsigned long long eventType
@@ -1769,7 +1779,6 @@ ctypedef struct nvmlEventData_v2_t 'nvmlEventData_v2_t':
     unsigned long long instanceId
     unsigned long long timestampUsec
     unsigned long long traceId
-    unsigned int dataType
     unsigned int gpuInstanceId
     unsigned int computeInstanceId
     unsigned int severity
@@ -2735,9 +2744,9 @@ cdef nvmlReturn_t nvmlDevicePerfMetricsGetSamples_v1(nvmlDevice_t device, nvmlPe
 cdef nvmlReturn_t nvmlDeviceSetNvlinkBwModeAsync_v1(nvmlDevice_t device, nvmlNvlinkSetBwModeAsync_v1_t* setBwModeAsync) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
 cdef nvmlReturn_t nvmlDeviceGetNvLinkTelemetrySamples_v1(nvmlDevice_t device, nvmlNvlinkTelemetrySamples_v1_t* samples) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
 cdef nvmlReturn_t nvmlEventSetRegisterGpuOperationalEvents_v1(nvmlEventSet_t eventSet, const nvmlGpuOperationalEventConfig_v1_t* config) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventData_v2_t* data, unsigned int timeoutms) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, unsigned int* count) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, unsigned int index, nvmlOperationalEventContextInfo_v1_t* info) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t nvmlEventSetGetContextData_v1(nvmlEventSet_t set, unsigned int index, void* data, unsigned int* dataSize) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
-cdef nvmlReturn_t nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, unsigned int index, nvmlGpuOperationalEventContextLegacyXid_v1_t* xid) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventSetWait_v3_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, nvmlEventSetGetContextCount_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, nvmlEventSetGetContextInfo_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t nvmlEventSetGetContextData_v1(nvmlEventSet_t set, nvmlEventSetGetContextData_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
+cdef nvmlReturn_t nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
 cdef nvmlReturn_t nvmlDeviceGetBankRemapperStatus_v1(nvmlDevice_t device, nvmlEccBankRemapperStatus_v1_t* pBankRemapperStatus) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil
diff --git a/cuda_bindings/cuda/bindings/cynvml.pyx b/cuda_bindings/cuda/bindings/cynvml.pyx
index 6c62117b741..c309bc66eaa 100644
--- a/cuda_bindings/cuda/bindings/cynvml.pyx
+++ b/cuda_bindings/cuda/bindings/cynvml.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=099ee5a0fb0a12b6d7e67b841b75a59bad0b98a1cfc171914aa985729c034980
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f5af75e5d248a615a2165cbd490ef48486c2b9e3a3957aec27050eda3de5f329
 from ._internal cimport nvml as _nvml
 
 
@@ -1469,24 +1468,24 @@ cdef nvmlReturn_t nvmlEventSetRegisterGpuOperationalEvents_v1(nvmlEventSet_t eve
     return _nvml._nvmlEventSetRegisterGpuOperationalEvents_v1(eventSet, config)
 
 
-cdef nvmlReturn_t nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventData_v2_t* data, unsigned int timeoutms) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
-    return _nvml._nvmlEventSetWait_v3(set, data, timeoutms)
+cdef nvmlReturn_t nvmlEventSetWait_v3(nvmlEventSet_t set, nvmlEventSetWait_v3_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+    return _nvml._nvmlEventSetWait_v3(set, params)
 
 
-cdef nvmlReturn_t nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, unsigned int* count) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
-    return _nvml._nvmlEventSetGetContextCount_v1(set, count)
+cdef nvmlReturn_t nvmlEventSetGetContextCount_v1(nvmlEventSet_t set, nvmlEventSetGetContextCount_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+    return _nvml._nvmlEventSetGetContextCount_v1(set, params)
 
 
-cdef nvmlReturn_t nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, unsigned int index, nvmlOperationalEventContextInfo_v1_t* info) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
-    return _nvml._nvmlEventSetGetContextInfo_v1(set, index, info)
+cdef nvmlReturn_t nvmlEventSetGetContextInfo_v1(nvmlEventSet_t set, nvmlEventSetGetContextInfo_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+    return _nvml._nvmlEventSetGetContextInfo_v1(set, params)
 
 
-cdef nvmlReturn_t nvmlEventSetGetContextData_v1(nvmlEventSet_t set, unsigned int index, void* data, unsigned int* dataSize) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
-    return _nvml._nvmlEventSetGetContextData_v1(set, index, data, dataSize)
+cdef nvmlReturn_t nvmlEventSetGetContextData_v1(nvmlEventSet_t set, nvmlEventSetGetContextData_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+    return _nvml._nvmlEventSetGetContextData_v1(set, params)
 
 
-cdef nvmlReturn_t nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, unsigned int index, nvmlGpuOperationalEventContextLegacyXid_v1_t* xid) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
-    return _nvml._nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(set, index, xid)
+cdef nvmlReturn_t nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(nvmlEventSet_t set, nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t* params) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
+    return _nvml._nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(set, params)
 
 
 cdef nvmlReturn_t nvmlDeviceGetBankRemapperStatus_v1(nvmlDevice_t device, nvmlEccBankRemapperStatus_v1_t* pBankRemapperStatus) except?_NVMLRETURN_T_INTERNAL_LOADING_ERROR nogil:
diff --git a/cuda_bindings/cuda/bindings/cynvrtc.pxd b/cuda_bindings/cuda/bindings/cynvrtc.pxd
index 37e76005971..62f3056d226 100644
--- a/cuda_bindings/cuda/bindings/cynvrtc.pxd
+++ b/cuda_bindings/cuda/bindings/cynvrtc.pxd
@@ -2,14 +2,12 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a5984ec05eaf04c2ac41c7771b8f7b364aeab3379ee9785f1b24be8d3cf54996
-from libc.stdint cimport uint32_t, uint64_t
 
 
 # ENUMS
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a5c9499b37f9bbb764b0cac167daeae7f4539de7093938c95d2fdc83fe70e8f6
 cdef extern from 'nvrtc.h':
     ctypedef enum nvrtcResult "nvrtcResult":
         NVRTC_SUCCESS
diff --git a/cuda_bindings/cuda/bindings/cynvrtc.pyx b/cuda_bindings/cuda/bindings/cynvrtc.pyx
index fba8bc6a646..77481cfd41f 100644
--- a/cuda_bindings/cuda/bindings/cynvrtc.pyx
+++ b/cuda_bindings/cuda/bindings/cynvrtc.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1d9a881bfe3a610482ffafe142e4f1ce9b0fbaa994c5b5ffc3479aaffa3321ee
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=6f99f863837a6b8fb2da89dfe53cb7a4d42ae5e413c181bbfb8e557a1fec0bff
 from ._internal cimport nvrtc as _nvrtc
 
 cdef const char* nvrtcGetErrorString(nvrtcResult result) except?NULL nogil:
diff --git a/cuda_bindings/cuda/bindings/cynvvm.pxd b/cuda_bindings/cuda/bindings/cynvvm.pxd
index 265ba1e67ac..1dea8578b40 100644
--- a/cuda_bindings/cuda/bindings/cynvvm.pxd
+++ b/cuda_bindings/cuda/bindings/cynvvm.pxd
@@ -2,7 +2,7 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
 
 
 ###############################################################################
@@ -10,8 +10,7 @@
 ###############################################################################
 
 # enums
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a12951d46579f8e61f9db52baac664267a20686d4817cd73fca72880384938c8
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=060a4e1d735676d6239664555a8a07b292481085ca0f5b5f362ce5289f20ca6d
 ctypedef enum nvvmResult "nvvmResult":
     NVVM_SUCCESS "NVVM_SUCCESS" = 0
     NVVM_ERROR_OUT_OF_MEMORY "NVVM_ERROR_OUT_OF_MEMORY" = 1
diff --git a/cuda_bindings/cuda/bindings/cynvvm.pyx b/cuda_bindings/cuda/bindings/cynvvm.pyx
index acfac1325ff..45028385633 100644
--- a/cuda_bindings/cuda/bindings/cynvvm.pyx
+++ b/cuda_bindings/cuda/bindings/cynvvm.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=7b192f7eeaa6f6cf5d27ad50ab58bd7120734a43628621ee954ab223b0e772c5
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f235b24d553d40a065b8e5df12f584994d30eb6a3f52fc0dd35d7202c703f05b
 from ._internal cimport nvvm as _nvvm
 
 
diff --git a/cuda_bindings/cuda/bindings/cyruntime.pxd b/cuda_bindings/cuda/bindings/cyruntime.pxd
index 387c3f09d7f..2d705a6be16 100644
--- a/cuda_bindings/cuda/bindings/cyruntime.pxd
+++ b/cuda_bindings/cuda/bindings/cyruntime.pxd
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=833f9a47fd72d2c4d0b0b88e49283e323464e1cfb40f424ab9915beb9d24502a
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=c3643e519b69bdb09b9c4c6ff3ecd3aebb180636d00e9a7bd2fe129cbed3eeb4
 from libc.stdint cimport uint32_t, uint64_t
 
 
diff --git a/cuda_bindings/cuda/bindings/cyruntime.pyx b/cuda_bindings/cuda/bindings/cyruntime.pyx
index 73324b51498..2e6e08aa3cf 100644
--- a/cuda_bindings/cuda/bindings/cyruntime.pyx
+++ b/cuda_bindings/cuda/bindings/cyruntime.pyx
@@ -2,10 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.0 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.0 to 13.4.1. Do not modify it directly.
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=688a31f40f86e60ac9bab47ed3c6c11f0762c60016d8167d3a57f3b3dc61c7cf
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=d40a4f5510e4271a0984232f64fe01ac712187b248fb15167fbc8e40f024d512
 from ._internal cimport runtime as _runtime
 
 cdef cudaError_t cudaDeviceReset() except ?cudaErrorCallRequiresNewerDriver nogil:
diff --git a/cuda_bindings/cuda/bindings/driver.pxd b/cuda_bindings/cuda/bindings/driver.pxd
index 44d474ca68e..454c4cd7e59 100644
--- a/cuda_bindings/cuda/bindings/driver.pxd
+++ b/cuda_bindings/cuda/bindings/driver.pxd
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated with version 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=3493d4c4789723331ed15bd7d54668deeccd7d41b0eafe2361c3b3313e2b8032
+# This code was automatically generated with version 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=4f3e3117475b43ef1ebbe0cd972d2aa6ef4dc5d449a43f1d9ad1d01625604c32
 cimport cuda.bindings.cydriver as cydriver
 
 include "_lib/utils.pxd"
diff --git a/cuda_bindings/cuda/bindings/driver.pyx b/cuda_bindings/cuda/bindings/driver.pyx
index 92237525d80..781d040c1f7 100644
--- a/cuda_bindings/cuda/bindings/driver.pyx
+++ b/cuda_bindings/cuda/bindings/driver.pyx
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated with version 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a1404cb4432dcb406b0793e27235118beca37669afc1986a9d5d91c354bbcc1a
+# This code was automatically generated with version 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=79336857bd6bf7884714e40db0ea94f28275fb08b283efa6bae52b1e93529c14
 from typing import Any, Optional
 import cython
 import ctypes
diff --git a/cuda_bindings/cuda/bindings/nvfatbin.pxd b/cuda_bindings/cuda/bindings/nvfatbin.pxd
index aca95c85185..192e7f55fde 100644
--- a/cuda_bindings/cuda/bindings/nvfatbin.pxd
+++ b/cuda_bindings/cuda/bindings/nvfatbin.pxd
@@ -2,11 +2,17 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.4.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.4.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=9ead77b928fe2009e92249025e5b38bf079a25fc0d9737aafd3cbeddb5c86661
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f9455d8c181ccdf20d59511bf1236f302dbe9ef903b61035cc1dd971e278caa1
-from libc.stdint cimport intptr_t, uint32_t
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport intptr_t
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
 from .cynvfatbin cimport *
 
diff --git a/cuda_bindings/cuda/bindings/nvfatbin.pyx b/cuda_bindings/cuda/bindings/nvfatbin.pyx
index 8e640a970d3..477026d721e 100644
--- a/cuda_bindings/cuda/bindings/nvfatbin.pyx
+++ b/cuda_bindings/cuda/bindings/nvfatbin.pyx
@@ -2,22 +2,53 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.4.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a9f06b8372f6c9da9bd1056df4fe0095a6e4a2b85496da6cca9a5496b641a909
+# This code was automatically generated across versions from 12.4.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=a696e744ee4520d7a8db8937f28c9ae9b92ff208900c1aba6b3dcf866a960e64
 
 
 # <<<< PREAMBLE CONTENT >>>>
 
+cimport cpython as _cyb_cpython
+from libc.stdint cimport intptr_t
+
 from cuda.bindings._internal._fast_enum import FastEnum as _cyb_FastEnum
 
+cdef intptr_t _cyb_get_buffer_pointer(buf, Py_ssize_t size, readonly=True) except?-1:
+    cdef intptr_t ptr
+    cdef int flags = _cyb_cpython.PyBUF_ANY_CONTIGUOUS
+    if not readonly:
+        flags |= _cyb_cpython.PyBUF_WRITABLE
+    cdef int status = -1
+    cdef _cyb_cpython.Py_buffer view
+    if isinstance(buf, int):
+        ptr = <intptr_t>buf
+    else:
+        try:
+            status = _cyb_cpython.PyObject_GetBuffer(buf, &view, flags)
+            if size != -1:
+                assert view.len == size
+            assert view.ndim == 1
+        except Exception as e:
+            adj = "writable " if not readonly else ""
+            raise ValueError(
+                "buf must be either a Python int representing the pointer "
+                f"address to a valid buffer, or a 1D contiguous {adj}"
+                f"buffer, of size {size}"
+            ) from e
+        else:
+            ptr = <intptr_t>view.buf
+        finally:
+            if status == 0:
+                _cyb_cpython.PyBuffer_Release(&view)
+    return ptr
+
 
 # <<<< END OF PREAMBLE CONTENT >>>>
 
 cimport cython  # NOQA
 
 from ._internal.utils cimport (get_resource_ptr, get_nested_resource_ptr, nested_resource, nullable_unique_ptr,
-                               get_buffer_pointer, get_resource_ptrs)
+                               get_resource_ptrs)
 
 from libcpp.vector cimport vector
 
@@ -157,7 +188,7 @@ cpdef add_ptx(intptr_t handle, code, size_t size, arch, identifier, options_cmd_
 
     .. seealso:: `nvFatbinAddPTX`
     """
-    cdef void* _code_ = get_buffer_pointer(code, size, readonly=True)
+    cdef void* _code_ = <void *>_cyb_get_buffer_pointer(code, size, readonly=True)
     if not isinstance(arch, str):
         raise TypeError("arch must be a Python str")
     cdef bytes _temp_arch_ = (<str>arch).encode()
@@ -189,7 +220,7 @@ cpdef add_cubin(intptr_t handle, code, size_t size, arch, identifier):
 
     .. seealso:: `nvFatbinAddCubin`
     """
-    cdef void* _code_ = get_buffer_pointer(code, size, readonly=True)
+    cdef void* _code_ = <void *>_cyb_get_buffer_pointer(code, size, readonly=True)
     if not isinstance(arch, str):
         raise TypeError("arch must be a Python str")
     cdef bytes _temp_arch_ = (<str>arch).encode()
@@ -218,7 +249,7 @@ cpdef add_ltoir(intptr_t handle, code, size_t size, arch, identifier, options_cm
 
     .. seealso:: `nvFatbinAddLTOIR`
     """
-    cdef void* _code_ = get_buffer_pointer(code, size, readonly=True)
+    cdef void* _code_ = <void *>_cyb_get_buffer_pointer(code, size, readonly=True)
     if not isinstance(arch, str):
         raise TypeError("arch must be a Python str")
     cdef bytes _temp_arch_ = (<str>arch).encode()
@@ -263,7 +294,7 @@ cpdef get(intptr_t handle, buffer):
 
     .. seealso:: `nvFatbinGet`
     """
-    cdef void* _buffer_ = get_buffer_pointer(buffer, -1, readonly=False)
+    cdef void* _buffer_ = <void *>_cyb_get_buffer_pointer(buffer, -1, readonly=False)
     with nogil:
         __status__ = nvFatbinGet(<Handle>handle, <void*>_buffer_)
     check_status(__status__)
@@ -289,7 +320,7 @@ cpdef tuple version():
 
 
 cpdef add_index(intptr_t handle, code, size_t size, identifier):
-    cdef void* _code_ = get_buffer_pointer(code, size, readonly=True)
+    cdef void* _code_ = <void *>_cyb_get_buffer_pointer(code, size, readonly=True)
     if not isinstance(identifier, str):
         raise TypeError("identifier must be a Python str")
     cdef bytes _temp_identifier_ = (<str>identifier).encode()
@@ -309,7 +340,7 @@ cpdef add_reloc(intptr_t handle, code, size_t size):
 
     .. seealso:: `nvFatbinAddReloc`
     """
-    cdef void* _code_ = get_buffer_pointer(code, size, readonly=True)
+    cdef void* _code_ = <void *>_cyb_get_buffer_pointer(code, size, readonly=True)
     with nogil:
         __status__ = nvFatbinAddReloc(<Handle>handle, <const void*>_code_, size)
     check_status(__status__)
@@ -328,7 +359,7 @@ cpdef add_tile_ir(intptr_t handle, code, size_t size, identifier, options_cmd_li
 
     .. seealso:: `nvFatbinAddTileIR`
     """
-    cdef void* _code_ = get_buffer_pointer(code, size, readonly=True)
+    cdef void* _code_ = <void *>_cyb_get_buffer_pointer(code, size, readonly=True)
     if not isinstance(identifier, str):
         raise TypeError("identifier must be a Python str")
     cdef bytes _temp_identifier_ = (<str>identifier).encode()
diff --git a/cuda_bindings/cuda/bindings/nvjitlink.pxd b/cuda_bindings/cuda/bindings/nvjitlink.pxd
index 7c55364f171..b383554eaca 100644
--- a/cuda_bindings/cuda/bindings/nvjitlink.pxd
+++ b/cuda_bindings/cuda/bindings/nvjitlink.pxd
@@ -2,11 +2,20 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=bdd807ca03377f36b064e28eaa2421255316987c009a65a55f05fbc1a22e2bf3
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=71dbc31e82ef2e456eb1a686757dc7a9f951a37f7c4d813d8b4ed92956a0f225
-from libc.stdint cimport intptr_t, uint32_t
+
+
+# <<<< PREAMBLE CONTENT >>>>
+
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+)
+
+
+# <<<< END OF PREAMBLE CONTENT >>>>
 
 from .cynvjitlink cimport *
 
diff --git a/cuda_bindings/cuda/bindings/nvjitlink.pyx b/cuda_bindings/cuda/bindings/nvjitlink.pyx
index adeb4c40de9..5476ab63c89 100644
--- a/cuda_bindings/cuda/bindings/nvjitlink.pyx
+++ b/cuda_bindings/cuda/bindings/nvjitlink.pyx
@@ -2,22 +2,56 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f722861e068fe62c47806f8fc7757afc24a313435cc14026e1b4f59d1b7f2be7
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=930ba914df7615926a16dd5224f9250eb512e83c1b85e8282470f252706359a8
 
 
 # <<<< PREAMBLE CONTENT >>>>
 
+cimport cpython as _cyb_cpython
+from libc.stdint cimport (
+    intptr_t,
+    uint32_t,
+)
+
 from cuda.bindings._internal._fast_enum import FastEnum as _cyb_FastEnum
 
+cdef intptr_t _cyb_get_buffer_pointer(buf, Py_ssize_t size, readonly=True) except?-1:
+    cdef intptr_t ptr
+    cdef int flags = _cyb_cpython.PyBUF_ANY_CONTIGUOUS
+    if not readonly:
+        flags |= _cyb_cpython.PyBUF_WRITABLE
+    cdef int status = -1
+    cdef _cyb_cpython.Py_buffer view
+    if isinstance(buf, int):
+        ptr = <intptr_t>buf
+    else:
+        try:
+            status = _cyb_cpython.PyObject_GetBuffer(buf, &view, flags)
+            if size != -1:
+                assert view.len == size
+            assert view.ndim == 1
+        except Exception as e:
+            adj = "writable " if not readonly else ""
+            raise ValueError(
+                "buf must be either a Python int representing the pointer "
+                f"address to a valid buffer, or a 1D contiguous {adj}"
+                f"buffer, of size {size}"
+            ) from e
+        else:
+            ptr = <intptr_t>view.buf
+        finally:
+            if status == 0:
+                _cyb_cpython.PyBuffer_Release(&view)
+    return ptr
+
 
 # <<<< END OF PREAMBLE CONTENT >>>>
 
 cimport cython  # NOQA
 
 from ._internal.utils cimport (get_resource_ptr, get_nested_resource_ptr, nested_resource, nullable_unique_ptr,
-                               get_buffer_pointer, get_resource_ptrs)
+                               get_resource_ptrs)
 
 from libcpp.vector cimport vector
 
@@ -153,7 +187,7 @@ cpdef add_data(intptr_t handle, int input_type, data, size_t size, name):
 
     .. seealso:: `nvJitLinkAddData`
     """
-    cdef void* _data_ = get_buffer_pointer(data, size, readonly=True)
+    cdef void* _data_ = <void *>_cyb_get_buffer_pointer(data, size, readonly=True)
     if not isinstance(name, str):
         raise TypeError("name must be a Python str")
     cdef bytes _temp_name_ = (<str>name).encode()
@@ -222,7 +256,7 @@ cpdef get_linked_cubin(intptr_t handle, cubin):
 
     .. seealso:: `nvJitLinkGetLinkedCubin`
     """
-    cdef void* _cubin_ = get_buffer_pointer(cubin, -1, readonly=False)
+    cdef void* _cubin_ = <void *>_cyb_get_buffer_pointer(cubin, -1, readonly=False)
     with nogil:
         __status__ = nvJitLinkGetLinkedCubin(<Handle>handle, <void*>_cubin_)
     check_status(__status__)
@@ -255,7 +289,7 @@ cpdef get_linked_ptx(intptr_t handle, ptx):
 
     .. seealso:: `nvJitLinkGetLinkedPtx`
     """
-    cdef void* _ptx_ = get_buffer_pointer(ptx, -1, readonly=False)
+    cdef void* _ptx_ = <void *>_cyb_get_buffer_pointer(ptx, -1, readonly=False)
     with nogil:
         __status__ = nvJitLinkGetLinkedPtx(<Handle>handle, <char*>_ptx_)
     check_status(__status__)
@@ -288,7 +322,7 @@ cpdef get_error_log(intptr_t handle, log):
 
     .. seealso:: `nvJitLinkGetErrorLog`
     """
-    cdef void* _log_ = get_buffer_pointer(log, -1, readonly=False)
+    cdef void* _log_ = <void *>_cyb_get_buffer_pointer(log, -1, readonly=False)
     with nogil:
         __status__ = nvJitLinkGetErrorLog(<Handle>handle, <char*>_log_)
     check_status(__status__)
@@ -321,7 +355,7 @@ cpdef get_info_log(intptr_t handle, log):
 
     .. seealso:: `nvJitLinkGetInfoLog`
     """
-    cdef void* _log_ = get_buffer_pointer(log, -1, readonly=False)
+    cdef void* _log_ = <void *>_cyb_get_buffer_pointer(log, -1, readonly=False)
     with nogil:
         __status__ = nvJitLinkGetInfoLog(<Handle>handle, <char*>_log_)
     check_status(__status__)
@@ -373,7 +407,7 @@ cpdef get_linked_ltoir(intptr_t handle, ltoir):
 
     .. seealso:: `nvJitLinkGetLinkedLTOIR`
     """
-    cdef void* _ltoir_ = get_buffer_pointer(ltoir, -1, readonly=False)
+    cdef void* _ltoir_ = <void *>_cyb_get_buffer_pointer(ltoir, -1, readonly=False)
     with nogil:
         __status__ = nvJitLinkGetLinkedLTOIR(<Handle>handle, <void*>_ltoir_)
     check_status(__status__)
diff --git a/cuda_bindings/cuda/bindings/nvml.pxd b/cuda_bindings/cuda/bindings/nvml.pxd
index 40546231530..6f35132912f 100644
--- a/cuda_bindings/cuda/bindings/nvml.pxd
+++ b/cuda_bindings/cuda/bindings/nvml.pxd
@@ -2,12 +2,18 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=635b329217b9c57fce06de4ffd743372a120b5039eb247f49205bd4d2baf663c
+
+
+
+# <<<< PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=f699a98280e825837b6ddf7fb083deca9f51318e2406acefd67481a68b43a165
 from libc.stdint cimport intptr_t
 
+
+# <<<< END OF PREAMBLE CONTENT >>>>
+
 from .cynvml cimport *
 
 
@@ -446,8 +452,5 @@ cpdef object device_perf_metrics_get_samples_v1(intptr_t device)
 cpdef object device_set_nvlink_bw_mode_async_v1(intptr_t device)
 cpdef object device_get_nv_link_telemetry_samples_v1(intptr_t device)
 cpdef event_set_register_gpu_operational_events_v1(intptr_t event_set, intptr_t config)
-cpdef object event_set_wait_v3(intptr_t set, unsigned int timeoutms)
-cpdef unsigned int event_set_get_context_count_v1(intptr_t set) except? 0
-cpdef object event_set_get_context_info_v1(intptr_t set, unsigned int index)
-cpdef object event_set_get_gpu_operational_event_context_legacy_xid_v1(intptr_t set, unsigned int index)
+cpdef object event_set_get_context_count_v1(intptr_t set)
 cpdef object device_get_bank_remapper_status_v1(intptr_t device)
diff --git a/cuda_bindings/cuda/bindings/nvml.pyx b/cuda_bindings/cuda/bindings/nvml.pyx
index b8b720ee11f..9f0d104abba 100644
--- a/cuda_bindings/cuda/bindings/nvml.pyx
+++ b/cuda_bindings/cuda/bindings/nvml.pyx
@@ -2,9 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.9.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=e6637452fb185e3d30ab3d126d11f1f4de18b77785d64948b4ee580f4ddf03fe
+# This code was automatically generated across versions from 12.9.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=7447d022b0937ff32b98e8a8a6f0a3e0564884c4a217b51e9312290015c7a406
 
 
 # <<<< PREAMBLE CONTENT >>>>
@@ -13,6 +12,7 @@ cimport cpython as _cyb_cpython
 cimport cpython.buffer as _cyb_cpython_buffer
 cimport cpython.memoryview as _cyb_cpython_memoryview
 from cython cimport view as _cyb_view
+from libc.stdint cimport intptr_t
 from libc.stdlib cimport (
     calloc as _cyb_calloc,
     free as _cyb_free,
@@ -73,7 +73,7 @@ from cython cimport view
 cimport cpython
 from libc.string cimport memcpy
 
-from ._internal.utils cimport (get_buffer_pointer, get_nested_resource_ptr,
+from ._internal.utils cimport (get_nested_resource_ptr,
                                nested_resource)
 
 from cuda.bindings._internal._fast_enum import FastEnum as _FastEnum
@@ -848,7 +848,7 @@ class GpmMetricId(_cyb_FastEnum):
     GPM_METRIC_HMMA_TENSOR_UTIL = (NVML_GPM_METRIC_HMMA_TENSOR_UTIL, "Percentage of time the GPU's SMs were doing HMMA tensor operations. 0.0 - 100.0.")
     GPM_METRIC_DMMA_TENSOR_UTIL = (NVML_GPM_METRIC_DMMA_TENSOR_UTIL, "Percentage of time the GPU's SMs were doing DMMA tensor operations. 0.0 - 100.0.")
     GPM_METRIC_IMMA_TENSOR_UTIL = (NVML_GPM_METRIC_IMMA_TENSOR_UTIL, "Percentage of time the GPU's SMs were doing IMMA tensor operations. 0.0 - 100.0.")
-    GPM_METRIC_DRAM_BW_UTIL = (NVML_GPM_METRIC_DRAM_BW_UTIL, 'Percentage of DRAM bw used vs theoretical maximum. 0.0 - 100.0 *\u200d/.')
+    GPM_METRIC_DRAM_BW_UTIL = (NVML_GPM_METRIC_DRAM_BW_UTIL, 'Percentage of DRAM bw used vs theoretical maximum. `0.0 - 100.0 */`.')
     GPM_METRIC_FP64_UTIL = (NVML_GPM_METRIC_FP64_UTIL, "Percentage of time the GPU's SMs were doing non-tensor FP64 math. 0.0 - 100.0.")
     GPM_METRIC_FP32_UTIL = (NVML_GPM_METRIC_FP32_UTIL, "Percentage of time the GPU's SMs were doing non-tensor FP32 math. 0.0 - 100.0.")
     GPM_METRIC_FP16_UTIL = (NVML_GPM_METRIC_FP16_UTIL, "Percentage of time the GPU's SMs were doing non-tensor FP16 math. 0.0 - 100.0.")
@@ -1392,10 +1392,10 @@ class CPERType(_cyb_FastEnum):
 
 class GpuOperationalEventLogLevel(_cyb_FastEnum):
     """
-    Log-level values used by GPU Operational Events.These values are used
-    both for event reporting in `nvmlEventData_v2_t` and for subscription
-    filtering in `nvmlGpuOperationalEventConfig_v1_t`. Higher numeric
-    values represent more selective log levels.
+    Log-level values used by GPU Operational Events.  These values are used
+    both for event reporting in `nvmlEventSetWait_v3_t` and for
+    subscription filtering in `nvmlGpuOperationalEventConfig_v1_t`. Higher
+    numeric values represent more selective log levels.
     `NVML_GPU_OPERATIONAL_EVENT_LOG_LEVEL_ALL` disables log-level filtering
     when used as a subscription threshold. Event data may contain newer
     log-level values that are not named in this header; clients should
@@ -1412,8 +1412,8 @@ class GpuOperationalEventLogLevel(_cyb_FastEnum):
 
 class OperationalEventSeverity(_cyb_FastEnum):
     """
-    Severity values used by Operational Events.These values are used both
-    for event reporting in `nvmlEventData_v2_t` and for subscription
+    Severity values used by Operational Events.  These values are used both
+    for event reporting in `nvmlEventSetWait_v3_t` and for subscription
     filtering in `nvmlGpuOperationalEventConfig_v1_t`. Higher numeric
     values represent more selective severities.
     `NVML_OPERATIONAL_EVENT_SEVERITY_ALL` disables severity filtering when
@@ -1440,10 +1440,10 @@ class EventDataType(_cyb_FastEnum):
 
 class GpuOperationalEventContextType(_cyb_FastEnum):
     """
-    NVML-defined GPU Operational Event context classifications.These values
-    describe the NVML public interpretation of a context payload. The
-    original source-defined context type is returned separately in
-    `nvmlOperationalEventContextInfo_v1_t.sourceEventContextType`.
+    NVML-defined GPU Operational Event context classifications.  These
+    values describe the NVML public interpretation of a context payload.
+    The original source-defined context type is returned separately in
+    `nvmlEventSetGetContextInfo_v1_t.sourceEventContextType`.
 
     See `nvmlGpuOperationalEventContextType_t`.
     """
@@ -14943,7 +14943,7 @@ cdef class DevicePowerMizerModes_v1:
 
     @property
     def supported_power_mizer_modes(self):
-        """int: OUT: Bitmask of supported powermizer modes. The bitmask of supported power mizer modes on this device. The supported modes can be combined using the bitwise OR operator '|'. For example, if a device supports all PowerMizer modes, the bitmask would be: supportedPowerMizerModes = ((1 << NVML_POWER_MIZER_MODE_ADAPTIVE) | (1 << NVML_POWER_MIZER_MODE_PREFER_MAXIMUM_PERFORMANCE) | (1 << NVML_POWER_MIZER_MODE_AUTO) | (1 << NVML_POWER_MIZER_MODE_PREFER_CONSISTENT_PERFORMANCE));  This bitmask can be used to check which power mizer modes are available on the device by performing a bitwise AND operation with the specific mode you want to check."""
+        """int: OUT: Bitmask of supported powermizer modes.   The bitmask of supported power mizer modes on this device. The supported modes can be combined using the bitwise OR operator '|'. For example, if a device supports all PowerMizer modes, the bitmask would be: supportedPowerMizerModes = ((1 << NVML_POWER_MIZER_MODE_ADAPTIVE) | (1 << NVML_POWER_MIZER_MODE_PREFER_MAXIMUM_PERFORMANCE) | (1 << NVML_POWER_MIZER_MODE_AUTO) | (1 << NVML_POWER_MIZER_MODE_PREFER_CONSISTENT_PERFORMANCE));  This bitmask can be used to check which power mizer modes are available on the device by performing a bitwise AND operation with the specific mode you want to check."""
         return self._ptr[0].supportedPowerMizerModes
 
     @supported_power_mizer_modes.setter
@@ -18423,51 +18423,183 @@ cdef class AdaptiveTgpModeInfo_v1:
         return obj
 
 
-cdef _get_operational_event_context_info_v1_dtype_offsets():
-    cdef nvmlOperationalEventContextInfo_v1_t pod
+cdef _get_event_set_get_context_count_v1_dtype_offsets():
+    cdef nvmlEventSetGetContextCount_v1_t pod
+    return _numpy.dtype({
+        'names': ['count'],
+        'formats': [_numpy.uint32],
+        'offsets': [
+            (<intptr_t>&(pod.count)) - (<intptr_t>&pod),
+        ],
+        'itemsize': sizeof(nvmlEventSetGetContextCount_v1_t),
+    })
+
+event_set_get_context_count_v1_dtype = _get_event_set_get_context_count_v1_dtype_offsets()
+
+cdef class EventSetGetContextCount_v1:
+    """Empty-initialize an instance of `nvmlEventSetGetContextCount_v1_t`.
+
+
+    .. seealso:: `nvmlEventSetGetContextCount_v1_t`
+    """
+    cdef:
+        nvmlEventSetGetContextCount_v1_t *_ptr
+        object _owner
+        bint _owned
+        bint _readonly
+
+    def __init__(self):
+        self._ptr = <nvmlEventSetGetContextCount_v1_t *>_cyb_calloc(1, sizeof(nvmlEventSetGetContextCount_v1_t))
+        if self._ptr == NULL:
+            raise MemoryError("Error allocating EventSetGetContextCount_v1")
+        self._owner = None
+        self._owned = True
+        self._readonly = False
+
+    def __dealloc__(self):
+        cdef nvmlEventSetGetContextCount_v1_t *ptr
+        if self._owned and self._ptr != NULL:
+            ptr = self._ptr
+            self._ptr = NULL
+            _cyb_free(ptr)
+
+    def __repr__(self):
+        return f"<{__name__}.EventSetGetContextCount_v1 object at {hex(id(self))}>"
+
+    @property
+    def ptr(self):
+        """Get the pointer address to the data as Python :class:`int`."""
+        return <intptr_t>(self._ptr)
+
+    cdef intptr_t _get_ptr(self):
+        return <intptr_t>(self._ptr)
+
+    def __int__(self):
+        return <intptr_t>(self._ptr)
+
+    def __eq__(self, other):
+        cdef EventSetGetContextCount_v1 other_
+        if not isinstance(other, EventSetGetContextCount_v1):
+            return False
+        other_ = other
+        return (_cyb_memcmp(<void *><intptr_t>(self._ptr), <void *><intptr_t>(other_._ptr), sizeof(nvmlEventSetGetContextCount_v1_t)) == 0)
+
+    def __getbuffer__(self, _cyb_cpython.Py_buffer *buffer, int flags):
+        _cyb___getbuffer(self, buffer, <void *>self._ptr, sizeof(nvmlEventSetGetContextCount_v1_t), self._readonly)
+
+    def __releasebuffer__(self, Py_buffer *buffer):
+        pass
+
+    def __setitem__(self, key, val):
+        if key == 0 and isinstance(val, _numpy.ndarray):
+            self._ptr = <nvmlEventSetGetContextCount_v1_t *>_cyb_malloc(sizeof(nvmlEventSetGetContextCount_v1_t))
+            if self._ptr == NULL:
+                raise MemoryError("Error allocating EventSetGetContextCount_v1")
+            _cyb_memcpy(<void*>self._ptr, <void*><intptr_t>val.ctypes.data, sizeof(nvmlEventSetGetContextCount_v1_t))
+            self._owner = None
+            self._owned = True
+            self._readonly = not val.flags.writeable
+        else:
+            setattr(self, key, val)
+
+    @property
+    def count(self):
+        """int: [out] Number of context records associated with the most recent event."""
+        return self._ptr[0].count
+
+    @count.setter
+    def count(self, val):
+        if self._readonly:
+            raise ValueError("This EventSetGetContextCount_v1 instance is read-only")
+        self._ptr[0].count = val
+
+    @staticmethod
+    def from_buffer(buffer):
+        """Create an EventSetGetContextCount_v1 instance with the memory from the given buffer."""
+        return _cyb_from_buffer(buffer, sizeof(nvmlEventSetGetContextCount_v1_t), EventSetGetContextCount_v1)
+
+    @staticmethod
+    def from_data(data):
+        """Create an EventSetGetContextCount_v1 instance wrapping the given NumPy array.
+
+        Args:
+            data (_numpy.ndarray): a single-element array of dtype `event_set_get_context_count_v1_dtype` holding the data.
+        """
+        return _cyb_from_data(data, "event_set_get_context_count_v1_dtype", event_set_get_context_count_v1_dtype, EventSetGetContextCount_v1)
+
+    @staticmethod
+    def from_ptr(intptr_t ptr, bint readonly=False, object owner=None):
+        """Create an EventSetGetContextCount_v1 instance wrapping the given pointer.
+
+        Args:
+            ptr (intptr_t): pointer address as Python :class:`int` to the data.
+            owner (object): The Python object that owns the pointer. If not provided, data will be copied.
+            readonly (bool): whether the data is read-only (to the user). default is `False`.
+        """
+        if ptr == 0:
+            raise ValueError("ptr must not be null (0)")
+        cdef EventSetGetContextCount_v1 obj = EventSetGetContextCount_v1.__new__(EventSetGetContextCount_v1)
+        if owner is None:
+            obj._ptr = <nvmlEventSetGetContextCount_v1_t *>_cyb_malloc(sizeof(nvmlEventSetGetContextCount_v1_t))
+            if obj._ptr == NULL:
+                raise MemoryError("Error allocating EventSetGetContextCount_v1")
+            _cyb_memcpy(<void*>(obj._ptr), <void*>ptr, sizeof(nvmlEventSetGetContextCount_v1_t))
+            obj._owner = None
+            obj._owned = True
+        else:
+            obj._ptr = <nvmlEventSetGetContextCount_v1_t *>ptr
+            obj._owner = owner
+            obj._owned = False
+        obj._readonly = readonly
+        return obj
+
+
+cdef _get_event_set_get_context_info_v1_dtype_offsets():
+    cdef nvmlEventSetGetContextInfo_v1_t pod
     return _numpy.dtype({
-        'names': ['nvml_gpu_operational_event_context_type', 'source_event_context_type', 'data_size', 'data_format_version'],
-        'formats': [_numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint16],
+        'names': ['index', 'nvml_gpu_operational_event_context_type', 'source_event_context_type', 'data_size', 'data_format_version'],
+        'formats': [_numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint16],
         'offsets': [
+            (<intptr_t>&(pod.index)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.nvmlGpuOperationalEventContextType)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.sourceEventContextType)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.dataSize)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.dataFormatVersion)) - (<intptr_t>&pod),
         ],
-        'itemsize': sizeof(nvmlOperationalEventContextInfo_v1_t),
+        'itemsize': sizeof(nvmlEventSetGetContextInfo_v1_t),
     })
 
-operational_event_context_info_v1_dtype = _get_operational_event_context_info_v1_dtype_offsets()
+event_set_get_context_info_v1_dtype = _get_event_set_get_context_info_v1_dtype_offsets()
 
-cdef class OperationalEventContextInfo_v1:
-    """Empty-initialize an instance of `nvmlOperationalEventContextInfo_v1_t`.
+cdef class EventSetGetContextInfo_v1:
+    """Empty-initialize an instance of `nvmlEventSetGetContextInfo_v1_t`.
 
 
-    .. seealso:: `nvmlOperationalEventContextInfo_v1_t`
+    .. seealso:: `nvmlEventSetGetContextInfo_v1_t`
     """
     cdef:
-        nvmlOperationalEventContextInfo_v1_t *_ptr
+        nvmlEventSetGetContextInfo_v1_t *_ptr
         object _owner
         bint _owned
         bint _readonly
 
     def __init__(self):
-        self._ptr = <nvmlOperationalEventContextInfo_v1_t *>_cyb_calloc(1, sizeof(nvmlOperationalEventContextInfo_v1_t))
+        self._ptr = <nvmlEventSetGetContextInfo_v1_t *>_cyb_calloc(1, sizeof(nvmlEventSetGetContextInfo_v1_t))
         if self._ptr == NULL:
-            raise MemoryError("Error allocating OperationalEventContextInfo_v1")
+            raise MemoryError("Error allocating EventSetGetContextInfo_v1")
         self._owner = None
         self._owned = True
         self._readonly = False
 
     def __dealloc__(self):
-        cdef nvmlOperationalEventContextInfo_v1_t *ptr
+        cdef nvmlEventSetGetContextInfo_v1_t *ptr
         if self._owned and self._ptr != NULL:
             ptr = self._ptr
             self._ptr = NULL
             _cyb_free(ptr)
 
     def __repr__(self):
-        return f"<{__name__}.OperationalEventContextInfo_v1 object at {hex(id(self))}>"
+        return f"<{__name__}.EventSetGetContextInfo_v1 object at {hex(id(self))}>"
 
     @property
     def ptr(self):
@@ -18481,91 +18613,102 @@ cdef class OperationalEventContextInfo_v1:
         return <intptr_t>(self._ptr)
 
     def __eq__(self, other):
-        cdef OperationalEventContextInfo_v1 other_
-        if not isinstance(other, OperationalEventContextInfo_v1):
+        cdef EventSetGetContextInfo_v1 other_
+        if not isinstance(other, EventSetGetContextInfo_v1):
             return False
         other_ = other
-        return (_cyb_memcmp(<void *><intptr_t>(self._ptr), <void *><intptr_t>(other_._ptr), sizeof(nvmlOperationalEventContextInfo_v1_t)) == 0)
+        return (_cyb_memcmp(<void *><intptr_t>(self._ptr), <void *><intptr_t>(other_._ptr), sizeof(nvmlEventSetGetContextInfo_v1_t)) == 0)
 
     def __getbuffer__(self, _cyb_cpython.Py_buffer *buffer, int flags):
-        _cyb___getbuffer(self, buffer, <void *>self._ptr, sizeof(nvmlOperationalEventContextInfo_v1_t), self._readonly)
+        _cyb___getbuffer(self, buffer, <void *>self._ptr, sizeof(nvmlEventSetGetContextInfo_v1_t), self._readonly)
 
     def __releasebuffer__(self, Py_buffer *buffer):
         pass
 
     def __setitem__(self, key, val):
         if key == 0 and isinstance(val, _numpy.ndarray):
-            self._ptr = <nvmlOperationalEventContextInfo_v1_t *>_cyb_malloc(sizeof(nvmlOperationalEventContextInfo_v1_t))
+            self._ptr = <nvmlEventSetGetContextInfo_v1_t *>_cyb_malloc(sizeof(nvmlEventSetGetContextInfo_v1_t))
             if self._ptr == NULL:
-                raise MemoryError("Error allocating OperationalEventContextInfo_v1")
-            _cyb_memcpy(<void*>self._ptr, <void*><intptr_t>val.ctypes.data, sizeof(nvmlOperationalEventContextInfo_v1_t))
+                raise MemoryError("Error allocating EventSetGetContextInfo_v1")
+            _cyb_memcpy(<void*>self._ptr, <void*><intptr_t>val.ctypes.data, sizeof(nvmlEventSetGetContextInfo_v1_t))
             self._owner = None
             self._owned = True
             self._readonly = not val.flags.writeable
         else:
             setattr(self, key, val)
 
+    @property
+    def index(self):
+        """int: [in] Zero-based context index."""
+        return self._ptr[0].index
+
+    @index.setter
+    def index(self, val):
+        if self._readonly:
+            raise ValueError("This EventSetGetContextInfo_v1 instance is read-only")
+        self._ptr[0].index = val
+
     @property
     def nvml_gpu_operational_event_context_type(self):
-        """int: """
+        """int: [out] `nvmlGpuOperationalEventContextType_t` value describing the NVML public interpretation of the context payload."""
         return self._ptr[0].nvmlGpuOperationalEventContextType
 
     @nvml_gpu_operational_event_context_type.setter
     def nvml_gpu_operational_event_context_type(self, val):
         if self._readonly:
-            raise ValueError("This OperationalEventContextInfo_v1 instance is read-only")
+            raise ValueError("This EventSetGetContextInfo_v1 instance is read-only")
         self._ptr[0].nvmlGpuOperationalEventContextType = val
 
     @property
     def source_event_context_type(self):
-        """int: """
+        """int: [out] Source-defined context payload type identifier carried by the event."""
         return self._ptr[0].sourceEventContextType
 
     @source_event_context_type.setter
     def source_event_context_type(self, val):
         if self._readonly:
-            raise ValueError("This OperationalEventContextInfo_v1 instance is read-only")
+            raise ValueError("This EventSetGetContextInfo_v1 instance is read-only")
         self._ptr[0].sourceEventContextType = val
 
     @property
     def data_size(self):
-        """int: """
+        """int: [out] Context payload size in bytes, excluding alignment padding."""
         return self._ptr[0].dataSize
 
     @data_size.setter
     def data_size(self, val):
         if self._readonly:
-            raise ValueError("This OperationalEventContextInfo_v1 instance is read-only")
+            raise ValueError("This EventSetGetContextInfo_v1 instance is read-only")
         self._ptr[0].dataSize = val
 
     @property
     def data_format_version(self):
-        """int: """
+        """int: [out] Payload format version for `sourceEventContextType`."""
         return self._ptr[0].dataFormatVersion
 
     @data_format_version.setter
     def data_format_version(self, val):
         if self._readonly:
-            raise ValueError("This OperationalEventContextInfo_v1 instance is read-only")
+            raise ValueError("This EventSetGetContextInfo_v1 instance is read-only")
         self._ptr[0].dataFormatVersion = val
 
     @staticmethod
     def from_buffer(buffer):
-        """Create an OperationalEventContextInfo_v1 instance with the memory from the given buffer."""
-        return _cyb_from_buffer(buffer, sizeof(nvmlOperationalEventContextInfo_v1_t), OperationalEventContextInfo_v1)
+        """Create an EventSetGetContextInfo_v1 instance with the memory from the given buffer."""
+        return _cyb_from_buffer(buffer, sizeof(nvmlEventSetGetContextInfo_v1_t), EventSetGetContextInfo_v1)
 
     @staticmethod
     def from_data(data):
-        """Create an OperationalEventContextInfo_v1 instance wrapping the given NumPy array.
+        """Create an EventSetGetContextInfo_v1 instance wrapping the given NumPy array.
 
         Args:
-            data (_numpy.ndarray): a single-element array of dtype `operational_event_context_info_v1_dtype` holding the data.
+            data (_numpy.ndarray): a single-element array of dtype `event_set_get_context_info_v1_dtype` holding the data.
         """
-        return _cyb_from_data(data, "operational_event_context_info_v1_dtype", operational_event_context_info_v1_dtype, OperationalEventContextInfo_v1)
+        return _cyb_from_data(data, "event_set_get_context_info_v1_dtype", event_set_get_context_info_v1_dtype, EventSetGetContextInfo_v1)
 
     @staticmethod
     def from_ptr(intptr_t ptr, bint readonly=False, object owner=None):
-        """Create an OperationalEventContextInfo_v1 instance wrapping the given pointer.
+        """Create an EventSetGetContextInfo_v1 instance wrapping the given pointer.
 
         Args:
             ptr (intptr_t): pointer address as Python :class:`int` to the data.
@@ -18574,64 +18717,65 @@ cdef class OperationalEventContextInfo_v1:
         """
         if ptr == 0:
             raise ValueError("ptr must not be null (0)")
-        cdef OperationalEventContextInfo_v1 obj = OperationalEventContextInfo_v1.__new__(OperationalEventContextInfo_v1)
+        cdef EventSetGetContextInfo_v1 obj = EventSetGetContextInfo_v1.__new__(EventSetGetContextInfo_v1)
         if owner is None:
-            obj._ptr = <nvmlOperationalEventContextInfo_v1_t *>_cyb_malloc(sizeof(nvmlOperationalEventContextInfo_v1_t))
+            obj._ptr = <nvmlEventSetGetContextInfo_v1_t *>_cyb_malloc(sizeof(nvmlEventSetGetContextInfo_v1_t))
             if obj._ptr == NULL:
-                raise MemoryError("Error allocating OperationalEventContextInfo_v1")
-            _cyb_memcpy(<void*>(obj._ptr), <void*>ptr, sizeof(nvmlOperationalEventContextInfo_v1_t))
+                raise MemoryError("Error allocating EventSetGetContextInfo_v1")
+            _cyb_memcpy(<void*>(obj._ptr), <void*>ptr, sizeof(nvmlEventSetGetContextInfo_v1_t))
             obj._owner = None
             obj._owned = True
         else:
-            obj._ptr = <nvmlOperationalEventContextInfo_v1_t *>ptr
+            obj._ptr = <nvmlEventSetGetContextInfo_v1_t *>ptr
             obj._owner = owner
             obj._owned = False
         obj._readonly = readonly
         return obj
 
 
-cdef _get_gpu_operational_event_context_legacy_xid_v1_dtype_offsets():
-    cdef nvmlGpuOperationalEventContextLegacyXid_v1_t pod
+cdef _get_event_set_get_gpu_operational_event_context_legacy_xid_v1_dtype_offsets():
+    cdef nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t pod
     return _numpy.dtype({
-        'names': ['xid_code'],
-        'formats': [_numpy.uint32],
+        'names': ['index', 'xid_code'],
+        'formats': [_numpy.uint32, _numpy.uint32],
         'offsets': [
+            (<intptr_t>&(pod.index)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.xidCode)) - (<intptr_t>&pod),
         ],
-        'itemsize': sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t),
+        'itemsize': sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t),
     })
 
-gpu_operational_event_context_legacy_xid_v1_dtype = _get_gpu_operational_event_context_legacy_xid_v1_dtype_offsets()
+event_set_get_gpu_operational_event_context_legacy_xid_v1_dtype = _get_event_set_get_gpu_operational_event_context_legacy_xid_v1_dtype_offsets()
 
-cdef class GpuOperationalEventContextLegacyXid_v1:
-    """Empty-initialize an instance of `nvmlGpuOperationalEventContextLegacyXid_v1_t`.
+cdef class EventSetGetGpuOperationalEventContextLegacyXid_v1:
+    """Empty-initialize an instance of `nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t`.
 
 
-    .. seealso:: `nvmlGpuOperationalEventContextLegacyXid_v1_t`
+    .. seealso:: `nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t`
     """
     cdef:
-        nvmlGpuOperationalEventContextLegacyXid_v1_t *_ptr
+        nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *_ptr
         object _owner
         bint _owned
         bint _readonly
 
     def __init__(self):
-        self._ptr = <nvmlGpuOperationalEventContextLegacyXid_v1_t *>_cyb_calloc(1, sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t))
+        self._ptr = <nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *>_cyb_calloc(1, sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t))
         if self._ptr == NULL:
-            raise MemoryError("Error allocating GpuOperationalEventContextLegacyXid_v1")
+            raise MemoryError("Error allocating EventSetGetGpuOperationalEventContextLegacyXid_v1")
         self._owner = None
         self._owned = True
         self._readonly = False
 
     def __dealloc__(self):
-        cdef nvmlGpuOperationalEventContextLegacyXid_v1_t *ptr
+        cdef nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *ptr
         if self._owned and self._ptr != NULL:
             ptr = self._ptr
             self._ptr = NULL
             _cyb_free(ptr)
 
     def __repr__(self):
-        return f"<{__name__}.GpuOperationalEventContextLegacyXid_v1 object at {hex(id(self))}>"
+        return f"<{__name__}.EventSetGetGpuOperationalEventContextLegacyXid_v1 object at {hex(id(self))}>"
 
     @property
     def ptr(self):
@@ -18645,58 +18789,69 @@ cdef class GpuOperationalEventContextLegacyXid_v1:
         return <intptr_t>(self._ptr)
 
     def __eq__(self, other):
-        cdef GpuOperationalEventContextLegacyXid_v1 other_
-        if not isinstance(other, GpuOperationalEventContextLegacyXid_v1):
+        cdef EventSetGetGpuOperationalEventContextLegacyXid_v1 other_
+        if not isinstance(other, EventSetGetGpuOperationalEventContextLegacyXid_v1):
             return False
         other_ = other
-        return (_cyb_memcmp(<void *><intptr_t>(self._ptr), <void *><intptr_t>(other_._ptr), sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t)) == 0)
+        return (_cyb_memcmp(<void *><intptr_t>(self._ptr), <void *><intptr_t>(other_._ptr), sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t)) == 0)
 
     def __getbuffer__(self, _cyb_cpython.Py_buffer *buffer, int flags):
-        _cyb___getbuffer(self, buffer, <void *>self._ptr, sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t), self._readonly)
+        _cyb___getbuffer(self, buffer, <void *>self._ptr, sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t), self._readonly)
 
     def __releasebuffer__(self, Py_buffer *buffer):
         pass
 
     def __setitem__(self, key, val):
         if key == 0 and isinstance(val, _numpy.ndarray):
-            self._ptr = <nvmlGpuOperationalEventContextLegacyXid_v1_t *>_cyb_malloc(sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t))
+            self._ptr = <nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *>_cyb_malloc(sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t))
             if self._ptr == NULL:
-                raise MemoryError("Error allocating GpuOperationalEventContextLegacyXid_v1")
-            _cyb_memcpy(<void*>self._ptr, <void*><intptr_t>val.ctypes.data, sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t))
+                raise MemoryError("Error allocating EventSetGetGpuOperationalEventContextLegacyXid_v1")
+            _cyb_memcpy(<void*>self._ptr, <void*><intptr_t>val.ctypes.data, sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t))
             self._owner = None
             self._owned = True
             self._readonly = not val.flags.writeable
         else:
             setattr(self, key, val)
 
+    @property
+    def index(self):
+        """int: [in] Zero-based context index."""
+        return self._ptr[0].index
+
+    @index.setter
+    def index(self, val):
+        if self._readonly:
+            raise ValueError("This EventSetGetGpuOperationalEventContextLegacyXid_v1 instance is read-only")
+        self._ptr[0].index = val
+
     @property
     def xid_code(self):
-        """int: """
+        """int: [out] Legacy Xid code carried in a GPU Operational Event context."""
         return self._ptr[0].xidCode
 
     @xid_code.setter
     def xid_code(self, val):
         if self._readonly:
-            raise ValueError("This GpuOperationalEventContextLegacyXid_v1 instance is read-only")
+            raise ValueError("This EventSetGetGpuOperationalEventContextLegacyXid_v1 instance is read-only")
         self._ptr[0].xidCode = val
 
     @staticmethod
     def from_buffer(buffer):
-        """Create an GpuOperationalEventContextLegacyXid_v1 instance with the memory from the given buffer."""
-        return _cyb_from_buffer(buffer, sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t), GpuOperationalEventContextLegacyXid_v1)
+        """Create an EventSetGetGpuOperationalEventContextLegacyXid_v1 instance with the memory from the given buffer."""
+        return _cyb_from_buffer(buffer, sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t), EventSetGetGpuOperationalEventContextLegacyXid_v1)
 
     @staticmethod
     def from_data(data):
-        """Create an GpuOperationalEventContextLegacyXid_v1 instance wrapping the given NumPy array.
+        """Create an EventSetGetGpuOperationalEventContextLegacyXid_v1 instance wrapping the given NumPy array.
 
         Args:
-            data (_numpy.ndarray): a single-element array of dtype `gpu_operational_event_context_legacy_xid_v1_dtype` holding the data.
+            data (_numpy.ndarray): a single-element array of dtype `event_set_get_gpu_operational_event_context_legacy_xid_v1_dtype` holding the data.
         """
-        return _cyb_from_data(data, "gpu_operational_event_context_legacy_xid_v1_dtype", gpu_operational_event_context_legacy_xid_v1_dtype, GpuOperationalEventContextLegacyXid_v1)
+        return _cyb_from_data(data, "event_set_get_gpu_operational_event_context_legacy_xid_v1_dtype", event_set_get_gpu_operational_event_context_legacy_xid_v1_dtype, EventSetGetGpuOperationalEventContextLegacyXid_v1)
 
     @staticmethod
     def from_ptr(intptr_t ptr, bint readonly=False, object owner=None):
-        """Create an GpuOperationalEventContextLegacyXid_v1 instance wrapping the given pointer.
+        """Create an EventSetGetGpuOperationalEventContextLegacyXid_v1 instance wrapping the given pointer.
 
         Args:
             ptr (intptr_t): pointer address as Python :class:`int` to the data.
@@ -18705,16 +18860,16 @@ cdef class GpuOperationalEventContextLegacyXid_v1:
         """
         if ptr == 0:
             raise ValueError("ptr must not be null (0)")
-        cdef GpuOperationalEventContextLegacyXid_v1 obj = GpuOperationalEventContextLegacyXid_v1.__new__(GpuOperationalEventContextLegacyXid_v1)
+        cdef EventSetGetGpuOperationalEventContextLegacyXid_v1 obj = EventSetGetGpuOperationalEventContextLegacyXid_v1.__new__(EventSetGetGpuOperationalEventContextLegacyXid_v1)
         if owner is None:
-            obj._ptr = <nvmlGpuOperationalEventContextLegacyXid_v1_t *>_cyb_malloc(sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t))
+            obj._ptr = <nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *>_cyb_malloc(sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t))
             if obj._ptr == NULL:
-                raise MemoryError("Error allocating GpuOperationalEventContextLegacyXid_v1")
-            _cyb_memcpy(<void*>(obj._ptr), <void*>ptr, sizeof(nvmlGpuOperationalEventContextLegacyXid_v1_t))
+                raise MemoryError("Error allocating EventSetGetGpuOperationalEventContextLegacyXid_v1")
+            _cyb_memcpy(<void*>(obj._ptr), <void*>ptr, sizeof(nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t))
             obj._owner = None
             obj._owned = True
         else:
-            obj._ptr = <nvmlGpuOperationalEventContextLegacyXid_v1_t *>ptr
+            obj._ptr = <nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *>ptr
             obj._owner = owner
             obj._owned = False
         obj._readonly = readonly
@@ -19023,12 +19178,14 @@ cdef class GpuOperationalEventConfig_v1:
         return obj
 
 
-cdef _get_event_data_v2_dtype_offsets():
-    cdef nvmlEventData_v2_t pod
+cdef _get_event_set_wait_v3_dtype_offsets():
+    cdef nvmlEventSetWait_v3_t pod
     return _numpy.dtype({
-        'names': ['uuid', 'source_module', 'event_type', 'event_data', 'group_cursor', 'instance_id', 'timestamp_usec', 'trace_id', 'data_type', 'gpu_instance_id', 'compute_instance_id', 'severity', 'category_id', 'module_event_code', 'scope', 'originator', 'module_instance', 'chiplet_id', 'log_level', 'attributes', 'group_cper_size', 'group_attributes', 'group_size', 'group_index'],
-        'formats': [(_numpy.int8, 96), (_numpy.int8, 16), _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint8, _numpy.uint8],
+        'names': ['timeout_ms', 'data_type', 'uuid', 'source_module', 'event_type', 'event_data', 'group_cursor', 'instance_id', 'timestamp_usec', 'trace_id', 'gpu_instance_id', 'compute_instance_id', 'severity', 'category_id', 'module_event_code', 'scope', 'originator', 'module_instance', 'chiplet_id', 'log_level', 'attributes', 'group_cper_size', 'group_attributes', 'group_size', 'group_index'],
+        'formats': [_numpy.uint32, _numpy.uint32, (_numpy.int8, 96), (_numpy.int8, 16), _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint64, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint32, _numpy.uint8, _numpy.uint8],
         'offsets': [
+            (<intptr_t>&(pod.timeoutMs)) - (<intptr_t>&pod),
+            (<intptr_t>&(pod.dataType)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.uuid)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.sourceModule)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.eventType)) - (<intptr_t>&pod),
@@ -19037,7 +19194,6 @@ cdef _get_event_data_v2_dtype_offsets():
             (<intptr_t>&(pod.instanceId)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.timestampUsec)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.traceId)) - (<intptr_t>&pod),
-            (<intptr_t>&(pod.dataType)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.gpuInstanceId)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.computeInstanceId)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.severity)) - (<intptr_t>&pod),
@@ -19054,40 +19210,40 @@ cdef _get_event_data_v2_dtype_offsets():
             (<intptr_t>&(pod.groupSize)) - (<intptr_t>&pod),
             (<intptr_t>&(pod.groupIndex)) - (<intptr_t>&pod),
         ],
-        'itemsize': sizeof(nvmlEventData_v2_t),
+        'itemsize': sizeof(nvmlEventSetWait_v3_t),
     })
 
-event_data_v2_dtype = _get_event_data_v2_dtype_offsets()
+event_set_wait_v3_dtype = _get_event_set_wait_v3_dtype_offsets()
 
-cdef class EventData_v2:
-    """Empty-initialize an instance of `nvmlEventData_v2_t`.
+cdef class EventSetWait_v3:
+    """Empty-initialize an instance of `nvmlEventSetWait_v3_t`.
 
 
-    .. seealso:: `nvmlEventData_v2_t`
+    .. seealso:: `nvmlEventSetWait_v3_t`
     """
     cdef:
-        nvmlEventData_v2_t *_ptr
+        nvmlEventSetWait_v3_t *_ptr
         object _owner
         bint _owned
         bint _readonly
 
     def __init__(self):
-        self._ptr = <nvmlEventData_v2_t *>_cyb_calloc(1, sizeof(nvmlEventData_v2_t))
+        self._ptr = <nvmlEventSetWait_v3_t *>_cyb_calloc(1, sizeof(nvmlEventSetWait_v3_t))
         if self._ptr == NULL:
-            raise MemoryError("Error allocating EventData_v2")
+            raise MemoryError("Error allocating EventSetWait_v3")
         self._owner = None
         self._owned = True
         self._readonly = False
 
     def __dealloc__(self):
-        cdef nvmlEventData_v2_t *ptr
+        cdef nvmlEventSetWait_v3_t *ptr
         if self._owned and self._ptr != NULL:
             ptr = self._ptr
             self._ptr = NULL
             _cyb_free(ptr)
 
     def __repr__(self):
-        return f"<{__name__}.EventData_v2 object at {hex(id(self))}>"
+        return f"<{__name__}.EventSetWait_v3 object at {hex(id(self))}>"
 
     @property
     def ptr(self):
@@ -19101,39 +19257,61 @@ cdef class EventData_v2:
         return <intptr_t>(self._ptr)
 
     def __eq__(self, other):
-        cdef EventData_v2 other_
-        if not isinstance(other, EventData_v2):
+        cdef EventSetWait_v3 other_
+        if not isinstance(other, EventSetWait_v3):
             return False
         other_ = other
-        return (_cyb_memcmp(<void *><intptr_t>(self._ptr), <void *><intptr_t>(other_._ptr), sizeof(nvmlEventData_v2_t)) == 0)
+        return (_cyb_memcmp(<void *><intptr_t>(self._ptr), <void *><intptr_t>(other_._ptr), sizeof(nvmlEventSetWait_v3_t)) == 0)
 
     def __getbuffer__(self, _cyb_cpython.Py_buffer *buffer, int flags):
-        _cyb___getbuffer(self, buffer, <void *>self._ptr, sizeof(nvmlEventData_v2_t), self._readonly)
+        _cyb___getbuffer(self, buffer, <void *>self._ptr, sizeof(nvmlEventSetWait_v3_t), self._readonly)
 
     def __releasebuffer__(self, Py_buffer *buffer):
         pass
 
     def __setitem__(self, key, val):
         if key == 0 and isinstance(val, _numpy.ndarray):
-            self._ptr = <nvmlEventData_v2_t *>_cyb_malloc(sizeof(nvmlEventData_v2_t))
+            self._ptr = <nvmlEventSetWait_v3_t *>_cyb_malloc(sizeof(nvmlEventSetWait_v3_t))
             if self._ptr == NULL:
-                raise MemoryError("Error allocating EventData_v2")
-            _cyb_memcpy(<void*>self._ptr, <void*><intptr_t>val.ctypes.data, sizeof(nvmlEventData_v2_t))
+                raise MemoryError("Error allocating EventSetWait_v3")
+            _cyb_memcpy(<void*>self._ptr, <void*><intptr_t>val.ctypes.data, sizeof(nvmlEventSetWait_v3_t))
             self._owner = None
             self._owned = True
             self._readonly = not val.flags.writeable
         else:
             setattr(self, key, val)
 
+    @property
+    def timeout_ms(self):
+        """int: [in] Maximum amount of time to wait, in milliseconds."""
+        return self._ptr[0].timeoutMs
+
+    @timeout_ms.setter
+    def timeout_ms(self, val):
+        if self._readonly:
+            raise ValueError("This EventSetWait_v3 instance is read-only")
+        self._ptr[0].timeoutMs = val
+
+    @property
+    def data_type(self):
+        """int: [out] `nvmlEventDataType_t` value indicating which event-data format is populated."""
+        return self._ptr[0].dataType
+
+    @data_type.setter
+    def data_type(self, val):
+        if self._readonly:
+            raise ValueError("This EventSetWait_v3 instance is read-only")
+        self._ptr[0].dataType = val
+
     @property
     def uuid(self):
-        """~_numpy.int8: (array of length 96)."""
+        """~_numpy.int8: (array of length 96).[out] UUID for the GPU where the event occurred. Empty if unavailable."""
         return _cyb_cpython.PyUnicode_FromString(self._ptr[0].uuid)
 
     @uuid.setter
     def uuid(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         cdef bytes buf = val.encode()
         if len(buf) >= 96:
             raise ValueError("String too long for field uuid, max length is 95")
@@ -19142,13 +19320,13 @@ cdef class EventData_v2:
 
     @property
     def source_module(self):
-        """~_numpy.int8: (array of length 16)."""
+        """~_numpy.int8: (array of length 16).[out] Source module signature for structured events. Not guaranteed to be NULL-terminated. Empty for NVML event-bit events."""
         return _cyb_cpython.PyUnicode_FromString(self._ptr[0].sourceModule)
 
     @source_module.setter
     def source_module(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         cdef bytes buf = val.encode()
         if len(buf) >= 16:
             raise ValueError("String too long for field source_module, max length is 15")
@@ -19157,263 +19335,252 @@ cdef class EventData_v2:
 
     @property
     def event_type(self):
-        """int: """
+        """int: [out] NVML event bit for `NVML_EVENT_DATA_TYPE_NVML_EVENT` events; `nvmlEventTypeNone` for structured events."""
         return self._ptr[0].eventType
 
     @event_type.setter
     def event_type(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].eventType = val
 
     @property
     def event_data(self):
-        """int: """
+        """int: [out] Xid code for `nvmlEventTypeXidCriticalError`, or 0 when not applicable."""
         return self._ptr[0].eventData
 
     @event_data.setter
     def event_data(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].eventData = val
 
     @property
     def group_cursor(self):
-        """int: """
+        """int: [out] Structured event group identifier. 0 for NVML event-bit events."""
         return self._ptr[0].groupCursor
 
     @group_cursor.setter
     def group_cursor(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].groupCursor = val
 
     @property
     def instance_id(self):
-        """int: """
+        """int: [out] Structured event sequence identifier. 0 for NVML event-bit events."""
         return self._ptr[0].instanceId
 
     @instance_id.setter
     def instance_id(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].instanceId = val
 
     @property
     def timestamp_usec(self):
-        """int: """
+        """int: [out] Event timestamp in microseconds. 0 if unavailable."""
         return self._ptr[0].timestampUsec
 
     @timestamp_usec.setter
     def timestamp_usec(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].timestampUsec = val
 
     @property
     def trace_id(self):
-        """int: """
+        """int: [out] Structured event trace identifier. 0 for NVML event-bit events."""
         return self._ptr[0].traceId
 
     @trace_id.setter
     def trace_id(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].traceId = val
 
-    @property
-    def data_type(self):
-        """int: """
-        return self._ptr[0].dataType
-
-    @data_type.setter
-    def data_type(self, val):
-        if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
-        self._ptr[0].dataType = val
-
     @property
     def gpu_instance_id(self):
-        """int: """
+        """int: [out] MIG GPU instance ID for NVML event-bit data, or `NVML_GPU_INSTANCE_ID_ANY` when not applicable."""
         return self._ptr[0].gpuInstanceId
 
     @gpu_instance_id.setter
     def gpu_instance_id(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].gpuInstanceId = val
 
     @property
     def compute_instance_id(self):
-        """int: """
+        """int: [out] MIG compute instance ID for NVML event-bit data, or `NVML_COMPUTE_INSTANCE_ID_ANY` when not applicable."""
         return self._ptr[0].computeInstanceId
 
     @compute_instance_id.setter
     def compute_instance_id(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].computeInstanceId = val
 
     @property
     def severity(self):
-        """int: """
+        """int: [out] `nvmlOperationalEventSeverity_t` value for structured events. May contain newer severity values not named in this header. `NVML_OPERATIONAL_EVENT_SEVERITY_ALL` for NVML event-bit events."""
         return self._ptr[0].severity
 
     @severity.setter
     def severity(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].severity = val
 
     @property
     def category_id(self):
-        """int: """
+        """int: [out] Source-defined structured event category identifier. 0 for NVML event-bit events."""
         return self._ptr[0].categoryId
 
     @category_id.setter
     def category_id(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].categoryId = val
 
     @property
     def module_event_code(self):
-        """int: """
+        """int: [out] Source-module-defined event code. Interpret with `sourceModule`. 0 for NVML event-bit events."""
         return self._ptr[0].moduleEventCode
 
     @module_event_code.setter
     def module_event_code(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].moduleEventCode = val
 
     @property
     def scope(self):
-        """int: """
+        """int: [out] Structured event scope identifier. 0 for NVML event-bit events."""
         return self._ptr[0].scope
 
     @scope.setter
     def scope(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].scope = val
 
     @property
     def originator(self):
-        """int: """
+        """int: [out] Structured event originator identifier. 0 for NVML event-bit events."""
         return self._ptr[0].originator
 
     @originator.setter
     def originator(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].originator = val
 
     @property
     def module_instance(self):
-        """int: """
+        """int: [out] Structured event module instance identifier. 0 for NVML event-bit events."""
         return self._ptr[0].moduleInstance
 
     @module_instance.setter
     def module_instance(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].moduleInstance = val
 
     @property
     def chiplet_id(self):
-        """int: """
+        """int: [out] Structured event chiplet identifier. 0 for NVML event-bit events."""
         return self._ptr[0].chipletId
 
     @chiplet_id.setter
     def chiplet_id(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].chipletId = val
 
     @property
     def log_level(self):
-        """int: """
+        """int: [out] `nvmlGpuOperationalEventLogLevel_t` value for structured GPU Operational Events. May contain newer log-level values not named in this header. `NVML_GPU_OPERATIONAL_EVENT_LOG_LEVEL_ALL` for NVML event-bit events."""
         return self._ptr[0].logLevel
 
     @log_level.setter
     def log_level(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].logLevel = val
 
     @property
     def attributes(self):
-        """int: """
+        """int: [out] Bitmask of `NVML_OPERATIONAL_EVENT_ATTR_*` values for structured events. May contain newer bits not named in this header. 0 for NVML event-bit events. May include `NVML_OPERATIONAL_EVENT_ATTR_OVERFLOW` if events or associated payloads were dropped."""
         return self._ptr[0].attributes
 
     @attributes.setter
     def attributes(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].attributes = val
 
     @property
     def group_cper_size(self):
-        """int: """
+        """int: [out] Associated CPER record size in bytes. 0 when unavailable."""
         return self._ptr[0].groupCperSize
 
     @group_cper_size.setter
     def group_cper_size(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].groupCperSize = val
 
     @property
     def group_attributes(self):
-        """int: """
+        """int: [out] Bitmask of `NVML_OPERATIONAL_EVENT_GROUP_ATTR_*` values for structured events. May contain newer bits not named in this header. 0 for NVML event-bit events."""
         return self._ptr[0].groupAttributes
 
     @group_attributes.setter
     def group_attributes(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].groupAttributes = val
 
     @property
     def group_size(self):
-        """int: """
+        """int: [out] Total number of events in the structured event group. 0 for NVML event-bit events."""
         return self._ptr[0].groupSize
 
     @group_size.setter
     def group_size(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].groupSize = val
 
     @property
     def group_index(self):
-        """int: """
+        """int: [out] Zero-based index within the structured event group. 0 for NVML event-bit events."""
         return self._ptr[0].groupIndex
 
     @group_index.setter
     def group_index(self, val):
         if self._readonly:
-            raise ValueError("This EventData_v2 instance is read-only")
+            raise ValueError("This EventSetWait_v3 instance is read-only")
         self._ptr[0].groupIndex = val
 
     @staticmethod
     def from_buffer(buffer):
-        """Create an EventData_v2 instance with the memory from the given buffer."""
-        return _cyb_from_buffer(buffer, sizeof(nvmlEventData_v2_t), EventData_v2)
+        """Create an EventSetWait_v3 instance with the memory from the given buffer."""
+        return _cyb_from_buffer(buffer, sizeof(nvmlEventSetWait_v3_t), EventSetWait_v3)
 
     @staticmethod
     def from_data(data):
-        """Create an EventData_v2 instance wrapping the given NumPy array.
+        """Create an EventSetWait_v3 instance wrapping the given NumPy array.
 
         Args:
-            data (_numpy.ndarray): a single-element array of dtype `event_data_v2_dtype` holding the data.
+            data (_numpy.ndarray): a single-element array of dtype `event_set_wait_v3_dtype` holding the data.
         """
-        return _cyb_from_data(data, "event_data_v2_dtype", event_data_v2_dtype, EventData_v2)
+        return _cyb_from_data(data, "event_set_wait_v3_dtype", event_set_wait_v3_dtype, EventSetWait_v3)
 
     @staticmethod
     def from_ptr(intptr_t ptr, bint readonly=False, object owner=None):
-        """Create an EventData_v2 instance wrapping the given pointer.
+        """Create an EventSetWait_v3 instance wrapping the given pointer.
 
         Args:
             ptr (intptr_t): pointer address as Python :class:`int` to the data.
@@ -19422,16 +19589,16 @@ cdef class EventData_v2:
         """
         if ptr == 0:
             raise ValueError("ptr must not be null (0)")
-        cdef EventData_v2 obj = EventData_v2.__new__(EventData_v2)
+        cdef EventSetWait_v3 obj = EventSetWait_v3.__new__(EventSetWait_v3)
         if owner is None:
-            obj._ptr = <nvmlEventData_v2_t *>_cyb_malloc(sizeof(nvmlEventData_v2_t))
+            obj._ptr = <nvmlEventSetWait_v3_t *>_cyb_malloc(sizeof(nvmlEventSetWait_v3_t))
             if obj._ptr == NULL:
-                raise MemoryError("Error allocating EventData_v2")
-            _cyb_memcpy(<void*>(obj._ptr), <void*>ptr, sizeof(nvmlEventData_v2_t))
+                raise MemoryError("Error allocating EventSetWait_v3")
+            _cyb_memcpy(<void*>(obj._ptr), <void*>ptr, sizeof(nvmlEventSetWait_v3_t))
             obj._owner = None
             obj._owned = True
         else:
-            obj._ptr = <nvmlEventData_v2_t *>ptr
+            obj._ptr = <nvmlEventSetWait_v3_t *>ptr
             obj._owner = owner
             obj._owned = False
         obj._readonly = readonly
@@ -33833,29 +34000,7 @@ cpdef event_set_register_gpu_operational_events_v1(intptr_t event_set, intptr_t
     check_status(__status__)
 
 
-cpdef object event_set_wait_v3(intptr_t set, unsigned int timeoutms):
-    """Waits on an event set and returns the next event in the extended event format.
-
-    Args:
-        set (intptr_t): Reference to set of events to wait on.
-        timeoutms (unsigned int): Maximum amount of wait time in
-            milliseconds for registered event.
-
-    Returns:
-        nvmlEventData_v2_t: Reference in which to return extended
-            event data.
-
-    .. seealso:: `nvmlEventSetWait_v3`
-    """
-    cdef EventData_v2 data_py = EventData_v2()
-    cdef nvmlEventData_v2_t *data = <nvmlEventData_v2_t *><intptr_t>(data_py._get_ptr())
-    with nogil:
-        __status__ = nvmlEventSetWait_v3(<EventSet>set, data, timeoutms)
-    check_status(__status__)
-    return data_py
-
-
-cpdef unsigned int event_set_get_context_count_v1(intptr_t set) except? 0:
+cpdef object event_set_get_context_count_v1(intptr_t set):
     """Gets the number of context records for the most recent event returned by ``nvmlEventSetWait_v3`` on this event set.
 
     Args:
@@ -33863,60 +34008,17 @@ cpdef unsigned int event_set_get_context_count_v1(intptr_t set) except? 0:
             ``nvmlEventSetWait_v3``.
 
     Returns:
-        unsigned int: Reference in which to return the number of
-            context records.
+        nvmlEventSetGetContextCount_v1_t: Parameters in which to
+            return the number of context records.
 
     .. seealso:: `nvmlEventSetGetContextCount_v1`
     """
-    cdef unsigned int count
+    cdef EventSetGetContextCount_v1 params_py = EventSetGetContextCount_v1()
+    cdef nvmlEventSetGetContextCount_v1_t *params = <nvmlEventSetGetContextCount_v1_t *><intptr_t>(params_py._get_ptr())
     with nogil:
-        __status__ = nvmlEventSetGetContextCount_v1(<EventSet>set, &count)
+        __status__ = nvmlEventSetGetContextCount_v1(<EventSet>set, params)
     check_status(__status__)
-    return count
-
-
-cpdef object event_set_get_context_info_v1(intptr_t set, unsigned int index):
-    """Gets metadata for a context record from the most recent event returned by ``nvmlEventSetWait_v3``.
-
-    Args:
-        set (intptr_t): Event set previously used with
-            ``nvmlEventSetWait_v3``.
-        index (unsigned int): Zero-based context index.
-
-    Returns:
-        nvmlOperationalEventContextInfo_v1_t: Reference in which to
-            return context metadata.
-
-    .. seealso:: `nvmlEventSetGetContextInfo_v1`
-    """
-    cdef OperationalEventContextInfo_v1 info_py = OperationalEventContextInfo_v1()
-    cdef nvmlOperationalEventContextInfo_v1_t *info = <nvmlOperationalEventContextInfo_v1_t *><intptr_t>(info_py._get_ptr())
-    with nogil:
-        __status__ = nvmlEventSetGetContextInfo_v1(<EventSet>set, index, info)
-    check_status(__status__)
-    return info_py
-
-
-cpdef object event_set_get_gpu_operational_event_context_legacy_xid_v1(intptr_t set, unsigned int index):
-    """Gets decoded GPU legacy-Xid context data for a context record from the most recent event returned by ``nvmlEventSetWait_v3``.
-
-    Args:
-        set (intptr_t): Event set previously used with
-            ``nvmlEventSetWait_v3``.
-        index (unsigned int): Zero-based context index.
-
-    Returns:
-        nvmlGpuOperationalEventContextLegacyXid_v1_t: Reference in
-            which to return legacy-Xid context data.
-
-    .. seealso:: `nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1`
-    """
-    cdef GpuOperationalEventContextLegacyXid_v1 xid_py = GpuOperationalEventContextLegacyXid_v1()
-    cdef nvmlGpuOperationalEventContextLegacyXid_v1_t *xid = <nvmlGpuOperationalEventContextLegacyXid_v1_t *><intptr_t>(xid_py._get_ptr())
-    with nogil:
-        __status__ = nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(<EventSet>set, index, xid)
-    check_status(__status__)
-    return xid_py
+    return params_py
 
 
 cpdef object device_get_bank_remapper_status_v1(intptr_t device):
@@ -34278,7 +34380,7 @@ cpdef object device_get_field_values(intptr_t device, values):
         __status__ = nvmlDeviceGetFieldValues(<Device>device, valuesCount, ptr)
     check_status(__status__)
 
-    values_._data.resize((valuesCount,))
+    values_._data = values_._data[:valuesCount]
     return values_
 
 
@@ -34922,7 +35024,7 @@ cpdef object system_event_set_wait(intptr_t event_set, unsigned int timeout_ms,
         request[0].dataSize = buffer_size
         __status__ = nvmlSystemEventSetWait(<nvmlSystemEventSetWaitRequest_t*>request)
     check_status(__status__)
-    event_data._data.resize((request[0].numEvent,))
+    event_data._data = event_data._data[:request[0].numEvent]
     return event_data
 
 
@@ -35622,6 +35724,84 @@ cpdef str vgpu_type_get_name(unsigned int vgpu_type_id):
     return cpython.PyUnicode_FromStringAndSize(vgpu_type_name, size[0])
 
 
+cpdef object event_set_wait_v3(intptr_t set, unsigned int timeout_ms):
+    """Wait for events of the specified type to occur for any device in the set,
+    returning a structured event record.
+
+    For Turing™ or newer fully supported devices.
+
+    For Linux only.
+
+    Args:
+        set (EventSet): Handle to the event set.
+        timeout_ms (unsigned int): Maximum time to wait, in milliseconds.
+
+    Returns:
+        EventSetWait_v3: Structured event data record.
+
+    .. seealso:: `nvmlEventSetWait_v3`
+    """
+    cdef EventSetWait_v3 params = EventSetWait_v3()
+    cdef nvmlEventSetWait_v3_t *ptr = <nvmlEventSetWait_v3_t *>params._get_ptr()
+    ptr.timeoutMs = timeout_ms
+    with nogil:
+        __status__ = nvmlEventSetWait_v3(<EventSet>set, ptr)
+    check_status(__status__)
+    return params
+
+
+cpdef object event_set_get_context_info_v1(intptr_t set, unsigned int index):
+    """Retrieve context metadata for a context record from the most recent event
+    returned by :func:`event_set_wait_v3`.
+
+    For Turing™ or newer fully supported devices.
+
+    For Linux only.
+
+    Args:
+        set (EventSet): Handle to the event set.
+        index (unsigned int): Zero-based index of the context record.
+
+    Returns:
+        EventSetGetContextInfo_v1: Context metadata record.
+
+    .. seealso:: `nvmlEventSetGetContextInfo_v1`
+    """
+    cdef EventSetGetContextInfo_v1 params = EventSetGetContextInfo_v1()
+    cdef nvmlEventSetGetContextInfo_v1_t *ptr = <nvmlEventSetGetContextInfo_v1_t *>params._get_ptr()
+    ptr.index = index
+    with nogil:
+        __status__ = nvmlEventSetGetContextInfo_v1(<EventSet>set, ptr)
+    check_status(__status__)
+    return params
+
+
+cpdef object event_set_get_gpu_operational_event_context_legacy_xid_v1(intptr_t set, unsigned int index):
+    """Retrieve the decoded legacy-Xid context data for a context record from the
+    most recent event returned by :func:`event_set_wait_v3`.
+
+    For Turing™ or newer fully supported devices.
+
+    For Linux only.
+
+    Args:
+        set (EventSet): Handle to the event set.
+        index (unsigned int): Zero-based index of the context record.
+
+    Returns:
+        EventSetGetGpuOperationalEventContextLegacyXid_v1: Decoded Xid context record.
+
+    .. seealso:: `nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1`
+    """
+    cdef EventSetGetGpuOperationalEventContextLegacyXid_v1 params = EventSetGetGpuOperationalEventContextLegacyXid_v1()
+    cdef nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *ptr = <nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1_t *>params._get_ptr()
+    ptr.index = index
+    with nogil:
+        __status__ = nvmlEventSetGetGpuOperationalEventContextLegacyXid_v1(<EventSet>set, ptr)
+    check_status(__status__)
+    return params
+
+
 cpdef bytes event_set_get_context_data_v1(intptr_t set, unsigned int index):
     """Copies the raw payload for a context record from the most recent event returned by
     :func:`event_set_wait_v3`.
@@ -35639,14 +35819,17 @@ cpdef bytes event_set_get_context_data_v1(intptr_t set, unsigned int index):
 
     .. seealso:: `nvmlEventSetGetContextData_v1`
     """
-    cdef unsigned int data_size
+    cdef nvmlEventSetGetContextData_v1_t params
+    params.index = index
+    params.data = NULL
+    params.dataSize = 0
     with nogil:
-        __status__ = nvmlEventSetGetContextData_v1(<EventSet>set, index, NULL, &data_size)
+        __status__ = nvmlEventSetGetContextData_v1(<EventSet>set, &params)
     check_status_size(__status__)
-    cdef bytes data = bytes(data_size)
-    cdef void *_data_ = <char*>data
+    cdef bytes data = bytes(params.dataSize)
+    params.data = <char*>data
     with nogil:
-        __status__ = nvmlEventSetGetContextData_v1(<EventSet>set, index, _data_, &data_size)
+        __status__ = nvmlEventSetGetContextData_v1(<EventSet>set, &params)
     check_status(__status__)
     return data
 del _cyb_FastEnum
diff --git a/cuda_bindings/cuda/bindings/nvrtc.pxd b/cuda_bindings/cuda/bindings/nvrtc.pxd
index 6e72b78f0d3..2e7ca2b505a 100644
--- a/cuda_bindings/cuda/bindings/nvrtc.pxd
+++ b/cuda_bindings/cuda/bindings/nvrtc.pxd
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated with version 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=315bc7e377beef4b6e7e6dbb58c18dd44c06655387f58ccdfacd96a4fa464c60
+# This code was automatically generated with version 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=ba23f6c3908c2fa6496002f8def30ec166cec8643e4de22c1741040b2c4b2965
 cimport cuda.bindings.cynvrtc as cynvrtc
 
 include "_lib/utils.pxd"
@@ -22,69 +21,35 @@ cdef class nvrtcProgram:
     cdef cynvrtc.nvrtcProgram  _pvt_val
     cdef cynvrtc.nvrtcProgram* _pvt_ptr
 
-cdef class anon_struct0:
+cdef class nvrtcBundledHeadersInfo:
     """
-    Attributes
-    ----------
-
-    available : int
-
-
-
-    compressedSize : size_t
-
-
-
-    uncompressedSize : size_t
-
-
-
-    cudaVersionMajor : int
-
-
-
-    cudaVersionMinor : int
-
+    Structure containing information about bundled headers.
 
-
-    numFiles : unsigned int
-
-
-
-    Methods
-    -------
-    getPtr()
-        Get memory address of class instance
-    """
-    cdef cynvrtc.nvrtcBundledHeadersInfo* _pvt_ptr
-
-cdef class nvrtcBundledHeadersInfo(anon_struct0):
-    """
     Attributes
     ----------
 
     available : int
-
+        Non-zero if bundled headers are available
 
 
     compressedSize : size_t
-
+        Size of compressed archive in bytes
 
 
     uncompressedSize : size_t
-
+        Estimated size when extracted in bytes
 
 
     cudaVersionMajor : int
-
+        CUDA major version of bundled headers
 
 
     cudaVersionMinor : int
-
+        CUDA minor version of bundled headers
 
 
     numFiles : unsigned int
-
+        Number of header files in the bundle
 
 
     Methods
@@ -93,3 +58,4 @@ cdef class nvrtcBundledHeadersInfo(anon_struct0):
         Get memory address of class instance
     """
     cdef cynvrtc.nvrtcBundledHeadersInfo _pvt_val
+    cdef cynvrtc.nvrtcBundledHeadersInfo* _pvt_ptr
diff --git a/cuda_bindings/cuda/bindings/nvrtc.pyx b/cuda_bindings/cuda/bindings/nvrtc.pyx
index b4b4d713579..a44c48b935d 100644
--- a/cuda_bindings/cuda/bindings/nvrtc.pyx
+++ b/cuda_bindings/cuda/bindings/nvrtc.pyx
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated with version 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=9dcd9e24a5962a3fa156378497290ef95c84fb433d2c31c6e2a5da5528391fe8
+# This code was automatically generated with version 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=014131536ed098f8c76a069b25d8ff44edd3f2554ae23b127e1b686ae2d6a69d
 from typing import Any, Optional
 import cython
 import ctypes
@@ -45,8 +44,10 @@ ctypedef unsigned long long float_ptr
 ctypedef unsigned long long double_ptr
 ctypedef unsigned long long void_ptr
 
-#: Flags for nvrtcInstallBundledHeaders.Skip installation if version marker
-#: exists and version matches. This is the default behavior when flags=0.
+#: Flags for nvrtcInstallBundledHeaders.
+#:
+#: Skip installation if version marker exists and version matches. This is
+#: the default behavior when flags=0.
 NVRTC_INSTALL_HEADERS_SKIP_IF_EXISTS = cynvrtc.NVRTC_INSTALL_HEADERS_SKIP_IF_EXISTS
 
 #: Clear existing directory contents before installation. Guarantees
@@ -140,33 +141,35 @@ cdef class nvrtcProgram:
     def getPtr(self):
         return <void_ptr>self._pvt_ptr
 
-cdef class anon_struct0:
+cdef class nvrtcBundledHeadersInfo:
     """
+    Structure containing information about bundled headers.
+
     Attributes
     ----------
 
     available : int
-
+        Non-zero if bundled headers are available
 
 
     compressedSize : size_t
-
+        Size of compressed archive in bytes
 
 
     uncompressedSize : size_t
-
+        Estimated size when extracted in bytes
 
 
     cudaVersionMajor : int
-
+        CUDA major version of bundled headers
 
 
     cudaVersionMinor : int
-
+        CUDA minor version of bundled headers
 
 
     numFiles : unsigned int
-
+        Number of header files in the bundle
 
 
     Methods
@@ -174,10 +177,12 @@ cdef class anon_struct0:
     getPtr()
         Get memory address of class instance
     """
-    def __cinit__(self, void_ptr _ptr):
-        self._pvt_ptr = <cynvrtc.nvrtcBundledHeadersInfo *>_ptr
-
-    def __init__(self, void_ptr _ptr):
+    def __cinit__(self, void_ptr _ptr = 0):
+        if _ptr == 0:
+            self._pvt_ptr = &self._pvt_val
+        else:
+            self._pvt_ptr = <cynvrtc.nvrtcBundledHeadersInfo *>_ptr
+    def __init__(self, void_ptr _ptr = 0):
         pass
     def __dealloc__(self):
         pass
@@ -274,49 +279,6 @@ cdef class anon_struct0:
         self._pvt_ptr[0].numFiles = numFiles
 
 
-cdef class nvrtcBundledHeadersInfo(anon_struct0):
-    """
-    Attributes
-    ----------
-
-    available : int
-
-
-
-    compressedSize : size_t
-
-
-
-    uncompressedSize : size_t
-
-
-
-    cudaVersionMajor : int
-
-
-
-    cudaVersionMinor : int
-
-
-
-    numFiles : unsigned int
-
-
-
-    Methods
-    -------
-    getPtr()
-        Get memory address of class instance
-    """
-    def __cinit__(self, void_ptr _ptr = 0):
-        if _ptr == 0:
-            self._pvt_ptr = <cynvrtc.nvrtcBundledHeadersInfo *>&self._pvt_val
-        else:
-            self._pvt_ptr = <cynvrtc.nvrtcBundledHeadersInfo *>_ptr
-
-    def __init__(self, void_ptr _ptr = 0):
-        pass
-
 @cython.embedsignature(True)
 def nvrtcGetErrorString(result not None : nvrtcResult):
     """ nvrtcGetErrorString is a helper function that returns a string describing the given :py:obj:`~.nvrtcResult` code, e.g., NVRTC_SUCCESS to `"NVRTC_SUCCESS"`. For unrecognized enumeration values, it returns `"NVRTC_ERROR unknown"`.
diff --git a/cuda_bindings/cuda/bindings/nvvm.pxd b/cuda_bindings/cuda/bindings/nvvm.pxd
index 6e96ef7c920..9e78ece8069 100644
--- a/cuda_bindings/cuda/bindings/nvvm.pxd
+++ b/cuda_bindings/cuda/bindings/nvvm.pxd
@@ -2,12 +2,18 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=ee88a87ab53668207e31e3b38c1593a3cd3724e02300ebea7574aafb509bb3b6
+
+
+
+# <<<< PREAMBLE CONTENT >>>>
 
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=64399bc158dff1d573ee582b859de69945c0aa7daca57980ad1372b441bd0fbd
 from libc.stdint cimport intptr_t
 
+
+# <<<< END OF PREAMBLE CONTENT >>>>
+
 from .cynvvm cimport *
 
 
diff --git a/cuda_bindings/cuda/bindings/nvvm.pyx b/cuda_bindings/cuda/bindings/nvvm.pyx
index fecc9c36856..cff0b446a52 100644
--- a/cuda_bindings/cuda/bindings/nvvm.pyx
+++ b/cuda_bindings/cuda/bindings/nvvm.pyx
@@ -2,21 +2,52 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 #
-# This code was automatically generated across versions from 12.0.1 to 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=c4c368f2adb8e24c25c067370ec9263cbd656df971795916276cdd859d339743
+# This code was automatically generated across versions from 12.0.1 to 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=37902d13a165dba391225d644f9ee67747150ede2f719ea5e0870618f6db50ec
 
 
 # <<<< PREAMBLE CONTENT >>>>
 
+cimport cpython as _cyb_cpython
+from libc.stdint cimport intptr_t
+
 from cuda.bindings._internal._fast_enum import FastEnum as _cyb_FastEnum
 
+cdef intptr_t _cyb_get_buffer_pointer(buf, Py_ssize_t size, readonly=True) except?-1:
+    cdef intptr_t ptr
+    cdef int flags = _cyb_cpython.PyBUF_ANY_CONTIGUOUS
+    if not readonly:
+        flags |= _cyb_cpython.PyBUF_WRITABLE
+    cdef int status = -1
+    cdef _cyb_cpython.Py_buffer view
+    if isinstance(buf, int):
+        ptr = <intptr_t>buf
+    else:
+        try:
+            status = _cyb_cpython.PyObject_GetBuffer(buf, &view, flags)
+            if size != -1:
+                assert view.len == size
+            assert view.ndim == 1
+        except Exception as e:
+            adj = "writable " if not readonly else ""
+            raise ValueError(
+                "buf must be either a Python int representing the pointer "
+                f"address to a valid buffer, or a 1D contiguous {adj}"
+                f"buffer, of size {size}"
+            ) from e
+        else:
+            ptr = <intptr_t>view.buf
+        finally:
+            if status == 0:
+                _cyb_cpython.PyBuffer_Release(&view)
+    return ptr
+
 
 # <<<< END OF PREAMBLE CONTENT >>>>
 
 cimport cython  # NOQA
 
-from ._internal.utils cimport (get_buffer_pointer, get_nested_resource_ptr,
+from ._internal.utils cimport (get_nested_resource_ptr,
                                nested_resource)
 
 
@@ -171,7 +202,7 @@ cpdef add_module_to_program(intptr_t prog, buffer, size_t size, name):
 
     .. seealso:: `nvvmAddModuleToProgram`
     """
-    cdef void* _buffer_ = get_buffer_pointer(buffer, size, readonly=True)
+    cdef void* _buffer_ = <void *>_cyb_get_buffer_pointer(buffer, size, readonly=True)
     if not isinstance(name, str):
         raise TypeError("name must be a Python str")
     cdef bytes _temp_name_ = (<str>name).encode()
@@ -193,7 +224,7 @@ cpdef lazy_add_module_to_program(intptr_t prog, buffer, size_t size, name):
 
     .. seealso:: `nvvmLazyAddModuleToProgram`
     """
-    cdef void* _buffer_ = get_buffer_pointer(buffer, size, readonly=True)
+    cdef void* _buffer_ = <void *>_cyb_get_buffer_pointer(buffer, size, readonly=True)
     if not isinstance(name, str):
         raise TypeError("name must be a Python str")
     cdef bytes _temp_name_ = (<str>name).encode()
@@ -279,7 +310,7 @@ cpdef get_compiled_result(intptr_t prog, buffer):
 
     .. seealso:: `nvvmGetCompiledResult`
     """
-    cdef void* _buffer_ = get_buffer_pointer(buffer, -1, readonly=False)
+    cdef void* _buffer_ = <void *>_cyb_get_buffer_pointer(buffer, -1, readonly=False)
     with nogil:
         __status__ = nvvmGetCompiledResult(<Program>prog, <char*>_buffer_)
     check_status(__status__)
@@ -313,7 +344,7 @@ cpdef get_program_log(intptr_t prog, buffer):
 
     .. seealso:: `nvvmGetProgramLog`
     """
-    cdef void* _buffer_ = get_buffer_pointer(buffer, -1, readonly=False)
+    cdef void* _buffer_ = <void *>_cyb_get_buffer_pointer(buffer, -1, readonly=False)
     with nogil:
         __status__ = nvvmGetProgramLog(<Program>prog, <char*>_buffer_)
     check_status(__status__)
diff --git a/cuda_bindings/cuda/bindings/runtime.pxd b/cuda_bindings/cuda/bindings/runtime.pxd
index ec25a1ee7c6..3665c0a1eba 100644
--- a/cuda_bindings/cuda/bindings/runtime.pxd
+++ b/cuda_bindings/cuda/bindings/runtime.pxd
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated with version 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=5aa83c59fe0efd6b7e04554fe5342e91b15f6bd7d06bc3c3a1b9edd772ae8765
+# This code was automatically generated with version 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=7449c15b6137a39e8e9c26a3aee810954cead6b88b7c8a768abb9a2bc5875913
 cimport cuda.bindings.cyruntime as cyruntime
 
 include "_lib/utils.pxd"
diff --git a/cuda_bindings/cuda/bindings/runtime.pyx b/cuda_bindings/cuda/bindings/runtime.pyx
index c84748ebbde..4546ed78f45 100644
--- a/cuda_bindings/cuda/bindings/runtime.pyx
+++ b/cuda_bindings/cuda/bindings/runtime.pyx
@@ -1,9 +1,8 @@
 # SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-# This code was automatically generated with version 13.4.0. Do not modify it directly.
-# !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=632a03657f085ae740d8137492ed61dac76e32eec0571a3bb73a2471da87bf08
+# This code was automatically generated with version 13.4.1. Do not modify it directly.
+# CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=144b063e6665a8eda3633307d63f7bd708b343d3f3be6f61e0f39b5890fcc76e
 from typing import Any, Optional
 import cython
 import ctypes
diff --git a/cuda_bindings/cuda/bindings/utils/__init__.py b/cuda_bindings/cuda/bindings/utils/__init__.py
index 0bfff4b78be..69618239d91 100644
--- a/cuda_bindings/cuda/bindings/utils/__init__.py
+++ b/cuda_bindings/cuda/bindings/utils/__init__.py
@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 from typing import Any, Callable
 
+from ._envvar import envvar_bool
 from ._nvvm_utils import check_nvvm_compiler_options
 from ._ptx_utils import get_minimal_required_cuda_ver_from_ptx_ver, get_ptx_ver
 from ._version_check import warn_if_cuda_major_version_mismatch
@@ -27,6 +28,9 @@ def get_cuda_native_handle(obj: Any) -> int:
     """
     obj_type = type(obj)
     try:
-        return _handle_getters[obj_type](obj)
+        getter = _handle_getters[obj_type]
     except KeyError:
         raise TypeError("Unknown type: " + str(obj_type)) from None
+    # Deliberately outside the try: a KeyError raised by the getter itself is a
+    # bug in that getter, not an unregistered type.
+    return getter(obj)
diff --git a/cuda_bindings/cuda/bindings/utils/_envvar.py b/cuda_bindings/cuda/bindings/utils/_envvar.py
new file mode 100644
index 00000000000..16a812f0035
--- /dev/null
+++ b/cuda_bindings/cuda/bindings/utils/_envvar.py
@@ -0,0 +1,35 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import os
+
+_TRUE_VALUES = frozenset({"1", "true", "yes", "on"})
+_FALSE_VALUES = frozenset({"0", "false", "no", "off"})
+
+
+def envvar_bool(name: str, default: bool = False) -> bool:
+    """Read a bool-like environment variable.
+
+    Unset, empty, or whitespace-only means ``default``. ``1/true/yes/on`` and
+    ``0/false/no/off`` are recognised case-insensitively, and any other integer
+    follows C truthiness, so ``2`` is true and ``-0`` is false.
+
+    A value that is none of those keeps the historical set-means-true
+    behaviour rather than raising, because these variables are read during
+    import and a raise would turn a typo into an import failure.
+    """
+    raw = os.environ.get(name)
+    if raw is None:
+        return default
+    raw = raw.strip()
+    if not raw:
+        return default
+    lowered = raw.lower()
+    if lowered in _TRUE_VALUES:
+        return True
+    if lowered in _FALSE_VALUES:
+        return False
+    try:
+        return int(raw, 0) != 0
+    except ValueError:
+        return True
diff --git a/cuda_bindings/cuda/bindings/utils/_version_check.py b/cuda_bindings/cuda/bindings/utils/_version_check.py
index 5c68b50152e..d05c313b7a1 100644
--- a/cuda_bindings/cuda/bindings/utils/_version_check.py
+++ b/cuda_bindings/cuda/bindings/utils/_version_check.py
@@ -1,14 +1,17 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-import os
 import threading
 import warnings
 
+from ._envvar import envvar_bool
+
 # Track whether we've already checked major version compatibility
 _major_version_compatibility_checked = False
 _lock = threading.Lock()
 
+_DISABLE_WARNING_ENV_VAR = "CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING"
+
 
 def warn_if_cuda_major_version_mismatch():
     """Warn if the CUDA driver major version is older than cuda-bindings compile-time version.
@@ -21,7 +24,8 @@ def warn_if_cuda_major_version_mismatch():
     The check runs only once per process. Subsequent calls are no-ops.
 
     The warning can be suppressed by setting the environment variable
-    ``CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING=1``.
+    ``CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING=1``. Setting it to ``0`` (or
+    leaving it unset or empty) keeps the warning enabled.
     """
     global _major_version_compatibility_checked
     if _major_version_compatibility_checked:
@@ -32,7 +36,7 @@ def warn_if_cuda_major_version_mismatch():
         _major_version_compatibility_checked = True
 
     # Allow users to suppress the warning
-    if os.environ.get("CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING"):
+    if envvar_bool(_DISABLE_WARNING_ENV_VAR):
         return
 
     # Import here to avoid circular imports and allow lazy loading
@@ -55,7 +59,7 @@ def warn_if_cuda_major_version_mismatch():
             f"NVIDIA driver only supports up to CUDA {runtime_major}. Some cuda-bindings "
             f"features may not work correctly. Consider updating your NVIDIA driver, "
             f"or using a cuda-bindings version built for CUDA {runtime_major}. "
-            f"(Set CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING=1 to suppress this warning.)",
+            f"(Set {_DISABLE_WARNING_ENV_VAR}=1 to suppress this warning.)",
             UserWarning,
             stacklevel=3,
         )
diff --git a/cuda_bindings/docs/nv-versions.json b/cuda_bindings/docs/nv-versions.json
index 6f448535f01..08202cc65b6 100644
--- a/cuda_bindings/docs/nv-versions.json
+++ b/cuda_bindings/docs/nv-versions.json
@@ -4,8 +4,8 @@
         "url": "https://nvidia.github.io/cuda-python/cuda-bindings/latest/"
     },
     {
-        "version": "13.4.0",
-        "url": "https://nvidia.github.io/cuda-python/cuda-bindings/13.4.0/"
+        "version": "13.4.1",
+        "url": "https://nvidia.github.io/cuda-python/cuda-bindings/13.4.1/"
     },
     {
         "version": "13.3.1",
diff --git a/cuda_bindings/docs/source/install.rst b/cuda_bindings/docs/source/install.rst
index 7f890365ea3..d77464ec91f 100644
--- a/cuda_bindings/docs/source/install.rst
+++ b/cuda_bindings/docs/source/install.rst
@@ -120,11 +120,14 @@ Requirements
 
 * CUDA Toolkit headers[^1]
 * CUDA Runtime static library[^2]
+* A git clone of the repository that includes tags[^3]
 
 [^1]: User projects that ``cimport`` CUDA symbols in Cython must also use CUDA Toolkit (CTK) types as provided by the ``cuda.bindings`` major.minor version. This results in CTK headers becoming a transitive dependency of downstream projects through CUDA Python.
 
 [^2]: The CUDA Runtime static library (``libcudart_static.a`` on Linux, ``cudart_static.lib`` on Windows) is part of the CUDA Toolkit. If using conda packages, it is contained in the ``cuda-cudart-static`` package.
 
+[^3]: The version is derived from git tags via ``setuptools-scm``, so the clone must include tags reaching back to at least the latest ``v*`` tag. Clone with ``git clone https://github.com/NVIDIA/cuda-python.git``; do not use ``--depth`` or ``--no-tags``, since a shallow clone builds without error but produces a bogus version such as ``0.1.dev1+g0d22cb444``. See `Cloning the repository <https://github.com/NVIDIA/cuda-python/blob/main/CONTRIBUTING.md>`_ for details and recovery steps.
+
 Source builds require that the provided CUDA headers are of the same major.minor version as the ``cuda.bindings`` you're trying to build. Despite this requirement, note that the minor version compatibility is still maintained. Use the ``CUDA_PATH`` (or ``CUDA_HOME``) environment variable to specify the location of your headers. If both are set, ``CUDA_PATH`` takes precedence. For example, if your headers are located in ``/usr/local/cuda/include``, then you should set ``CUDA_PATH`` with:
 
 .. code-block:: console
diff --git a/cuda_bindings/docs/source/module/driver.rst b/cuda_bindings/docs/source/module/driver.rst
index 8ed56ecbee3..4a7b5d68f7e 100644
--- a/cuda_bindings/docs/source/module/driver.rst
+++ b/cuda_bindings/docs/source/module/driver.rst
@@ -1,10 +1,9 @@
 .. SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 .. SPDX-License-Identifier: Apache-2.0
 
-.. This code was automatically generated with version 13.4.0. Do not modify it directly.
+.. This code was automatically generated with version 13.4.1. Do not modify it directly.
 
-.. !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-.. CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=d177af98becf52d0965c6bcaf352b66e8382b394bfaae3356ee54668bbc57d4d
+.. CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=8fb799afff57074126fc28394dc578e31f2d13bffcbecea17a8e14da87e419c7
 ------
 driver
 ------
diff --git a/cuda_bindings/docs/source/module/nvrtc.rst b/cuda_bindings/docs/source/module/nvrtc.rst
index c4e453bee6b..bedf6ed179d 100644
--- a/cuda_bindings/docs/source/module/nvrtc.rst
+++ b/cuda_bindings/docs/source/module/nvrtc.rst
@@ -1,10 +1,9 @@
 .. SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 .. SPDX-License-Identifier: Apache-2.0
 
-.. This code was automatically generated with version 13.4.0. Do not modify it directly.
+.. This code was automatically generated with version 13.4.1. Do not modify it directly.
 
-.. !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-.. CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=e81ae93eee7b54340488dc4be19f2767d6c7316292571214623473e1d8452da7
+.. CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=03c58049a86a77a6113432e5935ea831b2fd6d6980b3f98f20b0025d043e801a
 -----
 nvrtc
 -----
@@ -123,13 +122,18 @@ Bundled Headers Installation
 
 NVRTC defines the following types and functions for bundled headers installation and management.
 
+.. autoclass:: cuda.bindings.nvrtc.nvrtcBundledHeadersInfo
 .. autoclass:: cuda.bindings.nvrtc.nvrtcBundledHeadersInfo
 .. autofunction:: cuda.bindings.nvrtc.nvrtcInstallBundledHeaders
 .. autofunction:: cuda.bindings.nvrtc.nvrtcGetBundledHeadersInfo
 .. autofunction:: cuda.bindings.nvrtc.nvrtcRemoveBundledHeaders
 .. autoattribute:: cuda.bindings.nvrtc.NVRTC_INSTALL_HEADERS_SKIP_IF_EXISTS
 
-    Flags for nvrtcInstallBundledHeaders.Skip installation if version marker exists and version matches. This is the default behavior when flags=0.
+    Flags for nvrtcInstallBundledHeaders.
+
+
+
+    Skip installation if version marker exists and version matches. This is the default behavior when flags=0.
 
 .. autoattribute:: cuda.bindings.nvrtc.NVRTC_INSTALL_HEADERS_FORCE_OVERWRITE
 
diff --git a/cuda_bindings/docs/source/module/runtime.rst b/cuda_bindings/docs/source/module/runtime.rst
index d8698065d9b..f27a847e25f 100644
--- a/cuda_bindings/docs/source/module/runtime.rst
+++ b/cuda_bindings/docs/source/module/runtime.rst
@@ -1,10 +1,9 @@
 .. SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 .. SPDX-License-Identifier: Apache-2.0
 
-.. This code was automatically generated with version 13.4.0. Do not modify it directly.
+.. This code was automatically generated with version 13.4.1. Do not modify it directly.
 
-.. !!! WARNING: THIS FILE CONTAINS PRERELEASE APIs !!!
-.. CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=1db68a52c789dfc40b5b9e8f58768e090e2668500bed69cf25d90013bdfaef43
+.. CYTHON-BINDINGS-GENERATED-DO-NOT-MODIFY-THIS-FILE: format=1; content-sha256=408acc02ad695c94ce3060966b62863084ed3f1ac77da7e731e37b3cf7cf9b27
 -------
 runtime
 -------
diff --git a/cuda_bindings/docs/source/release/13.4.1-notes.rst b/cuda_bindings/docs/source/release/13.4.1-notes.rst
new file mode 100644
index 00000000000..e5f68443d45
--- /dev/null
+++ b/cuda_bindings/docs/source/release/13.4.1-notes.rst
@@ -0,0 +1,98 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. module:: cuda.bindings
+
+``cuda-bindings`` 13.4.1 Release notes
+======================================
+
+New APIs
+--------
+
+New APIs from CUDA Toolkit 13.4 are now available in ``cuda-bindings``.
+
+New driver API functions:
+
+* :func:`driver.cuDeviceGetFabricClusterUuid`
+* :func:`driver.cuDeviceGetCliqueCount`
+* :func:`driver.cuDeviceGetCliqueInfo`
+* :func:`driver.cuMemGetLocationInfo`
+* :func:`driver.cuGraphAddNode_v3`
+* :func:`driver.cuGraphNodeSetParams_v2`
+* :func:`driver.cuCheckpointOperationComplete`
+
+New runtime API functions:
+
+* :func:`runtime.cudaMemGetLocationInfo`
+
+New cuFile API functions:
+
+* :func:`cufile.readv`
+* :func:`cufile.writev`
+
+New NVML API functions:
+
+* :func:`nvml.system_get_cper_v1`
+* :func:`nvml.device_get_bbx_time_data_v1`
+* :func:`nvml.device_get_accounting_stats_v2`
+* :func:`nvml.device_get_remapped_rows_v2`
+* :func:`nvml.device_set_adaptive_tgp_mode_v1`
+* :func:`nvml.device_get_adaptive_tgp_mode_info_v1`
+* :func:`nvml.device_set_memory_limits_v1`
+* :func:`nvml.device_get_memory_limits_v1`
+* :func:`nvml.device_get_gpu_fabric_info_v4`
+* :func:`nvml.device_perf_metrics_get_samples_v1`
+* :func:`nvml.device_set_nvlink_bw_mode_async_v1`
+* :func:`nvml.device_get_nv_link_telemetry_samples_v1`
+* :func:`nvml.event_set_register_gpu_operational_events_v1`
+* :func:`nvml.event_set_wait_v3`
+* :func:`nvml.event_set_get_context_count_v1`
+* :func:`nvml.event_set_get_context_info_v1`
+* :func:`nvml.event_set_get_gpu_operational_event_context_legacy_xid_v1`
+* :func:`nvml.device_get_bank_remapper_status_v1`
+* :func:`nvml.event_set_get_context_data_v1`
+
+Bugfixes
+--------
+
+* Fixed a bug in the wrapping of ``nvrtcBundledHeadersInfo``.
+  (`PR #2754 <https://github.com/NVIDIA/cuda-python/pull/2754>`_)
+* Fixed ``CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING``: previously, setting it
+  to ``"0"`` (or any other non-empty string) still disabled the warning; it
+  is now parsed as a bool-like value, so ``"0"`` correctly leaves the warning
+  enabled.
+  (`PR #2581 <https://github.com/NVIDIA/cuda-python/pull/2581>`_)
+* Fixed a crash in ``nvml.system_event_set_wait`` caused by calling
+  ``resize()`` on a non-owning ``SystemEventData_v1._data`` view.
+  (`PR #2690 <https://github.com/NVIDIA/cuda-python/pull/2690>`_)
+* ``get_cuda_native_handle`` no longer misreports a ``KeyError`` raised from
+  within a registered getter as an "Unknown type" error.
+  (`PR #2551 <https://github.com/NVIDIA/cuda-python/pull/2551>`_)
+* Fixed ``cuFile`` status checking to no longer raise ``cuFileError``
+  spuriously when ``CUfileError_t.cu_err`` is set on a non-error path (for
+  example, BAR-size queries on GH200 systems).
+  (`PR #2530 <https://github.com/NVIDIA/cuda-python/pull/2530>`_)
+* Made ``param_packer.feed()`` safe under free-threaded Python by moving its
+  internal state initialization to import time.
+  (`PR #2417 <https://github.com/NVIDIA/cuda-python/pull/2417>`_)
+
+Deprecation Notices
+-------------------
+
+* Support for using ``cuda-bindings`` with Python 3.10 is deprecated and will be
+  removed in a future version.  Python 3.10 reaches end of life in October 2026
+  per the `CPython support cycle <https://devguide.python.org/versions/>`_.
+
+Prerelease feature
+------------------
+
+A new version of the ``nvrtc`` API is available as ``cuda.bindings._v2.nvrtc``.  The
+primary improvements are: (1) raising exceptions rather than returning error
+codes, (2) uses PEP8-compliant naming, and (3) more performance.  This API is
+still experimental and subject to change.
+
+Known issues
+------------
+
+* Updating from older versions (v12.6.2.post1 and below) via ``pip install -U cuda-python`` might not work. Please do a clean re-installation by uninstalling ``pip uninstall -y cuda-python`` followed by installing ``pip install cuda-python``.
+* ``nvml.system_get_process_name`` on WSL can return incorrect values.  To work around this, set the locale to "C" before calling ``nvml.device_get_compute_running_processes_v3`` (which sets the process names) and before calling ``nvml.system_get_process_name``. ``cuda_core`` does this automatically, but users of the raw NVML API will need to do this manually.
diff --git a/cuda_bindings/docs/source/release/13.4.1a0-notes.rst b/cuda_bindings/docs/source/release/13.4.1a0-notes.rst
new file mode 100644
index 00000000000..5a4c5f632c7
--- /dev/null
+++ b/cuda_bindings/docs/source/release/13.4.1a0-notes.rst
@@ -0,0 +1,98 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. module:: cuda.bindings
+
+``cuda-bindings`` 13.4.1a0 Release notes
+========================================
+
+New APIs
+--------
+
+New APIs from CUDA Toolkit 13.4 are now available in ``cuda-bindings``.
+
+New driver API functions:
+
+* :func:`driver.cuDeviceGetFabricClusterUuid`
+* :func:`driver.cuDeviceGetCliqueCount`
+* :func:`driver.cuDeviceGetCliqueInfo`
+* :func:`driver.cuMemGetLocationInfo`
+* :func:`driver.cuGraphAddNode_v3`
+* :func:`driver.cuGraphNodeSetParams_v2`
+* :func:`driver.cuCheckpointOperationComplete`
+
+New runtime API functions:
+
+* :func:`runtime.cudaMemGetLocationInfo`
+
+New cuFile API functions:
+
+* :func:`cufile.readv`
+* :func:`cufile.writev`
+
+New NVML API functions:
+
+* :func:`nvml.system_get_cper_v1`
+* :func:`nvml.device_get_bbx_time_data_v1`
+* :func:`nvml.device_get_accounting_stats_v2`
+* :func:`nvml.device_get_remapped_rows_v2`
+* :func:`nvml.device_set_adaptive_tgp_mode_v1`
+* :func:`nvml.device_get_adaptive_tgp_mode_info_v1`
+* :func:`nvml.device_set_memory_limits_v1`
+* :func:`nvml.device_get_memory_limits_v1`
+* :func:`nvml.device_get_gpu_fabric_info_v4`
+* :func:`nvml.device_perf_metrics_get_samples_v1`
+* :func:`nvml.device_set_nvlink_bw_mode_async_v1`
+* :func:`nvml.device_get_nv_link_telemetry_samples_v1`
+* :func:`nvml.event_set_register_gpu_operational_events_v1`
+* :func:`nvml.event_set_wait_v3`
+* :func:`nvml.event_set_get_context_count_v1`
+* :func:`nvml.event_set_get_context_info_v1`
+* :func:`nvml.event_set_get_gpu_operational_event_context_legacy_xid_v1`
+* :func:`nvml.device_get_bank_remapper_status_v1`
+* :func:`nvml.event_set_get_context_data_v1`
+
+Bugfixes
+--------
+
+* Fixed a bug in the wrapping of ``nvrtcBundledHeadersInfo``.
+  (`PR #2754 <https://github.com/NVIDIA/cuda-python/pull/2754>`_)
+* Fixed ``CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING``: previously, setting it
+  to ``"0"`` (or any other non-empty string) still disabled the warning; it
+  is now parsed as a bool-like value, so ``"0"`` correctly leaves the warning
+  enabled.
+  (`PR #2581 <https://github.com/NVIDIA/cuda-python/pull/2581>`_)
+* Fixed a crash in ``nvml.system_event_set_wait`` caused by calling
+  ``resize()`` on a non-owning ``SystemEventData_v1._data`` view.
+  (`PR #2690 <https://github.com/NVIDIA/cuda-python/pull/2690>`_)
+* ``get_cuda_native_handle`` no longer misreports a ``KeyError`` raised from
+  within a registered getter as an "Unknown type" error.
+  (`PR #2551 <https://github.com/NVIDIA/cuda-python/pull/2551>`_)
+* Fixed ``cuFile`` status checking to no longer raise ``cuFileError``
+  spuriously when ``CUfileError_t.cu_err`` is set on a non-error path (for
+  example, BAR-size queries on GH200 systems).
+  (`PR #2530 <https://github.com/NVIDIA/cuda-python/pull/2530>`_)
+* Made ``param_packer.feed()`` safe under free-threaded Python by moving its
+  internal state initialization to import time.
+  (`PR #2417 <https://github.com/NVIDIA/cuda-python/pull/2417>`_)
+
+Deprecation Notices
+-------------------
+
+* Support for using ``cuda-bindings`` with Python 3.10 is deprecated and will be
+  removed in a future version.  Python 3.10 reaches end of life in October 2026
+  per the `CPython support cycle <https://devguide.python.org/versions/>`_.
+
+Prerelease feature
+------------------
+
+A new version of the ``nvrtc`` API is available as ``cuda.bindings._v2.nvrtc``.  The
+primary improvements are: (1) raising exceptions rather than returning error
+codes, (2) uses PEP8-compliant naming, and (3) more performance.  This API is
+still experimental and subject to change.
+
+Known issues
+------------
+
+* Updating from older versions (v12.6.2.post1 and below) via ``pip install -U cuda-python`` might not work. Please do a clean re-installation by uninstalling ``pip uninstall -y cuda-python`` followed by installing ``pip install cuda-python``.
+* ``nvml.system_get_process_name`` on WSL can return incorrect values.  To work around this, set the locale to "C" before calling ``nvml.device_get_compute_running_processes_v3`` (which sets the process names) and before calling ``nvml.system_get_process_name``. ``cuda_core`` does this automatically, but users of the raw NVML API will need to do this manually.
diff --git a/cuda_bindings/examples/0_Introduction/clock_nvrtc.py b/cuda_bindings/examples/0_Introduction/clock_nvrtc.py
index 14572469e79..71b30d7efb0 100644
--- a/cuda_bindings/examples/0_Introduction/clock_nvrtc.py
+++ b/cuda_bindings/examples/0_Introduction/clock_nvrtc.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py b/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py
index cad35990e91..17ecb83adf5 100644
--- a/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py
+++ b/cuda_bindings/examples/0_Introduction/simple_cubemap_texture.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/0_Introduction/simple_p2p.py b/cuda_bindings/examples/0_Introduction/simple_p2p.py
index 0c6700bc8df..61b021c1793 100644
--- a/cuda_bindings/examples/0_Introduction/simple_p2p.py
+++ b/cuda_bindings/examples/0_Introduction/simple_p2p.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/0_Introduction/simple_zero_copy.py b/cuda_bindings/examples/0_Introduction/simple_zero_copy.py
index 72c5fe8b701..2c0692abcfb 100644
--- a/cuda_bindings/examples/0_Introduction/simple_zero_copy.py
+++ b/cuda_bindings/examples/0_Introduction/simple_zero_copy.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/0_Introduction/system_wide_atomics.py b/cuda_bindings/examples/0_Introduction/system_wide_atomics.py
index fde3e67ad8f..5d98a74f8a9 100644
--- a/cuda_bindings/examples/0_Introduction/system_wide_atomics.py
+++ b/cuda_bindings/examples/0_Introduction/system_wide_atomics.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/0_Introduction/vector_add_drv.py b/cuda_bindings/examples/0_Introduction/vector_add_drv.py
index d2356c0d3a1..7a987126f52 100644
--- a/cuda_bindings/examples/0_Introduction/vector_add_drv.py
+++ b/cuda_bindings/examples/0_Introduction/vector_add_drv.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/0_Introduction/vector_add_mmap.py b/cuda_bindings/examples/0_Introduction/vector_add_mmap.py
index 9faa45bedb8..2a8f4a99a1d 100644
--- a/cuda_bindings/examples/0_Introduction/vector_add_mmap.py
+++ b/cuda_bindings/examples/0_Introduction/vector_add_mmap.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py b/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py
index b45f11f317b..5118600a493 100644
--- a/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py
+++ b/cuda_bindings/examples/2_Concepts_and_Techniques/stream_ordered_allocation.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py b/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py
index 9a2ec3dec3b..615006049fd 100644
--- a/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py
+++ b/cuda_bindings/examples/3_CUDA_Features/global_to_shmem_async_copy.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py b/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py
index 317a774d5df..816bc84e274 100644
--- a/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py
+++ b/cuda_bindings/examples/3_CUDA_Features/simple_cuda_graphs.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py b/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py
index 83d359b1e93..488f57d03ab 100644
--- a/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py
+++ b/cuda_bindings/examples/4_CUDA_Libraries/conjugate_gradient_multi_block_cg.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py b/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py
index 459022784b3..348e8c38236 100644
--- a/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py
+++ b/cuda_bindings/examples/4_CUDA_Libraries/nvidia_smi.py
@@ -1,4 +1,4 @@
-# Copyright 2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 
diff --git a/cuda_bindings/examples/extra/iso_fd_modelling.py b/cuda_bindings/examples/extra/iso_fd_modelling.py
index 9fe9432862c..e1f29936a9f 100644
--- a/cuda_bindings/examples/extra/iso_fd_modelling.py
+++ b/cuda_bindings/examples/extra/iso_fd_modelling.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/examples/extra/jit_program.py b/cuda_bindings/examples/extra/jit_program.py
index 7a5cc1495fc..ad3409c1f68 100644
--- a/cuda_bindings/examples/extra/jit_program.py
+++ b/cuda_bindings/examples/extra/jit_program.py
@@ -1,4 +1,4 @@
-# Copyright 2021-2026 NVIDIA Corporation.  All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2021-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # ################################################################################
diff --git a/cuda_bindings/pixi.lock b/cuda_bindings/pixi.lock
index 65cb1f78793..81e0045322d 100644
--- a/cuda_bindings/pixi.lock
+++ b/cuda_bindings/pixi.lock
@@ -20,6 +20,8 @@ environments:
   cu12:
     channels:
     - url: https://conda.anaconda.org/conda-forge/
+    indexes:
+    - https://pypi.org/simple
     packages:
       linux-64:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
@@ -37,7 +39,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-impl-12.9.86-h4bc722e_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-tools-12.9.86-h4bc722e_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-profiler-api-12.9.79-h7938cbb_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.4-py314h1807b08_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.8-py314h1807b08_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/dav1d-1.2.1-hd590300_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h24cb091_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/ffmpeg-8.0.1-gpl_hcddb375_914.conda
@@ -77,15 +79,15 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libflac-1.5.0-he200343_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype-2.14.2-ha770c72_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype6-2.14.2-h73754d4_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_18.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-15.2.0-h69a702a_18.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.1.0-ha9f2e26_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-16.1.0-h69a702a_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-15.2.0-h69a702a_18.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-15.2.0-h68bc16d_18.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgl-1.7.0-ha4b6fd6_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.86.4-h6548e54_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libglvnd-1.7.0-ha4b6fd6_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libglx-1.7.0-ha4b6fd6_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_18.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-16.1.0-he0feb66_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libhwloc-2.12.2-default_hafda6a7_1000.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libhwy-1.3.0-h4c17acf_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libiconv-1.18-h3b78370_2.conda
@@ -120,8 +122,8 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libsanitizer-15.2.0-h90f66d4_18.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libsndfile-1.2.2-hc7d488a_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.52.0-hf4e2dac_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_18.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-15.2.0-hdf11a46_18.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-16.1.0-h934c35e_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-16.1.0-hdf11a46_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.10-hd0affe5_4.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.7.1-h9d88235_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libudev1-257.10-hd0affe5_4.conda
@@ -220,8 +222,9 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/wayland-protocols-1.47-hd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhcf101f3_1.conda
-      - conda_source: cuda-bindings[04818863] @ .
-      - conda_source: cuda-pathfinder[83159de6] @ ../cuda_pathfinder
+      - conda_source: cuda-bindings[595e6447] @ .
+      - conda_source: cuda-pathfinder[9139f4b4] @ ../cuda_pathfinder
+      - pypi: ../cuda_python_test_helpers
       linux-aarch64:
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/alsa-lib-1.2.15.3-he30d5cf_0.conda
@@ -238,7 +241,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvvm-impl-12.9.86-h7b14b0b_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvvm-tools-12.9.86-h7b14b0b_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-profiler-api-12.9.79-h16bee8c_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.4-py314h4c416a3_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.8-py314hc6b4731_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/dav1d-1.2.1-h31becfc_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/dbus-1.16.2-h70963c4_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ffmpeg-8.0.1-gpl_h62efc85_914.conda
@@ -275,15 +278,15 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libflac-1.5.0-he9c94f4_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libfreetype-2.14.2-h8af1aa0_0.conda
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       - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhcf101f3_1.conda
-      - conda_source: cuda-bindings[748b2e6f] @ .
-      - conda_source: cuda-pathfinder[4dfff30f] @ ../cuda_pathfinder
+      - conda_source: cuda-bindings[cb9a5e74] @ .
+      - conda_source: cuda-pathfinder[fa19867f] @ ../cuda_pathfinder
+      - pypi: ../cuda_python_test_helpers
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       - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda
-      - conda_source: cuda-bindings[341f49d8] @ .
-      - conda_source: cuda-pathfinder[169735b8] @ ../cuda_pathfinder
+      - conda_source: cuda-bindings[38bd5059] @ .
+      - conda_source: cuda-pathfinder[15190cc4] @ ../cuda_pathfinder
+      - pypi: ../cuda_python_test_helpers
   cu13:
     channels:
     - url: https://conda.anaconda.org/conda-forge/
+    indexes:
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@@ -574,7 +581,7 @@ environments:
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-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_16.conda
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+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-16.1.0-hdf11a46_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.13-h084b8d7_1.conda
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       - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhcf101f3_1.conda
-      - conda_source: cuda-bindings[5987685b] @ .
-      - conda_source: cuda-pathfinder[83159de6] @ ../cuda_pathfinder
+      - conda_source: cuda-bindings[33376fba] @ .
+      - conda_source: cuda-pathfinder[9139f4b4] @ ../cuda_pathfinder
+      - pypi: ../cuda_python_test_helpers
       linux-aarch64:
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-      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.4-py314h4c416a3_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.8-py314hc6b4731_0.conda
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-      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-15.2.0-h8acb6b2_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-16.1.0-h8acb6b2_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libhwloc-2.12.1-default_ha470c98_1003.conda
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-      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-ng-15.2.0-hdbbeba8_16.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-16.1.0-hef695bb_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-ng-16.1.0-hdbbeba8_1.conda
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@@ -933,8 +941,9 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2025c-hc9c84f9_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/zipp-3.23.0-pyhcf101f3_1.conda
-      - conda_source: cuda-bindings[d33f8c8b] @ .
-      - conda_source: cuda-pathfinder[4dfff30f] @ ../cuda_pathfinder
+      - conda_source: cuda-bindings[9909e402] @ .
+      - conda_source: cuda-pathfinder[fa19867f] @ ../cuda_pathfinder
+      - pypi: ../cuda_python_test_helpers
       win-64:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_1.conda
@@ -990,7 +999,7 @@ environments:
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-      - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.4-py314h344ed54_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.8-py314h344ed54_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/dav1d-1.2.1-hcfcfb64_0.conda
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       - conda: https://conda.anaconda.org/conda-forge/win-64/fontconfig-2.15.0-h765892d_1.conda
@@ -1066,11 +1075,14 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/win-64/x265-3.5-h2d74725_3.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda
-      - conda_source: cuda-bindings[8de8dc46] @ .
-      - conda_source: cuda-pathfinder[169735b8] @ ../cuda_pathfinder
+      - conda_source: cuda-bindings[943c652a] @ .
+      - conda_source: cuda-pathfinder[15190cc4] @ ../cuda_pathfinder
+      - pypi: ../cuda_python_test_helpers
   default:
     channels:
     - url: https://conda.anaconda.org/conda-forge/
+    indexes:
+    - https://pypi.org/simple
     packages:
       linux-64:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_libgcc_mutex-0.1-conda_forge.tar.bz2
@@ -1081,15 +1093,15 @@ environments:
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-      - conda_source: cuda-bindings[5987685b] @ .
-      - conda_source: cuda-pathfinder[83159de6] @ ../cuda_pathfinder
+      - conda_source: cuda-bindings[595e6447] @ .
+      - conda_source: cuda-pathfinder[9139f4b4] @ ../cuda_pathfinder
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   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-  - conda_source: cuda-pathfinder[83159de6] @ ../cuda_pathfinder
-- conda_source: cuda-bindings[341f49d8] @ .
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+  - conda_source: cuda-pathfinder[9139f4b4] @ ../cuda_pathfinder
+- conda_source: cuda-bindings[38bd5059] @ .
   variants:
     c_compiler: vs2022
     cuda_version: 12.*
@@ -16546,9 +17183,9 @@ packages:
       path: ../cuda_pathfinder
   build_packages:
   - conda: https://conda.anaconda.org/conda-forge/noarch/vswhere-3.1.7-h40126e0_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_39.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_41.conda
   host_packages:
-  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-h4c7d964_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-h4c7d964_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_win-64-12.9.27-h57928b3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_win-64-12.9.86-h57928b3_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_win-64-12.9.79-he0c23c2_0.conda
@@ -16556,15 +17193,15 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_win-64-12.9.79-he0c23c2_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_win-64-12.9.86-h57928b3_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
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   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_10.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-cudart-12.9.79-he0c23c2_0.conda
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   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-cudart-static-12.9.79-he0c23c2_0.conda
@@ -16574,28 +17211,28 @@ packages:
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   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-nvvm-tools-12.9.86-h2466b09_2.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-profiler-api-12.9.79-h57928b3_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.8-py314h344ed54_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.9-py314h344ed54_0.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.8.1-hac47afa_1.conda
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   - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.53.3-hf5d6505_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.3-hf411b9b_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.6-h4b44e0e_100_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.53.4-hf5d6505_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.3-hf411b9b_1.conda
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   - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h967ab96_3.conda
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-  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-h1b7c187_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36231-h1b9f54f_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36231-h1b9f54f_39.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.12.2-h7ca4a90_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-ha367084_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda
-  - conda_source: cuda-pathfinder[169735b8] @ ../cuda_pathfinder
-- conda_source: cuda-bindings[5987685b] @ .
+  - conda_source: cuda-pathfinder[15190cc4] @ ../cuda_pathfinder
+- conda_source: cuda-bindings[595e6447] @ .
   variants:
     c_stdlib: sysroot
     c_stdlib_version: '2.28'
-    cuda_version: 13.3.*
+    cuda_version: 12.*
     python: 3.14.*
     target_platform: linux-64
   depends:
@@ -16605,14 +17242,14 @@ packages:
   - cuda-pathfinder
   - libnvjitlink
   - cuda-nvrtc
-  - cuda-nvrtc >=13.3.33,<14.0a0
+  - cuda-nvrtc >=12.9.86,<13.0a0
   - cuda-nvvm
   - libnvfatbin
   - libcufile
-  - libcufile >=1.18.1.6,<2.0a0
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
+  - libcufile >=1.14.1.1,<2.0a0
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
   - __glibc >=2.28,<3.0.a0
   - python_abi 3.14.* *_cp314
   license: Apache-2.0
@@ -16623,183 +17260,79 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.46.1-default_hfdba357_102.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.46.1-default_h4852527_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-15.2.0-he0086c7_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-15.2.0-h7be306e_27.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-15.2.0-hda75c37_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-15.2.0-hcb00b6d_27.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-16.1.0-h5fcb69b_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-16.1.0-h5fd2508_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-16.1.0-he33a5f8_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-16.1.0-h5525346_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_102.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.1.0-ha9f2e26_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-16.1.0-he0feb66_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsanitizer-16.1.0-hf2715c6_1.conda
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+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-static_linux-64-12.9.79-h3f2d84a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-12.9.79-h3f2d84a_0.conda
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   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-  - conda_source: cuda-pathfinder[4dfff30f] @ ../cuda_pathfinder
-- conda_source: cuda-bindings[8de8dc46] @ .
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+  - conda_source: cuda-pathfinder[9139f4b4] @ ../cuda_pathfinder
+- conda_source: cuda-bindings[943c652a] @ .
   variants:
     c_compiler: vs2022
     cuda_version: 13.3.*
@@ -16826,25 +17359,25 @@ packages:
       path: ../cuda_pathfinder
   build_packages:
   - conda: https://conda.anaconda.org/conda-forge/noarch/vswhere-3.1.7-h40126e0_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_39.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_41.conda
   host_packages:
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_win-64-13.3.3.4.1-h57928b3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-h4c7d964_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_win-64-13.3.3.4.1-h57928b3_1.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_win-64-13.3.73-h57928b3_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_10.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-cudart-13.3.29-hac47afa_0.conda
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   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-cudart-static-13.3.29-hac47afa_0.conda
@@ -16854,24 +17387,24 @@ packages:
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   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-nvvm-tools-13.3.73-h2466b09_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.8-py314h344ed54_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.9-py314h344ed54_0.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.8.1-hac47afa_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.3-hf411b9b_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.6-h4b44e0e_100_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.53.4-hf5d6505_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.3-hf411b9b_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.6-h4b44e0e_101_cp314.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h967ab96_3.conda
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-  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36231-h1b9f54f_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36231-h1b9f54f_39.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.12.2-h7ca4a90_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-ha367084_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda
-  - conda_source: cuda-pathfinder[169735b8] @ ../cuda_pathfinder
-- conda_source: cuda-bindings[d33f8c8b] @ .
+  - conda_source: cuda-pathfinder[15190cc4] @ ../cuda_pathfinder
+- conda_source: cuda-bindings[9909e402] @ .
   variants:
     c_stdlib: sysroot
     c_stdlib_version: '2.28'
@@ -16890,9 +17423,9 @@ packages:
   - libnvfatbin
   - libcufile
   - libcufile >=1.18.1.6,<2.0a0
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
   - __glibc >=2.28,<3.0.a0
   - python_abi 3.14.* *_cp314
   license: Apache-2.0
@@ -16903,25 +17436,25 @@ packages:
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   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_linux-aarch64-2.46.1-default_hf1166c9_102.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-15.2.0-h7e4acf5_27.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_impl_linux-aarch64-16.1.0-h04da0f0_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_linux-aarch64-16.1.0-hed00b63_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-16.1.0-hd5c6868_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-16.1.0-h4223dcb_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_2.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-16.1.0-h8acb6b2_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsanitizer-16.1.0-h2510bd8_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-16.1.0-hef695bb_1.conda
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   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h85ac4a6_6.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-aarch64-4.18.0-h05a177a_9.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-aarch64-15.2.0-ha7b1723_119.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-aarch64-16.1.0-hd673532_101.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-aarch64-16.1.0-h2445e1f_101.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-aarch64-2.28-h585391f_9.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
   host_packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_10.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-13.3.29-h8f3c8d4_0.conda
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   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-static-13.3.29-h8f3c8d4_0.conda
@@ -16931,123 +17464,188 @@ packages:
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/icu-78.3-hcab7f73_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.9-py314hc6b4731_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcap-2.78-hf9559e3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcap-2.78-hfcc8634_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcufile-1.18.1.6-h42688b2_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-15.2.0-h8acb6b2_19.conda
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+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-aarch64-13.3.3.4.1-h579c4fd_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-  - conda_source: cuda-pathfinder[4dfff30f] @ ../cuda_pathfinder
-- conda_source: cuda-pathfinder[169735b8] @ ../cuda_pathfinder
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+  - conda_source: cuda-pathfinder[fa19867f] @ ../cuda_pathfinder
+- conda_source: cuda-bindings[cb9a5e74] @ .
   variants:
-    target_platform: noarch
+    c_stdlib: sysroot
+    c_stdlib_version: '2.28'
+    cuda_version: 12.*
+    python: 3.14.*
+    target_platform: linux-aarch64
   depends:
+  - python
   - python >=3.10
-  - python *
+  - cuda-version
+  - cuda-pathfinder
+  - libnvjitlink
+  - cuda-nvrtc
+  - cuda-nvrtc >=12.9.86,<13.0a0
+  - cuda-nvvm
+  - libnvfatbin
+  - libcufile
+  - libcufile >=1.14.1.1,<2.0a0
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
+  - __glibc >=2.28,<3.0.a0
+  - python_abi 3.14.* *_cp314
   license: Apache-2.0
-  host_packages:
-  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-h4c7d964_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
+  source_depends:
+    cuda-pathfinder:
+      path: ../cuda_pathfinder
+  build_packages:
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_impl_linux-aarch64-2.46.1-default_h5f4c503_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_linux-aarch64-2.46.1-default_hf1166c9_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_impl_linux-aarch64-16.1.0-h04da0f0_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_linux-aarch64-16.1.0-hed00b63_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-16.1.0-hd5c6868_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-16.1.0-h4223dcb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgcc-16.1.0-h205dda4_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-16.1.0-h8acb6b2_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsanitizer-16.1.0-h2510bd8_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-16.1.0-hef695bb_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h85ac4a6_6.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-aarch64-4.18.0-h05a177a_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-aarch64-16.1.0-hd673532_101.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-aarch64-16.1.0-h2445e1f_101.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-aarch64-2.28-h585391f_9.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.8.1-hac47afa_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.3-hfd05255_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.53.3-hf5d6505_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.3-hf411b9b_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.6-h4b44e0e_100_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h967ab96_3.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.11.29-h7ca4a90_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-h1b7c187_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36231-h1b9f54f_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36231-h1b9f54f_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda
-- conda_source: cuda-pathfinder[4dfff30f] @ ../cuda_pathfinder
-  variants:
-    target_platform: noarch
-  depends:
-  - python >=3.10
-  - python *
-  license: Apache-2.0
   host_packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_9.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/icu-78.3-hcab7f73_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_10.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-12.9.79-h3ae8b8a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-dev-12.9.79-h3ae8b8a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-static-12.9.79-h3ae8b8a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvrtc-12.9.86-h8f3c8d4_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvrtc-dev-12.9.86-h8f3c8d4_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvvm-12.9.86-he9431aa_106.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvvm-impl-12.9.86-h7b14b0b_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvvm-tools-12.9.86-h7b14b0b_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-profiler-api-12.9.79-h16bee8c_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.9-py314hc6b4731_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcap-2.78-hfcc8634_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcufile-1.14.1.1-had8bf56_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcufile-dev-1.14.1.1-he38c790_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-15.2.0-h8acb6b2_19.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgcc-16.1.0-h205dda4_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-16.1.0-h8acb6b2_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsqlite-3.53.3-h10b116e_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-15.2.0-hef695bb_19.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libnl-3.11.0-h86ecc28_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsqlite-3.53.4-h022381a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-16.1.0-hef695bb_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsystemd0-257.13-hfcc8634_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libudev1-257.13-hfcc8634_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libuuid-2.42.2-h1022ec0_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_3.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ncurses-6.6-hf8d1292_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/python-3.14.6-hc679e19_100_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/openssl-3.6.3-h546c87b_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/python-3.14.6-hc679e19_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/rdma-core-63.0-h1f0f388_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/readline-8.3-hb682ff5_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/uv-0.11.29-hbe9c82f_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/uv-0.12.2-hbe9c82f_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-hbd8a1cb_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/arm-variant-1.2.0-sbsa.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-aarch64-12.9.27-h579c4fd_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-aarch64-12.9.86-h579c4fd_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_linux-aarch64-12.9.79-h3ae8b8a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-static_linux-aarch64-12.9.79-h3ae8b8a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-aarch64-12.9.79-h3ae8b8a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_linux-aarch64-12.9.86-h579c4fd_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-- conda_source: cuda-pathfinder[83159de6] @ ../cuda_pathfinder
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+  - conda_source: cuda-pathfinder[fa19867f] @ ../cuda_pathfinder
+- conda_source: cuda-pathfinder[15190cc4] @ ../cuda_pathfinder
+  variants:
+    target_platform: noarch
+  depends:
+  - python >=3.10
+  - python *
+  license: Apache-2.0
+  host_packages:
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-h4c7d964_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_10.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.8.1-hac47afa_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.3-hfd05255_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.53.4-hf5d6505_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.3-hf411b9b_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.6-h4b44e0e_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h967ab96_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.12.2-h7ca4a90_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-ha367084_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda
+- conda_source: cuda-pathfinder[9139f4b4] @ ../cuda_pathfinder
   variants:
     target_platform: noarch
   depends:
@@ -17056,34 +17654,75 @@ packages:
   license: Apache-2.0
   host_packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_10.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h54a6638_2.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_102.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.8.1-hecca717_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.5.2-h3435931_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-15.2.0-he0feb66_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-15.2.0-he0feb66_19.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.1.0-ha9f2e26_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-16.1.0-he0feb66_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.3-hb03c661_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.53.3-h0c1763c_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_19.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.53.4-hf4e2dac_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-16.1.0-h934c35e_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.42.2-h5347b49_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.6-hdb14827_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.3-h35e630c_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.6-habeac84_100_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.3-h35e630c_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.6-habeac84_101_cp314.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd70dff1_3.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/uv-0.11.29-h2112641_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/uv-0.12.2-h2112641_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-hbd8a1cb_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+- conda_source: cuda-pathfinder[fa19867f] @ ../cuda_pathfinder
+  variants:
+    target_platform: noarch
+  depends:
+  - python >=3.10
+  - python *
+  license: Apache-2.0
+  host_packages:
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_10.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libexpat-2.8.1-hfae3067_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libffi-3.5.2-h376a255_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgcc-16.1.0-h205dda4_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-16.1.0-h8acb6b2_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/liblzma-5.8.3-he30d5cf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libmpdec-4.0.0-he30d5cf_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsqlite-3.53.4-h022381a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-16.1.0-hef695bb_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libuuid-2.42.2-h1022ec0_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ncurses-6.6-hf8d1292_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/openssl-3.6.3-h546c87b_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/python-3.14.6-hc679e19_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/readline-8.3-hb682ff5_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tk-8.6.13-noxft_h5cf4473_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/uv-0.12.2-hbe9c82f_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h85ac4a6_6.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.3-pyhcf101f3_0.conda
+- pypi: ../cuda_python_test_helpers
+  name: cuda-python-test-helpers
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/8c/79/017fab2f7167a9a9795665f894d04f77aafceca80821b51589bb4b23ff5c/nvidia_sphinx_theme-0.0.9.post1-py3-none-any.whl
   name: nvidia-sphinx-theme
   version: 0.0.9.post1
diff --git a/cuda_bindings/pixi.toml b/cuda_bindings/pixi.toml
index 943d57e11bb..f2a7dc0a6f7 100644
--- a/cuda_bindings/pixi.toml
+++ b/cuda_bindings/pixi.toml
@@ -10,7 +10,7 @@ preview = ["pixi-build"]
 [workspace.build-variants]
 python = ["3.10.*", "3.11.*", "3.12.*", "3.13.*", "3.14.*"]
 # Keep source-package metadata aligned with the consuming environment's CUDA major.
-cuda-version = ["12.*", "13.3.*"]
+cuda-version = ["12.*", "13.4.*"]
 
 [feature.test.dependencies]
 cuda-bindings = { path = "." }
@@ -21,11 +21,14 @@ pytest-repeat = "*"
 pyglet = ">=2.1.9"
 numpy = "*"
 
+[feature.test.pypi-dependencies]
+cuda-python-test-helpers = { path = "../cuda_python_test_helpers", editable = true }
+
 # Keep this dependency set aligned with cuda_python/docs/environment-docs.yml.
 [feature.docs.dependencies]
 cuda-bindings = "13.2.*"
 python = "3.12.*"
-cython = "*"
+cython = ">=3.2.5,<3.3"
 enum_tools = "*"
 make = "*"
 myst-nb = "*"
@@ -41,7 +44,7 @@ sphinx-copybutton = "*"
 sphinx-toolbox = "*"
 
 [feature.cython-tests.dependencies]
-cython = ">=3.2,<3.3" # for tests that exercise APIs from cython
+cython = ">=3.2.5,<3.3" # for tests that exercise APIs from cython
 setuptools = "*"      # for distutils
 gxx = "*"             # to compile the generated code
 # These are necessary because running the Cython tests requires compiling
@@ -73,7 +76,7 @@ CUDA_HOME = "$CONDA_PREFIX/Library"
 cuda-version = "12.*"
 
 [feature.cu13.dependencies]
-cuda-version = "13.3.*"
+cuda-version = "13.4.*"
 
 [environments]
 default = { features = ["test", "cython-tests"], solve-group = "default" }
@@ -115,7 +118,7 @@ python = "*"
 cuda-version = "*"
 setuptools = ">=80"
 setuptools-scm = ">=8"
-cython = ">=3.2,<3.3"
+cython = ">=3.2.5,<3.3"
 cuda-pathfinder = { path = "../cuda_pathfinder" }
 cuda-cudart-static = "*"
 cuda-nvrtc-dev = "*"
diff --git a/cuda_bindings/pyproject.toml b/cuda_bindings/pyproject.toml
index 9744a0a009b..eadc58949f7 100644
--- a/cuda_bindings/pyproject.toml
+++ b/cuda_bindings/pyproject.toml
@@ -4,7 +4,7 @@
 requires = [
     "setuptools>=80.0.0",
     "setuptools_scm[simple]>=8,!=10.1",
-    "cython>=3.2,<3.3",
+    "cython>=3.2.5,<3.3",
     "cuda-pathfinder>=1.5",
 ]
 build-backend = "build_hooks"
@@ -21,7 +21,6 @@ license-files = ["LICENSE"]
 requires-python = ">=3.10"
 classifiers = [
     "Intended Audience :: Developers",
-    "Topic :: Database",
     "Topic :: Scientific/Engineering",
     "Programming Language :: Python",
     "Programming Language :: Python :: 3.10",
@@ -44,17 +43,21 @@ all = [
 
 [dependency-groups]
 test = [
-    "cython>=3.2,<3.3",
+    "cython>=3.2.5,<3.3",
     "setuptools>=80.0.0",
     # TODO: remove the Python 3.15 guard once 3.15 is officially supported
     "matplotlib>=3.5.0,<=3.10.9; python_version < '3.15'",
-    "numpy>=1.21.1,<=2.5.0",
+    # <=2.6.0.dev0 admits scientific-python nightlies (for Python 3.15)
+    "numpy>=1.21.1,<=2.6.0.dev0",
     "pytest==9.1.0",
     "pytest-benchmark==5.2.3",
     "pytest-repeat==0.9.4",
     "pytest-randomly==4.1.0",
     "pyglet==2.1.14",
 ]
+test-ft = [
+    "pytest-run-parallel==0.10.0",
+]
 
 [project.urls]
 Repository = "https://github.com/NVIDIA/cuda-python"
@@ -88,7 +91,7 @@ repair-wheel-command = "delvewheel repair --namespace-pkg cuda -w {dest_dir} {wh
 
 [tool.pytest.ini_options]
 required_plugins = "pytest-benchmark"
-addopts = "--benchmark-disable --showlocals"
+addopts = "--benchmark-disable --showlocals --durations=20"
 norecursedirs = ["tests/cython", "examples"]
 xfail_strict = true
 # Keep this authorship marker registry in sync across all pytest config roots.
diff --git a/cuda_bindings/tests/conftest.py b/cuda_bindings/tests/conftest.py
index 1618d63a133..fada7d95601 100644
--- a/cuda_bindings/tests/conftest.py
+++ b/cuda_bindings/tests/conftest.py
@@ -2,30 +2,32 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import functools
+import importlib
 import inspect
 import pathlib
 import sys
 from contextlib import contextmanager
-from importlib.metadata import PackageNotFoundError, distribution
 
 import pytest
 
 import cuda.bindings.driver as cuda
 
-# Import shared test helpers for tests across subprojects.
-# PLEASE KEEP IN SYNC with copies in other conftest.py in this repo.
-_test_helpers_root = pathlib.Path(__file__).resolve().parents[2] / "cuda_python_test_helpers"
+# Keep in sync with cuda_core/tests/conftest.py.
 try:
-    distribution("cuda-python-test-helpers")
-except PackageNotFoundError as exc:
+    import cuda_python_test_helpers._pytest_plugin  # noqa: F401
+except ImportError as e:
+    # Don't call .resolve(): resolving symlinks can make parents[2] point
+    # somewhere other than the monorepo root if a sub-directory is symlinked.
+    _test_helpers_root = pathlib.Path(__file__).parents[2] / "cuda_python_test_helpers"
     if not _test_helpers_root.is_dir():
-        raise RuntimeError(
-            f"cuda-python-test-helpers not installed; expected checkout path {_test_helpers_root}"
-        ) from exc
-
-    test_helpers_root = str(_test_helpers_root)
-    if test_helpers_root not in sys.path:
-        sys.path.insert(0, test_helpers_root)
+        raise RuntimeError(f"cuda-python-test-helpers not installed and not found at {_test_helpers_root}") from e
+    for _k in list(sys.modules):
+        if _k == "cuda_python_test_helpers" or _k.startswith("cuda_python_test_helpers."):
+            del sys.modules[_k]
+    sys.path.insert(0, str(_test_helpers_root))
+    importlib.invalidate_caches()
+
+pytest_plugins = ["cuda_python_test_helpers._pytest_plugin"]
 
 
 def pytest_configure(config):
diff --git a/cuda_bindings/tests/cython/build_tests.bat b/cuda_bindings/tests/cython/build_tests.bat
index a59bcf53d05..0ef6abb06f3 100644
--- a/cuda_bindings/tests/cython/build_tests.bat
+++ b/cuda_bindings/tests/cython/build_tests.bat
@@ -4,7 +4,9 @@ REM SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIA
 REM SPDX-License-Identifier: Apache-2.0
 
 setlocal
-	set CL=%CL% /I"%CUDA_HOME%\include"
-	REM Use -j 1 to side-step any process-pool issues and ensure deterministic single-threaded builds
-	cythonize -3 -j 1 -i -Xfreethreading_compatible=True %~dp0test_*.pyx
-endlocal
+set CL=%CL% /I"%CUDA_HOME%\include"
+REM The Python driver provides Cython's .pxd include path and builds in this
+REM directory so Windows does not duplicate the checkout path in link outputs.
+python "%~dp0build_tests.py"
+set "BUILD_RESULT=%ERRORLEVEL%"
+endlocal & exit /b %BUILD_RESULT%
diff --git a/cuda_bindings/tests/cython/build_tests.py b/cuda_bindings/tests/cython/build_tests.py
index ac22e1fd962..5bde350e87b 100644
--- a/cuda_bindings/tests/cython/build_tests.py
+++ b/cuda_bindings/tests/cython/build_tests.py
@@ -34,7 +34,10 @@ def _bindings_source_root() -> Path:
 
 def main() -> None:
     script_dir = Path(__file__).resolve().parent
-    pyx_files = sorted(str(p) for p in script_dir.glob("test_*.pyx"))
+    # Avoid appending the absolute checkout path under build/temp: the
+    # concatenated path can exceed Windows' path limit. These files are siblings.
+    os.chdir(script_dir)
+    pyx_files = sorted(p.name for p in script_dir.glob("test_*.pyx"))
     if not pyx_files:
         raise SystemExit(f"no test_*.pyx files under {script_dir}")
 
@@ -46,13 +49,8 @@ def main() -> None:
         compiler_directives={"freethreading_compatible": True},
     )
 
-    # `build_ext --inplace` places the compiled .so relative to the current
-    # working directory, but pixi runs this task from the project root. pytest
-    # imports each extension by bare module name (see test_cython.py), which
-    # only resolves when the .so sits in tests/cython (the dir pytest puts on
-    # sys.path). chdir here so the .so lands next to its .pyx regardless of the
-    # invoking cwd.
-    os.chdir(script_dir)
+    # pytest imports each extension by bare module name (see test_cython.py),
+    # so build in-place next to its .pyx regardless of the invoking cwd.
     sys.argv = [sys.argv[0], "build_ext", "--inplace"]
     setup(name="cuda_bindings_cython_tests", ext_modules=ext_modules)
 
diff --git a/cuda_bindings/tests/cython/test_ccudart.pyx b/cuda_bindings/tests/cython/test_ccudart.pyx
index 4460ceb618a..3a59f952bd3 100644
--- a/cuda_bindings/tests/cython/test_ccudart.pyx
+++ b/cuda_bindings/tests/cython/test_ccudart.pyx
@@ -59,11 +59,8 @@ cdef extern from *:
 
 def test_ccudart_interoperable():
     # struct
-    cdef dim3 oldDim, newDim
-    oldDim.x = 1
-    oldDim.y = 2
-    oldDim.z = 3
-    newDim = copy_and_append_dim3(oldDim)
+    cdef dim3 oldDim = [1, 2, 3]
+    cdef dim3 newDim = copy_and_append_dim3(oldDim)
     assert oldDim.x + 1 == newDim.x
     assert oldDim.y + 1 == newDim.y
     assert oldDim.z + 1 == newDim.z
diff --git a/cuda_bindings/tests/legacy_api/test_legacy_nvrtc.py b/cuda_bindings/tests/legacy_api/test_legacy_nvrtc.py
index 90ff6766d41..02a42b9831b 100644
--- a/cuda_bindings/tests/legacy_api/test_legacy_nvrtc.py
+++ b/cuda_bindings/tests/legacy_api/test_legacy_nvrtc.py
@@ -35,3 +35,21 @@ def test_nvrtcGetLoweredName_failure():
     err, name = nvrtc.nvrtcGetLoweredName(0, b"I'm another elevated name!")
     assert err == nvrtc.nvrtcResult.NVRTC_ERROR_INVALID_PROGRAM
     assert name is None
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+@pytest.mark.skipif(nvrtcVersionLessThan(13, 3), reason="When nvrtcGetBundledHeadersInfo was introduced")
+def test_nvrtcGetBundledHeadersInfo():
+    info = nvrtc.nvrtcBundledHeadersInfo()
+    assert isinstance(info, nvrtc.nvrtcBundledHeadersInfo)
+
+    err, info, errorLog = nvrtc.nvrtcGetBundledHeadersInfo()
+    ASSERT_DRV(err)
+    assert isinstance(info, nvrtc.nvrtcBundledHeadersInfo)
+    assert info.available in (0, 1)
+    assert info.compressedSize >= 0
+    assert info.uncompressedSize >= 0
+    assert info.cudaVersionMajor >= 0
+    assert info.cudaVersionMinor >= 0
+    assert info.numFiles >= 0
+    assert errorLog is None
diff --git a/cuda_bindings/tests/nvml/__init__.py b/cuda_bindings/tests/nvml/__init__.py
index c746f897d2d..4baf1b49bc0 100644
--- a/cuda_bindings/tests/nvml/__init__.py
+++ b/cuda_bindings/tests/nvml/__init__.py
@@ -3,8 +3,7 @@
 
 
 import pytest
-
-from cuda.bindings._test_helpers.arch_check import hardware_supports_nvml
+from cuda_python_test_helpers.arch_check import hardware_supports_nvml
 
 if not hardware_supports_nvml():
     pytest.skip("NVML not supported on this platform", allow_module_level=True)
diff --git a/cuda_bindings/tests/nvml/conftest.py b/cuda_bindings/tests/nvml/conftest.py
index eece1d5c612..29e7cb697c2 100644
--- a/cuda_bindings/tests/nvml/conftest.py
+++ b/cuda_bindings/tests/nvml/conftest.py
@@ -1,12 +1,11 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-from collections import namedtuple
 
 import pytest
+from cuda_python_test_helpers.arch_check import unsupported_before  # noqa: F401
 
 from cuda.bindings import nvml
-from cuda.bindings._test_helpers.arch_check import unsupported_before  # noqa: F401
 
 
 class NVMLInitializer:
@@ -26,63 +25,19 @@ def nvml_init():
         yield
 
 
-@pytest.fixture(scope="session", autouse=True)
-def device_info():
-    dev_count = None
-    bus_id_to_board_details = {}
-
-    BoardCfg = namedtuple("BoardCfg", "name, ids_arr")
-
-    with NVMLInitializer():
-        dev_count = nvml.device_get_count_v2()
-
-        # Store some details for each device now when we know NVML is in known state
-        for i in range(dev_count):
-            try:
-                dev = nvml.device_get_handle_by_index_v2(i)
-            except nvml.NoPermissionError:
-                continue
-
-            name = nvml.device_get_name(dev)
-            # Get architecture name ex: Ampere, Kepler
-            arch_id = nvml.device_get_architecture(dev)
-
-            try:
-                pci_info = nvml.device_get_pci_info_v3(dev)
-            except nvml.NotSupportedError:
-                board = BoardCfg(name, ids_arr=[(-1, -1)])
-                bus_id = "unknown"
-                device_id = i
-            else:
-                board = BoardCfg(name, ids_arr=[(pci_info.pci_device_id, pci_info.pci_sub_system_id)])
-                bus_id = pci_info.bus_id
-                device_id = pci_info.device_
-
-            try:
-                serial = nvml.device_get_serial(dev)
-            except nvml.NvmlError:
-                serial = None
-
-            uuid = nvml.device_get_uuid(dev)
-
-            BoardDetails = namedtuple("BoardDetails", "name, board, arch_id, bus_id, device_id, serial")
-            bus_id_to_board_details[uuid] = BoardDetails(name, board, arch_id, bus_id, device_id, serial)
-
-    return bus_id_to_board_details
-
-
-def get_devices(device_info):
-    for uuid in list(device_info.keys()):
+def get_devices():
+    dev_count = nvml.device_get_count_v2()
+    for i in range(dev_count):
         try:
-            yield nvml.device_get_handle_by_uuid(uuid)
+            yield nvml.device_get_handle_by_index_v2(i)
         except nvml.NoPermissionError:
             continue  # ignore devices that can't be accessed
 
 
 @pytest.fixture
-def all_devices(device_info):
+def all_devices():
     with NVMLInitializer():
-        yield sorted(set(get_devices(device_info)))
+        yield sorted(set(get_devices()))
 
 
 @pytest.fixture
diff --git a/cuda_bindings/tests/nvml/test_compute_mode.py b/cuda_bindings/tests/nvml/test_compute_mode.py
index 83c7827f53a..3392a71e23b 100644
--- a/cuda_bindings/tests/nvml/test_compute_mode.py
+++ b/cuda_bindings/tests/nvml/test_compute_mode.py
@@ -18,15 +18,28 @@
 
 
 @pytest.mark.skipif(sys.platform == "win32", reason="Test not supported on Windows")
-def test_compute_mode_supported_nonroot(all_devices):
+def test_compute_mode_supported_nonroot(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
+        device_index = nvml.device_get_index(device)
+        original_compute_mode = None
+        with (
+            subtests.test(device_index=device_index, compute_mode_api="get_compute_mode"),
+            unsupported_before(device, None),
+        ):
             original_compute_mode = nvml.device_get_compute_mode(device)
+        if original_compute_mode is None:
+            continue
 
         for cm in COMPUTE_MODES:
-            try:
-                nvml.device_set_compute_mode(device, cm)
-            except nvml.NoPermissionError:
-                pytest.skip("Insufficient permissions to set compute mode")
-            nvml.device_set_compute_mode(device, original_compute_mode)
-            assert original_compute_mode == nvml.device_get_compute_mode(device), "Compute mode shouldn't have changed"
+            with subtests.test(device_index=device_index, compute_mode=cm.name):
+                try:
+                    nvml.device_set_compute_mode(device, cm)
+                except nvml.NoPermissionError:
+                    pytest.skip("Insufficient permissions to set compute mode")
+                except nvml.NvmlError:
+                    nvml.device_set_compute_mode(device, original_compute_mode)
+                    raise
+                nvml.device_set_compute_mode(device, original_compute_mode)
+                assert original_compute_mode == nvml.device_get_compute_mode(device), (
+                    "Compute mode shouldn't have changed"
+                )
diff --git a/cuda_bindings/tests/nvml/test_cuda.py b/cuda_bindings/tests/nvml/test_cuda.py
index c0feedb0f8d..4b4dcfb823a 100644
--- a/cuda_bindings/tests/nvml/test_cuda.py
+++ b/cuda_bindings/tests/nvml/test_cuda.py
@@ -62,9 +62,9 @@ def test_cuda_device_order():
     cuda_devices = get_cuda_device_names()
     nvml_devices = get_nvml_device_names()
 
-    if any("Thor" in device["name"] for device in nvml_devices):
-        pytest.skip("Skipping test on Thor, which has non-standard device naming")
-        return
+    for kind in ("Orin", "Thor"):
+        if any(kind in device["name"] for device in nvml_devices):
+            pytest.skip(f"Skipping test on {kind}, which has non-standard device naming")
 
     def compare(cuda_device, nvml_device):
         return cuda_device["name"] == nvml_device["name"] and (
diff --git a/cuda_bindings/tests/nvml/test_device.py b/cuda_bindings/tests/nvml/test_device.py
index 0d412ab24bd..4eb11fc2a1a 100644
--- a/cuda_bindings/tests/nvml/test_device.py
+++ b/cuda_bindings/tests/nvml/test_device.py
@@ -39,11 +39,12 @@ def test_clk_mon_status_t():
     assert not hasattr(obj, "clk_mon_list_size")
 
 
-def test_current_clock_freqs(all_devices):
+def test_current_clock_freqs(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
-            clk_freqs = nvml.device_get_current_clock_freqs(device)
-        assert isinstance(clk_freqs, str)
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            with unsupported_before(device, None):
+                clk_freqs = nvml.device_get_current_clock_freqs(device)
+            assert isinstance(clk_freqs, str)
 
 
 def test_grid_licensable_features(all_devices):
@@ -64,24 +65,29 @@ def test_grid_licensable_features(all_devices):
                 nvml.GridLicenseExpiry(feature.license_expiry)
 
 
-def test_get_handle_by_uuidv(all_devices):
+def test_get_handle_by_uuidv(all_devices, subtests):
     for device in all_devices:
-        uuid = nvml.device_get_uuid(device)
-        new_handle = nvml.device_get_handle_by_uuidv(nvml.UUIDType.ASCII, uuid.encode("ascii"))
-        assert new_handle == device
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            uuid = nvml.device_get_uuid(device)
+            if "Orin" in nvml.device_get_name(device) and len(uuid) == 36:
+                pytest.skip("UUID lookup is unsupported on Orin, which reports a UUID without a GPU- prefix")
+            with unsupported_before(device, None):
+                new_handle = nvml.device_get_handle_by_uuidv(nvml.UUIDType.ASCII, uuid.encode("ascii"))
+            assert new_handle == device
 
 
-def test_get_nv_link_supported_bw_modes(all_devices):
+def test_get_nv_link_supported_bw_modes(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
-            modes = nvml.device_get_nvlink_supported_bw_modes(device)
-        assert isinstance(modes, nvml.NvlinkSupportedBwModes_v1)
-        # #define NVML_NVLINK_TOTAL_SUPPORTED_BW_MODES 23
-        assert len(modes.bw_modes) <= 23
-        assert not hasattr(modes, "total_bw_modes")
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            with unsupported_before(device, None):
+                modes = nvml.device_get_nvlink_supported_bw_modes(device)
+            assert isinstance(modes, nvml.NvlinkSupportedBwModes_v1)
+            # #define NVML_NVLINK_TOTAL_SUPPORTED_BW_MODES 23
+            assert len(modes.bw_modes) <= 23
+            assert not hasattr(modes, "total_bw_modes")
 
-        for mode in modes.bw_modes:
-            assert isinstance(mode, np.uint8)
+            for mode in modes.bw_modes:
+                assert isinstance(mode, np.uint8)
 
 
 def test_device_get_pdi(all_devices):
@@ -91,62 +97,70 @@ def test_device_get_pdi(all_devices):
             assert isinstance(pdi, int)
 
 
-def test_device_get_performance_modes(all_devices):
+def test_device_get_performance_modes(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
-            modes = nvml.device_get_performance_modes(device)
-        assert isinstance(modes, str)
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            with unsupported_before(device, None):
+                modes = nvml.device_get_performance_modes(device)
+            assert isinstance(modes, str)
 
 
 @pytest.mark.skipif(cuda_version_less_than(13010), reason="Introduced in 13.1")
-def test_device_get_unrepairable_memory_flag(all_devices):
+def test_device_get_unrepairable_memory_flag(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
-            status = nvml.device_get_unrepairable_memory_flag_v1(device)
-        assert isinstance(status, int)
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            with unsupported_before(device, None):
+                status = nvml.device_get_unrepairable_memory_flag_v1(device)
+            assert isinstance(status, int)
 
 
-def test_device_vgpu_get_heterogeneous_mode(all_devices):
+def test_device_vgpu_get_heterogeneous_mode(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
-            mode = nvml.device_get_vgpu_heterogeneous_mode(device)
-        assert isinstance(mode, int)
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            with unsupported_before(device, None):
+                mode = nvml.device_get_vgpu_heterogeneous_mode(device)
+            assert isinstance(mode, int)
 
 
 @pytest.mark.skipif(cuda_version_less_than(13010), reason="Introduced in 13.1")
-def test_read_prm_counters(all_devices):
+def test_read_prm_counters(all_devices, subtests):
     for device in all_devices:
-        counters = nvml.PRMCounter_v1(5)
-        with unsupported_before(device, None):
-            read_counters = nvml.device_read_prm_counters_v1(device, counters)
-        assert counters is read_counters
-        assert len(read_counters) == 5
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            counters = nvml.PRMCounter_v1(5)
+            with unsupported_before(device, None):
+                read_counters = nvml.device_read_prm_counters_v1(device, counters)
+            assert counters is read_counters
+            assert len(read_counters) == 5
 
 
 @pytest.mark.thread_unsafe(reason="API appears to be thread-unsafe (2026-06)")
-def test_read_write_prm(all_devices):
+def test_read_write_prm(all_devices, subtests):
     for device in all_devices:
-        # Docs say supported in BLACKWELL or later
-        with unsupported_before(device, None):
-            try:
-                result = nvml.device_read_write_prm_v1(device, b"012345678")
-            except nvml.NoPermissionError:
-                pytest.skip("No permission to read/write PRM")
-        assert isinstance(result, tuple)
-        assert isinstance(result[0], int)
-        assert isinstance(result[1], bytes)
-
-
-def test_get_power_management_limit(all_devices):
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            # Docs say supported in BLACKWELL or later
+            with unsupported_before(device, None):
+                try:
+                    result = nvml.device_read_write_prm_v1(device, b"012345678")
+                except nvml.NoPermissionError:
+                    pytest.skip("No permission to read/write PRM")
+            assert isinstance(result, tuple)
+            assert isinstance(result[0], int)
+            assert isinstance(result[1], bytes)
+
+
+def test_get_power_management_limit(all_devices, subtests):
     for device in all_devices:
         # Docs say supported on KEPLER or later
-        with unsupported_before(device, None):
+        with subtests.test(device_index=nvml.device_get_index(device)), unsupported_before(device, None):
             nvml.device_get_power_management_limit(device)
 
 
-def test_set_power_management_limit(all_devices):
+def test_set_power_management_limit(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
+        with (
+            subtests.test(device_index=nvml.device_get_index(device)),
+            unsupported_before(device, None),
+        ):
             try:
                 nvml.device_set_power_management_limit_v2(device, nvml.PowerScope.GPU, 10000)
             except nvml.NoPermissionError:
@@ -155,18 +169,19 @@ def test_set_power_management_limit(all_devices):
                 pytest.skip("Invalid argument when setting power management limit -- probably unsupported")
 
 
-def test_set_temperature_threshold(all_devices):
+def test_set_temperature_threshold(all_devices, subtests):
     for device in all_devices:
-        # Docs say supported on MAXWELL or newer
-        with unsupported_before(device, None):
-            temp = nvml.device_get_temperature_threshold(
-                device, nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_CURR
-            )
-        try:
-            nvml.device_set_temperature_threshold(
-                device, nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_CURR, temp
-            )
-        except nvml.NoPermissionError:
-            pytest.skip("No permission to set temperature threshold")
-        except nvml.InvalidArgumentError:
-            pytest.skip("Invalid argument when setting temperature threshold -- this is probably the temp type")
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            # Docs say supported on MAXWELL or newer
+            with unsupported_before(device, None):
+                temp = nvml.device_get_temperature_threshold(
+                    device, nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_CURR
+                )
+            try:
+                nvml.device_set_temperature_threshold(
+                    device, nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_CURR, temp
+                )
+            except nvml.NoPermissionError:
+                pytest.skip("No permission to set temperature threshold")
+            except nvml.InvalidArgumentError:
+                pytest.skip("Invalid argument when setting temperature threshold -- this is probably the temp type")
diff --git a/cuda_bindings/tests/nvml/test_gpu.py b/cuda_bindings/tests/nvml/test_gpu.py
index 6757e4760f1..74d4f7489dc 100644
--- a/cuda_bindings/tests/nvml/test_gpu.py
+++ b/cuda_bindings/tests/nvml/test_gpu.py
@@ -10,7 +10,7 @@
 from .conftest import unsupported_before
 
 
-def test_gpu_get_module_id(nvml_init):
+def test_gpu_get_module_id(nvml_init, subtests):
     # Unique module IDs cannot exceed the number of GPUs on the system
     device_count = nvml.device_get_count_v2()
 
@@ -21,23 +21,25 @@ def test_gpu_get_module_id(nvml_init):
         if util.is_vgpu(device):
             continue
 
-        with unsupported_before(device, None):
-            module_id = nvml.device_get_module_id(device)
-        assert isinstance(module_id, int)
+        with subtests.test(device_index=i):
+            with unsupported_before(device, None):
+                module_id = nvml.device_get_module_id(device)
+            assert isinstance(module_id, int)
 
 
-def test_gpu_get_platform_info(all_devices):
+def test_gpu_get_platform_info(all_devices, subtests):
     for device in all_devices:
-        if util.is_vgpu(device):
-            pytest.skip(f"Not supported on vGPU device {device}")
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            if util.is_vgpu(device):
+                pytest.skip(f"Not supported on vGPU device {device}")
 
-        # Documentation says Blackwell or newer only, but this does seem to pass
-        # on some newer GPUs.
+            # Documentation says Blackwell or newer only, but this does seem to pass
+            # on some newer GPUs.
 
-        with unsupported_before(device, None):
-            platform_info = nvml.device_get_platform_info(device)
+            with unsupported_before(device, None):
+                platform_info = nvml.device_get_platform_info(device)
 
-        assert isinstance(platform_info, (nvml.PlatformInfo_v1, nvml.PlatformInfo_v2))
+            assert isinstance(platform_info, (nvml.PlatformInfo_v1, nvml.PlatformInfo_v2))
 
 
 # TODO: Test APIs related to GPU instances, which require specific hardware and root
@@ -58,10 +60,14 @@ def test_conf_compute_attestation_report_t(all_devices):
     assert report.nonce.dtype == np.uint8
 
 
-def test_gpu_conf_compute_attestation_report(all_devices):
+def test_gpu_conf_compute_attestation_report(all_devices, subtests):
     for device in all_devices:
         # Documentation says AMPERE or newer
-        with unsupported_before(device, None), pytest.raises(nvml.UnknownError):
+        with (
+            subtests.test(device_index=nvml.device_get_index(device)),
+            unsupported_before(device, None),
+            pytest.raises(nvml.UnknownError),
+        ):
             # The nonce string is nonsensical, so if this "works", we expect an UnknownError
             nvml.device_get_conf_compute_gpu_attestation_report(device, nonce=b"12345678")
 
@@ -74,9 +80,13 @@ def test_conf_compute_gpu_certificate_t():
     assert len(cert.attestation_cert_chain) == 0
 
 
-def test_conf_compute_gpu_certificate(all_devices):
+def test_conf_compute_gpu_certificate(all_devices, subtests):
     for device in all_devices:
         # Documentation says AMPERE or newer
-        with unsupported_before(device, None), pytest.raises(nvml.UnknownError):
+        with (
+            subtests.test(device_index=nvml.device_get_index(device)),
+            unsupported_before(device, None),
+            pytest.raises(nvml.UnknownError),
+        ):
             # This is expected to fail if the device doesn't have a proper certificate
             nvml.device_get_conf_compute_gpu_certificate(device)
diff --git a/cuda_bindings/tests/nvml/test_init.py b/cuda_bindings/tests/nvml/test_init.py
index a47af24dc6a..c56c400a0b9 100644
--- a/cuda_bindings/tests/nvml/test_init.py
+++ b/cuda_bindings/tests/nvml/test_init.py
@@ -7,6 +7,7 @@
 import pytest
 
 from cuda.bindings import nvml
+from cuda_python_test_helpers import driver_version_less_than
 
 
 def assert_nvml_is_initialized():
@@ -43,6 +44,7 @@ def get_architecture_name(arch):
 
 @pytest.mark.skipif(sys.platform == "win32", reason="Test not supported on Windows")
 @pytest.mark.thread_unsafe(reason="nvml init affects other threads")
+@pytest.mark.skipif(not driver_version_less_than(13040), reason="Init behavior changed in CUDA 13.4")
 def test_init_ref_count():
     """
     Verifies that we can call NVML shutdown and init(2) multiple times, and that ref counting works
diff --git a/cuda_bindings/tests/nvml/test_nvlink.py b/cuda_bindings/tests/nvml/test_nvlink.py
index 04bc8eaae4c..1ea9e25dfa7 100644
--- a/cuda_bindings/tests/nvml/test_nvlink.py
+++ b/cuda_bindings/tests/nvml/test_nvlink.py
@@ -27,8 +27,3 @@ def test_nvlink_get_link_count(all_devices):
         assert value.nvml_return == nvml.Return.SUCCESS or value.nvml_return == nvml.Return.ERROR_NOT_SUPPORTED, (
             f"Unexpected return {value.nvml_return} for link count field query"
         )
-
-        # The feature_nvlink_supported detection is not robust, so we
-        # can't be more specific about how many links we should find.
-        if value.nvml_return == nvml.Return.SUCCESS:
-            assert value.value.ui_val[0] <= nvml.NVLINK_MAX_LINKS, f"Unexpected link count {value.value.ui_val[0]}"
diff --git a/cuda_bindings/tests/nvml/test_pci.py b/cuda_bindings/tests/nvml/test_pci.py
index 74c7a65a655..877f9d2998a 100644
--- a/cuda_bindings/tests/nvml/test_pci.py
+++ b/cuda_bindings/tests/nvml/test_pci.py
@@ -9,12 +9,13 @@
 from .conftest import unsupported_before
 
 
-def test_discover_gpus(all_devices):
+def test_discover_gpus(all_devices, subtests):
     for device in all_devices:
-        pci_info = nvml.device_get_pci_info_v3(device)
-        # Docs say this should be supported on PASCAL and later
-        with unsupported_before(device, None), contextlib.suppress(nvml.OperatingSystemError):
-            nvml.device_discover_gpus(pci_info.ptr)
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            pci_info = nvml.device_get_pci_info_v3(device)
+            # Docs say this should be supported on PASCAL and later
+            with unsupported_before(device, None), contextlib.suppress(nvml.OperatingSystemError):
+                nvml.device_discover_gpus(pci_info.ptr)
 
 
 def test_bridge_chip_hierarchy_t():
@@ -24,12 +25,13 @@ def test_bridge_chip_hierarchy_t():
     assert isinstance(hierarchy.bridge_chip_info, nvml.BridgeChipInfo)
 
 
-def test_bridge_chip_info(all_devices):
+def test_bridge_chip_info(all_devices, subtests):
     for device in all_devices:
-        with unsupported_before(device, None):
-            info = nvml.device_get_bridge_chip_info(device)
-        assert isinstance(info, nvml.BridgeChipHierarchy)
-        for entry in info.bridge_chip_info:
-            assert isinstance(entry, nvml.BridgeChipInfo)
-            assert isinstance(entry.type, int)
-            assert isinstance(entry.fw_version, int)
+        with subtests.test(device_index=nvml.device_get_index(device)):
+            with unsupported_before(device, None):
+                info = nvml.device_get_bridge_chip_info(device)
+            assert isinstance(info, nvml.BridgeChipHierarchy)
+            for entry in info.bridge_chip_info:
+                assert isinstance(entry, nvml.BridgeChipInfo)
+                assert isinstance(entry.type, int)
+                assert isinstance(entry.fw_version, int)
diff --git a/cuda_bindings/tests/nvml/test_pynvml.py b/cuda_bindings/tests/nvml/test_pynvml.py
index 075f44b49b2..57b0b8c0f1c 100644
--- a/cuda_bindings/tests/nvml/test_pynvml.py
+++ b/cuda_bindings/tests/nvml/test_pynvml.py
@@ -4,13 +4,12 @@
 # A set of tests ported from https://github.com/gpuopenanalytics/pynvml/blob/11.5.3/pynvml/tests/test_nvml.py
 
 import os
-import time
 
 import pytest
 
 from cuda.bindings import nvml
+from cuda_python_test_helpers import IS_WINDOWS, IS_WSL
 
-from . import util
 from .conftest import unsupported_before
 
 XFAIL_LEGACY_NVLINK_MSG = "Legacy NVLink test expected to fail."
@@ -53,9 +52,13 @@ def test_device_get_attributes(mig_handles):
         pytest.skip("No MIG devices found")
 
 
-def test_device_get_handle_by_uuid(ngpus, uuids):
-    handles = [nvml.device_get_handle_by_uuid(uuids[i]) for i in range(ngpus)]
-    assert len(handles) == ngpus
+def test_device_get_handle_by_uuid(ngpus, handles, uuids, subtests):
+    for i in range(ngpus):
+        with subtests.test(device_index=i):
+            uuid = uuids[i]
+            if "Orin" in nvml.device_get_name(handles[i]) and len(uuid) == 36:
+                pytest.skip("UUID lookup is unsupported on Orin, which reports a UUID without a GPU- prefix")
+            assert nvml.device_get_handle_by_uuid(uuid) == handles[i]
 
 
 def test_device_get_handle_by_pci_bus_id(ngpus):
@@ -71,25 +74,27 @@ def test_device_get_handle_by_pci_bus_id(ngpus):
 
 
 @pytest.mark.parametrize("scope", [nvml.AffinityScope.NODE, nvml.AffinityScope.SOCKET])
-@pytest.mark.skipif(util.is_wsl() or util.is_windows(), reason="Not supported on WSL or Windows")
-def test_device_get_memory_affinity(handles, scope):
+@pytest.mark.skipif(IS_WSL or IS_WINDOWS, reason="Not supported on WSL or Windows")
+def test_device_get_memory_affinity(handles, scope, subtests):
     size = 1024
-    for handle in handles:
-        with unsupported_before(handle, nvml.DeviceArch.KEPLER):
-            node_set = nvml.device_get_memory_affinity(handle, size, scope)
-        assert node_set is not None
-        assert len(node_set) == size
+    for device_index, handle in enumerate(handles):
+        with subtests.test(device_index=device_index):
+            with unsupported_before(handle, None):
+                node_set = nvml.device_get_memory_affinity(handle, size, scope)
+            assert node_set is not None
+            assert len(node_set) == size
 
 
 @pytest.mark.parametrize("scope", [nvml.AffinityScope.NODE, nvml.AffinityScope.SOCKET])
-@pytest.mark.skipif(util.is_wsl() or util.is_windows(), reason="Not supported on WSL or Windows")
-def test_device_get_cpu_affinity_within_scope(handles, scope):
+@pytest.mark.skipif(IS_WSL or IS_WINDOWS, reason="Not supported on WSL or Windows")
+def test_device_get_cpu_affinity_within_scope(handles, scope, subtests):
     size = 1024
-    for handle in handles:
-        with unsupported_before(handle, nvml.DeviceArch.KEPLER):
-            cpu_set = nvml.device_get_cpu_affinity_within_scope(handle, size, scope)
-        assert cpu_set is not None
-        assert len(cpu_set) == size
+    for device_index, handle in enumerate(handles):
+        with subtests.test(device_index=device_index):
+            with unsupported_before(handle, None):
+                cpu_set = nvml.device_get_cpu_affinity_within_scope(handle, size, scope)
+            assert cpu_set is not None
+            assert len(cpu_set) == size
 
 
 @pytest.mark.parametrize(
@@ -150,29 +155,14 @@ def test_device_get_p2p_status(handles, index):
 # [Skipping] pynvml.nvmlDeviceGetEnforcedPowerLimit
 
 
-def test_device_get_power_usage(ngpus, handles):
-    for i in range(ngpus):
-        # Note: documentation says this is supported on Fermi or newer,
-        # but in practice it fails on some later architectures.
-        with unsupported_before(handles[i], None):
-            power_mwatts = nvml.device_get_power_usage(handles[i])
-        assert power_mwatts >= 0.0
-
-
-def test_device_get_total_energy_consumption(ngpus, handles):
+def test_device_get_power_usage(ngpus, handles, subtests):
     for i in range(ngpus):
-        with unsupported_before(handles[i], None):
-            energy_mjoules1 = nvml.device_get_total_energy_consumption(handles[i])
-
-        for j in range(10):  # idle for 150 ms
-            time.sleep(0.015)  # and check for increase every 15 ms
+        with subtests.test(device_index=i):
+            # Note: documentation says this is supported on Fermi or newer,
+            # but in practice it fails on some later architectures.
             with unsupported_before(handles[i], None):
-                energy_mjoules2 = nvml.device_get_total_energy_consumption(handles[i])
-            assert energy_mjoules2 >= energy_mjoules1
-            if energy_mjoules2 > energy_mjoules1:
-                break
-        else:
-            raise AssertionError("energy did not increase across 150 ms interval")
+                power_mwatts = nvml.device_get_power_usage(handles[i])
+            assert power_mwatts >= 0.0
 
 
 # [Skipping] pynvml.nvmlDeviceGetGpuOperationMode
@@ -180,11 +170,12 @@ def test_device_get_total_energy_consumption(ngpus, handles):
 # [Skipping] pynvml.nvmlDeviceGetPendingGpuOperationMode
 
 
-def test_device_get_memory_info(ngpus, handles):
+def test_device_get_memory_info(ngpus, handles, subtests):
     for i in range(ngpus):
-        with unsupported_before(handles[i], None):
-            meminfo = nvml.device_get_memory_info_v2(handles[i])
-        assert (meminfo.used <= meminfo.total) and (meminfo.free <= meminfo.total)
+        with subtests.test(device_index=i):
+            with unsupported_before(handles[i], None):
+                meminfo = nvml.device_get_memory_info_v2(handles[i])
+            assert (meminfo.used <= meminfo.total) and (meminfo.free <= meminfo.total)
 
 
 # [Skipping] pynvml.nvmlDeviceGetBAR1MemoryInfo
@@ -197,12 +188,13 @@ def test_device_get_memory_info(ngpus, handles):
 # [Skipping] pynvml.nvmlDeviceGetMemoryErrorCounter
 
 
-def test_device_get_utilization_rates(ngpus, handles):
+def test_device_get_utilization_rates(ngpus, handles, subtests):
     for i in range(ngpus):
-        with unsupported_before(handles[i], None):
-            urate = nvml.device_get_utilization_rates(handles[i])
-        assert urate.gpu >= 0
-        assert urate.memory >= 0
+        with subtests.test(device_index=i):
+            with unsupported_before(handles[i], None):
+                urate = nvml.device_get_utilization_rates(handles[i])
+            assert urate.gpu >= 0
+            assert urate.memory >= 0
 
 
 # [Skipping] pynvml.nvmlDeviceGetEncoderUtilization
@@ -255,14 +247,15 @@ def test_device_get_utilization_rates(ngpus, handles):
 # [Skipping] pynvml.nvmlDeviceGetViolationStatus
 
 
-def test_device_get_pcie_throughput(ngpus, handles):
+def test_device_get_pcie_throughput(ngpus, handles, subtests):
     for i in range(ngpus):
-        with unsupported_before(handles[i], None):
-            tx_bytes_tp = nvml.device_get_pcie_throughput(handles[i], nvml.PcieUtilCounter.PCIE_UTIL_TX_BYTES)
-        assert tx_bytes_tp >= 0
-        with unsupported_before(handles[i], None):
-            rx_bytes_tp = nvml.device_get_pcie_throughput(handles[i], nvml.PcieUtilCounter.PCIE_UTIL_RX_BYTES)
-        assert rx_bytes_tp >= 0
+        with subtests.test(device_index=i):
+            with unsupported_before(handles[i], None):
+                tx_bytes_tp = nvml.device_get_pcie_throughput(handles[i], nvml.PcieUtilCounter.PCIE_UTIL_TX_BYTES)
+            assert tx_bytes_tp >= 0
+            with unsupported_before(handles[i], None):
+                rx_bytes_tp = nvml.device_get_pcie_throughput(handles[i], nvml.PcieUtilCounter.PCIE_UTIL_RX_BYTES)
+            assert rx_bytes_tp >= 0
 
         # with pytest.raises(nvml.InvalidArgumentError):
         #     nvml.device_get_pcie_throughput(handles[i], nvml.PcieUtilCounter.PCIE_UTIL_COUNT)
@@ -277,27 +270,6 @@ def test_device_get_pcie_throughput(ngpus, handles):
 # Test pynvml.nvmlDeviceGetNvLinkRemotePciInfo
 
 
-@pytest.mark.parametrize(
-    "cap_type",
-    [
-        nvml.NvLinkCapability.NVLINK_CAP_P2P_SUPPORTED,  # P2P over NVLink is supported
-        nvml.NvLinkCapability.NVLINK_CAP_SYSMEM_ACCESS,  # Access to system memory is supported
-        nvml.NvLinkCapability.NVLINK_CAP_P2P_ATOMICS,  # P2P atomics are supported
-        nvml.NvLinkCapability.NVLINK_CAP_SYSMEM_ATOMICS,  # System memory atomics are supported
-        nvml.NvLinkCapability.NVLINK_CAP_SLI_BRIDGE,  # SLI is supported over this link
-        nvml.NvLinkCapability.NVLINK_CAP_VALID,
-    ],
-)  # Link is supported on this device
-def test_device_get_nvlink_capability(ngpus, handles, cap_type):
-    for i in range(ngpus):
-        for j in range(nvml.NVLINK_MAX_LINKS):
-            # By the documentation, this should be supported on PASCAL or newer,
-            # but this also seems to fail on newer.
-            with unsupported_before(handles[i], None):
-                cap = nvml.device_get_nvlink_capability(handles[i], j, cap_type)
-            assert cap >= 0
-
-
 # Test pynvml.nvmlDeviceResetNvLinkUtilizationCounter
 # Test pynvml.nvmlDeviceSetNvLinkUtilizationControl
 # Test pynvml.nvmlDeviceGetNvLinkUtilizationCounter
diff --git a/cuda_bindings/tests/nvml/test_util.py b/cuda_bindings/tests/nvml/test_util.py
new file mode 100644
index 00000000000..2eb46647777
--- /dev/null
+++ b/cuda_bindings/tests/nvml/test_util.py
@@ -0,0 +1,28 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+
+import pytest
+
+from cuda.bindings import nvml
+
+from . import util
+
+
+class _FakeFieldValue:
+    nvml_return = nvml.Return.SUCCESS
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_supports_nvlink_queries_a_real_field_id(monkeypatch):
+    """The helper has to name an enum that exists; nvml.FI never did."""
+    queried = {}
+
+    def fake_device_get_field_values(device, fields):
+        queried["field_id"] = fields[0].field_id
+        return [_FakeFieldValue()]
+
+    monkeypatch.setattr(nvml, "device_get_field_values", fake_device_get_field_values)
+
+    assert util.supports_nvlink(object()) is True
+    assert queried["field_id"] == nvml.FieldId.DEV_NVLINK_GET_STATE
diff --git a/cuda_bindings/tests/nvml/util.py b/cuda_bindings/tests/nvml/util.py
index 038fe58d8be..7d63a141706 100644
--- a/cuda_bindings/tests/nvml/util.py
+++ b/cuda_bindings/tests/nvml/util.py
@@ -2,29 +2,8 @@
 # SPDX-License-Identifier: Apache-2.0
 
 
-import functools
-import platform
-from pathlib import Path
-
 from cuda.bindings import nvml
 
-current_os = platform.system()
-if current_os == "VMkernel":
-    current_os = "Linux"  # Treat VMkernel as Linux
-
-
-def is_windows(os=current_os):
-    return os == "Windows"
-
-
-def is_linux(os=current_os):
-    return os == "Linux"
-
-
-@functools.cache
-def is_wsl(os=current_os):
-    return os == "Linux" and "microsoft" in Path("/proc/version").read_text().lower()
-
 
 def is_vgpu(device):
     """
@@ -43,5 +22,5 @@ def supports_ecc(device):
 
 def supports_nvlink(device):
     fields = nvml.FieldValue(1)
-    fields[0].field_id = nvml.FI.DEV_NVLINK_GET_STATE
+    fields[0].field_id = nvml.FieldId.DEV_NVLINK_GET_STATE
     return nvml.device_get_field_values(device, fields)[0].nvml_return == nvml.Return.SUCCESS
diff --git a/cuda_bindings/tests/test_cuda.py b/cuda_bindings/tests/test_cuda.py
index 423b667ead5..18c3c0e9d80 100644
--- a/cuda_bindings/tests/test_cuda.py
+++ b/cuda_bindings/tests/test_cuda.py
@@ -10,19 +10,12 @@
 
 import numpy as np
 import pytest
+from cuda_python_test_helpers.mempool import xfail_if_mempool_oom
 
 import cuda.bindings.driver as cuda
 import cuda.bindings.runtime as cudart
 from cuda.bindings import driver
-from cuda.bindings._test_helpers.mempool import xfail_if_mempool_oom
-
-
-def driverVersionLessThan(target):
-    (err,) = cuda.cuInit(0)
-    assert err == cuda.CUresult.CUDA_SUCCESS
-    err, version = cuda.cuDriverGetVersion()
-    assert err == cuda.CUresult.CUDA_SUCCESS
-    return version < target
+from cuda_python_test_helpers import driver_version_less_than
 
 
 def supportsMemoryPool():
@@ -265,7 +258,7 @@ def test_cuda_CUstreamBatchMemOpParams():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(11030) or not supportsMemoryPool(), reason="When new attributes were introduced"
+    driver_version_less_than(11030) or not supportsMemoryPool(), reason="When new attributes were introduced"
 )
 def test_cuda_memPool_attr():
     poolProps = cuda.CUmemPoolProps()
@@ -328,7 +321,7 @@ def test_cuda_memPool_attr():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(11030) or not supportsManagedMemory(), reason="When new attributes were introduced"
+    driver_version_less_than(11030) or not supportsManagedMemory(), reason="When new attributes were introduced"
 )
 def test_cuda_pointer_attr():
     err, ptr = cuda.cuMemAllocManaged(0x1000, cuda.CUmemAttach_flags.CU_MEM_ATTACH_GLOBAL.value)
@@ -379,7 +372,7 @@ def test_cuda_pointer_attr():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(11030) or not supportsManagedMemory(), reason="When new attributes were introduced"
+    driver_version_less_than(11030) or not supportsManagedMemory(), reason="When new attributes were introduced"
 )
 def test_pointer_get_attributes_device_ordinal():
     attributes = [
@@ -457,7 +450,9 @@ def test_cuda_mem_range_attr(device):
     assert err == cuda.CUresult.CUDA_SUCCESS
 
 
-@pytest.mark.skipif(driverVersionLessThan(11040) or not supportsMemoryPool(), reason="Mempool for graphs not supported")
+@pytest.mark.skipif(
+    driver_version_less_than(11040) or not supportsMemoryPool(), reason="Mempool for graphs not supported"
+)
 @pytest.mark.thread_unsafe(reason="used high memory can be higher if threaded.")
 def test_cuda_graphMem_attr(device):
     err, stream = cuda.cuStreamCreate(0)
@@ -516,7 +511,7 @@ def test_cuda_graphMem_attr(device):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(12010)
+    driver_version_less_than(12010)
     or not supportsCudaAPI("cuCoredumpSetAttributeGlobal")
     or not supportsCudaAPI("cuCoredumpGetAttributeGlobal"),
     reason="Coredump API not present",
@@ -566,7 +561,7 @@ def test_get_error_name_and_string():
 
 
 # TODO: cuStreamGetCaptureInfo_v2
-@pytest.mark.skipif(driverVersionLessThan(11030), reason="Driver too old for cuStreamGetCaptureInfo_v2")
+@pytest.mark.skipif(driver_version_less_than(11030), reason="Driver too old for cuStreamGetCaptureInfo_v2")
 def test_stream_capture():
     pass
 
@@ -636,7 +631,7 @@ def test_invalid_repr_attribute():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(12020)
+    driver_version_less_than(12020)
     or not supportsCudaAPI("cuGraphAddNode")
     or not supportsCudaAPI("cuGraphNodeSetParams")
     or not supportsCudaAPI("cuGraphExecNodeSetParams"),
@@ -748,7 +743,7 @@ def test_graph_poly():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(12040) or not supportsCudaAPI("cuDeviceGetDevResource"),
+    driver_version_less_than(12040) or not supportsCudaAPI("cuDeviceGetDevResource"),
     reason="Polymorphic graph APIs required",
 )
 def test_cuDeviceGetDevResource(device):
@@ -768,7 +763,7 @@ def test_cuDeviceGetDevResource(device):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(12030) or not supportsCudaAPI("cuGraphConditionalHandleCreate"),
+    driver_version_less_than(12030) or not supportsCudaAPI("cuGraphConditionalHandleCreate"),
     reason="Conditional graph APIs required",
 )
 def test_conditional(ctx):
@@ -830,14 +825,14 @@ def test_all_CUresult_codes():
     assert num_good >= 76  # CTK 11.0.3_450.51.06
 
 
-@pytest.mark.skipif(driverVersionLessThan(12030), reason="Driver too old for cuKernelGetName")
+@pytest.mark.skipif(driver_version_less_than(12030), reason="Driver too old for cuKernelGetName")
 def test_cuKernelGetName_failure():
     err, name = cuda.cuKernelGetName(0)
     assert err == cuda.CUresult.CUDA_ERROR_INVALID_VALUE
     assert name is None
 
 
-@pytest.mark.skipif(driverVersionLessThan(12030), reason="Driver too old for cuFuncGetName")
+@pytest.mark.skipif(driver_version_less_than(12030), reason="Driver too old for cuFuncGetName")
 def test_cuFuncGetName_failure():
     err, name = cuda.cuFuncGetName(0)
     assert err == cuda.CUresult.CUDA_ERROR_INVALID_VALUE
@@ -845,7 +840,7 @@ def test_cuFuncGetName_failure():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(12080) or not supportsCudaAPI("cuCheckpointProcessGetState"),
+    driver_version_less_than(12080) or not supportsCudaAPI("cuCheckpointProcessGetState"),
     reason="When API was introduced",
 )
 def test_cuCheckpointProcessGetState_failure():
@@ -887,7 +882,7 @@ def test_struct_pointer_comparison(target):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cuGraphGetId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cuGraphGetId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cuGraphGetId(device, ctx):
@@ -914,7 +909,7 @@ def test_cuGraphGetId(device, ctx):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cuGraphExecGetId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cuGraphExecGetId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cuGraphExecGetId(device, ctx):
@@ -1046,7 +1041,7 @@ def test_cuGraphNodeGetDependencies_edgeData_outlives_call(device, ctx):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cuGraphNodeGetLocalId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cuGraphNodeGetLocalId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cuGraphNodeGetLocalId(device, ctx):
@@ -1088,7 +1083,7 @@ def test_cuGraphNodeGetLocalId(device, ctx):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cuGraphNodeGetToolsId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cuGraphNodeGetToolsId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cuGraphNodeGetToolsId(device, ctx):
@@ -1117,7 +1112,7 @@ def test_cuGraphNodeGetToolsId(device, ctx):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cuGraphNodeGetContainingGraph"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cuGraphNodeGetContainingGraph"),
     reason="Requires CUDA 13.1+",
 )
 def test_cuGraphNodeGetContainingGraph(device, ctx):
@@ -1164,7 +1159,7 @@ def test_cuGraphNodeGetContainingGraph(device, ctx):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cuStreamGetDevResource"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cuStreamGetDevResource"),
     reason="Requires CUDA 13.1+",
 )
 def test_cuStreamGetDevResource(device, ctx):
@@ -1183,7 +1178,7 @@ def test_cuStreamGetDevResource(device, ctx):
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cuDevSmResourceSplit"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cuDevSmResourceSplit"),
     reason="Requires CUDA 13.1+",
 )
 def test_cuDevSmResourceSplit(device, ctx):
diff --git a/cuda_bindings/tests/test_cudart.py b/cuda_bindings/tests/test_cudart.py
index f0f289170c4..53702280679 100644
--- a/cuda_bindings/tests/test_cudart.py
+++ b/cuda_bindings/tests/test_cudart.py
@@ -6,12 +6,13 @@
 
 import numpy as np
 import pytest
+from cuda_python_test_helpers.mempool import xfail_if_mempool_oom
 
 import cuda.bindings.driver as cuda
 import cuda.bindings.runtime as cudart
 from cuda import pathfinder
 from cuda.bindings import runtime
-from cuda.bindings._test_helpers.mempool import xfail_if_mempool_oom
+from cuda_python_test_helpers import driver_version_less_than
 
 
 def isSuccess(err):
@@ -22,12 +23,6 @@ def assertSuccess(err):
     assert isSuccess(err)
 
 
-def driverVersionLessThan(target):
-    err, version = cudart.cudaDriverGetVersion()
-    assertSuccess(err)
-    return version < target
-
-
 def supportsMemoryPool():
     err, isSupported = cudart.cudaDeviceGetAttribute(cudart.cudaDeviceAttr.cudaDevAttrMemoryPoolsSupported, 0)
     return isSuccess(err) and isSupported
@@ -39,7 +34,16 @@ def supportsSparseTexturesDeviceFilter():
 
 
 def supportsCudaAPI(name):
-    return name in dir(cuda) or dir(cudart)
+    return name in dir(cuda) or name in dir(cudart)
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_supportsCudaAPI():
+    # Guards the operator precedence: `name in dir(cuda) or dir(cudart)` parses
+    # as `(name in dir(cuda)) or dir(cudart)`, which is truthy for every name.
+    assert supportsCudaAPI("cudaMalloc") is True  # runtime module
+    assert supportsCudaAPI("cuInit") is True  # driver module
+    assert supportsCudaAPI("this_is_not_a_cuda_api") is False
 
 
 def test_cudart_memcpy():
@@ -510,7 +514,7 @@ def test_cudart_cudaGetDeviceProperties():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(11030) or not supportsMemoryPool(), reason="When new attributes were introduced"
+    driver_version_less_than(11030) or not supportsMemoryPool(), reason="When new attributes were introduced"
 )
 def test_cudart_MemPool_attr():
     poolProps = cudart.cudaMemPoolProps()
@@ -1451,7 +1455,7 @@ def test_cudart_func_callback():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(12030) or not supportsCudaAPI("cudaGraphConditionalHandleCreate"),
+    driver_version_less_than(12030) or not supportsCudaAPI("cudaGraphConditionalHandleCreate"),
     reason="Conditional graph APIs required",
 )
 def test_cudart_conditional():
@@ -1509,7 +1513,7 @@ def test_getLocalRuntimeVersion():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaGraphGetId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaGraphGetId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaGraphGetId():
@@ -1536,7 +1540,7 @@ def test_cudaGraphGetId():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaGraphExecGetId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaGraphExecGetId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaGraphExecGetId():
@@ -1583,7 +1587,7 @@ def test_cudaGraphExecGetId():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaGraphNodeGetLocalId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaGraphNodeGetLocalId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaGraphNodeGetLocalId():
@@ -1625,7 +1629,7 @@ def test_cudaGraphNodeGetLocalId():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaGraphNodeGetToolsId"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaGraphNodeGetToolsId"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaGraphNodeGetToolsId():
@@ -1654,7 +1658,7 @@ def test_cudaGraphNodeGetToolsId():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaGraphNodeGetContainingGraph"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaGraphNodeGetContainingGraph"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaGraphNodeGetContainingGraph():
@@ -1701,7 +1705,7 @@ def test_cudaGraphNodeGetContainingGraph():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaStreamGetDevResource"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaStreamGetDevResource"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaStreamGetDevResource():
@@ -1720,7 +1724,7 @@ def test_cudaStreamGetDevResource():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaDeviceGetDevResource"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaDeviceGetDevResource"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaDeviceGetDevResource():
@@ -1735,7 +1739,7 @@ def test_cudaDeviceGetDevResource():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaDeviceGetExecutionCtx"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaDeviceGetExecutionCtx"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaExecutionCtxGetDevResource():
@@ -1753,7 +1757,7 @@ def test_cudaExecutionCtxGetDevResource():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaDeviceGetExecutionCtx"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaDeviceGetExecutionCtx"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaExecutionCtxGetDevice():
@@ -1773,7 +1777,7 @@ def test_cudaExecutionCtxGetDevice():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaDeviceGetExecutionCtx"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaDeviceGetExecutionCtx"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaExecutionCtxGetId():
@@ -1801,7 +1805,7 @@ def test_cudaExecutionCtxGetId():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaDevSmResourceSplit"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaDevSmResourceSplit"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaDevSmResourceSplit():
@@ -1870,7 +1874,7 @@ def test_cudaDevSmResourceSplit():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaDevSmResourceSplitByCount"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaDevSmResourceSplitByCount"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaDevSmResourceSplitByCount():
@@ -1893,7 +1897,7 @@ def test_cudaDevSmResourceSplitByCount():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaDevResourceGenerateDesc"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaDevResourceGenerateDesc"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaDevResourceGenerateDesc():
@@ -1910,7 +1914,7 @@ def test_cudaDevResourceGenerateDesc():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaGreenCtxCreate"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaGreenCtxCreate"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaGreenCtxCreate():
@@ -1941,7 +1945,7 @@ def test_cudaGreenCtxCreate():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaExecutionCtxStreamCreate"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaExecutionCtxStreamCreate"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaExecutionCtxStreamCreate():
@@ -1962,7 +1966,7 @@ def test_cudaExecutionCtxStreamCreate():
 
 
 @pytest.mark.skipif(
-    driverVersionLessThan(13010) or not supportsCudaAPI("cudaGraphConditionalHandleCreate_v2"),
+    driver_version_less_than(13010) or not supportsCudaAPI("cudaGraphConditionalHandleCreate_v2"),
     reason="Requires CUDA 13.1+",
 )
 def test_cudaGraphConditionalHandleCreate_v2():
diff --git a/cuda_bindings/tests/test_cufile.py b/cuda_bindings/tests/test_cufile.py
index 46bd8429a62..7de4ceb2e20 100644
--- a/cuda_bindings/tests/test_cufile.py
+++ b/cuda_bindings/tests/test_cufile.py
@@ -138,7 +138,7 @@ def ctx():
     (err,) = cuda.cuCtxSetCurrent(ctx)
     assert err == cuda.CUresult.CUDA_SUCCESS
 
-    yield
+    yield ctx
 
     cuda.cuDevicePrimaryCtxRelease(device)
 
diff --git a/cuda_bindings/tests/test_envvar.py b/cuda_bindings/tests/test_envvar.py
new file mode 100644
index 00000000000..a1f2d016910
--- /dev/null
+++ b/cuda_bindings/tests/test_envvar.py
@@ -0,0 +1,51 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import pytest
+
+from cuda.bindings.utils import envvar_bool
+
+_VAR = "CUDA_PYTHON_TEST_ENVVAR_BOOL"
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize(
+    ("raw", "expected"),
+    [
+        pytest.param("0", False, id="zero"),
+        pytest.param(" 0 ", False, id="zero-padded"),
+        pytest.param("", False, id="empty"),
+        pytest.param("   ", False, id="blank"),
+        pytest.param("1", True, id="one"),
+        pytest.param("2", True, id="two"),
+        pytest.param("-0", False, id="negative-zero"),
+        pytest.param("false", False, id="false"),
+        pytest.param("FALSE", False, id="false-upper"),
+        pytest.param("no", False, id="no"),
+        pytest.param("off", False, id="off"),
+        pytest.param("true", True, id="true"),
+        pytest.param("True", True, id="true-capitalised"),
+        pytest.param("yes", True, id="yes"),
+        pytest.param("on", True, id="on"),
+        # Anything unrecognised keeps the historical set-means-true behaviour.
+        pytest.param("banana", True, id="unrecognised"),
+    ],
+)
+def test_envvar_bool_parsing(monkeypatch, raw, expected):
+    monkeypatch.setenv(_VAR, raw)
+    assert envvar_bool(_VAR) is expected
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("default", [False, True])
+def test_envvar_bool_unset_returns_default(monkeypatch, default):
+    monkeypatch.delenv(_VAR, raising=False)
+    assert envvar_bool(_VAR, default) is default
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("raw", ["", "   "])
+def test_envvar_bool_blank_returns_default(monkeypatch, raw):
+    """Blank is "not set", so it must not override a True default."""
+    monkeypatch.setenv(_VAR, raw)
+    assert envvar_bool(_VAR, True) is True
diff --git a/cuda_bindings/tests/test_examples.py b/cuda_bindings/tests/test_examples.py
index 63a56c78fb7..a7a0524a217 100644
--- a/cuda_bindings/tests/test_examples.py
+++ b/cuda_bindings/tests/test_examples.py
@@ -7,8 +7,7 @@
 import sys
 
 import pytest
-
-from cuda.bindings._test_helpers.pep723 import has_package_requirements_or_skip
+from cuda_python_test_helpers.pep723 import has_package_requirements_or_skip
 
 examples_path = os.path.join(os.path.dirname(__file__), "..", "examples")
 examples_files = glob.glob(os.path.join(examples_path, "**/*.py"), recursive=True)
@@ -20,6 +19,7 @@ def test_example(example):
 
     env = os.environ.copy()
     env["CUDA_BINDINGS_SKIP_EXAMPLE"] = "100"
+    env["MPLBACKEND"] = "Agg"  # avoid plt.show() from blocking
 
     process = subprocess.run([sys.executable, example], capture_output=True, env=env)  # noqa: S603
     # returncode is a special value used in the examples to indicate that system requirements are not met.
diff --git a/cuda_bindings/tests/test_graphics_apis.py b/cuda_bindings/tests/test_graphics_apis.py
index 8b74d8d2a1d..e07e27069d7 100644
--- a/cuda_bindings/tests/test_graphics_apis.py
+++ b/cuda_bindings/tests/test_graphics_apis.py
@@ -7,47 +7,58 @@
 import os
 import sys
 
+import pyglet
 import pytest
+from cuda_python_test_helpers.graphics import is_gl_context_unavailable
 
 from cuda.bindings import runtime as cudart
 
+pytestmark = pytest.mark.thread_unsafe(reason="pyglet/OpenGL context is process-global")
 
-@contextlib.contextmanager
-def _gl_context():
-    """
-    Yield a (tex_id, tex_target) with a current GL context.
-    Tries:
-      1) Windows: hidden WGL window (no EGL)
-      2) Linux with DISPLAY/wayland: hidden window
-      3) Linux headless: EGL headless if available
-    Skips if none work.
-    """
-    pyglet = pytest.importorskip("pyglet")
 
-    # Prefer non-headless when a display is available; it's more portable and avoids EGL.
+def _configure_pyglet_headless():
+    """On headless Linux: enable EGL mode or skip if EGL is absent."""
     if sys.platform.startswith("linux") and not (os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY")):
         if ctypes.util.find_library("EGL") is None:
             pytest.skip("No DISPLAY and no EGL runtime available for headless context.")
         pyglet.options["headless"] = True
 
-    # Create a minimal offscreen/hidden context
-    win = None
-    try:
-        if not pyglet.options.get("headless"):
-            # Hidden window path (WGL on Windows, GLX/WLS on Linux)
-            from pyglet import gl
 
-            config = gl.Config(double_buffer=False)
-            win = pyglet.window.Window(visible=False, config=config)
+def _open_gl_window():
+    """Open a hidden window (or configure EGL headless). Returns the window or None.
+
+    Closes the window if switch_to() fails so a partially-constructed window does not leak.
+    """
+    if not pyglet.options.get("headless"):
+        # Hidden window path (WGL on Windows, GLX/WLS on Linux)
+        from pyglet import gl
+
+        config = gl.Config(double_buffer=False)
+        win = pyglet.window.Window(visible=False, config=config)
+        try:
             win.switch_to()
-        else:
-            # Headless EGL path; pyglet will arrange a pbuffer-like headless context
-            from pyglet.gl import headless  # noqa: F401
+        except Exception:
+            with contextlib.suppress(Exception):
+                win.close()
+            raise
+        return win
+    else:
+        # Headless EGL path; pyglet will arrange a pbuffer-like headless context
+        from pyglet.gl import headless  # noqa: F401
+
+        return None
 
-        # Make a tiny texture so we have a real GL object to register
-        from pyglet.gl import gl as _gl
 
-        tex_id = _gl.GLuint(0)
+def _allocate_gl_texture(win):
+    """Allocate a 2-D RGBA8 texture. Caller must have a current GL context.
+
+    Deletes the generated texture if a later GL call fails, so a partial
+    resource does not leak.
+    """
+    from pyglet.gl import gl as _gl
+
+    tex_id = _gl.GLuint(0)
+    try:
         _gl.glGenTextures(1, ctypes.byref(tex_id))
         target = _gl.GL_TEXTURE_2D
         _gl.glBindTexture(target, tex_id.value)
@@ -55,26 +66,40 @@ def _gl_context():
         _gl.glTexParameteri(target, _gl.GL_TEXTURE_MAG_FILTER, _gl.GL_NEAREST)
         width, height = 16, 16
         _gl.glTexImage2D(target, 0, _gl.GL_RGBA8, width, height, 0, _gl.GL_RGBA, _gl.GL_UNSIGNED_BYTE, None)
+        return tex_id, target
+    except Exception:
+        if tex_id.value:
+            with contextlib.suppress(Exception):
+                _gl.glDeleteTextures(1, ctypes.byref(tex_id))
+        raise
 
-        yield int(tex_id.value), int(target)
 
+@contextlib.contextmanager
+def _gl_context():
+    """Yield ``(tex_id, tex_target)`` with a current GL context, or skip if GL is unavailable."""
+    _configure_pyglet_headless()
+
+    try:
+        win = _open_gl_window()
     except Exception as e:
-        # Convert any pyglet/GL creation failure into a clean skip
-        pytest.skip(f"Could not create GL context/texture: {type(e).__name__}: {e}")
+        if is_gl_context_unavailable(e):
+            pytest.skip(f"Could not create GL context: {type(e).__name__}: {e}")
+        raise
+
+    tex_id = None
+    try:
+        tex_id, target = _allocate_gl_texture(win)
+        yield int(tex_id.value), int(target)
     finally:
-        # Best-effort cleanup
-        try:
-            from pyglet.gl import gl as _gl
+        if tex_id is not None:
+            with contextlib.suppress(Exception):
+                from pyglet.gl import gl as _gl
 
-            if tex_id.value:
-                _gl.glDeleteTextures(1, ctypes.byref(tex_id))
-        except Exception:  # noqa: S110
-            pass
-        try:
+                if tex_id.value:
+                    _gl.glDeleteTextures(1, ctypes.byref(tex_id))
+        with contextlib.suppress(Exception):
             if win is not None:
                 win.close()
-        except Exception:  # noqa: S110
-            pass
 
 
 @pytest.mark.parametrize(
diff --git a/cuda_bindings/tests/test_interoperability.py b/cuda_bindings/tests/test_interoperability.py
index 18a37ec6b4e..08bac311a2d 100644
--- a/cuda_bindings/tests/test_interoperability.py
+++ b/cuda_bindings/tests/test_interoperability.py
@@ -3,10 +3,10 @@
 
 import numpy as np
 import pytest
+from cuda_python_test_helpers.mempool import xfail_if_mempool_oom
 
 import cuda.bindings.driver as cuda
 import cuda.bindings.runtime as cudart
-from cuda.bindings._test_helpers.mempool import xfail_if_mempool_oom
 
 
 def supportsMemoryPool():
diff --git a/cuda_bindings/tests/test_nvrtc.py b/cuda_bindings/tests/test_nvrtc.py
index 26eea71a100..fd73b86eaa2 100644
--- a/cuda_bindings/tests/test_nvrtc.py
+++ b/cuda_bindings/tests/test_nvrtc.py
@@ -23,3 +23,20 @@ def test_get_lowered_name_failure():
         nvrtc.get_lowered_name(0, b"I'm an elevated name!")
     with pytest.raises(nvrtc.InvalidProgramError):
         nvrtc.get_lowered_name(0, b"I'm another elevated name!")
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+@pytest.mark.skipif(nvrtc_version_less_than(13, 3), reason="When nvrtcGetBundledHeadersInfo was introduced")
+def test_get_bundled_headers_info():
+    info = nvrtc.BundledHeadersInfo()
+    assert isinstance(info, nvrtc.BundledHeadersInfo)
+
+    info, error_log = nvrtc.get_bundled_headers_info()
+    assert isinstance(info, nvrtc.BundledHeadersInfo)
+    assert info.available in (0, 1)
+    assert info.compressed_size >= 0
+    assert info.uncompressed_size >= 0
+    assert info.cuda_version_major >= 0
+    assert info.cuda_version_minor >= 0
+    assert info.num_files >= 0
+    assert error_log is None
diff --git a/cuda_bindings/tests/test_utils.py b/cuda_bindings/tests/test_utils.py
index c767996bced..84f7ca7b722 100644
--- a/cuda_bindings/tests/test_utils.py
+++ b/cuda_bindings/tests/test_utils.py
@@ -115,6 +115,27 @@ def test_get_handle_error(target):
         handle = get_cuda_native_handle(target)
 
 
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_get_handle_does_not_report_a_registered_type_as_unknown(monkeypatch):
+    """A KeyError from inside a handle getter is a bug in that getter.
+
+    Reporting it as "Unknown type" is wrong twice over: the type *is*
+    registered, and `from None` hides the traceback that would say otherwise.
+    """
+    from cuda.bindings.utils import _handle_getters
+
+    class Registered:
+        pass
+
+    def getter(_obj):
+        raise KeyError("lookup inside the getter failed")
+
+    monkeypatch.setitem(_handle_getters, Registered, getter)
+
+    with pytest.raises(KeyError, match="lookup inside the getter failed"):
+        get_cuda_native_handle(Registered())
+
+
 @pytest.mark.parametrize(
     "module",
     # Top-level modules for external Python use
diff --git a/cuda_bindings/tests/test_version_check.py b/cuda_bindings/tests/test_version_check.py
index 03c3d7d3c2c..009322433d2 100644
--- a/cuda_bindings/tests/test_version_check.py
+++ b/cuda_bindings/tests/test_version_check.py
@@ -84,6 +84,27 @@ def test_warning_suppressed_by_env_var(self):
             warn_if_cuda_major_version_mismatch()
             assert len(w) == 0
 
+    @pytest.mark.agent_authored(model="claude-opus-5")
+    def test_warning_not_suppressed_when_env_var_is_zero(self):
+        """``=0`` is how a user says "no, keep warning me".
+
+        A bare truthiness test on the raw string made ``=0`` suppress the
+        warning -- the opposite of what the warning itself tells the user to
+        type, and the opposite of the other boolean knobs in this repository
+        (``CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM``,
+        ``CUDA_CORE_DONT_FIX_TAB_COMPLETION``), which both parse with ``int()``.
+        """
+        with (
+            mock.patch.object(driver, "CUDA_VERSION", 13000),
+            mock.patch.object(driver, "cuDriverGetVersion", return_value=(driver.CUresult.CUDA_SUCCESS, 12080)),
+            mock.patch.dict(os.environ, {"CUDA_PYTHON_DISABLE_MAJOR_VERSION_WARNING": "0"}),
+            warnings.catch_warnings(record=True) as w,
+        ):
+            warnings.simplefilter("always")
+            warn_if_cuda_major_version_mismatch()
+            assert len(w) == 1
+            assert issubclass(w[0].category, UserWarning)
+
     def test_error_when_driver_version_fails(self):
         """Should raise RuntimeError if cuDriverGetVersion fails."""
         with (
diff --git a/cuda_core/AGENTS.md b/cuda_core/AGENTS.md
index 83c96800e9d..9d80ab74aaa 100644
--- a/cuda_core/AGENTS.md
+++ b/cuda_core/AGENTS.md
@@ -151,6 +151,13 @@ a `StrEnum` is accepted as an argument, a `str` should also be acceptable.  An
 invalid value should raise an exception.  When a function returns a `str` drawn
 from a small number of values, return a `StrEnum` subclass instead.
 
+For `__post_init__` validation in frozen dataclasses, use the
+`not isinstance(value, EnumType) → try EnumType(value) except (ValueError,
+TypeError)` pattern (modelled on `_normalize_enum` in
+`cuda/core/texture/_texture.pyx`). This accepts the enum itself or a valid
+string, and raises `ValueError` eagerly for any other type rather than
+silently storing it.
+
 ### Exception handling
 
 Raising exceptions is preferred over a C-style return code that must be checked
diff --git a/cuda_core/LICENSE b/cuda_core/LICENSE
index d6f74778be8..f3fe76ecadf 100644
--- a/cuda_core/LICENSE
+++ b/cuda_core/LICENSE
@@ -176,3 +176,28 @@ Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
       of your accepting any such warranty or additional liability.
 
    END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
diff --git a/cuda_core/NOTICE b/cuda_core/NOTICE
index c4625e23899..f58d516a4ba 100644
--- a/cuda_core/NOTICE
+++ b/cuda_core/NOTICE
@@ -11,3 +11,20 @@ DLPack
 Copyright (c) 2017 by Contributors
 Licensed under the Apache License, Version 2.0.
 Source: https://github.com/dmlc/dlpack
+Vendored at: cuda/core/_include/dlpack.h
+
+PyTorch
+Copyright (c) 2016-     Facebook, Inc            (Adam Paszke)
+Copyright (c) 2014-     Facebook, Inc            (Soumith Chintala)
+Copyright (c) 2011-2014 Idiap Research Institute (Ronan Collobert)
+Copyright (c) 2012-2014 Deepmind Technologies    (Koray Kavukcuoglu)
+Copyright (c) 2011-2012 NEC Laboratories America (Koray Kavukcuoglu)
+Copyright (c) 2011-2013 NYU                      (Clement Farabet)
+Copyright (c) 2006-2010 NEC Laboratories America (Ronan Collobert, Leon Bottou, Iain Melvin, Jason Weston)
+Copyright (c) 2006      Idiap Research Institute (Samy Bengio)
+Copyright (c) 2001-2004 Idiap Research Institute (Ronan Collobert, Samy Bengio, Johnny Mariethoz)
+Licensed under the BSD 3-Clause License.
+Source: https://github.com/pytorch/pytorch
+Vendored at: cuda/core/_include/aoti_shim.h, and the accompanying
+cuda/core/_include/aoti_shim.def, which declares the same AOT Inductor
+stable C ABI symbol names for the MSVC linker on Windows.
diff --git a/cuda_core/build_hooks.py b/cuda_core/build_hooks.py
index dfd08d56733..fc112b5a74e 100644
--- a/cuda_core/build_hooks.py
+++ b/cuda_core/build_hooks.py
@@ -17,6 +17,7 @@
 from pathlib import Path
 
 from Cython.Build import cythonize
+from Cython.Compiler import Options as _CythonOptions
 from setuptools import Extension
 from setuptools import build_meta as _build_meta
 
@@ -45,9 +46,9 @@ def _import_get_cuda_path_or_home():
             cuda = None
 
         for p in sys.path:
-            sp_cuda = os.path.join(p, "cuda")
-            if os.path.isdir(os.path.join(sp_cuda, "pathfinder")):
-                cuda.__path__ = list(cuda.__path__) + [sp_cuda]
+            sp_cuda = Path(p) / "cuda"
+            if (sp_cuda / "pathfinder").is_dir():
+                cuda.__path__ = list(cuda.__path__) + [str(sp_cuda)]
                 break
         else:
             raise ModuleNotFoundError(
@@ -56,6 +57,11 @@ def _import_get_cuda_path_or_home():
             )
         import cuda.pathfinder
 
+    pathfinder_dir = Path(cuda.pathfinder.__file__).parent
+    print(
+        f"Using cuda-pathfinder {cuda.pathfinder.__version__} from {pathfinder_dir}",
+        file=sys.stderr,
+    )
     return cuda.pathfinder.get_cuda_path_or_home
 
 
@@ -118,6 +124,64 @@ def _determine_cuda_major_version() -> str:
 # used later by setup()
 _extensions = None
 
+# Where per-configuration build artifacts live. Anchored to this file rather
+# than the cwd, since a project can be built from anywhere.
+_BUILD_DIR = Path(__file__).parent / "build"
+
+# Records the CUDA major of the last completed build, so setup.py can force
+# build_ext when it changes. Written by record_build_major().
+_BUILD_MAJOR_STAMP = _BUILD_DIR / ".build-cuda-major"
+
+force_build_ext = False
+
+
+def _check_build_major() -> str:
+    """Return the CUDA major to key build artifacts by, and set force_build_ext.
+
+    Cython's up-to-date check does not hash ``compile_time_env``, so generated
+    sources for one CUDA major would otherwise be reused for another. Keying
+    the generated-source directory fixes that, but not the compiled extension:
+    in an editable install it lands in the source tree under a name keyed by
+    the Python ABI tag alone, with nowhere to record the CUDA major. On a
+    cu12 -> cu13 -> cu12 round trip build_ext would find the older cu12
+    generated source next to the newer cu13 .so and skip the rebuild, so the
+    major is also stamped and build_ext forced whenever it changes.
+    """
+    global force_build_ext
+
+    cuda_major = _determine_cuda_major_version()
+    try:
+        previous = _BUILD_MAJOR_STAMP.read_text(encoding="utf-8").strip()
+    except FileNotFoundError:
+        previous = None
+
+    # A missing stamp means the last build's major is unknown, so force too.
+    # On a first build that costs nothing: there are no artifacts to reuse.
+    if previous != cuda_major:
+        print(f"CUDA major of last build: {previous} (building {cuda_major}); forcing a full rebuild")
+        force_build_ext = True
+
+    return cuda_major
+
+
+def record_build_major() -> None:
+    """Stamp the CUDA major of the build that just completed.
+
+    setup.py calls this after build_ext succeeds, so that a build which failed
+    partway through does not claim outputs it never produced.
+    """
+    _BUILD_MAJOR_STAMP.parent.mkdir(parents=True, exist_ok=True)
+    _BUILD_MAJOR_STAMP.write_text(_determine_cuda_major_version() + "\n", encoding="utf-8")
+
+
+def _relativize_extension_sources(extensions) -> None:
+    """Keep absolute source paths out of setuptools' temporary build tree."""
+    for extension in extensions:
+        extension.sources = [
+            os.path.relpath(source, start=Path.cwd()) if os.path.isabs(source) else source
+            for source in extension.sources
+        ]
+
 
 def _build_cuda_core(debug=False):
     # Customizing the build hooks is needed because we must defer cythonization until cuda-bindings,
@@ -127,6 +191,9 @@ def _build_cuda_core(debug=False):
     # This function populates "_extensions".
     global _extensions
 
+    # Resolve CUDA first so the pathfinder import repairs PEP 517 namespace shadowing before importing bindings.
+    cuda_path = _get_cuda_path()
+
     # Add cuda-bindings to sys.path so Cython can find .pxd files
     # This is needed for editable installs where meta path finders don't work for Cython
     # We need to add the directory containing the 'cuda' package so Cython can resolve
@@ -135,6 +202,7 @@ def _build_cuda_core(debug=False):
         import cuda.bindings
 
         bindings_path = Path(cuda.bindings.__file__).parent  # .../cuda/bindings/
+        print(f"Using cuda-bindings {cuda.bindings.__version__} from {bindings_path}", file=sys.stderr)
         cuda_package_dir = bindings_path.parent.parent  # .../cuda_bindings/ (contains cuda/)
         if str(cuda_package_dir) not in sys.path:
             sys.path.insert(0, str(cuda_package_dir))
@@ -171,7 +239,7 @@ def get_sources(mod_name):
 
         return sources
 
-    all_include_dirs = [os.path.join(_get_cuda_path(), "include")]
+    all_include_dirs = [os.path.join(cuda_path, "include")]
     extra_compile_args = []
     extra_link_args = []
     extra_cythonize_kwargs = {}
@@ -209,21 +277,34 @@ def get_sources(mod_name):
         for mod in module_names()
     )
 
+    # Deliberately after the cuda.bindings import above: this re-enters
+    # _get_cuda_path() and reads cuda.h, which must not run before the
+    # pathfinder import has repaired PEP 517 namespace shadowing.
+    cuda_major = _check_build_major()
+
     nthreads = int(os.environ.get("CUDA_PYTHON_PARALLEL_LEVEL", os.cpu_count() // 2))
-    compile_time_env = {"CUDA_CORE_BUILD_MAJOR": int(_determine_cuda_major_version())}
+    compile_time_env = {"CUDA_CORE_BUILD_MAJOR": int(cuda_major)}
     compiler_directives = {"embedsignature": True, "warn.deprecated.IF": False, "freethreading_compatible": True}
+    _CythonOptions.warning_errors = True
     if COMPILE_FOR_COVERAGE:
         compiler_directives["linetrace"] = True
     _extensions = cythonize(
         ext_modules,
         verbose=True,
         language_level=3,
-        build_dir="." if COMPILE_FOR_COVERAGE else "build/cython",
+        # CUDA_PYTHON_COVERAGE deliberately generates in-tree so the sources can
+        # be packaged; every other build gets its own per-configuration cache,
+        # anchored alongside the stamp so both resolve the same from any cwd.
+        build_dir="." if COMPILE_FOR_COVERAGE else str(_BUILD_DIR / "cython" / f"cu{cuda_major}"),
         nthreads=nthreads,
         compiler_directives=compiler_directives,
         compile_time_env=compile_time_env,
         **extra_cythonize_kwargs,
     )
+    # Cython returns generated sources under the absolute build_dir above.
+    # setuptools mirrors absolute source paths into build/temp, which can push
+    # MSVC linker output paths past MAX_PATH in deeper Windows checkouts.
+    _relativize_extension_sources(_extensions)
 
     return
 
diff --git a/cuda_core/cuda/core/__init__.py b/cuda_core/cuda/core/__init__.py
index dc6fefdffea..7864ae794ca 100644
--- a/cuda_core/cuda/core/__init__.py
+++ b/cuda_core/cuda/core/__init__.py
@@ -36,12 +36,17 @@ def _patch_rlcompleter_for_cython_properties() -> None:
     # which rlcompleter's narrow isinstance(..., property) check misses; the
     # fallback getattr() then invokes the descriptor and any non-AttributeError
     # it raises kills tab completion. Extend that isinstance check to also
-    # match getset_descriptor / member_descriptor. Only installed in
-    # interactive mode so library users running scripts see no global
-    # rlcompleter side effect.
+    # match getset_descriptor / member_descriptor. Installed unconditionally
+    # (the patch is scoped to the rlcompleter module, so non-interactive users
+    # only pay for the import).
     import os
 
-    if int(os.environ.get("CUDA_CORE_DONT_FIX_TAB_COMPLETION", "0")):
+    raw_opt_out = os.environ.get("CUDA_CORE_DONT_FIX_TAB_COMPLETION", "").strip()
+    try:
+        opt_out = int(raw_opt_out) != 0
+    except ValueError:
+        opt_out = raw_opt_out != ""
+    if opt_out:
         # Explicit opt-out for users who don't want the global rlcompleter
         # side effect, even in an interactive session.
         return
@@ -69,45 +74,51 @@ class _PatchedProperty(metaclass=_PatchedPropMeta):
 
 
 from cuda.core import checkpoint, system, utils
-from cuda.core._context import Context, ContextOptions
-from cuda.core._device import Device
-from cuda.core._device_resources import (
-    DeviceResources,
-    SMResource,
-    SMResourceOptions,
-    WorkqueueResource,
-    WorkqueueResourceOptions,
-)
-from cuda.core._event import Event, EventOptions
-from cuda.core._graphics import GraphicsResource
-from cuda.core._host import Host
-from cuda.core._launch_config import LaunchConfig
-from cuda.core._launcher import launch
-from cuda.core._linker import Linker, LinkerOptions
-from cuda.core._memory import (
-    Buffer,
-    DeviceMemoryResource,
-    DeviceMemoryResourceOptions,
-    GraphMemoryResource,
-    LegacyPinnedMemoryResource,
-    ManagedBuffer,
-    ManagedMemoryResource,
-    ManagedMemoryResourceOptions,
-    MemoryResource,
-    PinnedMemoryResource,
-    PinnedMemoryResourceOptions,
-    VirtualMemoryResource,
-    VirtualMemoryResourceOptions,
-)
-from cuda.core._module import Kernel, ObjectCode
-from cuda.core._program import Program, ProgramOptions
-from cuda.core._stream import (
-    LEGACY_DEFAULT_STREAM,
-    PER_THREAD_DEFAULT_STREAM,
-    Stream,
-    StreamOptions,
-)
-from cuda.core._tensor_map import TensorMapDescriptor, TensorMapDescriptorOptions
+from cuda.core._context import *
+from cuda.core._context import __all__ as _context_all
+from cuda.core._device import *
+from cuda.core._device import __all__ as _device_all
+from cuda.core._device_resources import *
+from cuda.core._device_resources import __all__ as _device_resources_all
+from cuda.core._event import *
+from cuda.core._event import __all__ as _event_all
+from cuda.core._graphics import *
+from cuda.core._graphics import __all__ as _graphics_all
+from cuda.core._host import *
+from cuda.core._host import __all__ as _host_all
+from cuda.core._launch_config import *
+from cuda.core._launch_config import __all__ as _launch_config_all
+from cuda.core._launcher import *
+from cuda.core._launcher import __all__ as _launcher_all
+from cuda.core._linker import *
+from cuda.core._linker import __all__ as _linker_all
+from cuda.core._memory import *
+from cuda.core._memory import __all__ as _memory_all
+from cuda.core._module import *
+from cuda.core._module import __all__ as _module_all
+from cuda.core._program import *
+from cuda.core._program import __all__ as _program_all
+from cuda.core._stream import *
+from cuda.core._stream import __all__ as _stream_all
+from cuda.core._tensor_map import *
+from cuda.core._tensor_map import __all__ as _tensor_map_all
+
+__all__ = [
+    *_context_all,
+    *_device_all,
+    *_device_resources_all,
+    *_event_all,
+    *_graphics_all,
+    *_host_all,
+    *_launch_config_all,
+    *_launcher_all,
+    *_linker_all,
+    *_memory_all,
+    *_module_all,
+    *_program_all,
+    *_stream_all,
+    *_tensor_map_all,
+]
 
 # isort: split
 # Texture/surface types live under the cuda.core.texture namespace (not the
diff --git a/cuda_core/cuda/core/_context.pxd b/cuda_core/cuda/core/_context.pxd
index b0edf5a0674..078c0c33415 100644
--- a/cuda_core/cuda/core/_context.pxd
+++ b/cuda_core/cuda/core/_context.pxd
@@ -23,3 +23,9 @@ cdef class Context:
     cdef Context _from_green_ctx(type cls, GreenCtxHandle h_green_ctx, int device_id)
 
     cpdef close(self)
+
+
+cdef inline int Context_check_open(Context self) except -1:
+    if not self._h_context:
+        raise RuntimeError("Context has been closed")
+    return 0
diff --git a/cuda_core/cuda/core/_context.pyi b/cuda_core/cuda/core/_context.pyi
index afbc130882e..46d01e75715 100644
--- a/cuda_core/cuda/core/_context.pyi
+++ b/cuda_core/cuda/core/_context.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_context.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_context.pyx
 
 from collections.abc import Sequence
 from dataclasses import dataclass
@@ -8,8 +6,10 @@ from dataclasses import dataclass
 import cuda.bindings.driver
 from cuda.core._device_resources import (DeviceResources, SMResource,
                                          WorkqueueResource)
-from cuda.core._stream import Stream
+from cuda.core._stream import Stream, StreamOptions
 
+__all__ = ['Context', 'ContextOptions']
+DeviceResourcesType = Sequence[SMResource | WorkqueueResource]
 
 class Context:
     """CUDA context wrapper.
@@ -17,25 +17,18 @@ class Context:
     Context objects represent CUDA contexts and cannot be instantiated directly.
     Use Device or Stream APIs to obtain context objects.
     """
-
-    def close(self):
-        """Release this context wrapper's underlying CUDA handles."""
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @property
     def handle(self) -> cuda.bindings.driver.CUcontext | None:
         """Return the underlying CUcontext handle."""
-
     @property
-    def _handle(self) -> cuda.bindings.driver.CUcontext | None:
-        ...
-
+    def _handle(self) -> cuda.bindings.driver.CUcontext | None: ...
+    @property
+    def is_closed(self) -> bool:
+        """Whether this context has been closed."""
     @property
     def is_green(self) -> bool:
         """True if this context was created from device resources."""
-
     @property
     def resources(self) -> DeviceResources:
         """Query the hardware resources provisioned for this context.
@@ -46,8 +39,7 @@ class Context:
 
         Raises :class:`RuntimeError` if the context has been closed.
         """
-
-    def create_stream(self, options: object=None) -> Stream:
+    def create_stream(self, options: StreamOptions | None=None) -> Stream:
         """Create a new stream bound to this green context.
 
         This method is only available on green contexts. For primary
@@ -63,15 +55,11 @@ class Context:
         :obj:`~_stream.Stream`
             Newly created stream object.
         """
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
-    def __repr__(self) -> str:
-        ...
+    def close(self):
+        """Release this context wrapper's underlying CUDA handles."""
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
+    def __repr__(self) -> str: ...
 
 @dataclass
 class ContextOptions:
@@ -83,5 +71,3 @@ class ContextOptions:
         Device resources used to create a green context.
     """
     resources: DeviceResourcesType
-__all__ = ['Context', 'ContextOptions']
-DeviceResourcesType = Sequence[SMResource | WorkqueueResource]
\ No newline at end of file
diff --git a/cuda_core/cuda/core/_context.pyx b/cuda_core/cuda/core/_context.pyx
index 6da72addb0d..6855d0cc255 100644
--- a/cuda_core/cuda/core/_context.pyx
+++ b/cuda_core/cuda/core/_context.pyx
@@ -8,6 +8,8 @@ from collections.abc import Sequence
 from dataclasses import dataclass
 from typing import TYPE_CHECKING
 
+import cython
+
 from cuda.bindings cimport cydriver
 from cuda.core._device_resources cimport DeviceResources, SMResource, WorkqueueResource
 from cuda.core._device_resources import SMResource, WorkqueueResource
@@ -21,7 +23,7 @@ from cuda.core._resource_handles cimport (
     as_intptr,
     as_py,
 )
-from cuda.core._stream import Stream
+from cuda.core._stream import Stream, StreamOptions
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 
 if TYPE_CHECKING:
@@ -74,6 +76,11 @@ cdef class Context:
     def _handle(self) -> cuda.bindings.driver.CUcontext | None:
         return self.handle
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this context has been closed."""
+        return self._h_context.get() == NULL
+
     @property
     def is_green(self) -> bool:
         """True if this context was created from device resources."""
@@ -91,11 +98,11 @@ cdef class Context:
 
         Raises :class:`RuntimeError` if the context has been closed.
         """
-        if not self._h_context:
-            raise RuntimeError("Cannot query resources on a closed context")
+        Context_check_open(self)
         return DeviceResources._init_from_ctx(self._h_context, self._device_id)
 
-    def create_stream(self, options: object = None) -> Stream:
+    @cython.annotation_typing(False)
+    def create_stream(self, options: StreamOptions | None = None) -> Stream:
         """Create a new stream bound to this green context.
 
         This method is only available on green contexts. For primary
@@ -111,8 +118,7 @@ cdef class Context:
         :obj:`~_stream.Stream`
             Newly created stream object.
         """
-        if not self._h_context:
-            raise RuntimeError("Cannot create a stream on a closed context")
+        Context_check_open(self)
         if not self.is_green:
             raise RuntimeError(
                 "Context.create_stream() is only supported on green contexts. "
diff --git a/cuda_core/cuda/core/_cpp/GRAPH_ATTACHMENTS.md b/cuda_core/cuda/core/_cpp/GRAPH_ATTACHMENTS.md
index 89003ae0b7f..fdaf77785b2 100644
--- a/cuda_core/cuda/core/_cpp/GRAPH_ATTACHMENTS.md
+++ b/cuda_core/cuda/core/_cpp/GRAPH_ATTACHMENTS.md
@@ -77,12 +77,13 @@ The CUDA user-object reference count controls the attachment lifetime.
 `GraphAttachmentMap` only lets cuda.core find the attachment currently
 associated with a node.
 
-Each `NodeAttachment` contains two type-erased `OpaqueHandle` owners:
+Each `NodeAttachment` has two type-erased `OpaqueHandle` slots, allowing it to
+hold up to two node-specific resource owners. These are:
 
-- kernel: kernel and argument storage
-- host callback: callback and copied user data
-- memcpy: destination and source
-- memset or event: destination or event in the first owner
+- kernel node: kernel and argument storage
+- host callback node: callback and copied user data
+- memcpy node: destination and source
+- memset or event node: destination or event
 
 `OpaqueHandle` is `shared_ptr<const void>`. Existing cuda.core handles reuse
 their shared ownership when converted to it. Python objects and copied callback
@@ -93,23 +94,47 @@ published attachment. The resources those owners keep alive, including Python
 objects, may remain mutable, but they must not be modified in a way that
 releases resources still referenced by an installed parameter version.
 
+## Executable graph attachments
+
+Executable graphs can be modified after instantiation. Those updates may
+introduce new resources (events, memory, kernels, kernel parameters, and host
+callbacks) that must outlive in-flight launches. CUDA provides no way to attach
+user objects to an executable graph (`cuGraphRetainUserObject` accepts a
+`CUgraph` only), so cuda.core emulates that lifetime tracking.
+
+Before instantiation or whole-graph update, cuda.core retains one
+`ExecAttachments` accumulator on the source graph as a CUDA user object.
+Instantiation or `cuGraphExecUpdate` propagates that reference into the
+executable; cuda.core then releases the source graph's temporary reference so
+the executable (and its in-flight launches) own the accumulator. Individual
+node updates append owners to that accumulator through the same prepare/commit
+transaction used for definition attachments.
+
+Appended owners are never removed: each update can only grow the accumulator.
+A successful whole-graph update replaces the accumulator entirely, so the
+previous owners are dropped once their last launch finishes. Enable/disable
+attaches nothing. A child-graph update relies on CUDA cloning the replacement
+graph's user-object references, which carry the child definition's attachments.
+
 ## Deferred cleanup
 
 CUDA invokes a user-object destructor on an internal thread where CUDA API
 calls are forbidden. Destroying an attachment there could release handles whose
 deleters call CUDA or run Python finalizers.
 
-`NodeAttachment` therefore inherits from `DeferredCleanupItem`. The CUDA
+`NodeAttachment` and `ExecAttachments` therefore inherit from
+`DeferredCleanupItem`. The CUDA
 destructor callback only adds the attachment to the process-lifetime
 `DeferredCleanupQueue` and requests a `Py_AddPendingCall`.
 
 One pending call drains all queued attachments from Python's main thread. The
-queue coalesces work because CPython's pending-call queue is bounded. If
-scheduling fails, attachments stay queued and a later enqueue or safe cuda.core
-entry retries. Graph and executable-graph destruction and explicit close paths
-provide additional retry points. During Python finalization, scheduling stops
-and unreclaimable attachments are intentionally leaked rather than destroyed
-in an unsafe context.
+queue coalesces work because CPython's pending-call queue is bounded, and there
+could be many more deferred cleanup items than allowed pending calls. If
+`Py_AddPendingCall` fails, the attachments remain queued. A later successful
+`Py_AddPendingCall` will safely clean them up. Graph and executable-graph
+destruction and explicit close paths provide additional retry points. During
+Python finalization, scheduling stops and unreclaimable attachments are
+intentionally leaked rather than destroyed in an unsafe context.
 
 ## Graph hierarchy state
 
@@ -157,19 +182,15 @@ be invalidated when CUDA destroys that graph. They use separate
 
 ## Invariants
 
-1. The owner bundle of a published `NodeAttachment` is never modified in place.
+1. The owner bundle of a published `NodeAttachment` is never modified in place;
+   replace the whole bundle.
 2. CUDA user-object references, not metadata pointers, own attachments.
-3. Metadata is removed or replaced before its graph reference is released.
-4. Fallible attachment setup and metadata allocation happen before the CUDA
-   graph mutation they support.
-5. Every live cuda.core `CUgraph` has one canonical `GraphBox` and registry
-   entry.
-6. Graph boxes remain in parent-before-child order.
-7. Destroyed child boxes remain at stable addresses in the graveyard.
-8. A raw graph handle is unregistered before its box becomes a tombstone.
-9. CUDA callbacks only enqueue attachments; they never release owners or call
+3. Fallible attachment setup and metadata allocation happen before the CUDA
+   graph mutation they support; metadata is removed or replaced before its
+   graph reference is released.
+4. CUDA callbacks only enqueue attachments; they never release owners or call
    CUDA.
-10. Graph mutations and their metadata updates require the same external
+5. Graph mutations and their metadata updates require the same external
    synchronization as the underlying CUDA graph.
 
 ## Scope
@@ -177,10 +198,11 @@ be invalidated when CUDA destroys that graph. They use separate
 - Attachment metadata tracks graph mutations performed through cuda.core.
 - Raw driver clones receive the CUDA user-object references needed for safe
   execution, but cuda.core cannot reconstruct their node-to-attachment map.
-- Executable graphs rely on CUDA's inherited user-object references; they do
-  not use `GraphAttachmentMap`.
-- Direct executable-node updates require separate executable ownership and are
-  not tracked by definition attachment metadata.
+- Executable graphs keep one append-only accumulator instead of a
+  `GraphAttachmentMap`. cuda.core cannot map an executable node back to its
+  owners, so it can neither report nor release them individually.
+- Executable-node updates do not change definition attachment metadata, and
+  definition updates do not change an executable's accumulator.
 - Stream capture explicitly retains host callbacks. Other captured operations
   keep their documented caller-owned lifetime contract.
 - CPython's cyclic garbage collector cannot follow the ownership path from a
diff --git a/cuda_core/cuda/core/_cpp/resource_handles.cpp b/cuda_core/cuda/core/_cpp/resource_handles.cpp
index b3d2e3fe373..46f7b019379 100644
--- a/cuda_core/cuda/core/_cpp/resource_handles.cpp
+++ b/cuda_core/cuda/core/_cpp/resource_handles.cpp
@@ -9,13 +9,18 @@
 #include <atomic>
 #include <array>
 #include <cstdint>
+#include <cstdio>
 #include <cstdlib>
 #include <cstring>
+#include <functional>
 #include <list>
 #include <map>
 #include <mutex>
 #include <stdexcept>
+#include <thread>
+#include <type_traits>
 #include <unordered_map>
+#include <utility>
 #include <vector>
 
 #ifndef _WIN32
@@ -31,9 +36,15 @@ namespace cuda_core {
 // function pointers extracted from cuda.bindings.cydriver.__pyx_capi__.
 // ============================================================================
 
+decltype(&cuGetErrorName) p_cuGetErrorName = nullptr;
+decltype(&cuGetErrorString) p_cuGetErrorString = nullptr;
+
 decltype(&cuDevicePrimaryCtxRetain) p_cuDevicePrimaryCtxRetain = nullptr;
 decltype(&cuDevicePrimaryCtxRelease) p_cuDevicePrimaryCtxRelease = nullptr;
 decltype(&cuCtxGetCurrent) p_cuCtxGetCurrent = nullptr;
+decltype(&cuCtxSetCurrent) p_cuCtxSetCurrent = nullptr;
+decltype(&cuCtxSynchronize) p_cuCtxSynchronize = nullptr;
+decltype(&cuCtxGetStreamPriorityRange) p_cuCtxGetStreamPriorityRange = nullptr;
 decltype(&cuGreenCtxCreate) p_cuGreenCtxCreate = nullptr;
 decltype(&cuGreenCtxDestroy) p_cuGreenCtxDestroy = nullptr;
 decltype(&cuCtxFromGreenCtx) p_cuCtxFromGreenCtx = nullptr;
@@ -43,6 +54,7 @@ decltype(&cuGreenCtxStreamCreate) p_cuGreenCtxStreamCreate = nullptr;
 
 decltype(&cuStreamCreateWithPriority) p_cuStreamCreateWithPriority = nullptr;
 decltype(&cuStreamDestroy) p_cuStreamDestroy = nullptr;
+decltype(&cuStreamGetCtx) p_cuStreamGetCtx = nullptr;
 
 decltype(&cuEventCreate) p_cuEventCreate = nullptr;
 decltype(&cuEventDestroy) p_cuEventDestroy = nullptr;
@@ -74,6 +86,8 @@ decltype(&cuLibraryGetKernel) p_cuLibraryGetKernel = nullptr;
 
 // Graph
 decltype(&cuGraphDestroy) p_cuGraphDestroy = nullptr;
+decltype(&cuGraphInstantiateWithParams) p_cuGraphInstantiateWithParams = nullptr;
+decltype(&cuGraphExecUpdate) p_cuGraphExecUpdate = nullptr;
 decltype(&cuGraphExecDestroy) p_cuGraphExecDestroy = nullptr;
 decltype(&cuUserObjectCreate) p_cuUserObjectCreate = nullptr;
 decltype(&cuUserObjectRelease) p_cuUserObjectRelease = nullptr;
@@ -106,6 +120,13 @@ decltype(&cuDevSmResourceSplit) p_cuDevSmResourceSplit = nullptr;
 void* p_cuDevSmResourceSplit = nullptr;
 #endif
 
+// cuMemcpyWithAttributesAsync (13.2+ — may be null on older drivers/bindings)
+#if CUDA_VERSION >= 13020
+decltype(&cuMemcpyWithAttributesAsync) p_cuMemcpyWithAttributesAsync = nullptr;
+#else
+void* p_cuMemcpyWithAttributesAsync = nullptr;
+#endif
+
 // NVRTC function pointers
 decltype(&nvrtcDestroyProgram) p_nvrtcDestroyProgram = nullptr;
 
@@ -116,46 +137,34 @@ NvvmDestroyProgramFn p_nvvmDestroyProgram = nullptr;
 NvJitLinkDestroyFn p_nvJitLinkDestroy = nullptr;
 
 // ============================================================================
-// GIL management helpers
+// GIL and scoped-context management helpers
 // ============================================================================
 
 namespace {
 
-// Helper to release the GIL while calling into the CUDA driver.
-// This guard is *conditional*: if the caller already dropped the GIL,
-// we avoid calling PyEval_SaveThread (which requires holding the GIL).
-// It also handles the case where Python is finalizing and GIL operations
-// are no longer safe.
+// Conditionally release the GIL while calling into the CUDA driver.
 class GILReleaseGuard {
 public:
-    GILReleaseGuard() : tstate_(nullptr), released_(false) {
-        // Don't try to manipulate GIL if Python is finalizing
+    GILReleaseGuard() noexcept {
         if (!Py_IsInitialized() || py_is_finalizing()) {
             return;
         }
-        // PyGILState_Check() returns 1 if the GIL is held by this thread.
         if (PyGILState_Check()) {
             tstate_ = PyEval_SaveThread();
-            released_ = true;
         }
-        // Note: If the GIL is not released (finalizing, or not held):
-        // - Reduces parallelism (other Python threads remain blocked)
-        // - No deadlock risk as long as the guarded code doesn't call back into Python
     }
 
     ~GILReleaseGuard() {
-        if (released_) {
+        if (tstate_) {
             PyEval_RestoreThread(tstate_);
         }
     }
 
-    // Non-copyable, non-movable
     GILReleaseGuard(const GILReleaseGuard&) = delete;
     GILReleaseGuard& operator=(const GILReleaseGuard&) = delete;
 
 private:
-    PyThreadState* tstate_;
-    bool released_;
+    PyThreadState* tstate_ = nullptr;
 };
 
 // Helper to acquire the GIL when we might not hold it.
@@ -188,8 +197,235 @@ class GILAcquireGuard {
     bool acquired_;
 };
 
+void warn_on_cuda_error(const char* operation, CUresult status, const char* detail = nullptr) noexcept;
+
+// Make a context current and record the state needed to restore it.
+// An empty handle is a no-op: the operation runs in the caller's current
+// context, and nothing is restored on exit.
+CUresult enter_context(const ContextHandle& h_context, CUcontext* previous, int* changed) noexcept {
+    *previous = nullptr;
+    *changed = 0;
+    CUcontext target = as_cu(h_context);
+    if (!target) {
+        return CUDA_SUCCESS;
+    }
+
+    GILReleaseGuard gil;
+    CUresult status = p_cuCtxGetCurrent(previous);
+    if (status != CUDA_SUCCESS || *previous == target) {
+        return status;
+    }
+    status = p_cuCtxSetCurrent(target);
+    *changed = status == CUDA_SUCCESS;
+    return status;
+}
+
+// Restore the previous context and preserve an earlier operation error.
+CUresult exit_context(CUcontext previous, int changed, CUresult operation_status) noexcept {
+    CUresult restore_status = CUDA_SUCCESS;
+    if (changed) {
+        GILReleaseGuard gil;
+        restore_status = p_cuCtxSetCurrent(previous);
+    }
+    if (operation_status != CUDA_SUCCESS && restore_status != CUDA_SUCCESS) {
+        warn_on_cuda_error("cuCtxSetCurrent (restoring the caller's context)", restore_status);
+    }
+    return operation_status != CUDA_SUCCESS ? operation_status : restore_status;
+}
+
+// Require a callable to be invocable without throwing.
+#define ASSERT_NOTHROW_INVOCABLE(...) \
+    static_assert(std::is_nothrow_invocable_v<__VA_ARGS__>, "operation must be noexcept")
+
+// Store a stream and any state needed to preserve deallocation ordering.
+struct DeallocationStream {
+    StreamHandle h_stream;
+    std::thread::id ptds_tid{};
+};
+
+// Return whether a stream handle needs a current context to resolve it.
+bool is_default_stream(CUstream stream) noexcept {
+    return stream == nullptr || stream == CU_STREAM_LEGACY || stream == CU_STREAM_PER_THREAD;
+}
+
+// Return the context a deallocation-stream token must run under. Real streams
+// resolve their own context; default-stream tokens use the context bound at
+// allocation time. Warn when PTDS deallocation crosses host threads.
+ContextHandle deallocation_context(const DeallocationStream& stream) noexcept {
+    if (!is_default_stream(as_cu(stream.h_stream))) {
+        return {};
+    }
+    if (stream.ptds_tid != std::thread::id{}
+            && stream.ptds_tid != std::this_thread::get_id()) {
+        std::fprintf(
+            stderr,
+            "Warning: Buffer deallocation for a per-thread default stream "
+            "is running on a different host thread than the one that recorded "
+            "the deallocation stream; ordering relative to the allocating "
+            "thread's PTDS is not preserved\n");
+    }
+    return get_stream_context(stream.h_stream);
+}
+
+// Run an operation with the requested context current.
+template <typename Fn, typename... Args>
+CUresult invoke_in_context(const ContextHandle& h_context, Fn&& operation, Args&&... args) noexcept {
+    ASSERT_NOTHROW_INVOCABLE(Fn&&, Args&&...);
+    if (!h_context) {
+        return CUDA_ERROR_INVALID_CONTEXT;
+    }
+    CUcontext previous = nullptr;
+    int changed = 0;
+    CUresult status = enter_context(h_context, &previous, &changed);
+    if (status == CUDA_SUCCESS) {
+        status = std::invoke(std::forward<Fn>(operation), std::forward<Args>(args)...);
+    }
+    return exit_context(previous, changed, status);
+}
+
+// Run a creation operation and undo it if context restoration fails.
+// Context-independent undo always runs. Context-sensitive undo runs only
+// after verifying that the target context remains current; otherwise the
+// resource leaks rather than risking cleanup in the wrong context.
+template <typename Fn, typename Undo>
+CUresult invoke_in_context_or_undo(const ContextHandle& h_context, Fn&& operation,
+                                   Undo&& undo, bool undo_requires_target_context) noexcept {
+    ASSERT_NOTHROW_INVOCABLE(Fn&&);
+    ASSERT_NOTHROW_INVOCABLE(Undo&&);
+    if (!h_context) {
+        return CUDA_ERROR_INVALID_CONTEXT;
+    }
+    CUcontext previous = nullptr;
+    int changed = 0;
+    CUresult status = enter_context(h_context, &previous, &changed);
+    if (status != CUDA_SUCCESS) {
+        return status;
+    }
+    status = std::invoke(std::forward<Fn>(operation));
+    CUresult composite = exit_context(previous, changed, status);
+    if (status == CUDA_SUCCESS && composite != CUDA_SUCCESS) {
+        bool undo_ok = true;
+        if (undo_requires_target_context) {
+            CUcontext current = nullptr;
+            undo_ok = p_cuCtxGetCurrent(&current) == CUDA_SUCCESS
+                      && current == as_cu(h_context);
+        }
+        if (undo_ok) {
+            std::invoke(std::forward<Undo>(undo));
+        } else {
+            warn_on_cuda_error(
+                "cuCtxSetCurrent (restoring the caller's context)", composite,
+                "failed; cleanup of the new resource skipped because its context "
+                "is no longer current (resource leaked)");
+        }
+    }
+    return composite;
+}
+
+// Write a warning that includes the CUDA error name and description.
+void warn_on_cuda_error(const char* operation, CUresult status, const char* detail) noexcept {
+    const char* error_name = nullptr;
+    const char* error_description = nullptr;
+    CUresult name_status = p_cuGetErrorName(status, &error_name);
+    CUresult description_status = p_cuGetErrorString(status, &error_description);
+
+    if (name_status == CUDA_SUCCESS && description_status == CUDA_SUCCESS) {
+        if (detail) {
+            std::fprintf(stderr, "Warning: %s %s: %s: %s\n",
+                         operation, detail, error_name, error_description);
+        } else {
+            std::fprintf(stderr, "Warning: %s failed: %s: %s\n",
+                         operation, error_name, error_description);
+        }
+    } else {
+        if (detail) {
+            std::fprintf(stderr, "Warning: %s %s (CUDA error %d)\n",
+                         operation, detail, static_cast<int>(status));
+        } else {
+            std::fprintf(stderr, "Warning: %s failed (CUDA error %d)\n",
+                         operation, static_cast<int>(status));
+        }
+    }
+}
+
+// Run cleanup with the requested context current. Warn and skip the operation
+// if activation fails, and independently warn on operation or restoration
+// failure. Return the operation or activation status; restoration never
+// changes the return value.
+template <typename Fn, typename... Args>
+CUresult cleanup_in_context(const ContextHandle& h_context, const char* name,
+                            Fn&& operation, Args&&... args) noexcept {
+    ASSERT_NOTHROW_INVOCABLE(Fn&&, Args&&...);
+    CUcontext previous = nullptr;
+    int changed = 0;
+    CUresult status = enter_context(h_context, &previous, &changed);
+    if (status != CUDA_SUCCESS) {
+        warn_on_cuda_error(name, status,
+                           "skipped (context activation failed; resource leaked)");
+    } else {
+        status = std::invoke(std::forward<Fn>(operation), std::forward<Args>(args)...);
+        if (status != CUDA_SUCCESS) {
+            warn_on_cuda_error(name, status);
+        }
+    }
+    CUresult restore = exit_context(previous, changed, CUDA_SUCCESS);
+    if (restore != CUDA_SUCCESS) {
+        warn_on_cuda_error(name, restore, "failed while restoring the caller's context");
+    }
+    return status;
+}
+
+#undef ASSERT_NOTHROW_INVOCABLE
+
+// Decorate a CUDA operation to warn whenever it returns an error.
+template <auto& Function>
+class WarnOnFailure {
+public:
+    explicit WarnOnFailure(const char* operation) noexcept : operation_(operation) {}
+
+    template <typename... Args>
+    CUresult operator()(Args&&... args) const noexcept {
+        CUresult status = Function(std::forward<Args>(args)...);
+        if (status != CUDA_SUCCESS) {
+            warn_on_cuda_error(operation_, status);
+        }
+        return status;
+    }
+
+private:
+    const char* operation_;
+};
+
+// Warning-decorated CUDA operations used by non-throwing cleanup paths.
+const WarnOnFailure<p_cuStreamDestroy> pw_cuStreamDestroy{"cuStreamDestroy"};
+const WarnOnFailure<p_cuEventDestroy> pw_cuEventDestroy{"cuEventDestroy"};
+const WarnOnFailure<p_cuMemFree> pw_cuMemFree{"cuMemFree"};
+const WarnOnFailure<p_cuMemFreeAsync> pw_cuMemFreeAsync{"cuMemFreeAsync"};
+const WarnOnFailure<p_cuArrayDestroy> pw_cuArrayDestroy{"cuArrayDestroy"};
+const WarnOnFailure<p_cuMipmappedArrayDestroy> pw_cuMipmappedArrayDestroy{"cuMipmappedArrayDestroy"};
+const WarnOnFailure<p_cuTexObjectDestroy> pw_cuTexObjectDestroy{"cuTexObjectDestroy"};
+const WarnOnFailure<p_cuSurfObjectDestroy> pw_cuSurfObjectDestroy{"cuSurfObjectDestroy"};
+
 }  // namespace
 
+// Synchronize the provided context.
+CUresult context_synchronize(const ContextHandle& h_context) noexcept {
+    GILReleaseGuard gil;
+    return invoke_in_context(h_context, []() noexcept {
+        return p_cuCtxSynchronize();
+    });
+}
+
+// Query the stream priority range for the provided context.
+CUresult context_get_stream_priority_range(const ContextHandle& h_context,
+                                           int* least_priority,
+                                           int* greatest_priority) noexcept {
+    GILReleaseGuard gil;
+    return invoke_in_context(h_context, [&]() noexcept {
+        return p_cuCtxGetStreamPriorityRange(least_priority, greatest_priority);
+    });
+}
+
 // ============================================================================
 // CUDA user-object deferred cleanup
 //
@@ -361,6 +597,15 @@ class HandleRegistry {
         map_.erase(key);
     }
 
+    void register_handles(const std::vector<Handle>& handles) {
+        std::lock_guard<std::mutex> lock(mutex_);
+        for (const Handle& h : handles) {
+            if (h) {
+                map_[*h] = h;
+            }
+        }
+    }
+
     Handle lookup(const Key& key) {
         std::lock_guard<std::mutex> lock(mutex_);
         auto it = map_.find(key);
@@ -410,12 +655,14 @@ class HandleRegistry {
 // Thread-local status of the most recent CUDA API call in this module.
 static thread_local CUresult err = CUDA_SUCCESS;
 
+// Return and clear the calling thread's most recent CUDA error.
 CUresult get_last_error() noexcept {
     CUresult e = err;
     err = CUDA_SUCCESS;
     return e;
 }
 
+// Return the calling thread's most recent CUDA error without clearing it.
 CUresult peek_last_error() noexcept {
     return err;
 }
@@ -608,22 +855,21 @@ static HandleRegistry<CUstream, StreamHandle> stream_registry;
 
 StreamHandle create_stream_handle(const ContextHandle& h_ctx, unsigned int flags, int priority) {
     GILReleaseGuard gil;
-    CUstream stream;
-
-    // Dispatch: green context uses cuGreenCtxStreamCreate, primary uses cuStreamCreateWithPriority
+    CUstream stream = nullptr;
     GreenCtxHandle h_green = get_context_green_ctx(h_ctx);
     if (h_green) {
-        if (!p_cuGreenCtxStreamCreate) {
-            err = CUDA_ERROR_NOT_SUPPORTED;
-            return {};
-        }
-        if (CUDA_SUCCESS != (err = p_cuGreenCtxStreamCreate(&stream, as_cu(h_green), flags, priority))) {
-            return {};
-        }
+        err = p_cuGreenCtxStreamCreate
+            ? p_cuGreenCtxStreamCreate(&stream, as_cu(h_green), flags, priority)
+            : CUDA_ERROR_NOT_SUPPORTED;
     } else {
-        if (CUDA_SUCCESS != (err = p_cuStreamCreateWithPriority(&stream, flags, priority))) {
-            return {};
-        }
+        err = invoke_in_context_or_undo(
+            h_ctx,
+            [&]() noexcept { return p_cuStreamCreateWithPriority(&stream, flags, priority); },
+            [&]() noexcept { pw_cuStreamDestroy(stream); },
+            /*undo_requires_target_context=*/false);
+    }
+    if (err != CUDA_SUCCESS) {
+        return {};
     }
 
     auto box = std::shared_ptr<const StreamBox>(
@@ -631,7 +877,7 @@ StreamHandle create_stream_handle(const ContextHandle& h_ctx, unsigned int flags
         [](const StreamBox* b) {
             stream_registry.unregister_handle(b->resource);
             GILReleaseGuard gil;
-            p_cuStreamDestroy(b->resource);
+            pw_cuStreamDestroy(b->resource);
             delete b;
         }
     );
@@ -701,6 +947,7 @@ void py_object_user_object_destroy(void* py_object) noexcept {
     Py_DECREF(reinterpret_cast<PyObject*>(py_object));
 }
 
+// Return the context retained by a stream handle.
 ContextHandle get_stream_context(const StreamHandle& h) noexcept {
     return h ? get_box(h)->h_context : ContextHandle{};
 }
@@ -715,6 +962,70 @@ StreamHandle get_per_thread_stream() {
     return handle;
 }
 
+StreamHandle create_context_bound_legacy_stream(const ContextHandle& h_context) {
+    if (!h_context) {
+        return {};
+    }
+    // Default deleter: this handle never owns CU_STREAM_LEGACY, so nothing
+    // needs to run when the last reference is released.
+    auto box = std::make_shared<const StreamBox>(StreamBox{CU_STREAM_LEGACY, h_context});
+    return StreamHandle(box, &box->resource);
+}
+
+// ============================================================================
+// Deallocation streams
+//
+// A DeallocationStream is a StreamHandle used for ordering frees. It differs
+// from an ordinary StreamHandle only for default-stream tokens, for which it
+// stores the (de)allocation context. Ordinarily, the LEGACY and PER_THREAD
+// default streams resolve to whichever context is active at the time they are
+// used, but for storing deallocation recipes we need to pin the context. With
+// the PER_THREAD token, it is not possible to restore the original stream when
+// deallocation runs on a different thread. Therefore, in that case the
+// allocating host thread id is also stored so that cross-thread frees can be
+// detected and warnings can be issued.
+// ============================================================================
+
+// Real streams are copied unchanged. Default-stream tokens without an embedded
+// context are bound to the current context. Returns false (and sets err) when a
+// default-stream token cannot be bound because no context is current.
+static bool make_deallocation_stream(
+        const StreamHandle& h, DeallocationStream& out) noexcept {
+    out = {};
+    if (!h) {
+        return true;
+    }
+
+    const CUstream stream = as_cu(h);
+    if (!is_default_stream(stream)) {
+        out = DeallocationStream{h, {}};
+        return true;
+    }
+
+    StreamHandle h_bound = h;
+    if (!get_stream_context(h)) {
+        ContextHandle h_ctx = get_current_context();
+        if (!h_ctx) {
+            if (err == CUDA_SUCCESS) {
+                err = CUDA_ERROR_INVALID_CONTEXT;
+            }
+            return false;
+        }
+        // Do not register in stream_registry: the token value alone is not
+        // a unique stream identity (context is part of the meaning).
+        auto box = std::shared_ptr<const StreamBox>(
+            new StreamBox{stream, h_ctx});
+        h_bound = StreamHandle(box, &box->resource);
+    }
+
+    std::thread::id ptds_tid{};
+    if (stream == CU_STREAM_PER_THREAD) {
+        ptds_tid = std::this_thread::get_id();
+    }
+    out = DeallocationStream{std::move(h_bound), ptds_tid};
+    return true;
+}
+
 // ============================================================================
 // Event Handles
 // ============================================================================
@@ -753,6 +1064,7 @@ int get_event_device_id(const EventHandle& h) noexcept {
     return h ? get_box(h)->device_id : -1;
 }
 
+// Return the context retained by an event handle.
 ContextHandle get_event_context(const EventHandle& h) noexcept {
     return h ? get_box(h)->h_context : ContextHandle{};
 }
@@ -764,17 +1076,22 @@ EventHandle create_event_handle(const ContextHandle& h_ctx, unsigned int flags,
                                 bool timing_enabled, bool is_blocking_sync,
                                 bool ipc_enabled, int device_id) {
     GILReleaseGuard gil;
-    CUevent event;
-    if (CUDA_SUCCESS != (err = p_cuEventCreate(&event, flags))) {
+    CUevent event = nullptr;
+    err = invoke_in_context_or_undo(
+        h_ctx,
+        [&]() noexcept { return p_cuEventCreate(&event, flags); },
+        [&]() noexcept { pw_cuEventDestroy(event); },
+        /*undo_requires_target_context=*/false);
+    if (err != CUDA_SUCCESS) {
         return {};
     }
 
     auto box = std::shared_ptr<const EventBox>(
         new EventBox{event, timing_enabled, is_blocking_sync, ipc_enabled, device_id, h_ctx},
-        [h_ctx](const EventBox* b) {
+        [](const EventBox* b) {
             event_registry.unregister_handle(b->resource);
             GILReleaseGuard gil;
-            p_cuEventDestroy(b->resource);
+            pw_cuEventDestroy(b->resource);
             delete b;
         }
     );
@@ -783,8 +1100,23 @@ EventHandle create_event_handle(const ContextHandle& h_ctx, unsigned int flags,
     return h;
 }
 
-EventHandle create_event_handle_noctx(unsigned int flags) {
-    return create_event_handle(ContextHandle{}, flags, false, false, false, -1);
+EventHandle create_event_handle_for_stream(CUstream stream, unsigned int flags) {
+    // Resolve the stream's owning context (for default-stream tokens this is
+    // the current context, per cuStreamGetCtx) and create the event there, so
+    // it can be recorded on `stream` no matter which context is current.
+    CUcontext ctx = nullptr;
+    {
+        GILReleaseGuard gil;
+        err = p_cuStreamGetCtx(stream, &ctx);
+    }
+    if (err != CUDA_SUCCESS) {
+        return {};
+    }
+    if (!ctx) {
+        err = CUDA_ERROR_INVALID_CONTEXT;
+        return {};
+    }
+    return create_event_handle(create_context_handle_ref(ctx), flags, false, false, false, -1);
 }
 
 EventHandle create_event_handle_ref(CUevent event) {
@@ -808,7 +1140,7 @@ EventHandle create_event_handle_ipc(const CUipcEventHandle& ipc_handle,
         [](const EventBox* b) {
             event_registry.unregister_handle(b->resource);
             GILReleaseGuard gil;
-            p_cuEventDestroy(b->resource);
+            pw_cuEventDestroy(b->resource);
             delete b;
         }
     );
@@ -902,10 +1234,10 @@ MemoryPoolHandle create_mempool_handle_ipc(int fd, CUmemAllocationHandleType han
 namespace {
 struct DevicePtrBox {
     CUdeviceptr resource;
-    // Mutable to allow set_deallocation_stream() to update the stream
-    // through a const DevicePtrHandle. The stream can be changed after
-    // allocation (e.g., to synchronize deallocation with a different stream).
-    mutable StreamHandle h_stream;
+    // Mutable so set_deallocation_stream() can update free ordering through a
+    // const DevicePtrHandle. Built with make_deallocation_stream so default-
+    // stream tokens carry a bound context.
+    mutable DeallocationStream deallocation;
 };
 }  // namespace
 
@@ -913,7 +1245,7 @@ struct DevicePtrBox {
 // This works because DevicePtrHandle is a shared_ptr alias pointing to
 // &box->resource, so we can compute the containing struct using offsetof.
 // The const_cast is safe because we only use this to access the mutable
-// h_stream member or in the deleter (where the box is being destroyed).
+// deallocation member or in the deleter (where the box is being destroyed).
 static DevicePtrBox* get_box(const DevicePtrHandle& h) {
     const CUdeviceptr* p = h.get();
     return reinterpret_cast<DevicePtrBox*>(
@@ -921,12 +1253,22 @@ static DevicePtrBox* get_box(const DevicePtrHandle& h) {
     );
 }
 
+// Return the stream that orders a device pointer's deallocation.
 StreamHandle deallocation_stream(const DevicePtrHandle& h) noexcept {
-    return get_box(h)->h_stream;
+    return get_box(h)->deallocation.h_stream;
 }
 
-void set_deallocation_stream(const DevicePtrHandle& h, const StreamHandle& h_stream) noexcept {
-    get_box(h)->h_stream = h_stream;
+// Replace the stream that orders a device pointer's deallocation.
+CUresult set_deallocation_stream(const DevicePtrHandle& h, const StreamHandle& h_stream) noexcept {
+    if (!h) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+    DeallocationStream ds;
+    if (!make_deallocation_stream(h_stream, ds)) {
+        return err != CUDA_SUCCESS ? err : CUDA_ERROR_INVALID_CONTEXT;
+    }
+    get_box(h)->deallocation = std::move(ds);
+    return CUDA_SUCCESS;
 }
 
 DevicePtrHandle deviceptr_alloc_from_pool(size_t size, const MemoryPoolHandle& h_pool, const StreamHandle& h_stream) {
@@ -936,11 +1278,23 @@ DevicePtrHandle deviceptr_alloc_from_pool(size_t size, const MemoryPoolHandle& h
         return {};
     }
 
+    DeallocationStream ds;
+    if (!make_deallocation_stream(h_stream, ds)) {
+        pw_cuMemFreeAsync(ptr, as_cu(h_stream));
+        return {};
+    }
+
     auto box = std::shared_ptr<DevicePtrBox>(
-        new DevicePtrBox{ptr, h_stream},
+        new DevicePtrBox{ptr, std::move(ds)},
         [h_pool](DevicePtrBox* b) {
             GILReleaseGuard gil;
-            p_cuMemFreeAsync(b->resource, as_cu(b->h_stream));
+            const DeallocationStream& stream = b->deallocation;
+            cleanup_in_context(
+                deallocation_context(stream), "cuMemFreeAsync",
+                [&]() noexcept {
+                    return p_cuMemFreeAsync(
+                        b->resource, as_cu(stream.h_stream));
+                });
             delete b;
         }
     );
@@ -954,35 +1308,40 @@ DevicePtrHandle deviceptr_alloc_async(size_t size, const StreamHandle& h_stream)
         return {};
     }
 
-    auto box = std::shared_ptr<DevicePtrBox>(
-        new DevicePtrBox{ptr, h_stream},
-        [](DevicePtrBox* b) {
-            GILReleaseGuard gil;
-            p_cuMemFreeAsync(b->resource, as_cu(b->h_stream));
-            delete b;
-        }
-    );
-    return DevicePtrHandle(box, &box->resource);
-}
-
-DevicePtrHandle deviceptr_alloc(size_t size) {
-    GILReleaseGuard gil;
-    CUdeviceptr ptr;
-    if (CUDA_SUCCESS != (err = p_cuMemAlloc(&ptr, size))) {
+    DeallocationStream ds;
+    if (!make_deallocation_stream(h_stream, ds)) {
+        pw_cuMemFreeAsync(ptr, as_cu(h_stream));
         return {};
     }
 
     auto box = std::shared_ptr<DevicePtrBox>(
-        new DevicePtrBox{ptr, StreamHandle{}},
+        new DevicePtrBox{ptr, std::move(ds)},
         [](DevicePtrBox* b) {
             GILReleaseGuard gil;
-            p_cuMemFree(b->resource);
+            const DeallocationStream& stream = b->deallocation;
+            cleanup_in_context(
+                deallocation_context(stream), "cuMemFreeAsync",
+                [&]() noexcept {
+                    return p_cuMemFreeAsync(
+                        b->resource, as_cu(stream.h_stream));
+                });
             delete b;
         }
     );
     return DevicePtrHandle(box, &box->resource);
 }
 
+// Allocate device memory synchronously with the provided context current.
+CUresult deviceptr_alloc_raw(CUdeviceptr* ptr, size_t size,
+                             const ContextHandle& h_context) noexcept {
+    GILReleaseGuard gil;
+    return invoke_in_context_or_undo(
+        h_context,
+        [&]() noexcept { return p_cuMemAlloc(ptr, size); },
+        [&]() noexcept { pw_cuMemFree(*ptr); },
+        /*undo_requires_target_context=*/false);
+}
+
 DevicePtrHandle deviceptr_alloc_host(size_t size) {
     GILReleaseGuard gil;
     void* ptr;
@@ -991,7 +1350,7 @@ DevicePtrHandle deviceptr_alloc_host(size_t size) {
     }
 
     auto box = std::shared_ptr<DevicePtrBox>(
-        new DevicePtrBox{reinterpret_cast<CUdeviceptr>(ptr), StreamHandle{}},
+        new DevicePtrBox{reinterpret_cast<CUdeviceptr>(ptr), DeallocationStream{}},
         [](DevicePtrBox* b) {
             GILReleaseGuard gil;
             p_cuMemFreeHost(reinterpret_cast<void*>(b->resource));
@@ -1002,7 +1361,7 @@ DevicePtrHandle deviceptr_alloc_host(size_t size) {
 }
 
 DevicePtrHandle deviceptr_create_ref(CUdeviceptr ptr) {
-    auto box = std::make_shared<DevicePtrBox>(DevicePtrBox{ptr, StreamHandle{}});
+    auto box = std::make_shared<DevicePtrBox>(DevicePtrBox{ptr, DeallocationStream{}});
     return DevicePtrHandle(box, &box->resource);
 }
 
@@ -1018,7 +1377,7 @@ DevicePtrHandle deviceptr_create_with_owner(CUdeviceptr ptr, PyObject* owner) {
     }
     Py_INCREF(owner);
     auto box = std::shared_ptr<DevicePtrBox>(
-        new DevicePtrBox{ptr, StreamHandle{}},
+        new DevicePtrBox{ptr, DeallocationStream{}},
         [owner](DevicePtrBox* b) {
             GILAcquireGuard gil;
             if (gil.acquired()) {
@@ -1035,12 +1394,22 @@ DevicePtrHandle deviceptr_create_mapped_graphics(
     const GraphicsResourceHandle& h_resource,
     const StreamHandle& h_stream
 ) {
+    DeallocationStream ds;
+    if (!make_deallocation_stream(h_stream, ds)) {
+        return {};
+    }
     auto box = std::shared_ptr<DevicePtrBox>(
-        new DevicePtrBox{ptr, h_stream},
+        new DevicePtrBox{ptr, std::move(ds)},
         [h_resource](DevicePtrBox* b) {
             GILReleaseGuard gil;
             CUgraphicsResource resource = as_cu(h_resource);
-            p_cuGraphicsUnmapResources(1, &resource, as_cu(b->h_stream));
+            const DeallocationStream& stream = b->deallocation;
+            cleanup_in_context(
+                deallocation_context(stream), "cuGraphicsUnmapResources",
+                [&]() noexcept {
+                    return p_cuGraphicsUnmapResources(
+                        1, &resource, as_cu(stream.h_stream));
+                });
             delete b;
         }
     );
@@ -1068,12 +1437,18 @@ DevicePtrHandle deviceptr_create_with_mr(CUdeviceptr ptr, size_t size, PyObject*
     }
     Py_INCREF(mr);
     auto box = std::shared_ptr<DevicePtrBox>(
-        new DevicePtrBox{ptr, StreamHandle{}},
+        new DevicePtrBox{ptr, DeallocationStream{}},
         [mr, size](DevicePtrBox* b) {
             GILAcquireGuard gil;
             if (gil.acquired()) {
                 if (mr_dealloc_cb) {
-                    mr_dealloc_cb(mr, b->resource, size, b->h_stream);
+                    const DeallocationStream& stream = b->deallocation;
+                    cleanup_in_context(
+                        deallocation_context(stream), "MemoryResource.deallocate",
+                        [&]() noexcept {
+                            mr_dealloc_cb(mr, b->resource, size, stream.h_stream);
+                            return CUDA_SUCCESS;
+                        });
                 }
                 Py_DECREF(mr);
             }
@@ -1161,12 +1536,24 @@ DevicePtrHandle deviceptr_import_ipc(const MemoryPoolHandle& h_pool, const void*
             return {};
         }
 
+        DeallocationStream ds;
+        if (!make_deallocation_stream(h_stream, ds)) {
+            pw_cuMemFreeAsync(ptr, as_cu(h_stream));
+            return {};
+        }
+
         auto box = std::shared_ptr<DevicePtrBox>(
-            new DevicePtrBox{ptr, h_stream},
+            new DevicePtrBox{ptr, std::move(ds)},
             [h_pool, key](DevicePtrBox* b) {
                 ipc_ptr_cache.unregister_handle(key);
                 GILReleaseGuard gil;
-                p_cuMemFreeAsync(b->resource, as_cu(b->h_stream));
+                const DeallocationStream& stream = b->deallocation;
+                cleanup_in_context(
+                    deallocation_context(stream), "cuMemFreeAsync",
+                    [&]() noexcept {
+                        return p_cuMemFreeAsync(
+                            b->resource, as_cu(stream.h_stream));
+                    });
                 delete b;
             }
         );
@@ -1181,11 +1568,23 @@ DevicePtrHandle deviceptr_import_ipc(const MemoryPoolHandle& h_pool, const void*
             return {};
         }
 
+        DeallocationStream ds;
+        if (!make_deallocation_stream(h_stream, ds)) {
+            pw_cuMemFreeAsync(ptr, as_cu(h_stream));
+            return {};
+        }
+
         auto box = std::shared_ptr<DevicePtrBox>(
-            new DevicePtrBox{ptr, h_stream},
+            new DevicePtrBox{ptr, std::move(ds)},
             [h_pool](DevicePtrBox* b) {
                 GILReleaseGuard gil;
-                p_cuMemFreeAsync(b->resource, as_cu(b->h_stream));
+                const DeallocationStream& stream = b->deallocation;
+                cleanup_in_context(
+                    deallocation_context(stream), "cuMemFreeAsync",
+                    [&]() noexcept {
+                        return p_cuMemFreeAsync(
+                            b->resource, as_cu(stream.h_stream));
+                    });
                 delete b;
             }
         );
@@ -1341,7 +1740,8 @@ struct GraphHierarchy {
 };
 
 // See REGISTRY_DESIGN.md (Level 1: Driver Handle -> Resource Handle)
-static HandleRegistry<CUgraph, GraphHandle> graph_registry;
+using GraphRegistry = HandleRegistry<CUgraph, GraphHandle>;
+static GraphRegistry graph_registry;
 
 // Immutable resource owners for one version of a graph node's parameters.
 // Inheriting DeferredCleanupItem lets CUDA's user-object destructor enqueue
@@ -1404,52 +1804,71 @@ CUresult rekey_attachments(
     return CUDA_SUCCESS;
 }
 
-// Recursively copy and rekey attachments for a cloned graph hierarchy.
-// The caller must release the GIL before calling this function.
-CUresult copy_attachments(
+struct StagedGraphMetadata {
+    const GraphBox* source;
+    GraphBox* clone;
+    GraphAttachmentMap* attachments;
+};
+using StagedGraphMetadataList = std::vector<StagedGraphMetadata>;
+
+// Copy a source hierarchy into detached metadata before CUDA mutation.
+void stage_graph_metadata(
         const GraphBox& source,
         GraphBox& clone,
         GraphAttachmentMap& attachments,
-        std::list<GraphBox>& subgraphs) {
-    if (!p_cuGraphNodeFindInClone || !p_cuGraphChildGraphNodeGetGraph) {
-        return CUDA_ERROR_NOT_SUPPORTED;
-    }
-
+        std::list<GraphBox>& subgraphs,
+        StagedGraphMetadataList& staged) {
     attachments = source.attachments;
-    CUresult status = rekey_attachments(attachments, clone.resource);
-    if (status != CUDA_SUCCESS) {
-        return status;
-    }
+    staged.push_back({&source, &clone, &attachments});
 
     for (const GraphBox& source_child : source.hierarchy->graphs) {
         if (source_child.parent != &source || !source_child.resource) {
             continue;
         }
-
-        CUgraphNode cloned_owner = nullptr;
-        status = p_cuGraphNodeFindInClone(
-            &cloned_owner, source_child.owner_node, clone.resource);
-        if (status != CUDA_SUCCESS) {
-            return status;
-        }
-
-        CUgraph cloned_graph = nullptr;
-        status = p_cuGraphChildGraphNodeGetGraph(
-            cloned_owner, &cloned_graph);
-        if (status != CUDA_SUCCESS) {
-            return status;
-        }
-
         GraphBox& cloned_child = subgraphs.emplace_back(
-            cloned_graph,
+            nullptr,
             clone.hierarchy,
             &clone,
-            cloned_owner);
-        status = copy_attachments(
+            nullptr);
+        stage_graph_metadata(
             source_child,
             cloned_child,
             cloned_child.attachments,
-            subgraphs);
+            subgraphs,
+            staged);
+    }
+}
+
+// Bind staged metadata to a CUDA-cloned hierarchy. The root clone resource
+// must be populated before entry. The caller must release the GIL.
+CUresult rekey_graph_metadata(
+        StagedGraphMetadataList& staged) {
+    if (!p_cuGraphNodeFindInClone || !p_cuGraphChildGraphNodeGetGraph) {
+        return CUDA_ERROR_NOT_SUPPORTED;
+    }
+
+    CUresult status;
+    for (size_t i = 0; i < staged.size(); ++i) {
+        const GraphBox& source = *staged[i].source;
+        GraphBox& clone = *staged[i].clone;
+        if (i != 0) {
+            CUgraphNode cloned_owner = nullptr;
+            status = p_cuGraphNodeFindInClone(
+                &cloned_owner,
+                source.owner_node,
+                clone.parent->resource);
+            if (status == CUDA_SUCCESS) {
+                status = p_cuGraphChildGraphNodeGetGraph(
+                    cloned_owner, &clone.resource);
+            }
+            if (status != CUDA_SUCCESS) {
+                return status;
+            }
+            clone.owner_node = cloned_owner;
+        }
+
+        status = rekey_attachments(
+            *staged[i].attachments, clone.resource);
         if (status != CUDA_SUCCESS) {
             return status;
         }
@@ -1497,6 +1916,29 @@ void rollback_prepared_attachment(
     delete state;
 }
 
+// Detached metadata for a replacement embedded graph hierarchy. Preparation
+// copies every attachment map and allocates every GraphBox before CUDA destroys
+// the old embedded graph. Commit only rekeys and publishes it.
+struct PreparedChildGraphUpdateState {
+    GraphHandle h_parent;
+    GraphHandle h_source;
+    GraphBox* old_root = nullptr;
+    CUgraphNode owner_node = nullptr;
+    std::list<GraphBox> replacement;
+    StagedGraphMetadataList staged;
+    std::vector<GraphHandle> handles;
+
+    PreparedChildGraphUpdateState(
+            GraphHandle h_parent_,
+            GraphHandle h_source_,
+            GraphBox* old_root_,
+            CUgraphNode owner_node_)
+        : h_parent(std::move(h_parent_)),
+          h_source(std::move(h_source_)),
+          old_root(old_root_),
+          owner_node(owner_node_) {}
+};
+
 GraphHandle create_graph_handle(CUgraph graph) {
     if (!graph) {
         return {};
@@ -1543,15 +1985,112 @@ GraphHandle create_child_graph_handle(
         child_graph, hierarchy, parent, owner_node);
 
     GraphHandle h_child(h_parent, &child.resource);
-    try {
-        graph_registry.register_handle(child_graph, h_child);
-    } catch (...) {
-        hierarchy->graphs.pop_back();
-        throw;
-    }
+    graph_registry.register_handle(child_graph, h_child);
     return h_child;
 }
 
+CUresult graph_prepare_child_graph_update(
+        const GraphHandle& h_parent,
+        const GraphHandle& h_old_child,
+        CUgraphNode owner_node,
+        const GraphHandle& h_source,
+        PreparedChildGraphUpdate* out_prepared) {
+    if (!h_parent || !h_old_child || !owner_node ||
+        !h_source || !out_prepared) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+    out_prepared->reset();
+
+    GraphBox* parent = get_box(h_parent);
+    GraphBox* old_root = get_box(h_old_child);
+    GraphBox* source = get_box(h_source);
+    // A source from the destination hierarchy can include the old embedded
+    // subtree whose raw node keys CUDA destroys during replacement.
+    if (!parent->resource || !old_root->resource || !source->resource ||
+        old_root->parent != parent ||
+        old_root->owner_node != owner_node ||
+        source->hierarchy == parent->hierarchy) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+
+    PreparedChildGraphUpdate prepared =
+        std::make_shared<PreparedChildGraphUpdateState>(
+            h_parent, h_source, old_root, owner_node);
+
+    GraphBox& replacement_root =
+        prepared->replacement.emplace_back(
+            nullptr, parent->hierarchy, parent, owner_node);
+    stage_graph_metadata(
+        *source,
+        replacement_root,
+        replacement_root.attachments,
+        prepared->replacement,
+        prepared->staged);
+
+    const size_t graph_count = prepared->staged.size();
+    prepared->handles.reserve(graph_count);
+    for (const StagedGraphMetadata& graph : prepared->staged) {
+        prepared->handles.emplace_back(
+            h_parent, &graph.clone->resource);
+    }
+
+    *out_prepared = std::move(prepared);
+    return CUDA_SUCCESS;
+}
+
+void publish_child_graph_update(
+        PreparedChildGraphUpdateState& state,
+        GraphHandle* out_child) {
+    GraphBox* parent = get_box(state.h_parent);
+    parent->hierarchy->graphs.splice(
+        parent->hierarchy->graphs.end(), state.replacement);
+    *out_child = state.handles.front();
+    graph_registry.register_handles(state.handles);
+}
+
+CUresult graph_commit_child_graph_update(
+        PreparedChildGraphUpdate& prepared,
+        GraphHandle* out_child) {
+    if (!prepared || !out_child) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+    out_child->reset();
+
+    PreparedChildGraphUpdateState& state = *prepared;
+    GraphBox* parent = get_box(state.h_parent);
+    if (!parent->resource || !state.old_root->resource) {
+        prepared.reset();
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+
+    CUresult status = CUDA_ERROR_NOT_SUPPORTED;
+    CUgraph cloned_root = nullptr;
+    if (p_cuGraphChildGraphNodeGetGraph) {
+        GILReleaseGuard gil;
+        status = p_cuGraphChildGraphNodeGetGraph(
+            state.owner_node, &cloned_root);
+        if (status == CUDA_SUCCESS) {
+            state.staged.front().clone->resource = cloned_root;
+            status = rekey_graph_metadata(state.staged);
+        }
+    }
+
+    // CUDA has already destroyed the old embedded graph. No replacement
+    // metadata is visible yet, so this selects only the old generation.
+    invalidate_child_graph_state(
+        state.h_parent, state.owner_node);
+
+    if (status != CUDA_SUCCESS) {
+        prepared.reset();
+        throw std::runtime_error(
+            "failed to update graph metadata after child graph replacement");
+    }
+
+    publish_child_graph_update(state, out_child);
+    prepared.reset();
+    return status;
+}
+
 CUresult graph_get_attachment(
         const GraphHandle& h_graph, CUgraphNode node,
         OpaqueHandle* owner0, OpaqueHandle* owner1) {
@@ -1727,13 +2266,22 @@ CUresult graph_clone_attachments(
 
     // Build and rekey the clone metadata off-hierarchy so a CUDA mapping error
     // cannot partially publish it.
-    GraphAttachmentMap attachments = source->attachments;
+    GraphAttachmentMap attachments;
     std::list<GraphBox> subgraphs;
+    StagedGraphMetadataList staged;
+    stage_graph_metadata(
+        *source, *clone, attachments, subgraphs, staged);
+
+    std::vector<GraphHandle> handles;
+    handles.reserve(subgraphs.size());
+    for (GraphBox& graph : subgraphs) {
+        handles.emplace_back(h_clone, &graph.resource);
+    }
+
     CUresult status;
     {
         GILReleaseGuard gil;
-        status = copy_attachments(
-            *source, *clone, attachments, subgraphs);
+        status = rekey_graph_metadata(staged);
     }
     if (status != CUDA_SUCCESS) {
         return status;
@@ -1744,13 +2292,9 @@ CUresult graph_clone_attachments(
         return CUDA_SUCCESS;
     }
 
-    auto first = subgraphs.begin();
     clone->hierarchy->graphs.splice(
         clone->hierarchy->graphs.end(), subgraphs);
-    for (auto it = first; it != clone->hierarchy->graphs.end(); ++it) {
-        GraphHandle h_graph(h_clone, &it->resource);
-        graph_registry.register_handle(it->resource, h_graph);
-    }
+    graph_registry.register_handles(handles);
     return CUDA_SUCCESS;
 }
 
@@ -1759,26 +2303,274 @@ CUresult graph_clone_attachments(
 // ============================================================================
 
 namespace {
+
+// Append-only owners introduced by individual executable-node updates. CUDA
+// owns this payload through a user object propagated into the CUgraphExec.
+struct ExecAttachments : DeferredCleanupItem {
+    CUuserObject object = nullptr;
+    std::vector<OpaqueHandle> owners;
+};
+
 struct GraphExecBox {
-    CUgraphExec resource;
+    CUgraphExec resource = nullptr;
+    ExecAttachments* attachments = nullptr;  // Non-owning.
+
+    ~GraphExecBox() noexcept {
+        if (resource) {
+            GILReleaseGuard gil;
+            p_cuGraphExecDestroy(resource);
+        }
+        // The accumulator fields may be dangling after exec destruction.
+        retry_deferred_cleanup();
+    }
 };
-}  // namespace
 
-GraphExecHandle create_graph_exec_handle(CUgraphExec graph_exec) {
-    auto box = std::shared_ptr<const GraphExecBox>(
-        new GraphExecBox{graph_exec},
-        [](const GraphExecBox* b) {
-            {
+GraphExecBox* get_exec_box(const GraphExecHandle& h) noexcept {
+    return const_cast<GraphExecBox*>(
+        reinterpret_cast<const GraphExecBox*>(h.get()));
+}
+
+GraphExecHandle make_graph_exec_handle(
+        CUgraphExec graph_exec, ExecAttachments* attachments) {
+    struct RawGraphExecGuard {
+        CUgraphExec resource;
+
+        ~RawGraphExecGuard() noexcept {
+            if (resource) {
                 GILReleaseGuard gil;
-                p_cuGraphExecDestroy(b->resource);
+                p_cuGraphExecDestroy(resource);
             }
             retry_deferred_cleanup();
-            delete b;
         }
-    );
+    } guard{graph_exec};
+
+    auto box = std::make_shared<GraphExecBox>();
+    box->resource = graph_exec;
+    box->attachments = attachments;
+    guard.resource = nullptr;
     return GraphExecHandle(box, &box->resource);
 }
 
+// Holds a fresh accumulator retained on the source graph across a CUDA call
+// that propagates user objects into an exec. Releasing drops the source's
+// reference: after successful propagation the exec keeps the accumulator
+// alive, and otherwise this drops its last reference.
+struct ExecAttachmentStaging {
+    GraphHandle h_source;
+    ExecAttachments* accumulator = nullptr;
+
+    ~ExecAttachmentStaging() noexcept {
+        release();
+    }
+
+    CUresult release() noexcept {
+        if (!h_source || !accumulator) {
+            return CUDA_SUCCESS;
+        }
+        const CUuserObject object = accumulator->object;
+        const GraphHandle source = std::move(h_source);
+        accumulator = nullptr;
+        GILReleaseGuard gil;
+        return p_cuGraphReleaseUserObject(*source, object, 1);
+    }
+};
+
+// Create an accumulator and retain it on h_source, so that a following
+// instantiation or whole-graph update propagates a reference into the exec.
+CUresult stage_exec_attachments(
+        const GraphHandle& h_source, ExecAttachmentStaging* out_staging) {
+    if (!p_cuUserObjectCreate || !p_cuUserObjectRelease ||
+        !p_cuGraphRetainUserObject || !p_cuGraphReleaseUserObject) {
+        return CUDA_ERROR_NOT_SUPPORTED;
+    }
+
+    ensure_deferred_cleanup_ready();
+    auto* accumulator = new ExecAttachments;
+
+    CUuserObject object = nullptr;
+    CUresult status;
+    {
+        GILReleaseGuard gil;
+        status = p_cuUserObjectCreate(
+            &object,
+            static_cast<DeferredCleanupItem*>(accumulator),
+            reinterpret_cast<CUhostFn>(enqueue_cleanup),
+            1,
+            CU_USER_OBJECT_NO_DESTRUCTOR_SYNC);
+        if (status != CUDA_SUCCESS) {
+            delete accumulator;
+            return status;
+        }
+        accumulator->object = object;
+        status = p_cuGraphRetainUserObject(
+            *h_source, object, 1, CU_GRAPH_USER_OBJECT_MOVE);
+        if (status != CUDA_SUCCESS) {
+            // Dropping the last reference retires the accumulator.
+            p_cuUserObjectRelease(object, 1);
+            return status;
+        }
+    }
+
+    out_staging->h_source = h_source;
+    out_staging->accumulator = accumulator;
+    return CUDA_SUCCESS;
+}
+
+}  // namespace
+
+// State held by PreparedExecAttachment between preparation and commit. It keeps
+// the exec alive and remembers the accumulator size before the append, so that
+// rollback can drop owners staged for a mutation that CUDA rejected.
+struct PreparedExecAttachmentState {
+    GraphExecHandle h_exec;
+    ExecAttachments* attachments = nullptr;
+    size_t original_size = 0;
+
+    PreparedExecAttachmentState(
+            GraphExecHandle h_exec_,
+            ExecAttachments* attachments_,
+            size_t original_size_)
+        : h_exec(std::move(h_exec_)),
+          attachments(attachments_),
+          original_size(original_size_) {}
+};
+
+void rollback_prepared_exec_attachment(
+        PreparedExecAttachmentState* state) noexcept {
+    if (!state) {
+        return;
+    }
+    if (state->attachments) {
+        while (state->attachments->owners.size() > state->original_size) {
+            state->attachments->owners.pop_back();
+        }
+    }
+    delete state;
+}
+
+GraphExecHandle create_graph_exec_handle(
+        const GraphHandle& h_source,
+        CUDA_GRAPH_INSTANTIATE_PARAMS* params) {
+    if (!h_source || !*h_source || !params) {
+        err = CUDA_ERROR_INVALID_VALUE;
+        return {};
+    }
+    if (!p_cuGraphInstantiateWithParams) {
+        err = CUDA_ERROR_NOT_SUPPORTED;
+        return {};
+    }
+
+    ExecAttachmentStaging staging;
+    if (CUDA_SUCCESS != (err = stage_exec_attachments(h_source, &staging))) {
+        return {};
+    }
+
+    CUgraphExec graph_exec = nullptr;
+    {
+        GILReleaseGuard gil;
+        err = p_cuGraphInstantiateWithParams(&graph_exec, *h_source, params);
+    }
+    if (err != CUDA_SUCCESS) {
+        return {};
+    }
+    // CUDA can report a specific failure while returning success. The exec is
+    // then unusable, so it stays unadopted for the caller to diagnose from
+    // params->result_out.
+    if (params->result_out != CUDA_GRAPH_INSTANTIATE_SUCCESS) {
+        return {};
+    }
+    if (!graph_exec) {
+        err = CUDA_ERROR_INVALID_VALUE;
+        return {};
+    }
+
+    GraphExecHandle h_exec = make_graph_exec_handle(
+        graph_exec, staging.accumulator);
+    if (CUDA_SUCCESS != (err = staging.release())) {
+        return {};
+    }
+    return h_exec;
+}
+
+CUresult graph_exec_update(
+        const GraphExecHandle& h_exec,
+        const GraphHandle& h_source,
+        CUgraphExecUpdateResultInfo* result_info) {
+    if (!h_exec || !h_source || !*h_source || !result_info) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+    if (!p_cuGraphExecUpdate) {
+        return CUDA_ERROR_NOT_SUPPORTED;
+    }
+
+    GraphExecBox* box = get_exec_box(h_exec);
+    if (!box->resource) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+
+    ExecAttachmentStaging staging;
+    CUresult status = stage_exec_attachments(h_source, &staging);
+    if (status != CUDA_SUCCESS) {
+        return status;
+    }
+
+    {
+        GILReleaseGuard gil;
+        status = p_cuGraphExecUpdate(box->resource, *h_source, result_info);
+    }
+    if (status != CUDA_SUCCESS) {
+        return status;
+    }
+
+    // CUDA may already have retired the old accumulator. Publish the new one
+    // before releasing the source graph's temporary reference.
+    box->attachments = staging.accumulator;
+    return staging.release();
+}
+
+CUresult graph_prepare_exec_attachment(
+        const GraphExecHandle& h_exec,
+        OpaqueHandle owner0,
+        OpaqueHandle owner1,
+        PreparedExecAttachment* out_prepared) {
+    if (!out_prepared) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+    out_prepared->reset();
+    if (!h_exec) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+
+    GraphExecBox* box = get_exec_box(h_exec);
+    if (!box->resource || !box->attachments) {
+        return CUDA_ERROR_INVALID_VALUE;
+    }
+
+    ExecAttachments* attachments = box->attachments;
+    const size_t original_size = attachments->owners.size();
+    const size_t additions =
+        static_cast<size_t>(static_cast<bool>(owner0)) +
+        static_cast<size_t>(static_cast<bool>(owner1));
+    // Reserve before staging so that rollback and commit cannot allocate.
+    attachments->owners.reserve(original_size + additions);
+    PreparedExecAttachment prepared(
+        new PreparedExecAttachmentState(h_exec, attachments, original_size),
+        PreparedExecAttachmentDeleter{rollback_prepared_exec_attachment});
+    if (owner0) {
+        attachments->owners.emplace_back(std::move(owner0));
+    }
+    if (owner1) {
+        attachments->owners.emplace_back(std::move(owner1));
+    }
+    *out_prepared = std::move(prepared);
+    return CUDA_SUCCESS;
+}
+
+void graph_commit_exec_attachment(
+        PreparedExecAttachment& prepared) noexcept {
+    delete prepared.release();
+}
+
 namespace {
 struct GraphNodeBox {
     mutable CUgraphNode resource;
@@ -2045,12 +2837,18 @@ struct ArrayBox {
     // Non-null only for a mipmap-level view: keeps the parent mipmap (the real
     // owner of the level's storage) alive for as long as the level is held.
     MipmappedArrayHandle h_parent;
+    ContextHandle h_context;
 };
 
 struct MipmappedArrayBox {
     CUmipmappedArray resource;
+    ContextHandle h_context;
 };
 
+// Texture and surface objects are per-context pool indices. Destroying one
+// with the wrong context current can silently succeed without freeing it or
+// can free an unrelated object, so destruction must enter the creating
+// context. Handle-based resources resolve their own context and must not.
 struct TexObjectBox {
     // Tagged so TexObjectHandle is a distinct C++ type from DevicePtrHandle /
     // SurfObjectHandle (all wrap `unsigned long long`).
@@ -2059,31 +2857,64 @@ struct TexObjectBox {
     // DevicePtrHandle). The texture's resource is a union; we only need to keep
     // whichever backing it was built from alive, never to dereference it.
     std::shared_ptr<const void> h_backing;
+    ContextHandle h_context;
 };
 
 struct SurfObjectBox {
     SurfObjectValue resource;
     OpaqueArrayHandle h_array;  // surfaces are always array-backed
+    ContextHandle h_context;
 };
+
+// Recover an array's owning box from its aliased resource pointer.
+const ArrayBox* get_box(const OpaqueArrayHandle& h) noexcept {
+    const CUarray* p = h.get();
+    return reinterpret_cast<const ArrayBox*>(
+        reinterpret_cast<const char*>(p) - offsetof(ArrayBox, resource));
+}
+
+// Recover a mipmapped array's owning box from its aliased resource pointer.
+const MipmappedArrayBox* get_box(const MipmappedArrayHandle& h) noexcept {
+    const CUmipmappedArray* p = h.get();
+    return reinterpret_cast<const MipmappedArrayBox*>(
+        reinterpret_cast<const char*>(p)
+        - offsetof(MipmappedArrayBox, resource));
+}
+
+// Wrap an array with shared owning-destruction behavior.
+static OpaqueArrayHandle wrap_array_owned(CUarray arr, ContextHandle h_context) {
+    auto box = std::shared_ptr<const ArrayBox>(
+        new ArrayBox{arr, {}, std::move(h_context)},
+        [](const ArrayBox* b) {
+            GILReleaseGuard gil;
+            pw_cuArrayDestroy(b->resource);
+            delete b;
+        }
+    );
+    return OpaqueArrayHandle(box, &box->resource);
+}
+
 }  // namespace
 
-OpaqueArrayHandle create_array_handle(const CUDA_ARRAY3D_DESCRIPTOR& desc) {
+OpaqueArrayHandle create_array_handle(const ContextHandle& h_context, const CUDA_ARRAY3D_DESCRIPTOR& desc) {
     GILReleaseGuard gil;
-    CUarray arr;
-    if (CUDA_SUCCESS != (err = p_cuArray3DCreate(&arr, &desc))) {
+    CUarray arr = nullptr;
+    err = invoke_in_context_or_undo(
+        h_context,
+        [&]() noexcept { return p_cuArray3DCreate(&arr, &desc); },
+        [&]() noexcept { pw_cuArrayDestroy(arr); },
+        /*undo_requires_target_context=*/false);
+    if (err != CUDA_SUCCESS) {
         return {};
     }
-    // Allocation and adoption share the same owning lifetime; the only
-    // difference is who calls cuArray3DCreate. Delegate so the owning box and
-    // its destroy-on-last-ref deleter are defined in exactly one place.
-    return create_array_handle_owning(arr);
+    return wrap_array_owned(arr, h_context);
 }
 
 OpaqueArrayHandle create_array_handle_ref(CUarray arr) {
     if (!arr) {
         return {};
     }
-    auto box = std::make_shared<const ArrayBox>(ArrayBox{arr, {}});
+    auto box = std::make_shared<const ArrayBox>(ArrayBox{arr, {}, {}});
     return OpaqueArrayHandle(box, &box->resource);
 }
 
@@ -2091,64 +2922,81 @@ OpaqueArrayHandle create_array_handle_owning(CUarray arr) {
     if (!arr) {
         return {};
     }
-    auto box = std::shared_ptr<const ArrayBox>(
-        new ArrayBox{arr, {}},
-        [](const ArrayBox* b) {
-            GILReleaseGuard gil;
-            p_cuArrayDestroy(b->resource);
-            delete b;
-        }
-    );
-    return OpaqueArrayHandle(box, &box->resource);
+    return wrap_array_owned(arr, {});
+}
+
+// Return the context retained by an array handle.
+ContextHandle get_array_context(const OpaqueArrayHandle& h) noexcept {
+    return h ? get_box(h)->h_context : ContextHandle{};
 }
 
 OpaqueArrayHandle create_array_level_handle(const MipmappedArrayHandle& h_mip, unsigned int level) {
     GILReleaseGuard gil;
     CUarray arr;
+    ContextHandle h_context = h_mip ? get_box(h_mip)->h_context : ContextHandle{};
     if (CUDA_SUCCESS != (err = p_cuMipmappedArrayGetLevel(&arr, as_cu(h_mip), level))) {
         return {};
     }
     // Non-owning level view: storage belongs to the mipmap. Embed the mipmap
     // handle so the parent outlives this level; the deleter does not destroy.
     auto box = std::shared_ptr<const ArrayBox>(
-        new ArrayBox{arr, h_mip},
+        new ArrayBox{arr, h_mip, h_context},
         [](const ArrayBox* b) { delete b; }
     );
     return OpaqueArrayHandle(box, &box->resource);
 }
 
-MipmappedArrayHandle create_mipmapped_array_handle(const CUDA_ARRAY3D_DESCRIPTOR& desc,
+MipmappedArrayHandle create_mipmapped_array_handle(const ContextHandle& h_context,
+                                                   const CUDA_ARRAY3D_DESCRIPTOR& desc,
                                                    unsigned int num_levels) {
     GILReleaseGuard gil;
-    CUmipmappedArray mip;
-    if (CUDA_SUCCESS != (err = p_cuMipmappedArrayCreate(&mip, &desc, num_levels))) {
+    CUmipmappedArray mip = nullptr;
+    err = invoke_in_context_or_undo(
+        h_context,
+        [&]() noexcept { return p_cuMipmappedArrayCreate(&mip, &desc, num_levels); },
+        [&]() noexcept { pw_cuMipmappedArrayDestroy(mip); },
+        /*undo_requires_target_context=*/false);
+    if (err != CUDA_SUCCESS) {
         return {};
     }
     auto box = std::shared_ptr<const MipmappedArrayBox>(
-        new MipmappedArrayBox{mip},
+        new MipmappedArrayBox{mip, h_context},
         [](const MipmappedArrayBox* b) {
             GILReleaseGuard gil;
-            p_cuMipmappedArrayDestroy(b->resource);
+            pw_cuMipmappedArrayDestroy(b->resource);
             delete b;
         }
     );
     return MipmappedArrayHandle(box, &box->resource);
 }
 
+// Return the context retained by a mipmapped array handle.
+ContextHandle get_mipmapped_array_context(const MipmappedArrayHandle& h) noexcept {
+    return h ? get_box(h)->h_context : ContextHandle{};
+}
+
 namespace {
 TexObjectHandle make_tex_object_handle(const CUDA_RESOURCE_DESC& res,
                                        const CUDA_TEXTURE_DESC& tex,
-                                       std::shared_ptr<const void> h_backing) {
+                                       std::shared_ptr<const void> h_backing,
+                                       const ContextHandle& h_context) {
     GILReleaseGuard gil;
-    CUtexObject obj;
-    if (CUDA_SUCCESS != (err = p_cuTexObjectCreate(&obj, &res, &tex, nullptr))) {
+    CUtexObject obj = 0;
+    err = invoke_in_context_or_undo(
+        h_context,
+        [&]() noexcept { return p_cuTexObjectCreate(&obj, &res, &tex, nullptr); },
+        [&]() noexcept { pw_cuTexObjectDestroy(obj); },
+        /*undo_requires_target_context=*/true);
+    if (err != CUDA_SUCCESS) {
         return {};
     }
     auto box = std::shared_ptr<const TexObjectBox>(
-        new TexObjectBox{TexObjectValue{obj}, std::move(h_backing)},
+        new TexObjectBox{TexObjectValue{obj}, std::move(h_backing), h_context},
         [](const TexObjectBox* b) {
             GILReleaseGuard gil;
-            p_cuTexObjectDestroy(b->resource.raw);
+            cleanup_in_context(b->h_context, "cuTexObjectDestroy", [&]() noexcept {
+                return p_cuTexObjectDestroy(b->resource.raw);
+            });
             delete b;
         }
     );
@@ -2156,36 +3004,47 @@ TexObjectHandle make_tex_object_handle(const CUDA_RESOURCE_DESC& res,
 }
 }  // namespace
 
-TexObjectHandle create_tex_object_handle_array(const CUDA_RESOURCE_DESC& res,
+TexObjectHandle create_tex_object_handle_array(const ContextHandle& h_context,
+                                               const CUDA_RESOURCE_DESC& res,
                                                const CUDA_TEXTURE_DESC& tex,
                                                const OpaqueArrayHandle& h_backing) {
-    return make_tex_object_handle(res, tex, h_backing);
+    return make_tex_object_handle(res, tex, h_backing, h_context);
 }
 
-TexObjectHandle create_tex_object_handle_mipmap(const CUDA_RESOURCE_DESC& res,
+TexObjectHandle create_tex_object_handle_mipmap(const ContextHandle& h_context,
+                                                const CUDA_RESOURCE_DESC& res,
                                                 const CUDA_TEXTURE_DESC& tex,
                                                 const MipmappedArrayHandle& h_backing) {
-    return make_tex_object_handle(res, tex, h_backing);
+    return make_tex_object_handle(res, tex, h_backing, h_context);
 }
 
-TexObjectHandle create_tex_object_handle_linear(const CUDA_RESOURCE_DESC& res,
+TexObjectHandle create_tex_object_handle_linear(const ContextHandle& h_context,
+                                                const CUDA_RESOURCE_DESC& res,
                                                 const CUDA_TEXTURE_DESC& tex,
                                                 const DevicePtrHandle& h_backing) {
-    return make_tex_object_handle(res, tex, h_backing);
+    return make_tex_object_handle(res, tex, h_backing, h_context);
 }
 
-SurfObjectHandle create_surf_object_handle(const CUDA_RESOURCE_DESC& res,
+SurfObjectHandle create_surf_object_handle(const ContextHandle& h_context,
+                                           const CUDA_RESOURCE_DESC& res,
                                            const OpaqueArrayHandle& h_backing) {
     GILReleaseGuard gil;
-    CUsurfObject obj;
-    if (CUDA_SUCCESS != (err = p_cuSurfObjectCreate(&obj, &res))) {
+    CUsurfObject obj = 0;
+    err = invoke_in_context_or_undo(
+        h_context,
+        [&]() noexcept { return p_cuSurfObjectCreate(&obj, &res); },
+        [&]() noexcept { pw_cuSurfObjectDestroy(obj); },
+        /*undo_requires_target_context=*/true);
+    if (err != CUDA_SUCCESS) {
         return {};
     }
     auto box = std::shared_ptr<const SurfObjectBox>(
-        new SurfObjectBox{SurfObjectValue{obj}, h_backing},
+        new SurfObjectBox{SurfObjectValue{obj}, h_backing, h_context},
         [](const SurfObjectBox* b) {
             GILReleaseGuard gil;
-            p_cuSurfObjectDestroy(b->resource.raw);
+            cleanup_in_context(b->h_context, "cuSurfObjectDestroy", [&]() noexcept {
+                return p_cuSurfObjectDestroy(b->resource.raw);
+            });
             delete b;
         }
     );
@@ -2215,4 +3074,25 @@ bool has_sm_resource_split() noexcept {
     return p_cuDevSmResourceSplit != nullptr;
 }
 
+// ============================================================================
+// cuMemcpyWithAttributesAsync wrapper
+// ============================================================================
+
+CUresult memcpy_with_attributes_async(CUdeviceptr dst, CUdeviceptr src, size_t size,
+                                       void* attr, CUstream hStream) {
+#if CUDA_VERSION >= 13020
+    if (!p_cuMemcpyWithAttributesAsync) {
+        return CUDA_ERROR_NOT_SUPPORTED;
+    }
+    return p_cuMemcpyWithAttributesAsync(
+        dst, src, size, static_cast<CUmemcpyAttributes*>(attr), hStream);
+#else
+    return CUDA_ERROR_NOT_SUPPORTED;
+#endif
+}
+
+bool has_memcpy_with_attributes_async() noexcept {
+    return p_cuMemcpyWithAttributesAsync != nullptr;
+}
+
 }  // namespace cuda_core
diff --git a/cuda_core/cuda/core/_cpp/resource_handles.hpp b/cuda_core/cuda/core/_cpp/resource_handles.hpp
index 3a9d2d75cff..419710ea0d9 100644
--- a/cuda_core/cuda/core/_cpp/resource_handles.hpp
+++ b/cuda_core/cuda/core/_cpp/resource_handles.hpp
@@ -64,9 +64,15 @@ void clear_last_error() noexcept;
 // function pointers extracted from cuda.bindings.cydriver.__pyx_capi__.
 // ============================================================================
 
+extern decltype(&cuGetErrorName) p_cuGetErrorName;
+extern decltype(&cuGetErrorString) p_cuGetErrorString;
+
 extern decltype(&cuDevicePrimaryCtxRetain) p_cuDevicePrimaryCtxRetain;
 extern decltype(&cuDevicePrimaryCtxRelease) p_cuDevicePrimaryCtxRelease;
 extern decltype(&cuCtxGetCurrent) p_cuCtxGetCurrent;
+extern decltype(&cuCtxSetCurrent) p_cuCtxSetCurrent;
+extern decltype(&cuCtxSynchronize) p_cuCtxSynchronize;
+extern decltype(&cuCtxGetStreamPriorityRange) p_cuCtxGetStreamPriorityRange;
 extern decltype(&cuGreenCtxCreate) p_cuGreenCtxCreate;
 extern decltype(&cuGreenCtxDestroy) p_cuGreenCtxDestroy;
 extern decltype(&cuCtxFromGreenCtx) p_cuCtxFromGreenCtx;
@@ -76,6 +82,7 @@ extern decltype(&cuGreenCtxStreamCreate) p_cuGreenCtxStreamCreate;
 
 extern decltype(&cuStreamCreateWithPriority) p_cuStreamCreateWithPriority;
 extern decltype(&cuStreamDestroy) p_cuStreamDestroy;
+extern decltype(&cuStreamGetCtx) p_cuStreamGetCtx;
 
 extern decltype(&cuEventCreate) p_cuEventCreate;
 extern decltype(&cuEventDestroy) p_cuEventDestroy;
@@ -108,6 +115,8 @@ extern decltype(&cuLibraryGetKernel) p_cuLibraryGetKernel;
 
 // Graph
 extern decltype(&cuGraphDestroy) p_cuGraphDestroy;
+extern decltype(&cuGraphInstantiateWithParams) p_cuGraphInstantiateWithParams;
+extern decltype(&cuGraphExecUpdate) p_cuGraphExecUpdate;
 extern decltype(&cuGraphExecDestroy) p_cuGraphExecDestroy;
 extern decltype(&cuUserObjectCreate) p_cuUserObjectCreate;
 extern decltype(&cuUserObjectRelease) p_cuUserObjectRelease;
@@ -143,6 +152,15 @@ extern decltype(&cuDevSmResourceSplit) p_cuDevSmResourceSplit;
 extern void* p_cuDevSmResourceSplit;
 #endif
 
+// cuMemcpyWithAttributesAsync (13.2+ — may be null on older drivers/bindings)
+#if CUDA_VERSION >= 13020
+extern decltype(&cuMemcpyWithAttributesAsync) p_cuMemcpyWithAttributesAsync;
+#else
+// cuMemcpyWithAttributesAsync doesn't exist in CUDA < 13.2 headers, so use a
+// void* placeholder. The pointer is always null when built against older CUDA.
+extern void* p_cuMemcpyWithAttributesAsync;
+#endif
+
 // ============================================================================
 // NVRTC function pointers
 //
@@ -234,6 +252,17 @@ ContextHandle get_primary_context(int device_id);
 // Returns empty handle if no context is current (caller must check)
 ContextHandle get_current_context();
 
+// Synchronize the provided context. Releases the GIL around the driver call.
+// Returns CUDA_ERROR_INVALID_CONTEXT for an empty handle.
+CUresult context_synchronize(const ContextHandle& h_context) noexcept;
+
+// Query the stream priority range for the provided context.
+// Returns CUDA_ERROR_INVALID_CONTEXT for an empty handle.
+CUresult context_get_stream_priority_range(
+    const ContextHandle& h_context,
+    int* least_priority,
+    int* greatest_priority) noexcept;
+
 // ============================================================================
 // Stream handle functions
 // ============================================================================
@@ -275,6 +304,14 @@ StreamHandle get_legacy_stream();
 // Note: Per-thread stream has no specific context dependency.
 StreamHandle get_per_thread_stream();
 
+// Wrap CU_STREAM_LEGACY with an explicit context, bypassing the "bind to
+// whatever is current" resolution that a bare default-stream token uses (see
+// make_deallocation_stream). Lets a resource that always operates in one
+// known context (e.g. a synchronous, non-pooled allocator) record a correct
+// deallocation context without requiring that context to be current when the
+// token is created. Returns an empty handle for an empty h_context.
+StreamHandle create_context_bound_legacy_stream(const ContextHandle& h_context);
+
 // ============================================================================
 // Event handle functions
 // ============================================================================
@@ -288,11 +325,14 @@ EventHandle create_event_handle(const ContextHandle& h_ctx, unsigned int flags,
                                 bool timing_enabled, bool is_blocking_sync,
                                 bool ipc_enabled, int device_id);
 
-// Create an owning event handle without context dependency.
-// Use for temporary events that are created and destroyed in the same scope.
+// Create an owning event in the context that owns `stream`, so it can be
+// recorded on that stream regardless of which context is current. Default-
+// stream tokens resolve to the current context (cuStreamGetCtx semantics).
+// Use for temporary ordering events that are created and destroyed in the
+// same scope; the handle carries no device id.
 // When the last reference is released, cuEventDestroy is called automatically.
 // Returns empty handle on error (caller must check).
-EventHandle create_event_handle_noctx(unsigned int flags);
+EventHandle create_event_handle_for_stream(CUstream stream, unsigned int flags);
 
 // Create an owning event handle from an IPC handle.
 // The originating process owns the event and its context.
@@ -359,10 +399,11 @@ DevicePtrHandle deviceptr_alloc_from_pool(
 // Returns empty handle on error (caller must check).
 DevicePtrHandle deviceptr_alloc_async(size_t size, const StreamHandle& h_stream);
 
-// Allocate device memory synchronously via cuMemAlloc.
-// When the last reference is released, cuMemFree is called.
-// Returns empty handle on error (caller must check).
-DevicePtrHandle deviceptr_alloc(size_t size);
+// Allocate device memory synchronously via cuMemAlloc with the provided
+// context current. The caller owns the pointer and releases it with cuMemFree.
+// Returns CUDA_ERROR_INVALID_CONTEXT for an empty handle.
+CUresult deviceptr_alloc_raw(CUdeviceptr* ptr, size_t size,
+                             const ContextHandle& h_context) noexcept;
 
 // Allocate pinned host memory via cuMemAllocHost.
 // When the last reference is released, cuMemFreeHost is called.
@@ -421,7 +462,10 @@ DevicePtrHandle deviceptr_import_ipc(
 StreamHandle deallocation_stream(const DevicePtrHandle& h) noexcept;
 
 // Set the deallocation stream for a device pointer handle.
-void set_deallocation_stream(const DevicePtrHandle& h, const StreamHandle& h_stream) noexcept;
+// Returns CUDA_ERROR_INVALID_CONTEXT when a default-stream token cannot be
+// bound because no CUDA context is current.
+CUresult set_deallocation_stream(
+    const DevicePtrHandle& h, const StreamHandle& h_stream) noexcept;
 
 // ============================================================================
 // Library handle functions
@@ -516,6 +560,27 @@ struct PreparedAttachmentDeleter {
 using PreparedAttachment =
     std::unique_ptr<PreparedAttachmentState, PreparedAttachmentDeleter>;
 
+struct PreparedChildGraphUpdateState;
+// Opaque unpublished hierarchy transaction; releasing it discards staged
+// metadata unless graph_commit_child_graph_update publishes the replacement.
+using PreparedChildGraphUpdate =
+    std::shared_ptr<PreparedChildGraphUpdateState>;
+
+struct PreparedExecAttachmentState;
+using PreparedExecAttachmentRollback =
+    void (*)(PreparedExecAttachmentState*) noexcept;
+struct PreparedExecAttachmentDeleter {
+    PreparedExecAttachmentRollback rollback = nullptr;
+
+    void operator()(PreparedExecAttachmentState* state) const noexcept {
+        rollback(state);
+    }
+};
+// Opaque append transaction. Releasing it rolls back newly appended owners
+// unless graph_commit_exec_attachment has kept them.
+using PreparedExecAttachment =
+    std::unique_ptr<PreparedExecAttachmentState, PreparedExecAttachmentDeleter>;
+
 // Copy requested owners from node's current attachment. Pass nullptr to ignore
 // either owner; a missing attachment produces empty handles.
 CUresult graph_get_attachment(
@@ -543,6 +608,21 @@ CUresult graph_clone_attachments(
     const GraphHandle& h_clone,
     const GraphHandle& h_source);
 
+// Stage a complete metadata replacement before CUDA replaces an embedded
+// graph. Dropping the prepared state leaves the current hierarchy unchanged.
+CUresult graph_prepare_child_graph_update(
+    const GraphHandle& h_parent,
+    const GraphHandle& h_old_child,
+    CUgraphNode owner_node,
+    const GraphHandle& h_source,
+    PreparedChildGraphUpdate* out_prepared);
+
+// Rekey staged metadata to CUDA's replacement clone, retire the old embedded
+// hierarchy, and publish the replacement handle.
+CUresult graph_commit_child_graph_update(
+    PreparedChildGraphUpdate& prepared,
+    GraphHandle* out_child);
+
 // Invalidate cuda.core state for child graphs CUDA destroyed with owner_node.
 void invalidate_child_graph_state(
     const GraphHandle& h_parent,
@@ -552,9 +632,39 @@ void invalidate_child_graph_state(
 // Graph exec handle functions
 // ============================================================================
 
-// Wrap an externally-created CUgraphExec with RAII cleanup.
-// When the last reference is released, cuGraphExecDestroy is called automatically.
-GraphExecHandle create_graph_exec_handle(CUgraphExec graph_exec);
+// Create an owning exec handle by calling cuGraphInstantiateWithParams.
+// A fresh attachment accumulator is retained on h_source first, because CUDA
+// propagates user object references only at instantiation; an exec cannot
+// receive them afterwards. The exec is the sole owner once this returns.
+// When the last reference is released, cuGraphExecDestroy is called
+// automatically.
+// Returns empty handle on error (caller must check). The caller reads
+// params->result_out for the specific instantiation failure and
+// get_last_error() for a driver status.
+GraphExecHandle create_graph_exec_handle(
+    const GraphHandle& h_source,
+    CUDA_GRAPH_INSTANTIATE_PARAMS* params);
+
+// Update h_exec in place by calling cuGraphExecUpdate, and publish a fresh
+// accumulator when CUDA accepts the update. Writes result_info for the caller.
+CUresult graph_exec_update(
+    const GraphExecHandle& h_exec,
+    const GraphHandle& h_source,
+    CUgraphExecUpdateResultInfo* result_info);
+
+// Append owners before an executable-node mutation. The accumulator grows
+// because CUDA cannot attach user objects to an exec after instantiation, so
+// old owners stay reachable. Dropping the transaction restores the accumulator
+// to its original size.
+CUresult graph_prepare_exec_attachment(
+    const GraphExecHandle& h_exec,
+    OpaqueHandle owner0,
+    OpaqueHandle owner1,
+    PreparedExecAttachment* out_prepared);
+
+// Keep the owners added by graph_prepare_exec_attachment.
+void graph_commit_exec_attachment(
+    PreparedExecAttachment& prepared) noexcept;
 
 // ============================================================================
 // Graph node handle functions
@@ -658,7 +768,7 @@ FileDescriptorHandle create_fd_handle_ref(int fd);
 // Create an owning CUDA array via cuArray3DCreate.
 // When the last reference is released, cuArrayDestroy is called automatically.
 // Returns empty handle on error (caller must check).
-OpaqueArrayHandle create_array_handle(const CUDA_ARRAY3D_DESCRIPTOR& desc);
+OpaqueArrayHandle create_array_handle(const ContextHandle& h_context, const CUDA_ARRAY3D_DESCRIPTOR& desc);
 
 // Create a non-owning array handle (references an existing CUarray).
 // Use for arrays owned elsewhere (e.g. graphics interop). Never destroyed here.
@@ -668,6 +778,9 @@ OpaqueArrayHandle create_array_handle_ref(CUarray arr);
 // When the last reference is released, cuArrayDestroy is called automatically.
 OpaqueArrayHandle create_array_handle_owning(CUarray arr);
 
+// Return the context dependency associated with an array, if known.
+ContextHandle get_array_context(const OpaqueArrayHandle& h) noexcept;
+
 // Create a non-owning handle to a mipmap level via cuMipmappedArrayGetLevel.
 // The level CUarray is owned by the mipmap; the parent MipmappedArrayHandle is
 // embedded in the box so it outlives the level view. No destroy in the deleter.
@@ -677,27 +790,35 @@ OpaqueArrayHandle create_array_level_handle(const MipmappedArrayHandle& h_mip, u
 // Create an owning mipmapped array via cuMipmappedArrayCreate.
 // When the last reference is released, cuMipmappedArrayDestroy is called.
 // Returns empty handle on error (caller must check).
-MipmappedArrayHandle create_mipmapped_array_handle(const CUDA_ARRAY3D_DESCRIPTOR& desc,
+MipmappedArrayHandle create_mipmapped_array_handle(const ContextHandle& h_context,
+                                                   const CUDA_ARRAY3D_DESCRIPTOR& desc,
                                                    unsigned int num_levels);
 
+// Return the context dependency associated with a mipmapped array, if known.
+ContextHandle get_mipmapped_array_context(const MipmappedArrayHandle& h) noexcept;
+
 // Create an owning texture object via cuTexObjectCreate, embedding the backing
 // resource handle (array / mipmapped array / linear-or-pitch2d device pointer)
 // so the backing always outlives the texture. cuTexObjectDestroy runs in the
 // deleter. Returns empty handle on error (caller must check).
-TexObjectHandle create_tex_object_handle_array(const CUDA_RESOURCE_DESC& res,
+TexObjectHandle create_tex_object_handle_array(const ContextHandle& h_context,
+                                               const CUDA_RESOURCE_DESC& res,
                                                const CUDA_TEXTURE_DESC& tex,
                                                const OpaqueArrayHandle& h_backing);
-TexObjectHandle create_tex_object_handle_mipmap(const CUDA_RESOURCE_DESC& res,
+TexObjectHandle create_tex_object_handle_mipmap(const ContextHandle& h_context,
+                                                const CUDA_RESOURCE_DESC& res,
                                                 const CUDA_TEXTURE_DESC& tex,
                                                 const MipmappedArrayHandle& h_backing);
-TexObjectHandle create_tex_object_handle_linear(const CUDA_RESOURCE_DESC& res,
+TexObjectHandle create_tex_object_handle_linear(const ContextHandle& h_context,
+                                                const CUDA_RESOURCE_DESC& res,
                                                 const CUDA_TEXTURE_DESC& tex,
                                                 const DevicePtrHandle& h_backing);
 
 // Create an owning surface object via cuSurfObjectCreate, embedding the backing
 // array handle so it outlives the surface. cuSurfObjectDestroy runs in the
 // deleter. Returns empty handle on error (caller must check).
-SurfObjectHandle create_surf_object_handle(const CUDA_RESOURCE_DESC& res,
+SurfObjectHandle create_surf_object_handle(const ContextHandle& h_context,
+                                           const CUDA_RESOURCE_DESC& res,
                                            const OpaqueArrayHandle& h_backing);
 
 // ============================================================================
@@ -733,6 +854,10 @@ inline CUlibrary as_cu(const LibraryHandle& h) noexcept {
     return h ? *h : nullptr;
 }
 
+inline CUmodule as_cu(const CUmodule& h) noexcept {
+    return h;
+}
+
 inline CUkernel as_cu(const KernelHandle& h) noexcept {
     return h ? *h : nullptr;
 }
@@ -817,6 +942,10 @@ inline std::intptr_t as_intptr(const LibraryHandle& h) noexcept {
     return reinterpret_cast<std::intptr_t>(as_cu(h));
 }
 
+inline std::intptr_t as_intptr(const CUmodule& h) noexcept {
+    return reinterpret_cast<std::intptr_t>(as_cu(h));
+}
+
 inline std::intptr_t as_intptr(const KernelHandle& h) noexcept {
     return reinterpret_cast<std::intptr_t>(as_cu(h));
 }
@@ -947,6 +1076,10 @@ inline PyObject* as_py(const LibraryHandle& h) noexcept {
     return detail::make_py("cuda.bindings.driver", "CUlibrary", as_intptr(h));
 }
 
+inline PyObject* as_py(const CUmodule& h) noexcept {
+    return detail::make_py("cuda.bindings.driver", "CUmodule", as_intptr(h));
+}
+
 inline PyObject* as_py(const KernelHandle& h) noexcept {
     return detail::make_py("cuda.bindings.driver", "CUkernel", as_intptr(h));
 }
@@ -1026,4 +1159,21 @@ CUresult sm_resource_split(CUdevResource* result, unsigned int nbGroups,
 // Returns true if the cuDevSmResourceSplit function pointer is available.
 bool has_sm_resource_split() noexcept;
 
+// ============================================================================
+// cuMemcpyWithAttributesAsync wrapper (13.2+)
+//
+// Calls through p_cuMemcpyWithAttributesAsync if available, otherwise returns
+// CUDA_ERROR_NOT_SUPPORTED. This avoids a direct Cython cimport of the
+// cydriver cdef function, which would fail at module init on cuda-bindings
+// < 13.2 (see https://github.com/NVIDIA/cuda-python/issues/2063).
+// ============================================================================
+
+// attr is void* so the Cython declaration doesn't reference CUmemcpyAttributes
+// (absent from cuda-bindings built against CUDA < 12.8). The C++ side casts it.
+CUresult memcpy_with_attributes_async(CUdeviceptr dst, CUdeviceptr src, size_t size,
+                                       void* attr, CUstream hStream);
+
+// Returns true if the cuMemcpyWithAttributesAsync function pointer is available.
+bool has_memcpy_with_attributes_async() noexcept;
+
 }  // namespace cuda_core
diff --git a/cuda_core/cuda/core/_device.pyi b/cuda_core/cuda/core/_device.pyi
index a086f0d2523..8c2b273a6cd 100644
--- a/cuda_core/cuda/core/_device.pyi
+++ b/cuda_core/cuda/core/_device.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_device.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_device.pyx
 
 import threading
 
@@ -9,7 +7,7 @@ from cuda.core._context import Context, ContextOptions
 from cuda.core._device_resources import DeviceResources
 from cuda.core._event import Event, EventOptions
 from cuda.core._memory._buffer import Buffer, MemoryResource
-from cuda.core._stream import IsStreamType, Stream
+from cuda.core._stream import IsStreamType, Stream, StreamOptions
 from cuda.core._utils.cuda_utils import ComputeCapability
 from cuda.core.graph import GraphBuilder
 from cuda.core.texture import (MipmappedArray, MipmappedArrayOptions,
@@ -17,6 +15,9 @@ from cuda.core.texture import (MipmappedArray, MipmappedArrayOptions,
                                ResourceDescriptor, SurfaceObject,
                                TextureObject, TextureObjectOptions)
 
+_tls = threading.local()
+_lock = threading.Lock()
+__all__ = ['Device']
 
 class DeviceProperties:
     """
@@ -24,588 +25,441 @@ class DeviceProperties:
 
     Attributes are read-only and provide information about the device.
     """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @classmethod
-    def _init(cls, handle: int) -> DeviceProperties:
-        ...
-
+    def _init(cls, handle: int) -> DeviceProperties: ...
     @property
     def max_threads_per_block(self) -> int:
         """int: Maximum number of threads per block."""
-
     @property
     def max_block_dim_x(self) -> int:
         """int: Maximum block dimension X."""
-
     @property
     def max_block_dim_y(self) -> int:
         """int: Maximum block dimension Y."""
-
     @property
     def max_block_dim_z(self) -> int:
         """int: Maximum block dimension Z."""
-
     @property
     def max_grid_dim_x(self) -> int:
         """int: Maximum grid dimension X."""
-
     @property
     def max_grid_dim_y(self) -> int:
         """int: Maximum grid dimension Y."""
-
     @property
     def max_grid_dim_z(self) -> int:
         """int: Maximum grid dimension Z."""
-
     @property
     def max_shared_memory_per_block(self) -> int:
         """int: Maximum shared memory available per block in bytes."""
-
     @property
     def total_constant_memory(self) -> int:
         """int: Memory available on device for constant variables in a CUDA C kernel in bytes."""
-
     @property
     def warp_size(self) -> int:
         """int: Warp size in threads."""
-
     @property
     def max_pitch(self) -> int:
         """int: Maximum pitch in bytes allowed by memory copies."""
-
     @property
     def maximum_texture1d_width(self) -> int:
         """int: Maximum 1D texture width."""
-
     @property
     def maximum_texture1d_linear_width(self) -> int:
         """int: Maximum width for a 1D texture bound to linear memory."""
-
     @property
     def maximum_texture1d_mipmapped_width(self) -> int:
         """int: Maximum mipmapped 1D texture width."""
-
     @property
     def maximum_texture2d_width(self) -> int:
         """int: Maximum 2D texture width."""
-
     @property
     def maximum_texture2d_height(self) -> int:
         """int: Maximum 2D texture height."""
-
     @property
     def maximum_texture2d_linear_width(self) -> int:
         """int: Maximum width for a 2D texture bound to linear memory."""
-
     @property
     def maximum_texture2d_linear_height(self) -> int:
         """int: Maximum height for a 2D texture bound to linear memory."""
-
     @property
     def maximum_texture2d_linear_pitch(self) -> int:
         """int: Maximum pitch in bytes for a 2D texture bound to linear memory."""
-
     @property
     def maximum_texture2d_mipmapped_width(self) -> int:
         """int: Maximum mipmapped 2D texture width."""
-
     @property
     def maximum_texture2d_mipmapped_height(self) -> int:
         """int: Maximum mipmapped 2D texture height."""
-
     @property
     def maximum_texture3d_width(self) -> int:
         """int: Maximum 3D texture width."""
-
     @property
     def maximum_texture3d_height(self) -> int:
         """int: Maximum 3D texture height."""
-
     @property
     def maximum_texture3d_depth(self) -> int:
         """int: Maximum 3D texture depth."""
-
     @property
     def maximum_texture3d_width_alternate(self) -> int:
         """int: Alternate maximum 3D texture width, 0 if no alternate maximum 3D texture size is supported."""
-
     @property
     def maximum_texture3d_height_alternate(self) -> int:
         """int: Alternate maximum 3D texture height, 0 if no alternate maximum 3D texture size is supported."""
-
     @property
     def maximum_texture3d_depth_alternate(self) -> int:
         """int: Alternate maximum 3D texture depth, 0 if no alternate maximum 3D texture size is supported."""
-
     @property
     def maximum_texturecubemap_width(self) -> int:
         """int: Maximum cubemap texture width or height."""
-
     @property
     def maximum_texture1d_layered_width(self) -> int:
         """int: Maximum 1D layered texture width."""
-
     @property
     def maximum_texture1d_layered_layers(self) -> int:
         """int: Maximum layers in a 1D layered texture."""
-
     @property
     def maximum_texture2d_layered_width(self) -> int:
         """int: Maximum 2D layered texture width."""
-
     @property
     def maximum_texture2d_layered_height(self) -> int:
         """int: Maximum 2D layered texture height."""
-
     @property
     def maximum_texture2d_layered_layers(self) -> int:
         """int: Maximum layers in a 2D layered texture."""
-
     @property
     def maximum_texturecubemap_layered_width(self) -> int:
         """int: Maximum cubemap layered texture width or height."""
-
     @property
     def maximum_texturecubemap_layered_layers(self) -> int:
         """int: Maximum layers in a cubemap layered texture."""
-
     @property
     def maximum_surface1d_width(self) -> int:
         """int: Maximum 1D surface width."""
-
     @property
     def maximum_surface2d_width(self) -> int:
         """int: Maximum 2D surface width."""
-
     @property
     def maximum_surface2d_height(self) -> int:
         """int: Maximum 2D surface height."""
-
     @property
     def maximum_surface3d_width(self) -> int:
         """int: Maximum 3D surface width."""
-
     @property
     def maximum_surface3d_height(self) -> int:
         """int: Maximum 3D surface height."""
-
     @property
     def maximum_surface3d_depth(self) -> int:
         """int: Maximum 3D surface depth."""
-
     @property
     def maximum_surface1d_layered_width(self) -> int:
         """int: Maximum 1D layered surface width."""
-
     @property
     def maximum_surface1d_layered_layers(self) -> int:
         """int: Maximum layers in a 1D layered surface."""
-
     @property
     def maximum_surface2d_layered_width(self) -> int:
         """int: Maximum 2D layered surface width."""
-
     @property
     def maximum_surface2d_layered_height(self) -> int:
         """int: Maximum 2D layered surface height."""
-
     @property
     def maximum_surface2d_layered_layers(self) -> int:
         """int: Maximum layers in a 2D layered surface."""
-
     @property
     def maximum_surfacecubemap_width(self) -> int:
         """int: Maximum cubemap surface width."""
-
     @property
     def maximum_surfacecubemap_layered_width(self) -> int:
         """int: Maximum cubemap layered surface width."""
-
     @property
     def maximum_surfacecubemap_layered_layers(self) -> int:
         """int: Maximum layers in a cubemap layered surface."""
-
     @property
     def max_registers_per_block(self) -> int:
         """int: Maximum number of 32-bit registers available to a thread block."""
-
     @property
     def clock_rate(self) -> int:
         """int: Typical clock frequency in kilohertz."""
-
     @property
     def texture_alignment(self) -> int:
         """int: Alignment requirement for textures."""
-
     @property
     def texture_pitch_alignment(self) -> int:
         """int: Pitch alignment requirement for textures."""
-
     @property
     def gpu_overlap(self) -> bool:
         """bool: Device can possibly copy memory and execute a kernel concurrently. Deprecated. Use :attr:`~DeviceProperties.async_engine_count` instead."""
-
     @property
     def multiprocessor_count(self) -> int:
         """int: Number of multiprocessors on device."""
-
     @property
     def kernel_exec_timeout(self) -> bool:
         """bool: Specifies whether there is a run time limit on kernels."""
-
     @property
     def integrated(self) -> bool:
         """bool: Device is integrated with host memory."""
-
     @property
     def can_map_host_memory(self) -> bool:
         """bool: Device can map host memory into CUDA address space."""
-
     @property
     def compute_mode(self) -> int:
         """int: Compute mode (See CUcomputemode for details)."""
-
     @property
     def concurrent_kernels(self) -> bool:
         """bool: Device can possibly execute multiple kernels concurrently."""
-
     @property
     def ecc_enabled(self) -> bool:
         """bool: Device has ECC support enabled."""
-
     @property
     def pci_bus_id(self) -> int:
         """int: PCI bus ID of the device."""
-
     @property
     def pci_device_id(self) -> int:
         """int: PCI device ID of the device."""
-
     @property
     def pci_domain_id(self) -> int:
         """int: PCI domain ID of the device."""
-
     @property
     def tcc_driver(self) -> bool:
         """bool: Device is using TCC driver model."""
-
     @property
     def memory_clock_rate(self) -> int:
         """int: Peak memory clock frequency in kilohertz."""
-
     @property
     def global_memory_bus_width(self) -> int:
         """int: Global memory bus width in bits."""
-
     @property
     def l2_cache_size(self) -> int:
         """int: Size of L2 cache in bytes."""
-
     @property
     def max_threads_per_multiprocessor(self) -> int:
         """int: Maximum resident threads per multiprocessor."""
-
     @property
     def unified_addressing(self) -> bool:
         """bool: Device shares a unified address space with the host."""
-
     @property
     def compute_capability_major(self) -> int:
         """int: Major compute capability version number."""
-
     @property
     def compute_capability_minor(self) -> int:
         """int: Minor compute capability version number."""
-
     @property
     def global_l1_cache_supported(self) -> bool:
         """bool: Device supports caching globals in L1."""
-
     @property
     def local_l1_cache_supported(self) -> bool:
         """bool: Device supports caching locals in L1."""
-
     @property
     def max_shared_memory_per_multiprocessor(self) -> int:
         """int: Maximum shared memory available per multiprocessor in bytes."""
-
     @property
     def max_registers_per_multiprocessor(self) -> int:
         """int: Maximum number of 32-bit registers available per multiprocessor."""
-
     @property
     def managed_memory(self) -> bool:
         """bool: Device can allocate managed memory on this system."""
-
     @property
     def multi_gpu_board(self) -> bool:
         """bool: Device is on a multi-GPU board."""
-
     @property
     def multi_gpu_board_group_id(self) -> int:
         """int: Unique id for a group of devices on the same multi-GPU board."""
-
     @property
     def host_native_atomic_supported(self) -> bool:
         """bool: Link between the device and the host supports all native atomic operations."""
-
     @property
     def single_to_double_precision_perf_ratio(self) -> int:
         """int: Ratio of single precision performance (in floating-point operations per second) to double precision performance."""
-
     @property
     def pageable_memory_access(self) -> bool:
         """bool: Device supports coherently accessing pageable memory without calling cudaHostRegister on it."""
-
     @property
     def concurrent_managed_access(self) -> bool:
         """bool: Device can coherently access managed memory concurrently with the CPU."""
-
     @property
     def compute_preemption_supported(self) -> bool:
         """bool: Device supports compute preemption."""
-
     @property
     def can_use_host_pointer_for_registered_mem(self) -> bool:
         """bool: Device can access host registered memory at the same virtual address as the CPU."""
-
     @property
     def cooperative_launch(self) -> bool:
         """bool: Device supports launching cooperative kernels via cuLaunchCooperativeKernel."""
-
     @property
     def max_shared_memory_per_block_optin(self) -> int:
         """int: Maximum optin shared memory per block."""
-
     @property
     def pageable_memory_access_uses_host_page_tables(self) -> bool:
         """bool: Device accesses pageable memory via the host's page tables."""
-
     @property
     def direct_managed_mem_access_from_host(self) -> bool:
         """bool: The host can directly access managed memory on the device without migration."""
-
     @property
     def virtual_memory_management_supported(self) -> bool:
         """bool: Device supports virtual memory management APIs like cuMemAddressReserve, cuMemCreate, cuMemMap and related APIs."""
-
     @property
     def handle_type_posix_file_descriptor_supported(self) -> bool:
         """bool: Device supports exporting memory to a posix file descriptor with cuMemExportToShareableHandle, if requested via cuMemCreate."""
-
     @property
     def handle_type_win32_handle_supported(self) -> bool:
         """bool: Device supports exporting memory to a Win32 NT handle with cuMemExportToShareableHandle, if requested via cuMemCreate."""
-
     @property
     def handle_type_win32_kmt_handle_supported(self) -> bool:
         """bool: Device supports exporting memory to a Win32 KMT handle with cuMemExportToShareableHandle, if requested via cuMemCreate."""
-
     @property
     def max_blocks_per_multiprocessor(self) -> int:
         """int: Maximum number of blocks per multiprocessor."""
-
     @property
     def generic_compression_supported(self) -> bool:
         """bool: Device supports compression of memory."""
-
     @property
     def max_persisting_l2_cache_size(self) -> int:
         """int: Maximum L2 persisting lines capacity setting in bytes."""
-
     @property
     def max_access_policy_window_size(self) -> int:
         """int: Maximum value of CUaccessPolicyWindow.num_bytes."""
-
     @property
     def gpu_direct_rdma_with_cuda_vmm_supported(self) -> bool:
         """bool: Device supports specifying the GPUDirect RDMA flag with cuMemCreate."""
-
     @property
     def reserved_shared_memory_per_block(self) -> int:
         """int: Shared memory reserved by CUDA driver per block in bytes."""
-
     @property
     def sparse_cuda_array_supported(self) -> bool:
         """bool: Device supports sparse CUDA arrays and sparse CUDA mipmapped arrays."""
-
     @property
     def read_only_host_register_supported(self) -> bool:
         """bool: True if device supports using the cuMemHostRegister flag CU_MEMHOSTREGISTER_READ_ONLY to register memory that must be mapped as read-only to the GPU, False if not."""
-
     @property
     def memory_pools_supported(self) -> bool:
         """bool: Device supports using the cuMemAllocAsync and cuMemPool family of APIs."""
-
     @property
     def gpu_direct_rdma_supported(self) -> bool:
         """bool: Device supports GPUDirect RDMA APIs, like nvidia_p2p_get_pages (see https://docs.nvidia.com/cuda/gpudirect-rdma for more information)."""
-
     @property
     def gpu_direct_rdma_flush_writes_options(self) -> int:
         """int: The returned attribute shall be interpreted as a bitmask, where the individual bits are described by the CUflushGPUDirectRDMAWritesOptions enum."""
-
     @property
     def gpu_direct_rdma_writes_ordering(self) -> int:
         """int: GPUDirect RDMA writes to the device do not need to be flushed for consumers within the scope indicated by the returned attribute. See CUGPUDirectRDMAWritesOrdering for the numerical values returned here."""
-
     @property
     def mempool_supported_handle_types(self) -> int:
         """int: Handle types supported with mempool based IPC."""
-
     @property
     def deferred_mapping_cuda_array_supported(self) -> bool:
         """bool: Device supports deferred mapping CUDA arrays and CUDA mipmapped arrays."""
-
     @property
     def numa_config(self) -> int:
         """int: NUMA configuration of a device: value is of type CUdeviceNumaConfig enum."""
-
     @property
     def numa_id(self) -> int:
         """int: NUMA node ID of the GPU memory."""
-
     @property
     def multicast_supported(self) -> bool:
         """bool: Device supports switch multicast and reduction operations."""
-
     @property
     def surface_alignment(self) -> int:
         """int: Surface alignment requirement in bytes."""
-
     @property
     def async_engine_count(self) -> int:
         """int: Number of asynchronous engines."""
-
     @property
     def can_tex2d_gather(self) -> bool:
         """bool: True if device supports 2D texture gather operations, False if not."""
-
     @property
     def maximum_texture2d_gather_width(self) -> int:
         """int: Maximum 2D texture gather width."""
-
     @property
     def maximum_texture2d_gather_height(self) -> int:
         """int: Maximum 2D texture gather height."""
-
     @property
     def stream_priorities_supported(self) -> bool:
         """bool: True if device supports stream priorities, False if not."""
-
     @property
     def can_flush_remote_writes(self) -> bool:
         """bool: The CU_STREAM_WAIT_VALUE_FLUSH flag and the CU_STREAM_MEM_OP_FLUSH_REMOTE_WRITES MemOp are supported on the device. See Stream Memory Operations for additional details."""
-
     @property
     def host_register_supported(self) -> bool:
         """bool: Device supports host memory registration via cudaHostRegister."""
-
     @property
     def timeline_semaphore_interop_supported(self) -> bool:
         """bool: External timeline semaphore interop is supported on the device."""
-
     @property
     def cluster_launch(self) -> bool:
         """bool: Indicates device supports cluster launch."""
-
     @property
     def can_use_64_bit_stream_mem_ops(self) -> bool:
         """bool: 64-bit operations are supported in cuStreamBatchMemOp and related MemOp APIs."""
-
     @property
     def can_use_stream_wait_value_nor(self) -> bool:
         """bool: CU_STREAM_WAIT_VALUE_NOR is supported by MemOp APIs."""
-
     @property
     def dma_buf_supported(self) -> bool:
         """bool: Device supports buffer sharing with dma_buf mechanism."""
-
     @property
     def ipc_event_supported(self) -> bool:
         """bool: Device supports IPC Events."""
-
     @property
     def mem_sync_domain_count(self) -> int:
         """int: Number of memory domains the device supports."""
-
     @property
     def tensor_map_access_supported(self) -> bool:
         """bool: Device supports accessing memory using Tensor Map."""
-
     @property
     def handle_type_fabric_supported(self) -> bool:
         """bool: Device supports exporting memory to a fabric handle with cuMemExportToShareableHandle() or requested with cuMemCreate()."""
-
     @property
     def unified_function_pointers(self) -> bool:
         """bool: Device supports unified function pointers."""
-
     @property
     def mps_enabled(self) -> bool:
         """bool: Indicates if contexts created on this device will be shared via MPS."""
-
     @property
     def host_numa_id(self) -> int:
         """int: NUMA ID of the host node closest to the device. Returns -1 when system does not support NUMA."""
-
     @property
     def d3d12_cig_supported(self) -> bool:
         """bool: Device supports CIG with D3D12."""
-
     @property
     def mem_decompress_algorithm_mask(self) -> int:
         """int: The returned value shall be interpreted as a bitmask, where the individual bits are described by the CUmemDecompressAlgorithm enum."""
-
     @property
     def mem_decompress_maximum_length(self) -> int:
         """int: The returned value is the maximum length in bytes of a single decompress operation that is allowed."""
-
     @property
     def vulkan_cig_supported(self) -> bool:
         """bool: Device supports CIG with Vulkan."""
-
     @property
     def gpu_pci_device_id(self) -> int:
         """int: The combined 16-bit PCI device ID and 16-bit PCI vendor ID.
 
         Returns 0 if the driver does not support this query.
         """
-
     @property
     def gpu_pci_subsystem_id(self) -> int:
         """int: The combined 16-bit PCI subsystem ID and 16-bit PCI subsystem vendor ID.
 
         Returns 0 if the driver does not support this query.
         """
-
     @property
     def host_numa_virtual_memory_management_supported(self) -> bool:
         """bool: Device supports HOST_NUMA location with the virtual memory management APIs like cuMemCreate, cuMemMap and related APIs."""
-
     @property
     def host_numa_memory_pools_supported(self) -> bool:
         """bool: Device supports HOST_NUMA location with the cuMemAllocAsync and cuMemPool family of APIs."""
-
     @property
     def host_numa_multinode_ipc_supported(self) -> bool:
         """bool: Device supports HOST_NUMA location IPC between nodes in a multi-node system."""
-
     @property
     def host_memory_pools_supported(self) -> bool:
         """bool: Device supports HOST location with the cuMemAllocAsync and cuMemPool family of APIs."""
-
     @property
     def host_virtual_memory_management_supported(self) -> bool:
         """bool: Device supports HOST location with the virtual memory management APIs like cuMemCreate, cuMemMap and related APIs."""
-
     @property
     def host_alloc_dma_buf_supported(self) -> bool:
         """bool: Device supports page-locked host memory buffer sharing with dma_buf mechanism."""
-
     @property
     def only_partial_host_native_atomic_supported(self) -> bool:
         """bool: Link between the device and the host supports only some native atomic operations."""
@@ -638,12 +492,8 @@ class Device:
     """
     __slots__ = ('_device_id', '_memory_resource', '_has_inited', '_properties', '_resources', '_uuid', '_context', '__weakref__')
 
-    def __new__(cls, device_id: Device | int | None=None) -> Device:
-        ...
-
-    def _check_context_initialized(self) -> None:
-        ...
-
+    def __new__(cls, device_id: Device | int | None=None) -> Device: ...
+    def _check_context_initialized(self) -> None: ...
     @classmethod
     def get_all_devices(cls) -> tuple[Device, ...]:
         """
@@ -654,12 +504,9 @@ class Device:
         tuple of Device
             A tuple containing instances of available devices.
         """
-
     @classmethod
-    def _get_all_devices_from_cuda_driver(cls):
-        ...
-
-    def to_system_device(self) -> 'cuda.core.system.Device':
+    def _get_all_devices_from_cuda_driver(cls): ...
+    def to_system_device(self) -> cuda.core.system.Device:
         """
         Get the corresponding :class:`cuda.core.system.Device` (which is used
         for NVIDIA Management Library (NVML) access) for this
@@ -672,15 +519,12 @@ class Device:
         cuda.core.system.Device
             The corresponding system-level device instance used for NVML access.
         """
-
     @property
     def device_id(self) -> int:
         """Return device ordinal."""
-
     @property
     def pci_bus_id(self) -> str:
         """Return a PCI Bus Id string for this device."""
-
     def can_access_peer(self, peer: Device | int) -> bool:
         """Check if this device can access memory from the specified peer device.
 
@@ -692,7 +536,6 @@ class Device:
         peer : Device | int
             The peer device to check accessibility to. Can be a :obj:`~_device.Device` object or device ID.
         """
-
     @property
     def uuid(self) -> str:
         """Return a UUID for the device.
@@ -709,27 +552,21 @@ class Device:
         The UUID is cached after first access to avoid repeated CUDA API calls.
 
         """
-
     @property
     def name(self) -> str:
         """Return the device name."""
-
     @property
     def properties(self) -> DeviceProperties:
         """Return a :obj:`~_device.DeviceProperties` class with information about the device."""
-
     @property
     def resources(self) -> DeviceResources:
         """Return the hardware resource query namespace for this device."""
-
     @property
     def compute_capability(self) -> ComputeCapability:
         """Return a named tuple with 2 fields: major and minor."""
-
     @property
     def arch(self) -> str:
         """Return compute capability as a string (e.g., '75' for CC 7.5)."""
-
     @property
     def context(self) -> Context:
         """Return the :obj:`~_context.Context` associated with this device.
@@ -739,18 +576,14 @@ class Device:
         Device must be initialized.
 
         """
-
     @property
     def memory_resource(self) -> MemoryResource:
         """Return :obj:`~_memory.MemoryResource` associated with this device."""
-
     @memory_resource.setter
-    def memory_resource(self, mr: MemoryResource) -> None:
-        ...
-
+    def memory_resource(self, mr: MemoryResource) -> None: ...
     @property
     def default_stream(self) -> Stream:
-        """Return default CUDA :obj:`~_stream.Stream` associated with this device.
+        """Return a default CUDA :obj:`~_stream.Stream` token.
 
         The type of default stream returned depends on if the environment
         variable CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM is set.
@@ -758,23 +591,16 @@ class Device:
         If set, returns a per-thread default stream. Otherwise returns
         the legacy stream.
 
-        """
+        A default-stream token uses the device that is current when the token
+        is used.
 
+        """
     def __int__(self) -> int:
         """Return device_id."""
-
-    def __repr__(self) -> str:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __reduce__(self) -> tuple[object, ...]:
-        ...
-
+    def __repr__(self) -> str: ...
+    def __hash__(self) -> int: ...
+    def __eq__(self, other: object) -> bool: ...
+    def __reduce__(self) -> tuple[object, ...]: ...
     def set_current(self, ctx: Context | None=None) -> Context | None:
         """Set device to be used for GPU executions.
 
@@ -784,6 +610,12 @@ class Device:
 
         Providing a `ctx` causes the previous set context to be popped and returned.
 
+        If `ctx` was created on a different device than this receiver, the call
+        is delegated to that device's own :meth:`set_current`. This keeps the
+        owning device's bookkeeping consistent and lets a context this method
+        handed out for a foreign device be pushed back through any ``Device``
+        object, matching the CUDA context stack's own thread-wide semantics.
+
         Parameters
         ----------
         ctx : :obj:`~_context.Context`, optional
@@ -792,7 +624,9 @@ class Device:
         Returns
         -------
         :obj:`~_context.Context`, optional
-            Popped context.
+            The previous context, or ``None`` if no context was current. When
+            returned, its ``device_id`` identifies the device that was
+            previously current.
 
         Examples
         --------
@@ -805,7 +639,6 @@ class Device:
         >>> # ... do work on device 0 ...
 
         """
-
     def create_context(self, options: ContextOptions | None=None) -> Context:
         """Create a new :obj:`~_context.Context` object.
 
@@ -824,9 +657,8 @@ class Device:
             Newly created context object.
 
         """
-
-    def create_stream(self, obj: IsStreamType | None=None, options: object=None) -> Stream:
-        """Create a :obj:`~_stream.Stream` object.
+    def create_stream(self, obj: IsStreamType | None=None, options: StreamOptions | None=None) -> Stream:
+        """Create or wrap a :obj:`~_stream.Stream` object.
 
         New stream objects can be created in two different ways:
 
@@ -838,7 +670,7 @@ class Device:
 
         Note
         ----
-        Device must be initialized.
+        Device must be initialized. New streams are created on this device.
 
         Parameters
         ----------
@@ -853,9 +685,8 @@ class Device:
             Newly created stream object.
 
         """
-
     def create_event(self, options: EventOptions | None=None) -> Event:
-        """Create an :obj:`~_event.Event` object without recording it to a :obj:`~_stream.Stream`.
+        """Create an :obj:`~_event.Event` on this device without recording it to a :obj:`~_stream.Stream`.
 
         Note
         ----
@@ -872,7 +703,6 @@ class Device:
             Newly created event object.
 
         """
-
     def allocate(self, size: int, *, stream: Stream | GraphBuilder) -> Buffer:
         """Allocate device memory from a specified stream.
 
@@ -898,18 +728,21 @@ class Device:
             Newly created buffer object.
 
         """
-
     def sync(self) -> None:
-        """Synchronize the device.
+        """Synchronize this device's bound context.
+
+        Waits for all preceding work in this device's bound :obj:`~_context.Context`
+        to complete. Only that context is synchronized, not the device as a
+        whole; work queued in a different context on the same device (e.g. a
+        green context) is unaffected.
 
         Note
         ----
         Device must be initialized.
 
         """
-
     def create_graph_builder(self) -> GraphBuilder:
-        """Create a new :obj:`~graph.GraphBuilder` object.
+        """Create a new :obj:`~graph.GraphBuilder` on this device.
 
         Returns
         -------
@@ -917,14 +750,11 @@ class Device:
             Newly created graph builder object.
 
         """
-
     def create_opaque_array(self, options: OpaqueArrayOptions) -> OpaqueArray:
-        """Create an :obj:`~cuda.core.texture.OpaqueArray` on the current device.
+        """Create an :obj:`~cuda.core.texture.OpaqueArray` on this device.
 
         Allocates an opaque, hardware-laid-out CUDA array for texture/surface
-        access. The array is created in the current CUDA context, so make this
-        device current with :meth:`set_current` before calling (mirroring
-        :meth:`create_stream` / :meth:`create_event`).
+        access.
 
         Note
         ----
@@ -942,14 +772,11 @@ class Device:
 
         .. versionadded:: 1.1.0
         """
-
     def create_mipmapped_array(self, options: MipmappedArrayOptions) -> MipmappedArray:
-        """Create a :obj:`~cuda.core.texture.MipmappedArray` on the current device.
+        """Create a :obj:`~cuda.core.texture.MipmappedArray` on this device.
 
         Allocates a mipmapped CUDA array for texture/surface access across
-        levels. The array is created in the current CUDA context, so make this
-        device current with :meth:`set_current` before calling (mirroring
-        :meth:`create_stream` / :meth:`create_event`).
+        levels.
 
         Note
         ----
@@ -967,17 +794,14 @@ class Device:
 
         .. versionadded:: 1.1.0
         """
-
     def create_texture_object(self, *, resource: ResourceDescriptor, options: TextureObjectOptions | None=None) -> TextureObject:
-        """Create a :obj:`~cuda.core.texture.TextureObject` on the current device.
+        """Create a :obj:`~cuda.core.texture.TextureObject` on this device.
 
         Binds a resource (an :obj:`~cuda.core.texture.OpaqueArray` /
         :obj:`~cuda.core.texture.MipmappedArray` / linear or pitch2d
         :obj:`~cuda.core.Buffer`, wrapped in a
         :obj:`~cuda.core.texture.ResourceDescriptor`) as a bindless texture for
-        kernel-side sampled reads. The object is created in the current CUDA
-        context, so make this device current with :meth:`set_current` before
-        calling (mirroring :meth:`create_stream` / :meth:`create_event`).
+        kernel-side sampled reads. The resource must belong to this device.
 
         Note
         ----
@@ -997,17 +821,13 @@ class Device:
 
         .. versionadded:: 1.1.0
         """
-
     def create_surface_object(self, *, resource: ResourceDescriptor) -> SurfaceObject:
-        """Create a :obj:`~cuda.core.texture.SurfaceObject` on the current device.
+        """Create a :obj:`~cuda.core.texture.SurfaceObject` on this device.
 
         Binds an :obj:`~cuda.core.texture.OpaqueArray` (via a
         :obj:`~cuda.core.texture.ResourceDescriptor`) as a bindless surface for
         kernel-side typed load/store. The backing array must have been created
-        with ``is_surface_load_store=True``. The object is created in the
-        current CUDA context, so make this device current with
-        :meth:`set_current` before calling (mirroring :meth:`create_stream` /
-        :meth:`create_event`).
+        with ``is_surface_load_store=True`` and must belong to this device.
 
         Note
         ----
@@ -1026,5 +846,3 @@ class Device:
 
         .. versionadded:: 1.1.0
         """
-_tls = threading.local()
-_lock = threading.Lock()
\ No newline at end of file
diff --git a/cuda_core/cuda/core/_device.pyx b/cuda_core/cuda/core/_device.pyx
index fb2827ded55..a7e7d59e04a 100644
--- a/cuda_core/cuda/core/_device.pyx
+++ b/cuda_core/cuda/core/_device.pyx
@@ -12,7 +12,7 @@ from libcpp.vector cimport vector
 
 import threading
 
-from cuda.core._context cimport Context
+from cuda.core._context cimport Context, Context_check_open
 from cuda.core._context import ContextOptions
 from cuda.core._device_resources cimport DeviceResources, SMResource, WorkqueueResource
 from cuda.core._event cimport Event as cyEvent
@@ -23,12 +23,13 @@ from cuda.core._resource_handles cimport (
     GreenCtxHandle,
     create_context_handle_ref,
     create_green_ctx_handle,
+    context_synchronize,
     get_primary_context,
     get_last_error,
     as_cu,
 )
 
-from cuda.core._stream import IsStreamType, Stream
+from cuda.core._stream import IsStreamType, Stream, StreamOptions
 from cuda.core._utils.clear_error_support import assert_type
 from cuda.core._utils.cuda_utils import (
     ComputeCapability,
@@ -37,7 +38,9 @@ from cuda.core._utils.cuda_utils import (
     handle_return,
     runtime,
 )
-from cuda.core._stream cimport default_stream
+from cuda.core._stream cimport (
+    default_stream,
+)
 
 from typing import TYPE_CHECKING
 
@@ -61,6 +64,8 @@ _tls = threading.local()
 _lock = threading.Lock()
 cdef bint _is_cuInit = False
 
+__all__ = ['Device']
+
 
 cdef class DeviceProperties:
     """
@@ -922,34 +927,46 @@ cdef class DeviceProperties:
     @property
     def host_memory_pools_supported(self) -> bool:
         """bool: Device supports HOST location with the cuMemAllocAsync and cuMemPool family of APIs."""
-        return bool(
-            self._get_cached_attribute(driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_HOST_MEMORY_POOLS_SUPPORTED)
-        )
+        IF CUDA_CORE_BUILD_MAJOR < 13:
+            return False
+        ELSE:
+            return bool(
+                self._get_cached_attribute(driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_HOST_MEMORY_POOLS_SUPPORTED)
+            )
 
     @property
     def host_virtual_memory_management_supported(self) -> bool:
         """bool: Device supports HOST location with the virtual memory management APIs like cuMemCreate, cuMemMap and related APIs."""
-        return bool(
-            self._get_cached_attribute(
-                driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_HOST_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED
+        IF CUDA_CORE_BUILD_MAJOR < 13:
+            return False
+        ELSE:
+            return bool(
+                self._get_cached_attribute(
+                    driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_HOST_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED
+                )
             )
-        )
 
     @property
     def host_alloc_dma_buf_supported(self) -> bool:
         """bool: Device supports page-locked host memory buffer sharing with dma_buf mechanism."""
-        return bool(
-            self._get_cached_attribute(driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_HOST_ALLOC_DMA_BUF_SUPPORTED)
-        )
+        IF CUDA_CORE_BUILD_MAJOR < 13:
+            return False
+        ELSE:
+            return bool(
+                self._get_cached_attribute(driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_HOST_ALLOC_DMA_BUF_SUPPORTED)
+            )
 
     @property
     def only_partial_host_native_atomic_supported(self) -> bool:
         """bool: Link between the device and the host supports only some native atomic operations."""
-        return bool(
-            self._get_cached_attribute(
-                driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_ONLY_PARTIAL_HOST_NATIVE_ATOMIC_SUPPORTED
+        IF CUDA_CORE_BUILD_MAJOR < 13:
+            return False
+        ELSE:
+            return bool(
+                self._get_cached_attribute(
+                    driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_ONLY_PARTIAL_HOST_NATIVE_ATOMIC_SUPPORTED
+                )
             )
-        )
 
 
 class Device:
@@ -1007,6 +1024,7 @@ class Device:
             raise CUDAError(
                 f"Device {self._device_id} is not yet initialized, perhaps you forgot to call .set_current() first?"
             )
+        Context_check_open(self._context)
 
 
     @classmethod
@@ -1188,8 +1206,11 @@ class Device:
                 from cuda.core._memory import DeviceMemoryResource
                 self._memory_resource = DeviceMemoryResource(self._device_id)
             else:
-                from cuda.core._memory._legacy import _SynchronousMemoryResource
-                self._memory_resource = _SynchronousMemoryResource(self._device_id)
+                from cuda.core._memory._synchronous_memory_resource import (
+                    _SynchronousMemoryResource,
+                )
+                self._memory_resource = _SynchronousMemoryResource(
+                    self._device_id, self._context)
 
         return self._memory_resource
 
@@ -1201,7 +1222,7 @@ class Device:
 
     @property
     def default_stream(self) -> Stream:
-        """Return default CUDA :obj:`~_stream.Stream` associated with this device.
+        """Return a default CUDA :obj:`~_stream.Stream` token.
 
         The type of default stream returned depends on if the environment
         variable CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM is set.
@@ -1209,6 +1230,9 @@ class Device:
         If set, returns a per-thread default stream. Otherwise returns
         the legacy stream.
 
+        A default-stream token uses the device that is current when the token
+        is used.
+
         """
         return default_stream()
 
@@ -1239,6 +1263,12 @@ class Device:
 
         Providing a `ctx` causes the previous set context to be popped and returned.
 
+        If `ctx` was created on a different device than this receiver, the call
+        is delegated to that device's own :meth:`set_current`. This keeps the
+        owning device's bookkeeping consistent and lets a context this method
+        handed out for a foreign device be pushed back through any ``Device``
+        object, matching the CUDA context stack's own thread-wide semantics.
+
         Parameters
         ----------
         ctx : :obj:`~_context.Context`, optional
@@ -1247,7 +1277,9 @@ class Device:
         Returns
         -------
         :obj:`~_context.Context`, optional
-            Popped context.
+            The previous context, or ``None`` if no context was current. When
+            returned, its ``device_id`` identifies the device that was
+            previously current.
 
         Examples
         --------
@@ -1262,22 +1294,27 @@ class Device:
         """
         cdef ContextHandle h_context
         cdef cydriver.CUcontext prev_ctx, curr_ctx
+        cdef cydriver.CUdevice prev_dev
         cdef Context prev_owned = None
 
         if ctx is not None:
             # TODO: revisit once Context is cythonized
             assert_type(ctx, Context)
+            Context_check_open(ctx)
             if ctx._device_id != self._device_id:
-                raise RuntimeError(
-                    "the provided context was created on the device with"
-                    f" id={ctx._device_id}, which is different from the target id={self._device_id}"
-                )
+                # The CUDA context stack is per-thread, not per-Device-object,
+                # so pushing/popping a foreign-device context is delegated to
+                # the device that owns it; its own bookkeeping (_context,
+                # _has_inited) is what should track this push, not ours.
+                return Device(ctx._device_id).set_current(ctx)
             if self._has_inited and self._context is not None:
                 prev_owned = self._context
-            # prev_ctx is the previous context
             curr_ctx = as_cu(ctx._h_context)
             prev_ctx = NULL
             with nogil:
+                HANDLE_RETURN(cydriver.cuCtxGetCurrent(&prev_ctx))
+                if prev_ctx != NULL:
+                    HANDLE_RETURN(cydriver.cuCtxGetDevice(&prev_dev))
                 HANDLE_RETURN(cydriver.cuCtxPopCurrent(&prev_ctx))
                 HANDLE_RETURN(cydriver.cuCtxPushCurrent(curr_ctx))
             self._has_inited = True
@@ -1285,12 +1322,16 @@ class Device:
             if prev_ctx != NULL:
                 if prev_owned is not None and as_cu(prev_owned._h_context) == prev_ctx:
                     return prev_owned
-                return Context._from_handle(Context, create_context_handle_ref(prev_ctx), self._device_id)
+                return Context._from_handle(
+                    Context, create_context_handle_ref(prev_ctx), <int>prev_dev)
         else:
             # use primary ctx
             h_context = get_primary_context(self._device_id)
             if h_context.get() == NULL:
-                raise ValueError("Cannot set NULL context as current")
+                HANDLE_RETURN(get_last_error())
+                raise RuntimeError(
+                    f"Failed to retain the primary context for device {self._device_id}"
+                )
             with nogil:
                 HANDLE_RETURN(cydriver.cuCtxSetCurrent(as_cu(h_context)))
             self._has_inited = True
@@ -1319,7 +1360,6 @@ class Device:
         cdef object res
         cdef SMResource sm_res
         cdef WorkqueueResource wq_res
-        cdef GreenCtxHandle h_green
 
         if options is None:
             raise ValueError(
@@ -1351,7 +1391,7 @@ class Device:
             else:
                 raise TypeError(f"Unsupported context resource type: {type(res)}")
 
-        h_green = create_green_ctx_handle(
+        cdef GreenCtxHandle h_green = create_green_ctx_handle(
             c_resources.data(),
             <unsigned int>(c_resources.size()),
             <cydriver.CUdevice>(self._device_id),
@@ -1363,8 +1403,8 @@ class Device:
 
         return Context._from_green_ctx(Context, h_green, self._device_id)
 
-    def create_stream(self, obj: IsStreamType | None = None, options: object = None) -> Stream:
-        """Create a :obj:`~_stream.Stream` object.
+    def create_stream(self, obj: IsStreamType | None = None, options: StreamOptions | None = None) -> Stream:
+        """Create or wrap a :obj:`~_stream.Stream` object.
 
         New stream objects can be created in two different ways:
 
@@ -1376,7 +1416,7 @@ class Device:
 
         Note
         ----
-        Device must be initialized.
+        Device must be initialized. New streams are created on this device.
 
         Parameters
         ----------
@@ -1395,7 +1435,7 @@ class Device:
         return Stream._init(obj=obj, options=options, device_id=self._device_id, ctx=self._context)
 
     def create_event(self, options: EventOptions | None = None) -> Event:
-        """Create an :obj:`~_event.Event` object without recording it to a :obj:`~_stream.Stream`.
+        """Create an :obj:`~_event.Event` on this device without recording it to a :obj:`~_stream.Stream`.
 
         Note
         ----
@@ -1445,7 +1485,12 @@ class Device:
         return self.memory_resource.allocate(size, stream=stream)
 
     def sync(self) -> None:
-        """Synchronize the device.
+        """Synchronize this device's bound context.
+
+        Waits for all preceding work in this device's bound :obj:`~_context.Context`
+        to complete. Only that context is synchronized, not the device as a
+        whole; work queued in a different context on the same device (e.g. a
+        green context) is unaffected.
 
         Note
         ----
@@ -1453,10 +1498,11 @@ class Device:
 
         """
         self._check_context_initialized()
-        handle_return(runtime.cudaDeviceSynchronize())
+        cdef Context ctx = self._context
+        HANDLE_RETURN(context_synchronize(ctx._h_context))
 
     def create_graph_builder(self) -> GraphBuilder:
-        """Create a new :obj:`~graph.GraphBuilder` object.
+        """Create a new :obj:`~graph.GraphBuilder` on this device.
 
         Returns
         -------
@@ -1470,12 +1516,10 @@ class Device:
         return GraphBuilder._init(self.create_stream())
 
     def create_opaque_array(self, options: OpaqueArrayOptions) -> OpaqueArray:
-        """Create an :obj:`~cuda.core.texture.OpaqueArray` on the current device.
+        """Create an :obj:`~cuda.core.texture.OpaqueArray` on this device.
 
         Allocates an opaque, hardware-laid-out CUDA array for texture/surface
-        access. The array is created in the current CUDA context, so make this
-        device current with :meth:`set_current` before calling (mirroring
-        :meth:`create_stream` / :meth:`create_event`).
+        access.
 
         Note
         ----
@@ -1496,15 +1540,13 @@ class Device:
         from cuda.core.texture._array import _create_opaque_array
 
         self._check_context_initialized()
-        return _create_opaque_array(options)
+        return _create_opaque_array(options, self._context, self._device_id)
 
     def create_mipmapped_array(self, options: MipmappedArrayOptions) -> MipmappedArray:
-        """Create a :obj:`~cuda.core.texture.MipmappedArray` on the current device.
+        """Create a :obj:`~cuda.core.texture.MipmappedArray` on this device.
 
         Allocates a mipmapped CUDA array for texture/surface access across
-        levels. The array is created in the current CUDA context, so make this
-        device current with :meth:`set_current` before calling (mirroring
-        :meth:`create_stream` / :meth:`create_event`).
+        levels.
 
         Note
         ----
@@ -1525,20 +1567,18 @@ class Device:
         from cuda.core.texture._mipmapped_array import _create_mipmapped_array
 
         self._check_context_initialized()
-        return _create_mipmapped_array(options)
+        return _create_mipmapped_array(options, self._context, self._device_id)
 
     def create_texture_object(
         self, *, resource: ResourceDescriptor, options: TextureObjectOptions | None = None
     ) -> TextureObject:
-        """Create a :obj:`~cuda.core.texture.TextureObject` on the current device.
+        """Create a :obj:`~cuda.core.texture.TextureObject` on this device.
 
         Binds a resource (an :obj:`~cuda.core.texture.OpaqueArray` /
         :obj:`~cuda.core.texture.MipmappedArray` / linear or pitch2d
         :obj:`~cuda.core.Buffer`, wrapped in a
         :obj:`~cuda.core.texture.ResourceDescriptor`) as a bindless texture for
-        kernel-side sampled reads. The object is created in the current CUDA
-        context, so make this device current with :meth:`set_current` before
-        calling (mirroring :meth:`create_stream` / :meth:`create_event`).
+        kernel-side sampled reads. The resource must belong to this device.
 
         Note
         ----
@@ -1561,18 +1601,16 @@ class Device:
         from cuda.core.texture._texture import _create_texture_object
 
         self._check_context_initialized()
-        return _create_texture_object(resource, options)
+        return _create_texture_object(
+            resource, options, self._context, self._device_id)
 
     def create_surface_object(self, *, resource: ResourceDescriptor) -> SurfaceObject:
-        """Create a :obj:`~cuda.core.texture.SurfaceObject` on the current device.
+        """Create a :obj:`~cuda.core.texture.SurfaceObject` on this device.
 
         Binds an :obj:`~cuda.core.texture.OpaqueArray` (via a
         :obj:`~cuda.core.texture.ResourceDescriptor`) as a bindless surface for
         kernel-side typed load/store. The backing array must have been created
-        with ``is_surface_load_store=True``. The object is created in the
-        current CUDA context, so make this device current with
-        :meth:`set_current` before calling (mirroring :meth:`create_stream` /
-        :meth:`create_event`).
+        with ``is_surface_load_store=True`` and must belong to this device.
 
         Note
         ----
@@ -1594,7 +1632,8 @@ class Device:
         from cuda.core.texture._surface import _create_surface_object
 
         self._check_context_initialized()
-        return _create_surface_object(resource)
+        return _create_surface_object(
+            resource, self._context, self._device_id)
 
 
 cdef inline int Device_ensure_cuda_initialized() except? -1:
diff --git a/cuda_core/cuda/core/_device_resources.pyi b/cuda_core/cuda/core/_device_resources.pyi
index 7514f5a2f43..9d766502889 100644
--- a/cuda_core/cuda/core/_device_resources.pyi
+++ b/cuda_core/cuda/core/_device_resources.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_device_resources.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_device_resources.pyx
 
 from collections.abc import Sequence as SequenceABC
 from dataclasses import dataclass
@@ -8,6 +6,7 @@ from dataclasses import dataclass
 from cuda.core._device import Device
 from cuda.core.typing import WorkqueueSharingScopeType
 
+__all__ = ['DeviceResources', 'SMResource', 'SMResourceOptions', 'WorkqueueResource', 'WorkqueueResourceOptions']
 
 @dataclass
 class SMResourceOptions:
@@ -61,8 +60,7 @@ class WorkqueueResourceOptions:
     sharing_scope: WorkqueueSharingScopeType | str | None = None
     concurrency_limit: int | None = None
 
-    def __post_init__(self):
-        ...
+    def __post_init__(self): ...
 
 class SMResource:
     """Represent an SM (streaming multiprocessor) resource partition.
@@ -70,30 +68,22 @@ class SMResource:
     Instances are returned by :obj:`DeviceResources.sm` or
     :meth:`SMResource.split` and cannot be instantiated directly.
     """
-
-    def __init__(self, *args, **kwargs):
-        ...
-
+    def __init__(self, *args, **kwargs): ...
     @property
     def handle(self) -> int:
         """Return the address of the underlying ``CUdevResource`` struct."""
-
     @property
     def sm_count(self) -> int:
         """Total SMs available in this resource."""
-
     @property
     def min_partition_size(self) -> int:
         """Minimum SM count required to create a partition."""
-
     @property
     def coscheduled_alignment(self) -> int:
         """Number of SMs guaranteed to be co-scheduled."""
-
     @property
     def flags(self) -> int:
         """Raw flags from the underlying SM resource."""
-
     def split(self, options: SMResourceOptions, *, dry_run: bool=False) -> tuple[list[SMResource], SMResource]:
         """Split this SM resource into groups and a remainder.
 
@@ -120,14 +110,10 @@ class WorkqueueResource:
     Instances are returned by :obj:`DeviceResources.workqueue` and
     cannot be instantiated directly.
     """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @property
     def handle(self) -> int:
         """Return the address of the underlying config ``CUdevResource`` struct."""
-
     @property
     def sharing_scope(self) -> WorkqueueSharingScopeType:
         """Current sharing scope of this workqueue resource.
@@ -138,7 +124,6 @@ class WorkqueueResource:
         :meth:`configure` with
         :attr:`WorkqueueResourceOptions.sharing_scope`.
         """
-
     @property
     def concurrency_limit(self) -> int:
         """Current expected maximum concurrent stream-ordered workloads.
@@ -149,11 +134,9 @@ class WorkqueueResource:
         via :meth:`configure` with
         :attr:`WorkqueueResourceOptions.concurrency_limit`.
         """
-
     @property
     def device(self) -> Device:
         """The :class:`~cuda.core.Device` this workqueue resource is available on."""
-
     def configure(self, options: WorkqueueResourceOptions) -> None:
         """Configure the workqueue resource in place.
 
@@ -173,15 +156,10 @@ class DeviceResources:
 
     This class cannot be instantiated directly.
     """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @property
     def sm(self) -> SMResource:
         """Return the :obj:`SMResource` for this device or context."""
-
     @property
     def workqueue(self) -> WorkqueueResource:
         """Return the :obj:`WorkqueueResource` for this device or context."""
-__all__ = ['DeviceResources', 'SMResource', 'SMResourceOptions', 'WorkqueueResource', 'WorkqueueResourceOptions']
\ No newline at end of file
diff --git a/cuda_core/cuda/core/_device_resources.pyx b/cuda_core/cuda/core/_device_resources.pyx
index 0c952821a04..15ca6c56685 100644
--- a/cuda_core/cuda/core/_device_resources.pyx
+++ b/cuda_core/cuda/core/_device_resources.pyx
@@ -250,7 +250,6 @@ cdef object _resolve_split_by_count_request(SMResourceOptions options):
     cdef list counts = _broadcast_field(options.count, n_groups)
     cdef object first = counts[0]
     cdef object value
-    cdef unsigned int min_count
 
     if options.coscheduled_sm_count is not None:
         raise RuntimeError(
@@ -270,7 +269,7 @@ cdef object _resolve_split_by_count_request(SMResourceOptions options):
                 "use CUDA 13.1 or newer for per-group counts"
             )
 
-    min_count = _to_sm_count(first)
+    cdef unsigned int min_count = _to_sm_count(first)
     return n_groups, min_count
 
 
diff --git a/cuda_core/cuda/core/_dlpack.pyi b/cuda_core/cuda/core/_dlpack.pyi
index 575d9ced8f5..d2e442776f7 100644
--- a/cuda_core/cuda/core/_dlpack.pyi
+++ b/cuda_core/cuda/core/_dlpack.pyi
@@ -1,11 +1,17 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_dlpack.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_dlpack.pyx
 
 from enum import IntEnum
+from typing import Any, Callable, TypedDict
+
+from typing_extensions import TypeAlias
 
-_DLDeviceType = int
-DLDataTypeCode = int
+_DLDeviceType: TypeAlias = int
+DLDataTypeCode: TypeAlias = int
+DLPackManagedTensorAllocator: TypeAlias = Callable[[DLTensor, DLManagedTensorVersioned, Any, Callable[[Any, bytes, bytes], None]], int]
+DLPackManagedTensorFromPyObjectNoSync: TypeAlias = Callable[[Any, DLManagedTensorVersioned], int]
+DLPackManagedTensorToPyObjectNoSync: TypeAlias = Callable[[DLManagedTensorVersioned, Any], int]
+DLPackDLTensorFromPyObjectNoSync: TypeAlias = Callable[[Any, DLTensor], int]
+DLPackCurrentWorkStream: TypeAlias = Callable[[_DLDeviceType, int, Any], int]
 
 class DLDeviceType(IntEnum):
     kDLCPU = 1
@@ -13,12 +19,56 @@ class DLDeviceType(IntEnum):
     kDLCUDAHost = 3
     kDLCUDAManaged = 13
 
-def make_py_capsule(buf: object, versioned: bool) -> object:
-    ...
+class DLDevice(TypedDict):
+    device_type: _DLDeviceType
+    device_id: int
+
+class DLDataType(TypedDict):
+    code: int
+    bits: int
+    lanes: int
+
+class DLTensor(TypedDict):
+    data: Any
+    device: DLDevice
+    ndim: int
+    dtype: DLDataType
+    shape: int
+    strides: int
+    byte_offset: int
+
+class DLManagedTensor(TypedDict):
+    dl_tensor: DLTensor
+    manager_ctx: Any
+    deleter: Callable[[DLManagedTensor], None]
+
+class DLPackVersion(TypedDict):
+    major: int
+    minor: int
+
+class DLManagedTensorVersioned(TypedDict):
+    version: DLPackVersion
+    manager_ctx: Any
+    deleter: Callable[[DLManagedTensorVersioned], None]
+    flags: int
+    dl_tensor: DLTensor
+
+class DLPackExchangeAPIHeader(TypedDict):
+    version: DLPackVersion
+    prev_api: DLPackExchangeAPIHeader
+
+class DLPackExchangeAPI(TypedDict):
+    header: DLPackExchangeAPIHeader
+    managed_tensor_allocator: DLPackManagedTensorAllocator
+    managed_tensor_from_py_object_no_sync: DLPackManagedTensorFromPyObjectNoSync
+    managed_tensor_to_py_object_no_sync: DLPackManagedTensorToPyObjectNoSync
+    dltensor_from_py_object_no_sync: DLPackDLTensorFromPyObjectNoSync
+    current_work_stream: DLPackCurrentWorkStream
 
 def classify_dl_device(buf: object) -> tuple[int, int]:
     """Classify a buffer into a DLPack (device_type, device_id) pair.
 
     ``buf`` must expose ``is_device_accessible``, ``is_host_accessible``,
     ``is_managed``, and ``device_id`` attributes.
-    """
\ No newline at end of file
+    """
+def make_py_capsule(buf: object, versioned: bool) -> object: ...
diff --git a/cuda_core/cuda/core/_dlpack.pyx b/cuda_core/cuda/core/_dlpack.pyx
index 0c251881d11..a41b3a73e85 100644
--- a/cuda_core/cuda/core/_dlpack.pyx
+++ b/cuda_core/cuda/core/_dlpack.pyx
@@ -115,10 +115,8 @@ cdef inline int setup_dl_tensor_device(DLTensor* dl_tensor, object buf) except -
 
 
 cdef inline int setup_dl_tensor_dtype(DLTensor* dl_tensor) except -1 nogil:
-    cdef DLDataType* dtype = &dl_tensor.dtype
-    dtype.code = <uint8_t>kDLInt
-    dtype.lanes = <uint16_t>1
-    dtype.bits = <uint8_t>8
+    dl_tensor.dtype = DLDataType(
+        code=<uint8_t>kDLInt, bits=<uint8_t>8, lanes=<uint16_t>1)
     return 0
 
 
diff --git a/cuda_core/cuda/core/_event.pxd b/cuda_core/cuda/core/_event.pxd
index 5710b13699b..c1ab008d5e1 100644
--- a/cuda_core/cuda/core/_event.pxd
+++ b/cuda_core/cuda/core/_event.pxd
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # SPDX-License-Identifier: Apache-2.0
 
@@ -20,3 +20,10 @@ cdef class Event:
     cdef Event _from_handle(EventHandle h_event)
 
     cpdef close(self)
+
+
+cdef Event Event_accept(object arg)
+cdef inline int Event_check_open(Event self) except -1:
+    if not self._h_event:
+        raise RuntimeError("Event has been closed")
+    return 0
diff --git a/cuda_core/cuda/core/_event.pyi b/cuda_core/cuda/core/_event.pyi
index 1ea91308bc1..3177b5fff0b 100644
--- a/cuda_core/cuda/core/_event.pyi
+++ b/cuda_core/cuda/core/_event.pyi
@@ -1,14 +1,13 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_event.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_event.pyx
 
 from dataclasses import dataclass
 
 import cuda.bindings.driver
-import cython
+from _typeshed import Incomplete
 from cuda.core._context import Context
 from cuda.core._device import Device
 
+__all__ = ['Event', 'EventOptions']
 
 @dataclass
 class EventOptions:
@@ -61,39 +60,25 @@ class Event:
     and they should instead be created through a :obj:`~_stream.Stream` object.
 
     """
-
+    def __init__(self, *args, **kwargs) -> None: ...
     def close(self):
         """Destroy the event.
 
         Releases the event handle. The underlying CUDA event is destroyed
         when the last reference is released.
         """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
-    def __isub__(self, other: object):
-        ...
-
-    def __rsub__(self, other: object):
-        ...
-
-    def __sub__(self, other: Event) -> float:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __repr__(self) -> str:
-        ...
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this event has been closed."""
+    def __isub__(self, other: object): ...
+    def __rsub__(self, other: object): ...
+    def __sub__(self, other: Event) -> float: ...
+    def __hash__(self) -> int: ...
+    def __eq__(self, other: object) -> bool: ...
+    def __repr__(self) -> str: ...
     @property
     def ipc_descriptor(self) -> IPCEventDescriptor:
         """Descriptor for sharing this event with other processes."""
-
     @classmethod
     def from_ipc_descriptor(cls, ipc_descriptor: IPCEventDescriptor) -> Event:
         """Import an event that was exported from another process.
@@ -110,21 +95,17 @@ class Event:
             A new event backed by the imported IPC handle.
 
         """
-
     @property
     def is_ipc_enabled(self) -> bool:
         """Return True if the event can be shared across process boundaries, otherwise False."""
-
     @property
     def is_timing_enabled(self) -> bool:
         """Return True if the event records timing data, otherwise False."""
-
     @property
     def is_blocking_sync(self) -> bool:
         """Return True if the event uses blocking synchronization (the CPU
         thread blocks on :meth:`sync` instead of busy-waiting), otherwise False.
         """
-
     def sync(self) -> None:
         """Synchronize until the event completes.
 
@@ -134,11 +115,9 @@ class Event:
         thread busy-waits until the event has completed.
 
         """
-
     @property
     def is_done(self) -> bool:
         """Return True if all captured works have been completed, otherwise False."""
-
     @property
     def handle(self) -> cuda.bindings.driver.CUevent:
         """Return the underlying CUevent object.
@@ -148,7 +127,6 @@ class Event:
             This handle is a Python object. To get the memory address of the underlying C
             handle, call ``int(Event.handle)``.
         """
-
     @property
     def device(self) -> Device:
         """Return the :obj:`~_device.Device` singleton associated with this event.
@@ -160,26 +138,16 @@ class Event:
         context is set current after a event is created.
 
         """
-
     @property
     def context(self) -> Context:
         """Return the :obj:`~_context.Context` associated with this event."""
 
 class IPCEventDescriptor:
     """Serializable object describing an event that can be shared between processes."""
-
-    def __init__(self, *arg, **kwargs) -> None:
-        ...
-
+    def __init__(self, *arg, **kwargs) -> None: ...
     @staticmethod
-    def _init(reserved: bytes, is_blocking_sync: cython.bint) -> IPCEventDescriptor:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __reduce__(self) -> tuple[object, ...]:
-        ...
+    def _init(reserved: bytes, is_blocking_sync: Incomplete) -> IPCEventDescriptor: ...
+    def __eq__(self, other: object) -> bool: ...
+    def __reduce__(self) -> tuple[object, ...]: ...
 
-def _reduce_event(event: Event) -> tuple[object, ...]:
-    ...
\ No newline at end of file
+def _reduce_event(event: Event) -> tuple[object, ...]: ...
diff --git a/cuda_core/cuda/core/_event.pyx b/cuda_core/cuda/core/_event.pyx
index e5cb81ac41e..dcbb55ba5a4 100644
--- a/cuda_core/cuda/core/_event.pyx
+++ b/cuda_core/cuda/core/_event.pyx
@@ -43,6 +43,8 @@ if TYPE_CHECKING:
     import cuda.bindings.driver  # no-cython-lint
     from cuda.core._device import Device
 
+__all__ = ['Event', 'EventOptions']
+
 
 @dataclass
 cdef class EventOptions:
@@ -155,6 +157,11 @@ cdef class Event:
         """
         self._h_event.reset()
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this event has been closed."""
+        return self._h_event.get() == NULL
+
     def __isub__(self, other: object):
         return NotImplemented
 
@@ -163,14 +170,16 @@ cdef class Event:
 
     def __sub__(self, other: Event) -> float:
         # return self - other (in milliseconds)
+        Event_check_open(self)
+        cdef Event other_event = Event_accept(other)
         cdef float timing
         with nogil:
-            err = cydriver.cuEventElapsedTime(&timing, as_cu((<Event>other)._h_event), as_cu(self._h_event))
+            err = cydriver.cuEventElapsedTime(&timing, as_cu(other_event._h_event), as_cu(self._h_event))
         if err == 0:
             return timing
         else:
             if err == cydriver.CUresult.CUDA_ERROR_INVALID_HANDLE:
-                if not self.is_timing_enabled or not other.is_timing_enabled:
+                if not self.is_timing_enabled or not other_event.is_timing_enabled:
                     explanation = (
                         "Both Events must be created with timing enabled in order to subtract them; "
                         "use EventOptions(timing_enabled=True) when creating both events."
@@ -206,6 +215,7 @@ cdef class Event:
     @property
     def ipc_descriptor(self) -> IPCEventDescriptor:
         """Descriptor for sharing this event with other processes."""
+        Event_check_open(self)
         if self._ipc_descriptor is not None:
             return self._ipc_descriptor
         if not self.is_ipc_enabled:
@@ -253,11 +263,13 @@ cdef class Event:
     @property
     def is_ipc_enabled(self) -> bool:
         """Return True if the event can be shared across process boundaries, otherwise False."""
+        Event_check_open(self)
         return get_event_ipc_enabled(self._h_event)
 
     @property
     def is_timing_enabled(self) -> bool:
         """Return True if the event records timing data, otherwise False."""
+        Event_check_open(self)
         return get_event_timing_enabled(self._h_event)
 
     @property
@@ -265,6 +277,7 @@ cdef class Event:
         """Return True if the event uses blocking synchronization (the CPU
         thread blocks on :meth:`sync` instead of busy-waiting), otherwise False.
         """
+        Event_check_open(self)
         return get_event_is_blocking_sync(self._h_event)
 
     def sync(self) -> None:
@@ -276,12 +289,14 @@ cdef class Event:
         thread busy-waits until the event has completed.
 
         """
+        Event_check_open(self)
         with nogil:
             HANDLE_RETURN(cydriver.cuEventSynchronize(as_cu(self._h_event)))
 
     @property
     def is_done(self) -> bool:
         """Return True if all captured works have been completed, otherwise False."""
+        Event_check_open(self)
         with nogil:
             result = cydriver.cuEventQuery(as_cu(self._h_event))
         if result == cydriver.CUresult.CUDA_SUCCESS:
@@ -312,6 +327,7 @@ cdef class Event:
         context is set current after a event is created.
 
         """
+        Event_check_open(self)
         cdef int dev_id = get_event_device_id(self._h_event)
         if dev_id >= 0:
             from ._device import Device  # avoid circular import
@@ -320,11 +336,19 @@ cdef class Event:
     @property
     def context(self) -> Context:
         """Return the :obj:`~_context.Context` associated with this event."""
+        Event_check_open(self)
         cdef ContextHandle h_ctx = get_event_context(self._h_event)
         cdef int dev_id = get_event_device_id(self._h_event)
         if h_ctx and dev_id >= 0:
             return Context._from_handle(Context, h_ctx, dev_id)
 
+cdef Event Event_accept(object arg):
+    if not isinstance(arg, Event):
+        raise TypeError(f"Event expected, got {type(arg).__name__}")
+    cdef Event event = <Event>arg
+    Event_check_open(event)
+    return event
+
 
 cdef class IPCEventDescriptor:
     """Serializable object describing an event that can be shared between processes."""
diff --git a/cuda_core/cuda/core/_graphics.pyi b/cuda_core/cuda/core/_graphics.pyi
index b7022e5a18a..b819d90a1b1 100644
--- a/cuda_core/cuda/core/_graphics.pyi
+++ b/cuda_core/cuda/core/_graphics.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_graphics.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_graphics.pyx
 
 from typing import Sequence
 
@@ -8,6 +6,8 @@ from cuda.bindings import cydriver
 from cuda.core._memory._buffer import Buffer
 from cuda.core._stream import Stream
 
+__all__ = ['GraphicsResource']
+_REGISTER_FLAGS = {'none': cydriver.CU_GRAPHICS_REGISTER_FLAGS_NONE, 'read_only': cydriver.CU_GRAPHICS_REGISTER_FLAGS_READ_ONLY, 'write_discard': cydriver.CU_GRAPHICS_REGISTER_FLAGS_WRITE_DISCARD, 'surface_load_store': cydriver.CU_GRAPHICS_REGISTER_FLAGS_SURFACE_LDST, 'texture_gather': cydriver.CU_GRAPHICS_REGISTER_FLAGS_TEXTURE_GATHER}
 
 class GraphicsResource:
     """RAII wrapper for a CUDA graphics resource (``CUgraphicsResource``).
@@ -48,23 +48,7 @@ class GraphicsResource:
                 # ... launch kernels using buf.handle, buf.size ...
                 pass
     """
-
-    def close(self, stream: object=None):
-        """Unregister this graphics resource from CUDA.
-
-        If the resource is currently mapped, it is unmapped first. After
-        closing, the resource cannot be used again.
-
-        Parameters
-        ----------
-        stream : :class:`~cuda.core.Stream`, optional
-            Optional override for the stream used to close the currently
-            mapped buffer, if one exists.
-        """
-
-    def __init__(self) -> None:
-        ...
-
+    def __init__(self) -> None: ...
     @classmethod
     def from_gl_buffer(cls, gl_buffer: int, *, flags: str | tuple[str, ...] | list[str] | None=None, stream: Stream | None=None) -> GraphicsResource:
         """Register an OpenGL buffer object for CUDA access.
@@ -111,7 +95,6 @@ class GraphicsResource:
         ValueError
             If an unknown flag string is provided.
         """
-
     @classmethod
     def from_gl_image(cls, image: int, target: int, *, flags: str | tuple[str, ...] | list[str] | None=None) -> GraphicsResource:
         """Register an OpenGL texture or renderbuffer for CUDA access.
@@ -142,10 +125,7 @@ class GraphicsResource:
         ValueError
             If an unknown flag string is provided.
         """
-
-    def _get_mapped_buffer(self) -> object:
-        ...
-
+    def _get_mapped_buffer(self) -> object: ...
     def map(self, *, stream: Stream) -> Buffer:
         """Map this graphics resource for CUDA access.
 
@@ -178,7 +158,6 @@ class GraphicsResource:
         CUDAError
             If the mapping fails.
         """
-
     def unmap(self, *, stream: Stream | None=None) -> None:
         """Unmap this graphics resource, releasing it back to the graphics API.
 
@@ -198,29 +177,32 @@ class GraphicsResource:
         CUDAError
             If the unmapping fails.
         """
+    def __enter__(self) -> object: ...
+    def __exit__(self, exc_type: type | None, exc_val: BaseException | None, exc_tb: object) -> bool: ...
+    def close(self, stream: object | None=None):
+        """Unregister this graphics resource from CUDA.
 
-    def __enter__(self) -> object:
-        ...
-
-    def __exit__(self, exc_type: type | None, exc_val: BaseException | None, exc_tb: object) -> bool:
-        ...
+        If the resource is currently mapped, it is unmapped first. After
+        closing, the resource cannot be used again.
 
+        Parameters
+        ----------
+        stream : :class:`~cuda.core.Stream`, optional
+            Optional override for the stream used to close the currently
+            mapped buffer, if one exists.
+        """
     @property
     def is_mapped(self) -> bool:
         """Whether the resource is currently mapped for CUDA access."""
-
     @property
     def handle(self) -> int:
         """The raw ``CUgraphicsResource`` handle as a Python int."""
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this graphics resource has been closed."""
     @property
     def resource_handle(self) -> int:
         """Alias for :attr:`handle`."""
+    def __repr__(self) -> str: ...
 
-    def __repr__(self) -> str:
-        ...
-__all__ = ['GraphicsResource']
-_REGISTER_FLAGS = {'none': cydriver.CU_GRAPHICS_REGISTER_FLAGS_NONE, 'read_only': cydriver.CU_GRAPHICS_REGISTER_FLAGS_READ_ONLY, 'write_discard': cydriver.CU_GRAPHICS_REGISTER_FLAGS_WRITE_DISCARD, 'surface_load_store': cydriver.CU_GRAPHICS_REGISTER_FLAGS_SURFACE_LDST, 'texture_gather': cydriver.CU_GRAPHICS_REGISTER_FLAGS_TEXTURE_GATHER}
-
-def _parse_register_flags(flags: str | Sequence[str] | None) -> int:
-    ...
\ No newline at end of file
+def _parse_register_flags(flags: str | Sequence[str] | None) -> int: ...
diff --git a/cuda_core/cuda/core/_graphics.pyx b/cuda_core/cuda/core/_graphics.pyx
index c5fc5c83ecc..b8945bb0d71 100644
--- a/cuda_core/cuda/core/_graphics.pyx
+++ b/cuda_core/cuda/core/_graphics.pyx
@@ -45,6 +45,12 @@ def _parse_register_flags(flags: str | Sequence[str] | None) -> int:
     return result
 
 
+cdef inline int GraphicsResource_check_open(GraphicsResource self) except -1:
+    if not self._handle:
+        raise RuntimeError("GraphicsResource has been closed")
+    return 0
+
+
 cdef class GraphicsResource:
     """RAII wrapper for a CUDA graphics resource (``CUgraphicsResource``).
 
@@ -209,10 +215,9 @@ cdef class GraphicsResource:
         return self
 
     def _get_mapped_buffer(self) -> object:
-        cdef Buffer buf
         if self._mapped_buffer is None:
             return None
-        buf = <Buffer>self._mapped_buffer
+        cdef Buffer buf = <Buffer>self._mapped_buffer
         if not buf._h_ptr:
             self._mapped_buffer = None
             return None
@@ -250,20 +255,15 @@ cdef class GraphicsResource:
         CUDAError
             If the mapping fails.
         """
-        cdef Stream s_obj
-        cdef cydriver.CUgraphicsResource raw
-        cdef cydriver.CUstream cy_stream
         cdef cydriver.CUdeviceptr dev_ptr = 0
         cdef size_t size = 0
-        cdef Buffer buf
-        if not self._handle:
-            raise RuntimeError("GraphicsResource has been closed")
+        GraphicsResource_check_open(self)
         if self._get_mapped_buffer() is not None:
             raise RuntimeError("GraphicsResource is already mapped")
 
-        s_obj = Stream_accept(stream)
-        raw = as_cu(self._handle)
-        cy_stream = as_cu(s_obj._h_stream)
+        cdef Stream s_obj = Stream_accept(stream)
+        cdef cydriver.CUgraphicsResource raw = as_cu(self._handle)
+        cdef cydriver.CUstream cy_stream = as_cu(s_obj._h_stream)
         with nogil:
             HANDLE_RETURN(
                 cydriver.cuGraphicsMapResources(1, &raw, cy_stream)
@@ -271,7 +271,7 @@ cdef class GraphicsResource:
             HANDLE_RETURN(
                 cydriver.cuGraphicsResourceGetMappedPointer(&dev_ptr, &size, raw)
             )
-        buf = Buffer_from_deviceptr_handle(
+        cdef Buffer buf = Buffer_from_deviceptr_handle(
             deviceptr_create_mapped_graphics(dev_ptr, self._handle, s_obj._h_stream),
             size,
             None,
@@ -299,14 +299,11 @@ cdef class GraphicsResource:
         CUDAError
             If the unmapping fails.
         """
-        cdef object buf_obj
-        cdef Buffer buf
-        if not self._handle:
-            raise RuntimeError("GraphicsResource has been closed")
-        buf_obj = self._get_mapped_buffer()
+        GraphicsResource_check_open(self)
+        cdef object buf_obj = self._get_mapped_buffer()
         if buf_obj is None:
             raise RuntimeError("GraphicsResource is not mapped")
-        buf = <Buffer>buf_obj
+        cdef Buffer buf = <Buffer>buf_obj
         buf.close(stream=stream)
         self._mapped_buffer = None
 
@@ -332,11 +329,10 @@ cdef class GraphicsResource:
             Optional override for the stream used to close the currently
             mapped buffer, if one exists.
         """
-        cdef object buf_obj
         cdef Buffer buf
         if not self._handle:
             return
-        buf_obj = self._get_mapped_buffer()
+        cdef object buf_obj = self._get_mapped_buffer()
         if buf_obj is not None:
             buf = <Buffer>buf_obj
             buf.close(stream=stream)
@@ -355,6 +351,11 @@ cdef class GraphicsResource:
         """The raw ``CUgraphicsResource`` handle as a Python int."""
         return as_intptr(self._handle)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this graphics resource has been closed."""
+        return self._handle.get() == NULL
+
     @property
     def resource_handle(self) -> int:
         """Alias for :attr:`handle`."""
diff --git a/cuda_core/cuda/core/_host.py b/cuda_core/cuda/core/_host.py
index e74743d493a..30464409871 100644
--- a/cuda_core/cuda/core/_host.py
+++ b/cuda_core/cuda/core/_host.py
@@ -6,6 +6,8 @@
 import threading
 from typing import ClassVar
 
+__all__ = ["Host"]
+
 
 class Host:
     """Host (CPU) location for managed-memory operations.
diff --git a/cuda_core/cuda/core/_include/layout.hpp b/cuda_core/cuda/core/_include/layout.hpp
index b5da219df34..f92401a0205 100644
--- a/cuda_core/cuda/core/_include/layout.hpp
+++ b/cuda_core/cuda/core/_include/layout.hpp
@@ -1,5 +1,4 @@
-// SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES.
-// All rights reserved.
+// SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 //
 // SPDX-License-Identifier: Apache-2.0
 
diff --git a/cuda_core/cuda/core/_kernel_arg_handler.pyi b/cuda_core/cuda/core/_kernel_arg_handler.pyi
index 0ebd2c0d0b6..f5ef040b8de 100644
--- a/cuda_core/cuda/core/_kernel_arg_handler.pyi
+++ b/cuda_core/cuda/core/_kernel_arg_handler.pyi
@@ -1,18 +1,19 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_kernel_arg_handler.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_kernel_arg_handler.pyx
 
-from __future__ import annotations
+from typing import Any, Sequence, TypedDict
 
-from typing import Any, Sequence
+from _typeshed import Incomplete
+from typing_extensions import TypeAlias
 
-from libcpp.complex import complex as cpp_complex
+cpp_single_complex: TypeAlias = Incomplete
+cpp_double_complex: TypeAlias = Incomplete
+voidptr: TypeAlias = Any
 
+class __half_raw(TypedDict):
+    x: int
 
 class ParamHolder:
+    ptr: int
 
-    def __init__(self, kernel_args: Sequence[Any]) -> None:
-        ...
-
-    def __dealloc__(self) -> None:
-        ...
-cpp_single_complex = cpp_complex.complex
-cpp_double_complex = cpp_complex.complex
\ No newline at end of file
+    def __init__(self, kernel_args: Sequence[Any]) -> None: ...
+    def __dealloc__(self) -> None: ...
diff --git a/cuda_core/cuda/core/_kernel_arg_handler.pyx b/cuda_core/cuda/core/_kernel_arg_handler.pyx
index 9fa5d47e336..c36002b1d2d 100644
--- a/cuda_core/cuda/core/_kernel_arg_handler.pyx
+++ b/cuda_core/cuda/core/_kernel_arg_handler.pyx
@@ -17,6 +17,7 @@ from typing import Sequence, Any
 import numpy
 
 from cuda.core._memory import Buffer
+from cuda.core._memory._buffer cimport Buffer as cyBuffer, Buffer_check_open
 from cuda.core._tensor_map import TensorMapDescriptor as _TensorMapDescriptor_py
 from cuda.core._tensor_map cimport TensorMapDescriptor
 from cuda.core.graph._graph_definition cimport GraphCondition
@@ -282,6 +283,7 @@ cdef class ParamHolder:
         for i, arg in enumerate(kernel_args):
             arg_type = type(arg)
             if arg_type is Buffer:
+                Buffer_check_open(<cyBuffer>arg)
                 # we need the address of where the actual buffer address is stored
                 if type(arg.handle) is int:
                     # see note below on handling int arguments
@@ -327,6 +329,7 @@ cdef class ParamHolder:
                     continue
                 # If no exact types are found, fallback to slower `isinstance` check
                 elif isinstance(arg, Buffer):
+                    Buffer_check_open(<cyBuffer>arg)
                     if isinstance(arg.handle, int):
                         prepare_arg[intptr_t](self.data, self.data_addresses, arg.handle, i)
                         continue
diff --git a/cuda_core/cuda/core/_launch_config.pxd b/cuda_core/cuda/core/_launch_config.pxd
index 112007b9cfd..892a73f8efc 100644
--- a/cuda_core/cuda/core/_launch_config.pxd
+++ b/cuda_core/cuda/core/_launch_config.pxd
@@ -15,6 +15,7 @@ cdef class LaunchConfig:
         public tuple block
         public int shmem_size
         public bint is_cooperative
+        public bint programmatic_stream_serialization
 
         vector[cydriver.CUlaunchAttribute] _attrs
         object __weakref__
diff --git a/cuda_core/cuda/core/_launch_config.pyi b/cuda_core/cuda/core/_launch_config.pyi
index eac16c1878f..269fcff416e 100644
--- a/cuda_core/cuda/core/_launch_config.pyi
+++ b/cuda_core/cuda/core/_launch_config.pyi
@@ -1,9 +1,9 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_launch_config.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_launch_config.pyx
 
 from typing import Any
 
+_LAUNCH_CONFIG_ATTRS = ('grid', 'cluster', 'block', 'shmem_size', 'is_cooperative', 'programmatic_stream_serialization')
+__all__ = ['LaunchConfig']
 
 class LaunchConfig:
     """Customizable launch options.
@@ -18,15 +18,15 @@ class LaunchConfig:
 
     Attributes
     ----------
-    grid : Union[tuple, int]
+    grid : tuple | int
         Collection of threads that will execute a kernel function. When cluster
         is not specified, this represents the number of blocks, otherwise
         this represents the number of clusters.
-    cluster : Union[tuple, int]
+    cluster : tuple | int
         Group of blocks (Thread Block Cluster) that will execute on the same
         GPU Processing Cluster (GPC). Blocks within a cluster have access to
         distributed shared memory and can be explicitly synchronized.
-    block : Union[tuple, int]
+    block : tuple | int
         Group of threads (Thread Block) that will execute on the same
         streaming multiprocessor (SM). Threads within a thread blocks have
         access to shared memory and can be explicitly synchronized.
@@ -35,37 +35,41 @@ class LaunchConfig:
         (Default to size 0)
     is_cooperative : bool, optional
         Whether this config can be used to launch a cooperative kernel.
+    programmatic_stream_serialization : bool, optional
+        Whether to allow programmatic stream serialization (PDL). When True,
+        the kernel may overlap with a previous kernel in the same stream that
+        signals completion via programmatic means.
     """
+    grid: tuple[Any, ...]
+    cluster: tuple[Any, ...]
+    block: tuple[Any, ...]
+    shmem_size: int
+    is_cooperative: bool
+    programmatic_stream_serialization: bool
 
-    def __init__(self, grid: int | tuple[int, ...] | None=None, cluster: int | tuple[int, ...] | None=None, block: int | tuple[int, ...] | None=None, shmem_size: int | None=None, is_cooperative: bool=False) -> None:
+    def __init__(self, grid: int | tuple[int, ...] | None=None, cluster: int | tuple[int, ...] | None=None, block: int | tuple[int, ...] | None=None, shmem_size: int | None=None, is_cooperative: bool=False, programmatic_stream_serialization: bool=False) -> None:
         """Initialize LaunchConfig with validation.
 
         Parameters
         ----------
-        grid : Union[tuple, int], optional
+        grid : tuple | int, optional
             Grid dimensions (number of blocks or clusters if cluster is specified)
-        cluster : Union[tuple, int], optional
+        cluster : tuple | int, optional
             Cluster dimensions (Thread Block Cluster)
-        block : Union[tuple, int], optional
+        block : tuple | int, optional
             Block dimensions (threads per block)
         shmem_size : int, optional
             Dynamic shared memory size in bytes (default: 0)
         is_cooperative : bool, optional
             Whether to launch as cooperative kernel (default: False)
+        programmatic_stream_serialization : bool, optional
+            Whether to allow programmatic stream serialization / PDL (default: False)
         """
-
-    def _identity(self) -> tuple[Any, ...]:
-        ...
-
+    def _identity(self) -> tuple[Any, ...]: ...
     def __repr__(self) -> str:
         """Return string representation of LaunchConfig."""
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-_LAUNCH_CONFIG_ATTRS = ('grid', 'cluster', 'block', 'shmem_size', 'is_cooperative')
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
 
 def _to_native_launch_config(config: LaunchConfig) -> object:
     """Convert LaunchConfig to native driver CUlaunchConfig.
@@ -79,4 +83,4 @@ def _to_native_launch_config(config: LaunchConfig) -> object:
     -------
     driver.CUlaunchConfig
         Native CUDA driver launch configuration
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/_launch_config.pyx b/cuda_core/cuda/core/_launch_config.pyx
index a92ecf1f9e3..adbf9a16c5d 100644
--- a/cuda_core/cuda/core/_launch_config.pyx
+++ b/cuda_core/cuda/core/_launch_config.pyx
@@ -13,7 +13,16 @@ from cuda.core._utils.cuda_utils import (
     driver,
 )
 
-_LAUNCH_CONFIG_ATTRS = ('grid', 'cluster', 'block', 'shmem_size', 'is_cooperative')
+_LAUNCH_CONFIG_ATTRS = (
+    'grid',
+    'cluster',
+    'block',
+    'shmem_size',
+    'is_cooperative',
+    'programmatic_stream_serialization',
+)
+
+__all__ = ['LaunchConfig']
 
 
 cdef class LaunchConfig:
@@ -29,15 +38,15 @@ cdef class LaunchConfig:
 
     Attributes
     ----------
-    grid : Union[tuple, int]
+    grid : tuple | int
         Collection of threads that will execute a kernel function. When cluster
         is not specified, this represents the number of blocks, otherwise
         this represents the number of clusters.
-    cluster : Union[tuple, int]
+    cluster : tuple | int
         Group of blocks (Thread Block Cluster) that will execute on the same
         GPU Processing Cluster (GPC). Blocks within a cluster have access to
         distributed shared memory and can be explicitly synchronized.
-    block : Union[tuple, int]
+    block : tuple | int
         Group of threads (Thread Block) that will execute on the same
         streaming multiprocessor (SM). Threads within a thread blocks have
         access to shared memory and can be explicitly synchronized.
@@ -46,6 +55,10 @@ cdef class LaunchConfig:
         (Default to size 0)
     is_cooperative : bool, optional
         Whether this config can be used to launch a cooperative kernel.
+    programmatic_stream_serialization : bool, optional
+        Whether to allow programmatic stream serialization (PDL). When True,
+        the kernel may overlap with a previous kernel in the same stream that
+        signals completion via programmatic means.
     """
 
     # TODO: expand LaunchConfig to include other attributes
@@ -58,21 +71,24 @@ cdef class LaunchConfig:
         block: int | tuple[int, ...] | None = None,
         shmem_size: int | None = None,
         is_cooperative: bool = False,
+        programmatic_stream_serialization: bool = False,
     ) -> None:
         """Initialize LaunchConfig with validation.
 
         Parameters
         ----------
-        grid : Union[tuple, int], optional
+        grid : tuple | int, optional
             Grid dimensions (number of blocks or clusters if cluster is specified)
-        cluster : Union[tuple, int], optional
+        cluster : tuple | int, optional
             Cluster dimensions (Thread Block Cluster)
-        block : Union[tuple, int], optional
+        block : tuple | int, optional
             Block dimensions (threads per block)
         shmem_size : int, optional
             Dynamic shared memory size in bytes (default: 0)
         is_cooperative : bool, optional
             Whether to launch as cooperative kernel (default: False)
+        programmatic_stream_serialization : bool, optional
+            Whether to allow programmatic stream serialization / PDL (default: False)
         """
         # Convert and validate grid and block dimensions
         self.grid = cast_to_3_tuple("LaunchConfig.grid", grid)
@@ -99,6 +115,7 @@ cdef class LaunchConfig:
             self.shmem_size = shmem_size
 
         self.is_cooperative = is_cooperative
+        self.programmatic_stream_serialization = programmatic_stream_serialization
 
         if self.is_cooperative and not Device().properties.cooperative_launch:
             raise CUDAError("cooperative kernels are not supported on this device")
@@ -147,6 +164,11 @@ cdef class LaunchConfig:
             attr.value.cooperative = 1
             self._attrs.push_back(attr)
 
+        if self.programmatic_stream_serialization:
+            attr.id = cydriver.CUlaunchAttributeID.CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION
+            attr.value.programmaticStreamSerializationAllowed = 1
+            self._attrs.push_back(attr)
+
         drv_cfg.numAttrs = self._attrs.size()
         drv_cfg.attrs = self._attrs.data()
 
@@ -202,6 +224,12 @@ cpdef object _to_native_launch_config(LaunchConfig config):
         attr.value.cooperative = 1
         attrs.append(attr)
 
+    if config.programmatic_stream_serialization:
+        attr = driver.CUlaunchAttribute()
+        attr.id = driver.CUlaunchAttributeID.CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION
+        attr.value.programmaticStreamSerializationAllowed = 1
+        attrs.append(attr)
+
     drv_cfg.numAttrs = len(attrs)
     drv_cfg.attrs = attrs
 
diff --git a/cuda_core/cuda/core/_launcher.pyi b/cuda_core/cuda/core/_launcher.pyi
index a292c3eec95..c74b30c4f10 100644
--- a/cuda_core/cuda/core/_launcher.pyi
+++ b/cuda_core/cuda/core/_launcher.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_launcher.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_launcher.pyx
 
 from cuda.core._launch_config import LaunchConfig
 from cuda.core._module import Kernel
@@ -8,6 +6,7 @@ from cuda.core._stream import Stream
 from cuda.core.graph import GraphBuilder
 from cuda.core.typing import IsStreamType
 
+__all__ = ['launch']
 
 def launch(stream: Stream | GraphBuilder | IsStreamType, config: LaunchConfig, kernel: Kernel, *kernel_args) -> None:
     """Launches a :obj:`~_module.Kernel`
@@ -27,4 +26,4 @@ def launch(stream: Stream | GraphBuilder | IsStreamType, config: LaunchConfig, k
         Variable length argument list that is provided to the
         launching kernel.
 
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/_launcher.pyx b/cuda_core/cuda/core/_launcher.pyx
index d5ddaff4d56..036189790e0 100644
--- a/cuda_core/cuda/core/_launcher.pyx
+++ b/cuda_core/cuda/core/_launcher.pyx
@@ -24,6 +24,8 @@ if TYPE_CHECKING:
     from cuda.core.graph import GraphBuilder
     from cuda.core.typing import IsStreamType
 
+__all__ = ['launch']
+
 
 def launch(
     stream: Stream | GraphBuilder | IsStreamType,
diff --git a/cuda_core/cuda/core/_layout.pyi b/cuda_core/cuda/core/_layout.pyi
index 1562a2bf76f..718aea0fcbc 100644
--- a/cuda_core/cuda/core/_layout.pyi
+++ b/cuda_core/cuda/core/_layout.pyi
@@ -1,14 +1,20 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_layout.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_layout.pyx
 
-from __future__ import annotations
+from typing import TypedDict
 
-import cython
-from libcpp import vector
+from _typeshed import Incomplete
+from typing_extensions import TypeAlias
 
-OrderFlag = int
-Property = int
+OrderFlag: TypeAlias = int
+Property: TypeAlias = int
+extent_t: TypeAlias = int
+stride_t: TypeAlias = int
+axis_t: TypeAlias = int
+axes_mask_t: TypeAlias = int
+property_mask_t: TypeAlias = int
+extents_strides_t: TypeAlias = Incomplete
+axis_vec_t: TypeAlias = Incomplete
 
-@cython.final
 class _StridedLayout:
     """
     A class describing the layout of a multi-dimensional tensor
@@ -39,10 +45,10 @@ class _StridedLayout:
         The offset (as a number of elements, not bytes) of the element at
         index ``(0,) * ndim``. See also :attr:`slice_offset_in_bytes`.
     """
+    itemsize: int
+    slice_offset: stride_t
 
-    def __init__(self: _StridedLayout, shape: tuple[int, ...], strides: tuple[int, ...] | None, itemsize: int, divide_strides: bool=False) -> None:
-        ...
-
+    def __init__(self: _StridedLayout, shape: tuple[int, ...], strides: tuple[int, ...] | None, itemsize: int, divide_strides: bool=False) -> None: ...
     @classmethod
     def dense(cls, shape: tuple[int], itemsize: int, stride_order: str | tuple[int]='C') -> _StridedLayout:
         """
@@ -72,7 +78,6 @@ class _StridedLayout:
             assert _StridedLayout.dense((5, 3, 7), 1, (2, 0, 1)) == _StridedLayout((5, 3, 7), (3, 1, 15), 1)
 
         """
-
     @classmethod
     def dense_like(cls, other: _StridedLayout, stride_order: str | tuple[int]='K') -> _StridedLayout:
         """
@@ -109,13 +114,8 @@ class _StridedLayout:
             assert _StridedLayout.dense_like(layout, "C") == _StridedLayout((7, 5, 3), (15, 3, 1), 1)
             assert _StridedLayout.dense_like(layout, "F") == _StridedLayout((7, 5, 3), (1, 7, 35), 1)
         """
-
-    def __repr__(self: _StridedLayout) -> str:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
+    def __repr__(self: _StridedLayout) -> str: ...
+    def __eq__(self, other: object) -> bool: ...
     @property
     def ndim(self: _StridedLayout) -> int:
         """
@@ -123,7 +123,6 @@ class _StridedLayout:
 
         :type: int
         """
-
     @property
     def shape(self: _StridedLayout) -> tuple[int, ...]:
         """
@@ -131,7 +130,6 @@ class _StridedLayout:
 
         :type: tuple[int]
         """
-
     @property
     def strides(self: _StridedLayout) -> tuple[int, ...] | None:
         """
@@ -141,7 +139,6 @@ class _StridedLayout:
 
         :type: tuple[int] | None
         """
-
     @property
     def strides_in_bytes(self: _StridedLayout) -> tuple[int, ...] | None:
         """
@@ -149,7 +146,6 @@ class _StridedLayout:
 
         :type: tuple[int] | None
         """
-
     @property
     def stride_order(self: _StridedLayout) -> tuple[int, ...]:
         """
@@ -168,7 +164,6 @@ class _StridedLayout:
 
         :type: tuple[int]
         """
-
     @property
     def volume(self: _StridedLayout) -> int:
         """
@@ -176,7 +171,6 @@ class _StridedLayout:
 
         :type: int
         """
-
     @property
     def is_unique(self: _StridedLayout) -> bool:
         """
@@ -196,7 +190,6 @@ class _StridedLayout:
 
         :type: bool
         """
-
     @property
     def is_contiguous_c(self: _StridedLayout) -> bool:
         """
@@ -216,7 +209,6 @@ class _StridedLayout:
 
         :type: bool
         """
-
     @property
     def is_contiguous_f(self: _StridedLayout) -> bool:
         """
@@ -236,7 +228,6 @@ class _StridedLayout:
 
         :type: bool
         """
-
     @property
     def is_contiguous_any(self: _StridedLayout) -> bool:
         """
@@ -275,7 +266,6 @@ class _StridedLayout:
 
         :type: bool
         """
-
     @property
     def is_dense(self: _StridedLayout) -> bool:
         """
@@ -287,7 +277,6 @@ class _StridedLayout:
 
         :type: bool
         """
-
     @property
     def offset_bounds(self: _StridedLayout) -> tuple[int, int]:
         """
@@ -316,7 +305,6 @@ class _StridedLayout:
 
         :type: tuple[int, int]
         """
-
     @property
     def min_offset(self: _StridedLayout) -> int:
         """
@@ -324,7 +312,6 @@ class _StridedLayout:
 
         :type: int
         """
-
     @property
     def max_offset(self: _StridedLayout) -> int:
         """
@@ -332,7 +319,6 @@ class _StridedLayout:
 
         :type: int
         """
-
     @property
     def slice_offset_in_bytes(self: _StridedLayout) -> int:
         """
@@ -345,7 +331,6 @@ class _StridedLayout:
 
         :type: int
         """
-
     def required_size_in_bytes(self: _StridedLayout) -> int:
         """
         The memory allocation size (in bytes) needed so that
@@ -378,13 +363,11 @@ class _StridedLayout:
                 b_view = StridedMemoryView.from_buffer(mem, layout, a_view.dtype)
                 return b_view
         """
-
     def flattened_axis_mask(self: _StridedLayout) -> axes_mask_t:
         """
         A mask describing which axes of this layout are mergeable
         using the :meth:`flattened` method.
         """
-
     def to_dense(self: _StridedLayout, stride_order: object='K') -> _StridedLayout:
         """
         Returns a dense layout with the same shape and itemsize,
@@ -392,7 +375,6 @@ class _StridedLayout:
 
         See :meth:`dense_like` method documentation for details.
         """
-
     def reshaped(self: _StridedLayout, shape: tuple[int]) -> _StridedLayout:
         """
         Returns a layout with the new shape, if the new shape is compatible
@@ -415,13 +397,11 @@ class _StridedLayout:
             assert layout.permuted((2, 0, 1)).reshaped((4, 15,)) == _StridedLayout((4, 15), (1, 4), 1)
             # layout.permuted((2, 0, 1)).reshaped((20, 3)) -> error
         """
-
     def permuted(self: _StridedLayout, axis_order: tuple[int]) -> _StridedLayout:
         """
         Returns a new layout where the shape and strides tuples are permuted
         according to the specified permutation of axes.
         """
-
     def flattened(self: _StridedLayout, start_axis: int=0, end_axis: int=-1, mask: int | None=None) -> _StridedLayout:
         """
         Merges consecutive extents into a single extent (equal to the product of merged extents)
@@ -465,7 +445,6 @@ class _StridedLayout:
             assert layout.flattened(mask=mask) == _StridedLayout((4, 15), (15, 1), 4)
             assert layout2.flattened(mask=mask) == _StridedLayout((4, 15), (1, 4), 4)
         """
-
     def squeezed(self: _StridedLayout) -> _StridedLayout:
         """
         Returns a new layout where all the singleton dimensions (extents equal to 1)
@@ -473,14 +452,12 @@ class _StridedLayout:
         the returned layout will be reduced to a 1-dim layout
         with shape (0,) and strides (0,).
         """
-
     def unsqueezed(self: _StridedLayout, axis: int | tuple[int]) -> _StridedLayout:
         """
         Returns a new layout where the specified axis or axes are added as singleton extents.
         The ``axis`` can be either a single integer in range ``[0, ndim]``
         or a tuple of unique integers in range ``[0, ndim + len(axis) - 1]``.
         """
-
     def broadcast_to(self: _StridedLayout, shape: tuple[int]) -> _StridedLayout:
         """
         Returns a layout with the new shape, if the old shape can be
@@ -494,7 +471,6 @@ class _StridedLayout:
         Strides of the added or modified extents are set to 0, the remaining ones are unchanged.
         If the shapes are not compatible, a ValueError is raised.
         """
-
     def repacked(self: _StridedLayout, itemsize: int, data_ptr: int=0, axis: int=-1, keep_dim: bool=True) -> _StridedLayout:
         """
         Converts the layout to match the specified itemsize.
@@ -546,13 +522,11 @@ class _StridedLayout:
             b = numpy.from_dlpack(complex_view)
             assert b.shape == (5, 3)
         """
-
     def max_compatible_itemsize(self: _StridedLayout, max_itemsize: int=16, data_ptr: int=0, axis: int=-1) -> int:
         """
         Returns the maximum itemsize (but no greater than ``max_itemsize``) that can be used
         with the :meth:`repacked` method for the current layout.
         """
-
     def sliced(self: _StridedLayout, slices: int | slice | tuple[int | slice]) -> _StridedLayout:
         """
         Returns a sliced layout.
@@ -569,13 +543,10 @@ class _StridedLayout:
             any data access.
 
         """
+    def __getitem__(self: _StridedLayout, slices: int | slice | tuple[int | slice]) -> _StridedLayout: ...
 
-    def __getitem__(self: _StridedLayout, slices: int | slice | tuple[int | slice]) -> _StridedLayout:
-        ...
-extent_t = int
-stride_t = int
-axis_t = int
-axes_mask_t = int
-property_mask_t = int
-extents_strides_t = vector.vector
-axis_vec_t = vector.vector
\ No newline at end of file
+class BaseLayout(TypedDict):
+    _mem: extents_strides_t
+    shape: extent_t
+    strides: stride_t
+    ndim: int
diff --git a/cuda_core/cuda/core/_linker.pyi b/cuda_core/cuda/core/_linker.pyi
index 42b08313f78..4fed2399f7a 100644
--- a/cuda_core/cuda/core/_linker.pyi
+++ b/cuda_core/cuda/core/_linker.pyi
@@ -1,4 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_linker.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_linker.pyx
 
 """Linking machinery for combining object codes.
 
@@ -6,8 +6,6 @@ This module provides :class:`Linker` for linking one or more
 :class:`~cuda.core.ObjectCode` objects, with :class:`LinkerOptions` for
 configuration.
 """
-from __future__ import annotations
-
 from dataclasses import dataclass
 from typing import Union
 
@@ -15,7 +13,18 @@ import cuda.bindings.driver
 import cuda.bindings.nvjitlink
 from cuda.core._module import ObjectCode
 from cuda.core.typing import CompilerBackendType, ObjectCodeFormatType
+from typing_extensions import TypeAlias
 
+_keep_driver_in_stub: cuda.bindings.driver.CUlinkState
+_keep_nvjitlink_in_stub: cuda.bindings.nvjitlink.nvJitLinkHandle
+const_char_ptr: TypeAlias = bytes
+__all__ = ['Linker', 'LinkerOptions']
+LinkerHandleT = Union['cuda.bindings.nvjitlink.nvJitLinkHandle', 'cuda.bindings.driver.CUlinkState']
+_driver = None
+_inited = False
+_use_nvjitlink_backend = None
+_nvjitlink_input_types = None
+_driver_input_types = None
 
 class Linker:
     """Represent a linking machinery to link one or more object codes into
@@ -31,10 +40,10 @@ class Linker:
     options : :class:`LinkerOptions`, optional
         Options for the linker. If not provided, default options will be used.
     """
-
-    def __init__(self, options: LinkerOptions | None=None, *object_codes: ObjectCode):
-        ...
-
+    def __init__(self, *object_codes: ObjectCode, options: LinkerOptions | None=None): ...
+    @property
+    def is_closed(self) -> bool:
+        """Whether this linker has been closed."""
     def link(self, target_type: ObjectCodeFormatType | str) -> ObjectCode:
         """Link the provided object codes into a single output of the specified target type.
 
@@ -53,7 +62,6 @@ class Linker:
             Ensure that input object codes were compiled with appropriate
             flags for linking (e.g., relocatable device code enabled).
         """
-
     def get_error_log(self) -> str:
         """Get the error log generated by the linker.
 
@@ -62,7 +70,6 @@ class Linker:
         str
             The error log.
         """
-
     def get_info_log(self) -> str:
         """Get the info log generated by the linker.
 
@@ -71,10 +78,8 @@ class Linker:
         str
             The info log.
         """
-
     def close(self) -> None:
         """Destroy this linker."""
-
     @property
     def handle(self) -> LinkerHandleT:
         """Return the underlying handle object.
@@ -88,7 +93,6 @@ class Linker:
             This handle is a Python object. To get the memory address of the underlying C
             handle, call ``int(Linker.handle)``.
         """
-
     @classmethod
     def which_backend(cls) -> CompilerBackendType:
         """Return which linking backend will be used.
@@ -177,6 +181,18 @@ class LinkerOptions:
     no_cache : bool, optional
         Do not cache the intermediate steps of nvJitLink.
         Default: False.
+    numba_debug : bool, optional
+        Non-functional. ``numba_debug`` is an NVVM/NVRTC *compiler* option;
+        neither nvJitLink nor the driver's cuLink API recognizes it, so no
+        linking backend can honor it and the value is ignored.
+        Default: None.
+
+        .. deprecated:: 1.2.0
+            Setting this option emits a :class:`DeprecationWarning`. It has never
+            had an effect on any linking backend and will be removed in
+            ``cuda.core`` 2.0.0. Use
+            :attr:`ProgramOptions.numba_debug` on an NVVM or NVRTC compilation
+            path instead.
     """
     name: str | None = '<default linker>'
     arch: str | None = None
@@ -201,15 +217,9 @@ class LinkerOptions:
     no_cache: bool | None = None
     numba_debug: bool | None = None
 
-    def __post_init__(self) -> None:
-        ...
-
-    def _prepare_nvjitlink_options(self, as_bytes: bool=False) -> list[bytes] | list[str]:
-        ...
-
-    def _prepare_driver_options(self) -> tuple[list[object], list[object]]:
-        ...
-
+    def __post_init__(self) -> None: ...
+    def _prepare_nvjitlink_options(self, as_bytes: bool=False) -> list[bytes] | list[str]: ...
+    def _prepare_driver_options(self) -> tuple[list[object], list[object]]: ...
     def as_bytes(self, backend: str='nvjitlink') -> list[bytes]:
         """Convert linker options to bytes format for the nvjitlink backend.
 
@@ -230,21 +240,8 @@ class LinkerOptions:
         RuntimeError
             If nvJitLink backend is not available.
         """
-_keep_driver_in_stub: 'cuda.bindings.driver.CUlinkState'
-_keep_nvjitlink_in_stub: 'cuda.bindings.nvjitlink.nvJitLinkHandle'
-__all__ = ['Linker', 'LinkerOptions']
-LinkerHandleT = Union['cuda.bindings.nvjitlink.nvJitLinkHandle', 'cuda.bindings.driver.CUlinkState']
-_driver = None
-_inited = False
-_use_nvjitlink_backend = None
-_nvjitlink_input_types = None
-_driver_input_types = None
-
-def _nvjitlink_has_version_symbol(nvjitlink) -> bool:
-    ...
 
+def _nvjitlink_has_version_symbol(nvjitlink) -> bool: ...
 def _decide_nvjitlink_or_driver() -> bool:
     """Return True if falling back to the cuLink* driver APIs."""
-
-def _lazy_init() -> None:
-    ...
\ No newline at end of file
+def _lazy_init() -> None: ...
diff --git a/cuda_core/cuda/core/_linker.pyx b/cuda_core/cuda/core/_linker.pyx
index 753fa28b0d3..f104e2d158b 100644
--- a/cuda_core/cuda/core/_linker.pyx
+++ b/cuda_core/cuda/core/_linker.pyx
@@ -29,6 +29,7 @@ from dataclasses import dataclass
 from typing import TYPE_CHECKING, Union
 from warnings import warn
 
+from cuda.pathfinder import DynamicLibNotFoundError
 from cuda.pathfinder._optional_cuda_import import _optional_cuda_import
 from cuda.core._device import Device
 from cuda.core._module import ObjectCode
@@ -62,6 +63,13 @@ LinkerHandleT = Union["cuda.bindings.nvjitlink.nvJitLinkHandle", "cuda.bindings.
 # Principal class
 # =============================================================================
 
+
+cdef inline int Linker_check_open(Linker self) except -1:
+    if self.is_closed:
+        raise RuntimeError("Linker has been closed")
+    return 0
+
+
 cdef class Linker:
     """Represent a linking machinery to link one or more object codes into
     :class:`~cuda.core.ObjectCode`.
@@ -80,6 +88,13 @@ cdef class Linker:
     def __init__(self, *object_codes: ObjectCode, options: LinkerOptions | None = None):
         Linker_init(self, object_codes, options)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this linker has been closed."""
+        if self._use_nvjitlink:
+            return self._nvjitlink_handle.get() == NULL
+        return self._culink_handle.get() == NULL
+
     def link(self, target_type: ObjectCodeFormatType | str) -> ObjectCode:
         """Link the provided object codes into a single output of the specified target type.
 
@@ -98,6 +113,7 @@ cdef class Linker:
             Ensure that input object codes were compiled with appropriate
             flags for linking (e.g., relocatable device code enabled).
         """
+        Linker_check_open(self)
         return Linker_link(self, str(target_type))
 
     def get_error_log(self) -> str:
@@ -111,6 +127,7 @@ cdef class Linker:
         # After link(), the decoded log is cached here.
         if self._error_log is not None:
             return self._error_log
+        Linker_check_open(self)
         cdef cynvjitlink.nvJitLinkHandle c_h
         cdef size_t c_log_size = 0
         cdef char* c_log_ptr
@@ -137,6 +154,7 @@ cdef class Linker:
         # After link(), the decoded log is cached here.
         if self._info_log is not None:
             return self._info_log
+        Linker_check_open(self)
         cdef cynvjitlink.nvJitLinkHandle c_h
         cdef size_t c_log_size = 0
         cdef char* c_log_ptr
@@ -282,6 +300,18 @@ class LinkerOptions:
     no_cache : bool, optional
         Do not cache the intermediate steps of nvJitLink.
         Default: False.
+    numba_debug : bool, optional
+        Non-functional. ``numba_debug`` is an NVVM/NVRTC *compiler* option;
+        neither nvJitLink nor the driver's cuLink API recognizes it, so no
+        linking backend can honor it and the value is ignored.
+        Default: None.
+
+        .. deprecated:: 1.2.0
+            Setting this option emits a :class:`DeprecationWarning`. It has never
+            had an effect on any linking backend and will be removed in
+            ``cuda.core`` 2.0.0. Use
+            :attr:`ProgramOptions.numba_debug` on an NVVM or NVRTC compilation
+            path instead.
     """
 
     name: str | None = "<default linker>"
@@ -310,6 +340,21 @@ class LinkerOptions:
     def __post_init__(self) -> None:
         _lazy_init()
         self._name = self.name.encode()
+        # No linking backend reads ``numba_debug``, so warn where the value is
+        # supplied rather than in the option builders -- the user learns once,
+        # at the call site that set it, instead of once per link. The gate is
+        # ``is not None`` (unlike the ignore-warning on the PTX compile path):
+        # it is the *field* that is going away, so any explicit value earns the
+        # notice, including ``False``.
+        if self.numba_debug is not None:
+            warn(
+                "numba_debug is not supported by any linking backend and is ignored. "
+                "LinkerOptions.numba_debug is deprecated and will be removed in "
+                "cuda.core 2.0.0; use ProgramOptions.numba_debug on an NVVM or NVRTC "
+                "compilation path instead.",
+                DeprecationWarning,
+                stacklevel=3,
+            )
 
     def _prepare_nvjitlink_options(self, as_bytes: bool = False) -> list[bytes] | list[str]:
         options = []
@@ -544,11 +589,10 @@ cdef inline void Linker_add_code_object(Linker self, object object_code) except
     cdef cydriver.CUjitInputType c_drv_input_type
     cdef const char* c_data_ptr
     cdef size_t c_data_size
-    cdef const char* c_name_ptr
     cdef const char* c_file_ptr
 
     name_bytes = f"{object_code.name}".encode()
-    c_name_ptr = <const char*>name_bytes
+    cdef const char* c_name_ptr = <const char*>name_bytes
 
     input_types = _nvjitlink_input_types if self._use_nvjitlink else _driver_input_types
     py_input_type = input_types.get(object_code.code_type)
@@ -684,26 +728,30 @@ def _decide_nvjitlink_or_driver() -> bool:
         " For best results, consider upgrading to a recent version of"
     )
 
-    nvjitlink_module = _optional_cuda_import(
-        "cuda.bindings.nvjitlink",
-        probe_function=lambda module: module.version(),  # probe triggers nvJitLink runtime load
-    )
+    nvjitlink_module = _optional_cuda_import("cuda.bindings.nvjitlink")
     if nvjitlink_module is None:
         warn_txt = f"cuda.bindings.nvjitlink is not available, therefore {warn_txt_common} cuda-bindings."
     else:
         from cuda.bindings._internal import nvjitlink
 
-        if _nvjitlink_has_version_symbol(nvjitlink):
-            _use_nvjitlink_backend = True
-            return False  # Use nvjitlink
-        warn_txt = (
-            f"{'nvJitLink*.dll' if sys.platform == 'win32' else 'libnvJitLink.so*'} is too old (<12.3)."
-            f" Therefore cuda.bindings.nvjitlink is not usable and {warn_txt_common} nvJitLink."
-        )
+        try:
+            has_version_symbol = _nvjitlink_has_version_symbol(nvjitlink)
+        except DynamicLibNotFoundError:
+            warn_txt = (
+                f"cuda.bindings.nvjitlink is not available, therefore {warn_txt_common} cuda-bindings."
+            )
+        else:
+            if has_version_symbol:
+                _use_nvjitlink_backend = True
+                return False  # Use nvjitlink
+            warn_txt = (
+                f"{'nvJitLink*.dll' if sys.platform == 'win32' else 'libnvJitLink.so*'} is too old (<12.3)."
+                f" Therefore cuda.bindings.nvjitlink is not usable and {warn_txt_common} nvJitLink."
+            )
 
     warn(warn_txt, stacklevel=2, category=RuntimeWarning)
-    _use_nvjitlink_backend = False
     _driver = driver
+    _use_nvjitlink_backend = False
     return True
 
 
diff --git a/cuda_core/cuda/core/_memory/__init__.py b/cuda_core/cuda/core/_memory/__init__.py
index bf40a643f8c..d35ee814449 100644
--- a/cuda_core/cuda/core/_memory/__init__.py
+++ b/cuda_core/cuda/core/_memory/__init__.py
@@ -1,13 +1,34 @@
-# SPDX-FileCopyrightText: Copyright (c) 2024-2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # SPDX-License-Identifier: Apache-2.0
 
 from ._buffer import *
+from ._buffer import __all__ as _buffer_all
 from ._device_memory_resource import *
+from ._device_memory_resource import __all__ as _device_memory_resource_all
 from ._graph_memory_resource import *
+from ._graph_memory_resource import __all__ as _graph_memory_resource_all
 from ._ipc import *
+from ._ipc import __all__ as _ipc_all
 from ._legacy import *
-from ._managed_buffer import ManagedBuffer
+from ._legacy import __all__ as _legacy_all
+from ._managed_buffer import *
+from ._managed_buffer import __all__ as _managed_buffer_all
 from ._managed_memory_resource import *
+from ._managed_memory_resource import __all__ as _managed_memory_resource_all
 from ._pinned_memory_resource import *
+from ._pinned_memory_resource import __all__ as _pinned_memory_resource_all
 from ._virtual_memory_resource import *
+from ._virtual_memory_resource import __all__ as _virtual_memory_resource_all
+
+__all__ = [
+    *_buffer_all,
+    *_device_memory_resource_all,
+    *_graph_memory_resource_all,
+    *_ipc_all,
+    *_legacy_all,
+    *_managed_buffer_all,
+    *_managed_memory_resource_all,
+    *_pinned_memory_resource_all,
+    *_virtual_memory_resource_all,
+]
diff --git a/cuda_core/cuda/core/_memory/_buffer.pxd b/cuda_core/cuda/core/_memory/_buffer.pxd
index b552e69554d..75d94c91d58 100644
--- a/cuda_core/cuda/core/_memory/_buffer.pxd
+++ b/cuda_core/cuda/core/_memory/_buffer.pxd
@@ -44,3 +44,15 @@ cdef Buffer Buffer_from_deviceptr_handle(
     object ipc_descriptor = *,
     type cls = *,
 )
+
+
+# Shared argument coercion for the batched free functions (copy_batch,
+# prefetch_batch, discard_batch, discard_prefetch_batch). `single_hint`
+# names the per-buffer API to use instead when a bare Buffer is passed.
+cdef tuple Buffer_coerce_batch(object buffers, str what, str single_hint)
+
+
+cdef inline int Buffer_check_open(Buffer self) except -1:
+    if not self._h_ptr:
+        raise RuntimeError("Buffer has been closed")
+    return 0
diff --git a/cuda_core/cuda/core/_memory/_buffer.pyi b/cuda_core/cuda/core/_memory/_buffer.pyi
index 1d824cf6fc0..756b8661488 100644
--- a/cuda_core/cuda/core/_memory/_buffer.pyi
+++ b/cuda_core/cuda/core/_memory/_buffer.pyi
@@ -1,8 +1,8 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_buffer.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_buffer.pyx
 
-from __future__ import annotations
+from typing import TypedDict
 
-import cython
+from cuda.core._memory._copy_enums import CopyOptions
 from cuda.core._memory._device_memory_resource import DeviceMemoryResource
 from cuda.core._memory._ipc import IPCBufferDescriptor
 from cuda.core._memory._pinned_memory_resource import PinnedMemoryResource
@@ -11,6 +11,7 @@ from cuda.core._utils.pycompat import BufferProtocol
 from cuda.core.graph import GraphBuilder
 from cuda.core.typing import DevicePointerType
 
+__all__ = ['Buffer', 'MemoryResource']
 
 class Buffer:
     """Represent a handle to allocated memory.
@@ -28,34 +29,28 @@ class Buffer:
     by calling :meth:`from_ipc_descriptor` and therefore performs an IPC
     import. Do not unpickle buffers from untrusted sources.
     """
+    _size: int
 
-    def __cinit__(self) -> None:
-        ...
-
-    def _clear(self) -> None:
-        ...
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def _clear(self) -> None: ...
+    def __init__(self, *args, **kwargs) -> None: ...
     @classmethod
-    def _init(cls, ptr: DevicePointerType, size: int, mr: MemoryResource | None=None, ipc_descriptor: IPCBufferDescriptor | None=None, owner: object | None=None) -> Buffer:
+    def _init(cls, ptr: DevicePointerType, size: int, mr: MemoryResource | None=None, ipc_descriptor: IPCBufferDescriptor | None=None, owner: object | None=None, *, stream: Stream | GraphBuilder | None=None) -> Buffer:
         """Create a Buffer from a raw pointer.
 
         When ``mr`` is provided, the buffer takes ownership: ``mr.deallocate()``
         is called when the buffer is closed or garbage collected.  When ``owner``
         is provided, the owner is kept alive but no deallocation is performed.
+        When ``mr`` is provided, a deallocation stream is recorded at creation
+        (``stream`` if given, otherwise ``default_stream()``). Recording a
+        default-stream token requires a CUDA context to be current. Host-only
+        resources (``mr.is_device_accessible`` is ``False``) record no stream
+        and need no context.
         """
-
     @staticmethod
-    def _reduce_helper(mr, ipc_descriptor):
-        ...
-
-    def __reduce__(self) -> tuple[object, ...]:
-        ...
-
+    def _reduce_helper(mr, ipc_descriptor): ...
+    def __reduce__(self) -> tuple[object, ...]: ...
     @staticmethod
-    def from_handle(ptr: DevicePointerType, size: int, mr: MemoryResource | None=None, owner: object | None=None) -> Buffer:
+    def from_handle(ptr: DevicePointerType, size: int, mr: MemoryResource | None=None, owner: object | None=None, *, stream: Stream | GraphBuilder | None=None) -> Buffer:
         """Create a new :class:`Buffer` object from a pointer.
 
         Parameters
@@ -72,6 +67,15 @@ class Buffer:
             An object holding external allocation that the ``ptr`` points to.
             The reference is kept as long as the buffer is alive.
             The ``owner`` and ``mr`` cannot be specified together.
+        stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`, optional
+            Keyword-only. The stream used to order the buffer's deallocation
+            when ``mr`` owns the pointer. Defaults to ``default_stream()``.
+            Recording a default-stream token requires a CUDA context to be
+            current. Host-only resources (``mr.is_device_accessible`` is
+            ``False``) record no stream and need no context. If the buffer may
+            be freed from a different host thread,
+            pass a stream other than the per-thread default stream, which
+            refers to a different stream on each thread.
 
         Note
         ----
@@ -79,7 +83,6 @@ class Buffer:
         non-owning reference.  The pointer will NOT be freed when the
         :class:`Buffer` is closed or garbage collected.
         """
-
     @classmethod
     def from_ipc_descriptor(cls, mr: DeviceMemoryResource | PinnedMemoryResource, ipc_descriptor: IPCBufferDescriptor, *, stream: Stream) -> Buffer:
         """Import a buffer that was exported from another process.
@@ -100,12 +103,9 @@ class Buffer:
         and must be treated as untrusted input unless the peer is known to be
         cooperating.
         """
-
     @property
-    @cython.critical_section
     def ipc_descriptor(self) -> IPCBufferDescriptor:
         """Descriptor for sharing this buffer with other processes."""
-
     def close(self, stream: Stream | GraphBuilder | None=None) -> None:
         """Deallocate this buffer asynchronously on the given stream.
 
@@ -117,15 +117,44 @@ class Buffer:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`, optional
             The stream object to use for asynchronous deallocation. If None,
             the deallocation stream stored in the handle is used.
+
+        See Also
+        --------
+        set_deallocation_stream
+            Change the deallocation stream without closing the buffer.
         """
+    def set_deallocation_stream(self, stream: Stream | GraphBuilder) -> None:
+        """Change the stream that orders this buffer's eventual deallocation.
 
-    def __enter__(self):
-        ...
+        The buffer remains open and usable. A later :meth:`close` without a
+        stream, garbage collection, or release of the final retained device
+        pointer handle uses the replacement stream.
 
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        ...
+        This method does not synchronize streams or establish dependencies.
+        The caller must ensure that allocation and all accesses are ordered
+        before the deallocation on ``stream``.
 
-    def copy_to(self, dst: Buffer | None=None, *, stream: Stream | GraphBuilder) -> Buffer:
+        Parameters
+        ----------
+        stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
+            The stream to use for eventual asynchronous deallocation.
+
+        Raises
+        ------
+        RuntimeError
+            If the buffer is already closed, or if a default-stream token
+            cannot be bound because no CUDA context is current.
+        TypeError
+            If ``stream`` is ``None`` or is not an accepted stream object.
+
+        Notes
+        -----
+        Synchronizing concurrent mutation and destruction of the same buffer
+        is the caller's responsibility.
+        """
+    def __enter__(self): ...
+    def __exit__(self, exc_type, exc_val, exc_tb): ...
+    def copy_to(self, dst: Buffer | None=None, *, stream: Stream | GraphBuilder, options: CopyOptions | None=None) -> Buffer:
         """Copy from this buffer to the dst buffer asynchronously on the given stream.
 
         Copies the data from this buffer to the provided dst buffer.
@@ -140,10 +169,31 @@ class Buffer:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
             Keyword argument specifying the stream for the
             asynchronous copy
+        options : :class:`~utils.CopyOptions`, optional
+            Transfer hints (source access order, location hints, overlap mode).
+            Honored when cuda.bindings and the driver are both CUDA 13.2 or
+            newer. Not accepted with ``LEGACY_DEFAULT_STREAM``; use
+            ``PER_THREAD_DEFAULT_STREAM`` instead. Not accepted with a
+            capturing stream either, since a graph cannot represent these
+            attributes; use :meth:`graph.GraphNode.memcpy` for a plain,
+            non-attributed copy node, or pass ``options=None``. On an older
+            cuda.bindings/driver, ``src_access_order`` values of ``STREAM``
+            and ``ANY`` are silently ignored; ``DURING_API_CALL`` raises
+            instead of silently downgrading its guarantee.
 
-        """
+        Raises
+        ------
+        TypeError
+            If ``options`` is not a :class:`~utils.CopyOptions` instance, or
+            if ``options`` is given together with ``LEGACY_DEFAULT_STREAM``
+            or a stream currently in graph capture mode.
+        RuntimeError
+            If ``options.src_access_order`` is ``DURING_API_CALL`` and
+            cuda.bindings or the driver is older than CUDA 13.2: falling
+            back to a plain copy cannot honor that guarantee.
 
-    def copy_from(self, src: Buffer, *, stream: Stream | GraphBuilder) -> None:
+        """
+    def copy_from(self, src: Buffer, *, stream: Stream | GraphBuilder, options: CopyOptions | None=None) -> None:
         """Copy from the src buffer to this buffer asynchronously on the given stream.
 
         Parameters
@@ -153,9 +203,29 @@ class Buffer:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
             Keyword argument specifying the stream for the
             asynchronous copy
+        options : :class:`~utils.CopyOptions`, optional
+            Transfer hints (source access order, location hints, overlap mode).
+            Honored when cuda.bindings and the driver are both CUDA 13.2 or
+            newer. Not accepted with ``LEGACY_DEFAULT_STREAM``; use
+            ``PER_THREAD_DEFAULT_STREAM`` instead. Not accepted with a
+            capturing stream either, since a graph cannot represent these
+            attributes; use :meth:`graph.GraphNode.memcpy` for a plain,
+            non-attributed copy node, or pass ``options=None``. On an older
+            cuda.bindings/driver, ``src_access_order`` values of ``STREAM``
+            and ``ANY`` are silently ignored; ``DURING_API_CALL`` raises
+            instead of silently downgrading its guarantee.
 
+        Raises
+        ------
+        TypeError
+            If ``options`` is not a :class:`~utils.CopyOptions` instance, or
+            if ``options`` is given together with ``LEGACY_DEFAULT_STREAM``
+            or a stream currently in graph capture mode.
+        RuntimeError
+            If ``options.src_access_order`` is ``DURING_API_CALL`` and
+            cuda.bindings or the driver is older than CUDA 13.2: falling
+            back to a plain copy cannot honor that guarantee.
         """
-
     def fill(self, value: int | BufferProtocol, *, stream: Stream | GraphBuilder) -> None:
         """Fill this buffer with a repeating byte pattern.
 
@@ -178,23 +248,13 @@ class Buffer:
             If int value is outside [0, 256).
 
         """
-
-    def __dlpack__(self, *, stream: int | None=None, max_version: tuple[int, int] | None=None, dl_device: tuple[int, int] | None=None, copy: bool | None=None) -> object:
-        ...
-
-    def __dlpack_device__(self) -> tuple[int, int]:
-        ...
-
-    def __buffer__(self, flags: int, /) -> memoryview:
-        ...
-
-    def __release_buffer__(self, buffer: memoryview, /) -> None:
-        ...
-
+    def __dlpack__(self, *, stream: int | None=None, max_version: tuple[int, int] | None=None, dl_device: tuple[int, int] | None=None, copy: bool | None=None) -> object: ...
+    def __dlpack_device__(self) -> tuple[int, int]: ...
+    def __buffer__(self, flags: int, /) -> memoryview: ...
+    def __release_buffer__(self, buffer: memoryview, /) -> None: ...
     @property
     def device_id(self) -> int:
-        """Return the device ordinal of this buffer."""
-
+        """Return the device ordinal of this buffer, or -1 for memory not bound to a device."""
     @property
     def handle(self) -> int:
         """Return the buffer handle object.
@@ -204,40 +264,30 @@ class Buffer:
             This handle is a Python object. To get the memory address of the underlying C
             handle, call ``int(Buffer.handle)``.
         """
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
-    def __repr__(self) -> str:
-        ...
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this buffer has been closed."""
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
+    def __repr__(self) -> str: ...
     @property
     def is_device_accessible(self) -> bool:
         """Return True if this buffer can be accessed by the GPU, otherwise False."""
-
     @property
     def is_host_accessible(self) -> bool:
         """Return True if this buffer can be accessed by the CPU, otherwise False."""
-
     @property
     def is_managed(self) -> bool:
         """Return True if this buffer is CUDA managed (unified) memory, otherwise False."""
-
     @property
     def is_mapped(self) -> bool:
         """Return True if this buffer is mapped into the process via IPC."""
-
     @property
     def memory_resource(self) -> MemoryResource:
         """Return the memory resource associated with this buffer."""
-
     @property
     def size(self) -> int:
         """Return the memory size of this buffer."""
-
     @property
     def owner(self) -> object:
         """Return the object holding external allocation."""
@@ -253,7 +303,6 @@ class MemoryResource:
     buffer properties are retrieved simply by looking up the underlying memory
     resource's respective property.)
     """
-
     def allocate(self, size: int, *, stream: Stream | GraphBuilder) -> Buffer:
         """Allocate a buffer of the requested size.
 
@@ -264,7 +313,12 @@ class MemoryResource:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
             Keyword-only. The stream on which to perform the allocation
             asynchronously. Must be passed explicitly; pass
-            ``device.default_stream`` to use the default stream.
+            ``device.default_stream`` to use the default stream. For subclasses
+            that support stream-ordered deallocation, this stream also orders
+            the buffer's eventual deallocation, so if the buffer may be freed
+            from a different host thread, prefer a stream other than the
+            per-thread default stream, which refers to a different stream on
+            each thread.
 
         Returns
         -------
@@ -272,7 +326,6 @@ class MemoryResource:
             The allocated buffer object, which can be used for device or host operations
             depending on the resource's properties.
         """
-
     def deallocate(self, ptr: DevicePointerType, size: int, *, stream: Stream | GraphBuilder) -> None:
         """Deallocate a buffer previously allocated by this resource.
 
@@ -287,20 +340,21 @@ class MemoryResource:
             asynchronously. Must be passed explicitly; pass
             ``device.default_stream`` to use the default stream.
         """
-
     @property
     def is_device_accessible(self) -> bool:
         """Whether buffers allocated by this resource are device-accessible."""
-
     @property
     def is_host_accessible(self) -> bool:
         """Whether buffers allocated by this resource are host-accessible."""
-
     @property
     def is_managed(self) -> bool:
         """Whether buffers allocated by this resource are CUDA managed (unified) memory."""
-
     @property
     def device_id(self) -> int:
         """Device ID associated with this memory resource, or -1 if not applicable."""
-__all__ = ['Buffer', 'MemoryResource']
\ No newline at end of file
+
+class _MemAttrs(TypedDict):
+    device_id: int
+    is_device_accessible: bool
+    is_host_accessible: bool
+    is_managed: bool
diff --git a/cuda_core/cuda/core/_memory/_buffer.pyx b/cuda_core/cuda/core/_memory/_buffer.pyx
index 97ef892547d..52539b8c314 100644
--- a/cuda_core/cuda/core/_memory/_buffer.pyx
+++ b/cuda_core/cuda/core/_memory/_buffer.pyx
@@ -16,21 +16,31 @@ from cuda.core._memory cimport _ipc
 from cuda.core._resource_handles cimport (
     DevicePtrHandle,
     StreamHandle,
+    ContextHandle,
     deviceptr_create_with_owner,
     deviceptr_create_with_mr,
     register_mr_dealloc_callback,
     as_intptr,
     as_cu,
+    get_current_context,
     set_deallocation_stream,
 )
 from cuda.core.typing import DevicePointerType
 
-from cuda.core._stream cimport Stream, Stream_accept, default_stream
+from cuda.core._memory._copy_attributes cimport _with_attributes_available
+from cuda.core._memory._copy_attributes cimport _to_cu_memcpy_attributes  # no-cython-lint
+
+IF CUDA_CORE_BUILD_MAJOR >= 13:
+    from cuda.core._resource_handles cimport memcpy_with_attributes_async
+
+from cuda.core._stream cimport Stream, Stream_accept, Stream_is_legacy_default_token, default_stream
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN, _parse_fill_value
 
 import sys
+from collections.abc import Sequence
 from typing import TYPE_CHECKING
 
+from cuda.core._memory._copy_enums import CopyOptions, _reject_unsupported_during_api_call
 from cuda.core._utils.pycompat import BufferProtocol
 from cuda.core._dlpack import classify_dl_device, make_py_capsule
 from cuda.core._device import Device
@@ -49,23 +59,16 @@ cdef void _mr_dealloc_callback(
     size_t size,
     const StreamHandle& h_stream,
 ) noexcept:
-    """Called by the C++ deleter to deallocate via MemoryResource.deallocate.
-
-    This is the C++ teardown path: there is no Python caller frame from
-    which to obtain a stream. If the device-pointer handle was created
-    without ``set_deallocation_stream`` being called (e.g. buffers minted
-    via ``Buffer.from_handle(ptr, size, mr=mr)`` from DLPack import,
-    third-party adapters, or other foreign sources), ``h_stream`` is
-    empty here. Stream-ordered MR ``deallocate`` overrides reject
-    ``stream=None`` (issue #2001), so without a fallback the destructor
-    would print a warning and leak the allocation. Fall back to the
-    legacy/per-thread default stream so the free still happens; this is
-    the unique exception to the "no implicit default-stream fallback"
-    policy because the teardown has no other source of truth.
-    """
+    """Called by the C++ deleter to deallocate via MemoryResource.deallocate."""
     cdef Stream stream
     try:
-        stream = Stream._from_handle(Stream, h_stream) if h_stream else default_stream()
+        if not h_stream:
+            # No stream was recorded: host-only memory (Buffer._init records
+            # none) or a Buffer released before one was set. The default-stream
+            # token needs no CUDA context to construct.
+            stream = default_stream()
+        else:
+            stream = Stream._from_handle(Stream, h_stream)
         mr.deallocate(int(ptr), size, stream=stream)
     except Exception as exc:
         print(f"Warning: mr.deallocate() failed during Buffer destruction: {exc}",
@@ -74,6 +77,23 @@ cdef void _mr_dealloc_callback(
 register_mr_dealloc_callback(_mr_dealloc_callback)
 
 
+cdef inline void _apply_deallocation_stream(
+        const DevicePtrHandle& h_ptr, const StreamHandle& h_stream) except *:
+    """Record h_stream as the deallocation stream for h_ptr.
+
+    Translates CUDA_ERROR_INVALID_CONTEXT (default-stream token with no current
+    context) into a descriptive RuntimeError instead of a raw CUDAError.
+    """
+    cdef cydriver.CUresult status = set_deallocation_stream(h_ptr, h_stream)
+    if status == cydriver.CUresult.CUDA_ERROR_INVALID_CONTEXT:
+        raise RuntimeError(
+            "Cannot record a default deallocation stream when no CUDA context is "
+            "current. Call Device.set_current() first, or pass stream= with a "
+            "non-default Stream."
+        )
+    HANDLE_RETURN(status)
+
+
 __all__ = ['Buffer', 'MemoryResource']
 
 
@@ -136,11 +156,81 @@ cdef inline int _query_memory_attrs(
 
 cdef inline void _init_memory_attrs(Buffer self):
     """Initialize memory attributes by querying the pointer."""
+    Buffer_check_open(self)
     if not self._mem_attrs_inited.load(memory_order_acquire):
         _query_memory_attrs(self._mem_attrs, as_cu(self._h_ptr))
         self._mem_attrs_inited.store(True, memory_order_release)
 
 
+cdef bint _stream_is_capturing(Stream s):
+    cdef cydriver.CUstreamCaptureStatus cap_status
+    IF CUDA_CORE_BUILD_MAJOR >= 13:
+        HANDLE_RETURN(cydriver.cuStreamGetCaptureInfo(as_cu(s._h_stream), &cap_status,
+                                                     NULL, NULL, NULL, NULL, NULL))
+    ELSE:
+        HANDLE_RETURN(cydriver.cuStreamGetCaptureInfo(as_cu(s._h_stream), &cap_status,
+                                                     NULL, NULL, NULL, NULL))
+    return cap_status == cydriver.CU_STREAM_CAPTURE_STATUS_ACTIVE
+
+
+cdef void _do_copy_with_attributes(
+    cydriver.CUdeviceptr dst, cydriver.CUdeviceptr src, size_t nbytes,
+    object options, cydriver.CUstream hstream,
+):
+    IF CUDA_CORE_BUILD_MAJOR >= 13:
+        # Routed through the memcpy_with_attributes_async() C++ shim since
+        # cydriver.cuMemcpyWithAttributesAsync is absent from cuda-bindings < 13.2.
+        cdef cydriver.CUmemcpyAttributes cu_attr = _to_cu_memcpy_attributes(options)
+        with nogil:
+            HANDLE_RETURN(memcpy_with_attributes_async(dst, src, nbytes, <void*>&cu_attr, hstream))
+    ELSE:
+        pass  # unreachable: _with_attributes_available() is always False on CUDA 12
+
+
+cdef void _dispatch_buffer_copy(
+    cydriver.CUdeviceptr dst, cydriver.CUdeviceptr src, size_t nbytes,
+    Stream s, object options, str method_name,
+):
+    """Submit a single copy, honoring CopyOptions when the attributes path is usable."""
+    if options is None:
+        with nogil:
+            HANDLE_RETURN(cydriver.cuMemcpyAsync(dst, src, nbytes, as_cu(s._h_stream)))
+        return
+    if not isinstance(options, CopyOptions):
+        raise TypeError(
+            f"{method_name}: options must be CopyOptions, got {type(options).__name__}"
+        )
+    if Stream_is_legacy_default_token(s):
+        raise TypeError(
+            f"{method_name} does not accept LEGACY_DEFAULT_STREAM with options "
+            "(matches copy_batch); cuMemcpyWithAttributesAsync rejects it outright, "
+            "unlike PER_THREAD_DEFAULT_STREAM, which is a real stream to the driver "
+            "and is accepted. Pass an explicit stream, PER_THREAD_DEFAULT_STREAM, "
+            "or options=None."
+        )
+    if _stream_is_capturing(s):
+        raise TypeError(
+            f"{method_name} does not support graph capture with options "
+            "(matches copy_batch); the driver has no graph-node form of "
+            "cuMemcpyWithAttributesAsync, so options cannot be honored in a graph. "
+            "Use GraphNode.memcpy for a plain (non-attributed) copy node, or pass "
+            "options=None."
+        )
+    if _with_attributes_available():
+        _do_copy_with_attributes(dst, src, nbytes, options, as_cu(s._h_stream))
+    else:
+        _reject_unsupported_during_api_call(
+            options.src_access_order,
+            "cuda.bindings and the driver to both report CUDA 13.2 or newer "
+            "(cuMemcpyWithAttributesAsync is unavailable here)",
+        )
+        # STREAM and ANY never require access sooner than stream order, so
+        # cuMemcpyAsync satisfies them; options are otherwise silently
+        # ignored on this pre-CUDA-13.2 fallback path, matching copy_batch.
+        with nogil:
+            HANDLE_RETURN(cydriver.cuMemcpyAsync(dst, src, nbytes, as_cu(s._h_stream)))
+
+
 cdef class Buffer:
     """Represent a handle to allocated memory.
 
@@ -176,20 +266,50 @@ cdef class Buffer:
     def _init(
         cls, ptr: DevicePointerType, size_t size, mr: MemoryResource | None = None,
         ipc_descriptor: IPCBufferDescriptor | None = None,
-        owner : object | None = None
+        owner : object | None = None,
+        *,
+        stream: Stream | GraphBuilder | None = None,
     ) -> Buffer:
         """Create a Buffer from a raw pointer.
 
         When ``mr`` is provided, the buffer takes ownership: ``mr.deallocate()``
         is called when the buffer is closed or garbage collected.  When ``owner``
         is provided, the owner is kept alive but no deallocation is performed.
+        When ``mr`` is provided, a deallocation stream is recorded at creation
+        (``stream`` if given, otherwise ``default_stream()``). Recording a
+        default-stream token requires a CUDA context to be current. Host-only
+        resources (``mr.is_device_accessible`` is ``False``) record no stream
+        and need no context.
         """
         if mr is not None and owner is not None:
             raise ValueError("owner and memory resource cannot be both specified together")
+        if stream is not None and mr is None:
+            raise ValueError("stream requires a memory resource (mr)")
         cdef Buffer self = Buffer.__new__(cls)
         cdef uintptr_t c_ptr = <uintptr_t>(int(ptr))
+        cdef Stream s
+        cdef cydriver.CUresult _ds_status
+        cdef bint record_stream
         if mr is not None:
+            s = Stream_accept(default_stream() if stream is None else stream)
+            # Host-only memory needs no CUDA context to free, so no deallocation
+            # stream is recorded and the driver is not called.
+            record_stream = mr.is_device_accessible
             self._h_ptr = deviceptr_create_with_mr(c_ptr, size, mr)
+            if record_stream:
+                _ds_status = set_deallocation_stream(self._h_ptr, s._h_stream)
+                if _ds_status != cydriver.CUresult.CUDA_SUCCESS:
+                    # Reset before raising: the DevicePtrHandle destructor would otherwise
+                    # invoke _mr_dealloc_callback, which catches any inner exception and
+                    # clears the exception state, swallowing the error we're about to raise.
+                    self._h_ptr.reset()
+                    if _ds_status == cydriver.CUresult.CUDA_ERROR_INVALID_CONTEXT:
+                        raise RuntimeError(
+                            "Cannot record a default deallocation stream when no CUDA context is "
+                            "current. Call Device.set_current() first, or pass stream= with a "
+                            "non-default Stream."
+                        )
+                    HANDLE_RETURN(_ds_status)
         else:
             self._h_ptr = deviceptr_create_with_owner(c_ptr, owner)
         self._size = size
@@ -201,22 +321,32 @@ cdef class Buffer:
 
     @staticmethod
     def _reduce_helper(mr, ipc_descriptor):
+        cdef ContextHandle h_ctx = get_current_context()
+        cdef int device_id
+        if not h_ctx:
+            # Spawned processes unpickle arguments before entering their target,
+            # so initialize the context needed to bind the default-stream token.
+            device_id = mr.device_id
+            (Device(device_id) if device_id >= 0 else Device()).set_current()
         # The parent process's stream is not portable across processes, so the
         # pickle path cannot thread an explicit stream through. Seed the
         # imported buffer's deallocation with the current context's default
-        # stream; the receiver can override via buffer.close(stream).
+        # stream; the receiver can override it before or during close.
         return Buffer.from_ipc_descriptor(mr, ipc_descriptor, stream=default_stream())
 
     def __reduce__(self) -> tuple[object, ...]:
         # Unpickling performs a live CUDA IPC import from descriptor bytes in the
         # pickle stream. Only deserialize Buffers from a trusted principal.
         # Must not serialize the parent's stream!
+        Buffer_check_open(self)
         return Buffer._reduce_helper, (self.memory_resource, self.ipc_descriptor)
 
     @staticmethod
     def from_handle(
         ptr: DevicePointerType, size_t size, mr: MemoryResource | None = None,
         owner: object | None = None,
+        *,
+        stream: Stream | GraphBuilder | None = None,
     ) -> Buffer:
         """Create a new :class:`Buffer` object from a pointer.
 
@@ -234,6 +364,15 @@ cdef class Buffer:
             An object holding external allocation that the ``ptr`` points to.
             The reference is kept as long as the buffer is alive.
             The ``owner`` and ``mr`` cannot be specified together.
+        stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`, optional
+            Keyword-only. The stream used to order the buffer's deallocation
+            when ``mr`` owns the pointer. Defaults to ``default_stream()``.
+            Recording a default-stream token requires a CUDA context to be
+            current. Host-only resources (``mr.is_device_accessible`` is
+            ``False``) record no stream and need no context. If the buffer may
+            be freed from a different host thread,
+            pass a stream other than the per-thread default stream, which
+            refers to a different stream on each thread.
 
         Note
         ----
@@ -241,7 +380,7 @@ cdef class Buffer:
         non-owning reference.  The pointer will NOT be freed when the
         :class:`Buffer` is closed or garbage collected.
         """
-        return Buffer._init(ptr, size, mr=mr, owner=owner)
+        return Buffer._init(ptr, size, mr=mr, owner=owner, stream=stream)
 
     @classmethod
     def from_ipc_descriptor(
@@ -272,8 +411,12 @@ cdef class Buffer:
     @cython.critical_section
     def ipc_descriptor(self) -> IPCBufferDescriptor:
         """Descriptor for sharing this buffer with other processes."""
+        Buffer_check_open(self)
+        cdef object ipc_data
         if self._ipc_data is None:
-            self._ipc_data = IPCDataForBuffer(_ipc.Buffer_get_ipc_descriptor(self), False)
+            ipc_data = IPCDataForBuffer(_ipc.Buffer_get_ipc_descriptor(self), False)
+            if self._ipc_data is None:
+                self._ipc_data = ipc_data
         return self._ipc_data.ipc_descriptor
 
     def close(self, stream: Stream | GraphBuilder | None = None) -> None:
@@ -287,9 +430,45 @@ cdef class Buffer:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`, optional
             The stream object to use for asynchronous deallocation. If None,
             the deallocation stream stored in the handle is used.
+
+        See Also
+        --------
+        set_deallocation_stream
+            Change the deallocation stream without closing the buffer.
         """
         Buffer_close(self, stream)
 
+    def set_deallocation_stream(self, stream: Stream | GraphBuilder) -> None:
+        """Change the stream that orders this buffer's eventual deallocation.
+
+        The buffer remains open and usable. A later :meth:`close` without a
+        stream, garbage collection, or release of the final retained device
+        pointer handle uses the replacement stream.
+
+        This method does not synchronize streams or establish dependencies.
+        The caller must ensure that allocation and all accesses are ordered
+        before the deallocation on ``stream``.
+
+        Parameters
+        ----------
+        stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
+            The stream to use for eventual asynchronous deallocation.
+
+        Raises
+        ------
+        RuntimeError
+            If the buffer is already closed, or if a default-stream token
+            cannot be bound because no CUDA context is current.
+        TypeError
+            If ``stream`` is ``None`` or is not an accepted stream object.
+
+        Notes
+        -----
+        Synchronizing concurrent mutation and destruction of the same buffer
+        is the caller's responsibility.
+        """
+        Buffer_set_deallocation_stream(self, stream)
+
     def __enter__(self):
         return self
 
@@ -297,7 +476,8 @@ cdef class Buffer:
         self.close()
         return False
 
-    def copy_to(self, dst: Buffer | None = None, *, stream: Stream | GraphBuilder) -> Buffer:
+    def copy_to(self, dst: Buffer | None = None, *, stream: Stream | GraphBuilder,
+                options: CopyOptions | None = None) -> Buffer:
         """Copy from this buffer to the dst buffer asynchronously on the given stream.
 
         Copies the data from this buffer to the provided dst buffer.
@@ -312,8 +492,31 @@ cdef class Buffer:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
             Keyword argument specifying the stream for the
             asynchronous copy
+        options : :class:`~utils.CopyOptions`, optional
+            Transfer hints (source access order, location hints, overlap mode).
+            Honored when cuda.bindings and the driver are both CUDA 13.2 or
+            newer. Not accepted with ``LEGACY_DEFAULT_STREAM``; use
+            ``PER_THREAD_DEFAULT_STREAM`` instead. Not accepted with a
+            capturing stream either, since a graph cannot represent these
+            attributes; use :meth:`graph.GraphNode.memcpy` for a plain,
+            non-attributed copy node, or pass ``options=None``. On an older
+            cuda.bindings/driver, ``src_access_order`` values of ``STREAM``
+            and ``ANY`` are silently ignored; ``DURING_API_CALL`` raises
+            instead of silently downgrading its guarantee.
+
+        Raises
+        ------
+        TypeError
+            If ``options`` is not a :class:`~utils.CopyOptions` instance, or
+            if ``options`` is given together with ``LEGACY_DEFAULT_STREAM``
+            or a stream currently in graph capture mode.
+        RuntimeError
+            If ``options.src_access_order`` is ``DURING_API_CALL`` and
+            cuda.bindings or the driver is older than CUDA 13.2: falling
+            back to a plain copy cannot honor that guarantee.
 
         """
+        Buffer_check_open(self)
         cdef Stream s = Stream_accept(stream)
         cdef size_t src_size = self._size
 
@@ -322,18 +525,20 @@ cdef class Buffer:
                 raise ValueError("a destination buffer must be provided (this "
                                  "buffer does not have a memory_resource)")
             dst = self._memory_resource.allocate(src_size, stream=s)
+        else:
+            Buffer_check_open(<Buffer>dst)
 
         cdef size_t dst_size = dst._size
         if dst_size != src_size:
             raise ValueError( "buffer sizes mismatch between src and dst (sizes "
                              f"are: src={src_size}, dst={dst_size})"
             )
-        with nogil:
-            HANDLE_RETURN(cydriver.cuMemcpyAsync(
-                as_cu(dst._h_ptr), as_cu(self._h_ptr), src_size, as_cu(s._h_stream)))
+        _dispatch_buffer_copy(
+            as_cu(dst._h_ptr), as_cu(self._h_ptr), src_size, s, options, "copy_to")
         return dst
 
-    def copy_from(self, src: Buffer, *, stream: Stream | GraphBuilder) -> None:
+    def copy_from(self, src: Buffer, *, stream: Stream | GraphBuilder,
+                  options: CopyOptions | None = None) -> None:
         """Copy from the src buffer to this buffer asynchronously on the given stream.
 
         Parameters
@@ -343,8 +548,31 @@ cdef class Buffer:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
             Keyword argument specifying the stream for the
             asynchronous copy
+        options : :class:`~utils.CopyOptions`, optional
+            Transfer hints (source access order, location hints, overlap mode).
+            Honored when cuda.bindings and the driver are both CUDA 13.2 or
+            newer. Not accepted with ``LEGACY_DEFAULT_STREAM``; use
+            ``PER_THREAD_DEFAULT_STREAM`` instead. Not accepted with a
+            capturing stream either, since a graph cannot represent these
+            attributes; use :meth:`graph.GraphNode.memcpy` for a plain,
+            non-attributed copy node, or pass ``options=None``. On an older
+            cuda.bindings/driver, ``src_access_order`` values of ``STREAM``
+            and ``ANY`` are silently ignored; ``DURING_API_CALL`` raises
+            instead of silently downgrading its guarantee.
 
+        Raises
+        ------
+        TypeError
+            If ``options`` is not a :class:`~utils.CopyOptions` instance, or
+            if ``options`` is given together with ``LEGACY_DEFAULT_STREAM``
+            or a stream currently in graph capture mode.
+        RuntimeError
+            If ``options.src_access_order`` is ``DURING_API_CALL`` and
+            cuda.bindings or the driver is older than CUDA 13.2: falling
+            back to a plain copy cannot honor that guarantee.
         """
+        Buffer_check_open(self)
+        Buffer_check_open(src)
         cdef Stream s = Stream_accept(stream)
         cdef size_t dst_size = self._size
         cdef size_t src_size = src._size
@@ -353,9 +581,8 @@ cdef class Buffer:
             raise ValueError( "buffer sizes mismatch between src and dst (sizes "
                              f"are: src={src_size}, dst={dst_size})"
             )
-        with nogil:
-            HANDLE_RETURN(cydriver.cuMemcpyAsync(
-                as_cu(self._h_ptr), as_cu(src._h_ptr), dst_size, as_cu(s._h_stream)))
+        _dispatch_buffer_copy(
+            as_cu(self._h_ptr), as_cu(src._h_ptr), dst_size, s, options, "copy_from")
 
     def fill(self, value: int | BufferProtocol, *, stream: Stream | GraphBuilder) -> None:
         """Fill this buffer with a repeating byte pattern.
@@ -379,6 +606,7 @@ cdef class Buffer:
             If int value is outside [0, 256).
 
         """
+        Buffer_check_open(self)
         cdef Stream s_stream = Stream_accept(stream)
         cdef unsigned int val
         cdef unsigned int elem_size
@@ -412,6 +640,7 @@ cdef class Buffer:
     ) -> object:
         # Note: we ignore the stream argument entirely (as if it is -1).
         # It is the user's responsibility to maintain stream order.
+        Buffer_check_open(self)
         if dl_device is not None:
             raise BufferError("Sorry, not supported: dl_device other than None")
         if copy is True:
@@ -422,10 +651,10 @@ cdef class Buffer:
             if not isinstance(max_version, tuple) or len(max_version) != 2:
                 raise BufferError(f"Expected max_version tuple[int, int], got {max_version}")
             versioned = max_version >= (1, 0)
-        capsule = make_py_capsule(self, versioned)
-        return capsule
+        return make_py_capsule(self, versioned)
 
     def __dlpack_device__(self) -> tuple[int, int]:
+        Buffer_check_open(self)
         return classify_dl_device(self)
 
     def __buffer__(self, flags: int, /) -> memoryview:
@@ -441,7 +670,8 @@ cdef class Buffer:
 
     @property
     def device_id(self) -> int:
-        """Return the device ordinal of this buffer."""
+        """Return the device ordinal of this buffer, or -1 for memory not bound to a device."""
+        Buffer_check_open(self)
         if self._memory_resource is not None:
             return self._memory_resource.device_id
         _init_memory_attrs(self)
@@ -460,6 +690,11 @@ cdef class Buffer:
         # that expect a raw pointer value
         return as_intptr(self._h_ptr)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this buffer has been closed."""
+        return self._h_ptr.get() == NULL
+
     def __eq__(self, other: object) -> bool:
         if not isinstance(other, Buffer):
             return NotImplemented
@@ -477,6 +712,7 @@ cdef class Buffer:
     @property
     def is_device_accessible(self) -> bool:
         """Return True if this buffer can be accessed by the GPU, otherwise False."""
+        Buffer_check_open(self)
         if self._memory_resource is not None:
             return self._memory_resource.is_device_accessible
         _init_memory_attrs(self)
@@ -485,6 +721,7 @@ cdef class Buffer:
     @property
     def is_host_accessible(self) -> bool:
         """Return True if this buffer can be accessed by the CPU, otherwise False."""
+        Buffer_check_open(self)
         if self._memory_resource is not None:
             return self._memory_resource.is_host_accessible
         _init_memory_attrs(self)
@@ -493,6 +730,7 @@ cdef class Buffer:
     @property
     def is_managed(self) -> bool:
         """Return True if this buffer is CUDA managed (unified) memory, otherwise False."""
+        Buffer_check_open(self)
         _init_memory_attrs(self)
         if self._mem_attrs.is_managed:
             return True
@@ -544,7 +782,12 @@ cdef class MemoryResource:
         stream : :obj:`~_stream.Stream` | :obj:`~graph.GraphBuilder`
             Keyword-only. The stream on which to perform the allocation
             asynchronously. Must be passed explicitly; pass
-            ``device.default_stream`` to use the default stream.
+            ``device.default_stream`` to use the default stream. For subclasses
+            that support stream-ordered deallocation, this stream also orders
+            the buffer's eventual deallocation, so if the buffer may be freed
+            from a different host thread, prefer a stream other than the
+            per-thread default stream, which refers to a different stream on
+            each thread.
 
         Returns
         -------
@@ -617,18 +860,50 @@ cdef Buffer Buffer_from_deviceptr_handle(
     return buf
 
 
+cdef tuple Buffer_coerce_batch(object buffers, str what, str single_hint):
+    """Coerce ``buffers`` to a ``tuple[Buffer, ...]``; reject a bare Buffer.
+
+    Shared by the batched free functions. Passing one Buffer is rejected
+    rather than treated as a one-element batch so that the per-buffer API
+    named by ``single_hint`` stays the single obvious way to do it.
+    """
+    cdef list out
+    if isinstance(buffers, Buffer):
+        raise TypeError(
+            f"{what}: pass a sequence of Buffers; for a single buffer use {single_hint}"
+        )
+    if not isinstance(buffers, Sequence):
+        raise TypeError(
+            f"{what}: buffers must be a sequence of Buffer, got {type(buffers).__name__}"
+        )
+    if not buffers:
+        raise ValueError(f"{what}: empty buffers sequence")
+    out = []
+    for item in buffers:
+        if not isinstance(item, Buffer):
+            raise TypeError(f"{what}: expected Buffer, got {type(item).__name__}")
+        Buffer_check_open(<Buffer>item)
+        out.append(item)
+    return tuple(out)
+
+cdef inline void Buffer_set_deallocation_stream(Buffer self, object stream):
+    """Validate and replace a live buffer's deallocation recipe."""
+    Buffer_check_open(self)
+    cdef Stream s = Stream_accept(stream)
+    _apply_deallocation_stream(self._h_ptr, s._h_stream)
+
+
 cdef inline void Buffer_close(Buffer self, object stream):
     """Close a buffer, freeing its memory."""
-    cdef Stream s
     if not self._h_ptr:
         return
     # Update deallocation stream if provided
     if stream is not None:
-        s = Stream_accept(stream)
-        set_deallocation_stream(self._h_ptr, s._h_stream)
+        Buffer_set_deallocation_stream(self, stream)
     # Reset handle - RAII deleter will free the memory (and release owner ref in C++)
     self._h_ptr.reset()
     self._size = 0
     self._memory_resource = None
     self._ipc_data = None
     self._owner = None
+    self._mem_attrs_inited.store(False)
diff --git a/cuda_core/cuda/core/_memory/_copy_attributes.pxd b/cuda_core/cuda/core/_memory/_copy_attributes.pxd
new file mode 100644
index 00000000000..96c213dfec5
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_copy_attributes.pxd
@@ -0,0 +1,31 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+# Neutral leaf module: declares the CopyOptions-to-CUmemcpyAttributes converter
+# and the 13.2 availability gate so both _buffer and _copy_ops can cimport them
+# without either depending on the other.
+
+from cuda.bindings cimport cydriver
+from cuda.core._utils.version cimport cy_binding_version, cy_driver_version  # no-cython-lint
+
+
+IF CUDA_CORE_BUILD_MAJOR >= 13:
+    from cuda.core._resource_handles cimport has_memcpy_with_attributes_async
+
+    cdef inline bint _with_attributes_available():
+        # has_memcpy_with_attributes_async() says whether the installed
+        # cuda-bindings actually exports cuMemcpyWithAttributesAsync (13.2+);
+        # the version checks alone are not sufficient, since cuda.core's build
+        # can be paired with a cuda-bindings install older than what it built
+        # against (see https://github.com/NVIDIA/cuda-python/issues/2063).
+        return (
+            has_memcpy_with_attributes_async()
+            and cy_driver_version() >= (13, 2, 0)
+            and cy_binding_version() >= (13, 2, 0)
+        )
+ELSE:
+    cdef inline bint _with_attributes_available():
+        return False
+
+cdef cydriver.CUmemcpyAttributes _to_cu_memcpy_attributes(object attr)
diff --git a/cuda_core/cuda/core/_memory/_copy_attributes.pyi b/cuda_core/cuda/core/_memory/_copy_attributes.pyi
new file mode 100644
index 00000000000..5eaf371b8c4
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_copy_attributes.pyi
@@ -0,0 +1 @@
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_copy_attributes.pyx
diff --git a/cuda_core/cuda/core/_memory/_copy_attributes.pyx b/cuda_core/cuda/core/_memory/_copy_attributes.pyx
new file mode 100644
index 00000000000..5618cf35527
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_copy_attributes.pyx
@@ -0,0 +1,28 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from libc.string cimport memset
+
+from cuda.bindings cimport cydriver
+from cuda.core._memory._location cimport to_cumemlocation
+
+from cuda.core._memory._managed_location import _coerce_location
+
+
+cdef cydriver.CUmemcpyAttributes _to_cu_memcpy_attributes(object attr):
+    """Convert a CopyOptions to a cydriver.CUmemcpyAttributes struct."""
+    cdef cydriver.CUmemcpyAttributes cu_attr
+    memset(&cu_attr, 0, sizeof(cydriver.CUmemcpyAttributes))
+    cu_attr.srcAccessOrder = <cydriver.CUmemcpySrcAccessOrder>(<int>attr._to_driver_enum())
+    cu_attr.flags = <unsigned int>(<int>attr._to_driver_flags())
+
+    cdef object src_loc = _coerce_location(attr.src_location_hint, allow_none=True)
+    cdef object dst_loc = _coerce_location(attr.dst_location_hint, allow_none=True)
+
+    if src_loc is not None:
+        cu_attr.srcLocHint = to_cumemlocation(src_loc.kind, src_loc.id)
+    if dst_loc is not None:
+        cu_attr.dstLocHint = to_cumemlocation(dst_loc.kind, dst_loc.id)
+
+    return cu_attr
diff --git a/cuda_core/cuda/core/_memory/_copy_enums.py b/cuda_core/cuda/core/_memory/_copy_enums.py
new file mode 100644
index 00000000000..84c72e71110
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_copy_enums.py
@@ -0,0 +1,212 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+import dataclasses
+from collections.abc import Sequence
+
+from cuda.core._device import Device
+from cuda.core._host import Host
+from cuda.core._utils.cuda_utils import driver
+from cuda.core._utils.pycompat import StrEnum
+from cuda.core._utils.version import binding_version
+
+__all__ = ["CopyOptions", "MemcpyOverlapMode", "MemcpySrcAccessOrder"]
+
+
+class MemcpySrcAccessOrder(StrEnum):
+    """Source access order hint for batched memcpy operations.
+
+    Maps to ``CUmemcpySrcAccessOrder``.
+
+    ``STREAM``
+        Source reads follow stream order. Earlier stream work may still be
+        accessing the source when the copy is enqueued.
+    ``DURING_API_CALL``
+        The driver may read the source out of stream order, but all reads
+        are complete before :func:`copy_batch` returns. No earlier stream
+        work may be accessing the source at the time of the call.
+    ``ANY``
+        The driver may read the source after the call returns. The caller
+        must keep the source unchanged until the copy completes in stream
+        order. No earlier stream work may be accessing the source.
+    """
+
+    STREAM = "stream"
+    DURING_API_CALL = "during_api_call"
+    ANY = "any"
+
+
+class MemcpyOverlapMode(StrEnum):
+    """Overlap mode hint for batched memcpy operations.
+
+    Maps to ``CUmemcpyFlags``.
+
+    ``DEFAULT``
+        No overlap preference; the driver uses its default scheduling.
+    ``PREFER_OVERLAP_WITH_COMPUTE``
+        Hint that the copy should preferably overlap with concurrent
+        compute work. This is advisory and may be ignored depending on
+        the platform and copy parameters.
+    """
+
+    DEFAULT = "default"
+    PREFER_OVERLAP_WITH_COMPUTE = "prefer_overlap_with_compute"
+
+
+@dataclasses.dataclass(frozen=True)
+class CopyOptions:
+    """Attribute bundle for a single copy within a batched memcpy.
+
+    Parameters
+    ----------
+    src_access_order : :class:`MemcpySrcAccessOrder` or str
+        Hint describing how the source will be accessed.
+        Default is ``"stream"`` (stream-ordered access).
+    src_location_hint : :class:`cuda.core.Device` | :class:`cuda.core.Host` | None
+        Hint for the source memory location. Honored only for managed
+        memory on devices with concurrent managed access and for
+        system-allocated pageable memory on devices with pageable memory
+        access; ignored for all other memory types. Does not prefetch
+        memory and does not set persistent memory advice.
+        ``None`` means no hint.
+    dst_location_hint : :class:`cuda.core.Device` | :class:`cuda.core.Host` | None
+        Hint for the destination memory location. Same semantics and
+        restrictions as ``src_location_hint``. ``None`` means no hint.
+    overlap_mode : :class:`MemcpyOverlapMode` or str
+        Hint requesting that the copy overlap with concurrent compute work.
+        This is advisory; it has an effect only on devices that support it.
+        Default is ``"default"``.
+    """
+
+    src_access_order: MemcpySrcAccessOrder | str = "stream"
+    src_location_hint: Device | Host | None = None
+    dst_location_hint: Device | Host | None = None
+    overlap_mode: MemcpyOverlapMode | str = "default"
+
+    def __post_init__(self):
+        # Frozen, unlike the other *Options dataclasses in cuda.core, because
+        # the batched-API contract agreed in NVIDIA/cuda-python#1775 specifies
+        # immutable per-call options:
+        # https://github.com/NVIDIA/cuda-python/pull/1775#issuecomment-4355502334
+        #
+        # Normalizing str -> StrEnum therefore has to go through
+        # object.__setattr__; a plain assignment would raise
+        # FrozenInstanceError. Done here rather than at use so that a typo
+        # fails at construction and the field always holds the enum.
+        if not isinstance(self.src_access_order, MemcpySrcAccessOrder):
+            try:
+                object.__setattr__(
+                    self,
+                    "src_access_order",
+                    MemcpySrcAccessOrder(self.src_access_order),
+                )
+            except (ValueError, TypeError) as exc:
+                raise ValueError(f"invalid src_access_order: {self.src_access_order!r}") from exc
+        if not isinstance(self.overlap_mode, MemcpyOverlapMode):
+            try:
+                object.__setattr__(
+                    self,
+                    "overlap_mode",
+                    MemcpyOverlapMode(self.overlap_mode),
+                )
+            except (ValueError, TypeError) as exc:
+                raise ValueError(f"invalid overlap_mode: {self.overlap_mode!r}") from exc
+
+    def _to_driver_enum(self) -> int:
+        """Return the driver CUmemcpySrcAccessOrder value."""
+        if not _SRC_ACCESS_ORDER_TO_DRIVER:
+            raise NotImplementedError(_CUDA13_REQUIRED)
+        return _SRC_ACCESS_ORDER_TO_DRIVER[MemcpySrcAccessOrder(self.src_access_order)]
+
+    def _to_driver_flags(self) -> int:
+        """Return the driver CUmemcpyFlags value."""
+        if not _OVERLAP_MODE_TO_DRIVER:
+            raise NotImplementedError(_CUDA13_REQUIRED)
+        return _OVERLAP_MODE_TO_DRIVER[MemcpyOverlapMode(self.overlap_mode)]
+
+
+_CUDA13_REQUIRED = "copy attributes require cuda.bindings 13.0 or newer"
+
+# CUmemcpySrcAccessOrder and CUmemcpyFlags are exposed by cuda.bindings 13.0+,
+# so these maps are empty when it is older. Nothing reaches them there:
+# copy_batch refuses non-default CopyOptions when the batched entry point is
+# unavailable.
+#
+# Keyed by ``str``: under ``python_version = "3.10"`` mypy resolves StrEnum to
+# the unstubbed backports shim and so infers the members as plain ``str``.
+# StrEnum members are ``str`` instances, so this holds on every version. The
+# values are wrapped in ``int()`` because the driver enums are untyped.
+_SRC_ACCESS_ORDER_TO_DRIVER: dict[str, int]
+_OVERLAP_MODE_TO_DRIVER: dict[str, int]
+
+if binding_version() >= (13, 0, 0):
+    _src_order = driver.CUmemcpySrcAccessOrder
+    _flags = driver.CUmemcpyFlags
+    _SRC_ACCESS_ORDER_TO_DRIVER = {
+        MemcpySrcAccessOrder.STREAM: int(_src_order.CU_MEMCPY_SRC_ACCESS_ORDER_STREAM),
+        MemcpySrcAccessOrder.DURING_API_CALL: int(_src_order.CU_MEMCPY_SRC_ACCESS_ORDER_DURING_API_CALL),
+        MemcpySrcAccessOrder.ANY: int(_src_order.CU_MEMCPY_SRC_ACCESS_ORDER_ANY),
+    }
+    _OVERLAP_MODE_TO_DRIVER = {
+        MemcpyOverlapMode.DEFAULT: int(_flags.CU_MEMCPY_FLAG_DEFAULT),
+        MemcpyOverlapMode.PREFER_OVERLAP_WITH_COMPUTE: int(_flags.CU_MEMCPY_FLAG_PREFER_OVERLAP_WITH_COMPUTE),
+    }
+    del _src_order, _flags
+else:
+    _SRC_ACCESS_ORDER_TO_DRIVER = {}
+    _OVERLAP_MODE_TO_DRIVER = {}
+
+
+def _reject_unsupported_during_api_call(
+    src_access_order: MemcpySrcAccessOrder, requirement: str, *, index: int | None = None
+) -> None:
+    """Raise if ``src_access_order`` is DURING_API_CALL but the native attributes
+    path (``cuMemcpyWithAttributesAsync`` / ``cuMemcpyBatchAsync``) is unavailable.
+
+    STREAM and ANY never promise access sooner than stream order, so a plain
+    ``cuMemcpyAsync`` fallback satisfies them; DURING_API_CALL specifically
+    promises all source reads complete before the call returns, which
+    ``cuMemcpyAsync`` cannot provide (it reads the source in stream order
+    only). Silently downgrading that guarantee would let a caller reuse or
+    overwrite the source buffer before the real, stream-ordered read
+    happens: a silent data race, not a missed optimization. ``requirement``
+    names what the native path needs and why it is unavailable here;
+    ``index`` identifies the offending copy within a batch.
+
+    Internal, but deliberately importable: shared between the per-buffer and
+    batched fallback paths so both raise identically, and directly testable
+    without needing an actual old driver/bindings install.
+    """
+    if src_access_order != MemcpySrcAccessOrder.DURING_API_CALL:
+        return
+    where = f" at index {index}" if index is not None else ""
+    raise RuntimeError(
+        f"src_access_order=DURING_API_CALL{where} requires {requirement}. A "
+        "plain cuMemcpyAsync fallback reads the source in stream order only, "
+        "which would silently violate the guarantee that all source reads "
+        "complete before the call returns, letting the caller reuse the "
+        "source buffer before the real (stream-ordered) read happens. Use "
+        "src_access_order=STREAM or ANY, or omit options, if that works for "
+        "your use case."
+    )
+
+
+def _attr_run_starts(attrs: Sequence[CopyOptions]) -> list[int]:
+    """Return the start index of each maximal run of equal attributes.
+
+    This mirrors the ``attrsIdxs`` indirection that ``cuMemcpyBatchAsync``
+    expects: ``attrs[k]`` applies to the copies in
+    ``[starts[k], starts[k + 1])``. Collapsing equal neighbours means a
+    broadcast attribute is passed to the driver once (``numAttrs == 1``)
+    rather than repeated per copy.
+    """
+    starts: list[int] = []
+    prev: CopyOptions | None = None
+    for i, attr in enumerate(attrs):
+        if i == 0 or attr != prev:
+            starts.append(i)
+        prev = attr
+    return starts
diff --git a/cuda_core/cuda/core/_memory/_copy_ops.pyi b/cuda_core/cuda/core/_memory/_copy_ops.pyi
new file mode 100644
index 00000000000..ff76140d2ba
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_copy_ops.pyi
@@ -0,0 +1,93 @@
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_copy_ops.pyx
+
+from collections.abc import Sequence
+
+from cuda.core._memory._buffer import Buffer
+from cuda.core._memory._copy_enums import CopyOptions
+from cuda.core._stream import Stream
+
+_SINGLE_COPY_HINT = 'Buffer.copy_to / Buffer.copy_from'
+
+def _normalize_copy_options(options: CopyOptions | Sequence[CopyOptions] | None, n: int) -> tuple[CopyOptions, ...]:
+    """Expand ``options`` to exactly one :class:`CopyOptions` per copy.
+
+    ``None`` and a scalar broadcast; a sequence pairs by index and must
+    already have length ``n``.
+
+    Internal, but deliberately importable: options are hints that change
+    how the driver stages a transfer and never the bytes it produces, so
+    this expansion (and the run encoding applied to it) is the only
+    observable evidence that a scalar reached every copy.
+    """
+def copy_batch(stream: Stream, srcs: Sequence[Buffer], dsts: Sequence[Buffer], *, options: CopyOptions | Sequence[CopyOptions] | None=None) -> None:
+    """Copy a batch of buffers asynchronously.
+
+    Source buffer and destination buffer sizes must match. For a single
+    buffer, use :meth:`Buffer.copy_to` or :meth:`Buffer.copy_from`.
+
+    The driver provides no graph-node form of ``cuMemcpyBatchAsync``, so
+    this cannot be captured into a graph. Both passing a
+    :class:`~graph.GraphBuilder` and passing its underlying
+    :attr:`~graph.GraphBuilder.stream` while capture is active are
+    rejected. Build graph copies with
+    :meth:`graph.GraphNode.memcpy` or per-buffer :meth:`Buffer.copy_to`.
+
+    Parameters
+    ----------
+    stream : :class:`~_stream.Stream`
+        Stream for the asynchronous copy. First positional and required
+        (mirrors :func:`launch`). Does not accept a capturing stream
+        (including a :class:`~graph.GraphBuilder`'s underlying stream); use
+        :meth:`graph.GraphNode.memcpy` or per-buffer
+        :meth:`Buffer.copy_to` to build copies into a graph. Does not accept
+        ``LEGACY_DEFAULT_STREAM``, which ``cuMemcpyBatchAsync`` rejects
+        outright; ``PER_THREAD_DEFAULT_STREAM`` is a real stream to the
+        driver and is accepted.
+    srcs : Sequence[:class:`Buffer`]
+        Source buffers. Must be a sequence, not a single Buffer.
+    dsts : Sequence[:class:`Buffer`]
+        Destination buffers. Must match ``len(srcs)``.
+    options : :class:`CopyOptions` | Sequence[:class:`CopyOptions`] | None
+        Per-copy options. A single value applies to every copy; a
+        sequence pairs by index and must match ``len(srcs)``. ``None``
+        uses stream-ordered defaults.
+
+    Raises
+    ------
+    ValueError
+        If lengths or sizes mismatch.
+    TypeError
+        If a single Buffer is passed instead of a sequence, if
+        ``LEGACY_DEFAULT_STREAM`` is passed, or if the stream is currently
+        in graph capture mode.
+    RuntimeError
+        If any copy requests ``src_access_order=DURING_API_CALL`` and the
+        native ``cuMemcpyBatchAsync`` path is unavailable (see Notes): the
+        per-copy ``cuMemcpyAsync`` fallback reads the source in stream
+        order only, which cannot honor that guarantee.
+
+    Notes
+    -----
+    Batching through ``cuMemcpyBatchAsync`` requires all three of:
+    ``cuda.core`` built against CUDA 13 headers, ``cuda.bindings`` 13.0 or
+    newer, and a driver reporting CUDA 13.0 or newer
+    (``cuDriverGetVersion() >= 13000``). ``cuda.bindings`` binds only the
+    CUDA 13.0 revision of the entry point, so a driver that predates it is
+    refused even where it implements the earlier CUDA 12.8 signature.
+
+    The driver may execute batch items concurrently and in any order.
+    A batch must therefore not contain copies where the source range of
+    one copy overlaps the destination range of another; such aliasing
+    produces undefined results. Detecting overlaps at runtime is
+    impractical; callers are responsible for ensuring no aliasing exists.
+
+    On pre-CUDA 13 installs the copies fall back to a Python-level loop
+    over ``cuMemcpyAsync``, so the potential performance benefit of
+    asynchronous batched copies is not realized. ``src_access_order`` values
+    of ``STREAM`` and ``ANY`` are silently ignored on the fallback path
+    (stream-ordered access already satisfies both); ``DURING_API_CALL``
+    raises ``RuntimeError`` instead, since silently downgrading it to
+    stream-ordered access would let a caller reuse the source buffer before
+    the real read happens.
+
+    """
diff --git a/cuda_core/cuda/core/_memory/_copy_ops.pyx b/cuda_core/cuda/core/_memory/_copy_ops.pyx
new file mode 100644
index 00000000000..e57be2e40a0
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_copy_ops.pyx
@@ -0,0 +1,319 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+from collections.abc import Sequence
+
+IF CUDA_CORE_BUILD_MAJOR >= 13:
+    from libcpp.vector cimport vector
+
+from cuda.bindings cimport cydriver
+from cuda.core._memory._buffer cimport Buffer, Buffer_coerce_batch
+from cuda.core._memory._copy_attributes cimport _to_cu_memcpy_attributes  # no-cython-lint
+from cuda.core._resource_handles cimport as_cu
+from cuda.core._stream cimport Stream, Stream_accept, Stream_is_legacy_default_token
+from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
+
+# cy_driver_version and _attr_run_starts are referenced only from CUDA 13
+# branches. cython-lint does not evaluate compile-time IF blocks, so they need
+# a pragma to be seen as used.
+from cuda.core._utils.version cimport cy_driver_version  # no-cython-lint
+
+from cuda.core._memory._copy_enums import (
+    CopyOptions,
+    _attr_run_starts,  # no-cython-lint
+    _reject_unsupported_during_api_call,
+)
+
+_SINGLE_COPY_HINT = "Buffer.copy_to / Buffer.copy_from"
+
+
+cdef inline bint _batch_entry_point_available():
+    """Whether cuMemcpyBatchAsync can actually be called here.
+
+    Requires ``cuda.core`` built against CUDA 13 headers (compile time) and
+    a driver reporting CUDA 13.0 or newer, i.e.
+    ``cuDriverGetVersion() >= 13000`` (run time).
+
+    The run-time bound is set by the binding layer, not by when the driver
+    gained the feature. CUDA 12.8 already exposed a ``cuMemcpyBatchAsync``,
+    but its signature carried a ``failIdx`` out-parameter that CUDA 13.0
+    dropped. ``cuda.bindings`` resolves only the 13.0 revision, via
+    ``cuGetProcAddress_v2('cuMemcpyBatchAsync', ..., 13000, ...)``, so an
+    older driver yields a NULL pointer even though it may implement the
+    earlier entry point.
+    """
+    IF CUDA_CORE_BUILD_MAJOR >= 13:
+        return cy_driver_version() >= (13, 0, 0)
+    ELSE:
+        return False
+
+
+def _normalize_copy_options(
+    options: CopyOptions | Sequence[CopyOptions] | None,
+    Py_ssize_t n,
+) -> tuple[CopyOptions, ...]:
+    """Expand ``options`` to exactly one :class:`CopyOptions` per copy.
+
+    ``None`` and a scalar broadcast; a sequence pairs by index and must
+    already have length ``n``.
+
+    Internal, but deliberately importable: options are hints that change
+    how the driver stages a transfer and never the bytes it produces, so
+    this expansion (and the run encoding applied to it) is the only
+    observable evidence that a scalar reached every copy.
+    """
+    if options is None:
+        return (CopyOptions(),) * n
+    if isinstance(options, CopyOptions):
+        return (options,) * n
+    if isinstance(options, Sequence):
+        if len(options) != n:
+            raise ValueError(
+                f"copy_batch: options length {len(options)} does not match "
+                f"buffers length {n}"
+            )
+        for a in options:
+            if not isinstance(a, CopyOptions):
+                raise TypeError(
+                    f"copy_batch: each options element must be CopyOptions, "
+                    f"got {type(a).__name__}"
+                )
+        return tuple(options)
+    raise TypeError(
+        f"copy_batch: options must be CopyOptions or a sequence of "
+        f"CopyOptions, got {type(options).__name__}"
+    )
+
+
+def copy_batch(
+    stream: Stream,
+    srcs: Sequence[Buffer],
+    dsts: Sequence[Buffer],
+    *,
+    options: CopyOptions | Sequence[CopyOptions] | None = None,
+) -> None:
+    """Copy a batch of buffers asynchronously.
+
+    Source buffer and destination buffer sizes must match. For a single
+    buffer, use :meth:`Buffer.copy_to` or :meth:`Buffer.copy_from`.
+
+    The driver provides no graph-node form of ``cuMemcpyBatchAsync``, so
+    this cannot be captured into a graph. Both passing a
+    :class:`~graph.GraphBuilder` and passing its underlying
+    :attr:`~graph.GraphBuilder.stream` while capture is active are
+    rejected. Build graph copies with
+    :meth:`graph.GraphNode.memcpy` or per-buffer :meth:`Buffer.copy_to`.
+
+    Parameters
+    ----------
+    stream : :class:`~_stream.Stream`
+        Stream for the asynchronous copy. First positional and required
+        (mirrors :func:`launch`). Does not accept a capturing stream
+        (including a :class:`~graph.GraphBuilder`\'s underlying stream); use
+        :meth:`graph.GraphNode.memcpy` or per-buffer
+        :meth:`Buffer.copy_to` to build copies into a graph. Does not accept
+        ``LEGACY_DEFAULT_STREAM``, which ``cuMemcpyBatchAsync`` rejects
+        outright; ``PER_THREAD_DEFAULT_STREAM`` is a real stream to the
+        driver and is accepted.
+    srcs : Sequence[:class:`Buffer`]
+        Source buffers. Must be a sequence, not a single Buffer.
+    dsts : Sequence[:class:`Buffer`]
+        Destination buffers. Must match ``len(srcs)``.
+    options : :class:`CopyOptions` | Sequence[:class:`CopyOptions`] | None
+        Per-copy options. A single value applies to every copy; a
+        sequence pairs by index and must match ``len(srcs)``. ``None``
+        uses stream-ordered defaults.
+
+    Raises
+    ------
+    ValueError
+        If lengths or sizes mismatch.
+    TypeError
+        If a single Buffer is passed instead of a sequence, if
+        ``LEGACY_DEFAULT_STREAM`` is passed, or if the stream is currently
+        in graph capture mode.
+    RuntimeError
+        If any copy requests ``src_access_order=DURING_API_CALL`` and the
+        native ``cuMemcpyBatchAsync`` path is unavailable (see Notes): the
+        per-copy ``cuMemcpyAsync`` fallback reads the source in stream
+        order only, which cannot honor that guarantee.
+
+    Notes
+    -----
+    Batching through ``cuMemcpyBatchAsync`` requires all three of:
+    ``cuda.core`` built against CUDA 13 headers, ``cuda.bindings`` 13.0 or
+    newer, and a driver reporting CUDA 13.0 or newer
+    (``cuDriverGetVersion() >= 13000``). ``cuda.bindings`` binds only the
+    CUDA 13.0 revision of the entry point, so a driver that predates it is
+    refused even where it implements the earlier CUDA 12.8 signature.
+
+    The driver may execute batch items concurrently and in any order.
+    A batch must therefore not contain copies where the source range of
+    one copy overlaps the destination range of another; such aliasing
+    produces undefined results. Detecting overlaps at runtime is
+    impractical; callers are responsible for ensuring no aliasing exists.
+
+    On pre-CUDA 13 installs the copies fall back to a Python-level loop
+    over ``cuMemcpyAsync``, so the potential performance benefit of
+    asynchronous batched copies is not realized. ``src_access_order`` values
+    of ``STREAM`` and ``ANY`` are silently ignored on the fallback path
+    (stream-ordered access already satisfies both); ``DURING_API_CALL``
+    raises ``RuntimeError`` instead, since silently downgrading it to
+    stream-ordered access would let a caller reuse the source buffer before
+    the real read happens.
+
+    """
+    cdef tuple src_bufs = Buffer_coerce_batch(srcs, "copy_batch", _SINGLE_COPY_HINT)
+    cdef tuple dst_bufs = Buffer_coerce_batch(dsts, "copy_batch", _SINGLE_COPY_HINT)
+    cdef Py_ssize_t n = len(src_bufs)
+
+    if len(dst_bufs) != n:
+        raise ValueError(
+            f"copy_batch: srcs length {n} does not match dsts length {len(dst_bufs)}"
+        )
+
+    cdef Stream s = Stream_accept(stream)
+
+    if Stream_is_legacy_default_token(s):
+        raise TypeError(
+            "copy_batch does not accept LEGACY_DEFAULT_STREAM; cuMemcpyBatchAsync "
+            "rejects it outright, unlike PER_THREAD_DEFAULT_STREAM, which is a real "
+            "stream to the driver and is accepted. Pass an explicit stream or "
+            "PER_THREAD_DEFAULT_STREAM."
+        )
+
+    cdef cydriver.CUstreamCaptureStatus _cap_status
+    IF CUDA_CORE_BUILD_MAJOR >= 13:
+        HANDLE_RETURN(cydriver.cuStreamGetCaptureInfo(as_cu(s._h_stream), &_cap_status,
+                                                      NULL, NULL, NULL, NULL, NULL))
+    ELSE:
+        HANDLE_RETURN(cydriver.cuStreamGetCaptureInfo(as_cu(s._h_stream), &_cap_status,
+                                                      NULL, NULL, NULL, NULL))
+    if _cap_status == cydriver.CU_STREAM_CAPTURE_STATUS_ACTIVE:
+        raise TypeError(
+            "copy_batch does not support graph capture; "
+            "use GraphNode.memcpy or per-buffer Buffer.copy_to instead"
+        )
+
+    cdef Buffer src_buf
+    cdef Buffer dst_buf
+    cdef Py_ssize_t i
+
+    for i in range(n):
+        src_buf = <Buffer>src_bufs[i]
+        dst_buf = <Buffer>dst_bufs[i]
+        if src_buf.size != dst_buf.size:
+            raise ValueError(
+                f"copy_batch: buffer size mismatch at index {i} "
+                f"(src={src_buf.size}, dst={dst_buf.size})"
+            )
+
+    cdef tuple attr_tuple = _normalize_copy_options(options, n)
+
+    _do_copy_batch(src_bufs, dst_bufs, s, attr_tuple)
+
+
+cdef void _do_copy_batch(tuple src_bufs, tuple dst_bufs, Stream s, tuple attr_tuple):
+    IF CUDA_CORE_BUILD_MAJOR >= 13:
+        # Building against CUDA 13 headers says nothing about the installed
+        # driver, so the run-time version still has to be checked before
+        # calling a 13.0-only entry point (see PRs #2054 / #2064).
+        if _batch_entry_point_available():
+            _do_copy_batch_native(src_bufs, dst_bufs, s, attr_tuple)
+        else:
+            _reject_during_api_call_fallback(attr_tuple)
+            _do_copy_batch_loop(src_bufs, dst_bufs, s)
+    ELSE:
+        _reject_during_api_call_fallback(attr_tuple)
+        _do_copy_batch_loop(src_bufs, dst_bufs, s)
+
+
+cdef void _reject_during_api_call_fallback(tuple attr_tuple):
+    """Raise before the per-copy cuMemcpyAsync loop if any copy needs
+    DURING_API_CALL, which that fallback cannot honor (see
+    _reject_unsupported_during_api_call for why this must raise rather than
+    silently ignore the option, unlike STREAM and ANY).
+    """
+    cdef Py_ssize_t i
+    for i in range(len(attr_tuple)):
+        _reject_unsupported_during_api_call(
+            (<object>attr_tuple[i]).src_access_order,
+            "cuda.core built against CUDA 13 headers and cuda.bindings/driver "
+            "13.0 or newer (cuMemcpyBatchAsync is unavailable here)",
+            index=i,
+        )
+
+
+cdef void _do_copy_batch_loop(tuple src_bufs, tuple dst_bufs, Stream s):
+    """Per-copy cuMemcpyAsync fallback where the batch entry point is absent.
+
+    Issues copies one at a time, so the performance benefit of batching is
+    not realized. STREAM and ANY are silently ignored here (satisfied by
+    stream-ordered cuMemcpyAsync regardless); DURING_API_CALL is rejected by
+    _reject_during_api_call_fallback before this is ever called.
+    """
+    cdef Py_ssize_t n = len(src_bufs)
+    cdef Py_ssize_t i
+    cdef Buffer src_buf
+    cdef Buffer dst_buf
+    cdef size_t nbytes
+    cdef cydriver.CUstream hstream = as_cu(s._h_stream)
+
+    for i in range(n):
+        src_buf = <Buffer>src_bufs[i]
+        dst_buf = <Buffer>dst_bufs[i]
+        nbytes = src_buf._size
+        with nogil:
+            HANDLE_RETURN(cydriver.cuMemcpyAsync(
+                as_cu(dst_buf._h_ptr), as_cu(src_buf._h_ptr), nbytes, hstream))
+
+
+IF CUDA_CORE_BUILD_MAJOR >= 13:
+    cdef void _do_copy_batch_native(tuple src_bufs, tuple dst_bufs, Stream s, tuple attr_tuple):
+        cdef Py_ssize_t n = len(src_bufs)
+        cdef cydriver.CUstream hstream = as_cu(s._h_stream)
+        cdef vector[cydriver.CUdeviceptr] dst_ptrs
+        cdef vector[cydriver.CUdeviceptr] src_ptrs
+        cdef vector[size_t] sizes
+        cdef vector[size_t] attrs_idxs
+        dst_ptrs.resize(n)
+        src_ptrs.resize(n)
+        sizes.resize(n)
+
+        cdef Buffer src_buf
+        cdef Buffer dst_buf
+        cdef Py_ssize_t i
+
+        # Collapse equal neighbouring attributes into runs so a broadcast
+        # attribute reaches the driver once (numAttrs == 1) instead of being
+        # repeated per copy. attrs[k] applies to [attrsIdxs[k], attrsIdxs[k+1]).
+        cdef list run_starts = _attr_run_starts(attr_tuple)
+        cdef vector[cydriver.CUmemcpyAttributes] cu_attrs
+        cdef size_t num_attrs = <size_t>len(run_starts)
+        cu_attrs.reserve(num_attrs)
+        attrs_idxs.reserve(num_attrs)
+        for i in run_starts:
+            cu_attrs.push_back(_to_cu_memcpy_attributes(attr_tuple[i]))
+            attrs_idxs.push_back(<size_t>i)
+
+        for i in range(n):
+            src_buf = <Buffer>src_bufs[i]
+            dst_buf = <Buffer>dst_bufs[i]
+            src_ptrs[i] = as_cu(src_buf._h_ptr)
+            dst_ptrs[i] = as_cu(dst_buf._h_ptr)
+            sizes[i] = src_buf.size
+
+        with nogil:
+            HANDLE_RETURN(cydriver.cuMemcpyBatchAsync(
+                dst_ptrs.data(),
+                src_ptrs.data(),
+                sizes.data(),
+                <size_t>n,
+                cu_attrs.data(),
+                attrs_idxs.data(),
+                num_attrs,
+                hstream,
+            ))
diff --git a/cuda_core/cuda/core/_memory/_device_memory_resource.pyi b/cuda_core/cuda/core/_memory/_device_memory_resource.pyi
index 21862b32b7a..337d03baf4a 100644
--- a/cuda_core/cuda/core/_memory/_device_memory_resource.pyi
+++ b/cuda_core/cuda/core/_memory/_device_memory_resource.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_device_memory_resource.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_device_memory_resource.pyx
 
 import uuid
 from dataclasses import dataclass
@@ -10,6 +8,7 @@ from cuda.core._memory._ipc import IPCAllocationHandle
 from cuda.core._memory._memory_pool import _MemPool
 from cuda.core._memory._peer_access_utils import PeerAccessibleBySetProxy
 
+__all__ = ['DeviceMemoryResource', 'DeviceMemoryResourceOptions']
 
 @dataclass
 class DeviceMemoryResourceOptions:
@@ -116,16 +115,8 @@ class DeviceMemoryResource(_MemPool):
     descriptors from trusted peers, and do not unpickle buffers from
     untrusted sources.
     """
-
-    def __cinit__(self, *args, **kwargs) -> None:
-        ...
-
-    def __init__(self, device_id: Device | int, options: DeviceMemoryResourceOptions | dict[str, object] | None=None) -> None:
-        ...
-
-    def __reduce__(self) -> tuple[object, ...]:
-        ...
-
+    def __init__(self, device_id: Device | int, options: DeviceMemoryResourceOptions | None=None) -> None: ...
+    def __reduce__(self) -> tuple[object, ...]: ...
     @staticmethod
     def from_registry(uuid: uuid.UUID) -> DeviceMemoryResource:
         """
@@ -136,7 +127,6 @@ class DeviceMemoryResource(_MemPool):
         RuntimeError
             If no mapped memory resource is found in the registry.
         """
-
     def register(self, uuid: uuid.UUID) -> DeviceMemoryResource:
         """
         Register a mapped memory resource.
@@ -146,7 +136,6 @@ class DeviceMemoryResource(_MemPool):
         The registered mapped memory resource. If one was previously registered
         with the given key, it is returned.
         """
-
     @classmethod
     def from_allocation_handle(cls, device_id: Device | int, alloc_handle: int | IPCAllocationHandle) -> DeviceMemoryResource:
         """Create a device memory resource from an allocation handle.
@@ -170,7 +159,6 @@ class DeviceMemoryResource(_MemPool):
         -------
             A new device memory resource instance with the imported handle.
         """
-
     @property
     def allocation_handle(self) -> IPCAllocationHandle:
         """Shareable handle for this memory pool (requires IPC).
@@ -178,11 +166,9 @@ class DeviceMemoryResource(_MemPool):
         The handle can be used to share the memory pool with other processes.
         The handle is cached in this `MemoryResource` and owned by it.
         """
-
     @property
     def device_id(self) -> int:
         """The associated device ordinal."""
-
     @property
     def peer_accessible_by(self) -> PeerAccessibleBySetProxy:
         """
@@ -202,19 +188,14 @@ class DeviceMemoryResource(_MemPool):
         >>> dmr.peer_accessible_by.add(2)  # update access to include device 2
         >>> dmr.peer_accessible_by = []    # revoke peer access
         """
-
     @peer_accessible_by.setter
-    def peer_accessible_by(self, devices) -> None:
-        ...
-
+    def peer_accessible_by(self, devices) -> None: ...
     @property
     def is_device_accessible(self) -> bool:
         """Return True. This memory resource provides device-accessible buffers."""
-
     @property
     def is_host_accessible(self) -> bool:
         """Return False. This memory resource does not provide host-accessible buffers."""
-__all__ = ['DeviceMemoryResource', 'DeviceMemoryResourceOptions']
 
 def DMR_mempool_get_access(dmr: DeviceMemoryResource, device_id: int) -> str:
     """
@@ -230,6 +211,4 @@ def DMR_mempool_get_access(dmr: DeviceMemoryResource, device_id: int) -> str:
     str
         Access permissions: "rw" for read-write, "r" for read-only, "" for no access.
     """
-
-def _deep_reduce_device_memory_resource(mr) -> tuple[object, ...]:
-    ...
\ No newline at end of file
+def _deep_reduce_device_memory_resource(mr) -> tuple[object, ...]: ...
diff --git a/cuda_core/cuda/core/_memory/_device_memory_resource.pyx b/cuda_core/cuda/core/_memory/_device_memory_resource.pyx
index 45d8d543ac4..62dc4f9e747 100644
--- a/cuda_core/cuda/core/_memory/_device_memory_resource.pyx
+++ b/cuda_core/cuda/core/_memory/_device_memory_resource.pyx
@@ -5,20 +5,19 @@
 from __future__ import annotations
 
 from cuda.bindings cimport cydriver
+from cuda.core._memory._location cimport cumemlocation_from_id
 from cuda.core._memory._memory_pool cimport (
-    _MemPool, MP_init_create_pool, MP_raise_release_threshold,
+    _MemPool, MP_check_open, MP_init_create_pool, MP_raise_release_threshold,
 )
 from cuda.core._memory cimport _ipc
 from cuda.core._memory._ipc cimport IPCAllocationHandle
-from cuda.core._resource_handles cimport (
-    as_cu,
-    get_device_mempool,
-    get_last_error,
-)
+from cuda.core._resource_handles cimport as_cu, get_device_mempool, get_last_error
 from cuda.core._utils.cuda_utils cimport (
     check_or_create_options,
     HANDLE_RETURN,
 )
+
+import cython
 from dataclasses import dataclass
 import multiprocessing
 import platform  # no-cython-lint
@@ -145,14 +144,16 @@ cdef class DeviceMemoryResource(_MemPool):
     def __cinit__(self, *args, **kwargs) -> None:
         self._dev_id = cydriver.CU_DEVICE_INVALID
 
+    @cython.annotation_typing(False)
     def __init__(
         self,
         device_id: Device | int,
-        options: DeviceMemoryResourceOptions | dict[str, object] | None = None
+        options: DeviceMemoryResourceOptions | None = None
     ) -> None:
         _DMR_init(self, device_id, options)
 
     def __reduce__(self) -> tuple[object, ...]:
+        MP_check_open(self)
         return DeviceMemoryResource.from_registry, (self.uuid,)
 
     @staticmethod
@@ -216,6 +217,7 @@ cdef class DeviceMemoryResource(_MemPool):
         The handle can be used to share the memory pool with other processes.
         The handle is cached in this `MemoryResource` and owned by it.
         """
+        MP_check_open(self)
         if not self.is_ipc_enabled:
             raise RuntimeError("Memory resource is not IPC-enabled")
         return self._ipc_data._alloc_handle
@@ -244,6 +246,7 @@ cdef class DeviceMemoryResource(_MemPool):
         >>> dmr.peer_accessible_by.add(2)  # update access to include device 2
         >>> dmr.peer_accessible_by = []    # revoke peer access
         """
+        MP_check_open(self)
         return PeerAccessibleBySetProxy(self)
 
     @peer_accessible_by.setter
@@ -321,10 +324,8 @@ cpdef str DMR_mempool_get_access(DeviceMemoryResource dmr, int device_id):
 
     cdef int dev_id = Device(device_id).device_id
     cdef cydriver.CUmemAccess_flags flags
-    cdef cydriver.CUmemLocation location
-
-    location.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE
-    location.id = dev_id
+    cdef cydriver.CUmemLocation location = cumemlocation_from_id(
+        cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE, dev_id)
 
     with nogil:
         HANDLE_RETURN(cydriver.cuMemPoolGetAccess(&flags, as_cu(dmr._h_pool), &location))
diff --git a/cuda_core/cuda/core/_memory/_graph_memory_resource.pyi b/cuda_core/cuda/core/_memory/_graph_memory_resource.pyi
index b34f968fdc9..fd23fec5833 100644
--- a/cuda_core/cuda/core/_memory/_graph_memory_resource.pyi
+++ b/cuda_core/cuda/core/_memory/_graph_memory_resource.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_graph_memory_resource.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_graph_memory_resource.pyx
 
 from cuda.core._device import Device
 from cuda.core._memory._buffer import Buffer, MemoryResource
@@ -8,82 +6,59 @@ from cuda.core._stream import Stream
 from cuda.core.graph import GraphBuilder
 from cuda.core.typing import DevicePointerType
 
+__all__ = ['GraphMemoryResource']
 
 class GraphMemoryResourceAttributes:
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @classmethod
-    def _init(cls, device_id: int) -> GraphMemoryResourceAttributes:
-        ...
-
-    def __repr__(self) -> str:
-        ...
-
+    def _init(cls, device_id: int) -> GraphMemoryResourceAttributes: ...
+    def __repr__(self) -> str: ...
     @property
     def reserved_mem_current(self) -> int:
         """Current amount of backing memory allocated."""
-
     @property
     def reserved_mem_high(self) -> int:
         """
         High watermark of backing memory allocated. It can be set to zero to
         reset it to the current usage.
         """
-
     @reserved_mem_high.setter
-    def reserved_mem_high(self, value: int) -> None:
-        ...
-
+    def reserved_mem_high(self, value: int) -> None: ...
     @property
     def used_mem_current(self) -> int:
         """Current amount of memory in use."""
-
     @property
     def used_mem_high(self) -> int:
         """
         High watermark of memory in use. It can be set to zero to reset it to
         the current usage.
         """
-
     @used_mem_high.setter
-    def used_mem_high(self, value: int) -> None:
-        ...
+    def used_mem_high(self, value: int) -> None: ...
 
 class cyGraphMemoryResource(MemoryResource):
-
-    def __cinit__(self, device_id: int) -> None:
-        ...
-
+    def __init__(self, device_id: int) -> None: ...
     def allocate(self, size: int, *, stream: Stream | GraphBuilder) -> Buffer:
         """
         Allocate a buffer of the requested size. See documentation for :obj:`~_memory.MemoryResource`.
         """
-
     def deallocate(self, ptr: DevicePointerType, size: int, *, stream: Stream | GraphBuilder) -> None:
         """
         Deallocate a buffer of the requested size. See documentation for :obj:`~_memory.MemoryResource`.
         """
-
     def close(self) -> None:
         """No operation (provided for compatibility)."""
-
     def trim(self) -> None:
         """Free unused memory that was cached on the specified device for use with graphs back to the OS."""
-
     @property
     def attributes(self) -> GraphMemoryResourceAttributes:
         """Asynchronous allocation attributes related to graphs."""
-
     @property
     def device_id(self) -> int:
         """The associated device ordinal."""
-
     @property
     def is_device_accessible(self) -> bool:
         """Return True. This memory resource provides device-accessible buffers."""
-
     @property
     def is_host_accessible(self) -> bool:
         """Return False. This memory resource does not provide host-accessible buffers."""
@@ -106,11 +81,6 @@ class GraphMemoryResource(cyGraphMemoryResource):
     device_id: int | Device
         Device or Device ordinal for which a graph memory resource is obtained.
     """
-
-    def __new__(cls, device_id: int | Device) -> GraphMemoryResource:
-        ...
-
+    def __new__(cls, device_id: int | Device) -> GraphMemoryResource: ...
     @classmethod
-    def _create(cls, device_id: int) -> GraphMemoryResource:
-        ...
-__all__ = ['GraphMemoryResource']
\ No newline at end of file
+    def _create(cls, device_id: int) -> GraphMemoryResource: ...
diff --git a/cuda_core/cuda/core/_memory/_graph_memory_resource.pyx b/cuda_core/cuda/core/_memory/_graph_memory_resource.pyx
index e845a47b080..67ecf97f58c 100644
--- a/cuda_core/cuda/core/_memory/_graph_memory_resource.pyx
+++ b/cuda_core/cuda/core/_memory/_graph_memory_resource.pyx
@@ -225,7 +225,7 @@ cdef inline Buffer GMR_allocate(cyGraphMemoryResource self, size_t size, Stream
     return Buffer_from_deviceptr_handle(h_ptr, size, self, None)
 
 
-cdef inline void GMR_deallocate(intptr_t ptr, size_t size, Stream stream) noexcept:
+cdef inline void GMR_deallocate(intptr_t ptr, size_t size, Stream stream) except *:
     cdef cydriver.CUstream s = as_cu(stream._h_stream)
     cdef cydriver.CUdeviceptr devptr = <cydriver.CUdeviceptr>ptr
     with nogil:
diff --git a/cuda_core/cuda/core/_memory/_ipc.pyi b/cuda_core/cuda/core/_memory/_ipc.pyi
index 0c912a567bd..ef8f4110f3f 100644
--- a/cuda_core/cuda/core/_memory/_ipc.pyi
+++ b/cuda_core/cuda/core/_memory/_ipc.pyi
@@ -1,41 +1,26 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_ipc.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_ipc.pyx
 
 import uuid
 
+__all__ = []
 
 class IPCDataForBuffer:
     """Data members related to sharing memory buffers via IPC."""
-
-    def __cinit__(self, ipc_descriptor: IPCBufferDescriptor, is_mapped: bool) -> None:
-        ...
-
+    def __init__(self, ipc_descriptor: IPCBufferDescriptor, is_mapped: bool) -> None: ...
     @property
-    def ipc_descriptor(self) -> IPCBufferDescriptor:
-        ...
-
+    def ipc_descriptor(self) -> IPCBufferDescriptor: ...
     @property
-    def is_mapped(self) -> bool:
-        ...
+    def is_mapped(self) -> bool: ...
 
 class IPCDataForMR:
     """Data members related to sharing memory resources via IPC."""
-
-    def __cinit__(self, alloc_handle: IPCAllocationHandle, is_mapped: bool) -> None:
-        ...
-
+    def __init__(self, alloc_handle: IPCAllocationHandle, is_mapped: bool) -> None: ...
     @property
-    def alloc_handle(self) -> IPCAllocationHandle:
-        ...
-
+    def alloc_handle(self) -> IPCAllocationHandle: ...
     @property
-    def is_mapped(self) -> bool:
-        ...
-
+    def is_mapped(self) -> bool: ...
     @property
-    def uuid(self) -> uuid.UUID | None:
-        ...
+    def uuid(self) -> uuid.UUID | None: ...
 
 class IPCBufferDescriptor:
     """Serializable object describing a buffer that can be shared between processes.
@@ -46,48 +31,28 @@ class IPCBufferDescriptor:
     Receivers must treat them as untrusted and import only through
     :meth:`Buffer.from_ipc_descriptor`.
     """
-
-    def __init__(self, *arg, **kwargs) -> None:
-        ...
-
+    def __init__(self, *arg, **kwargs) -> None: ...
     @staticmethod
-    def _init(reserved: bytes, size: int) -> IPCBufferDescriptor:
-        ...
-
-    def __reduce__(self) -> tuple[object, ...]:
-        ...
-
+    def _init(reserved: bytes, size: int) -> IPCBufferDescriptor: ...
+    def __reduce__(self) -> tuple[object, ...]: ...
     @property
-    def size(self) -> int:
-        ...
+    def size(self) -> int: ...
 
 class IPCAllocationHandle:
     """Shareable handle to an IPC-enabled device memory pool."""
-
+    def __init__(self, *arg, **kwargs) -> None: ...
+    @classmethod
+    def _init(cls, handle: int, uuid: uuid.UUID | None) -> IPCAllocationHandle: ...
     def close(self):
         """Close the handle."""
-
-    def __init__(self, *arg, **kwargs) -> None:
-        ...
-
-    @classmethod
-    def _init(cls, handle: int, uuid: uuid.UUID | None) -> IPCAllocationHandle:
-        ...
-
-    def __int__(self) -> int:
-        ...
-
     @property
-    def handle(self) -> int:
-        ...
-
+    def is_closed(self) -> bool:
+        """Whether this allocation handle has been closed."""
+    def __int__(self) -> int: ...
     @property
-    def uuid(self) -> uuid.UUID:
-        ...
-__all__ = ['IPCBufferDescriptor', 'IPCAllocationHandle']
-
-def _reduce_allocation_handle(alloc_handle: IPCAllocationHandle) -> tuple[object, ...]:
-    ...
+    def handle(self) -> int: ...
+    @property
+    def uuid(self) -> uuid.UUID: ...
 
-def _reconstruct_allocation_handle(cls: type, df: object, uuid: uuid.UUID | None) -> IPCAllocationHandle:
-    ...
\ No newline at end of file
+def _reduce_allocation_handle(alloc_handle: IPCAllocationHandle) -> tuple[object, ...]: ...
+def _reconstruct_allocation_handle(cls: type, df: object, uuid: uuid.UUID | None) -> IPCAllocationHandle: ...
diff --git a/cuda_core/cuda/core/_memory/_ipc.pyx b/cuda_core/cuda/core/_memory/_ipc.pyx
index d03f51a26ce..ae8db6589b4 100644
--- a/cuda_core/cuda/core/_memory/_ipc.pyx
+++ b/cuda_core/cuda/core/_memory/_ipc.pyx
@@ -6,8 +6,8 @@ cimport cpython
 
 from libc.stddef cimport size_t
 from cuda.bindings cimport cydriver
-from cuda.core._memory._buffer cimport Buffer, Buffer_from_deviceptr_handle
-from cuda.core._memory._memory_pool cimport _MemPool
+from cuda.core._memory._buffer cimport Buffer, Buffer_check_open, Buffer_from_deviceptr_handle
+from cuda.core._memory._memory_pool cimport _MemPool, MP_check_open
 from cuda.core._stream cimport Stream, Stream_accept
 from cuda.core._resource_handles cimport (
     DevicePtrHandle,
@@ -16,7 +16,6 @@ from cuda.core._resource_handles cimport (
     deviceptr_import_ipc,
     get_last_error,
     as_cu,
-    as_intptr,
     as_py,
 )
 
@@ -29,7 +28,7 @@ import platform
 import uuid
 import weakref
 
-__all__ = ['IPCBufferDescriptor', 'IPCAllocationHandle']
+__all__ = []
 
 
 cdef object registry = weakref.WeakValueDictionary()
@@ -110,6 +109,12 @@ cdef class IPCBufferDescriptor:
         return <const void*><const char*>(self._payload)
 
 
+cdef inline int IPCAllocationHandle_check_open(IPCAllocationHandle self) except -1:
+    if self._h_fd.get() == NULL:
+        raise RuntimeError("IPCAllocationHandle has been closed")
+    return 0
+
+
 cdef class IPCAllocationHandle:
     """Shareable handle to an IPC-enabled device memory pool."""
 
@@ -129,8 +134,13 @@ cdef class IPCAllocationHandle:
         """Close the handle."""
         self._h_fd.reset()
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this allocation handle has been closed."""
+        return self._h_fd.get() == NULL
+
     def __int__(self) -> int:
-        if not self._h_fd or as_intptr(self._h_fd) < 0:
+        if self._h_fd.get() == NULL:
             raise ValueError(
                 f"Cannot convert IPCAllocationHandle to int: the handle (id={id(self)}) is closed."
             )
@@ -146,6 +156,7 @@ cdef class IPCAllocationHandle:
 
 
 def _reduce_allocation_handle(alloc_handle: IPCAllocationHandle) -> tuple[object, ...]:
+    IPCAllocationHandle_check_open(alloc_handle)
     check_multiprocessing_start_method()
     df = multiprocessing.reduction.DupFd(alloc_handle.handle)
     return _reconstruct_allocation_handle, (type(alloc_handle), df, alloc_handle.uuid)
@@ -161,6 +172,7 @@ multiprocessing.reduction.register(IPCAllocationHandle, _reduce_allocation_handl
 # Buffer IPC Implementation
 # -------------------------
 cdef IPCBufferDescriptor Buffer_get_ipc_descriptor(Buffer self):
+    Buffer_check_open(self)
     if not self.memory_resource.is_ipc_enabled:
         raise RuntimeError("Memory resource is not IPC-enabled")
     cdef cydriver.CUmemPoolPtrExportData data
@@ -177,6 +189,7 @@ cdef Buffer Buffer_from_ipc_descriptor(
     cls, _MemPool mr, IPCBufferDescriptor ipc_descriptor, stream
 ):
     """Import a buffer that was exported from another process."""
+    MP_check_open(mr)
     if not mr.is_ipc_enabled:
         raise RuntimeError("Memory resource is not IPC-enabled")
     cdef size_t payload_size = len(ipc_descriptor._payload)
@@ -214,6 +227,9 @@ cdef Buffer Buffer_from_ipc_descriptor(
 # ---------------------------
 
 cdef _MemPool MP_from_allocation_handle(cls, alloc_handle):
+    if isinstance(alloc_handle, IPCAllocationHandle):
+        IPCAllocationHandle_check_open(<IPCAllocationHandle>alloc_handle)
+
     # Quick exit for registry hits.
     uuid = getattr(alloc_handle, 'uuid', None)  # no-cython-lint
     mr = registry.get(uuid)
@@ -222,6 +238,7 @@ cdef _MemPool MP_from_allocation_handle(cls, alloc_handle):
             raise TypeError(
                 f"Registry contains a {type(mr).__name__} for uuid "
                 f"{uuid}, but {cls.__name__} was requested")
+        MP_check_open(<_MemPool>mr)
         return mr
 
     # Ensure we have an allocation handle. Duplicate the file descriptor, if
@@ -258,16 +275,23 @@ cdef _MemPool MP_from_allocation_handle(cls, alloc_handle):
 
 
 cdef _MemPool MP_from_registry(uuid):
+    cdef _MemPool mr
     try:
-        return registry[uuid]
+        mr = registry[uuid]
+        MP_check_open(mr)
+        return mr
     except KeyError:
         raise RuntimeError(f"Memory resource {uuid} was not found") from None
 
 
 cdef _MemPool MP_register(_MemPool self, uuid):
+    MP_check_open(self)
     existing = registry.get(uuid)
     if existing is not None:
+        MP_check_open(<_MemPool>existing)
         return existing
+    if not self.is_ipc_enabled:
+        raise RuntimeError("Memory resource is not IPC-enabled")
     assert self.uuid is None or self.uuid == uuid
     registry[uuid] = self
     self._ipc_data._alloc_handle._uuid = uuid
@@ -276,6 +300,7 @@ cdef _MemPool MP_register(_MemPool self, uuid):
 
 cdef IPCAllocationHandle MP_export_mempool(_MemPool self):
     # Note: This is Linux only (int for file descriptor)
+    MP_check_open(self)
     cdef int fd
     with nogil:
         HANDLE_RETURN(cydriver.cuMemPoolExportToShareableHandle(
diff --git a/cuda_core/cuda/core/_memory/_legacy.py b/cuda_core/cuda/core/_memory/_legacy.py
index 4acbcb54e3a..f3dff33a133 100644
--- a/cuda_core/cuda/core/_memory/_legacy.py
+++ b/cuda_core/cuda/core/_memory/_legacy.py
@@ -94,49 +94,5 @@ def is_host_accessible(self) -> bool:
 
     @property
     def device_id(self) -> int:
-        """This memory resource is not bound to any GPU."""
-        raise RuntimeError("a pinned memory resource is not bound to any GPU")
-
-
-class _SynchronousMemoryResource(MemoryResource):
-    __slots__ = ("_device_id",)
-
-    def __init__(self, device_id: int) -> None:
-        from .._device import Device
-
-        self._device_id = Device(device_id).device_id
-
-    def allocate(self, size: int, *, stream: Stream | GraphBuilder | None = None) -> Buffer:
-        # cuMemAlloc is synchronous; stream is accepted (and validated)
-        # for interface conformance but not used.
-        from cuda.core._stream import Stream_accept
-
-        if stream is not None:
-            Stream_accept(stream)
-        if size:
-            err, ptr = driver.cuMemAlloc(size)
-            raise_if_driver_error(err)
-        else:
-            ptr = 0
-        return Buffer._init(ptr, size, self)
-
-    def deallocate(self, ptr: DevicePointerType, size: int, *, stream: Stream | GraphBuilder | None = None) -> None:
-        from cuda.core._stream import Stream_accept
-
-        if stream is not None:
-            Stream_accept(stream).sync()
-        if size:
-            (err,) = driver.cuMemFree(ptr)
-            raise_if_driver_error(err)
-
-    @property
-    def is_device_accessible(self) -> bool:
-        return True
-
-    @property
-    def is_host_accessible(self) -> bool:
-        return False
-
-    @property
-    def device_id(self) -> int:
-        return self._device_id
+        """Return -1. Pinned memory is host memory and is not bound to a specific device."""
+        return -1
diff --git a/cuda_core/cuda/core/_memory/_location.pxd b/cuda_core/cuda/core/_memory/_location.pxd
new file mode 100644
index 00000000000..a9cc525827b
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_location.pxd
@@ -0,0 +1,62 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+# Conversion helpers for the driver's ``CUmemLocation`` struct.
+#
+# Header-only so both the managed-memory ops and the batched copy path can
+# cimport it without either module depending on the other.
+#
+# Both helpers use field assignment rather than Cython struct literals
+# (``CUmemLocation(type=..., id=...)``) so this source keeps compiling if a
+# future generated ``cydriver.pxd`` adds a sibling member to the struct's
+# anonymous union (e.g. CUDA 13.4's ``localized`` arm): Cython's struct-literal
+# coercion warns "Not all members given for struct" whenever a call site does
+# not name every declared member, and cuda_core promotes that warning to a
+# build error.
+
+from cuda.bindings cimport cydriver
+
+
+cdef inline cydriver.CUmemLocation cumemlocation_from_id(
+    cydriver.CUmemLocationType loc_type, int loc_id
+):
+    """Build a ``CUmemLocation`` whose active payload is the ``id`` field.
+
+    ``loc_type`` must be one of the kinds whose payload is ``id``
+    (``CU_MEM_LOCATION_TYPE_DEVICE``, ``HOST``, ``HOST_NUMA``, or
+    ``HOST_NUMA_CURRENT``); it must not be used for
+    ``CU_MEM_LOCATION_TYPE_DEVICE_LOCALITY_DOMAIN``, whose payload is a
+    separate ``localized`` union member.
+
+    For call sites that already carry a ``CUmemLocationType`` value (e.g.
+    from a pool-configuration parameter), rather than the ``kind`` string
+    used by :func:`to_cumemlocation`.
+    """
+    cdef cydriver.CUmemLocation cu_loc
+    cu_loc.type = loc_type
+    cu_loc.id = loc_id
+    return cu_loc
+
+
+IF CUDA_CORE_BUILD_MAJOR >= 13:
+    cdef inline cydriver.CUmemLocation to_cumemlocation(str kind, int loc_id):
+        if kind == "device":
+            return cumemlocation_from_id(
+                cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE, loc_id)
+        elif kind == "host":
+            return cumemlocation_from_id(
+                cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST, 0)
+        elif kind == "host_numa":
+            return cumemlocation_from_id(
+                cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST_NUMA, loc_id)
+        elif kind == "host_numa_current":
+            return cumemlocation_from_id(
+                cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT, 0)
+        else:
+            raise ValueError(f"unknown location kind: {kind!r}")
+ELSE:
+    cdef inline cydriver.CUmemLocation to_cumemlocation(str kind, int loc_id):
+        raise NotImplementedError(
+            "CUmemLocation requires cuda.core built against CUDA 13 headers"
+        )
diff --git a/cuda_core/cuda/core/_memory/_location.pyi b/cuda_core/cuda/core/_memory/_location.pyi
new file mode 100644
index 00000000000..1a10ac85487
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_location.pyi
@@ -0,0 +1 @@
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_location.pxd
diff --git a/cuda_core/cuda/core/_memory/_managed_buffer.py b/cuda_core/cuda/core/_memory/_managed_buffer.py
index 9a8333e7094..646f83221e8 100644
--- a/cuda_core/cuda/core/_memory/_managed_buffer.py
+++ b/cuda_core/cuda/core/_memory/_managed_buffer.py
@@ -25,6 +25,8 @@
     from cuda.core._stream import Stream
     from cuda.core.graph import GraphBuilder
 
+__all__ = ["ManagedBuffer"]
+
 
 _INT_SIZE = 4
 
@@ -43,7 +45,13 @@
 _ATTR_ACCESSED_BY = _RANGE.CU_MEM_RANGE_ATTRIBUTE_ACCESSED_BY
 
 
+def _check_open(buf: Buffer) -> None:
+    if buf.is_closed:
+        raise RuntimeError("Buffer has been closed")
+
+
 def _get_int_attr(buf: Buffer, attribute: Any) -> int:
+    _check_open(buf)
     return int(handle_return(driver.cuMemRangeGetAttribute(_INT_SIZE, attribute, buf.handle, buf.size)))
 
 
@@ -53,6 +61,7 @@ def _query_accessed_by(buf: Buffer) -> list[Device | Host]:
     Driver fills an int32 array: device id, ``-1`` = host, ``-2`` = empty.
     Sized to ``cuDeviceGetCount() + 1`` (every visible device plus host).
     """
+    _check_open(buf)
     num_devices = handle_return(driver.cuDeviceGetCount())
     n = num_devices + 1
     raw = handle_return(driver.cuMemRangeGetAttribute(n * _INT_SIZE, _ATTR_ACCESSED_BY, buf.handle, buf.size))
@@ -152,6 +161,8 @@ def from_handle(
         size: int,
         mr: MemoryResource | None = None,
         owner: object | None = None,
+        *,
+        stream: Stream | GraphBuilder | None = None,
     ) -> Buffer:
         """Wrap an existing managed-memory pointer in a :class:`ManagedBuffer`.
 
@@ -171,8 +182,15 @@ def from_handle(
         owner : object, optional
             An object that keeps the underlying allocation alive.
             ``owner`` and ``mr`` cannot both be specified.
+        stream : Stream | GraphBuilder, optional
+            Keyword-only. The stream used to order the buffer's deallocation
+            when ``mr`` owns the pointer. Defaults to ``default_stream()``.
+            Recording a default-stream token requires a CUDA context to be
+            current. If the buffer may be freed from a different host thread,
+            pass a stream other than the per-thread default stream, which
+            refers to a different stream on each thread.
         """
-        return cls._init(ptr, size, mr=mr, owner=owner)
+        return cls._init(ptr, size, mr=mr, owner=owner, stream=stream)
 
     @property
     def read_mostly(self) -> bool:
@@ -217,10 +235,12 @@ def preferred_location(self, value: Device | Host | None) -> None:
     @property
     def accessed_by(self) -> AccessedBySetProxy:
         """Live set-like view of ``set_accessed_by`` locations."""
+        _check_open(self)
         return AccessedBySetProxy(self)
 
     @accessed_by.setter
     def accessed_by(self, locations: Iterable[Device | Host]) -> None:
+        _check_open(self)
         # Validate every target before issuing any cuMemAdvise so an invalid
         # element can't leave accessed_by partially mutated.
         target: set[Device | Host] = set()
diff --git a/cuda_core/cuda/core/_memory/_managed_memory_ops.pyi b/cuda_core/cuda/core/_memory/_managed_memory_ops.pyi
index ca29265f103..8327e154f70 100644
--- a/cuda_core/cuda/core/_memory/_managed_memory_ops.pyi
+++ b/cuda_core/cuda/core/_memory/_managed_memory_ops.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_managed_memory_ops.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_managed_memory_ops.pyx
 
 from collections.abc import Sequence
 
@@ -11,6 +9,7 @@ from cuda.core._memory._buffer import Buffer
 from cuda.core._stream import Stream
 from cuda.core._utils.cuda_utils import driver
 
+_SINGLE_MANAGED_HINT = 'the ManagedBuffer instance method'
 
 def discard_batch(stream: Stream | GraphBuilder, buffers: Sequence[Buffer]) -> None:
     """Discard a batch of managed-memory ranges.
@@ -33,17 +32,14 @@ def discard_batch(stream: Stream | GraphBuilder, buffers: Sequence[Buffer]) -> N
     NotImplementedError
         On a CUDA 12 build of ``cuda.core``.
     """
-
 def _do_single_discard_py(buf: Buffer, stream: Stream | GraphBuilder | None) -> None:
     """Internal: single-buffer discard for ManagedBuffer.discard()."""
-
 def _advise_one(buf: Buffer, advice: driver.CUmem_advise, location: Device | Host | None) -> None:
     """Internal: apply managed-memory advice to a single buffer.
 
     Used by :class:`ManagedBuffer` property setters. Not part of the
     public API.
     """
-
 def prefetch_batch(stream: Stream | GraphBuilder, buffers: Sequence[Buffer], locations: Device | Host | Sequence[Device | Host]) -> None:
     """Prefetch a batch of managed-memory ranges to target locations.
 
@@ -67,16 +63,12 @@ def prefetch_batch(stream: Stream | GraphBuilder, buffers: Sequence[Buffer], loc
     ``cuMemPrefetchAsync`` per buffer (no batched driver entry point on
     CUDA 12). CUDA 13 builds use ``cuMemPrefetchBatchAsync`` directly.
     """
-
 def _do_single_prefetch_py(buf: Buffer, location: Device | Host | None, stream: Stream | GraphBuilder | None) -> None:
     """Internal: single-buffer prefetch for ManagedBuffer.prefetch().
 
     Uses cuMemPrefetchAsync (works on CUDA 12 and 13).
     """
-
-def _read_preferred_location_v2(buf: Buffer) -> Device | Host | None:
-    ...
-
+def _read_preferred_location_v2(buf: Buffer) -> Device | Host | None: ...
 def discard_prefetch_batch(stream: Stream | GraphBuilder, buffers: Sequence[Buffer], locations: Device | Host | Sequence[Device | Host]) -> None:
     """Discard a batch of managed-memory ranges and prefetch them to target locations.
 
@@ -99,7 +91,6 @@ def discard_prefetch_batch(stream: Stream | GraphBuilder, buffers: Sequence[Buff
     NotImplementedError
         On a CUDA 12 build of ``cuda.core``.
     """
-
 def _do_single_discard_prefetch_py(buf: Buffer, location: Device | Host | None, stream: Stream | GraphBuilder | None) -> None:
     """Internal: single-buffer discard+prefetch for
-    ManagedBuffer.discard_prefetch()."""
\ No newline at end of file
+    ManagedBuffer.discard_prefetch()."""
diff --git a/cuda_core/cuda/core/_memory/_managed_memory_ops.pyx b/cuda_core/cuda/core/_memory/_managed_memory_ops.pyx
index c07fb719dd9..649468ad020 100644
--- a/cuda_core/cuda/core/_memory/_managed_memory_ops.pyx
+++ b/cuda_core/cuda/core/_memory/_managed_memory_ops.pyx
@@ -11,7 +11,13 @@ IF CUDA_CORE_BUILD_MAJOR >= 13:
     from libcpp.vector cimport vector
 
 from cuda.bindings cimport cydriver
-from cuda.core._memory._buffer cimport Buffer
+from cuda.core._memory._buffer cimport Buffer, Buffer_check_open, Buffer_coerce_batch  # no-cython-lint
+
+# to_cumemlocation / cumemlocation_from_id are referenced only from CUDA 13
+# branches. cython-lint does not evaluate compile-time IF blocks, so they
+# need a pragma to be seen as used.
+from cuda.core._memory._location cimport cumemlocation_from_id  # no-cython-lint
+from cuda.core._memory._location cimport to_cumemlocation  # no-cython-lint
 from cuda.core._resource_handles cimport as_cu
 from cuda.core._stream cimport Stream, Stream_accept
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
@@ -52,35 +58,19 @@ cdef void _require_managed_buffer(Buffer self, str what):
         raise ValueError(f"{what} requires a managed-memory allocation")
 
 
-cdef tuple _coerce_batch_buffers(object buffers, str what):
+_SINGLE_MANAGED_HINT = "the ManagedBuffer instance method"
+
+
+cdef inline tuple _coerce_batch_buffers(object buffers, str what):
     """Coerce ``buffers`` to a tuple[Buffer, ...]; rejects a single Buffer.
 
     For single-buffer operations, use the corresponding ManagedBuffer
     instance method instead.
     """
-    cdef Buffer buf
-    cdef list out
-    if isinstance(buffers, Buffer):
-        raise TypeError(
-            f"{what}: pass a sequence of Buffers; for a single buffer use "
-            f"the ManagedBuffer instance method"
-        )
-    if isinstance(buffers, Sequence):
-        if not buffers:
-            raise ValueError(f"{what}: empty buffers sequence")
-        out = []
-        for t in buffers:
-            buf = <Buffer?>t
-            out.append(buf)
-        return tuple(out)
-    raise TypeError(
-        f"{what}: buffers must be a sequence of Buffer, "
-        f"got {type(buffers).__name__}"
-    )
+    return Buffer_coerce_batch(buffers, what, _SINGLE_MANAGED_HINT)
 
 
 cdef tuple _broadcast_locations(object location, Py_ssize_t n, bint allow_none, str what):
-    cdef object coerced
     if isinstance(location, Sequence):
         if len(location) != n:
             raise ValueError(
@@ -88,29 +78,11 @@ cdef tuple _broadcast_locations(object location, Py_ssize_t n, bint allow_none,
                 f"targets length {n}"
             )
         return tuple(_coerce_location(loc, allow_none=allow_none) for loc in location)
-    coerced = _coerce_location(location, allow_none=allow_none)
+    cdef object coerced = _coerce_location(location, allow_none=allow_none)
     return tuple([coerced] * n)
 
 
-IF CUDA_CORE_BUILD_MAJOR >= 13:
-    # Convert a _LocSpec dataclass to a cydriver.CUmemLocation struct.
-    cdef inline cydriver.CUmemLocation _to_cumemlocation(object loc):
-        cdef cydriver.CUmemLocation out
-        cdef str kind = loc.kind
-        if kind == "device":
-            out.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE
-            out.id = <int>loc.id
-        elif kind == "host":
-            out.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST
-            out.id = 0
-        elif kind == "host_numa":
-            out.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST_NUMA
-            out.id = <int>loc.id
-        else:  # host_numa_current
-            out.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST_NUMA_CURRENT
-            out.id = 0
-        return out
-ELSE:
+IF CUDA_CORE_BUILD_MAJOR < 13:
     # CUDA 12 cuMemPrefetchAsync takes a device ordinal (-1 = host).
     cdef inline int _to_legacy_device(object loc) except? -2:
         cdef str kind = loc.kind
@@ -223,10 +195,10 @@ cdef void _do_single_advise(Buffer buf, object advice_value, object loc, bint al
             # Driver ignores location for read_mostly / unset_preferred_location
             # advice values but still validates the CUmemLocation; pass a
             # host placeholder.
-            cu_loc.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST
-            cu_loc.id = 0
+            cu_loc = cumemlocation_from_id(
+                cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_HOST, 0)
         else:
-            cu_loc = _to_cumemlocation(loc)
+            cu_loc = to_cumemlocation(loc.kind, loc.id)
         with nogil:
             HANDLE_RETURN(cydriver.cuMemAdvise(cu_ptr, nbytes, advice_enum, cu_loc))
     ELSE:
@@ -290,7 +262,7 @@ cdef void _do_single_prefetch(Buffer buf, object loc, Stream s):
     cdef size_t nbytes = buf._size
     cdef cydriver.CUstream hstream = as_cu(s._h_stream)
     IF CUDA_CORE_BUILD_MAJOR >= 13:
-        cdef cydriver.CUmemLocation cu_loc = _to_cumemlocation(loc)
+        cdef cydriver.CUmemLocation cu_loc = to_cumemlocation(loc.kind, loc.id)
         with nogil:
             HANDLE_RETURN(cydriver.cuMemPrefetchAsync(cu_ptr, nbytes, cu_loc, 0, hstream))
     ELSE:
@@ -318,6 +290,7 @@ IF CUDA_CORE_BUILD_MAJOR >= 13:
 
         Returns Device | Host | None.
         """
+        Buffer_check_open(buf)
         cdef cydriver.CUdeviceptr cu_ptr = as_cu(buf._h_ptr)
         cdef size_t nbytes = buf._size
         cdef int loc_type = 0
@@ -359,11 +332,13 @@ IF CUDA_CORE_BUILD_MAJOR >= 13:
         loc_indices.resize(n)
         cdef Buffer buf
         cdef Py_ssize_t i
+        cdef object loc_spec
         for i in range(n):
             buf = <Buffer>bufs[i]
             ptrs[i] = as_cu(buf._h_ptr)
             sizes[i] = buf._size
-            loc_arr[i] = _to_cumemlocation(locs[i])
+            loc_spec = locs[i]
+            loc_arr[i] = to_cumemlocation(loc_spec.kind, loc_spec.id)
             loc_indices[i] = <size_t>i
         with nogil:
             HANDLE_RETURN(fn(
diff --git a/cuda_core/cuda/core/_memory/_managed_memory_resource.pyi b/cuda_core/cuda/core/_memory/_managed_memory_resource.pyi
index 7f3f584e5ca..8659a7f5933 100644
--- a/cuda_core/cuda/core/_memory/_managed_memory_resource.pyi
+++ b/cuda_core/cuda/core/_memory/_managed_memory_resource.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_managed_memory_resource.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_managed_memory_resource.pyx
 
 from dataclasses import dataclass
 
@@ -10,6 +8,7 @@ from cuda.core._stream import Stream
 from cuda.core.graph import GraphBuilder
 from cuda.core.typing import ManagedMemoryLocationType
 
+__all__ = ['ManagedMemoryResource', 'ManagedMemoryResourceOptions']
 
 @dataclass
 class ManagedMemoryResourceOptions:
@@ -76,10 +75,7 @@ class ManagedMemoryResource(_MemPool):
     IPC (Inter-Process Communication) is not currently supported for managed
     memory pools.
     """
-
-    def __init__(self, options: ManagedMemoryResourceOptions | dict[str, object] | None=None) -> None:
-        ...
-
+    def __init__(self, options: ManagedMemoryResourceOptions | None=None) -> None: ...
     def allocate(self, size: int, *, stream: Stream | GraphBuilder) -> ManagedBuffer:
         """Allocate a managed-memory buffer of the requested size.
 
@@ -101,11 +97,9 @@ class ManagedMemoryResource(_MemPool):
             and instance methods (``prefetch``, ``discard``,
             ``discard_prefetch``).
         """
-
     @property
     def device_id(self) -> int:
         """The preferred device ordinal, or -1 if the preferred location is not a device."""
-
     @property
     def preferred_location(self) -> tuple[ManagedMemoryLocationType, int | None] | None:
         """The preferred location for managed memory allocations.
@@ -115,19 +109,15 @@ class ManagedMemoryResource(_MemPool):
         ``"host"``, or ``"host_numa"``, and *id* is the device ordinal,
         ``None`` (for ``"host"``), or the NUMA node ID, respectively.
         """
-
     @property
     def is_device_accessible(self) -> bool:
         """Return True. This memory resource provides device-accessible buffers."""
-
     @property
     def is_host_accessible(self) -> bool:
         """Return True. This memory resource provides host-accessible buffers."""
-
     @property
     def is_managed(self) -> bool:
         """Return True. This memory resource provides managed (unified) memory buffers."""
-__all__ = ['ManagedMemoryResource', 'ManagedMemoryResourceOptions']
 
 def reset_concurrent_access_warning() -> None:
-    """Reset the concurrent access warning flag for testing purposes."""
\ No newline at end of file
+    """Reset the concurrent access warning flag for testing purposes."""
diff --git a/cuda_core/cuda/core/_memory/_managed_memory_resource.pyx b/cuda_core/cuda/core/_memory/_managed_memory_resource.pyx
index d5a637a7b50..738a2ff4af7 100644
--- a/cuda_core/cuda/core/_memory/_managed_memory_resource.pyx
+++ b/cuda_core/cuda/core/_memory/_managed_memory_resource.pyx
@@ -6,13 +6,14 @@ from __future__ import annotations
 
 from cuda.bindings cimport cydriver
 
-from cuda.core._memory._memory_pool cimport _MemPool, _MP_allocate
+from cuda.core._memory._memory_pool cimport _MemPool, _MP_allocate, MP_check_open
 from cuda.core._memory._memory_pool cimport MP_init_create_pool, MP_init_current_pool  # no-cython-lint
 from cuda.core._stream cimport Stream, Stream_accept
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 from cuda.core._utils.cuda_utils cimport check_or_create_options  # no-cython-lint
 from cuda.core._utils.cuda_utils import CUDAError  # no-cython-lint
 
+import cython
 from dataclasses import dataclass
 import threading
 from typing import TYPE_CHECKING
@@ -97,7 +98,8 @@ cdef class ManagedMemoryResource(_MemPool):
     memory pools.
     """
 
-    def __init__(self, options: ManagedMemoryResourceOptions | dict[str, object] | None = None) -> None:
+    @cython.annotation_typing(False)
+    def __init__(self, options: ManagedMemoryResourceOptions | None = None) -> None:
         _MMR_init(self, options)
 
     def allocate(self, size_t size, *, stream: Stream | GraphBuilder) -> ManagedBuffer:
@@ -121,6 +123,7 @@ cdef class ManagedMemoryResource(_MemPool):
             and instance methods (``prefetch``, ``discard``,
             ``discard_prefetch``).
         """
+        MP_check_open(self)
         assert isinstance(stream, Stream), "Only Stream is supported for managed memory allocations"
         if self.is_mapped:
             raise TypeError("Cannot allocate from a mapped IPC-enabled memory resource")
diff --git a/cuda_core/cuda/core/_memory/_memory_pool.pxd b/cuda_core/cuda/core/_memory/_memory_pool.pxd
index 3a6c3107cfd..23e5eba588e 100644
--- a/cuda_core/cuda/core/_memory/_memory_pool.pxd
+++ b/cuda_core/cuda/core/_memory/_memory_pool.pxd
@@ -37,6 +37,12 @@ cdef int MP_init_current_pool(
 cdef int MP_raise_release_threshold(_MemPool self) except? -1
 
 
+cdef inline int MP_check_open(_MemPool self) except -1:
+    if not self._h_pool:
+        raise RuntimeError(f"{self.__class__.__name__} has been closed")
+    return 0
+
+
 # Allocate from this pool, returning an instance of `cls` (defaulting to
 # Buffer). Subclasses (e.g. ManagedMemoryResource) pass their own buffer
 # subclass so their `allocate` returns the typed object.
diff --git a/cuda_core/cuda/core/_memory/_memory_pool.pyi b/cuda_core/cuda/core/_memory/_memory_pool.pyi
index 7f8c64aedda..8d5e56d9f26 100644
--- a/cuda_core/cuda/core/_memory/_memory_pool.pyi
+++ b/cuda_core/cuda/core/_memory/_memory_pool.pyi
@@ -1,10 +1,7 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_memory_pool.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_memory_pool.pyx
 
 import uuid
 
-import cython
 from cuda.core._memory._buffer import Buffer, MemoryResource
 from cuda.core._stream import Stream
 from cuda.core.graph import GraphBuilder
@@ -13,56 +10,47 @@ from cuda.core.typing import DevicePointerType
 
 class _MemPoolAttributes:
     """Provides access to memory pool attributes."""
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
-    def __repr__(self) -> str:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
+    def __repr__(self) -> str: ...
     @property
     def reuse_follow_event_dependencies(self) -> bool:
         """Allow memory to be reused when there are event dependencies between streams."""
-
     @property
     def reuse_allow_opportunistic(self) -> bool:
         """Allow reuse of completed frees without dependencies."""
-
     @property
     def reuse_allow_internal_dependencies(self) -> bool:
         """Allow insertion of new stream dependencies for memory reuse."""
-
     @property
     def release_threshold(self) -> int:
         """Amount of reserved memory to hold before OS release."""
-
     @property
     def reserved_mem_current(self) -> int:
         """Current amount of backing memory allocated."""
-
     @property
     def reserved_mem_high(self) -> int:
         """High watermark of backing memory allocated."""
-
     @property
     def used_mem_current(self) -> int:
         """Current amount of memory in use."""
-
     @property
     def used_mem_high(self) -> int:
         """High watermark of memory in use."""
 
 class _MemPool(MemoryResource):
-
-    def __cinit__(self) -> None:
-        ...
-
+    def __init__(self) -> None: ...
     def close(self) -> None:
-        """
-        Close the memory resource and destroy the associated memory pool
-        if owned.
-        """
+        """Release this object's reference to the memory pool.
 
+        New allocations and operations requiring this object's pool handle are
+        rejected afterward. For owned pools, release of the underlying pool's
+        resources is deferred until all outstanding allocations are freed and
+        pending free operations complete. :meth:`deallocate` remains available
+        after :meth:`close` so existing allocations can still be released.
+        """
+    @property
+    def is_closed(self) -> bool:
+        """Whether this memory resource has been closed."""
     def allocate(self, size: int, *, stream: Stream | GraphBuilder) -> Buffer:
         """Allocate a buffer of the requested size.
 
@@ -81,7 +69,6 @@ class _MemPool(MemoryResource):
             The allocated buffer object, which is accessible on the device that this memory
             resource was created for.
         """
-
     def deallocate(self, ptr: DevicePointerType, size: int, *, stream: Stream | GraphBuilder) -> None:
         """Deallocate a buffer previously allocated by this resource.
 
@@ -96,34 +83,27 @@ class _MemPool(MemoryResource):
             asynchronously. Must be passed explicitly; pass
             ``device.default_stream`` to use the default stream.
         """
-
     @property
-    @cython.critical_section
     def attributes(self) -> _MemPoolAttributes:
         """Memory pool attributes."""
-
     @property
     def handle(self) -> object:
         """Handle to the underlying memory pool."""
-
     @property
     def is_handle_owned(self) -> bool:
         """Whether the memory resource handle is owned. If False, ``close`` has no effect."""
-
     @property
     def is_ipc_enabled(self) -> bool:
         """Whether this memory resource has IPC enabled."""
-
     @property
     def is_mapped(self) -> bool:
         """
         Whether this is a mapping of an IPC-enabled memory resource from
         another process.  If True, allocation is not permitted.
         """
-
     @property
     def uuid(self) -> uuid.UUID | None:
         """
         A universally unique identifier for this memory resource. Meaningful
         only for IPC-enabled memory resources.
-        """
\ No newline at end of file
+        """
diff --git a/cuda_core/cuda/core/_memory/_memory_pool.pyx b/cuda_core/cuda/core/_memory/_memory_pool.pyx
index cf7c48068f1..6e5d26e7df8 100644
--- a/cuda_core/cuda/core/_memory/_memory_pool.pyx
+++ b/cuda_core/cuda/core/_memory/_memory_pool.pyx
@@ -12,6 +12,9 @@ from libc.string cimport memset
 from cuda.bindings cimport cydriver
 from cuda.core._memory._buffer cimport Buffer, Buffer_from_deviceptr_handle, MemoryResource
 from cuda.core._memory cimport _ipc
+# cumemlocation_from_id is referenced only from a CUDA 13 branch. cython-lint
+# does not evaluate compile-time IF blocks, so it needs a pragma to be seen as used.
+from cuda.core._memory._location cimport cumemlocation_from_id  # no-cython-lint
 from cuda.core._stream cimport Stream_accept, Stream
 from cuda.core._resource_handles cimport (
     MemoryPoolHandle,
@@ -127,12 +130,21 @@ cdef class _MemPool(MemoryResource):
         self._attributes = None
 
     def close(self) -> None:
-        """
-        Close the memory resource and destroy the associated memory pool
-        if owned.
+        """Release this object's reference to the memory pool.
+
+        New allocations and operations requiring this object's pool handle are
+        rejected afterward. For owned pools, release of the underlying pool's
+        resources is deferred until all outstanding allocations are freed and
+        pending free operations complete. :meth:`deallocate` remains available
+        after :meth:`close` so existing allocations can still be released.
         """
         _MP_close(self)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this memory resource has been closed."""
+        return self._h_pool.get() == NULL
+
     def allocate(self, size_t size, *, stream: Stream | GraphBuilder) -> Buffer:
         """Allocate a buffer of the requested size.
 
@@ -151,6 +163,7 @@ cdef class _MemPool(MemoryResource):
             The allocated buffer object, which is accessible on the device that this memory
             resource was created for.
         """
+        MP_check_open(self)
         if self.is_mapped:
             raise TypeError("Cannot allocate from a mapped IPC-enabled memory resource")
         cdef Stream s = Stream_accept(stream)
@@ -183,8 +196,12 @@ cdef class _MemPool(MemoryResource):
     @cython.critical_section
     def attributes(self) -> _MemPoolAttributes:
         """Memory pool attributes."""
+        MP_check_open(self)
+        cdef _MemPoolAttributes attributes
         if self._attributes is None:
-            self._attributes = _MemPoolAttributes._init(self._h_pool)
+            attributes = _MemPoolAttributes._init(self._h_pool)
+            if self._attributes is None:
+                self._attributes = attributes
         return self._attributes
 
     @property
@@ -275,19 +292,17 @@ cdef int MP_init_current_pool(
     Requires CUDA 13+.
     """
     IF CUDA_CORE_BUILD_MAJOR >= 13:
-        cdef cydriver.CUmemLocation loc
         cdef cydriver.CUmemoryPool pool
-        loc.id = loc_id
-        loc.type = loc_type
+        cdef cydriver.CUmemLocation loc = cumemlocation_from_id(loc_type, loc_id)
         with nogil:
             HANDLE_RETURN(cydriver.cuMemGetMemPool(&pool, &loc, alloc_type))
         self._h_pool = create_mempool_handle_ref(pool)
         self._mempool_owned = False
+        return 0
     ELSE:
         raise RuntimeError(
             "Getting the current memory pool requires CUDA 13.0 or later"
         )
-    return 0
 
 
 cdef int MP_raise_release_threshold(_MemPool self) except? -1:
@@ -297,6 +312,7 @@ cdef int MP_raise_release_threshold(_MemPool self) except? -1:
     the OS as soon as there are no active suballocations.  Setting it to
     ULLONG_MAX avoids repeated OS round-trips.
     """
+    MP_check_open(self)
     cdef cydriver.cuuint64_t current_threshold
     cdef cydriver.cuuint64_t max_threshold = ULLONG_MAX
     with nogil:
@@ -327,6 +343,7 @@ cdef inline int check_not_capturing(cydriver.CUstream s) except?-1 nogil:
 
 
 cdef Buffer _MP_allocate(_MemPool self, size_t size, Stream stream, type cls = Buffer):
+    MP_check_open(self)
     cdef cydriver.CUstream s = as_cu(stream._h_stream)
     cdef DevicePtrHandle h_ptr
     with nogil:
@@ -345,15 +362,11 @@ cdef Buffer _MP_allocate(_MemPool self, size_t size, Stream stream, type cls = B
 
 cdef inline void _MP_deallocate(
     _MemPool self, uintptr_t ptr, size_t size, Stream stream
-) noexcept nogil:
+) except *:
     cdef cydriver.CUstream s = as_cu(stream._h_stream)
     cdef cydriver.CUdeviceptr devptr = <cydriver.CUdeviceptr>ptr
-    cdef cydriver.CUresult r
     with nogil:
-        r = cydriver.cuMemFreeAsync(devptr, s)
-        if r != cydriver.CUDA_ERROR_INVALID_CONTEXT:
-            HANDLE_RETURN(r)
-
+        HANDLE_RETURN(cydriver.cuMemFreeAsync(devptr, s))
 
 cdef inline _MP_close(_MemPool self):
     if not self._h_pool:
diff --git a/cuda_core/cuda/core/_memory/_peer_access_utils.pyi b/cuda_core/cuda/core/_memory/_peer_access_utils.pyi
index fa2b5c490a4..83dde54945e 100644
--- a/cuda_core/cuda/core/_memory/_peer_access_utils.pyi
+++ b/cuda_core/cuda/core/_memory/_peer_access_utils.pyi
@@ -1,14 +1,13 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_peer_access_utils.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_peer_access_utils.pyx
 
-from __future__ import annotations
-
-from collections.abc import Callable, Iterable, Iterator, Set
+from collections.abc import Callable, Iterable, Iterator, MutableSet, Set
 from dataclasses import dataclass
-from typing import Any
+from typing import Any, TypeVar
 
 from cuda.core._device import Device
 from cuda.core._memory._device_memory_resource import DeviceMemoryResource
 
+_S = TypeVar('_S')
 
 @dataclass(frozen=True)
 class PeerAccessPlan:
@@ -17,7 +16,7 @@ class PeerAccessPlan:
     to_add: tuple[int, ...]
     to_remove: tuple[int, ...]
 
-class PeerAccessibleBySetProxy:
+class PeerAccessibleBySetProxy(MutableSet['Device']):
     """Live driver-backed view of the peer devices granted access to a memory pool.
 
     Reads (``__contains__``, ``__iter__``, ``len(...)``) call ``cuMemPoolGetAccess``;
@@ -37,58 +36,33 @@ class PeerAccessibleBySetProxy:
     """
     __slots__ = ('_mr',)
 
-    def __init__(self, mr: DeviceMemoryResource) -> None:
-        ...
-
+    def __init__(self, mr: DeviceMemoryResource) -> None: ...
     @classmethod
-    def _from_iterable(cls, it: Iterable[Device]) -> set[Device]:
-        ...
-
-    def __contains__(self, value: object) -> bool:
-        ...
-
-    def __iter__(self) -> Iterator[Device]:
-        ...
-
-    def __len__(self) -> int:
-        ...
-
+    def _from_iterable(cls, it: Iterable[_S]) -> set[_S]: ...
+    def __contains__(self, value: object) -> bool: ...
+    def __iter__(self) -> Iterator[Device]: ...
+    def __len__(self) -> int: ...
     def add(self, value: Device | int) -> None:
         """Grant peer access from ``value`` to allocations in this pool."""
-
     def discard(self, value: Device | int) -> None:
         """Revoke peer access from ``value`` to allocations in this pool."""
-
     def clear(self) -> None:
         """Revoke all peer access in a single driver call."""
-
     def update(self, *others: Iterable[Device | int]) -> None:
         """Grant peer access to every device in ``others`` in one driver call."""
-
     def difference_update(self, *others: Iterable[Device | int]) -> None:
         """Revoke peer access for every device in ``others`` in one driver call."""
-
     def intersection_update(self, *others: Iterable[Device | int]) -> None:
         """Restrict peer access to the intersection in a single driver call."""
-
     def symmetric_difference_update(self, other: Iterable[Device | int]) -> None:
         """Toggle peer access for every device in ``other`` in one driver call."""
-
-    def __ior__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:
-        ...
-
-    def __iand__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:
-        ...
-
-    def __isub__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:
-        ...
-
-    def __ixor__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:
+    def __ior__(self, other: Set[Any]) -> PeerAccessibleBySetProxy: # type: ignore[misc]
         ...
-
-    def __repr__(self) -> str:
+    def __iand__(self, other: Set[Any]) -> PeerAccessibleBySetProxy: ...
+    def __isub__(self, other: Set[Any]) -> PeerAccessibleBySetProxy: ...
+    def __ixor__(self, other: Set[Any]) -> PeerAccessibleBySetProxy: # type: ignore[misc]
         ...
-
+    def __repr__(self) -> str: ...
     def _apply(self, additions, removals) -> None:
         """Compute the diff and issue a single ``cuMemPoolSetAccess``.
 
@@ -98,24 +72,12 @@ class PeerAccessibleBySetProxy:
         removals bypass that check (revoking is always permitted).
         """
 
-def replace_peer_accessible_by(mr: DeviceMemoryResource, devices: object) -> None:
-    """Replace the full peer-access set in a single batched driver call.
-
-    Backs the ``mr.peer_accessible_by = [...]`` setter. Uses the same planner
-    as the proxy's bulk ops; the only difference is that adds and removes are
-    derived from the symmetric difference between current driver state and the
-    requested target set.
-    """
-
 def normalize_peer_access_targets(owner_device_id: int, requested_devices: Iterable[object], *, resolve_device_id: Callable[[object], int]) -> tuple[int, ...]:
     """Return sorted, unique peer device IDs, excluding the owner device."""
-
 def plan_peer_access_update(owner_device_id: int, current_peer_ids: Iterable[int], requested_devices: Iterable[object], *, resolve_device_id: Callable[[object], int], can_access_peer: Callable[[int], bool]) -> PeerAccessPlan:
     """Compute the peer-access target state and add/remove deltas."""
-
 def _resolve_peer_device_id(value: Device | int | None) -> int:
     """Coerce ``Device | int`` into a device-ordinal int."""
-
 def _set_pool_access(mr: object, to_add: tuple[int, ...], to_remove: tuple[int, ...]) -> None:
     """Issue one ``cuMemPoolSetAccess`` for the given add/remove deltas.
 
@@ -127,7 +89,6 @@ def _set_pool_access(mr: object, to_add: tuple[int, ...], to_remove: tuple[int,
     Preconditions: ``len(to_add) + len(to_remove) > 0`` (the caller is
     responsible for skipping empty diffs).
     """
-
 def _apply_peer_access_diff(mr: DeviceMemoryResource, to_add: Iterable[int], to_remove: Iterable[int]) -> None:
     """Apply a peer-access diff in at most one driver call.
 
@@ -135,4 +96,12 @@ def _apply_peer_access_diff(mr: DeviceMemoryResource, to_add: Iterable[int], to_
     ``peer_accessible_by`` setter routes through this function. Empty diffs
     short-circuit here so the driver-level helper :func:`_set_pool_access` is
     only invoked when there is actual work for ``cuMemPoolSetAccess`` to do.
-    """
\ No newline at end of file
+    """
+def replace_peer_accessible_by(mr: DeviceMemoryResource, devices: object) -> None:
+    """Replace the full peer-access set in a single batched driver call.
+
+    Backs the ``mr.peer_accessible_by = [...]`` setter. Uses the same planner
+    as the proxy's bulk ops; the only difference is that adds and removes are
+    derived from the symmetric difference between current driver state and the
+    requested target set.
+    """
diff --git a/cuda_core/cuda/core/_memory/_peer_access_utils.pyx b/cuda_core/cuda/core/_memory/_peer_access_utils.pyx
index 9a035378ecf..21f88258f57 100644
--- a/cuda_core/cuda/core/_memory/_peer_access_utils.pyx
+++ b/cuda_core/cuda/core/_memory/_peer_access_utils.pyx
@@ -6,10 +6,14 @@ from __future__ import annotations
 
 from collections.abc import Callable, Iterable, Iterator, MutableSet, Set
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, TypeVar
+
+_S = TypeVar("_S")
 
 from cuda.bindings cimport cydriver
 from cuda.core._memory._device_memory_resource cimport DeviceMemoryResource
+from cuda.core._memory._location cimport cumemlocation_from_id
+from cuda.core._memory._memory_pool cimport MP_check_open
 from cuda.core._resource_handles cimport as_cu
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 from cpython.mem cimport PyMem_Malloc, PyMem_Free
@@ -79,12 +83,19 @@ def _resolve_peer_device_id(value: Device | int | None) -> int:
 
 # ---- driver-touching helpers (cdef inline, called from .pyx code) -----------
 
+cdef inline DeviceMemoryResource _check_peer_access_open(object mr):
+    cdef DeviceMemoryResource mr_typed = <DeviceMemoryResource>mr
+    MP_check_open(mr_typed)
+    return mr_typed
+
+
 cdef inline tuple _query_peer_access_ids(DeviceMemoryResource mr):
     """Return the current peer device IDs as a sorted tuple of ints.
 
     The full driver loop runs inside a single ``nogil`` block. Because
     ``range(total)`` ascends, the result is already sorted.
     """
+    MP_check_open(mr)
     cdef int total
     cdef int dev_id
     cdef int owner_id = mr._dev_id
@@ -92,7 +103,7 @@ cdef inline tuple _query_peer_access_ids(DeviceMemoryResource mr):
     cdef cydriver.CUmemLocation location
     cdef cydriver.CUmemoryPool h_pool = as_cu(mr._h_pool)
     cdef vector[int] peers
-    cdef size_t i, n
+    cdef size_t i
 
     location.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE
 
@@ -106,17 +117,16 @@ cdef inline tuple _query_peer_access_ids(DeviceMemoryResource mr):
             if flags == cydriver.CUmemAccess_flags.CU_MEM_ACCESS_FLAGS_PROT_READWRITE:
                 peers.push_back(dev_id)
 
-    n = peers.size()
+    cdef size_t n = peers.size()
     return tuple(peers[i] for i in range(n))
 
 
 cdef inline bint _peer_access_includes(DeviceMemoryResource mr, int dev_id):
     """Return True if peer access from ``dev_id`` is currently granted."""
+    MP_check_open(mr)
     cdef cydriver.CUmemAccess_flags flags
-    cdef cydriver.CUmemLocation location
-
-    location.type = cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE
-    location.id = dev_id
+    cdef cydriver.CUmemLocation location = cumemlocation_from_id(
+        cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE, dev_id)
     with nogil:
         HANDLE_RETURN(cydriver.cuMemPoolGetAccess(&flags, as_cu(mr._h_pool), &location))
     return flags == cydriver.CUmemAccess_flags.CU_MEM_ACCESS_FLAGS_PROT_READWRITE
@@ -134,6 +144,7 @@ def _set_pool_access(mr: object, to_add: tuple[int, ...], to_remove: tuple[int,
     responsible for skipping empty diffs).
     """
     cdef DeviceMemoryResource mr_typed = <DeviceMemoryResource>mr
+    MP_check_open(mr_typed)
     cdef size_t count = len(to_add) + len(to_remove)
     cdef cydriver.CUmemAccessDesc* access_desc = NULL
     cdef size_t i = 0
@@ -169,6 +180,7 @@ def _apply_peer_access_diff(mr: DeviceMemoryResource, to_add: Iterable[int], to_
     short-circuit here so the driver-level helper :func:`_set_pool_access` is
     only invoked when there is actual work for ``cuMemPoolSetAccess`` to do.
     """
+    MP_check_open(mr)
     add_tuple = tuple(to_add)
     remove_tuple = tuple(to_remove)
     if not add_tuple and not remove_tuple:
@@ -184,6 +196,7 @@ cpdef void replace_peer_accessible_by(DeviceMemoryResource mr, object devices):
     derived from the symmetric difference between current driver state and the
     requested target set.
     """
+    MP_check_open(mr)
     from cuda.core._device import Device
 
     this_dev = Device(mr._dev_id)
@@ -224,7 +237,7 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
         self._mr = mr
 
     @classmethod
-    def _from_iterable(cls, it: Iterable[Device]) -> set[Device]:  # type: ignore[override]
+    def _from_iterable(cls, it: Iterable[_S]) -> set[_S]:
         # Binary set operators (&, |, -, ^) collect their result through
         # _from_iterable. Returning a plain set lets the user reason about
         # the result independently of any pool's driver state.
@@ -233,27 +246,29 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
     # --- abstract MutableSet methods ---
 
     def __contains__(self, value: object) -> bool:
+        cdef DeviceMemoryResource mr = _check_peer_access_open(self._mr)
         try:
             dev_id = _resolve_peer_device_id(value)
         except (TypeError, ValueError):
             return False
-        cdef DeviceMemoryResource mr = <DeviceMemoryResource>self._mr
         if dev_id == mr._dev_id:
             return False
         return _peer_access_includes(mr, dev_id)
 
     def __iter__(self) -> Iterator[Device]:
+        cdef DeviceMemoryResource mr = _check_peer_access_open(self._mr)
         from cuda.core._device import Device
 
-        return iter(Device(dev_id) for dev_id in _query_peer_access_ids(self._mr))
+        return iter(Device(dev_id) for dev_id in _query_peer_access_ids(mr))
 
     def __len__(self) -> int:
-        return len(_query_peer_access_ids(self._mr))
+        cdef DeviceMemoryResource mr = _check_peer_access_open(self._mr)
+        return len(_query_peer_access_ids(mr))
 
     def add(self, value: Device | int) -> None:
         """Grant peer access from ``value`` to allocations in this pool."""
+        cdef DeviceMemoryResource mr = _check_peer_access_open(self._mr)
         dev_id = _resolve_peer_device_id(value)
-        cdef DeviceMemoryResource mr = <DeviceMemoryResource>self._mr
         if dev_id == mr._dev_id:
             return
         if _peer_access_includes(mr, dev_id):
@@ -265,11 +280,11 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
 
     def discard(self, value: Device | int) -> None:
         """Revoke peer access from ``value`` to allocations in this pool."""
+        cdef DeviceMemoryResource mr = _check_peer_access_open(self._mr)
         try:
             dev_id = _resolve_peer_device_id(value)
         except (TypeError, ValueError):
             return
-        cdef DeviceMemoryResource mr = <DeviceMemoryResource>self._mr
         if dev_id == mr._dev_id:
             return
         if not _peer_access_includes(mr, dev_id):
@@ -280,10 +295,12 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
 
     def clear(self) -> None:
         """Revoke all peer access in a single driver call."""
+        _check_peer_access_open(self._mr)
         self._apply((), _query_peer_access_ids(self._mr))
 
     def update(self, *others: Iterable[Device | int]) -> None:
         """Grant peer access to every device in ``others`` in one driver call."""
+        _check_peer_access_open(self._mr)
         to_add = []
         for other in others:
             to_add.extend(other)
@@ -292,6 +309,7 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
 
     def difference_update(self, *others: Iterable[Device | int]) -> None:
         """Revoke peer access for every device in ``others`` in one driver call."""
+        _check_peer_access_open(self._mr)
         revoke_ids = set()
         for other in others:
             for value in other:
@@ -306,6 +324,7 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
 
     def intersection_update(self, *others: Iterable[Device | int]) -> None:
         """Restrict peer access to the intersection in a single driver call."""
+        _check_peer_access_open(self._mr)
         keep_ids = None
         for other in others:
             ids = set()
@@ -324,6 +343,7 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
 
     def symmetric_difference_update(self, other: Iterable[Device | int]) -> None:
         """Toggle peer access for every device in ``other`` in one driver call."""
+        _check_peer_access_open(self._mr)
         toggle_ids = set()
         for value in other:
             try:
@@ -336,7 +356,7 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
         if to_add or to_remove:
             self._apply(to_add, to_remove)
 
-    def __ior__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:
+    def __ior__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:  # type: ignore[misc]
         self.update(other)
         return self
 
@@ -351,7 +371,7 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
             self.difference_update(other)
         return self
 
-    def __ixor__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:
+    def __ixor__(self, other: Set[Any]) -> PeerAccessibleBySetProxy:  # type: ignore[misc]
         self.symmetric_difference_update(other)
         return self
 
@@ -370,7 +390,7 @@ class PeerAccessibleBySetProxy(MutableSet["Device"]):
         """
         from cuda.core._device import Device
 
-        cdef DeviceMemoryResource mr = <DeviceMemoryResource>self._mr
+        cdef DeviceMemoryResource mr = _check_peer_access_open(self._mr)
         owner_id = mr._dev_id
         owner = Device(owner_id)
         current = _query_peer_access_ids(mr)
diff --git a/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyi b/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyi
index a83cd8ea581..7c9aa1f6ecd 100644
--- a/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyi
+++ b/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyi
@@ -1,13 +1,15 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memory/_pinned_memory_resource.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_pinned_memory_resource.pyx
 
 import uuid
 from dataclasses import dataclass
 
+from cuda.core._memory._buffer import Buffer
 from cuda.core._memory._ipc import IPCAllocationHandle
 from cuda.core._memory._memory_pool import _MemPool
+from cuda.core._stream import Stream
+from cuda.core.graph import GraphBuilder
 
+__all__ = ['PinnedMemoryResource', 'PinnedMemoryResourceOptions']
 
 @dataclass
 class PinnedMemoryResourceOptions:
@@ -63,6 +65,14 @@ class PinnedMemoryResource(_MemPool):
 
     Notes
     -----
+    The device associated with ``stream`` must support host memory pools. If
+    ``numa_id`` is set or derived for IPC, it must support host NUMA memory pools.
+    You can query these capabilities through
+    ``Device.properties.host_memory_pools_supported`` and
+    ``Device.properties.host_numa_memory_pools_supported``. If the required pool
+    is unsupported and stream-ordered allocation is not needed, use
+    :class:`LegacyPinnedMemoryResource`.
+
     To create an IPC-Enabled memory resource (MR) that is capable of sharing
     allocations between processes, specify ``ipc_enabled=True`` in the initializer
     option. When IPC is enabled and ``numa_id`` is not specified, the NUMA node
@@ -72,13 +82,10 @@ class PinnedMemoryResource(_MemPool):
 
     See :class:`DeviceMemoryResource` for more details on IPC usage patterns.
     """
-
-    def __init__(self, options: PinnedMemoryResourceOptions | dict[str, object] | None=None) -> None:
-        ...
-
-    def __reduce__(self) -> tuple[object, ...]:
-        ...
-
+    def __init__(self, options: PinnedMemoryResourceOptions | None=None) -> None: ...
+    def allocate(self, size: int, *, stream: Stream | GraphBuilder) -> Buffer:
+        """Allocate a host-pinned buffer asynchronously on the supplied stream."""
+    def __reduce__(self) -> tuple[object, ...]: ...
     @staticmethod
     def from_registry(uuid: uuid.UUID) -> PinnedMemoryResource:
         """
@@ -89,7 +96,6 @@ class PinnedMemoryResource(_MemPool):
         RuntimeError
             If no mapped memory resource is found in the registry.
         """
-
     def register(self, uuid: uuid.UUID) -> PinnedMemoryResource:
         """
         Register a mapped memory resource.
@@ -99,7 +105,6 @@ class PinnedMemoryResource(_MemPool):
         The registered mapped memory resource. If one was previously registered
         with the given key, it is returned.
         """
-
     @classmethod
     def from_allocation_handle(cls, alloc_handle: int | IPCAllocationHandle) -> PinnedMemoryResource:
         """Create a host-pinned memory resource from an allocation handle.
@@ -118,7 +123,6 @@ class PinnedMemoryResource(_MemPool):
         -------
             A new host-pinned memory resource instance with the imported handle.
         """
-
     @property
     def allocation_handle(self) -> IPCAllocationHandle:
         """Shareable handle for this memory pool (requires IPC).
@@ -126,23 +130,17 @@ class PinnedMemoryResource(_MemPool):
         The handle can be used to share the memory pool with other processes.
         The handle is cached in this `MemoryResource` and owned by it.
         """
-
     @property
     def device_id(self) -> int:
         """Return -1. Pinned memory is host memory and is not associated with a specific device."""
-
     @property
     def numa_id(self) -> int:
         """The host NUMA node ID used for pool placement, or -1 for OS-managed placement."""
-
     @property
     def is_device_accessible(self) -> bool:
         """Return True. This memory resource provides device-accessible buffers."""
-
     @property
     def is_host_accessible(self) -> bool:
         """Return True. This memory resource provides host-accessible buffers."""
-__all__ = ['PinnedMemoryResource', 'PinnedMemoryResourceOptions']
 
-def _deep_reduce_pinned_memory_resource(mr: object) -> tuple[object, ...]:
-    ...
\ No newline at end of file
+def _deep_reduce_pinned_memory_resource(mr: object) -> tuple[object, ...]: ...
diff --git a/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyx b/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyx
index 4335fbb41c2..18621fb08bc 100644
--- a/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyx
+++ b/cuda_core/cuda/core/_memory/_pinned_memory_resource.pyx
@@ -5,14 +5,23 @@
 from __future__ import annotations
 
 from cuda.bindings cimport cydriver
-from cuda.core._memory._memory_pool cimport _MemPool, MP_init_create_pool, MP_init_current_pool
+from cuda.core._memory._buffer cimport Buffer
+from cuda.core._memory._memory_pool cimport (
+    _MemPool,
+    _MP_allocate,
+    MP_check_open,
+    MP_init_create_pool,
+    MP_init_current_pool,
+)
 from cuda.core._memory cimport _ipc
 from cuda.core._memory._ipc cimport IPCAllocationHandle
+from cuda.core._stream cimport Stream, Stream_accept
 from cuda.core._utils.cuda_utils cimport (
     check_or_create_options,
     HANDLE_RETURN,
 )
 
+import cython
 from dataclasses import dataclass
 import multiprocessing
 import platform  # no-cython-lint
@@ -20,6 +29,11 @@ import uuid
 
 from cuda.core._utils.cuda_utils import check_multiprocessing_start_method
 
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from cuda.core.graph import GraphBuilder
+
 __all__ = ['PinnedMemoryResource', 'PinnedMemoryResourceOptions']
 
 
@@ -78,6 +92,14 @@ cdef class PinnedMemoryResource(_MemPool):
 
     Notes
     -----
+    The device associated with ``stream`` must support host memory pools. If
+    ``numa_id`` is set or derived for IPC, it must support host NUMA memory pools.
+    You can query these capabilities through
+    ``Device.properties.host_memory_pools_supported`` and
+    ``Device.properties.host_numa_memory_pools_supported``. If the required pool
+    is unsupported and stream-ordered allocation is not needed, use
+    :class:`LegacyPinnedMemoryResource`.
+
     To create an IPC-Enabled memory resource (MR) that is capable of sharing
     allocations between processes, specify ``ipc_enabled=True`` in the initializer
     option. When IPC is enabled and ``numa_id`` is not specified, the NUMA node
@@ -88,10 +110,33 @@ cdef class PinnedMemoryResource(_MemPool):
     See :class:`DeviceMemoryResource` for more details on IPC usage patterns.
     """
 
-    def __init__(self, options: PinnedMemoryResourceOptions | dict[str, object] | None = None) -> None:
+    @cython.annotation_typing(False)
+    def __init__(self, options: PinnedMemoryResourceOptions | None = None) -> None:
         _PMR_init(self, options)
 
+    def allocate(self, size_t size, *, stream: Stream | GraphBuilder) -> Buffer:
+        """Allocate a host-pinned buffer asynchronously on the supplied stream."""
+        MP_check_open(self)
+        if self.is_mapped:
+            raise TypeError("Cannot allocate from a mapped IPC-enabled memory resource")
+        cdef Stream s = Stream_accept(stream)
+        device = s.device
+        cdef bint supported = (
+            device.properties.host_numa_memory_pools_supported
+            if self._numa_id >= 0
+            else device.properties.host_memory_pools_supported
+        )
+
+        if not supported:
+            raise RuntimeError(
+                f"CUDA device {device.device_id} does not support the requested "
+                "host memory pool for PinnedMemoryResource. Use "
+                "LegacyPinnedMemoryResource if memory-pool features are not required."
+            )
+        return _MP_allocate(self, size, s)
+
     def __reduce__(self) -> tuple[object, ...]:
+        MP_check_open(self)
         return PinnedMemoryResource.from_registry, (self.uuid,)
 
     @staticmethod
@@ -155,6 +200,7 @@ cdef class PinnedMemoryResource(_MemPool):
         The handle can be used to share the memory pool with other processes.
         The handle is cached in this `MemoryResource` and owned by it.
         """
+        MP_check_open(self)
         if not self.is_ipc_enabled:
             raise RuntimeError("Memory resource is not IPC-enabled")
         return self._ipc_data._alloc_handle
diff --git a/cuda_core/cuda/core/_memory/_synchronous_memory_resource.pyi b/cuda_core/cuda/core/_memory/_synchronous_memory_resource.pyi
new file mode 100644
index 00000000000..73136b896b9
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_synchronous_memory_resource.pyi
@@ -0,0 +1,23 @@
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memory/_synchronous_memory_resource.pyx
+
+from cuda.core._context import Context
+from cuda.core._memory._buffer import Buffer, MemoryResource
+from cuda.core._stream import Stream
+from cuda.core.graph import GraphBuilder
+from cuda.core.typing import DevicePointerType
+
+__all__ = []
+
+class _SynchronousMemoryResource(MemoryResource):
+    __slots__ = ('_context', '_device_id')
+
+    def __init__(self, device_id: int, context=None) -> None: ...
+    def _resolve_context(self) -> Context: ...
+    def allocate(self, size: int, *, stream: Stream | GraphBuilder | None=None) -> Buffer: ...
+    def deallocate(self, ptr: DevicePointerType, size: int, *, stream: Stream | GraphBuilder | None=None) -> None: ...
+    @property
+    def is_device_accessible(self) -> bool: ...
+    @property
+    def is_host_accessible(self) -> bool: ...
+    @property
+    def device_id(self) -> int: ...
diff --git a/cuda_core/cuda/core/_memory/_synchronous_memory_resource.pyx b/cuda_core/cuda/core/_memory/_synchronous_memory_resource.pyx
new file mode 100644
index 00000000000..f02f38f69b1
--- /dev/null
+++ b/cuda_core/cuda/core/_memory/_synchronous_memory_resource.pyx
@@ -0,0 +1,115 @@
+# SPDX-FileCopyrightText: Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+from libc.stdint cimport uintptr_t
+
+from cuda.bindings cimport cydriver
+from cuda.core._context cimport Context
+from cuda.core._memory._buffer cimport Buffer, MemoryResource
+from cuda.core._resource_handles cimport (
+    ContextHandle,
+    create_context_bound_legacy_stream,
+    deviceptr_alloc_raw,
+    get_last_error,
+    get_primary_context,
+)
+from cuda.core._stream cimport Stream, Stream_accept, Stream_is_default_token
+from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
+
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from cuda.core.graph import GraphBuilder
+    from cuda.core.typing import DevicePointerType
+
+__all__ = []
+
+
+class _SynchronousMemoryResource(MemoryResource):
+    __slots__ = ("_context", "_device_id")
+
+    def __init__(self, device_id: int, context=None) -> None:
+        from .._device import Device
+
+        self._device_id = Device(device_id).device_id
+        # Resolved lazily (in _resolve_context) so that construction with
+        # context=None does no CUDA work; the primary context is retained
+        # only once actually needed, on the first allocate()/deallocate().
+        self._context = context
+
+    def _resolve_context(self) -> Context:
+        cdef ContextHandle h_context
+        if self._context is None:
+            h_context = get_primary_context(self._device_id)
+            if not h_context:
+                HANDLE_RETURN(get_last_error())
+            self._context = Context._from_handle(
+                Context, h_context, self._device_id)
+        return self._context
+
+    def allocate(
+        self,
+        size_t size,
+        *,
+        stream: Stream | GraphBuilder | None = None,
+    ) -> Buffer:
+        # cuMemAlloc/cuMemFree are synchronous; a caller-supplied stream is
+        # accepted (and validated) for interface conformance and, if it is a
+        # real stream, recorded as the stream that orders deallocation.
+        cdef Context context = self._resolve_context()
+        cdef Stream dealloc_stream = None
+        if stream is not None:
+            dealloc_stream = Stream_accept(stream)
+        if dealloc_stream is None or Stream_is_default_token(dealloc_stream):
+            # A default-stream token carries no context of its own; Buffer._init
+            # would bind it to whichever context is current when it records the
+            # deallocation stream (and fail if none is). Bind it to this
+            # resource's context instead, so Buffer teardown frees in the right
+            # context no matter what is current then. Always the legacy token:
+            # a per-thread token would also arm the cross-thread PTDS warning,
+            # which is noise for a synchronous resource.
+            dealloc_stream = Stream._from_handle(
+                Stream, create_context_bound_legacy_stream(context._h_context))
+
+        cdef cydriver.CUdeviceptr ptr = 0
+        if size:
+            with nogil:
+                HANDLE_RETURN(deviceptr_alloc_raw(&ptr, size, context._h_context))
+        return Buffer._init(<uintptr_t>ptr, size, self, stream=dealloc_stream)
+
+    def deallocate(
+        self,
+        ptr: DevicePointerType,
+        size_t size,
+        *,
+        stream: Stream | GraphBuilder | None = None,
+    ) -> None:
+        if stream is not None:
+            Stream_accept(stream).sync()
+        # No context switch here, by design (settled in the review of #2750):
+        # cuMemFree does not need a current context. The driver resolves the
+        # allocation's owning context from the pointer through unified
+        # addressing and frees it there (cuapiMemFree_common: "a current
+        # context is not required to free the device memory"). On the Buffer
+        # teardown path the C++ deleter has additionally already made the
+        # recorded deallocation context, bound by allocate() above, current.
+        cdef cydriver.CUdeviceptr devptr
+        if size:
+            devptr = <cydriver.CUdeviceptr><uintptr_t>int(ptr)
+            with nogil:
+                HANDLE_RETURN(cydriver.cuMemFree(devptr))
+
+    @property
+    def is_device_accessible(self) -> bool:
+        return True
+
+    @property
+    def is_host_accessible(self) -> bool:
+        return False
+
+    @property
+    def device_id(self) -> int:
+        return self._device_id
diff --git a/cuda_core/cuda/core/_memory/_virtual_memory_resource.py b/cuda_core/cuda/core/_memory/_virtual_memory_resource.py
index f30e6e3838d..2c4f3f6867e 100644
--- a/cuda_core/cuda/core/_memory/_virtual_memory_resource.py
+++ b/cuda_core/cuda/core/_memory/_virtual_memory_resource.py
@@ -33,6 +33,16 @@
 
 __all__ = ["VirtualMemoryResource", "VirtualMemoryResourceOptions"]
 
+# Location types whose physical backing lives in host memory. Shared by
+# VirtualMemoryResource.__init__ and is_host_accessible so the two cannot drift.
+_HOST_LOCATION_TYPES = frozenset(
+    {
+        VirtualMemoryLocationType.HOST,
+        VirtualMemoryLocationType.HOST_NUMA,
+        VirtualMemoryLocationType.HOST_NUMA_CURRENT,
+    }
+)
+
 
 @dataclass
 class VirtualMemoryResourceOptions:
@@ -46,10 +56,9 @@ class VirtualMemoryResourceOptions:
     location_type: :obj:`~_memory.VirtualMemoryLocationType` | str
         Controls the location of the allocation.
     handle_type: :obj:`~_memory.VirtualMemoryHandleType` | str
-        Export handle type for the physical allocation. Use
-        ``"posix_fd"`` on Linux if you plan to
-        import/export the allocation (required for cuMemRetainAllocationHandle).
-        Use `None` if you don't need an exportable handle.
+        Export handle type for the physical allocation. Use ``"posix_fd"`` on
+        Linux if you plan to import/export the allocation. Use `None` if you
+        don't need an exportable handle.
     gpu_direct_rdma: bool
         Hint that the allocation should be GDR-capable (if supported).
     granularity: :obj:`~_memory.VirtualMemoryGranularityType` | str
@@ -170,8 +179,7 @@ def __init__(self, device_id: Device | int, config: VirtualMemoryResourceOptions
         self.config: VirtualMemoryResourceOptions = check_or_create_options(  # type: ignore[assignment]
             VirtualMemoryResourceOptions, config, "VirtualMemoryResource options", keep_none=False
         )
-        # Matches ("host", "host_numa", "host_numa_current")
-        if "host" in self.config.location_type:
+        if self.config.location_type in _HOST_LOCATION_TYPES:
             self.device = None
 
         if not self.device and self.config.location_type == "device":
@@ -221,6 +229,10 @@ def modify_allocation(
         Buffer
             The same buffer with updated size and properties, preserving the original pointer
         """
+        if not isinstance(buf, Buffer):
+            raise TypeError(f"buf must be a Buffer, got {type(buf).__name__}")
+        if buf.is_closed:
+            raise RuntimeError("Buffer has been closed")
         if config is not None:
             self.config = config
 
@@ -342,10 +354,9 @@ def _grow_allocation_fast_path(
             # All succeeded, cancel undo actions
             trans.commit()
 
-        # Update the buffer size (pointer stays the same)
-        # TODO: #2049 This is a real bug, accessing _size which doesn't exist.
-        # Fix bug and remove the "type: ignore[attr-defined]" comment.
-        buf._size = new_size  # type: ignore[attr-defined]
+        # Update the buffer size (pointer stays the same). `Buffer.size` has
+        # no public setter, so this reaches into the private attribute.
+        buf._size = new_size
         return buf
 
     def _grow_allocation_slow_path(
@@ -610,7 +621,7 @@ def is_host_accessible(self) -> bool:
         """
         Indicates whether the allocated memory is accessible from the host.
         """
-        return self.config.location_type == "host"
+        return self.config.location_type in _HOST_LOCATION_TYPES
 
     @property
     def device_id(self) -> int:
diff --git a/cuda_core/cuda/core/_memoryview.pyi b/cuda_core/cuda/core/_memoryview.pyi
index e0ed0d3cf0d..6084734d037 100644
--- a/cuda_core/cuda/core/_memoryview.pyi
+++ b/cuda_core/cuda/core/_memoryview.pyi
@@ -1,19 +1,21 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_memoryview.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_memoryview.pyx
 
 import functools
 from collections.abc import Callable
-from typing import Any
+from typing import Any, TypedDict
 
 import numpy
 from cuda.core._layout import _StridedLayout
 from cuda.core._memory import Buffer
 from cuda.core._stream import Stream
+from cuda.core._tensor_map import TensorMapDescriptorOptions
 
 from ._dlpack import *
 
 
+class PyTypeObject(TypedDict):
+    tp_dict: Any
+
 class StridedMemoryView:
     """A class holding metadata of a strided dense array/tensor.
 
@@ -70,10 +72,13 @@ class StridedMemoryView:
         it will be the Buffer instance passed to the method.
 
     """
+    ptr: int
+    device_id: int
+    is_device_accessible: bool
+    readonly: bool
+    exporting_obj: object
 
-    def __init__(self, obj: object=None, stream_ptr: int | None=None) -> None:
-        ...
-
+    def __init__(self, obj: object | None=None, stream_ptr: int | None=None) -> None: ...
     @classmethod
     def from_dlpack(cls, obj: object, stream_ptr: int | None=None) -> StridedMemoryView:
         """Create a view from an object supporting the `DLPack <https://dmlc.github.io/dlpack/latest/>`_ protocol.
@@ -86,7 +91,6 @@ class StridedMemoryView:
         stream_ptr : int, optional
             Stream pointer for synchronization. If ``None``, no synchronization is performed.
         """
-
     @classmethod
     def from_cuda_array_interface(cls, obj: object, stream_ptr: int | None=None) -> StridedMemoryView:
         """Create a view from an object supporting the `__cuda_array_interface__ <https://numba.readthedocs.io/en/stable/cuda/cuda_array_interface.html>`_ protocol.
@@ -98,7 +102,6 @@ class StridedMemoryView:
         stream_ptr : int, optional
             Stream pointer for synchronization. If ``None``, no synchronization is performed.
         """
-
     @classmethod
     def from_array_interface(cls, obj: object) -> StridedMemoryView:
         """Create a view from an object supporting the `__array_interface__ <https://numpy.org/doc/stable/reference/arrays.interface.html>`_ protocol.
@@ -108,7 +111,6 @@ class StridedMemoryView:
         obj : object
             An object implementing the `__array_interface__ <https://numpy.org/doc/stable/reference/arrays.interface.html>`_ protocol (e.g., a numpy array).
         """
-
     @classmethod
     def from_any_interface(cls, obj: object, stream_ptr: int | None=None) -> StridedMemoryView:
         """Create a view by automatically selecting the best available protocol.
@@ -126,7 +128,6 @@ class StridedMemoryView:
         stream_ptr : int, optional
             Stream pointer for synchronization. If ``None``, no synchronization is performed.
         """
-
     @classmethod
     def from_buffer(cls, buffer: Buffer, shape: tuple[int, ...], strides: tuple[int, ...] | None=None, *, itemsize: int | None=None, dtype: numpy.dtype | None=None, is_readonly: bool=False) -> StridedMemoryView:
         """
@@ -155,17 +156,13 @@ class StridedMemoryView:
         is_readonly : bool, optional
             Whether the mark the view as readonly.
         """
-
-    def __dealloc__(self) -> None:
-        ...
-
+    def __dealloc__(self) -> None: ...
     def view(self, layout: _StridedLayout | None=None, dtype: numpy.dtype | None=None) -> StridedMemoryView:
         """
         Creates a new view with adjusted layout and dtype.
         Same as calling :meth:`from_buffer` with the current buffer.
         """
-
-    def as_tensor_map(self, box_dim: tuple[int, ...] | None=None, *, options: object=None, element_strides: tuple[int, ...] | None=None, data_type: object=None, interleave: object=None, swizzle: object=None, l2_promotion: object=None, oob_fill: object=None) -> object:
+    def as_tensor_map(self, box_dim: tuple[int, ...] | None=None, *, options: TensorMapDescriptorOptions | None=None, element_strides: tuple[int, ...] | None=None, data_type: object | None=None, interleave: object | None=None, swizzle: object | None=None, l2_promotion: object | None=None, oob_fill: object | None=None) -> object:
         """Create a tiled :obj:`TensorMapDescriptor` from this view.
 
         This is the public entry point for creating tiled tensor map
@@ -173,8 +170,7 @@ class StridedMemoryView:
         individual keyword arguments directly, or provide bundled tiled
         options via ``options=``.
         """
-
-    def copy_from(self, other: StridedMemoryView, stream: Stream, allocator: object=None, blocking: bool | None=None) -> None:
+    def copy_from(self, other: StridedMemoryView, stream: Stream, allocator: object | None=None, blocking: bool | None=None) -> None:
         """
         Copies the data from the other view into this view.
 
@@ -202,43 +198,32 @@ class StridedMemoryView:
                     * for device-to-device, it defaults to ``False`` (non-blocking),
                     * for host-to-device or device-to-host, it defaults to ``True`` (blocking).
         """
-
-    def copy_to(self, other: StridedMemoryView, stream: Stream | None=None, allocator: object=None, blocking: bool | None=None) -> None:
+    def copy_to(self, other: StridedMemoryView, stream: Stream | None=None, allocator: object | None=None, blocking: bool | None=None) -> None:
         """
         Copies the data from this view into the ``other`` view.
 
         For details, see :meth:`copy_from`.
         """
-
-    def __dlpack__(self, *, stream: int | None=None, max_version: tuple[int, int] | None=None, dl_device: tuple[int, int] | None=None, copy: bool | None=None) -> object:
-        ...
-
-    def __dlpack_device__(self) -> tuple[int, int]:
-        ...
-
+    def __dlpack__(self, *, stream: int | None=None, max_version: tuple[int, int] | None=None, dl_device: tuple[int, int] | None=None, copy: bool | None=None) -> object: ...
+    def __dlpack_device__(self) -> tuple[int, int]: ...
     @property
     def _layout(self) -> _StridedLayout:
         """
         The layout of the tensor. For StridedMemoryView created from DLPack or CAI,
         the layout is inferred from the tensor object's metadata.
         """
-
     @property
-    def size(self) -> int:
-        ...
-
+    def size(self) -> int: ...
     @property
     def shape(self) -> tuple[int, ...]:
         """
         Shape of the tensor.
         """
-
     @property
     def strides(self) -> tuple[int, ...] | None:
         """
         Strides of the tensor (in **counts**, not bytes).
         """
-
     @property
     def dtype(self) -> numpy.dtype | None:
         """
@@ -249,33 +234,21 @@ class StridedMemoryView:
         installed. If ``ml_dtypes`` is not available and such a tensor is encountered,
         a :obj:`NotImplementedError` will be raised.
         """
-
-    def __repr__(self) -> str:
-        ...
+    def __repr__(self) -> str: ...
 
 class _StridedMemoryViewProxy:
+    obj: object
+    has_dlpack: bool
 
-    def view(self, stream_ptr=None) -> StridedMemoryView:
-        ...
-
-    def __init__(self, obj: object) -> None:
-        ...
-_SMV_DLPACK_EXCHANGE_API_CAPSULE = ...
-
-def view_as_cai(obj, stream_ptr, view=None) -> StridedMemoryView:
-    ...
-
-def view_as_array_interface(obj, view=None) -> StridedMemoryView:
-    ...
+    def __init__(self, obj: object) -> None: ...
+    def view(self, stream_ptr=None) -> StridedMemoryView: ...
 
 @functools.lru_cache
-def _typestr2dtype(typestr: str) -> numpy.dtype:
-    ...
-
+def _typestr2dtype(typestr: str) -> numpy.dtype: ...
 @functools.lru_cache
-def _typestr2itemsize(typestr: str) -> int:
-    ...
-
+def _typestr2itemsize(typestr: str) -> int: ...
+def view_as_cai(obj, stream_ptr, view=None) -> StridedMemoryView: ...
+def view_as_array_interface(obj, view=None) -> StridedMemoryView: ...
 def args_viewable_as_strided_memory(arg_indices: tuple[int, ...]) -> Callable[[Callable[..., Any]], Callable[..., Any]]:
     """
     Decorator to create proxy objects to :obj:`StridedMemoryView` for the
@@ -304,4 +277,4 @@ def args_viewable_as_strided_memory(arg_indices: tuple[int, ...]) -> Callable[[C
     ----------
     arg_indices : tuple
         The indices of the target positional arguments.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/_memoryview.pyx b/cuda_core/cuda/core/_memoryview.pyx
index d6dd9bb2454..129cb91711b 100644
--- a/cuda_core/cuda/core/_memoryview.pyx
+++ b/cuda_core/cuda/core/_memoryview.pyx
@@ -16,15 +16,19 @@ import functools
 import sys
 import warnings
 from collections.abc import Callable  # no-cython-lint  # used in string annotations below
-from typing import Any  # no-cython-lint  # used in string annotations below
+from typing import TYPE_CHECKING, Any  # no-cython-lint  # used in string annotations below
+
+if TYPE_CHECKING:
+    from cuda.core._tensor_map import TensorMapDescriptorOptions
 
 import numpy
 
 from cuda.bindings cimport cydriver
 from cuda.core._resource_handles cimport (
     EventHandle,
-    create_event_handle_noctx,
+    create_event_handle_for_stream,
     as_cu,
+    get_last_error,
 )
 
 from cuda.core._utils.cuda_utils import handle_return, driver
@@ -32,6 +36,7 @@ from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 
 
 from cuda.core._memory import Buffer
+from cuda.core._memory._buffer cimport Buffer as cyBuffer, Buffer_check_open
 
 
 # ---------------------------------------------------------------------------
@@ -377,7 +382,7 @@ cdef class StridedMemoryView:
         self,
         box_dim: tuple[int, ...] | None = None,
         *,
-        options: object = None,
+        options: TensorMapDescriptorOptions | None = None,
         element_strides: tuple[int, ...] | None = None,
         data_type: object = None,
         interleave: object = None,
@@ -544,13 +549,16 @@ cdef class StridedMemoryView:
 
     @cython.critical_section
     cdef inline _StridedLayout get_layout(self):
+        cdef _StridedLayout layout
         if self._layout is None:
             if self.dl_tensor:
-                self._layout = layout_from_dlpack(self.dl_tensor)
+                layout = layout_from_dlpack(self.dl_tensor)
             elif self.metadata is not None:
-                self._layout = layout_from_cai(self.metadata)
+                layout = layout_from_cai(self.metadata)
             else:
                 raise ValueError("Cannot infer layout from the exporting object")
+            if self._layout is None:
+                self._layout = layout
         return self._layout
 
     @cython.critical_section
@@ -560,24 +568,31 @@ cdef class StridedMemoryView:
         If the SMV was created from a Buffer, it will return the same Buffer instance.
         Otherwise, it will create a new instance with owner set to the exporting object.
         """
+        cdef object buffer
         if self._buffer is None:
             if isinstance(self.exporting_obj, Buffer):
-                self._buffer = self.exporting_obj
+                buffer = self.exporting_obj
             else:
-                self._buffer = Buffer.from_handle(self.ptr, 0, owner=self.exporting_obj)
+                buffer = Buffer.from_handle(self.ptr, 0, owner=self.exporting_obj)
+            if self._buffer is None:
+                self._buffer = buffer
         return self._buffer
 
     @cython.critical_section
     cdef inline object get_dtype(self):
+        cdef object dtype
         if self._dtype is None:
+            dtype = None
             if self.dl_tensor != NULL:
-                self._dtype = dtype_dlpack_to_numpy(&self.dl_tensor.dtype)
+                dtype = dtype_dlpack_to_numpy(&self.dl_tensor.dtype)
             elif isinstance(self.metadata, int):
                 # AOTI dtype code stored by the torch tensor bridge
-                self._dtype = _get_tensor_bridge().resolve_aoti_dtype(
+                dtype = _get_tensor_bridge().resolve_aoti_dtype(
                     self.metadata)
             elif self.metadata is not None:
-                self._dtype = _typestr2dtype(self.metadata["typestr"])
+                dtype = _typestr2dtype(self.metadata["typestr"])
+            if self._dtype is None:
+                self._dtype = dtype
         return self._dtype
 
 
@@ -1092,7 +1107,7 @@ cdef StridedMemoryView view_as_dlpack(obj, stream_ptr, view=None):
     cdef StridedMemoryView buf = StridedMemoryView() if view is None else view
     buf.dl_tensor = dl_tensor
     buf.metadata = capsule
-    buf.ptr = <intptr_t>(dl_tensor.data)
+    buf.ptr = <intptr_t>(dl_tensor.data) + <intptr_t>(dl_tensor.byte_offset)
     buf.device_id = device_id
     buf.is_device_accessible = is_device_accessible
     buf.readonly = is_readonly
@@ -1213,7 +1228,12 @@ cpdef StridedMemoryView view_as_cai(obj, stream_ptr, view=None):
             # establish stream order
             if producer_s != consumer_s:
                 with nogil:
-                    h_event = create_event_handle_noctx(cydriver.CUevent_flags.CU_EVENT_DISABLE_TIMING)
+                    # The event must belong to the producer stream's context to
+                    # be recorded on it, whatever context is current here.
+                    h_event = create_event_handle_for_stream(
+                        <cydriver.CUstream>producer_s, cydriver.CUevent_flags.CU_EVENT_DISABLE_TIMING)
+                    if not h_event:
+                        HANDLE_RETURN(get_last_error())
                     HANDLE_RETURN(cydriver.cuEventRecord(
                         as_cu(h_event), <cydriver.CUstream>producer_s))
                     HANDLE_RETURN(cydriver.cuStreamWaitEvent(
@@ -1247,7 +1267,7 @@ cpdef StridedMemoryView view_as_array_interface(obj, view=None):
     buf.get_layout()
     buf.ptr, buf.readonly = data["data"]
     buf.is_device_accessible = False
-    buf.device_id = handle_return(driver.cuCtxGetDevice())
+    buf.device_id = -1
     return buf
 
 
@@ -1322,6 +1342,8 @@ cdef inline int view_buffer_strided(
     object dtype,
     bint is_readonly,
 ) except -1:
+    if isinstance(buffer, Buffer):
+        Buffer_check_open(<cyBuffer>buffer)
     if dtype is not None:
         dtype = numpy.dtype(dtype)
         if dtype.itemsize != layout.itemsize:
diff --git a/cuda_core/cuda/core/_module.pxd b/cuda_core/cuda/core/_module.pxd
index 78f871b5ba2..5e9d08fc13f 100644
--- a/cuda_core/cuda/core/_module.pxd
+++ b/cuda_core/cuda/core/_module.pxd
@@ -2,6 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
+from libcpp.mutex cimport py_safe_once_flag
+
 from cuda.bindings cimport cydriver
 from cuda.core._resource_handles cimport LibraryHandle, KernelHandle
 
@@ -32,6 +34,7 @@ cdef class ObjectCode:
         object _module      # bytes/str source
         dict _sym_map
         str _name
+        py_safe_once_flag _load_once
         object __weakref__
 
     cdef int _lazy_load_module(self) except -1
diff --git a/cuda_core/cuda/core/_module.pyi b/cuda_core/cuda/core/_module.pyi
index f51b4cb2817..e73c47f471f 100644
--- a/cuda_core/cuda/core/_module.pyi
+++ b/cuda_core/cuda/core/_module.pyi
@@ -1,16 +1,17 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_module.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_module.pyx
 
 from collections import namedtuple
 from os import PathLike
 
-import cython
 from cuda.core._device import Device
 from cuda.core._launch_config import LaunchConfig
 from cuda.core._stream import Stream
 from cuda.core._utils.cuda_utils import driver
 
+__all__ = ['Kernel', 'ObjectCode']
+MaxPotentialBlockSizeOccupancyResult = namedtuple('MaxPotentialBlockSizeOccupancyResult', ('min_grid_size', 'max_block_size'))
+ParamInfo = namedtuple('ParamInfo', ['offset', 'size'])
+CodeTypeT = bytes | bytearray | str
 
 class KernelAttributes:
     """Read-only view of a kernel's per-device attributes.
@@ -22,10 +23,7 @@ class KernelAttributes:
     views share the underlying cache so a value queried through one view
     is visible through the others.
     """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     def __getitem__(self, device: Device | int) -> KernelAttributes:
         """Return a view of these attributes bound to a specific device.
 
@@ -41,77 +39,61 @@ class KernelAttributes:
             A view bound to ``device`` that shares the underlying cache
             with this view.
         """
-
     @property
     def max_threads_per_block(self) -> int:
         """int : The maximum number of threads per block.
         This attribute is read-only."""
-
     @property
     def shared_size_bytes(self) -> int:
         """int : The size in bytes of statically-allocated shared memory required by this function.
         This attribute is read-only."""
-
     @property
     def const_size_bytes(self) -> int:
         """int : The size in bytes of user-allocated constant memory required by this function.
         This attribute is read-only."""
-
     @property
     def local_size_bytes(self) -> int:
         """int : The size in bytes of local memory used by each thread of this function.
         This attribute is read-only."""
-
     @property
     def num_regs(self) -> int:
         """int : The number of registers used by each thread of this function.
         This attribute is read-only."""
-
     @property
     def ptx_version(self) -> int:
         """int : The PTX virtual architecture version for which the function was compiled.
         This attribute is read-only."""
-
     @property
     def binary_version(self) -> int:
         """int : The binary architecture version for which the function was compiled.
         This attribute is read-only."""
-
     @property
     def cache_mode_ca(self) -> bool:
         """bool : Whether the function has been compiled with user specified option "-Xptxas --dlcm=ca" set.
         This attribute is read-only."""
-
     @property
     def max_dynamic_shared_size_bytes(self) -> int:
         """int : The maximum size in bytes of dynamically-allocated shared memory that can be used
         by this function."""
-
     @property
     def preferred_shared_memory_carveout(self) -> int:
         """int : The shared memory carveout preference, in percent of the total shared memory."""
-
     @property
     def cluster_size_must_be_set(self) -> bool:
         """bool : The kernel must launch with a valid cluster size specified.
         This attribute is read-only."""
-
     @property
     def required_cluster_width(self) -> int:
         """int : The required cluster width in blocks."""
-
     @property
     def required_cluster_height(self) -> int:
         """int : The required cluster height in blocks."""
-
     @property
     def required_cluster_depth(self) -> int:
         """int : The required cluster depth in blocks."""
-
     @property
     def non_portable_cluster_size_allowed(self) -> bool:
         """bool : Whether the function can be launched with non-portable cluster size."""
-
     @property
     def cluster_scheduling_policy_preference(self) -> int:
         """int : The block scheduling policy of a function."""
@@ -120,10 +102,7 @@ class KernelOccupancy:
     """This class offers methods to query occupancy metrics that help determine optimal
     launch parameters such as block size, grid size, and shared memory usage.
     """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     def max_active_blocks_per_multiprocessor(self, block_size: int, dynamic_shared_memory_size: int) -> int:
         """Occupancy of the kernel.
 
@@ -149,7 +128,6 @@ class KernelOccupancy:
             theoretical multiprocessor utilization (occupancy).
 
         """
-
     def max_potential_block_size(self, dynamic_shared_memory_needed: int | driver.CUoccupancyB2DSize, block_size_limit: int) -> MaxPotentialBlockSizeOccupancyResult:
         """MaxPotentialBlockSizeOccupancyResult: Suggested launch configuration for reasonable occupancy.
 
@@ -158,7 +136,7 @@ class KernelOccupancy:
 
         Parameters
         ----------
-            dynamic_shared_memory_needed: Union[int, driver.CUoccupancyB2DSize]
+            dynamic_shared_memory_needed: int | driver.CUoccupancyB2DSize
                 The amount of dynamic shared memory in bytes needed by block.
                 Use `0` if block does not need shared memory. Use C-callable
                 represented by :obj:`~driver.CUoccupancyB2DSize` to encode
@@ -180,7 +158,6 @@ class KernelOccupancy:
             Interpreter Lock may lead to deadlocks.
 
         """
-
     def available_dynamic_shared_memory_per_block(self, num_blocks_per_multiprocessor: int, block_size: int) -> int:
         """Dynamic shared memory available per block for given launch configuration.
 
@@ -198,7 +175,6 @@ class KernelOccupancy:
         int
             Dynamic shared memory available per block for given launch configuration.
         """
-
     def max_potential_cluster_size(self, config: LaunchConfig, *, stream: Stream) -> int:
         """Maximum potential cluster size.
 
@@ -218,7 +194,6 @@ class KernelOccupancy:
         int
             The maximum cluster size that can be launched for this kernel and launch configuration.
         """
-
     def max_active_clusters(self, config: LaunchConfig, *, stream: Stream) -> int:
         """Maximum number of active clusters on the target device.
 
@@ -249,28 +224,19 @@ class Kernel:
     should instead be created through a :obj:`~_module.ObjectCode` object.
 
     """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @property
-    @cython.critical_section
     def attributes(self) -> KernelAttributes:
         """Get the read-only attributes of this kernel."""
-
     @property
     def num_arguments(self) -> int:
         """int : The number of arguments of this function"""
-
     @property
     def arguments_info(self) -> list[ParamInfo]:
         """list[ParamInfo]: (offset, size) for each argument of this function"""
-
     @property
-    @cython.critical_section
     def occupancy(self) -> KernelOccupancy:
         """Get the occupancy information for launching this kernel."""
-
     @property
     def handle(self) -> object:
         """Return the underlying kernel handle object.
@@ -280,11 +246,8 @@ class Kernel:
             This handle is a Python object. To get the memory address of the underlying C
             handle, call ``int(Kernel.handle)``.
         """
-
     @property
-    def _handle(self) -> object:
-        ...
-
+    def _handle(self) -> object: ...
     @staticmethod
     def from_handle(handle, mod: ObjectCode | None=None) -> Kernel:
         """Creates a new :obj:`Kernel` object from a kernel handle.
@@ -299,15 +262,9 @@ class Kernel:
             library lifetime for foreign kernels not created by
             cuda.core.
         """
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
-    def __repr__(self) -> str:
-        ...
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
+    def __repr__(self) -> str: ...
 
 class ObjectCode:
     """Represent a compiled program to be loaded onto the device.
@@ -322,127 +279,112 @@ class ObjectCode:
     from all other possible code types should be avoided in favor of compilation through
     :class:`~cuda.core.Program`
     """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @classmethod
-    def _init(cls, module, code_type, *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode:
-        ...
-
+    def _init(cls, module, code_type, *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode: ...
     @staticmethod
-    def _reduce_helper(module, code_type, name, symbol_mapping):
-        ...
-
-    def __reduce__(self) -> tuple[object, ...]:
-        ...
-
+    def _reduce_helper(module, code_type, name, symbol_mapping): ...
+    def __reduce__(self) -> tuple[object, ...]: ...
     @staticmethod
     def from_cubin(module: bytes | str | PathLike[str], *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode:
         """Create an :class:`ObjectCode` instance from an existing cubin.
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory cubin to load, or
             a file path object (or its string representation) pointing to the
             on-disk cubin to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
         """
-
     @staticmethod
     def from_ptx(module: bytes | str | PathLike[str], *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode:
         """Create an :class:`ObjectCode` instance from an existing PTX.
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory ptx code to load, or
             a file path object (or its string representation) pointing to the
             on-disk ptx file to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
         """
-
     @staticmethod
     def from_ltoir(module: bytes | str | PathLike[str], *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode:
         """Create an :class:`ObjectCode` instance from an existing LTOIR.
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory ltoir code to load,
             or a file path object (or its string representation) pointing to the
             on-disk ltoir file to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
         """
-
     @staticmethod
     def from_fatbin(module: bytes | str | PathLike[str], *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode:
         """Create an :class:`ObjectCode` instance from an existing fatbin.
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory fatbin to load, or
             or a file path object (or its string representation) pointing to the
             on-disk fatbin to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
         """
-
     @staticmethod
     def from_object(module: bytes | str, *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode:
         """Create an :class:`ObjectCode` instance from an existing object code.
 
         Parameters
         ----------
-        module : Union[bytes, str]
+        module : bytes | str
             Either a bytes object containing the in-memory object code to load, or
             a file path string pointing to the on-disk object code to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
         """
-
     @staticmethod
     def from_library(module: bytes | str, *, name: str='', symbol_mapping: dict[str, str] | None=None) -> ObjectCode:
         """Create an :class:`ObjectCode` instance from an existing library.
 
         Parameters
         ----------
-        module : Union[bytes, str]
+        module : bytes | str
             Either a bytes object containing the in-memory library to load, or
             a file path string pointing to the on-disk library to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
         """
-
     def get_kernel(self, name: str | bytes) -> Kernel:
         """Return the :obj:`~_module.Kernel` of a specified name from this object code.
 
@@ -457,8 +399,7 @@ class ObjectCode:
             Newly created kernel object.
 
         """
-
-    def get_module(self) -> object:
+    def get_module(self) -> driver.CUmodule:
         """Return a context-dependent :obj:`~driver.CUmodule` for legacy interop.
 
         Bridges the native :obj:`~driver.CUlibrary` (see :attr:`handle`) to a
@@ -471,23 +412,18 @@ class ObjectCode:
             Module handle for the current CUDA context, suitable for legacy
             driver APIs that accept ``CUmodule``.
         """
-
     @property
     def code(self) -> CodeTypeT:
         """Return the underlying code object."""
-
     @property
     def name(self) -> str:
         """Return a human-readable name of this code object."""
-
     @property
     def code_type(self) -> str:
         """Return the type of the underlying code object."""
-
     @property
     def symbol_mapping(self) -> dict[str, str]:
         """Return a copy of the symbol mapping dictionary."""
-
     @property
     def handle(self) -> object:
         """Return the native, context-independent :obj:`~driver.CUlibrary` handle.
@@ -500,16 +436,6 @@ class ObjectCode:
             This handle is a Python object. To get the memory address of the underlying C
             handle, call ``int(ObjectCode.handle)``.
         """
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
-    def __repr__(self) -> str:
-        ...
-__all__ = ['Kernel', 'ObjectCode']
-MaxPotentialBlockSizeOccupancyResult = namedtuple('MaxPotentialBlockSizeOccupancyResult', ('min_grid_size', 'max_block_size'))
-ParamInfo = namedtuple('ParamInfo', ['offset', 'size'])
-CodeTypeT = bytes | bytearray | str
\ No newline at end of file
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
+    def __repr__(self) -> str: ...
diff --git a/cuda_core/cuda/core/_module.pyx b/cuda_core/cuda/core/_module.pyx
index 5734e31414b..a350f14887f 100644
--- a/cuda_core/cuda/core/_module.pyx
+++ b/cuda_core/cuda/core/_module.pyx
@@ -6,7 +6,7 @@ from __future__ import annotations
 
 cimport cython
 from libc.stddef cimport size_t
-from libc.stdint cimport intptr_t
+from libcpp.mutex cimport py_safe_call_once
 
 from collections import namedtuple
 from os import fsencode, fspath, PathLike
@@ -300,7 +300,7 @@ cdef class KernelOccupancy:
 
         Parameters
         ----------
-            dynamic_shared_memory_needed: Union[int, driver.CUoccupancyB2DSize]
+            dynamic_shared_memory_needed: int | driver.CUoccupancyB2DSize
                 The amount of dynamic shared memory in bytes needed by block.
                 Use `0` if block does not need shared memory. Use C-callable
                 represented by :obj:`~driver.CUoccupancyB2DSize` to encode
@@ -459,8 +459,11 @@ cdef class Kernel:
     @cython.critical_section
     def attributes(self) -> KernelAttributes:
         """Get the read-only attributes of this kernel."""
+        cdef KernelAttributes attributes
         if self._attributes is None:
-            self._attributes = KernelAttributes._init(self._h_kernel)
+            attributes = KernelAttributes._init(self._h_kernel)
+            if self._attributes is None:
+                self._attributes = attributes
         return self._attributes
 
     cdef tuple _get_arguments_info(self, bint param_info=False):
@@ -507,8 +510,11 @@ cdef class Kernel:
     @cython.critical_section
     def occupancy(self) -> KernelOccupancy:
         """Get the occupancy information for launching this kernel."""
+        cdef KernelOccupancy occupancy
         if self._occupancy is None:
-            self._occupancy = KernelOccupancy._init(self._h_kernel)
+            occupancy = KernelOccupancy._init(self._h_kernel)
+            if self._occupancy is None:
+                self._occupancy = occupancy
         return self._occupancy
 
     @property
@@ -584,6 +590,31 @@ CodeTypeT = bytes | bytearray | str
 
 cdef tuple _supported_code_type = tuple(ObjectCodeFormatType.__members__.values())
 
+
+cdef void _lazy_load_module_once(void *self_v) except *:
+    # Call-once helper for the lazy module loading, we want to avoid unloading
+    # a module in case of threads racing, so use `call_once`.
+    cdef ObjectCode self = <ObjectCode>self_v
+    cdef LibraryHandle h_library
+    cdef bytes path_bytes
+    module = self._module
+    if isinstance(module, str):
+        path_bytes = module.encode()
+        h_library = create_library_handle_from_file(<const char*>path_bytes)
+    elif isinstance(module, (bytes, bytearray)):
+        h_library = create_library_handle_from_data(<const void*><char*>module)
+    elif isinstance(module, PathLike):
+        path_bytes = fsencode(module)
+        h_library = create_library_handle_from_file(<const char*>path_bytes)
+    else:
+        assert_type_str_or_bytes_like(module)
+        raise_code_path_meant_to_be_unreachable()
+        return
+    if not h_library:
+        HANDLE_RETURN(get_last_error())
+    self._h_library = h_library
+
+
 cdef class ObjectCode:
     """Represent a compiled program to be loaded onto the device.
 
@@ -638,13 +669,13 @@ cdef class ObjectCode:
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory cubin to load, or
             a file path object (or its string representation) pointing to the
             on-disk cubin to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
@@ -657,13 +688,13 @@ cdef class ObjectCode:
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory ptx code to load, or
             a file path object (or its string representation) pointing to the
             on-disk ptx file to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
@@ -676,13 +707,13 @@ cdef class ObjectCode:
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory ltoir code to load,
             or a file path object (or its string representation) pointing to the
             on-disk ltoir file to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
@@ -695,13 +726,13 @@ cdef class ObjectCode:
 
         Parameters
         ----------
-        module : Union[bytes, str, os.PathLike]
+        module : bytes | str | os.PathLike
             Either a bytes object containing the in-memory fatbin to load, or
             or a file path object (or its string representation) pointing to the
             on-disk fatbin to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
@@ -714,12 +745,12 @@ cdef class ObjectCode:
 
         Parameters
         ----------
-        module : Union[bytes, str]
+        module : bytes | str
             Either a bytes object containing the in-memory object code to load, or
             a file path string pointing to the on-disk object code to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
@@ -732,12 +763,12 @@ cdef class ObjectCode:
 
         Parameters
         ----------
-        module : Union[bytes, str]
+        module : bytes | str
             Either a bytes object containing the in-memory library to load, or
             a file path string pointing to the on-disk library to load.
-        name : Optional[str]
+        name : str | None
             A human-readable identifier representing this code object.
-        symbol_mapping : Optional[dict]
+        symbol_mapping : dict | None
             A dictionary specifying how the unmangled symbol names (as keys)
             should be mapped to the mangled names before trying to retrieve
             them (default to no mappings).
@@ -746,26 +777,8 @@ cdef class ObjectCode:
 
     # TODO: do we want to unload in a finalizer? Probably not..
 
-    @cython.critical_section
     cdef int _lazy_load_module(self) except -1:
-        if self._h_library:
-            return 0
-        module = self._module
-        cdef bytes path_bytes
-        if isinstance(module, str):
-            path_bytes = module.encode()
-            self._h_library = create_library_handle_from_file(<const char*>path_bytes)
-        elif isinstance(module, (bytes, bytearray)):
-            self._h_library = create_library_handle_from_data(<const void*><char*>module)
-        elif isinstance(module, PathLike):
-            path_bytes = fsencode(module)
-            self._h_library = create_library_handle_from_file(<const char*>path_bytes)
-        else:
-            assert_type_str_or_bytes_like(module)
-            raise_code_path_meant_to_be_unreachable()
-            return -1
-        if not self._h_library:
-            HANDLE_RETURN(get_last_error())
+        py_safe_call_once(self._load_once, _lazy_load_module_once, <void *>self)
         return 0
 
     def get_kernel(self, name: str | bytes) -> Kernel:
@@ -797,7 +810,7 @@ cdef class ObjectCode:
             HANDLE_RETURN(get_last_error())
         return Kernel._from_handle(h_kernel)
 
-    def get_module(self) -> object:
+    def get_module(self) -> driver.CUmodule:
         """Return a context-dependent :obj:`~driver.CUmodule` for legacy interop.
 
         Bridges the native :obj:`~driver.CUlibrary` (see :attr:`handle`) to a
@@ -814,7 +827,7 @@ cdef class ObjectCode:
         cdef cydriver.CUmodule mod
         with nogil:
             HANDLE_RETURN(cydriver.cuLibraryGetModule(&mod, as_cu(self._h_library)))
-        return driver.CUmodule(<intptr_t>mod)
+        return as_py(mod)
 
     @property
     def code(self) -> CodeTypeT:
diff --git a/cuda_core/cuda/core/_program.pxd b/cuda_core/cuda/core/_program.pxd
index cea430c3f20..e1cbaa6fbda 100644
--- a/cuda_core/cuda/core/_program.pxd
+++ b/cuda_core/cuda/core/_program.pxd
@@ -20,3 +20,5 @@ cdef class Program:
         bytes _code             # Source code as bytes: used for key derivation and NVRTC PCH retry
         str _code_type          # Normalised code_type ("c++", "ptx", "nvvm")
         str _pch_status         # PCH creation outcome after compile
+        bytes _nvrtc_name       # Source filepath given to NVRTC; a real path for debug builds
+        list _extra_options     # NVRTC options Program adds on top of ProgramOptions
diff --git a/cuda_core/cuda/core/_program.pyi b/cuda_core/cuda/core/_program.pyi
index df7ed66446a..2af6f6f8f62 100644
--- a/cuda_core/cuda/core/_program.pyi
+++ b/cuda_core/cuda/core/_program.pyi
@@ -1,12 +1,10 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_program.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_program.pyx
 
 """Compilation machinery for CUDA programs.
 
 This module provides :class:`Program` for compiling source code into
 :class:`~cuda.core.ObjectCode`, with :class:`ProgramOptions` for configuration.
 """
-from __future__ import annotations
-
 from dataclasses import dataclass
 
 from cuda.bindings import nvrtc
@@ -16,6 +14,10 @@ from cuda.core.typing import (CompilerBackendType, ObjectCodeFormatType,
                               PCHStatusType, SourceCodeType)
 from cuda.core.utils._program_cache import ProgramCacheResource
 
+__all__ = ['Program', 'ProgramOptions']
+ProgramHandleT = nvrtc.nvrtcProgram | int | LinkerHandleT
+_nvvm_module = None
+_nvvm_import_attempted = False
 
 class Program:
     """Represent a compilation machinery to process programs into
@@ -35,14 +37,25 @@ class Program:
     options : :class:`ProgramOptions`, optional
         Options to customize the compilation process.
     """
-
-    def __init__(self, code: str | bytes | bytearray, code_type: SourceCodeType | str, options: ProgramOptions | None=None):
-        ...
-
+    def __init__(self, code: str | bytes | bytearray, code_type: SourceCodeType | str, options: ProgramOptions | None=None): ...
     def close(self) -> None:
         """Destroy this program."""
+    def __dealloc__(self): ...
+    def _cleanup_debug_source(self): ...
+    def _unlink_debug_source(self, path: str) -> None: ...
+    def _try_materialize_nvrtc_debug_source(self, code: str) -> str | None:
+        """Write *code* to a ``{caller}_{kernel}_XXXXXXXX.cu`` temp file for cuda-gdb.
 
-    def compile(self, target_type: ObjectCodeFormatType | str, name_expressions: tuple[str, ...] | list[str]=..., logs: object=None, *, cache: ProgramCacheResource | None=None) -> ObjectCode:
+        ``caller`` is the Python file stem (no ``.py``). ``kernel`` is the first
+        ``__global__`` function name, or ``kernel`` if none is found.
+
+        Returns None if the filesystem is not writable, so the caller can fall back
+        to the label-only behavior instead of failing the compile.
+        """
+    @property
+    def is_closed(self) -> bool:
+        """Whether this program has been closed."""
+    def compile(self, target_type: ObjectCodeFormatType | str, name_expressions: tuple[str, ...] | list[str]=(), logs: object | None=None, *, cache: ProgramCacheResource | None=None) -> ObjectCode:
         """Compile the program to the specified target type.
 
         Parameters
@@ -90,7 +103,6 @@ class Program:
         :class:`~cuda.core.ObjectCode`
             The compiled object code.
         """
-
     @property
     def pch_status(self) -> PCHStatusType | None:
         """PCH creation outcome from the most recent :meth:`compile` call.
@@ -115,11 +127,9 @@ class Program:
            use the NVRTC backend. For PTX and NVVM programs this property
            always returns ``None``.
         """
-
     @property
     def backend(self) -> CompilerBackendType:
         """Return this Program instance's underlying :class:`CompilerBackendType`."""
-
     @property
     def handle(self) -> ProgramHandleT:
         """Return the underlying handle object.
@@ -133,9 +143,7 @@ class Program:
             This handle is a Python object. To get the memory address of the underlying C
             handle, call ``int(Program.handle)``.
         """
-
-    def __repr__(self) -> str:
-        ...
+    def __repr__(self) -> str: ...
 
 @dataclass
 class ProgramOptions:
@@ -145,6 +153,7 @@ class ProgramOptions:
     ----------
     name : str, optional
         Name of the program. If the compilation succeeds, the name is passed down to the generated :class:`ObjectCode`.
+        When set to `None`, ``"default_program"`` is used.
     arch : str, optional
         Pass the SM architecture value, such as ``sm_<CC>`` (for generating CUBIN) or
         ``compute_<CC>`` (for generating PTX). If not provided, the current device's architecture
@@ -165,7 +174,7 @@ class ProgramOptions:
         Enable device code optimization. When specified along with '-G', enables limited debug information generation
         for optimized device code.
         Default: None
-    ptxas_options : Union[str, list[str]], optional
+    ptxas_options : str | list[str], optional
         Specify one or more options directly to ptxas, the PTX optimizing assembler. Options should be strings.
         For example ["-v", "-O2"].
         Default: None
@@ -199,17 +208,24 @@ class ProgramOptions:
     gen_opt_lto : bool, optional
         Run the optimizer passes before generating the LTO IR.
         Default: False
-    define_macro : Union[str, tuple[str, str], list[Union[str, tuple[str, str]]]], optional
+    define_macro : str | tuple[str, str] | list[str | tuple[str, str]], optional
         Predefine a macro. Can be either a string, in which case that macro will be set to 1, a 2 element tuple of
         strings, in which case the first element is defined as the second, or a list of strings or tuples.
         Default: None
-    undefine_macro : Union[str, list[str]], optional
+    undefine_macro : str | list[str], optional
         Cancel any previous definition of a macro, or list of macros.
         Default: None
-    include_path : Union[str, list[str]], optional
+    include_path : str | list[str], optional
         Add the directory or directories to the list of directories to be searched for headers.
         Default: None
-    pre_include : Union[str, list[str]], optional
+    use_bundled_headers : bool, optional
+        Use the CUDA and CCCL headers bundled with NVRTC, installed into a per-user cache
+        directory, instead of requiring a full CUDA Toolkit installation. Implemented via NVRTC's
+        ``--use-bundled-headers=<dir>`` compiler option, which installs the headers into the cache
+        directory (skipping installation if already present and up to date) and adds that
+        directory to the include search path. NVRTC only.
+        Default: False
+    pre_include : str | list[str], optional
         Preinclude one or more headers during preprocessing. Can be either a string or a list of strings.
         Default: None
     no_source_include : bool, optional
@@ -242,13 +258,13 @@ class ProgramOptions:
     no_display_error_number : bool, optional
         Disable the display of a diagnostic number for warning messages.
         Default: False
-    diag_error : Union[int, list[int]], optional
+    diag_error : int | list[int], optional
         Emit error for a specified diagnostic message number or comma-separated list of numbers.
         Default: None
-    diag_suppress : Union[int, list[int]], optional
+    diag_suppress : int | list[int], optional
         Suppress a specified diagnostic message number or comma-separated list of numbers.
         Default: None
-    diag_warn : Union[int, list[int]], optional
+    diag_warn : int | list[int], optional
         Emit warning for a specified diagnostic message number or comma-separated list of numbers.
         Default: None
     brief_diagnostics : bool, optional
@@ -312,6 +328,14 @@ class ProgramOptions:
         Load NVIDIA's `libdevice <https://docs.nvidia.com/cuda/libdevice-users-guide/>`_
         math builtins library. Only supported for the NVVM backend.
         Default: False
+    numba_debug : bool, optional
+        Emit the debug information layout expected by Numba. Recognized only by
+        newer toolkits; compilers that do not support it reject the option with
+        an error. Applies only to the NVVM and NVRTC compilation backends --
+        ``code_type="ptx"`` is processed by the linker, which cannot honor it,
+        so enabling this option there emits a :class:`UserWarning` and the
+        option is ignored.
+        Default: None
     """
     name: str | None = 'default_program'
     arch: str | None = None
@@ -333,6 +357,7 @@ class ProgramOptions:
     define_macro: str | tuple[str, str] | list[str | tuple[str, str]] | tuple[str | tuple[str, str], ...] | None = None
     undefine_macro: str | list[str] | tuple[str] | None = None
     include_path: str | list[str] | tuple[str] | None = None
+    use_bundled_headers: bool | None = None
     pre_include: str | list[str] | tuple[str] | None = None
     no_source_include: bool | None = None
     std: str | None = None
@@ -368,15 +393,9 @@ class ProgramOptions:
     use_libdevice: bool | None = None
     numba_debug: bool | None = None
 
-    def __post_init__(self) -> None:
-        ...
-
-    def _prepare_nvrtc_options(self) -> list[bytes]:
-        ...
-
-    def _prepare_nvvm_options(self, as_bytes: bool=True) -> list[bytes] | list[str]:
-        ...
-
+    def __post_init__(self) -> None: ...
+    def _prepare_nvrtc_options(self) -> list[bytes]: ...
+    def _prepare_nvvm_options(self, as_bytes: bool=True) -> list[bytes] | list[str]: ...
     def as_bytes(self, backend: CompilerBackendType | str, target_type: ObjectCodeFormatType | str | None=None) -> list[bytes]:
         """Convert program options to bytes format for the specified backend.
 
@@ -409,19 +428,9 @@ class ProgramOptions:
         >>> options = ProgramOptions(arch="sm_80", debug=True)
         >>> nvrtc_options = options.as_bytes("nvrtc")
         """
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
     def _prepare_extra_sources_bytes(self) -> list[tuple[bytes, bytes]] | None:
         """Convert extra_sources to bytes format for NVVM."""
-__all__ = ['Program', 'ProgramOptions']
-ProgramHandleT = nvrtc.nvrtcProgram | int | LinkerHandleT
-_nvvm_module = None
-_nvvm_import_attempted = False
-
-def _can_load_generated_ptx() -> bool:
-    """Check if the driver can load PTX generated by the current NVRTC version."""
 
 def _program_compile_uncached(program, target_type, name_expressions, logs):
     """Run ``Program_compile`` without the cache wrapper.
@@ -432,9 +441,19 @@ def _program_compile_uncached(program, target_type, name_expressions, logs):
     and its methods cannot be reassigned from Python, so the seam must live
     outside the class.
     """
-
 def _get_nvvm_module() -> object:
     """Get the NVVM module, importing it lazily with availability checks."""
-
 def _find_libdevice_path() -> object:
-    """Find libdevice*.bc for NVVM compilation using cuda.pathfinder."""
\ No newline at end of file
+    """Find libdevice*.bc for NVVM compilation using cuda.pathfinder."""
+def _can_load_generated_ptx() -> bool:
+    """Check if the driver can load PTX generated by the current NVRTC version."""
+def _assert_single_dashed_nvvm_options(options: list[str]) -> None:
+    """Guard against emitting a double-dashed option to libNVVM.
+
+    libNVVM's parser accepts only single-dashed options and rejects the
+    double-dashed spelling of every option with NVVM_ERROR_INVALID_OPTION
+    (see #2570). Every option on this path is generated from typed fields, so
+    a double dash can only mean a bug in ``cuda.core`` rather than bad user
+    input. Fail here, naming the option, instead of leaving the user with
+    libNVVM's opaque error.
+    """
diff --git a/cuda_core/cuda/core/_program.pyx b/cuda_core/cuda/core/_program.pyx
index 2b2e5262a2c..9ea624f8e83 100644
--- a/cuda_core/cuda/core/_program.pyx
+++ b/cuda_core/cuda/core/_program.pyx
@@ -10,6 +10,10 @@ This module provides :class:`Program` for compiling source code into
 from __future__ import annotations
 
 from dataclasses import dataclass
+import os
+import re
+import sys
+import tempfile
 import threading
 from typing import TYPE_CHECKING
 from warnings import warn
@@ -43,6 +47,7 @@ from cuda.core._utils.cuda_utils import (
     is_sequence,
 )
 from cuda.core._utils.version import binding_version, driver_version
+from cuda.core.utils._cache_dir import _default_cache_dir
 from cuda.core.typing import ObjectCodeFormatType, CompilerBackendType, PCHStatusType, SourceCodeType
 
 __all__ = ["Program", "ProgramOptions"]
@@ -59,6 +64,12 @@ The ``int`` type covers NVVM handles, which don't have a wrapper class.
 # =============================================================================
 
 
+cdef inline int Program_check_open(Program self) except -1:
+    if self.is_closed:
+        raise RuntimeError("Program has been closed")
+    return 0
+
+
 cdef class Program:
     """Represent a compilation machinery to process programs into
     :class:`~cuda.core.ObjectCode`.
@@ -82,11 +93,67 @@ cdef class Program:
 
     def close(self) -> None:
         """Destroy this program."""
-        if self._linker:
+        if self._linker is not None:
             self._linker.close()
         # Reset handles - the C++ shared_ptr destructor handles cleanup
         self._h_nvrtc.reset()
         self._h_nvvm.reset()
+        self._cleanup_debug_source()
+
+    def __dealloc__(self):
+        self._cleanup_debug_source()
+
+    def _cleanup_debug_source(self):
+        # Only a temp file this Program wrote may be removed, and the name having
+        # moved off options.name is what says one was written. Without that test
+        # the caller's own file is deleted whenever options.name happens to match
+        # something on disk, since the unredirected name is just that path.
+        if self._nvrtc_name is not None and self._nvrtc_name != self._options._name:
+            self._unlink_debug_source(self._nvrtc_name.decode())
+
+    def _unlink_debug_source(self, path: str) -> None:
+        try:
+            os.unlink(path)
+        except OSError:
+            pass
+
+    def _try_materialize_nvrtc_debug_source(self, code: str) -> str | None:
+        """Write *code* to a ``{caller}_{kernel}_XXXXXXXX.cu`` temp file for cuda-gdb.
+
+        ``caller`` is the Python file stem (no ``.py``). ``kernel`` is the first
+        ``__global__`` function name, or ``kernel`` if none is found.
+
+        Returns None if the filesystem is not writable, so the caller can fall back
+        to the label-only behavior instead of failing the compile.
+        """
+        frame = sys._getframe()
+        while frame and frame.f_globals.get("__name__", "").startswith("cuda.core"):
+            frame = frame.f_back
+        caller = "program"
+        if frame:
+            caller = os.path.splitext(os.path.basename(frame.f_code.co_filename))[0]
+        match = re.search(r"__global__.*?(\w+)\s*\(", code, re.DOTALL)
+        prefix = re.sub(r"\W", "_", f"{caller}_{match.group(1) if match else 'kernel'}_")
+        try:
+            fd, path = tempfile.mkstemp(prefix=prefix, suffix=".cu")
+        except OSError:
+            return None
+        try:
+            with os.fdopen(fd, "w", encoding="utf-8") as f:
+                f.write(code)
+            return path
+        except OSError:
+            self._unlink_debug_source(path)
+            return None
+
+    @property
+    def is_closed(self) -> bool:
+        """Whether this program has been closed."""
+        if self._backend == "NVRTC":
+            return self._h_nvrtc.get() == NULL
+        if self._backend == "NVVM":
+            return self._h_nvvm.get() == NULL
+        return self._linker is None or self._linker.is_closed
 
     def compile(
         self,
@@ -143,6 +210,7 @@ cdef class Program:
         :class:`~cuda.core.ObjectCode`
             The compiled object code.
         """
+        Program_check_open(self)
         # Mirror Program_init's code_type normalization so callers can pass
         # ``ObjectCodeFormatType.PTX`` or ``"PTX"`` and get the same routing
         # / cache key as the lowercase string. ``Program_compile_nvrtc``
@@ -223,7 +291,7 @@ cdef class Program:
                     stacklevel=2,
                     category=RuntimeWarning,
                 )
-            return ObjectCode._init(hit_bytes, target_type, name=self._options.name)
+            return ObjectCode._init(hit_bytes, target_type, name=self._nvrtc_name.decode())
         compiled = _program_compile_uncached(self, target_type, name_expressions, logs)
         cache[key] = compiled
         return compiled
@@ -298,6 +366,7 @@ class ProgramOptions:
     ----------
     name : str, optional
         Name of the program. If the compilation succeeds, the name is passed down to the generated :class:`ObjectCode`.
+        When set to `None`, ``"default_program"`` is used.
     arch : str, optional
         Pass the SM architecture value, such as ``sm_<CC>`` (for generating CUBIN) or
         ``compute_<CC>`` (for generating PTX). If not provided, the current device's architecture
@@ -318,7 +387,7 @@ class ProgramOptions:
         Enable device code optimization. When specified along with '-G', enables limited debug information generation
         for optimized device code.
         Default: None
-    ptxas_options : Union[str, list[str]], optional
+    ptxas_options : str | list[str], optional
         Specify one or more options directly to ptxas, the PTX optimizing assembler. Options should be strings.
         For example ["-v", "-O2"].
         Default: None
@@ -352,17 +421,24 @@ class ProgramOptions:
     gen_opt_lto : bool, optional
         Run the optimizer passes before generating the LTO IR.
         Default: False
-    define_macro : Union[str, tuple[str, str], list[Union[str, tuple[str, str]]]], optional
+    define_macro : str | tuple[str, str] | list[str | tuple[str, str]], optional
         Predefine a macro. Can be either a string, in which case that macro will be set to 1, a 2 element tuple of
         strings, in which case the first element is defined as the second, or a list of strings or tuples.
         Default: None
-    undefine_macro : Union[str, list[str]], optional
+    undefine_macro : str | list[str], optional
         Cancel any previous definition of a macro, or list of macros.
         Default: None
-    include_path : Union[str, list[str]], optional
+    include_path : str | list[str], optional
         Add the directory or directories to the list of directories to be searched for headers.
         Default: None
-    pre_include : Union[str, list[str]], optional
+    use_bundled_headers : bool, optional
+        Use the CUDA and CCCL headers bundled with NVRTC, installed into a per-user cache
+        directory, instead of requiring a full CUDA Toolkit installation. Implemented via NVRTC's
+        ``--use-bundled-headers=<dir>`` compiler option, which installs the headers into the cache
+        directory (skipping installation if already present and up to date) and adds that
+        directory to the include search path. NVRTC only.
+        Default: False
+    pre_include : str | list[str], optional
         Preinclude one or more headers during preprocessing. Can be either a string or a list of strings.
         Default: None
     no_source_include : bool, optional
@@ -395,13 +471,13 @@ class ProgramOptions:
     no_display_error_number : bool, optional
         Disable the display of a diagnostic number for warning messages.
         Default: False
-    diag_error : Union[int, list[int]], optional
+    diag_error : int | list[int], optional
         Emit error for a specified diagnostic message number or comma-separated list of numbers.
         Default: None
-    diag_suppress : Union[int, list[int]], optional
+    diag_suppress : int | list[int], optional
         Suppress a specified diagnostic message number or comma-separated list of numbers.
         Default: None
-    diag_warn : Union[int, list[int]], optional
+    diag_warn : int | list[int], optional
         Emit warning for a specified diagnostic message number or comma-separated list of numbers.
         Default: None
     brief_diagnostics : bool, optional
@@ -465,6 +541,14 @@ class ProgramOptions:
         Load NVIDIA's `libdevice <https://docs.nvidia.com/cuda/libdevice-users-guide/>`_
         math builtins library. Only supported for the NVVM backend.
         Default: False
+    numba_debug : bool, optional
+        Emit the debug information layout expected by Numba. Recognized only by
+        newer toolkits; compilers that do not support it reject the option with
+        an error. Applies only to the NVVM and NVRTC compilation backends --
+        ``code_type="ptx"`` is processed by the linker, which cannot honor it,
+        so enabling this option there emits a :class:`UserWarning` and the
+        option is ignored.
+        Default: None
     """
 
     name: str | None = "default_program"
@@ -487,6 +571,7 @@ class ProgramOptions:
     define_macro: str | tuple[str, str] | list[str | tuple[str, str]] | tuple[str | tuple[str, str], ...] | None = None
     undefine_macro: str | list[str] | tuple[str] | None = None
     include_path: str | list[str] | tuple[str] | None = None
+    use_bundled_headers: bool | None = None
     pre_include: str | list[str] | tuple[str] | None = None
     no_source_include: bool | None = None
     std: str | None = None
@@ -523,10 +608,23 @@ class ProgramOptions:
     numba_debug: bool | None = None  # Custom option for Numba debugging
 
     def __post_init__(self) -> None:
+        # Set name to default if not provided
+        if self.name is None:
+            self.name = "default_program"
         self._name = self.name.encode()
         # Set arch to default if not provided
         if self.arch is None:
             self.arch = f"sm_{Device().arch}"
+        if self.use_bundled_headers:
+            # --use-bundled-headers (and the bundled CUDA/CCCL headers themselves) were
+            # introduced in NVRTC 13.3.
+            nvrtc_major, nvrtc_minor = handle_return(nvrtc.nvrtcVersion())
+            if (nvrtc_major, nvrtc_minor) < (13, 3):
+                raise RuntimeError(
+                    "use_bundled_headers requires NVRTC >= 13.3, but found "
+                    f"{nvrtc_major}.{nvrtc_minor}. Upgrade the CUDA Toolkit / driver providing "
+                    "libnvrtc, or set use_bundled_headers=False and supply include_path manually."
+                )
         if self.extra_sources is not None:
             if not is_sequence(self.extra_sources):
                 raise TypeError(
@@ -649,12 +747,10 @@ def _get_nvvm_module() -> object:
     """Get the NVVM module, importing it lazily with availability checks."""
     global _nvvm_module, _nvvm_import_attempted
 
-    if _nvvm_import_attempted:
-        if _nvvm_module is None:
-            raise RuntimeError("NVVM module is not available (previous import attempt failed)")
+    if _nvvm_module is not None:
         return _nvvm_module
-
-    _nvvm_import_attempted = True
+    if _nvvm_import_attempted:
+        raise RuntimeError("NVVM module is not available (previous import attempt failed)")
 
     try:
         version = binding_version()
@@ -678,16 +774,16 @@ def _get_nvvm_module() -> object:
 
     except RuntimeError:
         _nvvm_module = None
+        _nvvm_import_attempted = True
         raise
 
+
 def _find_libdevice_path() -> object:
     """Find libdevice*.bc for NVVM compilation using cuda.pathfinder."""
     from cuda.pathfinder import find_bitcode_lib
     return find_bitcode_lib("device")
 
 
-
-
 cdef inline bint _process_define_macro_inner(list options, object macro) except? -1:
     """Process a single define macro, returning True if successful."""
     if isinstance(macro, str):
@@ -723,6 +819,21 @@ cpdef bint _can_load_generated_ptx() except? -1:
 
 cdef inline object _translate_program_options(object options):
     """Translate ProgramOptions to LinkerOptions for PTX compilation."""
+    # ``numba_debug`` is an NVVM/NVRTC compiler option that no linking backend can
+    # honor. It used to be forwarded into ``LinkerOptions`` and dropped without a
+    # word; warn instead, and do not forward -- forwarding would only trigger the
+    # deprecation warning on a field the user never touched. ``UserWarning``, not
+    # ``DeprecationWarning``: ``ProgramOptions.numba_debug`` is not deprecated, it
+    # is fully supported on NVVM and NVRTC and merely inapplicable here. The gate
+    # is truthiness, matching ``_prepare_nvvm_options_impl``: only an enabled
+    # ``numba_debug`` asks for something this path cannot deliver.
+    if options.numba_debug:
+        warn(
+            "numba_debug is ignored for code_type='ptx', which is processed by the linker; "
+            "it applies only to the NVVM and NVRTC compilation backends.",
+            UserWarning,
+            stacklevel=4,
+        )
     return LinkerOptions(
         name=options.name,
         arch=options.arch,
@@ -738,7 +849,6 @@ cdef inline object _translate_program_options(object options):
         split_compile=options.split_compile,
         ptxas_options=options.ptxas_options,
         no_cache=options.no_cache,
-        numba_debug = options.numba_debug
     )
 
 
@@ -762,16 +872,33 @@ cdef inline int Program_init(Program self, object code, str code_type, object op
     self._libdevice_added = False
 
     self._pch_status = None
+    self._nvrtc_name = options._name
+    self._extra_options = []
 
     if code_type == "c++":
         assert_type(code, str)
         if options.extra_sources is not None:
             raise ValueError("extra_sources is not supported by the NVRTC backend (C++ code_type)")
 
+        if (options.debug or options.lineinfo) and options.name == "default_program":
+            debug_path = self._try_materialize_nvrtc_debug_source(code)
+            if debug_path is not None:
+                self._nvrtc_name = debug_path.encode()
+                # NVRTC resolves #include "..." against the directory of the name it
+                # is given, so moving the name into the temp dir would otherwise stop
+                # every quoted include from resolving where it did before.
+                try:
+                    include_dir = os.path.dirname(os.path.abspath(options.name))
+                except OSError:
+                    # abspath needs a cwd; with none there is no directory to restore.
+                    pass
+                else:
+                    self._extra_options = [b"--include-path=" + include_dir.encode()]
+
         # TODO: support pre-loaded headers & include names
         code_bytes = code.encode()
         code_ptr = <const char*>code_bytes
-        name_ptr = <const char*>options._name
+        name_ptr = <const char*>self._nvrtc_name
 
         with nogil:
             HANDLE_RETURN_NVRTC(NULL, cynvrtc.nvrtcCreateProgram(
@@ -940,10 +1067,10 @@ cdef object _read_pch_status(cynvrtc.nvrtcProgram prog):
 cdef object Program_compile_nvrtc(Program self, str target_type, object name_expressions, object logs):
     """Compile using NVRTC backend and return ObjectCode."""
     cdef cynvrtc.nvrtcProgram prog = as_cu(self._h_nvrtc)
-    cdef list options_list = self._options.as_bytes("nvrtc", target_type)
+    cdef list options_list = self._options.as_bytes("nvrtc", target_type) + self._extra_options
 
     result = _nvrtc_compile_and_extract(
-        prog, target_type, name_expressions, logs, options_list, self._options.name,
+        prog, target_type, name_expressions, logs, options_list, self._nvrtc_name.decode(),
     )
 
     cdef bint pch_creation_possible = self._options.create_pch or self._options.pch
@@ -971,14 +1098,14 @@ cdef object Program_compile_nvrtc(Program self, str target_type, object name_exp
 
     cdef cynvrtc.nvrtcProgram retry_prog
     cdef const char* code_ptr = <const char*>self._code
-    cdef const char* name_ptr = <const char*>self._options._name
+    cdef const char* name_ptr = <const char*>self._nvrtc_name
     with nogil:
         HANDLE_RETURN_NVRTC(NULL, cynvrtc.nvrtcCreateProgram(
             &retry_prog, code_ptr, name_ptr, 0, NULL, NULL))
     self._h_nvrtc = create_nvrtc_program_handle(retry_prog)
 
     result = _nvrtc_compile_and_extract(
-        retry_prog, target_type, name_expressions, logs, options_list, self._options.name,
+        retry_prog, target_type, name_expressions, logs, options_list, self._nvrtc_name.decode(),
     )
 
     status = _read_pch_status(retry_prog)
@@ -1124,6 +1251,8 @@ cdef inline list _prepare_nvrtc_options_impl(object opts):
         elif is_sequence(opts.undefine_macro):
             for macro in opts.undefine_macro:
                 options.append(f"--undefine-macro={macro}")
+    if opts.use_bundled_headers:
+        options.append(f"--use-bundled-headers={_default_cache_dir() / 'nvrtc-bundled-headers'}")
     if opts.include_path is not None:
         if isinstance(opts.include_path, str):
             options.append(f"--include-path={opts.include_path}")
@@ -1216,6 +1345,24 @@ cdef inline list _prepare_nvrtc_options_impl(object opts):
     return [o.encode() for o in options]
 
 
+cpdef void _assert_single_dashed_nvvm_options(options: list[str]) except *:
+    """Guard against emitting a double-dashed option to libNVVM.
+
+    libNVVM's parser accepts only single-dashed options and rejects the
+    double-dashed spelling of every option with NVVM_ERROR_INVALID_OPTION
+    (see #2570). Every option on this path is generated from typed fields, so
+    a double dash can only mean a bug in ``cuda.core`` rather than bad user
+    input. Fail here, naming the option, instead of leaving the user with
+    libNVVM's opaque error.
+    """
+    for option in options:
+        if option.startswith("--"):
+            raise RuntimeError(
+                f"Internal error: NVVM option {option!r} is double-dashed. libNVVM accepts "
+                f"only single-dashed options; emit {option[1:]!r} instead."
+            )
+
+
 cdef inline object _prepare_nvvm_options_impl(object opts, bint as_bytes):
     """Build NVVM-specific compiler options."""
     options = []
@@ -1228,8 +1375,10 @@ cdef inline object _prepare_nvvm_options_impl(object opts, bint as_bytes):
     options.append(f"-arch={arch}")
     if opts.debug is not None and opts.debug:
         options.append("-g")
+    # libNVVM only accepts single-dashed options; the double-dashed spelling
+    # accepted by NVRTC is rejected with NVVM_ERROR_INVALID_OPTION.
     if opts.numba_debug:
-        options.append("--numba-debug")
+        options.append("-numba-debug")
     if opts.device_code_optimize is False:
         options.append("-opt=0")
     elif opts.device_code_optimize is True:
@@ -1268,6 +1417,8 @@ cdef inline object _prepare_nvvm_options_impl(object opts, bint as_bytes):
         unsupported.append("undefine_macro")
     if opts.include_path is not None:
         unsupported.append("include_path")
+    if opts.use_bundled_headers:
+        unsupported.append("use_bundled_headers")
     if opts.pre_include is not None:
         unsupported.append("pre_include")
     if opts.no_source_include is not None and opts.no_source_include:
@@ -1309,6 +1460,8 @@ cdef inline object _prepare_nvvm_options_impl(object opts, bint as_bytes):
     if unsupported:
         raise CUDAError(f"The following options are not supported by NVVM backend: {', '.join(unsupported)}")
 
+    _assert_single_dashed_nvvm_options(options)
+
     if as_bytes:
         return [o.encode() for o in options]
     else:
diff --git a/cuda_core/cuda/core/_resource_handles.pxd b/cuda_core/cuda/core/_resource_handles.pxd
index 2f481fee4f8..fe075b6414b 100644
--- a/cuda_core/cuda/core/_resource_handles.pxd
+++ b/cuda_core/cuda/core/_resource_handles.pxd
@@ -71,6 +71,20 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
         PreparedAttachmentState, PreparedAttachmentDeleter
     ] PreparedAttachment
 
+    cppclass PreparedChildGraphUpdateState:
+        pass
+    ctypedef shared_ptr[
+        PreparedChildGraphUpdateState
+    ] PreparedChildGraphUpdate
+
+    cppclass PreparedExecAttachmentState:
+        pass
+    cppclass PreparedExecAttachmentDeleter:
+        pass
+    ctypedef unique_ptr[
+        PreparedExecAttachmentState, PreparedExecAttachmentDeleter
+    ] PreparedExecAttachment
+
     # as_cu() - extract the raw CUDA handle (inline C++)
     cydriver.CUcontext as_cu(ContextHandle h) noexcept nogil
     cydriver.CUgreenCtx as_cu(GreenCtxHandle h) noexcept nogil
@@ -79,6 +93,7 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
     cydriver.CUmemoryPool as_cu(MemoryPoolHandle h) noexcept nogil
     cydriver.CUdeviceptr as_cu(DevicePtrHandle h) noexcept nogil
     cydriver.CUlibrary as_cu(LibraryHandle h) noexcept nogil
+    cydriver.CUmodule as_cu(cydriver.CUmodule h) noexcept nogil
     cydriver.CUkernel as_cu(KernelHandle h) noexcept nogil
     cydriver.CUgraph as_cu(GraphHandle h) noexcept nogil
     cydriver.CUgraphExec as_cu(GraphExecHandle h) noexcept nogil
@@ -101,6 +116,7 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
     intptr_t as_intptr(MemoryPoolHandle h) noexcept nogil
     intptr_t as_intptr(DevicePtrHandle h) noexcept nogil
     intptr_t as_intptr(LibraryHandle h) noexcept nogil
+    intptr_t as_intptr(const cydriver.CUmodule& h) noexcept nogil
     intptr_t as_intptr(KernelHandle h) noexcept nogil
     intptr_t as_intptr(GraphHandle h) noexcept nogil
     intptr_t as_intptr(GraphExecHandle h) noexcept nogil
@@ -124,6 +140,7 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
     object as_py(MemoryPoolHandle h)
     object as_py(DevicePtrHandle h)
     object as_py(LibraryHandle h)
+    object as_py(const cydriver.CUmodule& h)
     object as_py(KernelHandle h)
     object as_py(GraphHandle h)
     object as_py(GraphExecHandle h)
@@ -161,6 +178,12 @@ cdef GreenCtxHandle create_green_ctx_handle(
 cdef GreenCtxHandle create_green_ctx_handle_ref(cydriver.CUgreenCtx ctx) except+ nogil
 cdef ContextHandle get_primary_context(int device_id) except+ nogil
 cdef ContextHandle get_current_context() except+ nogil
+cdef cydriver.CUresult context_synchronize(
+    const ContextHandle& h_context) noexcept nogil
+cdef cydriver.CUresult context_get_stream_priority_range(
+    const ContextHandle& h_context,
+    int* least_priority,
+    int* greatest_priority) noexcept nogil
 
 # Stream handles
 cdef StreamHandle create_stream_handle(
@@ -172,13 +195,16 @@ cdef void retry_deferred_cleanup() noexcept
 cdef ContextHandle get_stream_context(const StreamHandle& h) noexcept nogil
 cdef StreamHandle get_legacy_stream() except+ nogil
 cdef StreamHandle get_per_thread_stream() except+ nogil
+cdef StreamHandle create_context_bound_legacy_stream(
+    const ContextHandle& h_context) except+ nogil
 
 # Event handles
 cdef EventHandle create_event_handle(
     const ContextHandle& h_ctx, unsigned int flags,
     bint timing_enabled, bint is_blocking_sync,
     bint ipc_enabled, int device_id) except+ nogil
-cdef EventHandle create_event_handle_noctx(unsigned int flags) except+ nogil
+cdef EventHandle create_event_handle_for_stream(
+    cydriver.CUstream stream, unsigned int flags) except+ nogil
 cdef EventHandle create_event_handle_ref(cydriver.CUevent event) except+ nogil
 cdef EventHandle create_event_handle_ipc(
     const cydriver.CUipcEventHandle& ipc_handle, bint is_blocking_sync) except+ nogil
@@ -202,7 +228,8 @@ cdef MemoryPoolHandle create_mempool_handle_ipc(
 cdef DevicePtrHandle deviceptr_alloc_from_pool(
     size_t size, const MemoryPoolHandle& h_pool, const StreamHandle& h_stream) except+ nogil
 cdef DevicePtrHandle deviceptr_alloc_async(size_t size, const StreamHandle& h_stream) except+ nogil
-cdef DevicePtrHandle deviceptr_alloc(size_t size) except+ nogil
+cdef cydriver.CUresult deviceptr_alloc_raw(
+    cydriver.CUdeviceptr* ptr, size_t size, const ContextHandle& h_context) noexcept nogil
 cdef DevicePtrHandle deviceptr_alloc_host(size_t size) except+ nogil
 cdef DevicePtrHandle deviceptr_create_ref(cydriver.CUdeviceptr ptr) except+ nogil
 cdef DevicePtrHandle deviceptr_create_with_owner(cydriver.CUdeviceptr ptr, object owner) except+ nogil
@@ -222,7 +249,7 @@ cdef void register_mr_dealloc_callback(MRDeallocCallback cb) noexcept
 cdef DevicePtrHandle deviceptr_import_ipc(
     const MemoryPoolHandle& h_pool, const void* export_data, const StreamHandle& h_stream) except+ nogil
 cdef StreamHandle deallocation_stream(const DevicePtrHandle& h) noexcept nogil
-cdef void set_deallocation_stream(const DevicePtrHandle& h, const StreamHandle& h_stream) noexcept nogil
+cdef cydriver.CUresult set_deallocation_stream(const DevicePtrHandle& h, const StreamHandle& h_stream) noexcept nogil
 
 # Library handles
 cdef LibraryHandle create_library_handle_from_file(const char* path) except+ nogil
@@ -253,11 +280,30 @@ cdef cydriver.CUresult graph_commit_attachment(
     PreparedAttachment& prepared, cydriver.CUgraphNode node) except+
 cdef cydriver.CUresult graph_clone_attachments(
     const GraphHandle& h_clone, const GraphHandle& h_source) except+
+cdef cydriver.CUresult graph_prepare_child_graph_update(
+    const GraphHandle& h_parent, const GraphHandle& h_old_child,
+    cydriver.CUgraphNode owner_node, const GraphHandle& h_source,
+    PreparedChildGraphUpdate* out_prepared) except+
+cdef cydriver.CUresult graph_commit_child_graph_update(
+    PreparedChildGraphUpdate& prepared, GraphHandle* out_child) except+
 cdef void invalidate_child_graph_state(
     const GraphHandle& h_parent, cydriver.CUgraphNode owner_node) noexcept
 
 # Graph exec handles
-cdef GraphExecHandle create_graph_exec_handle(cydriver.CUgraphExec graph_exec) except+ nogil
+cdef GraphExecHandle create_graph_exec_handle(
+    const GraphHandle& h_source,
+    cydriver.CUDA_GRAPH_INSTANTIATE_PARAMS* params) except+
+cdef cydriver.CUresult graph_exec_update(
+    const GraphExecHandle& h_exec,
+    const GraphHandle& h_source,
+    cydriver.CUgraphExecUpdateResultInfo* result_info) except+
+cdef cydriver.CUresult graph_prepare_exec_attachment(
+    const GraphExecHandle& h_exec,
+    OpaqueHandle owner0,
+    OpaqueHandle owner1,
+    PreparedExecAttachment* out_prepared) except+
+cdef void graph_commit_exec_attachment(
+    PreparedExecAttachment& prepared) noexcept
 
 # Graph node handles
 cdef GraphNodeHandle create_graph_node_handle(cydriver.CUgraphNode node, const GraphHandle& h_graph) except+ nogil
@@ -289,23 +335,29 @@ cdef FileDescriptorHandle create_fd_handle(int fd) except+ nogil
 cdef FileDescriptorHandle create_fd_handle_ref(int fd) except+ nogil
 
 # Array / mipmapped-array / texture / surface handles (PR #467)
-cdef OpaqueArrayHandle create_array_handle(const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc) except+ nogil
+cdef OpaqueArrayHandle create_array_handle(
+    const ContextHandle& h_context, const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc) except+ nogil
 cdef OpaqueArrayHandle create_array_handle_ref(cydriver.CUarray arr) except+ nogil
 cdef OpaqueArrayHandle create_array_handle_owning(cydriver.CUarray arr) except+ nogil
+cdef ContextHandle get_array_context(const OpaqueArrayHandle& h) noexcept nogil
 cdef OpaqueArrayHandle create_array_level_handle(const MipmappedArrayHandle& h_mip, unsigned int level) except+ nogil
 cdef MipmappedArrayHandle create_mipmapped_array_handle(
-    const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc, unsigned int num_levels) except+ nogil
+    const ContextHandle& h_context, const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc,
+    unsigned int num_levels) except+ nogil
+cdef ContextHandle get_mipmapped_array_context(
+    const MipmappedArrayHandle& h) noexcept nogil
 cdef TexObjectHandle create_tex_object_handle_array(
-    const cydriver.CUDA_RESOURCE_DESC& res, const cydriver.CUDA_TEXTURE_DESC& tex,
-    const OpaqueArrayHandle& h_backing) except+ nogil
+    const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+    const cydriver.CUDA_TEXTURE_DESC& tex, const OpaqueArrayHandle& h_backing) except+ nogil
 cdef TexObjectHandle create_tex_object_handle_mipmap(
-    const cydriver.CUDA_RESOURCE_DESC& res, const cydriver.CUDA_TEXTURE_DESC& tex,
-    const MipmappedArrayHandle& h_backing) except+ nogil
+    const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+    const cydriver.CUDA_TEXTURE_DESC& tex, const MipmappedArrayHandle& h_backing) except+ nogil
 cdef TexObjectHandle create_tex_object_handle_linear(
-    const cydriver.CUDA_RESOURCE_DESC& res, const cydriver.CUDA_TEXTURE_DESC& tex,
-    const DevicePtrHandle& h_backing) except+ nogil
+    const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+    const cydriver.CUDA_TEXTURE_DESC& tex, const DevicePtrHandle& h_backing) except+ nogil
 cdef SurfObjectHandle create_surf_object_handle(
-    const cydriver.CUDA_RESOURCE_DESC& res, const OpaqueArrayHandle& h_backing) except+ nogil
+    const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+    const OpaqueArrayHandle& h_backing) except+ nogil
 
 # SM resource split (13.1+ — calls through function pointer, safe on older bindings)
 # groupParams is void* here to avoid referencing CU_DEV_SM_RESOURCE_GROUP_PARAMS
@@ -315,3 +367,11 @@ cdef cydriver.CUresult sm_resource_split(
     const cydriver.CUdevResource* input, cydriver.CUdevResource* remainder,
     unsigned int flags, void* groupParams) nogil
 cdef bint has_sm_resource_split() noexcept nogil
+
+# cuMemcpyWithAttributesAsync (13.2+ — calls through function pointer, safe on older bindings)
+# attr is void* here to avoid referencing CUmemcpyAttributes (absent from
+# cuda-bindings built against CUDA < 12.8). The C++ side casts it.
+cdef cydriver.CUresult memcpy_with_attributes_async(
+    cydriver.CUdeviceptr dst, cydriver.CUdeviceptr src, size_t size,
+    void* attr, cydriver.CUstream hStream) nogil
+cdef bint has_memcpy_with_attributes_async() noexcept nogil
diff --git a/cuda_core/cuda/core/_resource_handles.pyi b/cuda_core/cuda/core/_resource_handles.pyi
index f11f6f08e00..66cbf80761a 100644
--- a/cuda_core/cuda/core/_resource_handles.pyi
+++ b/cuda_core/cuda/core/_resource_handles.pyi
@@ -1,29 +1,43 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_resource_handles.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_resource_handles.pyx
 
-from __future__ import annotations
+from typing import Callable
 
-from libcpp.memory import shared_ptr, unique_ptr
+from _typeshed import Incomplete
+from cuda.bindings import cydriver
+from typing_extensions import TypeAlias
 
-ContextHandle = shared_ptr
-GreenCtxHandle = shared_ptr
-StreamHandle = shared_ptr
-EventHandle = shared_ptr
-MemoryPoolHandle = shared_ptr
-DevicePtrHandle = shared_ptr
-LibraryHandle = shared_ptr
-KernelHandle = shared_ptr
-GraphHandle = shared_ptr
-GraphExecHandle = shared_ptr
-GraphNodeHandle = shared_ptr
-GraphicsResourceHandle = shared_ptr
-NvrtcProgramHandle = shared_ptr
-NvvmProgramHandle = shared_ptr
-NvJitLinkHandle = shared_ptr
-CuLinkHandle = shared_ptr
-FileDescriptorHandle = shared_ptr
-OpaqueArrayHandle = shared_ptr
-MipmappedArrayHandle = shared_ptr
-TexObjectHandle = shared_ptr
-SurfObjectHandle = shared_ptr
-OpaqueHandle = shared_ptr
-PreparedAttachment = unique_ptr
\ No newline at end of file
+ContextHandle: TypeAlias = Incomplete
+GreenCtxHandle: TypeAlias = Incomplete
+StreamHandle: TypeAlias = Incomplete
+EventHandle: TypeAlias = Incomplete
+MemoryPoolHandle: TypeAlias = Incomplete
+DevicePtrHandle: TypeAlias = Incomplete
+LibraryHandle: TypeAlias = Incomplete
+KernelHandle: TypeAlias = Incomplete
+GraphHandle: TypeAlias = Incomplete
+GraphExecHandle: TypeAlias = Incomplete
+GraphNodeHandle: TypeAlias = Incomplete
+GraphicsResourceHandle: TypeAlias = Incomplete
+NvrtcProgramHandle: TypeAlias = Incomplete
+NvvmProgramHandle: TypeAlias = Incomplete
+NvJitLinkHandle: TypeAlias = Incomplete
+CuLinkHandle: TypeAlias = Incomplete
+FileDescriptorHandle: TypeAlias = Incomplete
+OpaqueArrayHandle: TypeAlias = Incomplete
+MipmappedArrayHandle: TypeAlias = Incomplete
+TexObjectHandle: TypeAlias = Incomplete
+SurfObjectHandle: TypeAlias = Incomplete
+OpaqueHandle: TypeAlias = Incomplete
+PreparedAttachment: TypeAlias = Incomplete
+PreparedChildGraphUpdate: TypeAlias = Incomplete
+PreparedExecAttachment: TypeAlias = Incomplete
+MRDeallocCallback: TypeAlias = Callable[[object, cydriver.CUdeviceptr, int, StreamHandle], None]
+NvvmProgramValue: TypeAlias = Incomplete
+NvJitLinkValue: TypeAlias = Incomplete
+TexObjectValue: TypeAlias = Incomplete
+SurfObjectValue: TypeAlias = Incomplete
+PreparedAttachmentState: TypeAlias = Incomplete
+PreparedAttachmentDeleter: TypeAlias = Incomplete
+PreparedChildGraphUpdateState: TypeAlias = Incomplete
+PreparedExecAttachmentState: TypeAlias = Incomplete
+PreparedExecAttachmentDeleter: TypeAlias = Incomplete
diff --git a/cuda_core/cuda/core/_resource_handles.pyx b/cuda_core/cuda/core/_resource_handles.pyx
index f6fb6ac4e20..0f8d6e15cde 100644
--- a/cuda_core/cuda/core/_resource_handles.pyx
+++ b/cuda_core/cuda/core/_resource_handles.pyx
@@ -51,6 +51,12 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
     ContextHandle get_primary_context "cuda_core::get_primary_context" (
         int device_id) except+ nogil
     ContextHandle get_current_context "cuda_core::get_current_context" () except+ nogil
+    cydriver.CUresult context_synchronize "cuda_core::context_synchronize" (
+        const ContextHandle& h_context) noexcept nogil
+    cydriver.CUresult context_get_stream_priority_range "cuda_core::context_get_stream_priority_range" (
+        const ContextHandle& h_context,
+        int* least_priority,
+        int* greatest_priority) noexcept nogil
 
     # Stream handles
     StreamHandle create_stream_handle "cuda_core::create_stream_handle" (
@@ -67,14 +73,16 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
         const StreamHandle& h) noexcept nogil
     StreamHandle get_legacy_stream "cuda_core::get_legacy_stream" () except+ nogil
     StreamHandle get_per_thread_stream "cuda_core::get_per_thread_stream" () except+ nogil
+    StreamHandle create_context_bound_legacy_stream "cuda_core::create_context_bound_legacy_stream" (
+        const ContextHandle& h_context) except+ nogil
 
     # Event handles (note: _create_event_handle* are internal due to C++ overloading)
     EventHandle create_event_handle "cuda_core::create_event_handle" (
         const ContextHandle& h_ctx, unsigned int flags,
         bint timing_enabled, bint is_blocking_sync,
         bint ipc_enabled, int device_id) except+ nogil
-    EventHandle create_event_handle_noctx "cuda_core::create_event_handle_noctx" (
-        unsigned int flags) except+ nogil
+    EventHandle create_event_handle_for_stream "cuda_core::create_event_handle_for_stream" (
+        cydriver.CUstream stream, unsigned int flags) except+ nogil
     EventHandle create_event_handle_ref "cuda_core::create_event_handle_ref" (
         cydriver.CUevent event) except+ nogil
     EventHandle create_event_handle_ipc "cuda_core::create_event_handle_ipc" (
@@ -107,7 +115,8 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
         size_t size, const MemoryPoolHandle& h_pool, const StreamHandle& h_stream) except+ nogil
     DevicePtrHandle deviceptr_alloc_async "cuda_core::deviceptr_alloc_async" (
         size_t size, const StreamHandle& h_stream) except+ nogil
-    DevicePtrHandle deviceptr_alloc "cuda_core::deviceptr_alloc" (size_t size) except+ nogil
+    cydriver.CUresult deviceptr_alloc_raw "cuda_core::deviceptr_alloc_raw" (
+        cydriver.CUdeviceptr* ptr, size_t size, const ContextHandle& h_context) noexcept nogil
     DevicePtrHandle deviceptr_alloc_host "cuda_core::deviceptr_alloc_host" (size_t size) except+ nogil
     DevicePtrHandle deviceptr_create_ref "cuda_core::deviceptr_create_ref" (
         cydriver.CUdeviceptr ptr) except+ nogil
@@ -128,7 +137,7 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
         const MemoryPoolHandle& h_pool, const void* export_data, const StreamHandle& h_stream) except+ nogil
     StreamHandle deallocation_stream "cuda_core::deallocation_stream" (
         const DevicePtrHandle& h) noexcept nogil
-    void set_deallocation_stream "cuda_core::set_deallocation_stream" (
+    cydriver.CUresult set_deallocation_stream "cuda_core::set_deallocation_stream" (
         const DevicePtrHandle& h, const StreamHandle& h_stream) noexcept nogil
 
     # Library handles
@@ -167,12 +176,30 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
         PreparedAttachment& prepared, cydriver.CUgraphNode node) except+
     cydriver.CUresult graph_clone_attachments "cuda_core::graph_clone_attachments" (
         const GraphHandle& h_clone, const GraphHandle& h_source) except+
+    cydriver.CUresult graph_prepare_child_graph_update "cuda_core::graph_prepare_child_graph_update" (
+        const GraphHandle& h_parent, const GraphHandle& h_old_child,
+        cydriver.CUgraphNode owner_node, const GraphHandle& h_source,
+        PreparedChildGraphUpdate* out_prepared) except+
+    cydriver.CUresult graph_commit_child_graph_update "cuda_core::graph_commit_child_graph_update" (
+        PreparedChildGraphUpdate& prepared, GraphHandle* out_child) except+
     void invalidate_child_graph_state "cuda_core::invalidate_child_graph_state" (
         const GraphHandle& h_parent, cydriver.CUgraphNode owner_node) noexcept
 
     # Graph exec handles
     GraphExecHandle create_graph_exec_handle "cuda_core::create_graph_exec_handle" (
-        cydriver.CUgraphExec graph_exec) except+ nogil
+        const GraphHandle& h_source,
+        cydriver.CUDA_GRAPH_INSTANTIATE_PARAMS* params) except+
+    cydriver.CUresult graph_exec_update "cuda_core::graph_exec_update" (
+        const GraphExecHandle& h_exec,
+        const GraphHandle& h_source,
+        cydriver.CUgraphExecUpdateResultInfo* result_info) except+
+    cydriver.CUresult graph_prepare_exec_attachment "cuda_core::graph_prepare_exec_attachment" (
+        const GraphExecHandle& h_exec,
+        OpaqueHandle owner0,
+        OpaqueHandle owner1,
+        PreparedExecAttachment* out_prepared) except+
+    void graph_commit_exec_attachment "cuda_core::graph_commit_exec_attachment" (
+        PreparedExecAttachment& prepared) noexcept
 
     # Graph node handles
     GraphNodeHandle create_graph_node_handle "cuda_core::create_graph_node_handle" (
@@ -225,28 +252,42 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
         unsigned int flags, void* groupParams) nogil
     bint has_sm_resource_split "cuda_core::has_sm_resource_split" () noexcept nogil
 
+    # cuMemcpyWithAttributesAsync (13.2+ wrapper — avoids direct cydriver cimport)
+    # attr is void* to avoid referencing CUmemcpyAttributes (absent from
+    # cuda-bindings built against CUDA < 12.8). The C++ side casts it.
+    cydriver.CUresult memcpy_with_attributes_async "cuda_core::memcpy_with_attributes_async" (
+        cydriver.CUdeviceptr dst, cydriver.CUdeviceptr src, size_t size,
+        void* attr, cydriver.CUstream hStream) nogil
+    bint has_memcpy_with_attributes_async "cuda_core::has_memcpy_with_attributes_async" () noexcept nogil
+
     # Array / mipmapped-array / texture / surface handles (PR #467)
     OpaqueArrayHandle create_array_handle "cuda_core::create_array_handle" (
-        const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc) except+ nogil
+        const ContextHandle& h_context, const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc) except+ nogil
     OpaqueArrayHandle create_array_handle_ref "cuda_core::create_array_handle_ref" (
         cydriver.CUarray arr) except+ nogil
     OpaqueArrayHandle create_array_handle_owning "cuda_core::create_array_handle_owning" (
         cydriver.CUarray arr) except+ nogil
+    ContextHandle get_array_context "cuda_core::get_array_context" (
+        const OpaqueArrayHandle& h) noexcept nogil
     OpaqueArrayHandle create_array_level_handle "cuda_core::create_array_level_handle" (
         const MipmappedArrayHandle& h_mip, unsigned int level) except+ nogil
     MipmappedArrayHandle create_mipmapped_array_handle "cuda_core::create_mipmapped_array_handle" (
-        const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc, unsigned int num_levels) except+ nogil
+        const ContextHandle& h_context, const cydriver.CUDA_ARRAY3D_DESCRIPTOR& desc,
+        unsigned int num_levels) except+ nogil
+    ContextHandle get_mipmapped_array_context "cuda_core::get_mipmapped_array_context" (
+        const MipmappedArrayHandle& h) noexcept nogil
     TexObjectHandle create_tex_object_handle_array "cuda_core::create_tex_object_handle_array" (
-        const cydriver.CUDA_RESOURCE_DESC& res, const cydriver.CUDA_TEXTURE_DESC& tex,
-        const OpaqueArrayHandle& h_backing) except+ nogil
+        const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+        const cydriver.CUDA_TEXTURE_DESC& tex, const OpaqueArrayHandle& h_backing) except+ nogil
     TexObjectHandle create_tex_object_handle_mipmap "cuda_core::create_tex_object_handle_mipmap" (
-        const cydriver.CUDA_RESOURCE_DESC& res, const cydriver.CUDA_TEXTURE_DESC& tex,
-        const MipmappedArrayHandle& h_backing) except+ nogil
+        const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+        const cydriver.CUDA_TEXTURE_DESC& tex, const MipmappedArrayHandle& h_backing) except+ nogil
     TexObjectHandle create_tex_object_handle_linear "cuda_core::create_tex_object_handle_linear" (
-        const cydriver.CUDA_RESOURCE_DESC& res, const cydriver.CUDA_TEXTURE_DESC& tex,
-        const DevicePtrHandle& h_backing) except+ nogil
+        const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+        const cydriver.CUDA_TEXTURE_DESC& tex, const DevicePtrHandle& h_backing) except+ nogil
     SurfObjectHandle create_surf_object_handle "cuda_core::create_surf_object_handle" (
-        const cydriver.CUDA_RESOURCE_DESC& res, const OpaqueArrayHandle& h_backing) except+ nogil
+        const ContextHandle& h_context, const cydriver.CUDA_RESOURCE_DESC& res,
+        const OpaqueArrayHandle& h_backing) except+ nogil
 
 
 # =============================================================================
@@ -271,10 +312,17 @@ cdef const char* _CUDA_DRIVER_API_V1_NAME = b"cuda.core._resource_handles._CUDA_
 
 # Declare extern variables with reinterpret_cast to allow void* assignment
 cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
+    # Error formatting
+    void* p_cuGetErrorName "reinterpret_cast<void*&>(cuda_core::p_cuGetErrorName)"
+    void* p_cuGetErrorString "reinterpret_cast<void*&>(cuda_core::p_cuGetErrorString)"
+
     # Context
     void* p_cuDevicePrimaryCtxRetain "reinterpret_cast<void*&>(cuda_core::p_cuDevicePrimaryCtxRetain)"
     void* p_cuDevicePrimaryCtxRelease "reinterpret_cast<void*&>(cuda_core::p_cuDevicePrimaryCtxRelease)"
     void* p_cuCtxGetCurrent "reinterpret_cast<void*&>(cuda_core::p_cuCtxGetCurrent)"
+    void* p_cuCtxSetCurrent "reinterpret_cast<void*&>(cuda_core::p_cuCtxSetCurrent)"
+    void* p_cuCtxSynchronize "reinterpret_cast<void*&>(cuda_core::p_cuCtxSynchronize)"
+    void* p_cuCtxGetStreamPriorityRange "reinterpret_cast<void*&>(cuda_core::p_cuCtxGetStreamPriorityRange)"
     void* p_cuGreenCtxCreate "reinterpret_cast<void*&>(cuda_core::p_cuGreenCtxCreate)"
     void* p_cuGreenCtxDestroy "reinterpret_cast<void*&>(cuda_core::p_cuGreenCtxDestroy)"
     void* p_cuCtxFromGreenCtx "reinterpret_cast<void*&>(cuda_core::p_cuCtxFromGreenCtx)"
@@ -284,6 +332,7 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
     # Stream
     void* p_cuStreamCreateWithPriority "reinterpret_cast<void*&>(cuda_core::p_cuStreamCreateWithPriority)"
     void* p_cuStreamDestroy "reinterpret_cast<void*&>(cuda_core::p_cuStreamDestroy)"
+    void* p_cuStreamGetCtx "reinterpret_cast<void*&>(cuda_core::p_cuStreamGetCtx)"
 
     # Event
     void* p_cuEventCreate "reinterpret_cast<void*&>(cuda_core::p_cuEventCreate)"
@@ -322,6 +371,8 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
 
     # Graph
     void* p_cuGraphDestroy "reinterpret_cast<void*&>(cuda_core::p_cuGraphDestroy)"
+    void* p_cuGraphInstantiateWithParams "reinterpret_cast<void*&>(cuda_core::p_cuGraphInstantiateWithParams)"
+    void* p_cuGraphExecUpdate "reinterpret_cast<void*&>(cuda_core::p_cuGraphExecUpdate)"
     void* p_cuGraphExecDestroy "reinterpret_cast<void*&>(cuda_core::p_cuGraphExecDestroy)"
     void* p_cuUserObjectCreate "reinterpret_cast<void*&>(cuda_core::p_cuUserObjectCreate)"
     void* p_cuUserObjectRelease "reinterpret_cast<void*&>(cuda_core::p_cuUserObjectRelease)"
@@ -351,6 +402,9 @@ cdef extern from "_cpp/resource_handles.hpp" namespace "cuda_core":
     # SM resource split (13.1+)
     void* p_cuDevSmResourceSplit "reinterpret_cast<void*&>(cuda_core::p_cuDevSmResourceSplit)"
 
+    # cuMemcpyWithAttributesAsync (13.2+)
+    void* p_cuMemcpyWithAttributesAsync "reinterpret_cast<void*&>(cuda_core::p_cuMemcpyWithAttributesAsync)"
+
     # NVRTC
     void* p_nvrtcDestroyProgram "reinterpret_cast<void*&>(cuda_core::p_nvrtcDestroyProgram)"
 
@@ -376,10 +430,12 @@ cdef void* _get_optional_driver_fn(str name):
 
 
 cdef void _init_driver_fn_pointers() noexcept:
+    global p_cuGetErrorName, p_cuGetErrorString
     global p_cuDevicePrimaryCtxRetain, p_cuDevicePrimaryCtxRelease, p_cuCtxGetCurrent
+    global p_cuCtxSetCurrent, p_cuCtxSynchronize, p_cuCtxGetStreamPriorityRange
     global p_cuGreenCtxCreate, p_cuGreenCtxDestroy, p_cuCtxFromGreenCtx
     global p_cuDevResourceGenerateDesc, p_cuGreenCtxStreamCreate
-    global p_cuStreamCreateWithPriority, p_cuStreamDestroy
+    global p_cuStreamCreateWithPriority, p_cuStreamDestroy, p_cuStreamGetCtx
     global p_cuEventCreate, p_cuEventDestroy, p_cuIpcOpenEventHandle
     global p_cuDeviceGetCount
     global p_cuMemPoolSetAccess, p_cuMemPoolDestroy, p_cuMemPoolCreate
@@ -388,22 +444,31 @@ cdef void _init_driver_fn_pointers() noexcept:
     global p_cuMemFreeAsync, p_cuMemFree, p_cuMemFreeHost
     global p_cuMemPoolImportPointer
     global p_cuLibraryLoadFromFile, p_cuLibraryLoadData, p_cuLibraryUnload, p_cuLibraryGetKernel
-    global p_cuGraphDestroy, p_cuGraphExecDestroy
+    global p_cuGraphDestroy, p_cuGraphInstantiateWithParams
+    global p_cuGraphExecUpdate, p_cuGraphExecDestroy
     global p_cuUserObjectCreate, p_cuUserObjectRelease
     global p_cuGraphRetainUserObject, p_cuGraphReleaseUserObject
     global p_cuGraphNodeFindInClone, p_cuGraphChildGraphNodeGetGraph
     global p_cuLinkDestroy
     global p_cuGraphicsUnmapResources, p_cuGraphicsUnregisterResource
     global p_cuDevSmResourceSplit
+    global p_cuMemcpyWithAttributesAsync
     global p_cuArray3DCreate, p_cuArrayDestroy
     global p_cuMipmappedArrayCreate, p_cuMipmappedArrayDestroy, p_cuMipmappedArrayGetLevel
     global p_cuTexObjectCreate, p_cuTexObjectDestroy
     global p_cuSurfObjectCreate, p_cuSurfObjectDestroy
 
+    # Error formatting
+    p_cuGetErrorName = _get_driver_fn("cuGetErrorName")
+    p_cuGetErrorString = _get_driver_fn("cuGetErrorString")
+
     # Context
     p_cuDevicePrimaryCtxRetain = _get_driver_fn("cuDevicePrimaryCtxRetain")
     p_cuDevicePrimaryCtxRelease = _get_driver_fn("cuDevicePrimaryCtxRelease")
     p_cuCtxGetCurrent = _get_driver_fn("cuCtxGetCurrent")
+    p_cuCtxSetCurrent = _get_driver_fn("cuCtxSetCurrent")
+    p_cuCtxSynchronize = _get_driver_fn("cuCtxSynchronize")
+    p_cuCtxGetStreamPriorityRange = _get_driver_fn("cuCtxGetStreamPriorityRange")
     p_cuGreenCtxCreate = _get_optional_driver_fn("cuGreenCtxCreate")
     p_cuGreenCtxDestroy = _get_optional_driver_fn("cuGreenCtxDestroy")
     p_cuCtxFromGreenCtx = _get_optional_driver_fn("cuCtxFromGreenCtx")
@@ -413,6 +478,7 @@ cdef void _init_driver_fn_pointers() noexcept:
     # Stream
     p_cuStreamCreateWithPriority = _get_driver_fn("cuStreamCreateWithPriority")
     p_cuStreamDestroy = _get_driver_fn("cuStreamDestroy")
+    p_cuStreamGetCtx = _get_driver_fn("cuStreamGetCtx")
 
     # Event
     p_cuEventCreate = _get_driver_fn("cuEventCreate")
@@ -451,6 +517,8 @@ cdef void _init_driver_fn_pointers() noexcept:
 
     # Graph
     p_cuGraphDestroy = _get_driver_fn("cuGraphDestroy")
+    p_cuGraphInstantiateWithParams = _get_driver_fn("cuGraphInstantiateWithParams")
+    p_cuGraphExecUpdate = _get_driver_fn("cuGraphExecUpdate")
     p_cuGraphExecDestroy = _get_driver_fn("cuGraphExecDestroy")
     p_cuUserObjectCreate = _get_driver_fn("cuUserObjectCreate")
     p_cuUserObjectRelease = _get_driver_fn("cuUserObjectRelease")
@@ -480,6 +548,9 @@ cdef void _init_driver_fn_pointers() noexcept:
     # SM resource split (13.1+ — may not exist in older cuda-bindings)
     p_cuDevSmResourceSplit = _get_optional_driver_fn("cuDevSmResourceSplit")
 
+    # cuMemcpyWithAttributesAsync (13.2+ — may not exist in older cuda-bindings)
+    p_cuMemcpyWithAttributesAsync = _get_optional_driver_fn("cuMemcpyWithAttributesAsync")
+
 _init_driver_fn_pointers()
 initialize_deferred_cleanup()
 
diff --git a/cuda_core/cuda/core/_stream.pxd b/cuda_core/cuda/core/_stream.pxd
index de16b84bde2..5de11a36761 100644
--- a/cuda_core/cuda/core/_stream.pxd
+++ b/cuda_core/cuda/core/_stream.pxd
@@ -23,3 +23,9 @@ cdef class Stream:
 
 cpdef Stream default_stream()
 cpdef Stream Stream_accept(arg, bint allow_stream_protocol=*)
+cdef inline int Stream_check_open(Stream self) except -1:
+    if not self._h_stream:
+        raise RuntimeError("Stream has been closed")
+    return 0
+cdef bint Stream_is_default_token(Stream self) noexcept nogil
+cdef bint Stream_is_legacy_default_token(Stream self) noexcept nogil
diff --git a/cuda_core/cuda/core/_stream.pyi b/cuda_core/cuda/core/_stream.pyi
index f4d78982a1d..eba5458d862 100644
--- a/cuda_core/cuda/core/_stream.pyi
+++ b/cuda_core/cuda/core/_stream.pyi
@@ -1,18 +1,19 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_stream.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_stream.pyx
 
 from dataclasses import dataclass
 from typing import Protocol
 
 import cuda.bindings.driver
-import cython
+from _typeshed import Incomplete
 from cuda.core._context import Context
 from cuda.core._device import Device
 from cuda.core._device_resources import DeviceResources
 from cuda.core._event import Event, EventOptions
 from cuda.core.graph import GraphBuilder
 
+__all__ = ['LEGACY_DEFAULT_STREAM', 'PER_THREAD_DEFAULT_STREAM', 'Stream', 'StreamOptions']
+LEGACY_DEFAULT_STREAM: Stream = Stream._legacy_default()
+PER_THREAD_DEFAULT_STREAM: Stream = Stream._per_thread_default()
 
 @dataclass
 class StreamOptions:
@@ -27,11 +28,10 @@ class StreamOptions:
         higher priority. (Default to lowest priority)
 
     """
-    nonblocking: cython.bint = True
+    nonblocking: Incomplete = True
     priority: int | None = None
 
 class IsStreamType(Protocol):
-
     def __cuda_stream__(self) -> tuple[int, int]:
         """
         For any Python object that is meant to be interpreted as a CUDA stream, the intent
@@ -56,42 +56,35 @@ class Stream:
     object, or created directly through using an existing handle
     using Stream.from_handle().
     """
-
-    def close(self):
-        """Destroy the stream.
-
-        Releases the stream handle. For owned streams, this destroys the
-        underlying CUDA stream. For borrowed streams, this releases the
-        reference and allows the Python owner to be GC'd.
-        """
-
-    def __init__(self, *args, **kwargs) -> None:
-        ...
-
+    def __init__(self, *args, **kwargs) -> None: ...
     @classmethod
     def _legacy_default(cls) -> Stream:
         """Return the legacy default stream (supports subclassing)."""
-
     @classmethod
     def _per_thread_default(cls) -> Stream:
         """Return the per-thread default stream (supports subclassing)."""
-
     @classmethod
-    def _init(cls, obj: IsStreamType | None=None, options: object=None, device_id: int | None=None, ctx: Context | None=None) -> Stream:
-        ...
+    def _init(cls, obj: IsStreamType | None=None, options: StreamOptions | None=None, device_id: int | None=None, ctx: Context | None=None) -> Stream: ...
+    def close(self):
+        """Destroy the stream.
 
+        Releases the stream handle. For owned streams, this destroys the
+        underlying CUDA stream. For borrowed streams, this releases the
+        reference and allows the Python owner to be GC'd.
+
+        .. warning::
+            Do not close :obj:`LEGACY_DEFAULT_STREAM` or
+            :obj:`PER_THREAD_DEFAULT_STREAM`. They are shared module-level
+            objects, so closing one invalidates it for the rest of the process.
+        """
+    @property
+    def is_closed(self) -> bool:
+        """Whether this stream has been closed."""
     def __cuda_stream__(self) -> tuple[int, int]:
         """Return an instance of a __cuda_stream__ protocol."""
-
-    def __hash__(self) -> int:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __repr__(self) -> str:
-        ...
-
+    def __hash__(self) -> int: ...
+    def __eq__(self, other: object) -> bool: ...
+    def __repr__(self) -> str: ...
     @property
     def handle(self) -> cuda.bindings.driver.CUstream:
         """Return the underlying ``CUstream`` object.
@@ -101,18 +94,14 @@ class Stream:
             This handle is a Python object. To get the memory address of the underlying C
             handle, call ``int(Stream.handle)``.
         """
-
     @property
     def is_nonblocking(self) -> bool:
         """Return True if this is a nonblocking stream, otherwise False."""
-
     @property
     def priority(self) -> int:
         """Return the stream priority."""
-
     def sync(self) -> None:
         """Synchronize the stream."""
-
     def record(self, event: Event | None=None, options: EventOptions | None=None) -> Event:
         """Record an event onto the stream.
 
@@ -131,8 +120,14 @@ class Stream:
         :obj:`~_event.Event`
             Newly created event object.
 
-        """
+        Note
+        ----
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so a newly created event is
+        associated with the current context at call time.
 
+        """
     def wait(self, event_or_stream: Event | Stream) -> None:
         """Wait for a CUDA event or a CUDA stream.
 
@@ -150,23 +145,34 @@ class Stream:
             streams.
 
         """
-
     @property
     def device(self) -> Device:
         """Return the :obj:`~_device.Device` singleton associated with this stream.
 
         Note
         ----
-        The current context on the device may differ from this
-        stream's context. This case occurs when a different CUDA
-        context is set current after a stream is created.
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so this returns the device for
+        the current context at call time.
 
-        """
+        For a created stream, the current context on the device may differ from
+        this stream's context. That case occurs when a different CUDA context is
+        set current after the stream is created.
 
+        """
     @property
     def context(self) -> Context:
-        """Return the :obj:`~_context.Context` associated with this stream."""
+        """Return the :obj:`~_context.Context` associated with this stream.
 
+        Note
+        ----
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so this returns the current
+        context at call time.
+
+        """
     @property
     def resources(self) -> DeviceResources:
         """Query the hardware resources provisioned for this stream's context.
@@ -174,8 +180,15 @@ class Stream:
         For streams created from a green context, returns the resources
         that context was provisioned with. For streams on the primary
         context, returns the full device resources.
-        """
 
+        Note
+        ----
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so this queries the current
+        context at call time.
+
+        """
     @staticmethod
     def from_handle(handle) -> Stream:
         """Create a new :obj:`~_stream.Stream` object from a foreign stream handle.
@@ -200,7 +213,6 @@ class Stream:
             Newly created stream object.
 
         """
-
     def create_graph_builder(self) -> GraphBuilder:
         """Create a new :obj:`~graph.GraphBuilder` object.
 
@@ -212,8 +224,6 @@ class Stream:
             Newly created graph builder object.
 
         """
-LEGACY_DEFAULT_STREAM: Stream = Stream._legacy_default()
-PER_THREAD_DEFAULT_STREAM: Stream = Stream._per_thread_default()
 
 def default_stream() -> Stream:
     """Return the default CUDA :obj:`~_stream.Stream`.
@@ -225,6 +235,4 @@ def default_stream() -> Stream:
     the legacy stream.
 
     """
-
-def Stream_accept(arg, allow_stream_protocol: bool=False) -> Stream:
-    ...
\ No newline at end of file
+def Stream_accept(arg, allow_stream_protocol: bool=False) -> Stream: ...
diff --git a/cuda_core/cuda/core/_stream.pyx b/cuda_core/cuda/core/_stream.pyx
index 5212ec5c7de..e662d67c87f 100644
--- a/cuda_core/cuda/core/_stream.pyx
+++ b/cuda_core/cuda/core/_stream.pyx
@@ -9,7 +9,7 @@ from libc.stdlib cimport strtol, getenv
 
 from cuda.bindings cimport cydriver
 
-from cuda.core._event cimport Event as cyEvent
+from cuda.core._event cimport Event as cyEvent, Event_accept
 from cuda.core._utils.cuda_utils cimport (
     check_or_create_options,
     HANDLE_RETURN,
@@ -20,7 +20,10 @@ import warnings
 from dataclasses import dataclass
 from typing import Protocol, TYPE_CHECKING
 
-from cuda.core._context cimport Context
+from cuda.core._context cimport (
+    Context,
+    Context_check_open,
+)
 from cuda.core._device_resources cimport DeviceResources
 from cuda.core._event import Event, EventOptions
 
@@ -29,9 +32,10 @@ from cuda.core._resource_handles cimport (
     EventHandle,
     StreamHandle,
     create_context_handle_ref,
-    create_event_handle_noctx,
+    create_event_handle_for_stream,
     create_stream_handle,
     create_stream_handle_with_owner,
+    context_get_stream_priority_range,
     get_current_context,
     get_last_error,
     get_legacy_stream,
@@ -47,6 +51,9 @@ if TYPE_CHECKING:
     from cuda.core._device import Device
     from cuda.core.graph import GraphBuilder
 
+__all__ = ['LEGACY_DEFAULT_STREAM', 'PER_THREAD_DEFAULT_STREAM', 'Stream', 'StreamOptions']
+
+
 @dataclass
 cdef class StreamOptions:
     """Customizable :obj:`~_stream.Stream` options.
@@ -120,16 +127,13 @@ cdef class Stream:
         return Stream._from_handle(cls, get_per_thread_stream())
 
     @classmethod
-    def _init(cls, obj: IsStreamType | None = None, options: object = None,
+    @cython.annotation_typing(False)
+    def _init(cls, obj: IsStreamType | None = None, options: StreamOptions | None = None,
               device_id: int | None = None, ctx: Context | None = None) -> Stream:
         cdef StreamHandle h_stream
         cdef cydriver.CUstream borrowed
         cdef ContextHandle h_context
-        cdef Stream self
-
-        # Extract context handle if provided
-        if ctx is not None:
-            h_context = (<Context>ctx)._h_context
+        cdef Context context
 
         if obj is not None and options is not None:
             raise ValueError("obj and options cannot be both specified")
@@ -141,6 +145,12 @@ cdef class Stream:
             h_stream = create_stream_handle_with_owner(borrowed, obj)
             return Stream._from_handle(cls, h_stream)
 
+        if ctx is None:
+            raise RuntimeError("A CUDA context is required to create a stream")
+        context = <Context>ctx
+        Context_check_open(context)
+        h_context = context._h_context
+
         cdef StreamOptions opts = check_or_create_options(StreamOptions, options, "Stream options")
         nonblocking = opts.nonblocking
         priority = opts.priority
@@ -150,14 +160,8 @@ cdef class Stream:
         # TODO: we might want to consider memoizing high/low per CUDA context and avoid this call
         cdef int high, low
         cdef cydriver.CUresult res_code
-        with nogil:
-            res_code = cydriver.cuCtxGetStreamPriorityRange(&high, &low)
-        if res_code != cydriver.CUresult.CUDA_SUCCESS:
-            if res_code == cydriver.CUresult.CUDA_ERROR_INVALID_CONTEXT:
-                raise RuntimeError(
-                    "No current CUDA context. Call dev.set_current() before creating streams."
-                )
-            HANDLE_RETURN(res_code)
+        res_code = context_get_stream_priority_range(context._h_context, &high, &low)
+        HANDLE_RETURN(res_code)
         cdef int prio
         if priority is not None:
             prio = priority
@@ -185,7 +189,7 @@ cdef class Stream:
                 )
             else:
                 HANDLE_RETURN(res_code)
-        self = Stream._from_handle(cls, h_stream)
+        cdef Stream self = Stream._from_handle(cls, h_stream)
         self._nonblocking = int(nonblocking)
         self._priority = prio
         if device_id is not None:
@@ -198,11 +202,22 @@ cdef class Stream:
         Releases the stream handle. For owned streams, this destroys the
         underlying CUDA stream. For borrowed streams, this releases the
         reference and allows the Python owner to be GC'd.
+
+        .. warning::
+            Do not close :obj:`LEGACY_DEFAULT_STREAM` or
+            :obj:`PER_THREAD_DEFAULT_STREAM`. They are shared module-level
+            objects, so closing one invalidates it for the rest of the process.
         """
         self._h_stream.reset()
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this stream has been closed."""
+        return self._h_stream.get() == NULL
+
     def __cuda_stream__(self) -> tuple[int, int]:
         """Return an instance of a __cuda_stream__ protocol."""
+        Stream_check_open(self)
         return (0, as_intptr(self._h_stream))
 
     def __hash__(self) -> int:
@@ -214,8 +229,11 @@ cdef class Stream:
         return as_intptr(self._h_stream) == as_intptr((<Stream>other)._h_stream)
 
     def __repr__(self) -> str:
-        Stream_ensure_ctx(self)
-        return f"<Stream handle={as_intptr(self._h_stream):#x} context={as_intptr(self._h_context):#x}>"
+        cdef ContextHandle h_context
+        if not self._h_stream:
+            return "<Stream handle=0x0 context=0x0>"
+        Stream_get_ctx(self, &h_context)
+        return f"<Stream handle={as_intptr(self._h_stream):#x} context={as_intptr(h_context):#x}>"
 
     @property
     def handle(self) -> cuda.bindings.driver.CUstream:
@@ -231,6 +249,7 @@ cdef class Stream:
     @property
     def is_nonblocking(self) -> bool:
         """Return True if this is a nonblocking stream, otherwise False."""
+        Stream_check_open(self)
         cdef unsigned int flags
         if self._nonblocking == -1:
             with nogil:
@@ -241,6 +260,7 @@ cdef class Stream:
     @property
     def priority(self) -> int:
         """Return the stream priority."""
+        Stream_check_open(self)
         cdef int prio
         if self._priority == INT32_MIN:
             with nogil:
@@ -250,6 +270,7 @@ cdef class Stream:
 
     def sync(self) -> None:
         """Synchronize the stream."""
+        Stream_check_open(self)
         with nogil:
             HANDLE_RETURN(cydriver.cuStreamSynchronize(as_cu(self._h_stream)))
 
@@ -271,23 +292,36 @@ cdef class Stream:
         :obj:`~_event.Event`
             Newly created event object.
 
+        Note
+        ----
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so a newly created event is
+        associated with the current context at call time.
+
         """
         # Create an Event object (or reusing the given one) by recording
         # on the stream. Event flags such as disabling timing, nonblocking,
         # and CU_EVENT_RECORD_EXTERNAL, can be set in EventOptions.
+        Stream_check_open(self)
+        cdef ContextHandle h_context
+        cdef int device_id
+        cdef cyEvent event_obj
         if event is None:
-            Stream_ensure_ctx_device(self)
-            event = cyEvent._init(cyEvent, self._device_id, self._h_context, options, False)
-        elif event.is_ipc_enabled:
+            Stream_get_ctx_device(self, &h_context, &device_id)
+            event_obj = cyEvent._init(cyEvent, device_id, h_context, options, False)
+        else:
+            event_obj = Event_accept(event)
+        if event is not None and event_obj.is_ipc_enabled:
             raise TypeError(
                 "IPC-enabled events should not be re-recorded, instead create a "
                 "new event by supplying options."
             )
 
-        cdef cydriver.CUevent e = as_cu((<cyEvent?>(event))._h_event)
+        cdef cydriver.CUevent e = as_cu(event_obj._h_event)
         with nogil:
             HANDLE_RETURN(cydriver.cuEventRecord(e, as_cu(self._h_stream)))
-        return event
+        return event_obj
 
     def wait(self, event_or_stream: Event | Stream) -> None:
         """Wait for a CUDA event or a CUDA stream.
@@ -306,20 +340,24 @@ cdef class Stream:
             streams.
 
         """
+        Stream_check_open(self)
         cdef Stream stream
+        cdef cyEvent event
         cdef EventHandle h_event
 
         # Handle Event directly
         if isinstance(event_or_stream, Event):
+            event = Event_accept(event_or_stream)
             with nogil:
                 # TODO: support flags other than 0?
                 HANDLE_RETURN(cydriver.cuStreamWaitEvent(
-                    as_cu(self._h_stream), as_cu((<cyEvent>event_or_stream)._h_event), 0))
+                    as_cu(self._h_stream), as_cu(event._h_event), 0))
             return
 
         # Convert to Stream if needed
         if isinstance(event_or_stream, Stream):
             stream = <Stream>event_or_stream
+            Stream_check_open(stream)
         else:
             try:
                 stream = Stream._init(obj=event_or_stream)
@@ -329,9 +367,14 @@ cdef class Stream:
                     f" got {type(event_or_stream)}"
                 ) from e
 
-        # Wait on stream via temporary event
+        # Wait on stream via a temporary event created in that stream's own
+        # context; an event from the current context would be rejected by
+        # cuEventRecord when the streams live on different devices.
         with nogil:
-            h_event = create_event_handle_noctx(cydriver.CUevent_flags.CU_EVENT_DISABLE_TIMING)
+            h_event = create_event_handle_for_stream(
+                as_cu(stream._h_stream), cydriver.CUevent_flags.CU_EVENT_DISABLE_TIMING)
+            if not h_event:
+                HANDLE_RETURN(get_last_error())
             HANDLE_RETURN(cydriver.cuEventRecord(as_cu(h_event), as_cu(stream._h_stream)))
             # TODO: support flags other than 0?
             HANDLE_RETURN(cydriver.cuStreamWaitEvent(as_cu(self._h_stream), as_cu(h_event), 0))
@@ -342,21 +385,40 @@ cdef class Stream:
 
         Note
         ----
-        The current context on the device may differ from this
-        stream's context. This case occurs when a different CUDA
-        context is set current after a stream is created.
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so this returns the device for
+        the current context at call time.
+
+        For a created stream, the current context on the device may differ from
+        this stream's context. That case occurs when a different CUDA context is
+        set current after the stream is created.
 
         """
+        Stream_check_open(self)
         from cuda.core._device import Device  # avoid circular import
-        Stream_ensure_ctx_device(self)
-        return Device(self._device_id)
+        cdef ContextHandle h_context
+        cdef int device_id
+        Stream_get_ctx_device(self, &h_context, &device_id)
+        return Device(device_id)
 
     @property
     def context(self) -> Context:
-        """Return the :obj:`~_context.Context` associated with this stream."""
-        Stream_ensure_ctx(self)
-        Stream_ensure_ctx_device(self)
-        return Context._from_handle(Context, self._h_context, self._device_id)
+        """Return the :obj:`~_context.Context` associated with this stream.
+
+        Note
+        ----
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so this returns the current
+        context at call time.
+
+        """
+        Stream_check_open(self)
+        cdef ContextHandle h_context
+        cdef int device_id
+        Stream_get_ctx_device(self, &h_context, &device_id)
+        return Context._from_handle(Context, h_context, device_id)
 
     @property
     def resources(self) -> DeviceResources:
@@ -365,10 +427,20 @@ cdef class Stream:
         For streams created from a green context, returns the resources
         that context was provisioned with. For streams on the primary
         context, returns the full device resources.
+
+        Note
+        ----
+        A default stream (:obj:`LEGACY_DEFAULT_STREAM` or
+        :obj:`PER_THREAD_DEFAULT_STREAM`) carries no context of its own; it
+        refers to whichever context is current, so this queries the current
+        context at call time.
+
         """
-        Stream_ensure_ctx(self)
-        Stream_ensure_ctx_device(self)
-        return DeviceResources._init_from_ctx(self._h_context, self._device_id)
+        Stream_check_open(self)
+        cdef ContextHandle h_context
+        cdef int device_id
+        Stream_get_ctx_device(self, &h_context, &device_id)
+        return DeviceResources._init_from_ctx(h_context, device_id)
 
     @staticmethod
     def from_handle(handle) -> Stream:
@@ -412,6 +484,7 @@ cdef class Stream:
             Newly created graph builder object.
 
         """
+        Stream_check_open(self)
         from cuda.core.graph._graph_builder import GraphBuilder
 
         return GraphBuilder._init(self)
@@ -444,46 +517,82 @@ cpdef Stream default_stream():
     else:
         return LEGACY_DEFAULT_STREAM
 
+cdef inline bint Stream_is_default_token(Stream self) noexcept nogil:
+    """Return True for CU_STREAM_LEGACY and CU_STREAM_PER_THREAD.
+
+    These tokens carry no context of their own; they refer to whatever context
+    is current, so nothing resolved from one may be cached on the object.
+    """
+    cdef uintptr_t h = <uintptr_t>as_cu(self._h_stream)
+    return h == <uintptr_t>cydriver.CU_STREAM_LEGACY or h == <uintptr_t>cydriver.CU_STREAM_PER_THREAD
 
-cdef inline int Stream_ensure_ctx(Stream self) except?-1 nogil:
-    """Ensure the stream's context handle is populated."""
+
+cdef inline bint Stream_is_legacy_default_token(Stream self) noexcept nogil:
+    """Return True only for CU_STREAM_LEGACY.
+
+    Unlike CU_STREAM_PER_THREAD, the legacy default stream token is rejected
+    outright (CUDA_ERROR_INVALID_VALUE) by cuMemcpyWithAttributesAsync and
+    cuMemcpyBatchAsync; CU_STREAM_PER_THREAD is a real stream to those entry
+    points and is accepted normally. Use this narrower check, not
+    Stream_is_default_token, wherever that distinction matters.
+    """
+    return <uintptr_t>as_cu(self._h_stream) == <uintptr_t>cydriver.CU_STREAM_LEGACY
+
+
+cdef inline int Stream_get_ctx(Stream self, ContextHandle* h_context) except?-1 nogil:
+    """Resolve the stream's context handle into ``h_context``."""
     cdef cydriver.CUcontext ctx
-    if not self._h_context:
-        self._h_context = get_stream_context(self._h_stream)
-    if self._h_context:
+    cdef bint is_default = Stream_is_default_token(self)
+
+    # Default-stream tokens must never reuse a sticky object field, even if
+    # something else populated ``_h_context`` (defense in depth for #2485).
+    if self._h_context and not is_default:
+        h_context[0] = self._h_context
         return 0
-    HANDLE_RETURN(cydriver.cuStreamGetCtx(as_cu(self._h_stream), &ctx))
-    if ctx != NULL:
-        with gil:
-            self._h_context = create_context_handle_ref(ctx)
+
+    h_context[0] = get_stream_context(self._h_stream)
+    if not h_context[0]:
+        HANDLE_RETURN(cydriver.cuStreamGetCtx(as_cu(self._h_stream), &ctx))
+        if ctx != NULL:
+            with gil:
+                h_context[0] = create_context_handle_ref(ctx)
+
+    if h_context[0] and not is_default:
+        self._h_context = h_context[0]
     return 0
 
 
-cdef inline int Stream_ensure_ctx_device(Stream self) except?-1:
-    """Ensure the stream's context and device_id are populated."""
+cdef inline int Stream_get_ctx_device(Stream self, ContextHandle* h_context, int* device_id) except?-1:
+    """Resolve the stream's context handle and device ID."""
     cdef cydriver.CUcontext ctx
     cdef cydriver.CUdevice target_dev
     cdef ContextHandle current_context
     cdef bint switch_context
+    cdef bint is_default = Stream_is_default_token(self)
 
-    if self._device_id < 0:
-        with nogil:
+    with nogil:
+        Stream_get_ctx(self, h_context)
+        if self._device_id >= 0 and not is_default:
+            device_id[0] = self._device_id
+        else:
             # Get device ID from context, switching context temporarily if needed
-            Stream_ensure_ctx(self)
             current_context = get_current_context()
-            switch_context = (as_cu(current_context) != as_cu(self._h_context))
+            switch_context = (as_cu(current_context) != as_cu(h_context[0]))
             if switch_context:
-                HANDLE_RETURN(cydriver.cuCtxPushCurrent(as_cu(self._h_context)))
+                HANDLE_RETURN(cydriver.cuCtxPushCurrent(as_cu(h_context[0])))
             HANDLE_RETURN(cydriver.cuCtxGetDevice(&target_dev))
             if switch_context:
                 HANDLE_RETURN(cydriver.cuCtxPopCurrent(&ctx))
-        self._device_id = <int>target_dev
+            device_id[0] = <int>target_dev
+            if not is_default:
+                self._device_id = device_id[0]
     return 0
 
 
 cdef cydriver.CUstream _handle_from_stream_protocol(obj) except*:
     if isinstance(obj, Stream):
-        return <cydriver.CUstream><uintptr_t>(obj.handle)
+        Stream_check_open(<Stream>obj)
+        return as_cu((<Stream>obj)._h_stream)
 
     try:
         cuda_stream_attr = obj.__cuda_stream__
@@ -494,7 +603,6 @@ cdef cydriver.CUstream _handle_from_stream_protocol(obj) except*:
         info = cuda_stream_attr()
     else:
         info = cuda_stream_attr
-        warnings.simplefilter("once", DeprecationWarning)
         warnings.warn(
             "Implementing __cuda_stream__ as an attribute is deprecated; it must be implemented as a method",
             stacklevel=3,
@@ -520,15 +628,20 @@ cdef cydriver.CUstream _handle_from_stream_protocol(obj) except*:
 cpdef Stream Stream_accept(arg, bint allow_stream_protocol=False):
     from cuda.core.graph._graph_builder import GraphBuilder
 
+    cdef Stream stream
     if arg is None:
         raise TypeError(
             "stream is required and must not be None; "
             "pass device.default_stream explicitly to use the default stream."
         )
     if isinstance(arg, Stream):
-        return <Stream>(arg)
+        stream = <Stream>arg
+        Stream_check_open(stream)
+        return stream
     elif isinstance(arg, GraphBuilder):
-        return <Stream>(arg.stream)
+        stream = <Stream>arg.stream
+        Stream_check_open(stream)
+        return stream
     elif allow_stream_protocol and hasattr(arg, "__cuda_stream__"):
         stream = Stream._init(arg)
         warnings.warn(
@@ -538,5 +651,5 @@ cpdef Stream Stream_accept(arg, bint allow_stream_protocol=False):
             stacklevel=2,
             category=DeprecationWarning,
         )
-        return <Stream>(stream)
+        return stream
     raise TypeError(f"Stream or GraphBuilder expected, got {type(arg).__name__}")
diff --git a/cuda_core/cuda/core/_tensor_bridge.pyi b/cuda_core/cuda/core/_tensor_bridge.pyi
index 22948d5b864..3afb8ee33ff 100644
--- a/cuda_core/cuda/core/_tensor_bridge.pyi
+++ b/cuda_core/cuda/core/_tensor_bridge.pyi
@@ -1,4 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_tensor_bridge.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_tensor_bridge.pyx
 
 """Tensor bridge: extract PyTorch tensor metadata via the AOTI stable C ABI.
 
@@ -46,13 +46,22 @@ Credit: Emilio Castillo (ecastillo@nvidia.com) – original tensor-bridge POC.
    ``torch._C`` has been re-opened with ``RTLD_GLOBAL`` *before*
    importing this module so that the AOTI symbols are visible.
 """
-from __future__ import annotations
+from typing import Any, Callable, TypedDict
 
 import numpy
 from cuda.core._memoryview import StridedMemoryView
+from typing_extensions import TypeAlias
 
-AOTITorchError = int
+AOTITorchError: TypeAlias = int
+AtenTensorHandle: TypeAlias = AtenTensorOpaque
+_get_cuda_stream_fn_t: TypeAlias = Callable[[int, Any], AOTITorchError]
 
+class PyObject(TypedDict): ...
+
+class AtenTensorOpaque(TypedDict): ...
+
+def resolve_aoti_dtype(dtype_code: int) -> numpy.dtype:
+    """Python-callable wrapper around _get_aoti_dtype (for lazy resolution)."""
 def sync_torch_stream(device_index: int, consumer_s: int) -> int:
     """Establish stream ordering between PyTorch's current CUDA stream
     and the given consumer stream.
@@ -61,10 +70,6 @@ def sync_torch_stream(device_index: int, consumer_s: int) -> int:
     the consumer stream wait on it.  This is a no-op if both streams are
     the same.
     """
-
-def resolve_aoti_dtype(dtype_code: int) -> numpy.dtype:
-    """Python-callable wrapper around _get_aoti_dtype (for lazy resolution)."""
-
 def view_as_torch_tensor(obj: object, stream_ptr: object, view: StridedMemoryView | None=None) -> StridedMemoryView:
     """Create/populate a :class:`StridedMemoryView` from a ``torch.Tensor``.
 
@@ -82,4 +87,4 @@ def view_as_torch_tensor(obj: object, stream_ptr: object, view: StridedMemoryVie
     view : StridedMemoryView, optional
         If provided, populate this existing view in-place.  Otherwise a
         new instance is created.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/_tensor_bridge.pyx b/cuda_core/cuda/core/_tensor_bridge.pyx
index dd41c77c051..ae7a6794507 100644
--- a/cuda_core/cuda/core/_tensor_bridge.pyx
+++ b/cuda_core/cuda/core/_tensor_bridge.pyx
@@ -56,8 +56,9 @@ from cuda.core._layout cimport _StridedLayout
 from cuda.bindings cimport cydriver
 from cuda.core._resource_handles cimport (
     EventHandle,
-    create_event_handle_noctx,
+    create_event_handle_for_stream,
     as_cu,
+    get_last_error,
 )
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 
@@ -318,8 +319,12 @@ cpdef int sync_torch_stream(int32_t device_index,
                b"aoti_torch_get_current_cuda_stream")
     if <intptr_t>producer_s != consumer_s:
         with nogil:
-            h_event = create_event_handle_noctx(
-                cydriver.CUevent_flags.CU_EVENT_DISABLE_TIMING)
+            # The event must belong to the producer stream's context to be
+            # recorded on it, whatever context is current here.
+            h_event = create_event_handle_for_stream(
+                <cydriver.CUstream>producer_s, cydriver.CUevent_flags.CU_EVENT_DISABLE_TIMING)
+            if not h_event:
+                HANDLE_RETURN(get_last_error())
             HANDLE_RETURN(cydriver.cuEventRecord(
                 as_cu(h_event), <cydriver.CUstream>producer_s))
             HANDLE_RETURN(cydriver.cuStreamWaitEvent(
@@ -361,9 +366,7 @@ def view_as_torch_tensor(
     cdef int32_t dtype_code
     cdef int32_t device_type, device_index
     cdef StridedMemoryView buf
-    cdef int itemsize
     cdef intptr_t _stream_ptr_int
-    cdef _StridedLayout layout
 
     # Note: we intentionally skip PyTorch's Python-level __dlpack__ guards
     # (requires_grad, is_conj, is_neg, non-strided layout, wrong-device)
@@ -436,8 +439,8 @@ def view_as_torch_tensor(
 
     # Build _StridedLayout.  init_from_ptr copies shape/strides so we are
     # safe even though they are borrowed pointers.
-    itemsize = _get_aoti_itemsize(dtype_code)
-    layout = _StridedLayout.__new__(_StridedLayout)
+    cdef int itemsize = _get_aoti_itemsize(dtype_code)
+    cdef _StridedLayout layout = _StridedLayout.__new__(_StridedLayout)
     layout.init_from_ptr(
         <int>ndim,
         sizes_ptr,
diff --git a/cuda_core/cuda/core/_tensor_map.pyi b/cuda_core/cuda/core/_tensor_map.pyi
index 986ab41549f..e1f0685bde9 100644
--- a/cuda_core/cuda/core/_tensor_map.pyi
+++ b/cuda_core/cuda/core/_tensor_map.pyi
@@ -1,15 +1,30 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_tensor_map.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_tensor_map.pyx
 
+import enum
 from dataclasses import dataclass
 
 import numpy
 from cuda.bindings import cydriver
 from cuda.core._device import Device
 
+__all__ = ['TensorMapDescriptor', 'TensorMapDescriptorOptions']
+_TMA_DT_UINT8: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT8)
+_TMA_DT_UINT16: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT16)
+_TMA_DT_UINT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT32)
+_TMA_DT_INT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT32)
+_TMA_DT_UINT64: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT64)
+_TMA_DT_INT64: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT64)
+_TMA_DT_FLOAT16: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT16)
+_TMA_DT_FLOAT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32)
+_TMA_DT_FLOAT64: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT64)
+_TMA_DT_BFLOAT16: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_BFLOAT16)
+_TMA_DT_FLOAT32_FTZ: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ)
+_TMA_DT_TFLOAT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32)
+_TMA_DT_TFLOAT32_FTZ: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ)
+_NUMPY_DTYPE_TO_TMA = {numpy.dtype(numpy.uint8): _TMA_DT_UINT8, numpy.dtype(numpy.uint16): _TMA_DT_UINT16, numpy.dtype(numpy.uint32): _TMA_DT_UINT32, numpy.dtype(numpy.int32): _TMA_DT_INT32, numpy.dtype(numpy.uint64): _TMA_DT_UINT64, numpy.dtype(numpy.int64): _TMA_DT_INT64, numpy.dtype(numpy.float16): _TMA_DT_FLOAT16, numpy.dtype(numpy.float32): _TMA_DT_FLOAT32, numpy.dtype(numpy.float64): _TMA_DT_FLOAT64}
+_TMA_DATA_TYPE_SIZE = {_TMA_DT_UINT8: 1, _TMA_DT_UINT16: 2, _TMA_DT_UINT32: 4, _TMA_DT_INT32: 4, _TMA_DT_UINT64: 8, _TMA_DT_INT64: 8, _TMA_DT_FLOAT16: 2, _TMA_DT_FLOAT32: 4, _TMA_DT_FLOAT64: 8, _TMA_DT_BFLOAT16: 2, _TMA_DT_FLOAT32_FTZ: 4, _TMA_DT_TFLOAT32: 4, _TMA_DT_TFLOAT32_FTZ: 4}
 
-class TensorMapDataType:
+class TensorMapDataType(enum.IntEnum):
     """Data types for tensor map descriptors.
 
     These correspond to the ``CUtensorMapDataType`` driver enum values.
@@ -28,7 +43,7 @@ class TensorMapDataType:
     TFLOAT32 = cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32
     TFLOAT32_FTZ = cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ
 
-class TensorMapInterleave:
+class TensorMapInterleave(enum.IntEnum):
     """Interleave layout for tensor map descriptors.
 
     These correspond to the ``CUtensorMapInterleave`` driver enum values.
@@ -37,7 +52,7 @@ class TensorMapInterleave:
     INTERLEAVE_16B = cydriver.CU_TENSOR_MAP_INTERLEAVE_16B
     INTERLEAVE_32B = cydriver.CU_TENSOR_MAP_INTERLEAVE_32B
 
-class TensorMapSwizzle:
+class TensorMapSwizzle(enum.IntEnum):
     """Swizzle mode for tensor map descriptors.
 
     These correspond to the ``CUtensorMapSwizzle`` driver enum values.
@@ -47,7 +62,7 @@ class TensorMapSwizzle:
     SWIZZLE_64B = cydriver.CU_TENSOR_MAP_SWIZZLE_64B
     SWIZZLE_128B = cydriver.CU_TENSOR_MAP_SWIZZLE_128B
 
-class TensorMapL2Promotion:
+class TensorMapL2Promotion(enum.IntEnum):
     """L2 promotion mode for tensor map descriptors.
 
     These correspond to the ``CUtensorMapL2promotion`` driver enum values.
@@ -57,7 +72,7 @@ class TensorMapL2Promotion:
     L2_128B = cydriver.CU_TENSOR_MAP_L2_PROMOTION_L2_128B
     L2_256B = cydriver.CU_TENSOR_MAP_L2_PROMOTION_L2_256B
 
-class TensorMapOOBFill:
+class TensorMapOOBFill(enum.IntEnum):
     """Out-of-bounds fill mode for tensor map descriptors.
 
     These correspond to the ``CUtensorMapFloatOOBfill`` driver enum values.
@@ -65,7 +80,7 @@ class TensorMapOOBFill:
     NONE = cydriver.CU_TENSOR_MAP_FLOAT_OOB_FILL_NONE
     NAN_REQUEST_ZERO_FMA = cydriver.CU_TENSOR_MAP_FLOAT_OOB_FILL_NAN_REQUEST_ZERO_FMA
 
-class TensorMapIm2ColWideMode:
+class TensorMapIm2ColWideMode(enum.IntEnum):
     """Im2col wide mode for tensor map descriptors.
 
     This enum is always defined for API stability, but the
@@ -105,8 +120,7 @@ class TensorMapDescriptorOptions:
     l2_promotion: TensorMapL2Promotion = TensorMapL2Promotion.NONE
     oob_fill: TensorMapOOBFill = TensorMapOOBFill.NONE
 
-    def __post_init__(self) -> None:
-        ...
+    def __post_init__(self) -> None: ...
 
 class TensorMapDescriptor:
     """Describes a TMA (Tensor Memory Accelerator) tensor map for Hopper+ GPUs.
@@ -121,16 +135,12 @@ class TensorMapDescriptor:
     descriptors can be passed directly to :func:`~cuda.core.launch` as a
     kernel argument.
     """
-
-    def __init__(self):
-        ...
-
+    def __init__(self): ...
     @property
     def device(self) -> Device | None:
         """Return the :obj:`~cuda.core.Device` associated with this descriptor."""
-
     @classmethod
-    def _from_tiled(cls, view, box_dim=None, *, options=None, element_strides=None, data_type=None, interleave=..., swizzle=..., l2_promotion=..., oob_fill=...):
+    def _from_tiled(cls, view, box_dim=None, *, options=None, element_strides=None, data_type=None, interleave=TensorMapInterleave.NONE, swizzle=TensorMapSwizzle.NONE, l2_promotion=TensorMapL2Promotion.NONE, oob_fill=TensorMapOOBFill.NONE):
         """Create a tiled TMA descriptor from a validated view.
 
         Parameters
@@ -171,9 +181,8 @@ class TensorMapDescriptor:
             If the tensor rank is outside [1, 5], the pointer is not
             16-byte aligned, or dimension/stride constraints are violated.
         """
-
     @classmethod
-    def _from_im2col(cls, view, pixel_box_lower_corner, pixel_box_upper_corner, channels_per_pixel, pixels_per_column, *, element_strides=None, data_type=None, interleave=..., swizzle=..., l2_promotion=..., oob_fill=...):
+    def _from_im2col(cls, view, pixel_box_lower_corner, pixel_box_upper_corner, channels_per_pixel, pixels_per_column, *, element_strides=None, data_type=None, interleave=TensorMapInterleave.NONE, swizzle=TensorMapSwizzle.NONE, l2_promotion=TensorMapL2Promotion.NONE, oob_fill=TensorMapOOBFill.NONE):
         """Create an im2col TMA descriptor from a validated view.
 
         Im2col layout is used for convolution-style data access patterns.
@@ -219,9 +228,8 @@ class TensorMapDescriptor:
             If the tensor rank is outside [3, 5], the pointer is not
             16-byte aligned, or other constraints are violated.
         """
-
     @classmethod
-    def _from_im2col_wide(cls, view, pixel_box_lower_corner_width, pixel_box_upper_corner_width, channels_per_pixel, pixels_per_column, *, element_strides=None, data_type=None, interleave=..., mode=..., swizzle=..., l2_promotion=..., oob_fill=...):
+    def _from_im2col_wide(cls, view, pixel_box_lower_corner_width, pixel_box_upper_corner_width, channels_per_pixel, pixels_per_column, *, element_strides=None, data_type=None, interleave=TensorMapInterleave.NONE, mode=TensorMapIm2ColWideMode.W, swizzle=TensorMapSwizzle.SWIZZLE_128B, l2_promotion=TensorMapL2Promotion.NONE, oob_fill=TensorMapOOBFill.NONE):
         """Create an im2col-wide TMA descriptor from a validated view.
 
         Im2col-wide layout loads elements exclusively along the W (width)
@@ -267,7 +275,6 @@ class TensorMapDescriptor:
             If the tensor rank is outside [3, 5], the pointer is not
             16-byte aligned, or other constraints are violated.
         """
-
     def replace_address(self, tensor: object) -> None:
         """Replace the global memory address in this tensor map descriptor.
 
@@ -281,43 +288,16 @@ class TensorMapDescriptor:
             or a :obj:`~cuda.core.StridedMemoryView`. Must refer to
             device-accessible memory with a 16-byte-aligned pointer.
         """
+    def __repr__(self) -> str: ...
 
-    def __repr__(self) -> str:
-        ...
-_TMA_DT_UINT8 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT8)
-_TMA_DT_UINT16 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT16)
-_TMA_DT_UINT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT32)
-_TMA_DT_INT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT32)
-_TMA_DT_UINT64 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT64)
-_TMA_DT_INT64 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT64)
-_TMA_DT_FLOAT16 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT16)
-_TMA_DT_FLOAT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32)
-_TMA_DT_FLOAT64 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT64)
-_TMA_DT_BFLOAT16 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_BFLOAT16)
-_TMA_DT_FLOAT32_FTZ = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ)
-_TMA_DT_TFLOAT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32)
-_TMA_DT_TFLOAT32_FTZ = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ)
-_NUMPY_DTYPE_TO_TMA = {numpy.dtype(numpy.uint8): _TMA_DT_UINT8, numpy.dtype(numpy.uint16): _TMA_DT_UINT16, numpy.dtype(numpy.uint32): _TMA_DT_UINT32, numpy.dtype(numpy.int32): _TMA_DT_INT32, numpy.dtype(numpy.uint64): _TMA_DT_UINT64, numpy.dtype(numpy.int64): _TMA_DT_INT64, numpy.dtype(numpy.float16): _TMA_DT_FLOAT16, numpy.dtype(numpy.float32): _TMA_DT_FLOAT32, numpy.dtype(numpy.float64): _TMA_DT_FLOAT64}
-_TMA_DATA_TYPE_SIZE = {_TMA_DT_UINT8: 1, _TMA_DT_UINT16: 2, _TMA_DT_UINT32: 4, _TMA_DT_INT32: 4, _TMA_DT_UINT64: 8, _TMA_DT_INT64: 8, _TMA_DT_FLOAT16: 2, _TMA_DT_FLOAT32: 4, _TMA_DT_FLOAT64: 8, _TMA_DT_BFLOAT16: 2, _TMA_DT_FLOAT32_FTZ: 4, _TMA_DT_TFLOAT32: 4, _TMA_DT_TFLOAT32_FTZ: 4}
-
-def _normalize_tensor_map_data_type(data_type):
-    ...
-
-def _normalize_tensor_map_sequence(name, values):
-    ...
-
-def _require_tensor_map_enum(name, value, enum_type):
-    ...
-
-def _coerce_tensor_map_descriptor_options(box_dim, options, *, element_strides, data_type, interleave, swizzle, l2_promotion, oob_fill):
-    ...
-
+def _normalize_tensor_map_data_type(data_type): ...
+def _normalize_tensor_map_sequence(name, values): ...
+def _require_tensor_map_enum(name, value, enum_type): ...
+def _coerce_tensor_map_descriptor_options(box_dim, options, *, element_strides, data_type, interleave, swizzle, l2_promotion, oob_fill): ...
 def _resolve_data_type(view, data_type):
     """Resolve the TMA data type from an explicit value or the view's dtype."""
-
 def _get_validated_view(tensor):
     """Obtain a device-accessible StridedMemoryView with a 16-byte-aligned pointer."""
-
 def _require_view_device(view, expected_device_id, operation):
     """Ensure device-local tensors match the current CUDA device.
 
@@ -325,12 +305,10 @@ def _require_view_device(view, expected_device_id, operation):
     ``kDLCUDAManaged`` with ``device_id=0`` regardless of the current device,
     so only true ``kDLCUDA`` tensors are rejected by device-id mismatch.
     """
-
 def _compute_byte_strides(shape, strides, elem_size):
     """Compute byte strides from element strides or C-contiguous fallback.
 
     Returns a tuple of byte strides in row-major order.
     """
-
 def _validate_element_strides(element_strides, rank):
-    """Validate or default element_strides to all-ones."""
\ No newline at end of file
+    """Validate or default element_strides to all-ones."""
diff --git a/cuda_core/cuda/core/_tensor_map.pyx b/cuda_core/cuda/core/_tensor_map.pyx
index 7e059fe7b98..3b8b54dd8f3 100644
--- a/cuda_core/cuda/core/_tensor_map.pyx
+++ b/cuda_core/cuda/core/_tensor_map.pyx
@@ -47,6 +47,8 @@ try:
 except ImportError:
     ml_bfloat16 = None
 
+__all__ = ['TensorMapDescriptor', 'TensorMapDescriptorOptions']
+
 
 class TensorMapDataType(enum.IntEnum):
     """Data types for tensor map descriptors.
@@ -130,19 +132,19 @@ ELSE:
         W128 = 1
 
 
-_TMA_DT_UINT8 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT8)
-_TMA_DT_UINT16 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT16)
-_TMA_DT_UINT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT32)
-_TMA_DT_INT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT32)
-_TMA_DT_UINT64 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT64)
-_TMA_DT_INT64 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT64)
-_TMA_DT_FLOAT16 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT16)
-_TMA_DT_FLOAT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32)
-_TMA_DT_FLOAT64 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT64)
-_TMA_DT_BFLOAT16 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_BFLOAT16)
-_TMA_DT_FLOAT32_FTZ = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ)
-_TMA_DT_TFLOAT32 = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32)
-_TMA_DT_TFLOAT32_FTZ = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ)
+_TMA_DT_UINT8: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT8)
+_TMA_DT_UINT16: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT16)
+_TMA_DT_UINT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT32)
+_TMA_DT_INT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT32)
+_TMA_DT_UINT64: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_UINT64)
+_TMA_DT_INT64: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_INT64)
+_TMA_DT_FLOAT16: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT16)
+_TMA_DT_FLOAT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32)
+_TMA_DT_FLOAT64: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT64)
+_TMA_DT_BFLOAT16: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_BFLOAT16)
+_TMA_DT_FLOAT32_FTZ: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_FLOAT32_FTZ)
+_TMA_DT_TFLOAT32: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32)
+_TMA_DT_TFLOAT32_FTZ: int = int(cydriver.CU_TENSOR_MAP_DATA_TYPE_TFLOAT32_FTZ)
 
 
 def _normalize_tensor_map_data_type(data_type):
@@ -485,7 +487,6 @@ cdef class TensorMapDescriptor:
     cdef int _check_context_compat(self) except -1:
         cdef cydriver.CUcontext current_ctx
         cdef cydriver.CUdevice current_dev
-        cdef int current_dev_id
         if self._context == 0 and self._device_id < 0:
             return 0
         with nogil:
@@ -497,7 +498,7 @@ cdef class TensorMapDescriptor:
                 "TensorMapDescriptor was created in a different CUDA context")
         with nogil:
             HANDLE_RETURN(cydriver.cuCtxGetDevice(&current_dev))
-        current_dev_id = <int>current_dev
+        cdef int current_dev_id = <int>current_dev
         if self._device_id >= 0 and current_dev_id != self._device_id:
             raise RuntimeError(
                 f"TensorMapDescriptor belongs to device {self._device_id}, "
diff --git a/cuda_core/cuda/core/_utils/_weak_handles.pyi b/cuda_core/cuda/core/_utils/_weak_handles.pyi
index 3cf095d7b87..7facc12b267 100644
--- a/cuda_core/cuda/core/_utils/_weak_handles.pyi
+++ b/cuda_core/cuda/core/_utils/_weak_handles.pyi
@@ -1,4 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_utils/_weak_handles.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_utils/_weak_handles.pyx
 
 """Test-only weak handles for resource-handle lifetime checks.
 
@@ -20,8 +20,10 @@ handle field (see ``*.pxd``), assigns to :ctype:`OpaqueHandle`, and extend the
 Python owners via ``make_opaque_py`` are not covered here -- use
 :class:`weakref.ref` on a weak-referenceable owner object in tests instead.
 """
-from __future__ import annotations
+from _typeshed import Incomplete
+from typing_extensions import TypeAlias
 
+OpaqueWeakHandle: TypeAlias = Incomplete
 
 class WeakHandle:
     """Non-owning weak handle for a resource's shared control block.
@@ -30,21 +32,18 @@ class WeakHandle:
     falsy once the last strong reference is released. Obtain instances via
     :func:`weak_handle` rather than constructing directly.
     """
-
-    def __bool__(self):
-        ...
-
+    def __bool__(self): ...
     def expired(self):
         """Return ``True`` once every strong owner of the handle is gone."""
-
     def use_count(self):
         """Number of strong owners currently sharing the handle."""
 
 def weak_handle(obj):
     """Return a :class:`WeakHandle` observing the resource behind ``obj``.
 
-    Currently supports :class:`~cuda.core.Buffer` (device allocation handle).
-    See the module docstring for how to add more types.
+    Currently supports :class:`~cuda.core.Buffer` (allocation handle) and
+    :class:`~cuda.core.graph.GraphDefinition` (graph hierarchy handle). See
+    the module docstring for how to add more types.
 
     Raises
     ------
@@ -52,4 +51,4 @@ def weak_handle(obj):
         If ``obj`` is a :class:`~cuda.core.Buffer` with no active allocation.
     TypeError
         If ``obj`` is not a supported type.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/_utils/_weak_handles.pyx b/cuda_core/cuda/core/_utils/_weak_handles.pyx
index 65737b958a6..d9f71e36772 100644
--- a/cuda_core/cuda/core/_utils/_weak_handles.pyx
+++ b/cuda_core/cuda/core/_utils/_weak_handles.pyx
@@ -23,6 +23,7 @@ Python owners via ``make_opaque_py`` are not covered here -- use
 """
 
 from cuda.core._memory._buffer cimport Buffer
+from cuda.core.graph._graph_definition cimport GraphDefinition
 from cuda.core._resource_handles cimport OpaqueHandle
 
 
@@ -85,11 +86,19 @@ cdef WeakHandle _weak_from_buffer(Buffer buf):
     return _weak_from_opaque(h)
 
 
+cdef WeakHandle _weak_from_graph_definition(GraphDefinition graph):
+    cdef OpaqueHandle h = graph._h_graph
+    if not h:
+        raise ValueError("GraphDefinition has no active graph")
+    return _weak_from_opaque(h)
+
+
 def weak_handle(obj):
     """Return a :class:`WeakHandle` observing the resource behind ``obj``.
 
-    Currently supports :class:`~cuda.core.Buffer` (device allocation handle).
-    See the module docstring for how to add more types.
+    Currently supports :class:`~cuda.core.Buffer` (allocation handle) and
+    :class:`~cuda.core.graph.GraphDefinition` (graph hierarchy handle). See
+    the module docstring for how to add more types.
 
     Raises
     ------
@@ -100,7 +109,9 @@ def weak_handle(obj):
     """
     if isinstance(obj, Buffer):
         return _weak_from_buffer(obj)
+    if isinstance(obj, GraphDefinition):
+        return _weak_from_graph_definition(obj)
     raise TypeError(
         f"weak_handle() does not support {type(obj).__name__!r}; "
-        "supported types: Buffer"
+        "supported types: Buffer, GraphDefinition"
     )
diff --git a/cuda_core/cuda/core/_utils/_wsl_locale.pyi b/cuda_core/cuda/core/_utils/_wsl_locale.pyi
index 267bdf244f0..ecee8bc773c 100644
--- a/cuda_core/cuda/core/_utils/_wsl_locale.pyi
+++ b/cuda_core/cuda/core/_utils/_wsl_locale.pyi
@@ -1,7 +1,10 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_utils/_wsl_locale.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_utils/_wsl_locale.pyx
 
-from __future__ import annotations
+from typing import Any
 
+from typing_extensions import TypeAlias
+
+locale_t: TypeAlias = Any
 
 class c_locale_guard:
     """Context manager that pins the calling thread to the "C" locale.
@@ -9,12 +12,6 @@ class c_locale_guard:
     Uses POSIX newlocale/uselocale/freelocale so other threads' view of the
     locale is unaffected. Restores the previous thread locale on exit.
     """
-
-    def __cinit__(self) -> None:
-        ...
-
-    def __enter__(self):
-        ...
-
-    def __exit__(self, exc_type, exc_val, exc_tb):
-        ...
\ No newline at end of file
+    def __init__(self) -> None: ...
+    def __enter__(self): ...
+    def __exit__(self, exc_type, exc_val, exc_tb): ...
diff --git a/cuda_core/cuda/core/_utils/cuda_utils.pxd b/cuda_core/cuda/core/_utils/cuda_utils.pxd
index 11e464e6381..9b485597912 100644
--- a/cuda_core/cuda/core/_utils/cuda_utils.pxd
+++ b/cuda_core/cuda/core/_utils/cuda_utils.pxd
@@ -18,11 +18,35 @@ ctypedef fused integer_t:
 cdef const cydriver.CUcontext CU_CONTEXT_INVALID = <cydriver.CUcontext>(-2)
 
 
-cdef int HANDLE_RETURN(cydriver.CUresult err) except?-1 nogil
-cdef int HANDLE_RETURN_NVRTC(cynvrtc.nvrtcProgram prog, cynvrtc.nvrtcResult err) except?-1 nogil
-cdef int HANDLE_RETURN_NVVM(cynvvm.nvvmProgram prog, cynvvm.nvvmResult err) except?-1 nogil
-cdef int HANDLE_RETURN_NVJITLINK(
-    cynvjitlink.nvJitLinkHandle handle, cynvjitlink.nvJitLinkResult err) except?-1 nogil
+cdef inline int HANDLE_RETURN(cydriver.CUresult err) except?-1 nogil:
+    if err != cydriver.CUresult.CUDA_SUCCESS:
+        return _check_driver_error(err)
+    return 0
+
+
+cdef inline int HANDLE_RETURN_NVRTC(cynvrtc.nvrtcProgram prog, cynvrtc.nvrtcResult err) except?-1 nogil:
+    """Handle NVRTC result codes, raising NVRTCError with program log on failure."""
+    if err == cynvrtc.nvrtcResult.NVRTC_SUCCESS:
+        return 0
+    with gil:
+        _raise_nvrtc_error(prog, err)
+
+
+cdef inline int HANDLE_RETURN_NVVM(cynvvm.nvvmProgram prog, cynvvm.nvvmResult err) except?-1 nogil:
+    """Handle NVVM result codes, raising nvvmError with program log on failure."""
+    if err == cynvvm.nvvmResult.NVVM_SUCCESS:
+        return 0
+    with gil:
+        _raise_nvvm_error(prog, err)
+
+
+cdef inline int HANDLE_RETURN_NVJITLINK(
+        cynvjitlink.nvJitLinkHandle handle, cynvjitlink.nvJitLinkResult err) except?-1 nogil:
+    """Handle nvJitLink result codes, raising nvJitLinkError with error log on failure."""
+    if err == cynvjitlink.nvJitLinkResult.NVJITLINK_SUCCESS:
+        return 0
+    with gil:
+        _raise_nvjitlink_error(handle, err)
 
 
 # Helper for retrieving the current CUDA device. Raises if no active context
@@ -34,7 +58,9 @@ cdef int _get_current_device_id() except? -1
 cpdef int _check_driver_error(cydriver.CUresult error) except?-1 nogil
 cpdef int _check_runtime_error(error) except?-1
 cpdef int _check_nvrtc_error(error) except?-1
-
+cdef int _raise_nvrtc_error(cynvrtc.nvrtcProgram prog, cynvrtc.nvrtcResult err) except -1
+cdef int _raise_nvvm_error(cynvvm.nvvmProgram prog, cynvvm.nvvmResult err) except -1
+cdef int _raise_nvjitlink_error(cynvjitlink.nvJitLinkHandle handle, cynvjitlink.nvJitLinkResult err) except -1
 
 cpdef check_or_create_options(type cls, options, str options_description=*, bint keep_none=*)
 
diff --git a/cuda_core/cuda/core/_utils/cuda_utils.pyi b/cuda_core/cuda/core/_utils/cuda_utils.pyi
index 87067927724..51f992fa238 100644
--- a/cuda_core/cuda/core/_utils/cuda_utils.pyi
+++ b/cuda_core/cuda/core/_utils/cuda_utils.pyi
@@ -1,21 +1,25 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_utils/cuda_utils.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_utils/cuda_utils.pyx
 
-from __future__ import annotations
-
-from collections import namedtuple
-from typing import Any, Callable
+from typing import Any, Callable, NamedTuple
 
 from cuda.bindings import cydriver
 from cuda.bindings import driver as driver
 from cuda.bindings import nvrtc as nvrtc
 from cuda.bindings import runtime as runtime
 
+_keep_driver_in_stub: driver.CUresult
+_keep_nvrtc_in_stub: nvrtc.nvrtcResult
+_keep_runtime_in_stub: runtime.cudaError_t
+_fork_warning_checked = False
+
+class CUDAError(Exception): ...
 
-class CUDAError(Exception):
-    ...
+class NVRTCError(CUDAError): ...
 
-class NVRTCError(CUDAError):
-    ...
+class ComputeCapability(NamedTuple):
+    """A named tuple of (major, minor) CUDA compute capability version numbers."""
+    major: int
+    minor: int
 
 class Transaction:
     """
@@ -35,81 +39,32 @@ class Transaction:
         append(fn, *args, **kwargs): Register an undo action to be called on rollback.
         commit(): Disarm all undo actions; nothing will be rolled back on exit.
     """
-
-    def __init__(self) -> None:
-        ...
-
-    def __enter__(self):
-        ...
-
-    def __exit__(self, exc_type, exc, tb):
-        ...
-
+    def __init__(self) -> None: ...
+    def __enter__(self): ...
+    def __exit__(self, exc_type, exc, tb): ...
     def append(self, fn: Callable[..., Any], /, *args: Any, **kwargs) -> None:
         """
         Register an undo action (runs if the with-block exits without commit()).
         Values are bound now via partial so late mutations don't bite you.
         """
-
     def commit(self) -> None:
         """
         Disarm all undo actions. After this, exiting the with-block does nothing.
         """
-_keep_driver_in_stub: 'driver.CUresult'
-_keep_nvrtc_in_stub: 'nvrtc.nvrtcResult'
-_keep_runtime_in_stub: 'runtime.cudaError_t'
-ComputeCapability = namedtuple('ComputeCapability', ('major', 'minor'))
-_fork_warning_checked = False
-
-def _check_driver_error(error: cydriver.CUresult) -> int:
-    ...
-
-def _check_runtime_error(error) -> int:
-    ...
-
-def _check_nvrtc_error(error, handle=None) -> int:
-    ...
 
+def cast_to_3_tuple(label: str, cfg: int | tuple[int, ...]) -> tuple[int, int, int]: ...
+def _check_driver_error(error: cydriver.CUresult) -> int: ...
+def _check_runtime_error(error) -> int: ...
+def _check_nvrtc_error(error, handle=None) -> int: ...
+def handle_return(result: tuple[Any, ...], handle: object | None=None) -> Any: ...
 def check_or_create_options(cls: type, options: object, options_description: str='', keep_none: bool=False) -> object:
     """
     Create the specified options dataclass from a dictionary of options or None.
     """
-
-def _parse_fill_value(value) -> tuple:
-    """Parse a fill/memset value into (raw_value, element_size).
-
-    Parameters
-    ----------
-    value : int or buffer-protocol object
-        - int: Must be in range [0, 256). Treated as 1-byte fill.
-        - bytes or buffer-protocol: Must be 1, 2, or 4 bytes.
-
-    Returns
-    -------
-    tuple of (int, int)
-        (raw_value, element_size) where element_size is 1, 2, or 4.
-
-    Raises
-    ------
-    OverflowError
-        If int value is outside [0, 256).
-    TypeError
-        If value is not an int and does not support the buffer protocol.
-    ValueError
-        If value byte length is not 1, 2, or 4.
-    """
-
-def cast_to_3_tuple(label: str, cfg: int | tuple[int, ...]) -> tuple[int, int, int]:
-    ...
-
-def handle_return(result: tuple[Any, ...], handle: object=None) -> Any:
-    ...
-
 def _handle_boolean_option(option: bool) -> str:
     """
     Convert a boolean option to a string representation.
     """
-
 def precondition(checker: Callable[..., None], what: str='') -> Callable[..., Any]:
     """
     A decorator that adds checks to ensure any preconditions are met.
@@ -122,23 +77,42 @@ def precondition(checker: Callable[..., None], what: str='') -> Callable[..., An
     Returns:
         Callable: A decorator that creates the wrapping.
     """
-
 def is_sequence(obj: object) -> bool:
     """
     Check if the given object is a sequence (list or tuple).
     """
-
 def is_nested_sequence(obj: object) -> bool:
     """
     Check if the given object is a nested sequence (list or tuple with atleast one list or tuple element).
     """
-
 def reset_fork_warning() -> None:
     """Reset the fork warning check flag for testing purposes.
 
     This function is intended for use in tests to allow multiple test runs
     to check the warning behavior.
     """
+def _parse_fill_value(value) -> tuple[Any, ...]:
+    """Parse a fill/memset value into (raw_value, element_size).
 
+    Parameters
+    ----------
+    value : int or buffer-protocol object
+        - int: Must be in range [0, 256). Treated as 1-byte fill.
+        - bytes or buffer-protocol: Must be 1, 2, or 4 bytes.
+
+    Returns
+    -------
+    tuple of (int, int)
+        (raw_value, element_size) where element_size is 1, 2, or 4.
+
+    Raises
+    ------
+    OverflowError
+        If int value is outside [0, 256).
+    TypeError
+        If value is not an int and does not support the buffer protocol.
+    ValueError
+        If value byte length is not 1, 2, or 4.
+    """
 def check_multiprocessing_start_method() -> None:
-    """Check if multiprocessing start method is 'fork' and warn if so."""
\ No newline at end of file
+    """Check if multiprocessing start method is 'fork' and warn if so."""
diff --git a/cuda_core/cuda/core/_utils/cuda_utils.pyx b/cuda_core/cuda/core/_utils/cuda_utils.pyx
index 318d4466bee..ce75746de56 100644
--- a/cuda_core/cuda/core/_utils/cuda_utils.pyx
+++ b/cuda_core/cuda/core/_utils/cuda_utils.pyx
@@ -7,10 +7,9 @@ from functools import partial
 import multiprocessing
 import platform
 import warnings
-from collections import namedtuple
 from collections.abc import Sequence
 from contextlib import ExitStack
-from typing import Any, Callable
+from typing import Any, Callable, NamedTuple
 
 from cuda.bindings import driver as driver, nvrtc as nvrtc, runtime as runtime
 
@@ -42,7 +41,10 @@ class NVRTCError(CUDAError):
 
 
 
-ComputeCapability = namedtuple("ComputeCapability", ("major", "minor"))
+class ComputeCapability(NamedTuple):
+    """A named tuple of (major, minor) CUDA compute capability version numbers."""
+    major: int
+    minor: int
 
 
 def cast_to_3_tuple(label: str, cfg: int | tuple[int, ...]) -> tuple[int, int, int]:
@@ -63,12 +65,6 @@ def cast_to_3_tuple(label: str, cfg: int | tuple[int, ...]) -> tuple[int, int, i
     return cfg + (1,) * (3 - len(cfg))
 
 
-cdef int HANDLE_RETURN(cydriver.CUresult err) except?-1 nogil:
-    if err != cydriver.CUresult.CUDA_SUCCESS:
-        return _check_driver_error(err)
-    return 0
-
-
 cdef int _get_current_device_id() except? -1:
     """Return the current thread's bound CUdevice ordinal."""
     cdef cydriver.CUdevice dev
@@ -77,14 +73,6 @@ cdef int _get_current_device_id() except? -1:
     return <int>dev
 
 
-cdef int HANDLE_RETURN_NVRTC(cynvrtc.nvrtcProgram prog, cynvrtc.nvrtcResult err) except?-1 nogil:
-    """Handle NVRTC result codes, raising NVRTCError with program log on failure."""
-    if err == cynvrtc.nvrtcResult.NVRTC_SUCCESS:
-        return 0
-    with gil:
-        _raise_nvrtc_error(prog, err)
-
-
 cdef int _raise_nvrtc_error(cynvrtc.nvrtcProgram prog, cynvrtc.nvrtcResult err) except -1:
     """Build error message with program log and raise NVRTCError."""
     cdef const char* err_str = cynvrtc.nvrtcGetErrorString(err)
@@ -103,14 +91,6 @@ cdef int _raise_nvrtc_error(cynvrtc.nvrtcProgram prog, cynvrtc.nvrtcResult err)
     raise NVRTCError(err_msg)
 
 
-cdef int HANDLE_RETURN_NVVM(cynvvm.nvvmProgram prog, cynvvm.nvvmResult err) except?-1 nogil:
-    """Handle NVVM result codes, raising nvvmError with program log on failure."""
-    if err == cynvvm.nvvmResult.NVVM_SUCCESS:
-        return 0
-    with gil:
-        _raise_nvvm_error(prog, err)
-
-
 cdef int _raise_nvvm_error(cynvvm.nvvmProgram prog, cynvvm.nvvmResult err) except -1:
     """Raise nvvmError annotated with the program log."""
     cdef size_t logsize = 0
@@ -128,15 +108,6 @@ cdef int _raise_nvvm_error(cynvvm.nvvmProgram prog, cynvvm.nvvmResult err) excep
     raise exc
 
 
-cdef int HANDLE_RETURN_NVJITLINK(
-        cynvjitlink.nvJitLinkHandle handle, cynvjitlink.nvJitLinkResult err) except?-1 nogil:
-    """Handle nvJitLink result codes, raising nvJitLinkError with error log on failure."""
-    if err == cynvjitlink.nvJitLinkResult.NVJITLINK_SUCCESS:
-        return 0
-    with gil:
-        _raise_nvjitlink_error(handle, err)
-
-
 cdef int _raise_nvjitlink_error(
         cynvjitlink.nvJitLinkHandle handle, cynvjitlink.nvJitLinkResult err) except -1:
     """Raise nvJitLinkError annotated with the error log."""
diff --git a/cuda_core/cuda/core/_utils/driver_cu_result_explanations_frozen.py b/cuda_core/cuda/core/_utils/driver_cu_result_explanations_frozen.py
index 567b9690380..41eb158f4e2 100644
--- a/cuda_core/cuda/core/_utils/driver_cu_result_explanations_frozen.py
+++ b/cuda_core/cuda/core/_utils/driver_cu_result_explanations_frozen.py
@@ -1,6 +1,13 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
+# Like the runtime counterpart, this fallback is a deliberately frozen
+# compatibility snapshot, not a release-maintained mirror of CUDA's enums.
+# Do not update it past CUDA Toolkit v13.1.1. Bindings releases new enough to
+# define later codes provide explanations through enum-member docstrings; if an
+# older binding receives one from a newer driver, it falls through to
+# cuGetErrorString(). Synchronizing this table with later Toolkit releases would
+# restore the duplicate maintenance burden removed by PR #1860.
 # CUDA Toolkit v13.1.1
 _FALLBACK_EXPLANATIONS = {
     0: (
diff --git a/cuda_core/cuda/core/_utils/enum_explanations_helpers.py b/cuda_core/cuda/core/_utils/enum_explanations_helpers.py
index 0dbe6d6bb60..6b666f4536c 100644
--- a/cuda_core/cuda/core/_utils/enum_explanations_helpers.py
+++ b/cuda_core/cuda/core/_utils/enum_explanations_helpers.py
@@ -31,6 +31,18 @@
 _ExplanationTableLoader = Callable[[], _ExplanationTable]
 
 
+def _parse_version_triple(version_str: str) -> tuple[int, int, int]:
+    """Parse a PEP 440 version string into a (major, minor, patch) triple.
+
+    Strips local-version identifiers and handles pre-release suffixes such as
+    ``0b1`` or ``0rc1`` by extracting only the leading integer from each
+    release segment.
+    """
+    parts = version_str.partition("+")[0].split(".")[:3]
+    ints = ([int(m.group(1)) if (m := re.match(r"(\d+)", v)) else 0 for v in parts] + [0, 0, 0])[:3]
+    return (ints[0], ints[1], ints[2])
+
+
 # ``version.pyx`` cannot be reused here (circular import via ``cuda_utils``).
 def _binding_version() -> tuple[int, int, int]:
     """Return the installed ``cuda-bindings`` version, or a conservative old value."""
@@ -38,10 +50,7 @@ def _binding_version() -> tuple[int, int, int]:
         version = importlib.metadata.version("cuda-bindings")
     except importlib.metadata.PackageNotFoundError:
         return (0, 0, 0)  # For very old versions of cuda-python
-
-    parts = version.partition("+")[0].split(".")[:3]
-    parts_int = ([int(v) for v in parts] + [0, 0, 0])[:3]
-    return (parts_int[0], parts_int[1], parts_int[2])
+    return _parse_version_triple(version)
 
 
 def _binding_version_has_usable_enum_docstrings(version: tuple[int, int, int]) -> bool:
diff --git a/cuda_core/cuda/core/_utils/version.pyi b/cuda_core/cuda/core/_utils/version.pyi
index bb7f0129917..db2e27a57d0 100644
--- a/cuda_core/cuda/core/_utils/version.pyi
+++ b/cuda_core/cuda/core/_utils/version.pyi
@@ -1,14 +1,18 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/_utils/version.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/_utils/version.pyx
 
 import functools
 
 
+def _parse_version_triple(version_str: str) -> tuple[int, int, int]:
+    """Parse a PEP 440 version string into a (major, minor, patch) triple.
+
+    Strips local-version identifiers and handles pre-release suffixes such as
+    ``0b1`` or ``0rc1`` by extracting only the leading integer from each
+    release segment.
+    """
 @functools.cache
 def binding_version() -> tuple[int, int, int]:
     """Return the cuda-bindings version as a (major, minor, patch) triple."""
-
 @functools.cache
 def driver_version() -> tuple[int, int, int]:
-    """Return the CUDA driver version as a (major, minor, patch) triple."""
\ No newline at end of file
+    """Return the CUDA driver version as a (major, minor, patch) triple."""
diff --git a/cuda_core/cuda/core/_utils/version.pyx b/cuda_core/cuda/core/_utils/version.pyx
index 09ea5852421..ed4c93c0262 100644
--- a/cuda_core/cuda/core/_utils/version.pyx
+++ b/cuda_core/cuda/core/_utils/version.pyx
@@ -4,18 +4,31 @@
 
 import functools
 import importlib.metadata
+import re
 
 from cuda.core._utils.cuda_utils import driver, handle_return
 
 
+def _parse_version_triple(version_str: str) -> tuple[int, int, int]:
+    """Parse a PEP 440 version string into a (major, minor, patch) triple.
+
+    Strips local-version identifiers and handles pre-release suffixes such as
+    ``0b1`` or ``0rc1`` by extracting only the leading integer from each
+    release segment.
+    """
+    parts = version_str.partition("+")[0].split(".")[:3]
+    ints = ([int(m.group(1)) if (m := re.match(r"(\d+)", v)) else 0 for v in parts] + [0, 0, 0])[:3]
+    return (ints[0], ints[1], ints[2])
+
+
 @functools.cache
 def binding_version() -> tuple[int, int, int]:
     """Return the cuda-bindings version as a (major, minor, patch) triple."""
     try:
-        parts = importlib.metadata.version("cuda-bindings").split(".")[:3]
+        version_str = importlib.metadata.version("cuda-bindings")
     except importlib.metadata.PackageNotFoundError:
-        parts = importlib.metadata.version("cuda-python").split(".")[:3]
-    return tuple(int(v) for v in parts)
+        version_str = importlib.metadata.version("cuda-python")
+    return _parse_version_triple(version_str)
 
 
 @functools.cache
diff --git a/cuda_core/cuda/core/graph/__init__.pxd b/cuda_core/cuda/core/graph/__init__.pxd
index f367745acc1..a018340d20d 100644
--- a/cuda_core/cuda/core/graph/__init__.pxd
+++ b/cuda_core/cuda/core/graph/__init__.pxd
@@ -11,6 +11,14 @@ from cuda.core.graph._subclasses cimport (
     EmptyNode,
     EventRecordNode,
     EventWaitNode,
+    ExecutableChildGraphNode,
+    ExecutableEventRecordNode,
+    ExecutableEventWaitNode,
+    ExecutableGraphNode,
+    ExecutableHostCallbackNode,
+    ExecutableKernelNode,
+    ExecutableMemcpyNode,
+    ExecutableMemsetNode,
     FreeNode,
     HostCallbackNode,
     IfElseNode,
diff --git a/cuda_core/cuda/core/graph/__init__.py b/cuda_core/cuda/core/graph/__init__.py
index e1091114368..507888321ea 100644
--- a/cuda_core/cuda/core/graph/__init__.py
+++ b/cuda_core/cuda/core/graph/__init__.py
@@ -2,7 +2,19 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
+from . import _graph_builder, _graph_definition, _graph_node, _subclasses
 from ._graph_builder import *
 from ._graph_definition import *
 from ._graph_node import *
 from ._subclasses import *
+
+# Aggregate the star-imported submodule exports so ``cuda.core.graph`` carries
+# an explicit ``__all__`` derived from its parts (no manual list to drift).
+__all__ = [
+    *_graph_builder.__all__,
+    *_graph_definition.__all__,
+    *_graph_node.__all__,
+    *_subclasses.__all__,
+]
+
+del _graph_builder, _graph_definition, _graph_node, _subclasses
diff --git a/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyi b/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyi
index 742b3777b04..850e231a3b0 100644
--- a/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyi
+++ b/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyi
@@ -1,58 +1,39 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/graph/_adjacency_set_proxy.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/graph/_adjacency_set_proxy.pyx
 
 """Mutable-set proxy for graph node predecessors and successors."""
-from __future__ import annotations
-
-from collections.abc import Iterator, Set
-from typing import Any
+from collections.abc import Iterable, Iterator, MutableSet, Set
+from typing import Any, Callable, TypeVar
 
+from cuda.bindings import cydriver
 from cuda.core.graph._graph_node import GraphNode
+from typing_extensions import TypeAlias
 
+_S = TypeVar('_S')
+_adj_fn_t: TypeAlias = Callable[[cydriver.CUgraphNode, cydriver.CUgraphNode, int], cydriver.CUresult]
 
-class AdjacencySetProxy:
+class AdjacencySetProxy(MutableSet[GraphNode]):
     """Mutable set proxy for a node's predecessors or successors.  Mutations
     write through to the underlying CUDA graph."""
     __slots__ = ('_core',)
 
-    def __init__(self, node: GraphNode, is_fwd: bool) -> None:
-        ...
-
+    def __init__(self, node: GraphNode, is_fwd: bool) -> None: ...
     @classmethod
-    def _from_iterable(cls, it) -> set[GraphNode]:
-        ...
-
-    def __contains__(self, x: object) -> bool:
-        ...
-
-    def __iter__(self) -> Iterator[GraphNode]:
-        ...
-
-    def __len__(self) -> int:
-        ...
-
-    def add(self, value: GraphNode) -> None:
-        ...
-
-    def discard(self, value: GraphNode) -> None:
-        ...
-
+    def _from_iterable(cls, it: Iterable[_S]) -> set[_S]: ...
+    def __contains__(self, x: object) -> bool: ...
+    def __iter__(self) -> Iterator[GraphNode]: ...
+    def __len__(self) -> int: ...
+    def add(self, value: GraphNode) -> None: ...
+    def discard(self, value: GraphNode) -> None: ...
     def clear(self) -> None:
         """Remove all edges in a single driver call."""
-
-    def __isub__(self, it: Set[Any]) -> 'AdjacencySetProxy':
+    def __isub__(self, it: Set[Any]) -> AdjacencySetProxy:
         """Remove edges to all nodes in *it* in a single driver call."""
-
     def update(self, *others) -> None:
         """Add edges to multiple nodes at once."""
-
-    def __ior__(self, it: Set[Any]) -> 'AdjacencySetProxy':
+    def __ior__(self, it: Set[Any]) -> AdjacencySetProxy: # type: ignore[misc]
         """Add edges to all nodes in *it* in a single driver call."""
-
-    def __repr__(self) -> str:
-        ...
+    def __repr__(self) -> str: ...
 
 class _AdjacencySetCore:
     """Cythonized core implementing AdjacencySetProxy"""
-
-    def __init__(self, node: GraphNode, is_fwd: bool):
-        ...
\ No newline at end of file
+    def __init__(self, node: GraphNode, is_fwd: bool): ...
diff --git a/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyx b/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyx
index e1762321ce0..8919067d0b0 100644
--- a/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyx
+++ b/cuda_core/cuda/core/graph/_adjacency_set_proxy.pyx
@@ -7,7 +7,7 @@
 from libc.stddef cimport size_t
 from libcpp.vector cimport vector
 from cuda.bindings cimport cydriver
-from cuda.core.graph._graph_node cimport GraphNode
+from cuda.core.graph._graph_node cimport GraphNode, GN_check_valid
 from cuda.core._resource_handles cimport (
     GraphHandle,
     GraphNodeHandle,
@@ -15,8 +15,10 @@ from cuda.core._resource_handles cimport (
     graph_node_get_graph,
 )
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
-from collections.abc import Iterator, MutableSet, Set
-from typing import Any
+from collections.abc import Iterable, Iterator, MutableSet, Set
+from typing import Any, TypeVar
+
+_S = TypeVar("_S")
 
 
 # ---- Python MutableSet wrapper ----------------------------------------------
@@ -32,7 +34,7 @@ class AdjacencySetProxy(MutableSet[GraphNode]):
 
     # Used by operators such as &|^ to create non-proxy views when needed.
     @classmethod
-    def _from_iterable(cls, it) -> set[GraphNode]:
+    def _from_iterable(cls, it: Iterable[_S]) -> set[_S]:
         return set(it)
 
     # --- abstract methods required by MutableSet ---
@@ -52,27 +54,30 @@ class AdjacencySetProxy(MutableSet[GraphNode]):
         if not isinstance(value, GraphNode):
             raise TypeError(
                 f"expected GraphNode, got {type(value).__name__}")
+        (<_AdjacencySetCore>self._core).check_mutation(value)
         if value in self:
             return
         (<_AdjacencySetCore>self._core).add_edge(<GraphNode>value)
 
     def discard(self, value: GraphNode) -> None:
-        if not isinstance(value, GraphNode):
-            return
+        (<_AdjacencySetCore>self._core).check_owner_mutable()
         if value not in self:
             return
+        (<_AdjacencySetCore>self._core).check_mutation(value)
         (<_AdjacencySetCore>self._core).remove_edge(<GraphNode>value)
 
     # --- override for bulk efficiency ---
 
     def clear(self) -> None:
         """Remove all edges in a single driver call."""
+        (<_AdjacencySetCore>self._core).check_owner_mutable()
         members = (<_AdjacencySetCore>self._core).query()
         if members:
             (<_AdjacencySetCore>self._core).remove_edges(members)
 
     def __isub__(self, it: Set[Any]) -> "AdjacencySetProxy":
         """Remove edges to all nodes in *it* in a single driver call."""
+        (<_AdjacencySetCore>self._core).check_owner_mutable()
         if it is self:
             self.clear()
         else:
@@ -83,6 +88,7 @@ class AdjacencySetProxy(MutableSet[GraphNode]):
 
     def update(self, *others) -> None:
         """Add edges to multiple nodes at once."""
+        (<_AdjacencySetCore>self._core).check_owner_mutable()
         nodes = []
         for other in others:
             if isinstance(other, GraphNode):
@@ -93,13 +99,15 @@ class AdjacencySetProxy(MutableSet[GraphNode]):
                         raise TypeError(
                             f"expected GraphNode, got {type(n).__name__}")
                     nodes.append(n)
+        for n in nodes:
+            (<_AdjacencySetCore>self._core).check_mutation(n)
         if not nodes:
             return
         new = [n for n in nodes if n not in self]
         if new:
             (<_AdjacencySetCore>self._core).add_edges(new)
 
-    def __ior__(self, it: Set[Any]) -> "AdjacencySetProxy":
+    def __ior__(self, it: Set[Any]) -> "AdjacencySetProxy":  # type: ignore[misc]
         """Add edges to all nodes in *it* in a single driver call."""
         self.update(it)
         return self
@@ -140,24 +148,41 @@ cdef class _AdjacencySetCore:
             c_from[0] = as_cu(other._h_node)
             c_to[0] = as_cu(self._h_node)
 
+    cdef inline void check_owner_mutable(self) except *:
+        if as_cu(self._h_graph) == NULL:
+            raise RuntimeError("GraphDefinition is no longer valid")
+        if as_cu(self._h_node) == NULL:
+            raise RuntimeError("GraphNode has been destroyed")
+
+    cdef inline void check_mutation(self, GraphNode other) except *:
+        self.check_owner_mutable()
+        GN_check_valid(other)
+        if other._is_entry:
+            raise ValueError("The virtual graph entry node cannot be used in an edge")
+        if as_cu(graph_node_get_graph(other._h_node)) != as_cu(self._h_graph):
+            raise ValueError("Graph nodes must belong to the same GraphDefinition")
+
     cdef list query(self):
         cdef cydriver.CUgraphNode c_node = as_cu(self._h_node)
         if c_node == NULL:
             return []
-        cdef cydriver.CUgraphNode buf[16]
-        cdef size_t count = 16
+        cdef cydriver.CUgraphNode stack_buf[16]
+        cdef cydriver.CUgraphNode* nodes
+        cdef size_t count = 0
         cdef size_t i
         with nogil:
-            HANDLE_RETURN(self._query_fn(c_node, buf, &count))
-        if count <= 16:
-            return [GraphNode._create(self._h_graph, buf[i])
-                    for i in range(count)]
+            HANDLE_RETURN(self._query_fn(c_node, NULL, &count))
+        if count == 0:
+            return []
         cdef vector[cydriver.CUgraphNode] nodes_vec
-        nodes_vec.resize(count)
+        if count <= 16:
+            nodes = stack_buf
+        else:
+            nodes_vec.resize(count)
+            nodes = nodes_vec.data()
         with nogil:
-            HANDLE_RETURN(self._query_fn(
-                c_node, nodes_vec.data(), &count))
-        return [GraphNode._create(self._h_graph, nodes_vec[i])
+            HANDLE_RETURN(self._query_fn(c_node, nodes, &count))
+        return [GraphNode._create(self._h_graph, nodes[i])
                 for i in range(count)]
 
     cdef bint contains(self, GraphNode other):
@@ -165,27 +190,24 @@ cdef class _AdjacencySetCore:
         cdef cydriver.CUgraphNode target = as_cu(other._h_node)
         if c_node == NULL or target == NULL:
             return False
-        cdef cydriver.CUgraphNode buf[16]
-        cdef size_t count = 16
+        cdef cydriver.CUgraphNode stack_buf[16]
+        cdef cydriver.CUgraphNode* nodes
+        cdef size_t count = 0
         cdef size_t i
         with nogil:
-            HANDLE_RETURN(self._query_fn(c_node, buf, &count))
-
-        # Fast path for small sets.
-        if count <= 16:
-            for i in range(count):
-                if buf[i] == target:
-                    return True
+            HANDLE_RETURN(self._query_fn(c_node, NULL, &count))
+        if count == 0:
             return False
-
-        # Fallback for large sets.
         cdef vector[cydriver.CUgraphNode] nodes_vec
-        nodes_vec.resize(count)
+        if count <= 16:
+            nodes = stack_buf
+        else:
+            nodes_vec.resize(count)
+            nodes = nodes_vec.data()
         with nogil:
-            HANDLE_RETURN(self._query_fn(c_node, nodes_vec.data(), &count))
-        assert count == nodes_vec.size()
+            HANDLE_RETURN(self._query_fn(c_node, nodes, &count))
         for i in range(count):
-            if nodes_vec[i] == target:
+            if nodes[i] == target:
                 return True
         return False
 
diff --git a/cuda_core/cuda/core/graph/_graph_builder.pxd b/cuda_core/cuda/core/graph/_graph_builder.pxd
index 660ebe8ec7d..eb75e6bd44a 100644
--- a/cuda_core/cuda/core/graph/_graph_builder.pxd
+++ b/cuda_core/cuda/core/graph/_graph_builder.pxd
@@ -24,4 +24,4 @@ cdef class Graph:
         object __weakref__
 
     @staticmethod
-    cdef Graph _init(cydriver.CUgraphExec graph_exec)
+    cdef Graph _init(GraphExecHandle h_graph_exec)
diff --git a/cuda_core/cuda/core/graph/_graph_builder.pyi b/cuda_core/cuda/core/graph/_graph_builder.pyi
index 4fbc6fb3903..732bc291036 100644
--- a/cuda_core/cuda/core/graph/_graph_builder.pyi
+++ b/cuda_core/cuda/core/graph/_graph_builder.pyi
@@ -1,15 +1,17 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/graph/_graph_builder.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/graph/_graph_builder.pyx
 
 from dataclasses import dataclass
 
 from cuda.core._stream import Stream
 from cuda.core._utils.cuda_utils import driver
 from cuda.core.graph._graph_definition import GraphCondition, GraphDefinition
+from cuda.core.graph._graph_node import GraphNode
+from cuda.core.graph._subclasses import ExecutableGraphNode
+from typing_extensions import TypeAlias
 
-_BuilderKind = int
-_CaptureState = int
+_BuilderKind: TypeAlias = int
+_CaptureState: TypeAlias = int
+__all__ = ['Graph', 'GraphBuilder', 'GraphCompleteOptions', 'GraphDebugPrintOptions']
 
 @dataclass
 class GraphDebugPrintOptions:
@@ -119,28 +121,21 @@ class GraphBuilder:
         retains the operands it is given.
 
     """
-
-    def __init__(self):
-        ...
-
-    def __dealloc__(self):
-        ...
-
+    def __init__(self): ...
+    def __dealloc__(self): ...
     @staticmethod
-    def _init(stream: Stream):
-        ...
-
+    def _init(stream: Stream): ...
     def close(self):
         """Destroy the graph builder."""
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this graph builder has been closed."""
     @property
     def stream(self) -> Stream:
         """Returns the stream associated with the graph builder."""
-
     @property
     def is_join_required(self) -> bool:
         """Returns True if this graph builder must be joined before building is ended."""
-
     @property
     def graph_definition(self) -> GraphDefinition:
         """The captured graph as an explicit :class:`~graph.GraphDefinition`.
@@ -187,7 +182,6 @@ class GraphBuilder:
             keeps working; only fresh access through this property is
             rejected once the builder is closed.
         """
-
     def begin_building(self, mode: str | None='relaxed') -> GraphBuilder:
         """Begins the building process.
 
@@ -204,14 +198,11 @@ class GraphBuilder:
             Default set to use relaxed.
 
         """
-
     @property
     def is_building(self) -> bool:
         """Returns True if the graph builder is currently building."""
-
     def end_building(self) -> GraphBuilder:
         """Ends the building process."""
-
     def complete(self, options: GraphCompleteOptions | None=None) -> Graph:
         """Completes the graph builder and returns the built :obj:`~graph.Graph` object.
 
@@ -226,7 +217,6 @@ class GraphBuilder:
             The newly built graph.
 
         """
-
     def debug_dot_print(self, path: str, options: GraphDebugPrintOptions | None=None) -> None:
         """Generates a DOT debug file for the graph builder.
 
@@ -238,7 +228,6 @@ class GraphBuilder:
             Customizable dataclass for the debug print options.
 
         """
-
     def split(self, count: int) -> tuple[GraphBuilder, ...]:
         """Splits the original graph builder into multiple graph builders.
 
@@ -257,7 +246,6 @@ class GraphBuilder:
             is always the original graph builder.
 
         """
-
     @staticmethod
     def join(*graph_builders: GraphBuilder) -> GraphBuilder:
         """Joins multiple graph builders into a single graph builder.
@@ -275,13 +263,9 @@ class GraphBuilder:
             The newly joined graph builder.
 
         """
-
     def __cuda_stream__(self) -> tuple[int, int]:
         """Return an instance of a __cuda_stream__ protocol."""
-
-    def _get_conditional_context(self) -> driver.CUcontext:
-        ...
-
+    def _get_conditional_context(self) -> driver.CUcontext: ...
     def create_condition(self, default_value: int | None=None) -> GraphCondition:
         """Create a condition variable for use with conditional nodes.
 
@@ -301,7 +285,6 @@ class GraphBuilder:
         GraphCondition
             A condition variable for controlling conditional execution.
         """
-
     def if_then(self, condition: GraphCondition) -> GraphBuilder:
         """Adds an if condition branch and returns a new graph builder for it.
 
@@ -322,7 +305,6 @@ class GraphBuilder:
             The newly created conditional graph builder.
 
         """
-
     def if_else(self, condition: GraphCondition) -> tuple[GraphBuilder, GraphBuilder]:
         """Adds an if-else condition branch and returns new graph builders for both branches.
 
@@ -343,7 +325,6 @@ class GraphBuilder:
             A tuple of two new graph builders, one for the if branch and one for the else branch.
 
         """
-
     def switch(self, condition: GraphCondition, count: int) -> tuple[GraphBuilder, ...]:
         """Adds a switch condition branch and returns new graph builders for all cases.
 
@@ -367,7 +348,6 @@ class GraphBuilder:
             A tuple of new graph builders, one for each branch.
 
         """
-
     def while_loop(self, condition: GraphCondition) -> GraphBuilder:
         """Adds a while loop and returns a new graph builder for it.
 
@@ -388,7 +368,6 @@ class GraphBuilder:
             The newly created while loop graph builder.
 
         """
-
     def embed(self, child: GraphBuilder):
         """Embed a previously-built :obj:`~graph.GraphBuilder` as a child node.
 
@@ -397,7 +376,6 @@ class GraphBuilder:
         child : :obj:`~graph.GraphBuilder`
             The child graph builder. Must have finished building.
         """
-
     def callback(self, fn, *, user_data=None) -> None:
         """Add a host callback to the graph during stream capture.
 
@@ -407,10 +385,12 @@ class GraphBuilder:
         - **Python callable**: Pass any callable. The GIL is acquired
           automatically. The callable must take no arguments; use closures
           or ``functools.partial`` to bind state.
-        - **ctypes function pointer**: Pass a ``ctypes.CFUNCTYPE`` instance.
-          The function receives a single ``void*`` argument (the
-          ``user_data``). The caller must keep the ctypes wrapper alive
-          for the lifetime of the graph.
+        - **ctypes function pointer**: The function receives a single
+          ``void*`` argument (the ``user_data``), and the caller must keep
+          the ctypes wrapper alive for the lifetime of the graph. Its
+          declared prototype must match the driver's ``CUhostFn``
+          (``void (*)(void*)``): ``ctypes.CFUNCTYPE(None, ctypes.c_void_p)``,
+          or ``ctypes.WINFUNCTYPE(None, ctypes.c_void_p)`` on Windows.
 
         .. warning::
 
@@ -430,6 +410,14 @@ class GraphBuilder:
             Only for ctypes function pointers. If ``int``, passed as a raw
             pointer (caller manages lifetime). If bytes-like, the data is
             copied and its lifetime is tied to the graph.
+
+        Raises
+        ------
+        TypeError
+            If ``fn`` is a ctypes function pointer whose declared prototype
+            does not match ``CUhostFn``.
+        ValueError
+            If ``user_data`` is given for a Python callable.
         """
 
 class Graph:
@@ -442,13 +430,12 @@ class Graph:
     Graphs must be built using a :obj:`~graph.GraphBuilder` object.
 
     """
-
-    def __init__(self):
-        ...
-
+    def __init__(self): ...
     def close(self) -> None:
         """Destroy the graph."""
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this executable graph has been closed."""
     @property
     def handle(self) -> driver.CUgraphExec:
         """Return the underlying ``CUgraphExec`` object.
@@ -459,8 +446,15 @@ class Graph:
             handle, call ``int()`` on the returned object.
 
         """
+    def __getitem__(self, node: GraphNode) -> ExecutableGraphNode:
+        """Return a view for updating *node* in this executable graph.
 
-    def update(self, source: 'GraphBuilder | GraphDefinition') -> None:
+        *node* is a definition node from the graph used to instantiate this
+        executable. Call ``update()`` on the returned view to replace that
+        node's parameters for future launches. Kernel, memcpy, and memset
+        views also support enabling and disabling the node.
+        """
+    def update(self, source: GraphBuilder | GraphDefinition) -> None:
         """Update the graph using a new graph definition.
 
         The topology of the provided source must be identical to this graph.
@@ -472,7 +466,6 @@ class Graph:
             finished building.
 
         """
-
     def upload(self, stream: Stream) -> None:
         """Uploads the graph in a stream.
 
@@ -482,7 +475,6 @@ class Graph:
             The stream in which to upload the graph
 
         """
-
     def launch(self, stream: Stream) -> None:
         """Launches the graph in a stream.
 
@@ -492,10 +484,7 @@ class Graph:
             The stream in which to launch the graph.
 
         """
-__all__ = ['Graph', 'GraphBuilder', 'GraphCompleteOptions', 'GraphDebugPrintOptions']
-
-def _instantiate_graph(h_graph, options: GraphCompleteOptions | None=None) -> Graph:
-    ...
 
+def _instantiate_graph(source, options: GraphCompleteOptions | None=None) -> Graph: ...
 def _capture_callback_with_tail_failure_for_testing(gb: GraphBuilder, fn, *, user_data=None):
-    """Exercise anonymous attachment retention after node discovery fails."""
\ No newline at end of file
+    """Exercise anonymous attachment retention after node discovery fails."""
diff --git a/cuda_core/cuda/core/graph/_graph_builder.pyx b/cuda_core/cuda/core/graph/_graph_builder.pyx
index 3f5b57060b6..071fff38386 100644
--- a/cuda_core/cuda/core/graph/_graph_builder.pyx
+++ b/cuda_core/cuda/core/graph/_graph_builder.pyx
@@ -9,21 +9,33 @@ from libc.stdint cimport intptr_t
 
 from cuda.bindings cimport cydriver
 
-from cuda.core.graph._graph_definition cimport GraphCondition, GraphDefinition
+from cuda.core.graph._graph_definition cimport (
+    GraphCondition,
+    GraphDefinition,
+    GD_check_valid,
+)
+from cuda.core.graph._graph_node cimport GraphNode, GN_check_valid
 from cuda.core.graph._host_callback cimport _resolve_host_callback
+from cuda.core.graph._subclasses cimport (
+    ExecutableGraphNode,
+    create_executable_node_view,
+)
 from cuda.core._resource_handles cimport (
+    GraphExecHandle,
     GraphHandle,
     OpaqueHandle,
     PreparedAttachment,
     as_cu, as_py,
     create_child_graph_handle, create_graph_exec_handle, create_graph_handle,
+    get_last_error,
     graph_clone_attachments,
     graph_commit_attachment,
+    graph_exec_update,
     graph_prepare_attachment,
     invalidate_child_graph_state,
     retry_deferred_cleanup,
 )
-from cuda.core._stream cimport Stream
+from cuda.core._stream cimport Stream, Stream_accept
 from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 from cuda.core._utils.version cimport cy_binding_version, cy_driver_version
 
@@ -161,29 +173,51 @@ class GraphCompleteOptions:
     use_node_priority: bool = False
 
 
-def _instantiate_graph(h_graph, options: GraphCompleteOptions | None = None) -> Graph:
-    cdef cydriver.CUgraphExec c_exec
-    params = driver.CUDA_GRAPH_INSTANTIATE_PARAMS()
+def _instantiate_graph(source, options: GraphCompleteOptions | None = None) -> Graph:
+    cdef GraphHandle h_graph
+    cdef GraphExecHandle h_exec
+    cdef cydriver.CUresult status
+
+    if isinstance(source, GraphBuilder):
+        GB_check_open(<GraphBuilder>source)
+        h_graph = (<GraphBuilder>source)._h_graph
+    elif isinstance(source, GraphDefinition):
+        GD_check_valid(<GraphDefinition>source)
+        h_graph = (<GraphDefinition>source)._h_graph
+    else:
+        raise TypeError(
+            f"expected GraphBuilder or GraphDefinition, got {type(source).__name__}")
+
+    cdef cydriver.CUDA_GRAPH_INSTANTIATE_PARAMS params = cydriver.CUDA_GRAPH_INSTANTIATE_PARAMS(
+        flags=0,
+        hUploadStream=<cydriver.CUstream>NULL,
+        hErrNode_out=<cydriver.CUgraphNode>NULL,
+        result_out=cydriver.CUgraphInstantiateResult.CUDA_GRAPH_INSTANTIATE_SUCCESS,
+    )
     if options:
         flags = 0
         if options.auto_free_on_launch:
             flags |= driver.CUgraphInstantiate_flags.CUDA_GRAPH_INSTANTIATE_FLAG_AUTO_FREE_ON_LAUNCH
-        if options.upload_stream:
+        if options.upload_stream is not None:
             flags |= driver.CUgraphInstantiate_flags.CUDA_GRAPH_INSTANTIATE_FLAG_UPLOAD
-            params.hUploadStream = options.upload_stream.handle
+            params.hUploadStream = as_cu(Stream_accept(options.upload_stream)._h_stream)
         if options.device_launch:
             flags |= driver.CUgraphInstantiate_flags.CUDA_GRAPH_INSTANTIATE_FLAG_DEVICE_LAUNCH
         if options.use_node_priority:
             flags |= driver.CUgraphInstantiate_flags.CUDA_GRAPH_INSTANTIATE_FLAG_USE_NODE_PRIORITY
         params.flags = flags
 
-    py_exec = handle_return(driver.cuGraphInstantiateWithParams(h_graph, params))
-    # Check result_out before wrapping the exec: on a non-SUCCESS result the exec
-    # may be invalid, and Graph._init's RAII deleter would call cuGraphExecDestroy
-    # on it during the exception unwind below.
+    # The exec is adopted only when result_out reports success, so the
+    # diagnostics below run before the handle is checked.
+    h_exec = create_graph_exec_handle(h_graph, &params)
+    status = get_last_error()
     if params.result_out == driver.CUgraphInstantiateResult.CUDA_GRAPH_INSTANTIATE_ERROR:
+        # HANDLE_RETURN raises CUDAError with the CUresult name and message (e.g. CUDA_ERROR_INVALID_VALUE)
+        # when status is not CUDA_SUCCESS.
+        HANDLE_RETURN(status)
         raise RuntimeError(
-            "Instantiation failed for an unexpected reason which is described in the return value of the function."
+            "CUDA graph instantiation failed, but cuGraphInstantiateWithParams "
+            "returned CUDA_SUCCESS; no driver error details are available."
         )
     elif params.result_out == driver.CUgraphInstantiateResult.CUDA_GRAPH_INSTANTIATE_INVALID_STRUCTURE:
         raise RuntimeError("Instantiation failed due to invalid structure, such as cycles.")
@@ -201,8 +235,9 @@ def _instantiate_graph(h_graph, options: GraphCompleteOptions | None = None) ->
     elif params.result_out != driver.CUgraphInstantiateResult.CUDA_GRAPH_INSTANTIATE_SUCCESS:
         raise RuntimeError(f"Graph instantiation failed with unexpected error code: {params.result_out}")
 
-    c_exec = <cydriver.CUgraphExec><intptr_t>int(py_exec)
-    return Graph._init(c_exec)
+    if as_cu(h_exec) == NULL:
+        HANDLE_RETURN(status)
+    return Graph._init(h_exec)
 
 
 # Distinguishes the three kinds of GraphBuilder, which differ in how they
@@ -292,9 +327,15 @@ cdef class GraphBuilder:
         self._state = CLOSED
         self._stream = None
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this graph builder has been closed."""
+        return self._state == CLOSED
+
     @property
     def stream(self) -> Stream:
         """Returns the stream associated with the graph builder."""
+        GB_check_open(self)
         return self._stream
 
     @property
@@ -474,7 +515,7 @@ cdef class GraphBuilder:
         if self._state != CAPTURE_ENDED:
             raise RuntimeError("Graph has not finished building.")
 
-        return _instantiate_graph(as_py(self._h_graph), options)
+        return _instantiate_graph(self, options)
 
     def debug_dot_print(self, path: str, options: GraphDebugPrintOptions | None = None) -> None:
         """Generates a DOT debug file for the graph builder.
@@ -551,6 +592,8 @@ cdef class GraphBuilder:
             raise TypeError("All arguments must be GraphBuilder instances")
         if len(graph_builders) < 2:
             raise ValueError("Must join with at least two graph builders")
+        for builder in graph_builders:
+            GB_check_open(builder)
 
         # Discover the root builder others should join
         root_idx = 0
@@ -776,6 +819,7 @@ cdef class GraphBuilder:
             The child graph builder. Must have finished building.
         """
         GB_check_open(self)
+        GB_check_open(child)
         if child._state != CAPTURE_ENDED:
             raise ValueError("Child graph has not finished building.")
 
@@ -837,10 +881,12 @@ cdef class GraphBuilder:
         - **Python callable**: Pass any callable. The GIL is acquired
           automatically. The callable must take no arguments; use closures
           or ``functools.partial`` to bind state.
-        - **ctypes function pointer**: Pass a ``ctypes.CFUNCTYPE`` instance.
-          The function receives a single ``void*`` argument (the
-          ``user_data``). The caller must keep the ctypes wrapper alive
-          for the lifetime of the graph.
+        - **ctypes function pointer**: The function receives a single
+          ``void*`` argument (the ``user_data``), and the caller must keep
+          the ctypes wrapper alive for the lifetime of the graph. Its
+          declared prototype must match the driver's ``CUhostFn``
+          (``void (*)(void*)``): ``ctypes.CFUNCTYPE(None, ctypes.c_void_p)``,
+          or ``ctypes.WINFUNCTYPE(None, ctypes.c_void_p)`` on Windows.
 
         .. warning::
 
@@ -860,6 +906,14 @@ cdef class GraphBuilder:
             Only for ctypes function pointers. If ``int``, passed as a raw
             pointer (caller manages lifetime). If bytes-like, the data is
             copied and its lifetime is tied to the graph.
+
+        Raises
+        ------
+        TypeError
+            If ``fn`` is a ctypes function pointer whose declared prototype
+            does not match ``CUhostFn``.
+        ValueError
+            If ``user_data`` is given for a Python callable.
         """
         GB_callback(self, fn, user_data, False)
 
@@ -898,11 +952,14 @@ cdef inline void GB_callback(
         if fail_tail_discovery_for_testing:
             raise RuntimeError("forced capture tail discovery failure")
         host_node = _capture_tail_node(c_stream)
-    except:
+    except BaseException as orig_exc:
         # CUDA added the callback, but its node cannot be identified.
         # Retain its owners anonymously to prevent dangling pointers.
         commit_status = graph_commit_attachment(prepared, NULL)
-        HANDLE_RETURN(commit_status)
+        try:
+            HANDLE_RETURN(commit_status)
+        except Exception as commit_exc:
+            raise commit_exc from orig_exc
         raise
     HANDLE_RETURN(graph_commit_attachment(prepared, host_node))
 
@@ -922,7 +979,7 @@ cdef inline int GB_check_open(GraphBuilder gb) except -1:
     instead.
     """
     if gb._state == CLOSED:
-        raise RuntimeError("Graph builder has been closed.")
+        raise RuntimeError("GraphBuilder has been closed")
     return 0
 
 
@@ -1060,9 +1117,9 @@ cdef class Graph:
         raise RuntimeError("directly constructing a Graph instance is not supported")
 
     @staticmethod
-    cdef Graph _init(cydriver.CUgraphExec graph_exec):
+    cdef Graph _init(GraphExecHandle h_graph_exec):
         cdef Graph self = Graph.__new__(Graph)
-        self._h_graph_exec = create_graph_exec_handle(graph_exec)
+        self._h_graph_exec = h_graph_exec
         return self
 
     def close(self) -> None:
@@ -1070,6 +1127,11 @@ cdef class Graph:
         self._h_graph_exec.reset()
         retry_deferred_cleanup()
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this executable graph has been closed."""
+        return self._h_graph_exec.get() == NULL
+
     @property
     def handle(self) -> driver.CUgraphExec:
         """Return the underlying ``CUgraphExec`` object.
@@ -1082,6 +1144,19 @@ cdef class Graph:
         """
         return as_py(self._h_graph_exec)
 
+    def __getitem__(self, node: GraphNode) -> ExecutableGraphNode:
+        """Return a view for updating *node* in this executable graph.
+
+        *node* is a definition node from the graph used to instantiate this
+        executable. Call ``update()`` on the returned view to replace that
+        node's parameters for future launches. Kernel, memcpy, and memset
+        views also support enabling and disabling the node.
+        """
+        Graph_check_open(self)
+        GN_check_valid(node)
+        return create_executable_node_view(
+            self._h_graph_exec, node)
+
     def update(self, source: "GraphBuilder | GraphDefinition") -> None:
         """Update the graph using a new graph definition.
 
@@ -1094,27 +1169,24 @@ cdef class Graph:
             finished building.
 
         """
-        from cuda.core.graph import GraphDefinition
-
-        cdef cydriver.CUgraph cu_graph
-        cdef cydriver.CUgraphExec cu_exec = as_cu(self._h_graph_exec)
+        Graph_check_open(self)
+        cdef GraphHandle h_source
 
         if isinstance(source, GraphBuilder):
-            if (<GraphBuilder>source)._state == CLOSED:
-                raise ValueError("Source graph builder has been closed.")
+            GB_check_open(<GraphBuilder>source)
             if (<GraphBuilder>source)._state != CAPTURE_ENDED:
                 raise ValueError("Graph has not finished building.")
-            cu_graph = as_cu((<GraphBuilder>source)._h_graph)
+            h_source = (<GraphBuilder>source)._h_graph
         elif isinstance(source, GraphDefinition):
-            cu_graph = <cydriver.CUgraph><intptr_t>int(source.handle)
+            GD_check_valid(<GraphDefinition>source)
+            h_source = (<GraphDefinition>source)._h_graph
         else:
             raise TypeError(
                 f"expected GraphBuilder or GraphDefinition, got {type(source).__name__}")
 
         cdef cydriver.CUgraphExecUpdateResultInfo result_info
-        cdef cydriver.CUresult err
-        with nogil:
-            err = cydriver.cuGraphExecUpdate(cu_exec, cu_graph, &result_info)
+        cdef cydriver.CUresult err = graph_exec_update(
+            self._h_graph_exec, h_source, &result_info)
         if err == cydriver.CUresult.CUDA_ERROR_GRAPH_EXEC_UPDATE_FAILURE:
             reason = driver.CUgraphExecUpdateResult(result_info.result)
             msg = f"Graph update failed: {reason.__doc__.strip()} ({reason.name})"
@@ -1130,8 +1202,10 @@ cdef class Graph:
             The stream in which to upload the graph
 
         """
+        Graph_check_open(self)
+        cdef Stream s = Stream_accept(stream)
         cdef cydriver.CUgraphExec c_exec = as_cu(self._h_graph_exec)
-        cdef cydriver.CUstream c_stream = <cydriver.CUstream><intptr_t>int(stream.handle)
+        cdef cydriver.CUstream c_stream = as_cu(s._h_stream)
         with nogil:
             HANDLE_RETURN(cydriver.cuGraphUpload(c_exec, c_stream))
 
@@ -1144,7 +1218,15 @@ cdef class Graph:
             The stream in which to launch the graph.
 
         """
+        Graph_check_open(self)
+        cdef Stream s = Stream_accept(stream)
         cdef cydriver.CUgraphExec c_exec = as_cu(self._h_graph_exec)
-        cdef cydriver.CUstream c_stream = <cydriver.CUstream><intptr_t>int(stream.handle)
+        cdef cydriver.CUstream c_stream = as_cu(s._h_stream)
         with nogil:
             HANDLE_RETURN(cydriver.cuGraphLaunch(c_exec, c_stream))
+
+
+cdef inline int Graph_check_open(Graph self) except -1:
+    if not self._h_graph_exec:
+        raise RuntimeError("Graph has been closed")
+    return 0
diff --git a/cuda_core/cuda/core/graph/_graph_definition.pxd b/cuda_core/cuda/core/graph/_graph_definition.pxd
index 6c15643c2fe..634c2ba2580 100644
--- a/cuda_core/cuda/core/graph/_graph_definition.pxd
+++ b/cuda_core/cuda/core/graph/_graph_definition.pxd
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 from cuda.bindings cimport cydriver
-from cuda.core._resource_handles cimport GraphHandle
+from cuda.core._resource_handles cimport GraphHandle, as_intptr
 
 
 cdef class GraphCondition:
@@ -22,3 +22,9 @@ cdef class GraphDefinition:
 
     @staticmethod
     cdef GraphDefinition _from_handle(GraphHandle h_graph)
+
+
+cdef inline int GD_check_valid(GraphDefinition self) except -1:
+    if as_intptr(self._h_graph) == 0:
+        raise RuntimeError("GraphDefinition is no longer valid")
+    return 0
diff --git a/cuda_core/cuda/core/graph/_graph_definition.pyi b/cuda_core/cuda/core/graph/_graph_definition.pyi
index 9780b53b586..cfdd1a14d17 100644
--- a/cuda_core/cuda/core/graph/_graph_definition.pyi
+++ b/cuda_core/cuda/core/graph/_graph_definition.pyi
@@ -1,8 +1,6 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/graph/_graph_definition.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/graph/_graph_definition.pyx
 
 """GraphDefinition: explicit CUDA graph definition."""
-from __future__ import annotations
-
 from cuda.core._device import Device
 from cuda.core._event import Event
 from cuda.core._launch_config import LaunchConfig
@@ -20,6 +18,7 @@ from cuda.core.graph._subclasses import (AllocNode, ChildGraphNode, EmptyNode,
                                          WhileNode)
 from cuda.core.typing import GraphMemoryType
 
+__all__ = ['GraphCondition', 'GraphDefinition']
 
 class GraphCondition:
     """A condition variable for conditional graph nodes.
@@ -36,16 +35,9 @@ class GraphCondition:
     ``CUgraphConditionalHandle`` value so device code can update the
     condition.
     """
-
-    def __repr__(self) -> str:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
+    def __repr__(self) -> str: ...
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
     @property
     def handle(self) -> driver.CUgraphConditionalHandle:
         """The raw CUgraphConditionalHandle as an int."""
@@ -63,47 +55,37 @@ class GraphDefinition:
     share underlying graph state. Mutations anywhere in that hierarchy must be
     externally synchronized.
     """
-
     def __init__(self):
         """Create a new empty graph definition."""
-
-    def __repr__(self) -> str:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
+    def __repr__(self) -> str: ...
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
+    @property
+    def is_valid(self) -> bool:
+        """Whether this graph definition remains valid."""
     @property
     def _entry(self) -> GraphNode:
         """Return the internal entry-point GraphNode (no dependencies)."""
-
-    def allocate(self, size: int, *, device: Device | int | None=None, memory_type: GraphMemoryType=..., peer_access: list[Device | int] | None=None) -> AllocNode:
+    def allocate(self, size: int, *, device: Device | int | None=None, memory_type: GraphMemoryType=GraphMemoryType.DEVICE, peer_access: list[Device | int] | None=None) -> AllocNode:
         """Add an entry-point memory allocation node (no dependencies).
 
         See :meth:`GraphNode.allocate` for full documentation.
         """
-
     def deallocate(self, dptr: int) -> FreeNode:
         """Add an entry-point memory free node (no dependencies).
 
         See :meth:`GraphNode.deallocate` for full documentation.
         """
-
     def memset(self, dst: Buffer | int, value, width: int, height: int=1, pitch: int=0, *, dst_owner=None) -> MemsetNode:
         """Add an entry-point memset node (no dependencies).
 
         See :meth:`GraphNode.memset` for full documentation.
         """
-
     def launch(self, config: LaunchConfig, kernel: Kernel, *args) -> KernelNode:
         """Add an entry-point kernel launch node (no dependencies).
 
         See :meth:`GraphNode.launch` for full documentation.
         """
-
     def empty(self) -> EmptyNode:
         """Add an entry-point empty node (no dependencies).
 
@@ -112,7 +94,6 @@ class GraphDefinition:
         EmptyNode
             A new EmptyNode with no dependencies.
         """
-
     def join(self, *nodes: GraphNode) -> EmptyNode:
         """Create an empty node that depends on all given nodes.
 
@@ -126,37 +107,31 @@ class GraphDefinition:
         EmptyNode
             A new EmptyNode that depends on all input nodes.
         """
-
     def memcpy(self, dst: Buffer | int, src: Buffer | int, size: int, *, dst_owner=None, src_owner=None) -> MemcpyNode:
         """Add an entry-point memcpy node (no dependencies).
 
         See :meth:`GraphNode.memcpy` for full documentation.
         """
-
     def embed(self, child: GraphDefinition) -> ChildGraphNode:
         """Add an entry-point child graph node (no dependencies).
 
         See :meth:`GraphNode.embed` for full documentation.
         """
-
     def record(self, event: Event) -> EventRecordNode:
         """Add an entry-point event record node (no dependencies).
 
         See :meth:`GraphNode.record` for full documentation.
         """
-
     def wait(self, event: Event) -> EventWaitNode:
         """Add an entry-point event wait node (no dependencies).
 
         See :meth:`GraphNode.wait` for full documentation.
         """
-
     def callback(self, fn, *, user_data=None) -> HostCallbackNode:
         """Add an entry-point host callback node (no dependencies).
 
         See :meth:`GraphNode.callback` for full documentation.
         """
-
     def create_condition(self, default_value: int | None=None) -> GraphCondition:
         """Create a condition variable for use with conditional nodes.
 
@@ -175,31 +150,26 @@ class GraphDefinition:
         GraphCondition
             A condition variable for controlling conditional execution.
         """
-
     def if_then(self, condition: GraphCondition) -> IfNode:
         """Add an entry-point if-conditional node (no dependencies).
 
         See :meth:`GraphNode.if_then` for full documentation.
         """
-
     def if_else(self, condition: GraphCondition) -> IfElseNode:
         """Add an entry-point if-else conditional node (no dependencies).
 
         See :meth:`GraphNode.if_else` for full documentation.
         """
-
     def while_loop(self, condition: GraphCondition) -> WhileNode:
         """Add an entry-point while-loop conditional node (no dependencies).
 
         See :meth:`GraphNode.while_loop` for full documentation.
         """
-
     def switch(self, condition: GraphCondition, count: int) -> SwitchNode:
         """Add an entry-point switch conditional node (no dependencies).
 
         See :meth:`GraphNode.switch` for full documentation.
         """
-
     def instantiate(self, options: GraphCompleteOptions | None=None) -> Graph:
         """Instantiate the graph definition into an executable Graph.
 
@@ -213,7 +183,6 @@ class GraphDefinition:
         Graph
             An executable graph that can be launched on a stream.
         """
-
     def debug_dot_print(self, path: str, options: GraphDebugPrintOptions | None=None) -> None:
         """Write a GraphViz DOT representation of the graph to a file.
 
@@ -224,7 +193,6 @@ class GraphDefinition:
         options : GraphDebugPrintOptions, optional
             Customizable options for the debug print.
         """
-
     def nodes(self) -> set[GraphNode]:
         """Return all nodes in the graph.
 
@@ -233,7 +201,6 @@ class GraphDefinition:
         set of GraphNode
             All nodes in the graph.
         """
-
     def edges(self) -> set[tuple[GraphNode, GraphNode]]:
         """Return all edges in the graph as (from_node, to_node) pairs.
 
@@ -243,8 +210,6 @@ class GraphDefinition:
             Each element is a (from_node, to_node) pair representing
             a dependency edge in the graph.
         """
-
     @property
     def handle(self) -> driver.CUgraph:
         """Return the underlying driver CUgraph handle."""
-__all__ = ['GraphCondition', 'GraphDefinition']
\ No newline at end of file
diff --git a/cuda_core/cuda/core/graph/_graph_definition.pyx b/cuda_core/cuda/core/graph/_graph_definition.pyx
index b2516034d61..c1a3999bc08 100644
--- a/cuda_core/cuda/core/graph/_graph_definition.pyx
+++ b/cuda_core/cuda/core/graph/_graph_definition.pyx
@@ -142,11 +142,18 @@ cdef class GraphDefinition:
     def __hash__(self) -> int:
         return hash(<uintptr_t>self._h_graph.get())
 
+    @property
+    def is_valid(self) -> bool:
+        """Whether this graph definition remains valid."""
+        return as_intptr(self._h_graph) != 0
+
     @property
     def _entry(self) -> GraphNode:
         """Return the internal entry-point GraphNode (no dependencies)."""
+        GD_check_valid(self)
         cdef GraphNode n = GraphNode.__new__(GraphNode)
         n._h_node = create_graph_node_handle(<cydriver.CUgraphNode>NULL, self._h_graph)
+        n._is_entry = True
         return n
 
     def allocate(self, size_t size, *, device: Device | int | None = None,
@@ -268,6 +275,7 @@ cdef class GraphDefinition:
         GraphCondition
             A condition variable for controlling conditional execution.
         """
+        GD_check_valid(self)
         cdef cydriver.CUgraphConditionalHandle c_handle
         cdef unsigned int flags = 0
         cdef unsigned int default_val = 0
@@ -325,10 +333,10 @@ cdef class GraphDefinition:
         Graph
             An executable graph that can be launched on a stream.
         """
+        GD_check_valid(self)
         from cuda.core.graph._graph_builder import _instantiate_graph
 
-        return _instantiate_graph(
-            driver.CUgraph(as_intptr(self._h_graph)), options)
+        return _instantiate_graph(self, options)
 
     def debug_dot_print(self, path: str, options: GraphDebugPrintOptions | None = None) -> None:
         """Write a GraphViz DOT representation of the graph to a file.
@@ -340,6 +348,7 @@ cdef class GraphDefinition:
         options : GraphDebugPrintOptions, optional
             Customizable options for the debug print.
         """
+        GD_check_valid(self)
         from cuda.core.graph._graph_builder import GraphDebugPrintOptions
 
         cdef unsigned int flags = 0
@@ -361,20 +370,19 @@ cdef class GraphDefinition:
         set of GraphNode
             All nodes in the graph.
         """
+        GD_check_valid(self)
         cdef vector[cydriver.CUgraphNode] nodes_vec
-        nodes_vec.resize(128)
-        cdef size_t num_nodes = 128
+        cdef size_t num_nodes = 0
 
         with nogil:
-            HANDLE_RETURN(cydriver.cuGraphGetNodes(as_cu(self._h_graph), nodes_vec.data(), &num_nodes))
+            HANDLE_RETURN(cydriver.cuGraphGetNodes(as_cu(self._h_graph), NULL, &num_nodes))
 
         if num_nodes == 0:
             return set()
 
-        if num_nodes > 128:
-            nodes_vec.resize(num_nodes)
-            with nogil:
-                HANDLE_RETURN(cydriver.cuGraphGetNodes(as_cu(self._h_graph), nodes_vec.data(), &num_nodes))
+        nodes_vec.resize(num_nodes)
+        with nogil:
+            HANDLE_RETURN(cydriver.cuGraphGetNodes(as_cu(self._h_graph), nodes_vec.data(), &num_nodes))
 
         return {GraphNode._create(self._h_graph, nodes_vec[i]) for i in range(num_nodes)}
 
@@ -387,33 +395,31 @@ cdef class GraphDefinition:
             Each element is a (from_node, to_node) pair representing
             a dependency edge in the graph.
         """
+        GD_check_valid(self)
         cdef vector[cydriver.CUgraphNode] from_nodes
         cdef vector[cydriver.CUgraphNode] to_nodes
-        from_nodes.resize(128)
-        to_nodes.resize(128)
-        cdef size_t num_edges = 128
+        cdef size_t num_edges = 0
 
         with nogil:
             IF CUDA_CORE_BUILD_MAJOR >= 13:
                 HANDLE_RETURN(cydriver.cuGraphGetEdges(
-                    as_cu(self._h_graph), from_nodes.data(), to_nodes.data(), NULL, &num_edges))
+                    as_cu(self._h_graph), NULL, NULL, NULL, &num_edges))
             ELSE:
                 HANDLE_RETURN(cydriver.cuGraphGetEdges(
-                    as_cu(self._h_graph), from_nodes.data(), to_nodes.data(), &num_edges))
+                    as_cu(self._h_graph), NULL, NULL, &num_edges))
 
         if num_edges == 0:
             return set()
 
-        if num_edges > 128:
-            from_nodes.resize(num_edges)
-            to_nodes.resize(num_edges)
-            with nogil:
-                IF CUDA_CORE_BUILD_MAJOR >= 13:
-                    HANDLE_RETURN(cydriver.cuGraphGetEdges(
-                        as_cu(self._h_graph), from_nodes.data(), to_nodes.data(), NULL, &num_edges))
-                ELSE:
-                    HANDLE_RETURN(cydriver.cuGraphGetEdges(
-                        as_cu(self._h_graph), from_nodes.data(), to_nodes.data(), &num_edges))
+        from_nodes.resize(num_edges)
+        to_nodes.resize(num_edges)
+        with nogil:
+            IF CUDA_CORE_BUILD_MAJOR >= 13:
+                HANDLE_RETURN(cydriver.cuGraphGetEdges(
+                    as_cu(self._h_graph), from_nodes.data(), to_nodes.data(), NULL, &num_edges))
+            ELSE:
+                HANDLE_RETURN(cydriver.cuGraphGetEdges(
+                    as_cu(self._h_graph), from_nodes.data(), to_nodes.data(), &num_edges))
 
         return {
             (GraphNode._create(self._h_graph, from_nodes[i]),
diff --git a/cuda_core/cuda/core/graph/_graph_node.pxd b/cuda_core/cuda/core/graph/_graph_node.pxd
index 0a87b70ad62..ef7d1ff0643 100644
--- a/cuda_core/cuda/core/graph/_graph_node.pxd
+++ b/cuda_core/cuda/core/graph/_graph_node.pxd
@@ -2,14 +2,43 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
+from libc.stddef cimport size_t
+
 from cuda.bindings cimport cydriver
-from cuda.core._resource_handles cimport GraphHandle, GraphNodeHandle
+from cuda.core._resource_handles cimport (
+    GraphHandle,
+    GraphNodeHandle,
+    OpaqueHandle,
+    as_intptr,
+    graph_node_get_graph,
+)
 
 
 cdef class GraphNode:
     cdef:
         GraphNodeHandle _h_node
+        bint _is_entry
         object __weakref__
 
     @staticmethod
     cdef GraphNode _create(GraphHandle h_graph, cydriver.CUgraphNode node)
+
+
+cdef inline int GN_check_valid(GraphNode self) except -1:
+    if as_intptr(graph_node_get_graph(self._h_node)) == 0:
+        raise RuntimeError("GraphNode belongs to an invalid GraphDefinition")
+    if not self._is_entry and as_intptr(self._h_node) == 0:
+        raise RuntimeError("GraphNode has been destroyed")
+    return 0
+
+
+cdef OpaqueHandle _resolve_memcpy_operand(
+    object operand, object owner, str side, cydriver.CUdeviceptr* out_ptr) except *
+
+cdef cydriver.CUmemorytype _get_memcpy_memory_type(
+    cydriver.CUdeviceptr ptr) except *
+
+cdef void _init_memcpy_params(
+    cydriver.CUdeviceptr dst, cydriver.CUdeviceptr src, size_t size,
+    cydriver.CUDA_MEMCPY3D* params, cydriver.CUmemorytype* dst_type,
+    cydriver.CUmemorytype* src_type) except *
diff --git a/cuda_core/cuda/core/graph/_graph_node.pyi b/cuda_core/cuda/core/graph/_graph_node.pyi
index 23bcbf191a3..effb5799c0f 100644
--- a/cuda_core/cuda/core/graph/_graph_node.pyi
+++ b/cuda_core/cuda/core/graph/_graph_node.pyi
@@ -1,8 +1,6 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/graph/_graph_node.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/graph/_graph_node.pyx
 
 """GraphNode base class — factory, properties, and builder methods."""
-from __future__ import annotations
-
 import weakref
 from collections.abc import Iterable
 
@@ -21,6 +19,8 @@ from cuda.core.graph._subclasses import (AllocNode, ChildGraphNode, EmptyNode,
                                          SwitchNode, WhileNode)
 from cuda.core.typing import GraphMemoryType
 
+__all__ = ['GraphNode']
+_node_registry: weakref.WeakValueDictionary[int, GraphNode] = weakref.WeakValueDictionary()
 
 class GraphNode:
     """A node in a graph definition.
@@ -29,16 +29,9 @@ class GraphNode:
     entry-point nodes with no dependencies) or on other Nodes (for
     nodes that depend on a predecessor).
     """
-
-    def __repr__(self) -> str:
-        ...
-
-    def __eq__(self, other: object) -> bool:
-        ...
-
-    def __hash__(self) -> int:
-        ...
-
+    def __repr__(self) -> str: ...
+    def __eq__(self, other: object) -> bool: ...
+    def __hash__(self) -> int: ...
     @property
     def type(self) -> driver.CUgraphNodeType | None:
         """Return the CUDA graph node type.
@@ -48,25 +41,21 @@ class GraphNode:
         CUgraphNodeType or None
             The node type enum value, or None for the entry node.
         """
-
     @property
     def graph(self) -> GraphDefinition:
         """Return the GraphDefinition this node belongs to."""
-
     @property
     def handle(self) -> driver.CUgraphNode:
         """Return the underlying driver CUgraphNode handle.
 
         Returns None for the entry node.
         """
-
     @property
     def is_valid(self) -> bool:
-        """Whether this node is valid (not destroyed).
+        """Whether this node and its graph definition remain valid.
 
         Returns ``False`` after :meth:`destroy` has been called.
         """
-
     def destroy(self) -> None:
         """Destroy this node and remove all its edges from the parent graph.
 
@@ -74,26 +63,22 @@ class GraphNode:
         cannot be re-added to any graph.  Safe to call on an
         already-destroyed node (no-op).
         """
-
     @property
     def pred(self) -> AdjacencySetProxy:
         """A mutable set-like view of this node's predecessors."""
-
     @pred.setter
-    def pred(self, value: Iterable[GraphNode]) -> None:
-        ...
-
+    def pred(self, value: Iterable[GraphNode]) -> None: ...
     @property
     def succ(self) -> AdjacencySetProxy:
         """A mutable set-like view of this node's successors."""
-
     @succ.setter
-    def succ(self, value: Iterable[GraphNode]) -> None:
-        ...
-
+    def succ(self, value: Iterable[GraphNode]) -> None: ...
     def launch(self, config: LaunchConfig, kernel: Kernel, *args) -> KernelNode:
         """Add a kernel launch node depending on this node.
 
+        Clustered and cooperative launch configurations are not currently
+        supported for graph kernel nodes.
+
         .. warning::
 
             Use caution when a retained kernel argument directly or indirectly
@@ -115,7 +100,6 @@ class GraphNode:
         KernelNode
             A new KernelNode representing the kernel launch.
         """
-
     def join(self, *nodes: GraphNode) -> EmptyNode:
         """Create an empty node that depends on this node and all given nodes.
 
@@ -131,8 +115,7 @@ class GraphNode:
         EmptyNode
             A new EmptyNode that depends on all input nodes.
         """
-
-    def allocate(self, size: int, *, device: Device | int | None=None, memory_type: GraphMemoryType=..., peer_access: list[Device | int] | None=None) -> AllocNode:
+    def allocate(self, size: int, *, device: Device | int | None=None, memory_type: GraphMemoryType=GraphMemoryType.DEVICE, peer_access: list[Device | int] | None=None) -> AllocNode:
         """Add a memory allocation node depending on this node.
 
         Parameters
@@ -171,7 +154,6 @@ class GraphNode:
         IPC (inter-process communication) is not supported for graph
         memory allocation nodes per CUDA documentation.
         """
-
     def deallocate(self, dptr: int) -> FreeNode:
         """Add a memory free node depending on this node.
 
@@ -185,7 +167,6 @@ class GraphNode:
         FreeNode
             A new FreeNode representing the free operation.
         """
-
     def memset(self, dst: Buffer | int, value, width: int, height: int=1, pitch: int=0, *, dst_owner=None) -> MemsetNode:
         """Add a memset node depending on this node.
 
@@ -227,7 +208,6 @@ class GraphNode:
         ValueError
             If ``dst_owner`` is given together with a :class:`Buffer` ``dst``.
         """
-
     def memcpy(self, dst: Buffer | int, src: Buffer | int, size: int, *, dst_owner=None, src_owner=None) -> MemcpyNode:
         """Add a memcpy node depending on this node.
 
@@ -274,7 +254,6 @@ class GraphNode:
             If ``dst_owner`` or ``src_owner`` is given together with a
             :class:`Buffer` ``dst`` or ``src`` respectively.
         """
-
     def embed(self, child: GraphDefinition) -> ChildGraphNode:
         """Add a child graph node depending on this node.
 
@@ -292,7 +271,6 @@ class GraphNode:
         ChildGraphNode
             A new ChildGraphNode representing the embedded sub-graph.
         """
-
     def record(self, event: Event) -> EventRecordNode:
         """Add an event record node depending on this node.
 
@@ -306,7 +284,6 @@ class GraphNode:
         EventRecordNode
             A new EventRecordNode representing the event record operation.
         """
-
     def wait(self, event: Event) -> EventWaitNode:
         """Add an event wait node depending on this node.
 
@@ -320,7 +297,6 @@ class GraphNode:
         EventWaitNode
             A new EventWaitNode representing the event wait operation.
         """
-
     def callback(self, fn, *, user_data=None) -> object:
         """Add a host callback node depending on this node.
 
@@ -330,10 +306,12 @@ class GraphNode:
         - **Python callable**: Pass any callable. The GIL is acquired
           automatically. The callable must take no arguments; use closures
           or ``functools.partial`` to bind state.
-        - **ctypes function pointer**: Pass a ``ctypes.CFUNCTYPE`` instance.
-          The function receives a single ``void*`` argument (the
-          ``user_data``). The caller must keep the ctypes wrapper alive
-          for the lifetime of the graph.
+        - **ctypes function pointer**: The function receives a single
+          ``void*`` argument (the ``user_data``), and the caller must keep
+          the ctypes wrapper alive for the lifetime of the graph. Its
+          declared prototype must match the driver's ``CUhostFn``
+          (``void (*)(void*)``): ``ctypes.CFUNCTYPE(None, ctypes.c_void_p)``,
+          or ``ctypes.WINFUNCTYPE(None, ctypes.c_void_p)`` on Windows.
 
         .. warning::
 
@@ -358,8 +336,15 @@ class GraphNode:
         -------
         HostCallbackNode
             A new HostCallbackNode representing the callback.
-        """
 
+        Raises
+        ------
+        TypeError
+            If ``fn`` is a ctypes function pointer whose declared prototype
+            does not match ``CUhostFn``.
+        ValueError
+            If ``user_data`` is given for a Python callable.
+        """
     def if_then(self, condition: GraphCondition) -> IfNode:
         """Add an if-conditional node depending on this node.
 
@@ -376,7 +361,6 @@ class GraphNode:
         IfNode
             A new IfNode with one branch accessible via ``.then``.
         """
-
     def if_else(self, condition: GraphCondition) -> IfElseNode:
         """Add an if-else conditional node depending on this node.
 
@@ -394,7 +378,6 @@ class GraphNode:
             A new IfElseNode with branches accessible via
             ``.then`` and ``.else_``.
         """
-
     def while_loop(self, condition: GraphCondition) -> WhileNode:
         """Add a while-loop conditional node depending on this node.
 
@@ -411,7 +394,6 @@ class GraphNode:
         WhileNode
             A new WhileNode with body accessible via ``.body``.
         """
-
     def switch(self, condition: GraphCondition, count: int) -> SwitchNode:
         """Add a switch conditional node depending on this node.
 
@@ -430,5 +412,3 @@ class GraphNode:
         SwitchNode
             A new SwitchNode with branches accessible via ``.branches``.
         """
-__all__ = ['GraphNode']
-_node_registry: weakref.WeakValueDictionary[int, GraphNode] = weakref.WeakValueDictionary()
\ No newline at end of file
diff --git a/cuda_core/cuda/core/graph/_graph_node.pyx b/cuda_core/cuda/core/graph/_graph_node.pyx
index 9e1cab09e7b..7295d786089 100644
--- a/cuda_core/cuda/core/graph/_graph_node.pyx
+++ b/cuda_core/cuda/core/graph/_graph_node.pyx
@@ -17,12 +17,17 @@ from libcpp.vector cimport vector
 
 from cuda.bindings cimport cydriver
 
-from cuda.core._event cimport Event
+from cuda.core._event cimport Event, Event_check_open
 from cuda.core._kernel_arg_handler cimport ParamHolder
 from cuda.core._launch_config cimport LaunchConfig
-from cuda.core._memory._buffer cimport Buffer
+from cuda.core._memory._buffer cimport Buffer, Buffer_check_open
+from cuda.core._memory._location cimport cumemlocation_from_id
 from cuda.core._module cimport Kernel
-from cuda.core.graph._graph_definition cimport GraphCondition, GraphDefinition
+from cuda.core.graph._graph_definition cimport (
+    GraphCondition,
+    GraphDefinition,
+    GD_check_valid,
+)
 from cuda.core.graph._subclasses cimport (
     AllocNode,
     ChildGraphNode,
@@ -101,7 +106,9 @@ cdef class GraphNode:
     def __repr__(self) -> str:
         cdef cydriver.CUgraphNode node = as_cu(self._h_node)
         if node == NULL:
-            return "<GraphNode entry>"
+            if self._is_entry and self.is_valid:
+                return "<GraphNode entry>"
+            return "<GraphNode destroyed>"
         return f"<GraphNode handle=0x{<uintptr_t>node:x}>"
 
     def __eq__(self, other: object) -> bool:
@@ -149,11 +156,14 @@ cdef class GraphNode:
 
     @property
     def is_valid(self) -> bool:
-        """Whether this node is valid (not destroyed).
+        """Whether this node and its graph definition remain valid.
 
         Returns ``False`` after :meth:`destroy` has been called.
         """
-        return as_intptr(self._h_node) != 0
+        return (
+            as_intptr(graph_node_get_graph(self._h_node)) != 0
+            and (self._is_entry or as_intptr(self._h_node) != 0)
+        )
 
     def destroy(self) -> None:
         """Destroy this node and remove all its edges from the parent graph.
@@ -163,13 +173,11 @@ cdef class GraphNode:
         already-destroyed node (no-op).
         """
         cdef cydriver.CUgraphNode node = as_cu(self._h_node)
-        cdef GraphHandle h_graph
-        cdef cydriver.CUresult cleanup_status
         cdef PreparedAttachment prepared
-        if node == NULL:
+        if self._is_entry or node == NULL:
             return
 
-        h_graph = graph_node_get_graph(self._h_node)
+        cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
         # Allocate the cleanup transaction before asking CUDA to destroy the
         # node. A failed CUDA call leaves metadata and wrappers unchanged.
         HANDLE_RETURN(graph_prepare_attachment(
@@ -178,7 +186,7 @@ cdef class GraphNode:
             HANDLE_RETURN(cydriver.cuGraphDestroyNode(node))
 
         # Publish attachment removal before invalidating graph and node aliases.
-        cleanup_status = graph_commit_attachment(prepared, node)
+        cdef cydriver.CUresult cleanup_status = graph_commit_attachment(prepared, node)
         invalidate_child_graph_state(h_graph, node)
         _node_registry.pop(<uintptr_t>self._h_node.get(), None)
         invalidate_graph_node(self._h_node)
@@ -209,6 +217,9 @@ cdef class GraphNode:
     def launch(self, config: LaunchConfig, kernel: Kernel, *args) -> KernelNode:
         """Add a kernel launch node depending on this node.
 
+        Clustered and cooperative launch configurations are not currently
+        supported for graph kernel nodes.
+
         .. warning::
 
             Use caution when a retained kernel argument directly or indirectly
@@ -230,6 +241,7 @@ cdef class GraphNode:
         KernelNode
             A new KernelNode representing the kernel launch.
         """
+        GN_check_valid(self)
         return GN_launch(self, config, <Kernel>kernel, ParamHolder(args))
 
     def join(self, *nodes: GraphNode) -> EmptyNode:
@@ -357,11 +369,12 @@ cdef class GraphNode:
         ValueError
             If ``dst_owner`` is given together with a :class:`Buffer` ``dst``.
         """
+        GN_check_valid(self)
         cdef cydriver.CUdeviceptr c_dst
         cdef unsigned int val
         cdef unsigned int elem_size
-        cdef OpaqueHandle dst_attachment_owner
-        dst_attachment_owner = _resolve_memcpy_operand(dst, dst_owner, "dst", &c_dst)
+        cdef OpaqueHandle dst_attachment_owner = _resolve_memcpy_operand(
+            dst, dst_owner, "dst", &c_dst)
         val, elem_size = _parse_fill_value(value)
         return GN_memset(
             self, c_dst, dst_attachment_owner,
@@ -421,11 +434,13 @@ cdef class GraphNode:
             If ``dst_owner`` or ``src_owner`` is given together with a
             :class:`Buffer` ``dst`` or ``src`` respectively.
         """
+        GN_check_valid(self)
         cdef cydriver.CUdeviceptr c_dst
         cdef cydriver.CUdeviceptr c_src
-        cdef OpaqueHandle dst_attachment_owner, src_attachment_owner
-        dst_attachment_owner = _resolve_memcpy_operand(dst, dst_owner, "dst", &c_dst)
-        src_attachment_owner = _resolve_memcpy_operand(src, src_owner, "src", &c_src)
+        cdef OpaqueHandle dst_attachment_owner = _resolve_memcpy_operand(
+            dst, dst_owner, "dst", &c_dst)
+        cdef OpaqueHandle src_attachment_owner = _resolve_memcpy_operand(
+            src, src_owner, "src", &c_src)
         return GN_memcpy(
             self, c_dst, dst_attachment_owner,
             c_src, src_attachment_owner, size)
@@ -488,10 +503,12 @@ cdef class GraphNode:
         - **Python callable**: Pass any callable. The GIL is acquired
           automatically. The callable must take no arguments; use closures
           or ``functools.partial`` to bind state.
-        - **ctypes function pointer**: Pass a ``ctypes.CFUNCTYPE`` instance.
-          The function receives a single ``void*`` argument (the
-          ``user_data``). The caller must keep the ctypes wrapper alive
-          for the lifetime of the graph.
+        - **ctypes function pointer**: The function receives a single
+          ``void*`` argument (the ``user_data``), and the caller must keep
+          the ctypes wrapper alive for the lifetime of the graph. Its
+          declared prototype must match the driver's ``CUhostFn``
+          (``void (*)(void*)``): ``ctypes.CFUNCTYPE(None, ctypes.c_void_p)``,
+          or ``ctypes.WINFUNCTYPE(None, ctypes.c_void_p)`` on Windows.
 
         .. warning::
 
@@ -516,6 +533,14 @@ cdef class GraphNode:
         -------
         HostCallbackNode
             A new HostCallbackNode representing the callback.
+
+        Raises
+        ------
+        TypeError
+            If ``fn`` is a ctypes function pointer whose declared prototype
+            does not match ``CUhostFn``.
+        ValueError
+            If ``user_data`` is given for a Python callable.
         """
         return GN_callback(self, fn, user_data)
 
@@ -609,6 +634,7 @@ cdef inline ConditionalNode _make_conditional_node(
         cydriver.CUgraphConditionalNodeType cond_type,
         unsigned int size,
         type node_cls):
+    GN_check_valid(pred)
     if not isinstance(condition, GraphCondition):
         raise TypeError(
             f"condition must be a GraphCondition object (from "
@@ -669,6 +695,7 @@ cdef inline GraphNode GN_create(GraphHandle h_graph, cydriver.CUgraphNode node):
     if node == NULL:
         n = GraphNode.__new__(GraphNode)
         (<GraphNode>n)._h_node = h_node
+        (<GraphNode>n)._is_entry = True
         return n
 
     # Return a registered object or create and register a new one.
@@ -711,37 +738,42 @@ cdef inline GraphNode GN_create_impl(GraphNodeHandle h_node):
         (<GraphNode>n)._h_node = h_node
         return n
 
-
 cdef inline KernelNode GN_launch(GraphNode self, LaunchConfig conf, Kernel ker, ParamHolder ker_args):
-    cdef cydriver.CUDA_KERNEL_NODE_PARAMS node_params
     cdef cydriver.CUgraphNode new_node = NULL
     cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
     cdef cydriver.CUgraphNode pred_node = as_cu(self._h_node)
     cdef cydriver.CUgraphNode* deps = NULL
     cdef size_t num_deps = 0
-    cdef OpaqueHandle kernel_owner, args_owner
+    cdef OpaqueHandle args_owner
     cdef PreparedAttachment prepared
 
+    GN_check_valid(self)
+    if conf.cluster is not None or conf.is_cooperative:
+        raise NotImplementedError(
+            "clustered or cooperative graph kernel nodes are not supported")
+
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
 
-    node_params.kern = as_cu(ker._h_kernel)
-    node_params.func = <cydriver.CUfunction>NULL
-    node_params.gridDimX = conf.grid[0]
-    node_params.gridDimY = conf.grid[1]
-    node_params.gridDimZ = conf.grid[2]
-    node_params.blockDimX = conf.block[0]
-    node_params.blockDimY = conf.block[1]
-    node_params.blockDimZ = conf.block[2]
-    node_params.sharedMemBytes = conf.shmem_size
-    node_params.kernelParams = <void**><uintptr_t>(ker_args.ptr)
-    node_params.extra = NULL
-    node_params.ctx = <cydriver.CUcontext>NULL
+    cdef cydriver.CUDA_KERNEL_NODE_PARAMS node_params = cydriver.CUDA_KERNEL_NODE_PARAMS(
+        kern=as_cu(ker._h_kernel),
+        func=<cydriver.CUfunction>NULL,
+        gridDimX=conf.grid[0],
+        gridDimY=conf.grid[1],
+        gridDimZ=conf.grid[2],
+        blockDimX=conf.block[0],
+        blockDimY=conf.block[1],
+        blockDimZ=conf.block[2],
+        sharedMemBytes=conf.shmem_size,
+        kernelParams=<void**><uintptr_t>(ker_args.ptr),
+        extra=NULL,
+        ctx=<cydriver.CUcontext>NULL,
+    )
 
     # Keep the kernel and argument objects alive because CUDA copies argument
     # values but does not retain the resources they reference.
-    kernel_owner = ker._h_kernel
+    cdef OpaqueHandle kernel_owner = ker._h_kernel
     kernel_args = ker_args.kernel_args
     if kernel_args is not None:
         args_owner = make_opaque_py(kernel_args)
@@ -769,9 +801,11 @@ cdef inline EmptyNode GN_join(GraphNode self, tuple nodes):
     cdef size_t num_deps = 0
     cdef cydriver.CUgraphNode pred_node = as_cu(self._h_node)
 
+    GN_check_valid(self)
     if pred_node != NULL:
         deps.push_back(pred_node)
     for other in nodes:
+        GN_check_valid(other)
         if as_cu((<GraphNode>other)._h_node) != NULL:
             deps.push_back(as_cu((<GraphNode>other)._h_node))
 
@@ -791,6 +825,7 @@ cdef inline AllocNode GN_alloc(GraphNode self, size_t size, object device,
     cdef int device_id
     cdef cydriver.CUdevice dev
 
+    GN_check_valid(self)
     if device is None:
         with nogil:
             HANDLE_RETURN(cydriver.cuCtxGetDevice(&dev))
@@ -810,6 +845,7 @@ cdef inline AllocNode GN_alloc(GraphNode self, size_t size, object device,
         num_deps = 1
 
     cdef vector[cydriver.CUmemAccessDesc] access_descs
+    cdef cydriver.CUmemAccessDesc access_desc
     cdef int peer_id
     cdef list peer_ids = []
 
@@ -817,13 +853,10 @@ cdef inline AllocNode GN_alloc(GraphNode self, size_t size, object device,
         for peer_dev in peer_access:
             peer_id = getattr(peer_dev, 'device_id', peer_dev)
             peer_ids.append(peer_id)
-            access_descs.push_back(cydriver.CUmemAccessDesc_st(
-                cydriver.CUmemLocation_st(
-                    cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE,
-                    peer_id
-                ),
-                cydriver.CUmemAccess_flags.CU_MEM_ACCESS_FLAGS_PROT_READWRITE
-            ))
+            access_desc.location = cumemlocation_from_id(
+                cydriver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE, peer_id)
+            access_desc.flags = cydriver.CUmemAccess_flags.CU_MEM_ACCESS_FLAGS_PROT_READWRITE
+            access_descs.push_back(access_desc)
 
     cdef str memory_type_str = "device" if memory_type is None else str(memory_type)
 
@@ -868,6 +901,7 @@ cdef inline FreeNode GN_free(GraphNode self, cydriver.CUdeviceptr c_dptr):
     cdef cydriver.CUgraphNode* deps = NULL
     cdef size_t num_deps = 0
 
+    GN_check_valid(self)
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
@@ -881,15 +915,16 @@ cdef inline FreeNode GN_free(GraphNode self, cydriver.CUdeviceptr c_dptr):
 
 cdef inline OpaqueHandle _buffer_attachment_owner(Buffer buf, str label):
     """Copy a Buffer's device-pointer handle into an attachment owner."""
-    cdef OpaqueHandle attachment_owner
-    if not buf._h_ptr:
-        raise ValueError(f"{label} Buffer has no active allocation")
-    attachment_owner = buf._h_ptr
+    Buffer_check_open(buf)
+    # The local is required: Cython permits the DevicePtrHandle -> OpaqueHandle
+    # conversion on assignment, but not directly in a return statement.
+    cdef OpaqueHandle attachment_owner = buf._h_ptr
     return attachment_owner
 
 
 cdef inline OpaqueHandle _resolve_memcpy_operand(
-        object operand, object owner, str side, cydriver.CUdeviceptr* out_ptr):
+        object operand, object owner, str side,
+        cydriver.CUdeviceptr* out_ptr) except *:
     """Resolve an operand to a pointer and optional attachment owner.
 
     ``operand`` is a :class:`Buffer` or a raw integer address; its device
@@ -928,7 +963,6 @@ cdef inline MemsetNode GN_memset(
         GraphNode self, cydriver.CUdeviceptr c_dst, OpaqueHandle dst_owner,
         unsigned int val, unsigned int elem_size,
         size_t width, size_t height, size_t pitch):
-    cdef cydriver.CUDA_MEMSET_NODE_PARAMS memset_params
     cdef cydriver.CUgraphNode new_node = NULL
     cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
     cdef cydriver.CUgraphNode pred_node = as_cu(self._h_node)
@@ -936,6 +970,7 @@ cdef inline MemsetNode GN_memset(
     cdef size_t num_deps = 0
     cdef PreparedAttachment prepared
 
+    GN_check_valid(self)
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
@@ -944,13 +979,14 @@ cdef inline MemsetNode GN_memset(
     with nogil:
         HANDLE_RETURN(cydriver.cuCtxGetCurrent(&ctx))
 
-    c_memset(&memset_params, 0, sizeof(memset_params))
-    memset_params.dst = c_dst
-    memset_params.value = val
-    memset_params.elementSize = elem_size
-    memset_params.width = width
-    memset_params.height = height
-    memset_params.pitch = pitch
+    cdef cydriver.CUDA_MEMSET_NODE_PARAMS memset_params = cydriver.CUDA_MEMSET_NODE_PARAMS(
+        dst=c_dst,
+        pitch=pitch,
+        value=val,
+        elementSize=elem_size,
+        width=width,
+        height=height,
+    )
 
     if dst_owner:
         HANDLE_RETURN(graph_prepare_attachment(
@@ -969,46 +1005,52 @@ cdef inline MemsetNode GN_memset(
         val, elem_size, width, height, pitch))
 
 
-cdef inline MemcpyNode GN_memcpy(
-        GraphNode self, cydriver.CUdeviceptr c_dst, OpaqueHandle dst_owner,
-        cydriver.CUdeviceptr c_src, OpaqueHandle src_owner, size_t size):
-    cdef unsigned int dst_mem_type = cydriver.CU_MEMORYTYPE_DEVICE
-    cdef unsigned int src_mem_type = cydriver.CU_MEMORYTYPE_DEVICE
+cdef cydriver.CUmemorytype _get_memcpy_memory_type(
+        cydriver.CUdeviceptr ptr) except *:
+    cdef unsigned int memory_type = cydriver.CU_MEMORYTYPE_DEVICE
     cdef cydriver.CUresult ret
     with nogil:
         ret = cydriver.cuPointerGetAttribute(
-            &dst_mem_type,
+            &memory_type,
             cydriver.CU_POINTER_ATTRIBUTE_MEMORY_TYPE,
-            c_dst)
-        if ret != cydriver.CUDA_SUCCESS and ret != cydriver.CUDA_ERROR_INVALID_VALUE:
-            HANDLE_RETURN(ret)
-        ret = cydriver.cuPointerGetAttribute(
-            &src_mem_type,
-            cydriver.CU_POINTER_ATTRIBUTE_MEMORY_TYPE,
-            c_src)
-        if ret != cydriver.CUDA_SUCCESS and ret != cydriver.CUDA_ERROR_INVALID_VALUE:
-            HANDLE_RETURN(ret)
-
-    cdef cydriver.CUmemorytype c_dst_type = <cydriver.CUmemorytype>dst_mem_type
-    cdef cydriver.CUmemorytype c_src_type = <cydriver.CUmemorytype>src_mem_type
-
-    cdef cydriver.CUDA_MEMCPY3D params
-    c_memset(&params, 0, sizeof(params))
-
-    params.srcMemoryType = c_src_type
-    params.dstMemoryType = c_dst_type
-    if c_src_type == cydriver.CU_MEMORYTYPE_HOST:
-        params.srcHost = <const void*><uintptr_t>c_src
+            ptr)
+    if ret != cydriver.CUDA_SUCCESS and ret != cydriver.CUDA_ERROR_INVALID_VALUE:
+        HANDLE_RETURN(ret)
+    return <cydriver.CUmemorytype>memory_type
+
+
+cdef void _init_memcpy_params(
+        cydriver.CUdeviceptr dst, cydriver.CUdeviceptr src, size_t size,
+        cydriver.CUDA_MEMCPY3D* params, cydriver.CUmemorytype* dst_type,
+        cydriver.CUmemorytype* src_type) except *:
+    dst_type[0] = _get_memcpy_memory_type(dst)
+    src_type[0] = _get_memcpy_memory_type(src)
+
+    c_memset(params, 0, sizeof(params[0]))
+    params.srcMemoryType = src_type[0]
+    params.dstMemoryType = dst_type[0]
+    if src_type[0] == cydriver.CU_MEMORYTYPE_HOST:
+        params.srcHost = <void*><uintptr_t>src
     else:
-        params.srcDevice = c_src
-    if c_dst_type == cydriver.CU_MEMORYTYPE_HOST:
-        params.dstHost = <void*><uintptr_t>c_dst
+        params.srcDevice = src
+    if dst_type[0] == cydriver.CU_MEMORYTYPE_HOST:
+        params.dstHost = <void*><uintptr_t>dst
     else:
-        params.dstDevice = c_dst
+        params.dstDevice = dst
     params.WidthInBytes = size
     params.Height = 1
     params.Depth = 1
 
+
+cdef inline MemcpyNode GN_memcpy(
+        GraphNode self, cydriver.CUdeviceptr c_dst, OpaqueHandle dst_owner,
+        cydriver.CUdeviceptr c_src, OpaqueHandle src_owner, size_t size):
+    cdef cydriver.CUDA_MEMCPY3D params
+    cdef cydriver.CUmemorytype c_dst_type
+    cdef cydriver.CUmemorytype c_src_type
+    _init_memcpy_params(
+        c_dst, c_src, size, &params, &c_dst_type, &c_src_type)
+
     cdef cydriver.CUgraphNode new_node = NULL
     cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
     cdef cydriver.CUgraphNode pred_node = as_cu(self._h_node)
@@ -1016,6 +1058,7 @@ cdef inline MemcpyNode GN_memcpy(
     cdef size_t num_deps = 0
     cdef PreparedAttachment prepared
 
+    GN_check_valid(self)
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
@@ -1046,6 +1089,8 @@ cdef inline ChildGraphNode GN_embed(GraphNode self, GraphDefinition child_def):
     cdef size_t num_deps = 0
     cdef cydriver.CUresult rollback_status
 
+    GN_check_valid(self)
+    GD_check_valid(child_def)
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
@@ -1076,19 +1121,20 @@ cdef inline ChildGraphNode GN_embed(GraphNode self, GraphDefinition child_def):
 
 
 cdef inline EventRecordNode GN_record_event(GraphNode self, Event ev):
+    GN_check_valid(self)
+    Event_check_open(ev)
     cdef cydriver.CUgraphNode new_node = NULL
     cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
     cdef cydriver.CUgraphNode pred_node = as_cu(self._h_node)
     cdef cydriver.CUgraphNode* deps = NULL
     cdef size_t num_deps = 0
-    cdef OpaqueHandle owner
     cdef PreparedAttachment prepared
 
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
 
-    owner = ev._h_event
+    cdef OpaqueHandle owner = ev._h_event
     HANDLE_RETURN(graph_prepare_attachment(
         h_graph, owner, OpaqueHandle(), &prepared))
 
@@ -1103,19 +1149,20 @@ cdef inline EventRecordNode GN_record_event(GraphNode self, Event ev):
 
 
 cdef inline EventWaitNode GN_wait_event(GraphNode self, Event ev):
+    GN_check_valid(self)
+    Event_check_open(ev)
     cdef cydriver.CUgraphNode new_node = NULL
     cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
     cdef cydriver.CUgraphNode pred_node = as_cu(self._h_node)
     cdef cydriver.CUgraphNode* deps = NULL
     cdef size_t num_deps = 0
-    cdef OpaqueHandle owner
     cdef PreparedAttachment prepared
 
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
 
-    owner = ev._h_event
+    cdef OpaqueHandle owner = ev._h_event
     HANDLE_RETURN(graph_prepare_attachment(
         h_graph, owner, OpaqueHandle(), &prepared))
 
@@ -1139,6 +1186,7 @@ cdef inline HostCallbackNode GN_callback(GraphNode self, object fn, object user_
     cdef OpaqueHandle fn_owner, data_owner
     cdef PreparedAttachment prepared
 
+    GN_check_valid(self)
     if pred_node != NULL:
         deps = &pred_node
         num_deps = 1
diff --git a/cuda_core/cuda/core/graph/_host_callback.pyi b/cuda_core/cuda/core/graph/_host_callback.pyi
index 6c9d0ead317..cc48abf95a1 100644
--- a/cuda_core/cuda/core/graph/_host_callback.pyi
+++ b/cuda_core/cuda/core/graph/_host_callback.pyi
@@ -1,3 +1,16 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/graph/_host_callback.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/graph/_host_callback.pyx
 
-from __future__ import annotations
\ No newline at end of file
+import sys
+
+_CUHOSTFN_HINT = 'ctypes.CFUNCTYPE(None, ctypes.c_void_p)' if sys.platform != 'win32' else 'ctypes.CFUNCTYPE(None, ctypes.c_void_p) or ctypes.WINFUNCTYPE(None, ctypes.c_void_p)'
+
+def _cuhostfn_type_error(detail):
+    """Build the rejection message for a non-conforming ctypes callback."""
+def _validate_ctypes_host_callback(fn):
+    """Reject ctypes callbacks whose declared prototype is not CUhostFn.
+
+    ``restype`` and ``argtypes`` are the prototype the caller declared, and are
+    what CUDA calls through. A function pointer taken from a shared library
+    keeps ctypes' defaults -- a ``c_int`` result and unspecified arguments --
+    until the caller declares otherwise, so it must be declared to be accepted.
+    """
diff --git a/cuda_core/cuda/core/graph/_host_callback.pyx b/cuda_core/cuda/core/graph/_host_callback.pyx
index 27f251abeae..4fb48f0d6ec 100644
--- a/cuda_core/cuda/core/graph/_host_callback.pyx
+++ b/cuda_core/cuda/core/graph/_host_callback.pyx
@@ -14,9 +14,47 @@ from cuda.core._resource_handles cimport (
     make_opaque_py,
 )
 
+import sys
 import ctypes as ct
 
 
+# CUhostFn is `void (CUDA_CB *)(void*)`. CUDA_CB is __stdcall on Windows and
+# empty elsewhere, but ctypes only honors that distinction when it builds a
+# callback on 32-bit x86 Windows, which cuda.core does not support: on win-64
+# and ARM64 both CFUNCTYPE and WINFUNCTYPE produce a FFI_DEFAULT_ABI thunk. The
+# declared result and argument types are all that remain worth checking.
+_CUHOSTFN_HINT = (
+    "ctypes.CFUNCTYPE(None, ctypes.c_void_p)"
+    if sys.platform != "win32"
+    else "ctypes.CFUNCTYPE(None, ctypes.c_void_p) or "
+    "ctypes.WINFUNCTYPE(None, ctypes.c_void_p)"
+)
+
+
+def _cuhostfn_type_error(detail):
+    """Build the rejection message for a non-conforming ctypes callback."""
+    return TypeError(
+        f"host callback {detail}; CUDA requires a callback matching CUhostFn "
+        f"(void (*)(void*)), declared as {_CUHOSTFN_HINT}. "
+        "Alternatively, pass a Python callable."
+    )
+
+
+def _validate_ctypes_host_callback(fn):
+    """Reject ctypes callbacks whose declared prototype is not CUhostFn.
+
+    ``restype`` and ``argtypes`` are the prototype the caller declared, and are
+    what CUDA calls through. A function pointer taken from a shared library
+    keeps ctypes' defaults -- a ``c_int`` result and unspecified arguments --
+    until the caller declares otherwise, so it must be declared to be accepted.
+    """
+    restype = fn.restype
+    argtypes = fn.argtypes
+    if restype is not None or argtypes is None or tuple(argtypes) != (ct.c_void_p,):
+        raise _cuhostfn_type_error(
+            f"has prototype restype={restype!r}, argtypes={argtypes!r}")
+
+
 cdef void _py_host_trampoline(void* data) noexcept with gil:
     (<object>data)()
 
@@ -36,8 +74,12 @@ cdef void _resolve_host_callback(
     ``cuGraphAddHostNode`` or ``cuLaunchHostFunc``. ``*out_fn_owner`` owns the
     callback object; ``*out_data_owner`` owns a copied ``user_data`` buffer and
     is left null otherwise. The caller attaches both owners to the graph node.
+
+    ctypes callbacks are validated against the ``CUhostFn`` ABI before their
+    address is passed to CUDA.
     """
     if isinstance(fn, ct._CFuncPtr):
+        _validate_ctypes_host_callback(fn)
         out_fn[0] = <cydriver.CUhostFn><uintptr_t>ct.cast(fn, ct.c_void_p).value
         if user_data is None:
             out_user_data[0] = NULL
@@ -54,6 +96,9 @@ cdef void _resolve_host_callback(
             else:
                 out_user_data[0] = NULL
     else:
+        if not callable(fn):
+            raise TypeError(
+                f"callback must be callable, got {type(fn).__name__}")
         if user_data is not None:
             raise ValueError(
                 "user_data is only supported with ctypes function pointers")
diff --git a/cuda_core/cuda/core/graph/_subclasses.pxd b/cuda_core/cuda/core/graph/_subclasses.pxd
index 7f84b713429..7f92eafe7e8 100644
--- a/cuda_core/cuda/core/graph/_subclasses.pxd
+++ b/cuda_core/cuda/core/graph/_subclasses.pxd
@@ -7,7 +7,13 @@ from libc.stddef cimport size_t
 from cuda.bindings cimport cydriver
 from cuda.core.graph._graph_definition cimport GraphCondition
 from cuda.core.graph._graph_node cimport GraphNode
-from cuda.core._resource_handles cimport EventHandle, GraphHandle, GraphNodeHandle, KernelHandle
+from cuda.core._resource_handles cimport (
+    EventHandle,
+    GraphExecHandle,
+    GraphHandle,
+    GraphNodeHandle,
+    KernelHandle,
+)
 
 
 cdef class EmptyNode(GraphNode):
@@ -172,3 +178,41 @@ cdef class WhileNode(ConditionalNode):
 
 cdef class SwitchNode(ConditionalNode):
     pass
+
+
+cdef class ExecutableGraphNode:
+    cdef:
+        GraphExecHandle _h_graph_exec
+        GraphNodeHandle _h_node
+
+
+cdef class ExecutableKernelNode(ExecutableGraphNode):
+    pass
+
+
+cdef class ExecutableMemsetNode(ExecutableGraphNode):
+    pass
+
+
+cdef class ExecutableMemcpyNode(ExecutableGraphNode):
+    pass
+
+
+cdef class ExecutableChildGraphNode(ExecutableGraphNode):
+    pass
+
+
+cdef class ExecutableEventRecordNode(ExecutableGraphNode):
+    pass
+
+
+cdef class ExecutableEventWaitNode(ExecutableGraphNode):
+    pass
+
+
+cdef class ExecutableHostCallbackNode(ExecutableGraphNode):
+    pass
+
+
+cdef ExecutableGraphNode create_executable_node_view(
+    const GraphExecHandle& h_exec, GraphNode node)
diff --git a/cuda_core/cuda/core/graph/_subclasses.pyi b/cuda_core/cuda/core/graph/_subclasses.pyi
index 345e6417c4d..e207e05eaca 100644
--- a/cuda_core/cuda/core/graph/_subclasses.pyi
+++ b/cuda_core/cuda/core/graph/_subclasses.pyi
@@ -1,21 +1,19 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/graph/_subclasses.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/graph/_subclasses.pyx
 
 """GraphNode subclasses — EmptyNode through SwitchNode."""
-from __future__ import annotations
-
 from cuda.core._event import Event
 from cuda.core._launch_config import LaunchConfig
+from cuda.core._memory._buffer import Buffer
 from cuda.core._module import Kernel
 from cuda.core.graph._graph_definition import GraphCondition, GraphDefinition
 from cuda.core.graph._graph_node import GraphNode
 from cuda.core.typing import GraphConditionalType
 
+__all__ = ['AllocNode', 'ChildGraphNode', 'ConditionalNode', 'EmptyNode', 'EventRecordNode', 'EventWaitNode', 'ExecutableChildGraphNode', 'ExecutableEventRecordNode', 'ExecutableEventWaitNode', 'ExecutableGraphNode', 'ExecutableHostCallbackNode', 'ExecutableKernelNode', 'ExecutableMemcpyNode', 'ExecutableMemsetNode', 'FreeNode', 'HostCallbackNode', 'IfElseNode', 'IfNode', 'KernelNode', 'MemcpyNode', 'MemsetNode', 'SwitchNode', 'WhileNode']
 
 class EmptyNode(GraphNode):
     """An empty (synchronization) node."""
-
-    def __repr__(self) -> str:
-        ...
+    def __repr__(self) -> str: ...
 
 class KernelNode(GraphNode):
     """A kernel launch node.
@@ -33,26 +31,33 @@ class KernelNode(GraphNode):
     config : LaunchConfig
         A LaunchConfig reconstructed from this node's parameters.
     """
+    def __repr__(self) -> str: ...
+    def update(self, *, config: LaunchConfig | None=None, kernel: Kernel | None=None, args=None) -> None:
+        """Replace selected kernel launch parameters.
 
-    def __repr__(self) -> str:
-        ...
+        Omitted parameters preserve their current values. Changing ``kernel``
+        requires ``args``, including ``args=()`` for a no-argument kernel.
+        Clustered and cooperative kernel nodes are not supported.
 
+        .. warning::
+
+            Use caution when a retained kernel argument directly or indirectly
+            owns a graph. Any reference cycle involving the argument and a
+            graph that retains it cannot be broken by Python's cyclic garbage
+            collector. Use a weak reference to break such cycles.
+        """
     @property
     def grid(self) -> tuple[int, int, int]:
         """Grid dimensions as a 3-tuple (gridDimX, gridDimY, gridDimZ)."""
-
     @property
     def block(self) -> tuple[int, int, int]:
         """Block dimensions as a 3-tuple (blockDimX, blockDimY, blockDimZ)."""
-
     @property
     def shmem_size(self) -> int:
         """Dynamic shared memory size in bytes."""
-
     @property
     def kernel(self) -> Kernel:
         """The Kernel object for this launch node."""
-
     @property
     def config(self) -> LaunchConfig:
         """A LaunchConfig reconstructed from this node's grid, block, and shmem_size.
@@ -77,26 +82,19 @@ class AllocNode(GraphNode):
     peer_access : tuple of int
         Device IDs that have read-write access to this allocation.
     """
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
     @property
     def dptr(self) -> int:
         """The device pointer for the allocation."""
-
     @property
     def bytesize(self) -> int:
         """The number of bytes allocated."""
-
     @property
     def device_id(self) -> int:
         """The device on which the allocation was made."""
-
     @property
     def memory_type(self) -> str:
         """The type of memory: ``"device"``, ``"host"``, or ``"managed"``."""
-
     @property
     def peer_access(self) -> tuple[int, ...]:
         """Device IDs with read-write access to this allocation."""
@@ -109,10 +107,7 @@ class FreeNode(GraphNode):
     dptr : int
         The device pointer being freed.
     """
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
     @property
     def dptr(self) -> int:
         """The device pointer being freed."""
@@ -135,30 +130,39 @@ class MemsetNode(GraphNode):
     pitch : int
         Pitch in bytes (unused if height is 1).
     """
+    def __repr__(self) -> str: ...
+    def update(self, *, dst: Buffer | int | None=None, value=None, width: int | None=None, height: int | None=None, pitch: int | None=None, dst_owner=None) -> None:
+        """Replace selected memset parameters.
+
+        Omitted parameters preserve their current values. ``dst_owner`` may
+        only accompany a raw-address ``dst``.
 
-    def __repr__(self) -> str:
-        ...
+        With CUDA 12.2 through 13.1, the node's intended CUDA context must be
+        current when this method is called. CUDA driver and ``cuda.bindings``
+        versions 13.2 and newer preserve the recorded context automatically.
 
+        .. warning::
+
+            Use caution when a retained operand owner directly or indirectly
+            owns a graph. Any reference cycle involving the owner and a graph
+            that retains it cannot be broken by Python's cyclic garbage
+            collector. Use a weak reference to break such cycles.
+        """
     @property
     def dptr(self) -> int:
         """The destination device pointer."""
-
     @property
     def value(self) -> int:
         """The fill value."""
-
     @property
     def element_size(self) -> int:
         """Element size in bytes (1, 2, or 4)."""
-
     @property
     def width(self) -> int:
         """Width of the row in elements."""
-
     @property
     def height(self) -> int:
         """Number of rows."""
-
     @property
     def pitch(self) -> int:
         """Pitch in bytes (unused if height is 1)."""
@@ -175,18 +179,32 @@ class MemcpyNode(GraphNode):
     size : int
         The number of bytes copied.
     """
+    def __repr__(self) -> str: ...
+    def update(self, *, dst: Buffer | int | None=None, src: Buffer | int | None=None, size: int | None=None, dst_owner=None, src_owner=None) -> None:
+        """Replace selected memcpy parameters.
+
+        Omitted parameters preserve their current values. ``dst_owner`` and
+        ``src_owner`` may only accompany their corresponding raw addresses.
+        Multidimensional, pitched, offset, and array-backed memcpy nodes are
+        not supported.
+
+        With CUDA 12.2 through 13.1, the node's intended CUDA context must be
+        current when this method is called. CUDA driver and ``cuda.bindings``
+        versions 13.2 and newer preserve the recorded context automatically.
 
-    def __repr__(self) -> str:
-        ...
+        .. warning::
 
+            Use caution when a retained operand owner directly or indirectly
+            owns a graph. Any reference cycle involving the owner and a graph
+            that retains it cannot be broken by Python's cyclic garbage
+            collector. Use a weak reference to break such cycles.
+        """
     @property
     def dst(self) -> int:
         """The destination pointer."""
-
     @property
     def src(self) -> int:
         """The source pointer."""
-
     @property
     def size(self) -> int:
         """The number of bytes copied."""
@@ -199,10 +217,12 @@ class ChildGraphNode(GraphNode):
     child_graph : GraphDefinition
         The embedded graph definition (non-owning wrapper).
     """
+    def __repr__(self) -> str: ...
+    def update(self, child: GraphDefinition) -> None:
+        """Replace the embedded graph with a clone of ``child``.
 
-    def __repr__(self) -> str:
-        ...
-
+        ``child`` must belong to an independent graph hierarchy.
+        """
     @property
     def child_graph(self) -> GraphDefinition:
         """The embedded graph definition (non-owning wrapper)."""
@@ -215,10 +235,9 @@ class EventRecordNode(GraphNode):
     event : Event
         The event being recorded.
     """
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
+    def update(self, event: Event) -> None:
+        """Replace the event recorded by this node."""
     @property
     def event(self) -> Event:
         """The event being recorded."""
@@ -231,10 +250,9 @@ class EventWaitNode(GraphNode):
     event : Event
         The event being waited on.
     """
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
+    def update(self, event: Event) -> None:
+        """Replace the event waited on by this node."""
     @property
     def event(self) -> Event:
         """The event being waited on."""
@@ -247,10 +265,25 @@ class HostCallbackNode(GraphNode):
     callback : callable or None
         The Python callable (None for ctypes function pointer callbacks).
     """
+    def __repr__(self) -> str: ...
+    def update(self, fn, *, user_data=None) -> None:
+        """Replace the callback and user-data binding for this node.
+
+        ``fn`` accepts the same forms as :meth:`~graph.GraphNode.callback`: a
+        Python callable, or a ctypes function pointer whose declared prototype
+        matches ``CUhostFn`` (``void (*)(void*)``). A mismatched ctypes
+        prototype raises ``TypeError``.
+
+        .. warning::
 
-    def __repr__(self) -> str:
-        ...
+            Callbacks must not call CUDA API functions. Doing so may
+            deadlock or corrupt driver state.
 
+            Use caution when a Python callback retains an object that owns a
+            graph. Any reference cycle involving the callback and a graph that
+            retains it cannot be broken by Python's cyclic garbage collector.
+            Use a weak reference to break such cycles.
+        """
     @property
     def callback(self):
         """The Python callable, or None for ctypes function pointer callbacks."""
@@ -273,14 +306,10 @@ class ConditionalNode(GraphNode):
     branches : tuple of GraphDefinition
         The body graphs for each branch (empty pre-13.2).
     """
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
     @property
     def condition(self) -> GraphCondition | None:
         """The condition variable controlling execution."""
-
     @property
     def cond_type(self) -> GraphConditionalType | None:
         """The conditional type: GraphConditionalType.IF, .WHILE, or .SWITCH
@@ -288,7 +317,6 @@ class ConditionalNode(GraphNode):
         Returns None when reconstructed from the driver pre-CUDA 13.2,
         as the conditional type cannot be determined.
         """
-
     @property
     def branches(self) -> tuple[GraphDefinition, ...]:
         """The body graphs for each branch as a tuple of GraphDefinition.
@@ -299,41 +327,109 @@ class ConditionalNode(GraphNode):
 
 class IfNode(ConditionalNode):
     """An if-conditional node."""
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
     @property
     def then(self) -> GraphDefinition:
         """The 'then' branch graph."""
 
 class IfElseNode(ConditionalNode):
     """An if-else conditional node."""
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
     @property
     def then(self) -> GraphDefinition:
         """The ``then`` branch graph (executed when condition is non-zero)."""
-
     @property
     def else_(self) -> GraphDefinition:
         """The ``else`` branch graph (executed when condition is zero)."""
 
 class WhileNode(ConditionalNode):
     """A while-loop conditional node."""
-
-    def __repr__(self) -> str:
-        ...
-
+    def __repr__(self) -> str: ...
     @property
     def body(self) -> GraphDefinition:
         """The loop body graph."""
 
 class SwitchNode(ConditionalNode):
     """A switch conditional node."""
+    def __repr__(self) -> str: ...
+
+class ExecutableGraphNode:
+    """A lightweight view pairing an executable graph with a source node.
+
+    Create executable-node views with ``graph[node]``. CUDA validates that the
+    node identifies a node in the executable graph when an operation is
+    performed.
+    """
+    def __init__(self): ...
+    def __repr__(self) -> str: ...
+
+class ExecutableKernelNode(ExecutableGraphNode):
+    """An executable kernel-node view."""
+    def update(self, *, config: LaunchConfig, kernel: Kernel, args) -> None:
+        """Replace all kernel launch parameters for future launches.
 
-    def __repr__(self) -> str:
-        ...
-__all__ = ['AllocNode', 'ChildGraphNode', 'ConditionalNode', 'EmptyNode', 'EventRecordNode', 'EventWaitNode', 'FreeNode', 'HostCallbackNode', 'IfElseNode', 'IfNode', 'KernelNode', 'MemcpyNode', 'MemsetNode', 'SwitchNode', 'WhileNode']
\ No newline at end of file
+        ``args`` must contain the complete argument sequence; use ``args=()``
+        for a no-argument kernel. Clustered and cooperative launch
+        configurations are not supported.
+        """
+    @property
+    def is_enabled(self) -> bool:
+        """Whether this node is enabled in the executable graph."""
+    def enable(self) -> None:
+        """Enable this node in the executable graph."""
+    def disable(self) -> None:
+        """Disable this node in the executable graph."""
+
+class ExecutableMemsetNode(ExecutableGraphNode):
+    """An executable memset-node view."""
+    def update(self, *, dst: Buffer | int, value, width: int, height: int=1, pitch: int=0) -> None:
+        """Replace all memset parameters for future launches."""
+    @property
+    def is_enabled(self) -> bool:
+        """Whether this node is enabled in the executable graph."""
+    def enable(self) -> None:
+        """Enable this node in the executable graph."""
+    def disable(self) -> None:
+        """Disable this node in the executable graph."""
+
+class ExecutableMemcpyNode(ExecutableGraphNode):
+    """An executable memcpy-node view."""
+    def update(self, *, dst: Buffer | int, src: Buffer | int, size: int) -> None:
+        """Replace all one-dimensional memcpy parameters for future launches."""
+    @property
+    def is_enabled(self) -> bool:
+        """Whether this node is enabled in the executable graph."""
+    def enable(self) -> None:
+        """Enable this node in the executable graph."""
+    def disable(self) -> None:
+        """Disable this node in the executable graph."""
+
+class ExecutableChildGraphNode(ExecutableGraphNode):
+    """An executable child-graph-node view."""
+    def update(self, child: GraphDefinition) -> None:
+        """Replace the embedded graph parameters for future launches."""
+
+class ExecutableEventRecordNode(ExecutableGraphNode):
+    """An executable event-record-node view."""
+    def update(self, event: Event) -> None:
+        """Replace the event recorded by future launches."""
+
+class ExecutableEventWaitNode(ExecutableGraphNode):
+    """An executable event-wait-node view."""
+    def update(self, event: Event) -> None:
+        """Replace the event waited on by future launches."""
+
+class ExecutableHostCallbackNode(ExecutableGraphNode):
+    """An executable host-callback-node view."""
+    def update(self, fn, *, user_data=None) -> None:
+        """Replace the callback and user-data binding for future launches.
+
+        ``fn`` may be a Python callable, or a ctypes function pointer whose
+        declared prototype matches ``CUhostFn`` (``void (*)(void*)``); a
+        mismatched prototype raises ``TypeError``.
+
+        .. warning::
+
+            Callbacks must not call CUDA API functions. Doing so may deadlock
+            or corrupt driver state.
+        """
diff --git a/cuda_core/cuda/core/graph/_subclasses.pyx b/cuda_core/cuda/core/graph/_subclasses.pyx
index 2fa08e2a6a1..2201f7babf0 100644
--- a/cuda_core/cuda/core/graph/_subclasses.pyx
+++ b/cuda_core/cuda/core/graph/_subclasses.pyx
@@ -8,29 +8,59 @@ from __future__ import annotations
 
 from libc.stddef cimport size_t
 from libc.stdint cimport uintptr_t
+from libc.string cimport memset as c_memset
 
 from cuda.bindings cimport cydriver
 
-from cuda.core._event cimport Event
+from cuda.core._event cimport Event, Event_check_open
+from cuda.core._kernel_arg_handler cimport ParamHolder
 from cuda.core._launch_config cimport LaunchConfig
+from cuda.core._memory._buffer cimport Buffer
 from cuda.core._module cimport Kernel
-from cuda.core.graph._graph_definition cimport GraphCondition, GraphDefinition
-from cuda.core.graph._graph_node cimport GraphNode
+from cuda.core.graph._graph_definition cimport (
+    GraphCondition,
+    GraphDefinition,
+    GD_check_valid,
+)
+from cuda.core.graph._graph_node cimport (
+    GraphNode,
+    GN_check_valid,
+    _get_memcpy_memory_type,
+    _init_memcpy_params,
+    _resolve_memcpy_operand,
+)
 from cuda.core._resource_handles cimport (
     EventHandle,
+    GraphExecHandle,
     GraphHandle,
-    KernelHandle,
     GraphNodeHandle,
+    KernelHandle,
+    OpaqueHandle,
+    PreparedAttachment,
+    PreparedChildGraphUpdate,
+    PreparedExecAttachment,
     as_cu,
     as_intptr,
-    create_event_handle_ref,
     create_child_graph_handle,
+    create_event_handle_ref,
     create_kernel_handle_ref,
+    graph_commit_attachment,
+    graph_commit_child_graph_update,
+    graph_commit_exec_attachment,
+    graph_get_attachment,
     graph_node_get_graph,
+    graph_prepare_attachment,
+    graph_prepare_child_graph_update,
+    graph_prepare_exec_attachment,
+    make_opaque_py,
 )
-from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
+from cuda.core._utils.cuda_utils cimport HANDLE_RETURN, _parse_fill_value
+from cuda.core._utils.version cimport cy_binding_version, cy_driver_version
 
-from cuda.core.graph._host_callback cimport _is_py_host_trampoline
+from cuda.core.graph._host_callback cimport (
+    _is_py_host_trampoline,
+    _resolve_host_callback,
+)
 
 from cuda.core._utils.cuda_utils import driver, handle_return
 from cuda.core.typing import GraphConditionalType
@@ -42,6 +72,14 @@ __all__ = [
     'EmptyNode',
     'EventRecordNode',
     'EventWaitNode',
+    'ExecutableChildGraphNode',
+    'ExecutableEventRecordNode',
+    'ExecutableEventWaitNode',
+    'ExecutableGraphNode',
+    'ExecutableHostCallbackNode',
+    'ExecutableKernelNode',
+    'ExecutableMemcpyNode',
+    'ExecutableMemsetNode',
     'FreeNode',
     'HostCallbackNode',
     'IfElseNode',
@@ -57,6 +95,120 @@ __all__ = [
 cdef bint _has_cuGraphNodeGetParams = False
 cdef bint _version_checked = False
 
+
+cdef void _require_graph_node_update_support() except *:
+    cdef tuple version = cy_driver_version()
+    if version < (12, 2, 0):
+        raise RuntimeError(
+            "Graph node mutation requires CUDA driver 12.2 or newer; "
+            f"using driver version {'.'.join(map(str, version))}"
+        )
+    version = cy_binding_version()
+    if version < (12, 2, 0):
+        raise RuntimeError(
+            "Graph node mutation requires cuda.bindings 12.2 or newer; "
+            f"using cuda.bindings version {'.'.join(map(str, version))}"
+        )
+
+
+cdef void _set_definition_node_params(
+        const GraphNodeHandle& h_node,
+        cydriver.CUgraphNodeParams* params,
+        OpaqueHandle owner0,
+        OpaqueHandle owner1=OpaqueHandle(),
+        cydriver.CUcontext update_ctx=NULL) except *:
+    cdef GraphHandle h_graph = graph_node_get_graph(h_node)
+    cdef cydriver.CUgraphNode node = as_cu(h_node)
+    if as_cu(h_graph) == NULL:
+        raise RuntimeError("GraphDefinition is no longer valid")
+    if node == NULL:
+        raise RuntimeError("GraphNode has been destroyed")
+    _require_graph_node_update_support()
+    cdef cydriver.CUcontext previous_ctx = NULL
+    cdef bint restore_ctx = False
+    cdef PreparedAttachment prepared
+
+    HANDLE_RETURN(graph_prepare_attachment(
+        h_graph, owner0, owner1, &prepared))
+    if update_ctx != NULL:
+        with nogil:
+            HANDLE_RETURN(cydriver.cuCtxGetCurrent(&previous_ctx))
+            if previous_ctx != update_ctx:
+                HANDLE_RETURN(cydriver.cuCtxSetCurrent(update_ctx))
+                restore_ctx = True
+    try:
+        with nogil:
+            HANDLE_RETURN(cydriver.cuGraphNodeSetParams(node, params))
+    finally:
+        if restore_ctx:
+            with nogil:
+                HANDLE_RETURN(cydriver.cuCtxSetCurrent(previous_ctx))
+    HANDLE_RETURN(graph_commit_attachment(prepared, node))
+
+
+cdef void _set_executable_node_params(
+        const GraphExecHandle& h_exec,
+        const GraphNodeHandle& h_node,
+        cydriver.CUgraphNodeParams* params,
+        OpaqueHandle owner0=OpaqueHandle(),
+        OpaqueHandle owner1=OpaqueHandle()) except *:
+    _require_graph_node_update_support()
+
+    cdef cydriver.CUgraphExec graph_exec = as_cu(h_exec)
+    cdef cydriver.CUgraphNode node = as_cu(h_node)
+    if graph_exec == NULL:
+        raise RuntimeError("Graph has been closed")
+    if node == NULL:
+        raise RuntimeError("GraphNode has been destroyed")
+
+    cdef PreparedExecAttachment prepared
+    HANDLE_RETURN(graph_prepare_exec_attachment(
+        h_exec, owner0, owner1, &prepared))
+
+    cdef cydriver.CUresult status
+    with nogil:
+        status = cydriver.cuGraphExecNodeSetParams(
+            graph_exec, node, params)
+    if status == cydriver.CUDA_SUCCESS:
+        graph_commit_exec_attachment(prepared)
+    HANDLE_RETURN(status)
+
+
+cdef bint _get_executable_node_enabled(
+        const GraphExecHandle& h_exec,
+        const GraphNodeHandle& h_node) except *:
+    _require_graph_node_update_support()
+
+    cdef cydriver.CUgraphExec graph_exec = as_cu(h_exec)
+    cdef cydriver.CUgraphNode node = as_cu(h_node)
+    cdef unsigned int enabled
+    if graph_exec == NULL:
+        raise RuntimeError("Graph has been closed")
+    if node == NULL:
+        raise RuntimeError("GraphNode has been destroyed")
+    with nogil:
+        HANDLE_RETURN(cydriver.cuGraphNodeGetEnabled(
+            graph_exec, node, &enabled))
+    return enabled != 0
+
+
+cdef void _set_executable_node_enabled(
+        const GraphExecHandle& h_exec,
+        const GraphNodeHandle& h_node,
+        bint enabled) except *:
+    _require_graph_node_update_support()
+
+    cdef cydriver.CUgraphExec graph_exec = as_cu(h_exec)
+    cdef cydriver.CUgraphNode node = as_cu(h_node)
+    if graph_exec == NULL:
+        raise RuntimeError("Graph has been closed")
+    if node == NULL:
+        raise RuntimeError("GraphNode has been destroyed")
+    with nogil:
+        HANDLE_RETURN(cydriver.cuGraphNodeSetEnabled(
+            graph_exec, node, <unsigned int>enabled))
+
+
 cdef bint _check_node_get_params():
     global _has_cuGraphNodeGetParams, _version_checked
     if not _version_checked:
@@ -68,6 +220,54 @@ cdef bint _check_node_get_params():
     return _has_cuGraphNodeGetParams
 
 
+cdef void _reject_unsupported_kernel_node(
+        cydriver.CUgraphNode node) except *:
+    cdef cydriver.CUkernelNodeAttrValue cluster
+    cdef cydriver.CUkernelNodeAttrValue cooperative
+
+    c_memset(&cluster, 0, sizeof(cluster))
+    c_memset(&cooperative, 0, sizeof(cooperative))
+    with nogil:
+        HANDLE_RETURN(cydriver.cuGraphKernelNodeGetAttribute(
+            node, <cydriver.CUkernelNodeAttrID>(
+                cydriver.CU_KERNEL_NODE_ATTRIBUTE_CLUSTER_DIMENSION),
+            &cluster))
+        HANDLE_RETURN(cydriver.cuGraphKernelNodeGetAttribute(
+            node, <cydriver.CUkernelNodeAttrID>(
+                cydriver.CU_KERNEL_NODE_ATTRIBUTE_COOPERATIVE),
+            &cooperative))
+    if (cluster.clusterDim.x != 0 or cluster.clusterDim.y != 0 or
+            cluster.clusterDim.z != 0 or cooperative.cooperative != 0):
+        raise NotImplementedError(
+            "updating clustered or cooperative kernel nodes is not supported")
+
+
+cdef bint _is_supported_memcpy_descriptor(
+        cydriver.CUDA_MEMCPY3D* params) noexcept nogil:
+    return (
+        (params.srcMemoryType == cydriver.CU_MEMORYTYPE_HOST or
+         params.srcMemoryType == cydriver.CU_MEMORYTYPE_DEVICE)
+        and (params.dstMemoryType == cydriver.CU_MEMORYTYPE_HOST or
+             params.dstMemoryType == cydriver.CU_MEMORYTYPE_DEVICE)
+        and params.srcXInBytes == 0
+        and params.srcY == 0
+        and params.srcZ == 0
+        and params.srcLOD == 0
+        and params.srcPitch == 0
+        and params.srcHeight == 0
+        and params.dstXInBytes == 0
+        and params.dstY == 0
+        and params.dstZ == 0
+        and params.dstLOD == 0
+        and params.dstPitch == 0
+        and params.dstHeight == 0
+        and params.Height == 1
+        and params.Depth == 1
+        and params.reserved0 == NULL
+        and params.reserved1 == NULL
+    )
+
+
 cdef class EmptyNode(GraphNode):
     """An empty (synchronization) node."""
 
@@ -130,6 +330,100 @@ cdef class KernelNode(GraphNode):
         return (f"<KernelNode handle=0x{as_intptr(self._h_node):x}"
                 f" kernel=0x{as_intptr(self._h_kernel):x}>")
 
+    def update(
+        self,
+        *,
+        config: LaunchConfig | None = None,
+        kernel: Kernel | None = None,
+        args=None,
+    ) -> None:
+        """Replace selected kernel launch parameters.
+
+        Omitted parameters preserve their current values. Changing ``kernel``
+        requires ``args``, including ``args=()`` for a no-argument kernel.
+        Clustered and cooperative kernel nodes are not supported.
+
+        .. warning::
+
+            Use caution when a retained kernel argument directly or indirectly
+            owns a graph. Any reference cycle involving the argument and a
+            graph that retains it cannot be broken by Python's cyclic garbage
+            collector. Use a weak reference to break such cycles.
+        """
+        GN_check_valid(self)
+        cdef LaunchConfig c_config
+        cdef Kernel c_kernel
+        cdef ParamHolder arg_holder
+        cdef object kernel_args
+        cdef KernelHandle h_kernel = self._h_kernel
+        cdef OpaqueHandle kernel_owner
+        cdef OpaqueHandle args_owner
+        cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
+        cdef cydriver.CUgraphNode node = as_cu(self._h_node)
+        cdef cydriver.CUgraphNodeParams params
+
+        if config is not None:
+            c_config = config
+            if (c_config.cluster is not None or
+                    c_config.is_cooperative):
+                raise NotImplementedError(
+                    "updating clustered or cooperative kernel nodes is not "
+                    "supported")
+        _require_graph_node_update_support()
+        _reject_unsupported_kernel_node(node)
+        if kernel is not None:
+            if args is None:
+                raise ValueError("changing kernel requires args")
+            c_kernel = kernel
+            h_kernel = c_kernel._h_kernel
+        if args is not None:
+            arg_holder = ParamHolder(args)
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_KERNEL
+        with nogil:
+            HANDLE_RETURN(cydriver.cuGraphKernelNodeGetParams(
+                node, <cydriver.CUDA_KERNEL_NODE_PARAMS*>&params.kernel))
+        HANDLE_RETURN(graph_get_attachment(
+            h_graph, node, &kernel_owner, &args_owner))
+
+        if config is not None:
+            params.kernel.gridDimX = c_config.grid[0]
+            params.kernel.gridDimY = c_config.grid[1]
+            params.kernel.gridDimZ = c_config.grid[2]
+            params.kernel.blockDimX = c_config.block[0]
+            params.kernel.blockDimY = c_config.block[1]
+            params.kernel.blockDimZ = c_config.block[2]
+            params.kernel.sharedMemBytes = c_config.shmem_size
+        if kernel is not None:
+            params.kernel.kern = as_cu(h_kernel)
+            params.kernel.func = <cydriver.CUfunction>NULL
+            params.kernel.ctx = <cydriver.CUcontext>NULL
+            kernel_owner = h_kernel
+        if args is not None:
+            params.kernel.kernelParams = <void**><uintptr_t>arg_holder.ptr
+            params.kernel.extra = NULL
+            kernel_args = arg_holder.kernel_args
+            if kernel_args is None:
+                args_owner = OpaqueHandle()
+            else:
+                args_owner = make_opaque_py(kernel_args)
+
+        _set_definition_node_params(
+            self._h_node, &params, kernel_owner, args_owner)
+        self._grid = (
+            params.kernel.gridDimX,
+            params.kernel.gridDimY,
+            params.kernel.gridDimZ,
+        )
+        self._block = (
+            params.kernel.blockDimX,
+            params.kernel.blockDimY,
+            params.kernel.blockDimZ,
+        )
+        self._shmem_size = params.kernel.sharedMemBytes
+        self._h_kernel = h_kernel
+
     @property
     def grid(self) -> tuple[int, int, int]:
         """Grid dimensions as a 3-tuple (gridDimX, gridDimY, gridDimZ)."""
@@ -340,6 +634,103 @@ cdef class MemsetNode(GraphNode):
         return (f"<MemsetNode handle=0x{as_intptr(self._h_node):x}"
                 f" dptr=0x{self._dptr:x} value={self._value}>")
 
+    def update(
+        self,
+        *,
+        dst: Buffer | int | None = None,
+        value=None,
+        width: int | None = None,
+        height: int | None = None,
+        pitch: int | None = None,
+        dst_owner=None,
+    ) -> None:
+        """Replace selected memset parameters.
+
+        Omitted parameters preserve their current values. ``dst_owner`` may
+        only accompany a raw-address ``dst``.
+
+        With CUDA 12.2 through 13.1, the node's intended CUDA context must be
+        current when this method is called. CUDA driver and ``cuda.bindings``
+        versions 13.2 and newer preserve the recorded context automatically.
+
+        .. warning::
+
+            Use caution when a retained operand owner directly or indirectly
+            owns a graph. Any reference cycle involving the owner and a graph
+            that retains it cannot be broken by Python's cyclic garbage
+            collector. Use a weak reference to break such cycles.
+        """
+        cdef OpaqueHandle dst_attachment_owner
+        GN_check_valid(self)
+        cdef GraphHandle h_graph
+        cdef cydriver.CUgraphNode node = as_cu(self._h_node)
+        cdef cydriver.CUcontext ctx = NULL
+        cdef cydriver.CUDA_MEMSET_NODE_PARAMS current
+        cdef cydriver.CUgraphNodeParams params
+        cdef object queried
+
+        if dst is None and dst_owner is not None:
+            raise ValueError("dst_owner requires dst")
+        if (dst is None and value is None and width is None and
+                height is None and pitch is None):
+            return
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_MEMSET
+        with nogil:
+            HANDLE_RETURN(cydriver.cuGraphMemsetNodeGetParams(
+                node, &current))
+        if _check_node_get_params():
+            queried = handle_return(driver.cuGraphNodeGetParams(
+                <uintptr_t>node))
+            ctx = <cydriver.CUcontext><uintptr_t>int(queried.memset.ctx)
+        else:
+            with nogil:
+                HANDLE_RETURN(cydriver.cuCtxGetCurrent(&ctx))
+
+        cdef cydriver.CUdeviceptr c_dst = current.dst
+        cdef unsigned int c_value = current.value
+        cdef unsigned int c_element_size = current.elementSize
+        cdef size_t c_width = current.width
+        cdef size_t c_height = current.height
+        cdef size_t c_pitch = current.pitch
+
+        if dst is None:
+            h_graph = graph_node_get_graph(self._h_node)
+            HANDLE_RETURN(graph_get_attachment(
+                h_graph, node,
+                &dst_attachment_owner, NULL))
+        else:
+            dst_attachment_owner = _resolve_memcpy_operand(
+                dst, dst_owner, "dst", &c_dst)
+
+        if value is not None:
+            c_value, c_element_size = _parse_fill_value(value)
+        if width is not None:
+            c_width = width
+        if height is not None:
+            c_height = height
+        if pitch is not None:
+            c_pitch = pitch
+
+        params.memset.dst = c_dst
+        params.memset.value = c_value
+        params.memset.elementSize = c_element_size
+        params.memset.width = c_width
+        params.memset.height = c_height
+        params.memset.pitch = c_pitch
+        params.memset.ctx = ctx
+
+        _set_definition_node_params(
+            self._h_node, &params, dst_attachment_owner,
+            OpaqueHandle(), params.memset.ctx)
+        self._dptr = c_dst
+        self._value = c_value
+        self._element_size = c_element_size
+        self._width = c_width
+        self._height = c_height
+        self._pitch = c_pitch
+
     @property
     def dptr(self) -> int:
         """The destination device pointer."""
@@ -428,6 +819,134 @@ cdef class MemcpyNode(GraphNode):
         return (f"<MemcpyNode handle=0x{as_intptr(self._h_node):x}"
                 f" dst=0x{self._dst:x}({dt}) src=0x{self._src:x}({st}) size={self._size}>")
 
+    def update(
+        self,
+        *,
+        dst: Buffer | int | None = None,
+        src: Buffer | int | None = None,
+        size: int | None = None,
+        dst_owner=None,
+        src_owner=None,
+    ) -> None:
+        """Replace selected memcpy parameters.
+
+        Omitted parameters preserve their current values. ``dst_owner`` and
+        ``src_owner`` may only accompany their corresponding raw addresses.
+        Multidimensional, pitched, offset, and array-backed memcpy nodes are
+        not supported.
+
+        With CUDA 12.2 through 13.1, the node's intended CUDA context must be
+        current when this method is called. CUDA driver and ``cuda.bindings``
+        versions 13.2 and newer preserve the recorded context automatically.
+
+        .. warning::
+
+            Use caution when a retained operand owner directly or indirectly
+            owns a graph. Any reference cycle involving the owner and a graph
+            that retains it cannot be broken by Python's cyclic garbage
+            collector. Use a weak reference to break such cycles.
+        """
+        cdef cydriver.CUdeviceptr c_dst = self._dst
+        cdef cydriver.CUdeviceptr c_src = self._src
+        cdef OpaqueHandle dst_attachment_owner
+        cdef OpaqueHandle src_attachment_owner
+        GN_check_valid(self)
+        cdef GraphHandle h_graph = graph_node_get_graph(self._h_node)
+        cdef cydriver.CUgraphNode node = as_cu(self._h_node)
+        cdef cydriver.CUcontext ctx = NULL
+        cdef cydriver.CUgraphNodeParams params
+        cdef cydriver.CUmemorytype c_dst_type
+        cdef cydriver.CUmemorytype c_src_type
+        cdef object queried
+
+        if dst is None and dst_owner is not None:
+            raise ValueError("dst_owner requires dst")
+        if src is None and src_owner is not None:
+            raise ValueError("src_owner requires src")
+        if dst is None and src is None and size is None:
+            return
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_MEMCPY
+        with nogil:
+            HANDLE_RETURN(cydriver.cuGraphMemcpyNodeGetParams(
+                node, &params.memcpy.copyParams))
+        if _check_node_get_params():
+            queried = handle_return(driver.cuGraphNodeGetParams(
+                <uintptr_t>node))
+            ctx = <cydriver.CUcontext><uintptr_t>int(
+                queried.memcpy.copyCtx)
+        else:
+            with nogil:
+                HANDLE_RETURN(cydriver.cuCtxGetCurrent(&ctx))
+        params.memcpy.copyCtx = ctx
+
+        if not _is_supported_memcpy_descriptor(&params.memcpy.copyParams):
+            raise NotImplementedError(
+                "updating multidimensional, pitched, offset, or array-backed "
+                "memcpy nodes is not supported")
+
+        c_dst_type = params.memcpy.copyParams.dstMemoryType
+        c_src_type = params.memcpy.copyParams.srcMemoryType
+        if c_dst_type == cydriver.CU_MEMORYTYPE_HOST:
+            c_dst = <cydriver.CUdeviceptr><uintptr_t>(
+                params.memcpy.copyParams.dstHost)
+        elif c_dst_type == cydriver.CU_MEMORYTYPE_DEVICE:
+            c_dst = params.memcpy.copyParams.dstDevice
+        else:
+            raise NotImplementedError(
+                f"unsupported destination memory type: {int(c_dst_type)}")
+        if c_src_type == cydriver.CU_MEMORYTYPE_HOST:
+            c_src = <cydriver.CUdeviceptr><uintptr_t>(
+                params.memcpy.copyParams.srcHost)
+        elif c_src_type == cydriver.CU_MEMORYTYPE_DEVICE:
+            c_src = params.memcpy.copyParams.srcDevice
+        else:
+            raise NotImplementedError(
+                f"unsupported source memory type: {int(c_src_type)}")
+
+        HANDLE_RETURN(graph_get_attachment(
+            h_graph, node,
+            &dst_attachment_owner, &src_attachment_owner))
+        if dst is not None:
+            dst_attachment_owner = _resolve_memcpy_operand(
+                dst, dst_owner, "dst", &c_dst)
+            c_dst_type = _get_memcpy_memory_type(c_dst)
+            params.memcpy.copyParams.dstMemoryType = c_dst_type
+            params.memcpy.copyParams.dstHost = NULL
+            params.memcpy.copyParams.dstDevice = 0
+            params.memcpy.copyParams.dstArray = NULL
+            params.memcpy.copyParams.reserved1 = NULL
+            if c_dst_type == cydriver.CU_MEMORYTYPE_HOST:
+                params.memcpy.copyParams.dstHost = <void*><uintptr_t>c_dst
+            else:
+                params.memcpy.copyParams.dstDevice = c_dst
+        if src is not None:
+            src_attachment_owner = _resolve_memcpy_operand(
+                src, src_owner, "src", &c_src)
+            c_src_type = _get_memcpy_memory_type(c_src)
+            params.memcpy.copyParams.srcMemoryType = c_src_type
+            params.memcpy.copyParams.srcHost = NULL
+            params.memcpy.copyParams.srcDevice = 0
+            params.memcpy.copyParams.srcArray = NULL
+            params.memcpy.copyParams.reserved0 = NULL
+            if c_src_type == cydriver.CU_MEMORYTYPE_HOST:
+                params.memcpy.copyParams.srcHost = <void*><uintptr_t>c_src
+            else:
+                params.memcpy.copyParams.srcDevice = c_src
+        if size is not None:
+            params.memcpy.copyParams.WidthInBytes = size
+
+        _set_definition_node_params(
+            self._h_node, &params,
+            dst_attachment_owner, src_attachment_owner,
+            params.memcpy.copyCtx)
+        self._dst = c_dst
+        self._src = c_src
+        self._size = params.memcpy.copyParams.WidthInBytes
+        self._dst_type = c_dst_type
+        self._src_type = c_src_type
+
     @property
     def dst(self) -> int:
         """The destination pointer."""
@@ -478,6 +997,39 @@ cdef class ChildGraphNode(GraphNode):
         return (f"<ChildGraphNode handle=0x{as_intptr(self._h_node):x}"
                 f" child=0x{as_intptr(self._h_child_graph):x}>")
 
+    def update(self, child: GraphDefinition) -> None:
+        """Replace the embedded graph with a clone of ``child``.
+
+        ``child`` must belong to an independent graph hierarchy.
+        """
+        GN_check_valid(self)
+        GD_check_valid(child)
+        cdef GraphHandle h_parent = graph_node_get_graph(self._h_node)
+        cdef GraphHandle h_replacement
+        cdef cydriver.CUgraphNode node = as_cu(self._h_node)
+        cdef cydriver.CUgraphNodeParams params
+        cdef cydriver.CUresult commit_status
+        cdef PreparedChildGraphUpdate prepared
+
+        _require_graph_node_update_support()
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_GRAPH
+        params.graph.graph = as_cu(child._h_graph)
+
+        HANDLE_RETURN(graph_prepare_child_graph_update(
+            h_parent, self._h_child_graph, node,
+            child._h_graph, &prepared))
+        with nogil:
+            HANDLE_RETURN(cydriver.cuGraphNodeSetParams(
+                node, &params))
+        try:
+            commit_status = graph_commit_child_graph_update(
+                prepared, &h_replacement)
+        finally:
+            if h_replacement:
+                self._h_child_graph = h_replacement
+        HANDLE_RETURN(commit_status)
+
     @property
     def child_graph(self) -> GraphDefinition:
         """The embedded graph definition (non-owning wrapper)."""
@@ -516,6 +1068,21 @@ cdef class EventRecordNode(GraphNode):
         return (f"<EventRecordNode handle=0x{as_intptr(self._h_node):x}"
                 f" event=0x{as_intptr(self._h_event):x}>")
 
+    def update(self, event: Event) -> None:
+        """Replace the event recorded by this node."""
+        GN_check_valid(self)
+        Event_check_open(event)
+        cdef OpaqueHandle event_owner = event._h_event
+        cdef cydriver.CUgraphNodeParams params
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_EVENT_RECORD
+        params.eventRecord.event = as_cu(event._h_event)
+
+        _set_definition_node_params(
+            self._h_node, &params, event_owner)
+        self._h_event = event._h_event
+
     @property
     def event(self) -> Event:
         """The event being recorded."""
@@ -554,6 +1121,21 @@ cdef class EventWaitNode(GraphNode):
         return (f"<EventWaitNode handle=0x{as_intptr(self._h_node):x}"
                 f" event=0x{as_intptr(self._h_event):x}>")
 
+    def update(self, event: Event) -> None:
+        """Replace the event waited on by this node."""
+        GN_check_valid(self)
+        Event_check_open(event)
+        cdef OpaqueHandle event_owner = event._h_event
+        cdef cydriver.CUgraphNodeParams params
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_WAIT_EVENT
+        params.eventWait.event = as_cu(event._h_event)
+
+        _set_definition_node_params(
+            self._h_node, &params, event_owner)
+        self._h_event = event._h_event
+
     @property
     def event(self) -> Event:
         """The event being waited on."""
@@ -604,6 +1186,43 @@ cdef class HostCallbackNode(GraphNode):
         return (f"<HostCallbackNode handle=0x{as_intptr(self._h_node):x}"
                 f" cfunc=0x{<uintptr_t>self._fn:x}>")
 
+    def update(self, fn, *, user_data=None) -> None:
+        """Replace the callback and user-data binding for this node.
+
+        ``fn`` accepts the same forms as :meth:`~graph.GraphNode.callback`: a
+        Python callable, or a ctypes function pointer whose declared prototype
+        matches ``CUhostFn`` (``void (*)(void*)``). A mismatched ctypes
+        prototype raises ``TypeError``.
+
+        .. warning::
+
+            Callbacks must not call CUDA API functions. Doing so may
+            deadlock or corrupt driver state.
+
+            Use caution when a Python callback retains an object that owns a
+            graph. Any reference cycle involving the callback and a graph that
+            retains it cannot be broken by Python's cyclic garbage collector.
+            Use a weak reference to break such cycles.
+        """
+        GN_check_valid(self)
+        cdef cydriver.CUhostFn c_fn
+        cdef void* c_user_data
+        cdef OpaqueHandle fn_owner, data_owner
+        cdef cydriver.CUgraphNodeParams params
+
+        _resolve_host_callback(
+            fn, user_data, &c_fn, &c_user_data, &fn_owner, &data_owner)
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_HOST
+        params.host.fn = c_fn
+        params.host.userData = c_user_data
+
+        _set_definition_node_params(
+            self._h_node, &params, fn_owner, data_owner)
+        self._callable = fn if _is_py_host_trampoline(c_fn) else None
+        self._fn = c_fn
+        self._user_data = c_user_data
+
     @property
     def callback(self):
         """The Python callable, or None for ctypes function pointer callbacks."""
@@ -765,3 +1384,305 @@ cdef class SwitchNode(ConditionalNode):
     def __repr__(self) -> str:
         return (f"<SwitchNode handle=0x{as_intptr(self._h_node):x}"
                 f" condition=0x{<unsigned long long>self._condition._c_handle:x}>")
+
+
+cdef class ExecutableGraphNode:
+    """A lightweight view pairing an executable graph with a source node.
+
+    Create executable-node views with ``graph[node]``. CUDA validates that the
+    node identifies a node in the executable graph when an operation is
+    performed.
+    """
+
+    def __init__(self):
+        raise RuntimeError(
+            "directly constructing an executable graph node is not supported")
+
+    def __repr__(self) -> str:
+        return (
+            f"<{type(self).__name__} graph=0x{as_intptr(self._h_graph_exec):x}"
+            f" node=0x{as_intptr(self._h_node):x}>"
+        )
+
+
+cdef class ExecutableKernelNode(ExecutableGraphNode):
+    """An executable kernel-node view."""
+
+    def update(
+        self,
+        *,
+        config: LaunchConfig,
+        kernel: Kernel,
+        args,
+    ) -> None:
+        """Replace all kernel launch parameters for future launches.
+
+        ``args`` must contain the complete argument sequence; use ``args=()``
+        for a no-argument kernel. Clustered and cooperative launch
+        configurations are not supported.
+        """
+        cdef LaunchConfig c_config = config
+        cdef Kernel c_kernel = kernel
+        cdef ParamHolder arg_holder
+        cdef object kernel_args
+        cdef OpaqueHandle kernel_owner = c_kernel._h_kernel
+        cdef OpaqueHandle args_owner
+        cdef cydriver.CUgraphNodeParams params
+
+        if c_config.cluster is not None or c_config.is_cooperative:
+            raise NotImplementedError(
+                "updating clustered or cooperative kernel nodes is not "
+                "supported")
+        arg_holder = ParamHolder(args)
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_KERNEL
+        params.kernel.kern = as_cu(c_kernel._h_kernel)
+        params.kernel.func = <cydriver.CUfunction>NULL
+        params.kernel.gridDimX = c_config.grid[0]
+        params.kernel.gridDimY = c_config.grid[1]
+        params.kernel.gridDimZ = c_config.grid[2]
+        params.kernel.blockDimX = c_config.block[0]
+        params.kernel.blockDimY = c_config.block[1]
+        params.kernel.blockDimZ = c_config.block[2]
+        params.kernel.sharedMemBytes = c_config.shmem_size
+        params.kernel.kernelParams = <void**><uintptr_t>arg_holder.ptr
+        params.kernel.extra = NULL
+        params.kernel.ctx = <cydriver.CUcontext>NULL
+
+        kernel_args = arg_holder.kernel_args
+        if kernel_args is not None:
+            args_owner = make_opaque_py(kernel_args)
+        _set_executable_node_params(
+            self._h_graph_exec, self._h_node, &params,
+            kernel_owner, args_owner)
+
+    @property
+    def is_enabled(self) -> bool:
+        """Whether this node is enabled in the executable graph."""
+        return _get_executable_node_enabled(
+            self._h_graph_exec, self._h_node)
+
+    def enable(self) -> None:
+        """Enable this node in the executable graph."""
+        _set_executable_node_enabled(
+            self._h_graph_exec, self._h_node, True)
+
+    def disable(self) -> None:
+        """Disable this node in the executable graph."""
+        _set_executable_node_enabled(
+            self._h_graph_exec, self._h_node, False)
+
+
+cdef class ExecutableMemsetNode(ExecutableGraphNode):
+    """An executable memset-node view."""
+
+    def update(
+        self,
+        *,
+        dst: Buffer | int,
+        value,
+        size_t width,
+        size_t height=1,
+        size_t pitch=0,
+    ) -> None:
+        """Replace all memset parameters for future launches."""
+        cdef cydriver.CUdeviceptr c_dst
+        cdef OpaqueHandle dst_owner = _resolve_memcpy_operand(
+            dst, None, "dst", &c_dst)
+        cdef unsigned int c_value
+        cdef unsigned int element_size
+        c_value, element_size = _parse_fill_value(value)
+
+        cdef cydriver.CUcontext ctx = NULL
+        cdef cydriver.CUgraphNodeParams params
+        with nogil:
+            HANDLE_RETURN(cydriver.cuCtxGetCurrent(&ctx))
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_MEMSET
+        params.memset.dst = c_dst
+        params.memset.value = c_value
+        params.memset.elementSize = element_size
+        params.memset.width = width
+        params.memset.height = height
+        params.memset.pitch = pitch
+        params.memset.ctx = ctx
+        _set_executable_node_params(
+            self._h_graph_exec, self._h_node, &params, dst_owner)
+
+    @property
+    def is_enabled(self) -> bool:
+        """Whether this node is enabled in the executable graph."""
+        return _get_executable_node_enabled(
+            self._h_graph_exec, self._h_node)
+
+    def enable(self) -> None:
+        """Enable this node in the executable graph."""
+        _set_executable_node_enabled(
+            self._h_graph_exec, self._h_node, True)
+
+    def disable(self) -> None:
+        """Disable this node in the executable graph."""
+        _set_executable_node_enabled(
+            self._h_graph_exec, self._h_node, False)
+
+
+cdef class ExecutableMemcpyNode(ExecutableGraphNode):
+    """An executable memcpy-node view."""
+
+    def update(
+        self,
+        *,
+        dst: Buffer | int,
+        src: Buffer | int,
+        size_t size,
+    ) -> None:
+        """Replace all one-dimensional memcpy parameters for future launches."""
+        cdef cydriver.CUdeviceptr c_dst
+        cdef cydriver.CUdeviceptr c_src
+        cdef OpaqueHandle dst_owner = _resolve_memcpy_operand(
+            dst, None, "dst", &c_dst)
+        cdef OpaqueHandle src_owner = _resolve_memcpy_operand(
+            src, None, "src", &c_src)
+        cdef cydriver.CUmemorytype dst_type
+        cdef cydriver.CUmemorytype src_type
+        cdef cydriver.CUcontext ctx = NULL
+        cdef cydriver.CUgraphNodeParams params
+
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_MEMCPY
+        _init_memcpy_params(
+            c_dst, c_src, size, &params.memcpy.copyParams,
+            &dst_type, &src_type)
+        with nogil:
+            HANDLE_RETURN(cydriver.cuCtxGetCurrent(&ctx))
+        params.memcpy.copyCtx = ctx
+        _set_executable_node_params(
+            self._h_graph_exec, self._h_node, &params,
+            dst_owner, src_owner)
+
+    @property
+    def is_enabled(self) -> bool:
+        """Whether this node is enabled in the executable graph."""
+        return _get_executable_node_enabled(
+            self._h_graph_exec, self._h_node)
+
+    def enable(self) -> None:
+        """Enable this node in the executable graph."""
+        _set_executable_node_enabled(
+            self._h_graph_exec, self._h_node, True)
+
+    def disable(self) -> None:
+        """Disable this node in the executable graph."""
+        _set_executable_node_enabled(
+            self._h_graph_exec, self._h_node, False)
+
+
+cdef class ExecutableChildGraphNode(ExecutableGraphNode):
+    """An executable child-graph-node view."""
+
+    def update(self, child: GraphDefinition) -> None:
+        """Replace the embedded graph parameters for future launches."""
+        GD_check_valid(child)
+        cdef cydriver.CUgraphNodeParams params
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_GRAPH
+        params.graph.graph = as_cu(child._h_graph)
+        _set_executable_node_params(
+            self._h_graph_exec, self._h_node, &params)
+
+
+cdef class ExecutableEventRecordNode(ExecutableGraphNode):
+    """An executable event-record-node view."""
+
+    def update(self, event: Event) -> None:
+        """Replace the event recorded by future launches."""
+        Event_check_open(event)
+        cdef OpaqueHandle event_owner = event._h_event
+        cdef cydriver.CUgraphNodeParams params
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_EVENT_RECORD
+        params.eventRecord.event = as_cu(event._h_event)
+        _set_executable_node_params(
+            self._h_graph_exec, self._h_node, &params, event_owner)
+
+
+cdef class ExecutableEventWaitNode(ExecutableGraphNode):
+    """An executable event-wait-node view."""
+
+    def update(self, event: Event) -> None:
+        """Replace the event waited on by future launches."""
+        Event_check_open(event)
+        cdef OpaqueHandle event_owner = event._h_event
+        cdef cydriver.CUgraphNodeParams params
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_WAIT_EVENT
+        params.eventWait.event = as_cu(event._h_event)
+        _set_executable_node_params(
+            self._h_graph_exec, self._h_node, &params, event_owner)
+
+
+cdef class ExecutableHostCallbackNode(ExecutableGraphNode):
+    """An executable host-callback-node view."""
+
+    def update(self, fn, *, user_data=None) -> None:
+        """Replace the callback and user-data binding for future launches.
+
+        ``fn`` may be a Python callable, or a ctypes function pointer whose
+        declared prototype matches ``CUhostFn`` (``void (*)(void*)``); a
+        mismatched prototype raises ``TypeError``.
+
+        .. warning::
+
+            Callbacks must not call CUDA API functions. Doing so may deadlock
+            or corrupt driver state.
+        """
+        cdef cydriver.CUhostFn c_fn
+        cdef void* c_user_data
+        cdef OpaqueHandle fn_owner
+        cdef OpaqueHandle data_owner
+        cdef cydriver.CUgraphNodeParams params
+
+        _resolve_host_callback(
+            fn, user_data, &c_fn, &c_user_data, &fn_owner, &data_owner)
+        c_memset(&params, 0, sizeof(params))
+        params.type = cydriver.CU_GRAPH_NODE_TYPE_HOST
+        params.host.fn = c_fn
+        params.host.userData = c_user_data
+        _set_executable_node_params(
+            self._h_graph_exec, self._h_node, &params,
+            fn_owner, data_owner)
+
+
+cdef ExecutableGraphNode create_executable_node_view(
+        const GraphExecHandle& h_exec,
+        GraphNode node):
+    cdef type view_type
+    if isinstance(node, KernelNode):
+        view_type = ExecutableKernelNode
+    elif isinstance(node, MemsetNode):
+        view_type = ExecutableMemsetNode
+    elif isinstance(node, MemcpyNode):
+        view_type = ExecutableMemcpyNode
+    elif isinstance(node, ChildGraphNode):
+        view_type = ExecutableChildGraphNode
+    elif isinstance(node, EventRecordNode):
+        view_type = ExecutableEventRecordNode
+    elif isinstance(node, EventWaitNode):
+        view_type = ExecutableEventWaitNode
+    elif isinstance(node, HostCallbackNode):
+        view_type = ExecutableHostCallbackNode
+    else:
+        raise TypeError(
+            f"{type(node).__name__} does not support executable updates")
+
+    if as_cu(h_exec) == NULL:
+        raise ValueError("executable graph has been closed")
+    if as_cu(node._h_node) == NULL:
+        raise ValueError("source graph node is no longer valid")
+
+    cdef ExecutableGraphNode view = view_type.__new__(view_type)
+    view._h_graph_exec = h_exec
+    view._h_node = node._h_node
+    return view
diff --git a/cuda_core/cuda/core/system/__init__.py b/cuda_core/cuda/core/system/__init__.py
index 685519f9b80..acb648549bc 100644
--- a/cuda_core/cuda/core/system/__init__.py
+++ b/cuda_core/cuda/core/system/__init__.py
@@ -12,8 +12,10 @@
 
 __all__ = [
     "CUDA_BINDINGS_NVML_IS_COMPATIBLE",
+    "get_driver_branch",
     "get_kernel_mode_driver_version",
     "get_num_devices",
+    "get_nvml_version",
     "get_process_name",
     "get_user_mode_driver_version",
 ]
@@ -40,7 +42,6 @@
     from .exceptions import *
     from .exceptions import __all__ as _exceptions_all
 
-    __all__.append("get_nvml_version")
     __all__.extend(_device_all)
     __all__.extend(_system_events_all)
     __all__.extend(_exceptions_all)
diff --git a/cuda_core/cuda/core/system/_device.pyi b/cuda_core/cuda/core/system/_device.pyi
index 4e0fa8cbb88..3e2a6bd018c 100644
--- a/cuda_core/cuda/core/system/_device.pyi
+++ b/cuda_core/cuda/core/system/_device.pyi
@@ -1,8 +1,6 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/system/_device.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/system/_device.pyx
 
-from __future__ import annotations
-
-from typing import Iterable
+from typing import Iterable, TypedDict
 
 import cuda.core
 from cuda.bindings import nvml
@@ -15,27 +13,58 @@ from cuda.core.system.typing import (AddressingMode, AffinityScope, ClockId,
                                      TemperatureThresholds, ThermalController,
                                      ThermalTarget)
 
+_CLOCK_ID_MAPPING = {ClockId.CURRENT: nvml.ClockId.CURRENT, ClockId.CUSTOMER_BOOST_MAX: nvml.ClockId.CUSTOMER_BOOST_MAX}
+_CLOCKS_EVENT_REASONS_MAPPING = {nvml.ClocksEventReasons.EVENT_REASON_NONE: ClocksEventReasons.NONE, nvml.ClocksEventReasons.EVENT_REASON_GPU_IDLE: ClocksEventReasons.GPU_IDLE, nvml.ClocksEventReasons.EVENT_REASON_APPLICATIONS_CLOCKS_SETTING: ClocksEventReasons.APPLICATIONS_CLOCKS_SETTING, nvml.ClocksEventReasons.EVENT_REASON_SW_POWER_CAP: ClocksEventReasons.SW_POWER_CAP, nvml.ClocksEventReasons.THROTTLE_REASON_HW_SLOWDOWN: ClocksEventReasons.HW_SLOWDOWN, nvml.ClocksEventReasons.EVENT_REASON_SYNC_BOOST: ClocksEventReasons.SYNC_BOOST, nvml.ClocksEventReasons.EVENT_REASON_SW_THERMAL_SLOWDOWN: ClocksEventReasons.SW_THERMAL_SLOWDOWN, nvml.ClocksEventReasons.THROTTLE_REASON_HW_THERMAL_SLOWDOWN: ClocksEventReasons.HW_THERMAL_SLOWDOWN, nvml.ClocksEventReasons.THROTTLE_REASON_HW_POWER_BRAKE_SLOWDOWN: ClocksEventReasons.HW_POWER_BRAKE_SLOWDOWN, nvml.ClocksEventReasons.EVENT_REASON_DISPLAY_CLOCK_SETTING: ClocksEventReasons.DISPLAY_CLOCK_SETTING, getattr(nvml.ClocksEventReasons, 'EVENT_REASON_BOARD_LIMIT', 512): ClocksEventReasons.BOARD_LIMIT, getattr(nvml.ClocksEventReasons, 'EVENT_REASON_RELIABILITY', 1024): ClocksEventReasons.RELIABILITY}
+_CLOCK_TYPE_MAPPING = {ClockType.GRAPHICS: nvml.ClockType.CLOCK_GRAPHICS, ClockType.SM: nvml.ClockType.CLOCK_SM, ClockType.MEMORY: nvml.ClockType.CLOCK_MEM, ClockType.VIDEO: nvml.ClockType.CLOCK_VIDEO}
+_COOLER_CONTROL_MAPPING = {nvml.CoolerControl.THERMAL_COOLER_SIGNAL_TOGGLE: CoolerControl.TOGGLE, nvml.CoolerControl.THERMAL_COOLER_SIGNAL_VARIABLE: CoolerControl.VARIABLE}
+_COOLER_TARGET_MAPPING = {nvml.CoolerTarget.THERMAL_NONE: CoolerTarget.NONE, nvml.CoolerTarget.THERMAL_GPU: CoolerTarget.GPU, nvml.CoolerTarget.THERMAL_MEMORY: CoolerTarget.MEMORY, nvml.CoolerTarget.THERMAL_POWER_SUPPLY: CoolerTarget.POWER_SUPPLY}
+_EVENT_TYPE_MAPPING = {nvml.EventType.NONE: EventType.NONE, nvml.EventType.SINGLE_BIT_ECC_ERROR: EventType.SINGLE_BIT_ECC_ERROR, nvml.EventType.DOUBLE_BIT_ECC_ERROR: EventType.DOUBLE_BIT_ECC_ERROR, nvml.EventType.PSTATE: EventType.PSTATE, nvml.EventType.XID_CRITICAL_ERROR: EventType.XID_CRITICAL_ERROR, nvml.EventType.CLOCK: EventType.CLOCK, nvml.EventType.POWER_SOURCE_CHANGE: EventType.POWER_SOURCE_CHANGE, nvml.EventType.MIG_CONFIG_CHANGE: EventType.MIG_CONFIG_CHANGE, nvml.EventType.SINGLE_BIT_ECC_ERROR_STORM: EventType.SINGLE_BIT_ECC_ERROR_STORM, nvml.EventType.DRAM_RETIREMENT_EVENT: EventType.DRAM_RETIREMENT_EVENT, nvml.EventType.DRAM_RETIREMENT_FAILURE: EventType.DRAM_RETIREMENT_FAILURE, nvml.EventType.NON_FATAL_POISON_ERROR: EventType.NON_FATAL_POISON_ERROR, nvml.EventType.FATAL_POISON_ERROR: EventType.FATAL_POISON_ERROR, nvml.EventType.GPU_UNAVAILABLE_ERROR: EventType.GPU_UNAVAILABLE_ERROR, nvml.EventType.GPU_RECOVERY_ACTION: EventType.GPU_RECOVERY_ACTION}
+_EVENT_TYPE_INV_MAPPING = {v: k for k, v in _EVENT_TYPE_MAPPING.items()}
+_FAN_CONTROL_POLICY_MAPPING = {nvml.FanControlPolicy.TEMPERATURE_CONTINUOUS_SW: FanControlPolicy.TEMPERATURE_CONTROLLED, nvml.FanControlPolicy.MANUAL: FanControlPolicy.MANUAL}
+_INFOROM_OBJECT_MAPPING = {InforomObject.OEM: nvml.InforomObject.INFOROM_OEM, InforomObject.ECC: nvml.InforomObject.INFOROM_ECC, InforomObject.POWER: nvml.InforomObject.INFOROM_POWER, InforomObject.DEN: nvml.InforomObject.INFOROM_DEN}
+_NVLINK_VERSION_MAPPING = {nvml.NvlinkVersion.VERSION_1_0: (1, 0), nvml.NvlinkVersion.VERSION_2_0: (2, 0), nvml.NvlinkVersion.VERSION_2_2: (2, 2), nvml.NvlinkVersion.VERSION_3_0: (3, 0), nvml.NvlinkVersion.VERSION_3_1: (3, 1), nvml.NvlinkVersion.VERSION_4_0: (4, 0), nvml.NvlinkVersion.VERSION_5_0: (5, 0)}
+_NVLINK_VERSION_6_0 = getattr(nvml.NvlinkVersion, 'VERSION_6_0', None)
+_TEMPERATURE_THRESHOLD_MAPPING = {TemperatureThresholds.SHUTDOWN: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_SHUTDOWN, TemperatureThresholds.SLOWDOWN: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_SLOWDOWN, TemperatureThresholds.MEM_MAX: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_MEM_MAX, TemperatureThresholds.GPU_MAX: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_GPU_MAX, TemperatureThresholds.ACOUSTIC_MIN: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_MIN, TemperatureThresholds.ACOUSTIC_CURR: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_CURR, TemperatureThresholds.ACOUSTIC_MAX: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_MAX, TemperatureThresholds.GPS_CURR: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_GPS_CURR}
+_THERMAL_CONTROLLER_MAPPING = {nvml.ThermalController.GPU_INTERNAL: ThermalController.GPU_INTERNAL, nvml.ThermalController.ADM1032: ThermalController.ADM1032, nvml.ThermalController.ADT7461: ThermalController.ADT7461, nvml.ThermalController.MAX6649: ThermalController.MAX6649, nvml.ThermalController.MAX1617: ThermalController.MAX1617, nvml.ThermalController.LM99: ThermalController.LM99, nvml.ThermalController.LM89: ThermalController.LM89, nvml.ThermalController.LM64: ThermalController.LM64, nvml.ThermalController.G781: ThermalController.G781, nvml.ThermalController.ADT7473: ThermalController.ADT7473, nvml.ThermalController.SBMAX6649: ThermalController.SBMAX6649, nvml.ThermalController.VBIOSEVT: ThermalController.VBIOSEVT, nvml.ThermalController.OS: ThermalController.OS, nvml.ThermalController.NVSYSCON_CANOAS: ThermalController.NVSYSCON_CANOAS, nvml.ThermalController.NVSYSCON_E551: ThermalController.NVSYSCON_E551, nvml.ThermalController.MAX6649R: ThermalController.MAX6649R, nvml.ThermalController.ADT7473S: ThermalController.ADT7473S, nvml.ThermalController.UNKNOWN: ThermalController.UNKNOWN}
+_THERMAL_TARGET_MAPPING = {nvml.ThermalTarget.NONE: ThermalTarget.NONE, nvml.ThermalTarget.GPU: ThermalTarget.GPU, nvml.ThermalTarget.MEMORY: ThermalTarget.MEMORY, nvml.ThermalTarget.POWER_SUPPLY: ThermalTarget.POWER_SUPPLY, nvml.ThermalTarget.BOARD: ThermalTarget.BOARD, nvml.ThermalTarget.VCD_BOARD: ThermalTarget.VCD_BOARD, nvml.ThermalTarget.VCD_INLET: ThermalTarget.VCD_INLET, nvml.ThermalTarget.VCD_OUTLET: ThermalTarget.VCD_OUTLET, nvml.ThermalTarget.ALL: ThermalTarget.ALL}
+_THERMAL_TARGET_INV_MAPPING = {v: k for k, v in _THERMAL_TARGET_MAPPING.items()}
+_ADDRESSING_MODE_MAPPING = {nvml.DeviceAddressingModeType.DEVICE_ADDRESSING_MODE_HMM: AddressingMode.HMM, nvml.DeviceAddressingModeType.DEVICE_ADDRESSING_MODE_ATS: AddressingMode.ATS}
+_AFFINITY_SCOPE_MAPPING = {AffinityScope.NODE: nvml.AffinityScope.NODE, AffinityScope.SOCKET: nvml.AffinityScope.SOCKET}
+_BRAND_TYPE_MAPPING = {nvml.BrandType.BRAND_UNKNOWN: 'Unknown', nvml.BrandType.BRAND_QUADRO: 'Quadro', nvml.BrandType.BRAND_TESLA: 'Tesla', nvml.BrandType.BRAND_NVS: 'NVS', nvml.BrandType.BRAND_GRID: 'GRID', nvml.BrandType.BRAND_GEFORCE: 'GeForce', nvml.BrandType.BRAND_TITAN: 'Titan', nvml.BrandType.BRAND_NVIDIA_VAPPS: 'NVIDIA vApps', nvml.BrandType.BRAND_NVIDIA_VPC: 'NVIDIA VPC', nvml.BrandType.BRAND_NVIDIA_VCS: 'NVIDIA VCS', nvml.BrandType.BRAND_NVIDIA_VWS: 'NVIDIA VWS', nvml.BrandType.BRAND_NVIDIA_CLOUD_GAMING: 'NVIDIA Cloud Gaming', nvml.BrandType.BRAND_NVIDIA_VGAMING: 'NVIDIA vGaming', nvml.BrandType.BRAND_QUADRO_RTX: 'Quadro RTX', nvml.BrandType.BRAND_NVIDIA_RTX: 'NVIDIA RTX', nvml.BrandType.BRAND_NVIDIA: 'NVIDIA', nvml.BrandType.BRAND_GEFORCE_RTX: 'GeForce RTX', nvml.BrandType.BRAND_TITAN_RTX: 'Titan RTX'}
+_GPU_P2P_CAPS_INDEX_MAPPING = {GpuP2PCapsIndex.READ: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_READ, GpuP2PCapsIndex.WRITE: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_WRITE, GpuP2PCapsIndex.NVLINK: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_NVLINK, GpuP2PCapsIndex.ATOMICS: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_ATOMICS, GpuP2PCapsIndex.PCI: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_PCI, GpuP2PCapsIndex.PROP: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_PROP, GpuP2PCapsIndex.UNKNOWN: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_UNKNOWN}
+_GPU_P2P_STATUS_MAPPING = {nvml.GpuP2PStatus.P2P_STATUS_OK: GpuP2PStatus.OK, nvml.GpuP2PStatus.P2P_STATUS_CHIPSET_NOT_SUPPORTED: GpuP2PStatus.CHIPSET_NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_GPU_NOT_SUPPORTED: GpuP2PStatus.GPU_NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_IOH_TOPOLOGY_NOT_SUPPORTED: GpuP2PStatus.IOH_TOPOLOGY_NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_DISABLED_BY_REGKEY: GpuP2PStatus.DISABLED_BY_REGKEY, nvml.GpuP2PStatus.P2P_STATUS_NOT_SUPPORTED: GpuP2PStatus.NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_UNKNOWN: GpuP2PStatus.UNKNOWN}
+_GPU_TOPOLOGY_LEVEL_MAPPING = {GpuTopologyLevel.INTERNAL: nvml.GpuTopologyLevel.TOPOLOGY_INTERNAL, GpuTopologyLevel.SINGLE: nvml.GpuTopologyLevel.TOPOLOGY_SINGLE, GpuTopologyLevel.MULTIPLE: nvml.GpuTopologyLevel.TOPOLOGY_MULTIPLE, GpuTopologyLevel.HOSTBRIDGE: nvml.GpuTopologyLevel.TOPOLOGY_HOSTBRIDGE, GpuTopologyLevel.NODE: nvml.GpuTopologyLevel.TOPOLOGY_NODE, GpuTopologyLevel.SYSTEM: nvml.GpuTopologyLevel.TOPOLOGY_SYSTEM}
+_GPU_TOPOLOGY_LEVEL_INV_MAPPING = {v: k for k, v in _GPU_TOPOLOGY_LEVEL_MAPPING.items()}
+__all__ = ['Device', 'get_p2p_status', 'get_topology_common_ancestor', 'NvlinkInfo']
+
+class _GpuDynamicPstatesUtilization(TypedDict):
+    bIsPresent: int
+    percentage: int
+    incThreshold: int
+    decThreshold: int
+
+class _ThermalSensor(TypedDict):
+    controller: int
+    defaultMinTemp: int
+    defaultMaxTemp: int
+    currentTemp: int
+    target: int
 
 class ClockOffsets:
     """
     Contains clock offset information.
     """
-
-    def __init__(self, clock_offset: nvml.ClockOffset):
-        ...
-
+    def __init__(self, clock_offset: nvml.ClockOffset): ...
     @property
     def clock_offset_mhz(self) -> int:
         """
         The current clock offset in MHz.
         """
-
     @property
     def max_offset_mhz(self) -> int:
         """
         The maximum clock offset in MHz.
         """
-
     @property
     def min_offset_mhz(self) -> int:
         """
@@ -46,11 +75,8 @@ class ClockInfo:
     """
     Accesses various clock information about a device.
     """
-
-    def __init__(self, handle: int, clock_type: ClockType | str):
-        ...
-
-    def get_current_mhz(self, clock_id: ClockId | str=...) -> int:
+    def __init__(self, handle: int, clock_type: ClockType | str): ...
+    def get_current_mhz(self, clock_id: ClockId | str=ClockId.CURRENT) -> int:
         """
         Get the current clock speed of a specific clock domain, in MHz.
 
@@ -66,7 +92,6 @@ class ClockInfo:
         int
             The clock speed in MHz.
         """
-
     def get_max_mhz(self) -> int:
         """
         Get the maximum clock speed of a specific clock domain, in MHz.
@@ -81,7 +106,6 @@ class ClockInfo:
         int
             The maximum clock speed in MHz.
         """
-
     def get_max_customer_boost_mhz(self) -> int:
         """
         Get the maximum customer boost clock speed of a specific clock, in MHz.
@@ -93,7 +117,6 @@ class ClockInfo:
         int
             The maximum customer boost clock speed in MHz.
         """
-
     def get_min_max_clock_of_pstate_mhz(self, pstate: int) -> tuple[int, int]:
         """
         Get the minimum and maximum clock speeds for this clock domain
@@ -111,7 +134,6 @@ class ClockInfo:
         tuple[int, int]
             A tuple containing the minimum and maximum clock speeds in MHz.
         """
-
     def get_offsets(self, pstate: int) -> ClockOffsets:
         """
         Retrieve min, max and current clock offset of some clock domain for a given Pstate.
@@ -132,10 +154,7 @@ class ClockInfo:
         """
 
 class CoolerInfo:
-
-    def __init__(self, cooler_info: nvml.CoolerInfo):
-        ...
-
+    def __init__(self, cooler_info: nvml.CoolerInfo): ...
     @property
     def signal_type(self) -> CoolerControl | None:
         """
@@ -143,7 +162,6 @@ class CoolerInfo:
 
         The possible types are variable and toggle.
         """
-
     @property
     def target(self) -> list[CoolerTarget]:
         """
@@ -157,58 +175,47 @@ class DeviceAttributes:
     """
     Various device attributes.
     """
-
-    def __init__(self, attributes: nvml.DeviceAttributes):
-        ...
-
+    def __init__(self, attributes: nvml.DeviceAttributes): ...
     @property
     def multiprocessor_count(self) -> int:
         """
         The streaming multiprocessor count
         """
-
     @property
     def shared_copy_engine_count(self) -> int:
         """
         The shared copy engine count
         """
-
     @property
     def shared_decoder_count(self) -> int:
         """
         The shared decoder engine count
         """
-
     @property
     def shared_encoder_count(self) -> int:
         """
         The shared encoder engine count
         """
-
     @property
     def shared_jpeg_count(self) -> int:
         """
         The shared JPEG engine count
         """
-
     @property
     def shared_ofa_count(self) -> int:
         """
         The shared optical flow accelerator (OFA) engine count
         """
-
     @property
     def gpu_instance_slice_count(self) -> int:
         """
         The GPU instance slice count
         """
-
     @property
     def compute_instance_slice_count(self) -> int:
         """
         The compute instance slice count
         """
-
     @property
     def memory_size_mb(self) -> int:
         """
@@ -219,22 +226,17 @@ class EventData:
     """
     Data about a single event.
     """
-
-    def __init__(self, event_data: nvml.EventData):
-        ...
-
+    def __init__(self, event_data: nvml.EventData): ...
     @property
     def device(self) -> Device:
         """
         The device on which the event occurred.
         """
-
     @property
     def event_type(self) -> EventType:
         """
         The type of event that was triggered.
         """
-
     @property
     def event_data(self) -> int:
         """
@@ -243,7 +245,6 @@ class EventData:
 
         Raises :class:`ValueError` for other event types.
         """
-
     @property
     def gpu_instance_id(self) -> int:
         """
@@ -253,7 +254,6 @@ class EventData:
 
         Raises :class:`ValueError` for other event types.
         """
-
     @property
     def compute_instance_id(self) -> int:
         """
@@ -268,13 +268,8 @@ class DeviceEvents:
     """
     Represents a set of events that can be waited on for a specific device.
     """
-
-    def __init__(self, device_handle: int, events: EventType | str | list[EventType | str]):
-        ...
-
-    def __dealloc__(self) -> None:
-        ...
-
+    def __init__(self, device_handle: int, events: EventType | str | list[EventType | str]): ...
+    def __dealloc__(self) -> None: ...
     def wait(self, timeout_ms: int=0) -> EventData:
         """
         Wait for events in the event set.
@@ -322,10 +317,7 @@ class FanInfo:
     """
     Manages information related to a specific fan on a specific device.
     """
-
-    def __init__(self, handle: int, fan: int):
-        ...
-
+    def __init__(self, handle: int, fan: int): ...
     @property
     def speed(self) -> int:
         """
@@ -340,11 +332,8 @@ class FanInfo:
         The fan speed is expressed as a percentage of the product's maximum
         noise tolerance fan speed.  This value may exceed 100% in certain cases.
         """
-
     @speed.setter
-    def speed(self, speed: int) -> None:
-        ...
-
+    def speed(self, speed: int) -> None: ...
     @property
     def speed_rpm(self) -> int:
         """
@@ -359,7 +348,6 @@ class FanInfo:
         physically blocked and unable to spin, the output will not match the
         actual fan speed.
         """
-
     @property
     def target_speed(self) -> int:
         """
@@ -375,7 +363,6 @@ class FanInfo:
         The fan speed is expressed as a percentage of the product's maximum
         noise tolerance fan speed.  This value may exceed 100% in certain cases.
         """
-
     @property
     def min_max_speed(self) -> tuple[int, int]:
         """
@@ -388,7 +375,6 @@ class FanInfo:
         tuple[int, int]
             A tuple of (min_speed, max_speed)
         """
-
     @property
     def control_policy(self) -> FanControlPolicy:
         """
@@ -398,7 +384,6 @@ class FanInfo:
 
         For all CUDA-capable discrete products with fans.
         """
-
     def set_default_speed(self) -> None:
         """
         Set the speed of the fan control policy to default.
@@ -412,29 +397,23 @@ class FieldValue:
 
     Use :meth:`Device.get_field_values` to get multiple field values at once.
     """
-
-    def __init__(self, field_value: nvml.FieldValue):
-        ...
-
+    def __init__(self, field_value: nvml.FieldValue): ...
     @property
     def field_id(self) -> FieldId:
         """
         The field ID.
         """
-
     @property
     def scope_id(self) -> int:
         """
         The scope ID.
         """
-
     @property
     def timestamp(self) -> int:
         """
         The CPU timestamp (in microseconds since 1970) at which the value was
         sampled.
         """
-
     @property
     def latency_usec(self) -> int:
         """
@@ -442,7 +421,6 @@ class FieldValue:
         be averaged across several fields that are serviced by the same driver
         call.
         """
-
     @property
     def value(self) -> int | float:
         """
@@ -458,16 +436,9 @@ class FieldValues:
     """
     Container of multiple field values.
     """
-
-    def __init__(self, field_values: nvml.FieldValue):
-        ...
-
-    def __getitem__(self, idx: int) -> FieldValue:
-        ...
-
-    def __len__(self) -> int:
-        ...
-
+    def __init__(self, field_values: nvml.FieldValue): ...
+    def __getitem__(self, idx: int) -> FieldValue: ...
+    def __len__(self) -> int: ...
     def validate(self) -> None:
         """
         Validate that there are no issues in any of the contained field values.
@@ -479,7 +450,6 @@ class FieldValues:
         :class:`cuda.core.system.NvmlError`
             If any of the contained field values has an associated exception.
         """
-
     def get_all_values(self) -> list[int | float]:
         """
         Get all field values as a list.
@@ -499,10 +469,7 @@ class FieldValues:
         """
 
 class InforomInfo:
-
-    def __init__(self, device: Device):
-        ...
-
+    def __init__(self, device: Device): ...
     def get_version(self, inforom: InforomObject | str) -> str:
         """
         Retrieves the InfoROM version for a given InfoROM object.
@@ -522,7 +489,6 @@ class InforomInfo:
         str
             The InfoROM version.
         """
-
     @property
     def image_version(self) -> str:
         """
@@ -539,7 +505,6 @@ class InforomInfo:
         str
             The InfoROM image version.
         """
-
     @property
     def configuration_checksum(self) -> int:
         """
@@ -557,7 +522,6 @@ class InforomInfo:
         int
             The InfoROM checksum.
         """
-
     def validate(self) -> None:
         """
         Reads the InfoROM from the flash and verifies the checksums.
@@ -569,7 +533,6 @@ class InforomInfo:
         :class:`cuda.core.system.CorruptedInforomError`
             If the device's InfoROM is corrupted.
         """
-
     @property
     def bbx_flush_time(self) -> tuple[int, int]:
         """
@@ -584,7 +547,6 @@ class InforomInfo:
             - timestamp: The start timestamp of the last BBX flush
             - duration_us: The duration (in μs) of the last BBX flush
         """
-
     @property
     def board_part_number(self) -> str:
         """
@@ -595,28 +557,22 @@ class MemoryInfo:
     """
     Memory allocation information for a device.
     """
-
-    def __init__(self, memory_info: nvml.Memory_v2):
-        ...
-
+    def __init__(self, memory_info: nvml.Memory_v2): ...
     @property
     def free(self) -> int:
         """
         Unallocated device memory (in bytes)
         """
-
     @property
     def total(self) -> int:
         """
         Total physical device memory (in bytes)
         """
-
     @property
     def used(self) -> int:
         """
         Allocated device memory (in bytes)
         """
-
     @property
     def reserved(self) -> int:
         """
@@ -627,22 +583,17 @@ class BAR1MemoryInfo(MemoryInfo):
     """
     BAR1 Memory allocation information for a device.
     """
-
-    def __init__(self, memory_info: nvml.BAR1Memory):
-        ...
-
+    def __init__(self, memory_info: nvml.BAR1Memory): ...
     @property
     def free(self) -> int:
         """
         Unallocated BAR1 memory (in bytes)
         """
-
     @property
     def total(self) -> int:
         """
         Total BAR1 memory (in bytes)
         """
-
     @property
     def used(self) -> int:
         """
@@ -650,10 +601,7 @@ class BAR1MemoryInfo(MemoryInfo):
         """
 
 class MigInfo:
-
-    def __init__(self, device: Device):
-        ...
-
+    def __init__(self, device: Device): ...
     @property
     def is_mig_device(self) -> bool:
         """
@@ -666,7 +614,6 @@ class MigInfo:
 
         For Ampere™ or newer fully supported devices.
         """
-
     @property
     def mode(self) -> bool:
         """
@@ -682,7 +629,6 @@ class MigInfo:
         bool
             `True` if current MIG mode is enabled.
         """
-
     @mode.setter
     def mode(self, mode: bool) -> None:
         """
@@ -698,7 +644,6 @@ class MigInfo:
         mode: bool
             `True` to enable MIG mode, `False` to disable MIG mode.
         """
-
     @property
     def pending_mode(self) -> bool:
         """
@@ -716,7 +661,6 @@ class MigInfo:
         bool
             `True` if pending MIG mode is enabled.
         """
-
     @property
     def device_count(self) -> int:
         """
@@ -731,7 +675,6 @@ class MigInfo:
         int
             The number of MIG devices (compute instances) on this GPU.
         """
-
     @property
     def parent(self) -> Device:
         """
@@ -744,7 +687,6 @@ class MigInfo:
         Device
             The parent GPU device for this MIG device.
         """
-
     def get_device_by_index(self, index: int) -> Device:
         """
         Get MIG device for the given index under its parent device.
@@ -768,7 +710,6 @@ class MigInfo:
         Device
             The MIG device corresponding to the given index.
         """
-
     def get_all_devices(self) -> Iterable[Device]:
         """
         Get all MIG devices under its parent device.
@@ -788,7 +729,6 @@ class MigInfo:
         """
 
 class _NvlinkInfoMeta(type):
-
     @property
     def max_links(cls):
         """
@@ -807,10 +747,7 @@ class _NvlinkInfo:
     """
     Nvlink information for a device.
     """
-
-    def __init__(self, device: Device, link: int):
-        ...
-
+    def __init__(self, device: Device, link: int): ...
     @property
     def version(self) -> tuple[int, int]:
         """
@@ -823,7 +760,6 @@ class _NvlinkInfo:
         tuple[int, int]
             The Nvlink version as a tuple of (major, minor).
         """
-
     @property
     def state(self) -> bool:
         """
@@ -839,71 +775,58 @@ class _NvlinkInfo:
             `True` if the Nvlink is active.
         """
 
-class NvlinkInfo(_NvlinkInfo, metaclass=_NvlinkInfoMeta):
-    ...
+class NvlinkInfo(_NvlinkInfo, metaclass=_NvlinkInfoMeta): ...
 
 class PciInfo:
     """
     PCI information about a GPU device.
     """
-
-    def __init__(self, pci_info_ext: nvml.PciInfoExt_v1, handle: int):
-        ...
-
+    def __init__(self, pci_info_ext: nvml.PciInfoExt_v1, handle: int): ...
     @property
     def bus(self) -> int:
         """
         The bus on which the device resides, 0 to 255
         """
-
     @property
     def bus_id(self) -> str:
         """
         The tuple domain:bus:device.function PCI identifier string
         """
-
     @property
     def device(self) -> int:
         """
         The device's id on the bus, 0 to 31
         """
-
     @property
     def domain(self) -> int:
         """
         The PCI domain on which the device's bus resides, 0 to 0xffffffff
         """
-
     @property
     def vendor_id(self) -> int:
         """
         The PCI vendor id of the device
         """
-
     @property
     def device_id(self) -> int:
         """
         The PCI device id of the device
         """
-
     @property
     def subsystem_id(self) -> int:
         """
         The subsystem device ID
         """
-
     @property
     def base_class(self) -> int:
         """
         The 8-bit PCI base class code
         """
-
     @property
     def sub_class(self) -> int:
         """
         The 8-bit PCI sub class code
         """
-
     @property
     def link_generation(self) -> int:
         """
@@ -915,7 +838,6 @@ class PciInfo:
         PCIe bus, the max link generation this function will report is
         generation 1.
         """
-
     @property
     def max_link_generation(self) -> int:
         """
@@ -923,7 +845,6 @@ class PciInfo:
 
         For Fermi™ or newer fully supported devices.
         """
-
     @property
     def max_link_width(self) -> int:
         """
@@ -935,7 +856,6 @@ class PciInfo:
         PCIe system bus this function will report
         a max link width of 8.
         """
-
     @property
     def current_link_generation(self) -> int:
         """
@@ -943,7 +863,6 @@ class PciInfo:
 
         For Fermi™ or newer fully supported devices.
         """
-
     @property
     def current_link_width(self) -> int:
         """
@@ -951,7 +870,6 @@ class PciInfo:
 
         For Fermi™ or newer fully supported devices.
         """
-
     @property
     def rx_throughput(self) -> int:
         """
@@ -965,7 +883,6 @@ class PciInfo:
         This method is not supported in virtual machines running virtual GPU
         (vGPU).
         """
-
     @property
     def tx_throughput(self) -> int:
         """
@@ -979,7 +896,6 @@ class PciInfo:
         This method is not supported in virtual machines running virtual GPU
         (vGPU).
         """
-
     @property
     def replay_counter(self) -> int:
         """
@@ -989,28 +905,22 @@ class PciInfo:
         """
 
 class GpuDynamicPstatesUtilization:
-
-    def __init__(self, ptr: int, owner: object):
-        ...
-
+    def __init__(self, ptr: int, owner: object): ...
     @property
     def is_present(self) -> bool:
         """
         Set if the utilization domain is present on this GPU.
         """
-
     @property
     def percentage(self) -> int:
         """
         Percentage of time where the domain is considered busy in the last 1-second interval.
         """
-
     @property
     def inc_threshold(self) -> int:
         """
         Utilization threshold that can trigger a perf-increasing P-State change when crossed.
         """
-
     @property
     def dec_threshold(self) -> int:
         """
@@ -1021,36 +931,25 @@ class GpuDynamicPstatesInfo:
     """
     Handles performance monitor samples from the device.
     """
-
-    def __init__(self, gpu_dynamic_pstates_info: nvml.GpuDynamicPstatesInfo):
-        ...
-
-    def __len__(self) -> int:
-        ...
-
-    def __getitem__(self, idx: int) -> GpuDynamicPstatesUtilization:
-        ...
+    def __init__(self, gpu_dynamic_pstates_info: nvml.GpuDynamicPstatesInfo): ...
+    def __len__(self) -> int: ...
+    def __getitem__(self, idx: int) -> GpuDynamicPstatesUtilization: ...
 
 class ProcessInfo:
     """
     Information about running compute processes on the GPU.
     """
-
-    def __init__(self, device: 'Device', process_info: nvml.ProcessInfo):
-        ...
-
+    def __init__(self, device: Device, process_info: nvml.ProcessInfo): ...
     @property
     def pid(self) -> int:
         """
         The PID of the process.
         """
-
     @property
     def used_gpu_memory(self) -> int:
         """
         The amount of GPU memory (in bytes) used by the process.
         """
-
     @property
     def gpu_instance_id(self) -> int:
         """
@@ -1058,7 +957,6 @@ class ProcessInfo:
 
         Only valid for processes running on MIG devices.
         """
-
     @property
     def compute_instance_id(self) -> int:
         """
@@ -1071,16 +969,12 @@ class RepairStatus:
     """
     Repair status for TPC/Channel repair.
     """
-
-    def __init__(self, handle: int):
-        ...
-
+    def __init__(self, handle: int): ...
     @property
     def channel_repair_pending(self) -> bool:
         """
         `True` if a channel repair is pending.
         """
-
     @property
     def tpc_repair_pending(self) -> bool:
         """
@@ -1088,46 +982,25 @@ class RepairStatus:
         """
 
 class ThermalSensor:
-
-    def __init__(self, ptr: int, owner: object):
-        ...
-
+    def __init__(self, ptr: int, owner: object): ...
     @property
-    def controller(self) -> ThermalController:
-        ...
-
+    def controller(self) -> ThermalController: ...
     @property
-    def default_min_temp(self) -> int:
-        ...
-
+    def default_min_temp(self) -> int: ...
     @property
-    def default_max_temp(self) -> int:
-        ...
-
+    def default_max_temp(self) -> int: ...
     @property
-    def current_temp(self) -> int:
-        ...
-
+    def current_temp(self) -> int: ...
     @property
-    def target(self) -> ThermalTarget:
-        ...
+    def target(self) -> ThermalTarget: ...
 
 class ThermalSettings:
-
-    def __init__(self, thermal_settings: nvml.ThermalSettings):
-        ...
-
-    def __len__(self) -> int:
-        ...
-
-    def __getitem__(self, idx: int) -> nvml.ThermalSensor:
-        ...
+    def __init__(self, thermal_settings: nvml.ThermalSettings): ...
+    def __len__(self) -> int: ...
+    def __getitem__(self, idx: int) -> nvml.ThermalSensor: ...
 
 class Temperature:
-
-    def __init__(self, handle: int):
-        ...
-
+    def __init__(self, handle: int): ...
     def get_sensor(self) -> int:
         """
         Get the temperature reading from a specific sensor on the device, in
@@ -1140,7 +1013,6 @@ class Temperature:
         int
             The temperature in degrees Celsius.
         """
-
     def get_threshold(self, threshold_type: TemperatureThresholds | str) -> int:
         """
         Retrieves the temperature threshold for this GPU with the specified
@@ -1162,13 +1034,11 @@ class Temperature:
         use :meth:`get_field_values` with ``NVML_FI_DEV_TEMPERATURE_*`` fields
         to retrieve temperature thresholds on these architectures.
         """
-
     @property
     def margin(self) -> int:
         """
         The thermal margin temperature (distance to nearest slowdown threshold) for the device.
         """
-
     def get_thermal_settings(self, sensor_index: ThermalTarget | str) -> ThermalSettings:
         """
         Used to execute a list of thermal system instructions.
@@ -1190,16 +1060,12 @@ class Utilization:
 
     For devices with compute capability 2.0 or higher.
     """
-
-    def __init__(self, utilization: nvml.Utilization):
-        ...
-
+    def __init__(self, utilization: nvml.Utilization): ...
     @property
     def gpu(self) -> int:
         """
         Percent of time over the past sample period during which one or more kernels was executing on the GPU.
         """
-
     @property
     def memory(self) -> int:
         """
@@ -1240,9 +1106,7 @@ class Device:
     """
     _handle: int
 
-    def __init__(self, *, index: int | None=None, uuid: bytes | str | None=None, pci_bus_id: bytes | str | None=None) -> None:
-        ...
-
+    def __init__(self, *, index: int | None=None, uuid: bytes | str | None=None, pci_bus_id: bytes | str | None=None) -> None: ...
     @property
     def index(self) -> int:
         """
@@ -1260,7 +1124,6 @@ class Device:
         Note: The NVML index may not correlate with other APIs, such as the CUDA
         device index.
         """
-
     @property
     def uuid(self) -> str:
         """
@@ -1272,7 +1135,6 @@ class Device:
         prefix.  If you need a `uuid` without that prefix (for example, to
         interact with CUDA), use the `uuid_without_prefix` property.
         """
-
     @property
     def uuid_without_prefix(self) -> str:
         """
@@ -1284,13 +1146,11 @@ class Device:
         prefix.  This property returns it without the prefix, to match the UUIDs
         used in CUDA.  If you need the prefix, use the `uuid` property.
         """
-
     @property
     def pci_bus_id(self) -> str:
         """
         Retrieves the PCI bus ID of this device.
         """
-
     @property
     def numa_node_id(self) -> int:
         """
@@ -1298,7 +1158,6 @@ class Device:
 
         This only applies to platforms where the GPUs are NUMA nodes.
         """
-
     @property
     def arch(self) -> DeviceArch:
         """
@@ -1308,13 +1167,11 @@ class Device:
         "VOLTA"``, and RTX A6000 will report ``DeviceArchitecture.name ==
         "AMPERE"``.
         """
-
     @property
     def name(self) -> str:
         """
         Name of the device, e.g.: `"Tesla V100-SXM2-32GB"`
         """
-
     @property
     def brand(self) -> str:
         """
@@ -1322,7 +1179,6 @@ class Device:
 
         Returns "Unknown" if the brand is unknown.
         """
-
     @property
     def serial(self) -> str:
         """
@@ -1331,7 +1187,6 @@ class Device:
 
         For all products with an InfoROM.
         """
-
     @property
     def module_id(self) -> int:
         """
@@ -1341,7 +1196,6 @@ class Device:
         on a given baseboard.  For non-baseboard products, this ID would always
         be 0.
         """
-
     @property
     def minor_number(self) -> int:
         """
@@ -1352,13 +1206,11 @@ class Device:
         The minor number is used by the Linux device driver to identify the
         device node in ``/dev/nvidiaX``.
         """
-
     @property
     def is_c2c_enabled(self) -> bool:
         """
         Whether the C2C (Chip-to-Chip) mode is enabled for this device.
         """
-
     @property
     def is_persistence_mode_enabled(self) -> bool:
         """
@@ -1366,11 +1218,8 @@ class Device:
 
         For Linux only.
         """
-
     @is_persistence_mode_enabled.setter
-    def is_persistence_mode_enabled(self, enabled: bool) -> None:
-        ...
-
+    def is_persistence_mode_enabled(self, enabled: bool) -> None: ...
     @property
     def cuda_compute_capability(self) -> tuple[int, int]:
         """
@@ -1378,8 +1227,7 @@ class Device:
 
         Returns a tuple `(major, minor)`.
         """
-
-    def to_cuda_device(self) -> 'cuda.core.Device':
+    def to_cuda_device(self) -> cuda.core.Device:
         """
         Get the corresponding :class:`cuda.core.Device` (which is used for CUDA
         access) for this :class:`cuda.core.system.Device` (which is used for
@@ -1401,7 +1249,6 @@ class Device:
             available CUDA device, since it can not be used directly, even
             though it can be enumerated from NVML.
         """
-
     @classmethod
     def get_device_count(cls) -> int:
         """
@@ -1412,7 +1259,6 @@ class Device:
         int
             The number of available devices.
         """
-
     @classmethod
     def get_all_devices(cls) -> Iterable[Device]:
         """
@@ -1423,13 +1269,11 @@ class Device:
         Iterator over :obj:`~Device`
             An iterator over available devices.
         """
-
     @property
     def addressing_mode(self) -> AddressingMode | None:
         """
         Get the :obj:`~AddressingMode` of the device.
         """
-
     @property
     def mig(self) -> MigInfo:
         """
@@ -1437,7 +1281,6 @@ class Device:
 
         For Ampere™ or newer fully supported devices.
         """
-
     @classmethod
     def get_all_devices_with_cpu_affinity(cls, cpu_index: int) -> Iterable[Device]:
         """
@@ -1455,8 +1298,7 @@ class Device:
         Iterator of :obj:`~Device`
             An iterator over available devices.
         """
-
-    def get_memory_affinity(self, scope: AffinityScope | str=...) -> list[int]:
+    def get_memory_affinity(self, scope: AffinityScope | str=AffinityScope.NODE) -> list[int]:
         """
         Retrieves a list of indices of NUMA nodes or CPU sockets with the ideal
         memory affinity for the device.
@@ -1481,8 +1323,7 @@ class Device:
             A list of indices of NUMA nodes or CPU sockets with the ideal memory
             affinity for the device.
         """
-
-    def get_cpu_affinity(self, scope: AffinityScope | str=...) -> list[int]:
+    def get_cpu_affinity(self, scope: AffinityScope | str=AffinityScope.NODE) -> list[int]:
         """
         Retrieves a list of indices of NUMA nodes or CPU sockets with the ideal
         CPU affinity for the device.
@@ -1507,7 +1348,6 @@ class Device:
             A list of indices of NUMA nodes or CPU sockets with the ideal memory
             affinity for the device.
         """
-
     def set_cpu_affinity(self) -> None:
         """
         Sets the ideal affinity for the calling thread and device.
@@ -1516,7 +1356,6 @@ class Device:
 
         Supported on Linux only.
         """
-
     def clear_cpu_affinity(self) -> None:
         """
         Clear all affinity bindings for the calling thread.
@@ -1525,12 +1364,10 @@ class Device:
 
         Supported on Linux only.
         """
-
     def get_clock(self, clock_type: ClockType | str) -> ClockInfo:
         """
         :obj:`~_device.ClockInfo` object to get information about and manage a specific clock on a device.
         """
-
     @property
     def is_auto_boosted_clocks_enabled(self) -> tuple[bool, bool]:
         """
@@ -1554,7 +1391,6 @@ class Device:
             The default Auto Boosted clocks behavior
 
         """
-
     @property
     def current_clock_event_reasons(self) -> list[ClocksEventReasons]:
         """
@@ -1562,7 +1398,6 @@ class Device:
 
         For all fully supported products.
         """
-
     @property
     def supported_clock_event_reasons(self) -> list[ClocksEventReasons]:
         """
@@ -1573,13 +1408,11 @@ class Device:
 
         This method is not supported in virtual machines running virtual GPU (vGPU).
         """
-
     @property
     def cooler(self) -> CoolerInfo:
         """
         :obj:`~_device.CoolerInfo` object with cooler information for the device.
         """
-
     @property
     def attributes(self) -> DeviceAttributes:
         """
@@ -1588,7 +1421,6 @@ class Device:
         For Ampere™ or newer fully supported devices.  Only available on Linux
         systems.
         """
-
     @property
     def is_display_connected(self) -> bool:
         """
@@ -1597,7 +1429,6 @@ class Device:
         Indicates whether a physical display (e.g. monitor) is currently connected to
         any of the device's connectors.
         """
-
     @property
     def is_display_active(self) -> bool:
         """
@@ -1609,7 +1440,6 @@ class Device:
 
         Display can be active even when no monitor is physically attached.
         """
-
     def register_events(self, events: EventType | str | list[EventType | str]) -> DeviceEvents:
         """
         Starts recording events on this device.
@@ -1650,7 +1480,6 @@ class Device:
         :class:`cuda.core.system.NotSupportedError`
             None of the requested event types are registered.
         """
-
     def get_supported_event_types(self) -> list[EventType]:
         """
         Get the list of event types supported by this device.
@@ -1663,18 +1492,15 @@ class Device:
         list[EventType]
             The list of supported event types.
         """
-
     def get_fan(self, fan: int=0) -> FanInfo:
         """
         :obj:`~_device.FanInfo` object to get information and manage a specific fan on a device.
         """
-
     @property
     def num_fans(self) -> int:
         """
         The number of fans on the device.
         """
-
     def get_field_values(self, field_ids: list[int | tuple[int, int]]) -> FieldValues:
         """
         Get multiple field values from the device.
@@ -1699,7 +1525,6 @@ class Device:
         :obj:`~_device.FieldValues`
             Container of field values corresponding to the requested field IDs.
         """
-
     def clear_field_values(self, field_ids: list[int | tuple[int, int]]) -> None:
         """
         Clear multiple field values from the device.
@@ -1712,7 +1537,6 @@ class Device:
             Each item may be either a single value from the :class:`FieldId`
             enum, or a pair of (:class:`FieldId`, scope ID).
         """
-
     @property
     def inforom(self) -> InforomInfo:
         """
@@ -1720,7 +1544,6 @@ class Device:
 
         For all products with an InfoROM.
         """
-
     @property
     def bar1_memory_info(self) -> BAR1MemoryInfo:
         """
@@ -1730,13 +1553,11 @@ class Device:
         accessed by the CPU or by 3rd party devices (peer-to-peer on the PCIE
         bus).
         """
-
     @property
     def memory_info(self) -> MemoryInfo:
         """
         :obj:`~_device.MemoryInfo` object with memory information.
         """
-
     def get_nvlink(self, link: int) -> NvlinkInfo:
         """
         Get :obj:`~NvlinkInfo` about this device.
@@ -1746,7 +1567,6 @@ class Device:
         .. version-changed:: 1.1.0
             Any link number not supported by this specific device will raise a `ValueError`.
         """
-
     def get_nvlink_count(self) -> int:
         """
         Get the number of NVLink links on this device.
@@ -1755,7 +1575,6 @@ class Device:
 
         .. version-added:: 1.1.0
         """
-
     def get_nvlinks(self) -> Iterable[NvlinkInfo]:
         """
         Get :obj:`~NvlinkInfo` about all NVLink links on this device.
@@ -1764,7 +1583,6 @@ class Device:
 
         .. version-added:: 1.1.0
         """
-
     @property
     def pci_info(self) -> PciInfo:
         """
@@ -1773,7 +1591,6 @@ class Device:
         Non-physical devices, such as MIG devices, may not have PCI attributes.
         In that case, this property will raise a `RuntimeError`.
         """
-
     @property
     def performance_state(self) -> int | None:
         """
@@ -1788,13 +1605,11 @@ class Device:
             where 0 is maximum performance and higher numbers are lower performance.
             Returns `None` if the performance state is unknown.
         """
-
     @property
     def dynamic_pstates_info(self) -> GpuDynamicPstatesInfo:
         """
         :obj:`~_device.GpuDynamicPstatesInfo` object with performance monitor samples from the associated subdevice.
         """
-
     @property
     def supported_pstates(self) -> list[int]:
         """
@@ -1810,7 +1625,6 @@ class Device:
             between 0 and 15, where 0 is maximum performance and higher numbers
             are lower performance.
         """
-
     @property
     def compute_running_processes(self) -> list[ProcessInfo]:
         """
@@ -1832,7 +1646,6 @@ class Device:
         Querying per-instance information using MIG device handles is not
         supported if the device is in vGPU Host virtualization mode.
         """
-
     @property
     def repair_status(self) -> RepairStatus:
         """
@@ -1840,13 +1653,11 @@ class Device:
 
         For Ampere™ or newer fully supported devices.
         """
-
     @property
     def temperature(self) -> Temperature:
         """
         :obj:`~_device.Temperature` object with temperature information for the device.
         """
-
     def get_topology_nearest_gpus(self, level: GpuTopologyLevel | str) -> Iterable[Device]:
         """
         Retrieve the GPUs that are nearest to this device at a specific interconnectivity level.
@@ -1863,7 +1674,6 @@ class Device:
         Iterable of :class:`Device`
             The nearest devices at the given topology level.
         """
-
     @property
     def utilization(self) -> Utilization:
         """
@@ -1884,35 +1694,11 @@ class Device:
         Utilization
             An object containing the current utilization rates for the device.
         """
-_CLOCK_ID_MAPPING = {ClockId.CURRENT: nvml.ClockId.CURRENT, ClockId.CUSTOMER_BOOST_MAX: nvml.ClockId.CUSTOMER_BOOST_MAX}
-_CLOCKS_EVENT_REASONS_MAPPING = {nvml.ClocksEventReasons.EVENT_REASON_NONE: ClocksEventReasons.NONE, nvml.ClocksEventReasons.EVENT_REASON_GPU_IDLE: ClocksEventReasons.GPU_IDLE, nvml.ClocksEventReasons.EVENT_REASON_APPLICATIONS_CLOCKS_SETTING: ClocksEventReasons.APPLICATIONS_CLOCKS_SETTING, nvml.ClocksEventReasons.EVENT_REASON_SW_POWER_CAP: ClocksEventReasons.SW_POWER_CAP, nvml.ClocksEventReasons.THROTTLE_REASON_HW_SLOWDOWN: ClocksEventReasons.HW_SLOWDOWN, nvml.ClocksEventReasons.EVENT_REASON_SYNC_BOOST: ClocksEventReasons.SYNC_BOOST, nvml.ClocksEventReasons.EVENT_REASON_SW_THERMAL_SLOWDOWN: ClocksEventReasons.SW_THERMAL_SLOWDOWN, nvml.ClocksEventReasons.THROTTLE_REASON_HW_THERMAL_SLOWDOWN: ClocksEventReasons.HW_THERMAL_SLOWDOWN, nvml.ClocksEventReasons.THROTTLE_REASON_HW_POWER_BRAKE_SLOWDOWN: ClocksEventReasons.HW_POWER_BRAKE_SLOWDOWN, nvml.ClocksEventReasons.EVENT_REASON_DISPLAY_CLOCK_SETTING: ClocksEventReasons.DISPLAY_CLOCK_SETTING, getattr(nvml.ClocksEventReasons, 'EVENT_REASON_BOARD_LIMIT', 512): ClocksEventReasons.BOARD_LIMIT, getattr(nvml.ClocksEventReasons, 'EVENT_REASON_RELIABILITY', 1024): ClocksEventReasons.RELIABILITY}
-_CLOCK_TYPE_MAPPING = {ClockType.GRAPHICS: nvml.ClockType.CLOCK_GRAPHICS, ClockType.SM: nvml.ClockType.CLOCK_SM, ClockType.MEMORY: nvml.ClockType.CLOCK_MEM, ClockType.VIDEO: nvml.ClockType.CLOCK_VIDEO}
-_COOLER_CONTROL_MAPPING = {nvml.CoolerControl.THERMAL_COOLER_SIGNAL_TOGGLE: CoolerControl.TOGGLE, nvml.CoolerControl.THERMAL_COOLER_SIGNAL_VARIABLE: CoolerControl.VARIABLE}
-_COOLER_TARGET_MAPPING = {nvml.CoolerTarget.THERMAL_NONE: CoolerTarget.NONE, nvml.CoolerTarget.THERMAL_GPU: CoolerTarget.GPU, nvml.CoolerTarget.THERMAL_MEMORY: CoolerTarget.MEMORY, nvml.CoolerTarget.THERMAL_POWER_SUPPLY: CoolerTarget.POWER_SUPPLY}
-_EVENT_TYPE_MAPPING = {nvml.EventType.NONE: EventType.NONE, nvml.EventType.SINGLE_BIT_ECC_ERROR: EventType.SINGLE_BIT_ECC_ERROR, nvml.EventType.DOUBLE_BIT_ECC_ERROR: EventType.DOUBLE_BIT_ECC_ERROR, nvml.EventType.PSTATE: EventType.PSTATE, nvml.EventType.XID_CRITICAL_ERROR: EventType.XID_CRITICAL_ERROR, nvml.EventType.CLOCK: EventType.CLOCK, nvml.EventType.POWER_SOURCE_CHANGE: EventType.POWER_SOURCE_CHANGE, nvml.EventType.MIG_CONFIG_CHANGE: EventType.MIG_CONFIG_CHANGE, nvml.EventType.SINGLE_BIT_ECC_ERROR_STORM: EventType.SINGLE_BIT_ECC_ERROR_STORM, nvml.EventType.DRAM_RETIREMENT_EVENT: EventType.DRAM_RETIREMENT_EVENT, nvml.EventType.DRAM_RETIREMENT_FAILURE: EventType.DRAM_RETIREMENT_FAILURE, nvml.EventType.NON_FATAL_POISON_ERROR: EventType.NON_FATAL_POISON_ERROR, nvml.EventType.FATAL_POISON_ERROR: EventType.FATAL_POISON_ERROR, nvml.EventType.GPU_UNAVAILABLE_ERROR: EventType.GPU_UNAVAILABLE_ERROR, nvml.EventType.GPU_RECOVERY_ACTION: EventType.GPU_RECOVERY_ACTION}
-_EVENT_TYPE_INV_MAPPING = {v: k for k, v in _EVENT_TYPE_MAPPING.items()}
-_FAN_CONTROL_POLICY_MAPPING = {nvml.FanControlPolicy.TEMPERATURE_CONTINUOUS_SW: FanControlPolicy.TEMPERATURE_CONTROLLED, nvml.FanControlPolicy.MANUAL: FanControlPolicy.MANUAL}
-_INFOROM_OBJECT_MAPPING = {InforomObject.OEM: nvml.InforomObject.INFOROM_OEM, InforomObject.ECC: nvml.InforomObject.INFOROM_ECC, InforomObject.POWER: nvml.InforomObject.INFOROM_POWER, InforomObject.DEN: nvml.InforomObject.INFOROM_DEN}
-_NVLINK_VERSION_MAPPING = {nvml.NvlinkVersion.VERSION_1_0: (1, 0), nvml.NvlinkVersion.VERSION_2_0: (2, 0), nvml.NvlinkVersion.VERSION_2_2: (2, 2), nvml.NvlinkVersion.VERSION_3_0: (3, 0), nvml.NvlinkVersion.VERSION_3_1: (3, 1), nvml.NvlinkVersion.VERSION_4_0: (4, 0), nvml.NvlinkVersion.VERSION_5_0: (5, 0)}
-_NVLINK_VERSION_6_0 = getattr(nvml.NvlinkVersion, 'VERSION_6_0', None)
-_TEMPERATURE_THRESHOLD_MAPPING = {TemperatureThresholds.SHUTDOWN: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_SHUTDOWN, TemperatureThresholds.SLOWDOWN: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_SLOWDOWN, TemperatureThresholds.MEM_MAX: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_MEM_MAX, TemperatureThresholds.GPU_MAX: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_GPU_MAX, TemperatureThresholds.ACOUSTIC_MIN: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_MIN, TemperatureThresholds.ACOUSTIC_CURR: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_CURR, TemperatureThresholds.ACOUSTIC_MAX: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_ACOUSTIC_MAX, TemperatureThresholds.GPS_CURR: nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_GPS_CURR}
-_THERMAL_CONTROLLER_MAPPING = {nvml.ThermalController.GPU_INTERNAL: ThermalController.GPU_INTERNAL, nvml.ThermalController.ADM1032: ThermalController.ADM1032, nvml.ThermalController.ADT7461: ThermalController.ADT7461, nvml.ThermalController.MAX6649: ThermalController.MAX6649, nvml.ThermalController.MAX1617: ThermalController.MAX1617, nvml.ThermalController.LM99: ThermalController.LM99, nvml.ThermalController.LM89: ThermalController.LM89, nvml.ThermalController.LM64: ThermalController.LM64, nvml.ThermalController.G781: ThermalController.G781, nvml.ThermalController.ADT7473: ThermalController.ADT7473, nvml.ThermalController.SBMAX6649: ThermalController.SBMAX6649, nvml.ThermalController.VBIOSEVT: ThermalController.VBIOSEVT, nvml.ThermalController.OS: ThermalController.OS, nvml.ThermalController.NVSYSCON_CANOAS: ThermalController.NVSYSCON_CANOAS, nvml.ThermalController.NVSYSCON_E551: ThermalController.NVSYSCON_E551, nvml.ThermalController.MAX6649R: ThermalController.MAX6649R, nvml.ThermalController.ADT7473S: ThermalController.ADT7473S, nvml.ThermalController.UNKNOWN: ThermalController.UNKNOWN}
-_THERMAL_TARGET_MAPPING = {nvml.ThermalTarget.NONE: ThermalTarget.NONE, nvml.ThermalTarget.GPU: ThermalTarget.GPU, nvml.ThermalTarget.MEMORY: ThermalTarget.MEMORY, nvml.ThermalTarget.POWER_SUPPLY: ThermalTarget.POWER_SUPPLY, nvml.ThermalTarget.BOARD: ThermalTarget.BOARD, nvml.ThermalTarget.VCD_BOARD: ThermalTarget.VCD_BOARD, nvml.ThermalTarget.VCD_INLET: ThermalTarget.VCD_INLET, nvml.ThermalTarget.VCD_OUTLET: ThermalTarget.VCD_OUTLET, nvml.ThermalTarget.ALL: ThermalTarget.ALL}
-_THERMAL_TARGET_INV_MAPPING = {v: k for k, v in _THERMAL_TARGET_MAPPING.items()}
-_ADDRESSING_MODE_MAPPING = {nvml.DeviceAddressingModeType.DEVICE_ADDRESSING_MODE_HMM: AddressingMode.HMM, nvml.DeviceAddressingModeType.DEVICE_ADDRESSING_MODE_ATS: AddressingMode.ATS}
-_AFFINITY_SCOPE_MAPPING = {AffinityScope.NODE: nvml.AffinityScope.NODE, AffinityScope.SOCKET: nvml.AffinityScope.SOCKET}
-_BRAND_TYPE_MAPPING = {nvml.BrandType.BRAND_UNKNOWN: 'Unknown', nvml.BrandType.BRAND_QUADRO: 'Quadro', nvml.BrandType.BRAND_TESLA: 'Tesla', nvml.BrandType.BRAND_NVS: 'NVS', nvml.BrandType.BRAND_GRID: 'GRID', nvml.BrandType.BRAND_GEFORCE: 'GeForce', nvml.BrandType.BRAND_TITAN: 'Titan', nvml.BrandType.BRAND_NVIDIA_VAPPS: 'NVIDIA vApps', nvml.BrandType.BRAND_NVIDIA_VPC: 'NVIDIA VPC', nvml.BrandType.BRAND_NVIDIA_VCS: 'NVIDIA VCS', nvml.BrandType.BRAND_NVIDIA_VWS: 'NVIDIA VWS', nvml.BrandType.BRAND_NVIDIA_CLOUD_GAMING: 'NVIDIA Cloud Gaming', nvml.BrandType.BRAND_NVIDIA_VGAMING: 'NVIDIA vGaming', nvml.BrandType.BRAND_QUADRO_RTX: 'Quadro RTX', nvml.BrandType.BRAND_NVIDIA_RTX: 'NVIDIA RTX', nvml.BrandType.BRAND_NVIDIA: 'NVIDIA', nvml.BrandType.BRAND_GEFORCE_RTX: 'GeForce RTX', nvml.BrandType.BRAND_TITAN_RTX: 'Titan RTX'}
-_GPU_P2P_CAPS_INDEX_MAPPING = {GpuP2PCapsIndex.READ: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_READ, GpuP2PCapsIndex.WRITE: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_WRITE, GpuP2PCapsIndex.NVLINK: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_NVLINK, GpuP2PCapsIndex.ATOMICS: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_ATOMICS, GpuP2PCapsIndex.PCI: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_PCI, GpuP2PCapsIndex.PROP: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_PROP, GpuP2PCapsIndex.UNKNOWN: nvml.GpuP2PCapsIndex.P2P_CAPS_INDEX_UNKNOWN}
-_GPU_P2P_STATUS_MAPPING = {nvml.GpuP2PStatus.P2P_STATUS_OK: GpuP2PStatus.OK, nvml.GpuP2PStatus.P2P_STATUS_CHIPSET_NOT_SUPPORTED: GpuP2PStatus.CHIPSET_NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_GPU_NOT_SUPPORTED: GpuP2PStatus.GPU_NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_IOH_TOPOLOGY_NOT_SUPPORTED: GpuP2PStatus.IOH_TOPOLOGY_NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_DISABLED_BY_REGKEY: GpuP2PStatus.DISABLED_BY_REGKEY, nvml.GpuP2PStatus.P2P_STATUS_NOT_SUPPORTED: GpuP2PStatus.NOT_SUPPORTED, nvml.GpuP2PStatus.P2P_STATUS_UNKNOWN: GpuP2PStatus.UNKNOWN}
-_GPU_TOPOLOGY_LEVEL_MAPPING = {GpuTopologyLevel.INTERNAL: nvml.GpuTopologyLevel.TOPOLOGY_INTERNAL, GpuTopologyLevel.SINGLE: nvml.GpuTopologyLevel.TOPOLOGY_SINGLE, GpuTopologyLevel.MULTIPLE: nvml.GpuTopologyLevel.TOPOLOGY_MULTIPLE, GpuTopologyLevel.HOSTBRIDGE: nvml.GpuTopologyLevel.TOPOLOGY_HOSTBRIDGE, GpuTopologyLevel.NODE: nvml.GpuTopologyLevel.TOPOLOGY_NODE, GpuTopologyLevel.SYSTEM: nvml.GpuTopologyLevel.TOPOLOGY_SYSTEM}
-_GPU_TOPOLOGY_LEVEL_INV_MAPPING = {v: k for k, v in _GPU_TOPOLOGY_LEVEL_MAPPING.items()}
-__all__ = ['Device', 'get_p2p_status', 'get_topology_common_ancestor', 'NvlinkInfo']
 
 def _unpack_bitmask(arr: object) -> list[int]:
     """
     Unpack a list of integers containing bitmasks.
     """
-
 def get_topology_common_ancestor(device1: Device, device2: Device) -> GpuTopologyLevel:
     """
     Retrieve the common ancestor for two devices.
@@ -1931,7 +1717,6 @@ def get_topology_common_ancestor(device1: Device, device2: Device) -> GpuTopolog
     :class:`GpuTopologyLevel`
         The common ancestor level of the two devices.
     """
-
 def get_p2p_status(device1: Device, device2: Device, index: GpuP2PCapsIndex | str) -> GpuP2PStatus:
     """
     Retrieve the P2P status between two devices.
@@ -1949,4 +1734,4 @@ def get_p2p_status(device1: Device, device2: Device, index: GpuP2PCapsIndex | st
     -------
     :class:`GpuP2PStatus`
         The P2P status between the two devices.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/system/_device.pyx b/cuda_core/cuda/core/system/_device.pyx
index fb4b9a3916d..c3bf23fe025 100644
--- a/cuda_core/cuda/core/system/_device.pyx
+++ b/cuda_core/cuda/core/system/_device.pyx
@@ -2,6 +2,8 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
+from __future__ import annotations
+
 from libc.stdint cimport intptr_t, uint64_t
 from libc.math cimport ceil
 
diff --git a/cuda_core/cuda/core/system/_device_attributes.pxi b/cuda_core/cuda/core/system/_device_attributes.pxi
index c18a7be35df..6cf6d4ee271 100644
--- a/cuda_core/cuda/core/system/_device_attributes.pxi
+++ b/cuda_core/cuda/core/system/_device_attributes.pxi
@@ -7,6 +7,8 @@ cdef class DeviceAttributes:
     """
     Various device attributes.
     """
+    cdef object _attributes
+
     def __init__(self, attributes: nvml.DeviceAttributes):
         self._attributes = attributes
 
diff --git a/cuda_core/cuda/core/system/_event.pxi b/cuda_core/cuda/core/system/_event.pxi
index f81e5934aa7..f845f57cf53 100644
--- a/cuda_core/cuda/core/system/_event.pxi
+++ b/cuda_core/cuda/core/system/_event.pxi
@@ -29,6 +29,8 @@ cdef class EventData:
     """
     Data about a single event.
     """
+    cdef object _event_data
+
     def __init__(self, event_data: nvml.EventData):
         self._event_data = event_data
 
diff --git a/cuda_core/cuda/core/system/_field_values.pxi b/cuda_core/cuda/core/system/_field_values.pxi
index 4a9e5cc748f..d109bc2bc13 100644
--- a/cuda_core/cuda/core/system/_field_values.pxi
+++ b/cuda_core/cuda/core/system/_field_values.pxi
@@ -75,7 +75,7 @@ cdef class FieldValue:
         elif value_type == ValueType.UNSIGNED_LONG_LONG:
             return int(value.ull_val[0])
         elif value_type == ValueType.SIGNED_LONG_LONG:
-            return int(value.ll_val[0])
+            return int(value.sll_val[0])
         elif value_type == ValueType.SIGNED_INT:
             return int(value.si_val[0])
         elif value_type == ValueType.UNSIGNED_SHORT:
diff --git a/cuda_core/cuda/core/system/_nvml_context.pyi b/cuda_core/cuda/core/system/_nvml_context.pyi
index e52a803b346..7650f28003a 100644
--- a/cuda_core/cuda/core/system/_nvml_context.pyi
+++ b/cuda_core/cuda/core/system/_nvml_context.pyi
@@ -1,17 +1,17 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/system/_nvml_context.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/system/_nvml_context.pyx
 
 import threading
 
-_NVMLState = int
+from typing_extensions import TypeAlias
+
+_NVMLState: TypeAlias = int
 _lock = threading.Lock()
 
+def _get_nvml_state() -> _NVMLState: ...
 def _initialize() -> None:
     """
     Initializes NVIDIA Management Library (NVML), ensuring it only happens once per process.
     """
-
 def validate() -> None:
     """
     Validate NVML state.
@@ -28,6 +28,3 @@ def validate() -> None:
     nvml.GpuNotFoundError
         If no GPUs are available.
     """
-
-def _get_nvml_state() -> _NVMLState:
-    ...
\ No newline at end of file
diff --git a/cuda_core/cuda/core/system/_process.pxi b/cuda_core/cuda/core/system/_process.pxi
index 019ebf5c323..4266f5b5914 100644
--- a/cuda_core/cuda/core/system/_process.pxi
+++ b/cuda_core/cuda/core/system/_process.pxi
@@ -7,7 +7,7 @@ class ProcessInfo:
     """
     Information about running compute processes on the GPU.
     """
-    def __init__(self, device: "Device", process_info: nvml.ProcessInfo):
+    def __init__(self, device: Device, process_info: nvml.ProcessInfo):
         self._device = device
         self._process_info = process_info
 
diff --git a/cuda_core/cuda/core/system/_system.pyi b/cuda_core/cuda/core/system/_system.pyi
index f25ce35be7f..b29b16f16aa 100644
--- a/cuda_core/cuda/core/system/_system.pyi
+++ b/cuda_core/cuda/core/system/_system.pyi
@@ -1,6 +1,4 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/system/_system.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/system/_system.pyx
 
 CUDA_BINDINGS_NVML_IS_COMPATIBLE: bool
 __all__ = ['get_driver_branch', 'get_kernel_mode_driver_version', 'get_user_mode_driver_version', 'get_nvml_version', 'get_num_devices', 'get_process_name', 'CUDA_BINDINGS_NVML_IS_COMPATIBLE']
@@ -17,7 +15,6 @@ def get_user_mode_driver_version() -> tuple[int, ...]:
     version : tuple[int, ...]
         A 2-tuple ``(MAJOR, MINOR)``, e.g. ``(13, 0)`` for CUDA 13.0.
     """
-
 def get_kernel_mode_driver_version() -> tuple[int, ...]:
     """
     Get the kernel-mode (KMD / GPU) driver version, e.g. 580.65.06.
@@ -33,7 +30,6 @@ def get_kernel_mode_driver_version() -> tuple[int, ...]:
     RuntimeError
         If the NVML library is not available.
     """
-
 def get_nvml_version() -> tuple[int, ...]:
     """
     The version of the NVML library.
@@ -43,7 +39,6 @@ def get_nvml_version() -> tuple[int, ...]:
     version: tuple[int, ...]
         Tuple of integers representing the NVML version components.
     """
-
 def get_driver_branch() -> str:
     """
     Retrieves the driver branch of the NVIDIA driver installed on the system.
@@ -53,12 +48,10 @@ def get_driver_branch() -> str:
     branch: str
         The driver branch string (e.g., ``"560"``, ``"open"``, etc.).
     """
-
 def get_num_devices() -> int:
     """
     Return the number of devices in the system.
     """
-
 def get_process_name(pid: int) -> str:
     """
     The name of process with given PID.
@@ -72,4 +65,4 @@ def get_process_name(pid: int) -> str:
     -------
     name: str
         The process name.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/system/_system_events.pyi b/cuda_core/cuda/core/system/_system_events.pyi
index 5ae5b86bc57..b8950ecc340 100644
--- a/cuda_core/cuda/core/system/_system_events.pyi
+++ b/cuda_core/cuda/core/system/_system_events.pyi
@@ -1,33 +1,29 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/system/_system_events.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/system/_system_events.pyx
 
 from cuda.bindings import nvml
 from cuda.core.system.typing import SystemEventType
 
 from . import _device
 
+_SYSTEM_EVENT_TYPE_MAPPING = {nvml.SystemEventType.GPU_DRIVER_UNBIND: SystemEventType.UNBIND, nvml.SystemEventType.GPU_DRIVER_BIND: SystemEventType.BIND}
+_SYSTEM_EVENT_TYPE_INV_MAPPING = {v: k for k, v in _SYSTEM_EVENT_TYPE_MAPPING.items()}
+__all__ = ['register_events']
 
 class SystemEvent:
     """
     Data about a collection of system events.
     """
-
-    def __init__(self, event_data: nvml.SystemEventData_v1):
-        ...
-
+    def __init__(self, event_data: nvml.SystemEventData_v1): ...
     @property
     def event_type(self) -> SystemEventType:
         """
         The :obj:`~SystemEventType` that was triggered.
         """
-
     @property
     def gpu_id(self) -> int:
         """
         The GPU ID in PCI ID format.
         """
-
     @property
     def device(self) -> _device.Device:
         """
@@ -38,13 +34,8 @@ class SystemEvents:
     """
     Data about a collection of system events.
     """
-
-    def __init__(self, event_data: nvml.SystemEventData_v1):
-        ...
-
-    def __len__(self) -> int:
-        ...
-
+    def __init__(self, event_data: nvml.SystemEventData_v1): ...
+    def __len__(self) -> int: ...
     def __getitem__(self, idx: int) -> SystemEvent:
         """
         Get the :obj:`~_system_events.SystemEvent` at the specified index.
@@ -54,13 +45,8 @@ class RegisteredSystemEvents:
     """
     Represents a set of events that can be waited on for a specific device.
     """
-
-    def __init__(self, events: SystemEventType | str | list[SystemEventType | str]):
-        ...
-
-    def __dealloc__(self) -> None:
-        ...
-
+    def __init__(self, events: SystemEventType | str | list[SystemEventType | str]): ...
+    def __dealloc__(self) -> None: ...
     def wait(self, timeout_ms: int=0, buffer_size: int=1) -> SystemEvents:
         """
         Wait for events in the system event set.
@@ -95,10 +81,12 @@ class RegisteredSystemEvents:
         :class:`cuda.core.system.GpuIsLostError`
             If the GPU has fallen off the bus or is otherwise inaccessible.
         """
-_SYSTEM_EVENT_TYPE_MAPPING = {nvml.SystemEventType.GPU_DRIVER_UNBIND: SystemEventType.UNBIND, nvml.SystemEventType.GPU_DRIVER_BIND: SystemEventType.BIND}
-_SYSTEM_EVENT_TYPE_INV_MAPPING = {v: k for k, v in _SYSTEM_EVENT_TYPE_MAPPING.items()}
-__all__ = ['register_events']
 
+def _pci_bus_id_from_gpu_id(gpu_id: int) -> str:
+    """
+    Decode an NVML System Event packed ``gpu_id`` into an NVML-style PCI bus ID
+    string.
+    """
 def register_events(events: SystemEventType | str | list[SystemEventType | str]) -> RegisteredSystemEvents:
     """
     Starts recording of events on test system.
@@ -130,4 +118,4 @@ def register_events(events: SystemEventType | str | list[SystemEventType | str])
     ------
     :class:`cuda.core.system.NotSupportedError`
         None of the requested event types are registered.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/system/_system_events.pyx b/cuda_core/cuda/core/system/_system_events.pyx
index 87a3dfcf1ef..865a1b74890 100644
--- a/cuda_core/cuda/core/system/_system_events.pyx
+++ b/cuda_core/cuda/core/system/_system_events.pyx
@@ -22,10 +22,23 @@ _SYSTEM_EVENT_TYPE_MAPPING = {
 _SYSTEM_EVENT_TYPE_INV_MAPPING = {v: k for k, v in _SYSTEM_EVENT_TYPE_MAPPING.items()}
 
 
+def _pci_bus_id_from_gpu_id(gpu_id: int) -> str:
+    """
+    Decode an NVML System Event packed ``gpu_id`` into an NVML-style PCI bus ID
+    string.
+    """
+    domain = (gpu_id >> 16) & 0xFFFF
+    bus = (gpu_id >> 8) & 0xFF
+    device = gpu_id & 0xFF
+    return f"{domain:08X}:{bus:02X}:{device:02X}.0"
+
+
 cdef class SystemEvent:
     """
     Data about a collection of system events.
     """
+    cdef object _event_data
+
     def __init__(self, event_data: nvml.SystemEventData_v1):
         assert len(event_data) == 1
         self._event_data = event_data
@@ -49,13 +62,15 @@ cdef class SystemEvent:
         """
         The :obj:`~_device.Device` associated with this event.
         """
-        return _device.Device(pci_bus_id=self.gpu_id)
+        return _device.Device(pci_bus_id=_pci_bus_id_from_gpu_id(self.gpu_id))
 
 
 cdef class SystemEvents:
     """
     Data about a collection of system events.
     """
+    cdef object _event_data
+
     def __init__(self, event_data: nvml.SystemEventData_v1):
         self._event_data = event_data
 
diff --git a/cuda_core/cuda/core/system/_temperature.pxi b/cuda_core/cuda/core/system/_temperature.pxi
index f5eed73de2c..82dc0cab785 100644
--- a/cuda_core/cuda/core/system/_temperature.pxi
+++ b/cuda_core/cuda/core/system/_temperature.pxi
@@ -173,7 +173,9 @@ cdef class Temperature:
             nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_MEM_MAX,
             nvml.TemperatureThresholds.TEMPERATURE_THRESHOLD_GPU_MAX
         ):
-            device_arch = nvml.DeviceArch(nvml.device_get_architecture(self._handle))
+            # Compare the raw value so newer NVML architecture constants remain
+            # forward-compatible.
+            device_arch = nvml.device_get_architecture(self._handle)
             if device_arch >= nvml.DeviceArch.ADA:
                 warnings.warn(
                     f"{threshold_type} is no longer recommended for Ada and later architectures. "
diff --git a/cuda_core/cuda/core/texture/_array.pxd b/cuda_core/cuda/core/texture/_array.pxd
index 5e380c8885a..ceb64e2401c 100644
--- a/cuda_core/cuda/core/texture/_array.pxd
+++ b/cuda_core/cuda/core/texture/_array.pxd
@@ -21,6 +21,12 @@ cdef class OpaqueArray:
     cpdef close(self)
 
 
+cdef inline int OpaqueArray_check_open(OpaqueArray self) except -1:
+    if not self._handle:
+        raise RuntimeError("OpaqueArray has been closed")
+    return 0
+
+
 # Wrap an existing OpaqueArrayHandle as a OpaqueArray, querying the driver for the
 # array's shape/format/channels/surface-flag metadata. Used by get_level and
 # the graphics-interop _from_handle path.
diff --git a/cuda_core/cuda/core/texture/_array.pyi b/cuda_core/cuda/core/texture/_array.pyi
index 380c2fe1c10..e18adde1393 100644
--- a/cuda_core/cuda/core/texture/_array.pyi
+++ b/cuda_core/cuda/core/texture/_array.pyi
@@ -1,13 +1,16 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/texture/_array.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/texture/_array.pyx
 
 from dataclasses import dataclass
 
 import numpy
 from cuda.bindings import cydriver
+from cuda.core._context import Context
 from cuda.core.typing import ArrayFormatType
 
+_ARRAYFORMAT_TO_CU = {ArrayFormatType.UINT8: int(cydriver.CU_AD_FORMAT_UNSIGNED_INT8), ArrayFormatType.UINT16: int(cydriver.CU_AD_FORMAT_UNSIGNED_INT16), ArrayFormatType.UINT32: int(cydriver.CU_AD_FORMAT_UNSIGNED_INT32), ArrayFormatType.INT8: int(cydriver.CU_AD_FORMAT_SIGNED_INT8), ArrayFormatType.INT16: int(cydriver.CU_AD_FORMAT_SIGNED_INT16), ArrayFormatType.INT32: int(cydriver.CU_AD_FORMAT_SIGNED_INT32), ArrayFormatType.FLOAT16: int(cydriver.CU_AD_FORMAT_HALF), ArrayFormatType.FLOAT32: int(cydriver.CU_AD_FORMAT_FLOAT)}
+_CU_TO_ARRAYFORMAT = {cu: fmt for fmt, cu in _ARRAYFORMAT_TO_CU.items()}
+_NUMPY_DTYPE_TO_ARRAYFORMAT = {numpy.dtype(fmt.value): fmt for fmt in ArrayFormatType}
+_FORMAT_ELEM_SIZE = {_ARRAYFORMAT_TO_CU[ArrayFormatType.UINT8]: 1, _ARRAYFORMAT_TO_CU[ArrayFormatType.INT8]: 1, _ARRAYFORMAT_TO_CU[ArrayFormatType.UINT16]: 2, _ARRAYFORMAT_TO_CU[ArrayFormatType.INT16]: 2, _ARRAYFORMAT_TO_CU[ArrayFormatType.FLOAT16]: 2, _ARRAYFORMAT_TO_CU[ArrayFormatType.UINT32]: 4, _ARRAYFORMAT_TO_CU[ArrayFormatType.INT32]: 4, _ARRAYFORMAT_TO_CU[ArrayFormatType.FLOAT32]: 4}
 
 @dataclass
 class OpaqueArrayOptions:
@@ -35,8 +38,7 @@ class OpaqueArrayOptions:
     num_channels: int
     is_surface_load_store: bool = False
 
-    def __post_init__(self):
-        ...
+    def __post_init__(self): ...
 
 class OpaqueArray:
     """An opaque, hardware-laid-out GPU allocation for texture/surface access.
@@ -61,19 +63,7 @@ class OpaqueArray:
 
     .. versionadded:: 1.1.0
     """
-
-    def close(self):
-        """Release this object's reference to the underlying ``CUarray``.
-
-        Destruction (``cuArrayDestroy``) happens via the handle's deleter when
-        the last reference is dropped; for a non-owning handle (graphics interop
-        or a mipmap-level view) nothing is destroyed. Idempotent: a second call
-        (or destruction after ``close()``) is a no-op.
-        """
-
-    def __init__(self, *args, **kwargs):
-        ...
-
+    def __init__(self, *args, **kwargs): ...
     @classmethod
     def _from_handle(cls, handle: int, owning: bool, *, device_id=None):
         """Wrap an externally-allocated ``CUarray``.
@@ -83,40 +73,34 @@ class OpaqueArray:
         underlying ``CUarray`` is never destroyed by this object. Shape, format,
         and channel count are queried from the driver.
         """
-
     @property
     def handle(self):
         """The underlying ``CUarray`` as an integer."""
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this array has been closed."""
     @property
     def shape(self):
         """Allocation shape, in elements."""
-
     @property
     def format(self):
         """The element :class:`~cuda.core.typing.ArrayFormatType`."""
-
     @property
     def num_channels(self):
         """Channels per element (1, 2, or 4)."""
-
     @property
     def element_bytes(self):
         """Bytes per element (format size * channels)."""
-
     @property
     def device(self):
         """The :class:`Device` this array was allocated on."""
-
     @property
     def is_surface_load_store(self):
         """True if this array was created with ``CUDA_ARRAY3D_SURFACE_LDST``
         and can be bound as a :class:`SurfaceObject`."""
-
     def _extent_bytes(self):
         """Return (width_bytes, height, depth) for cuMemcpy3D, with height/depth
         normalized to >=1 for lower-rank arrays."""
-
     def copy_from(self, src, *, stream) -> None:
         """Copy a full-array's worth of data into this array.
 
@@ -129,7 +113,6 @@ class OpaqueArray:
             Stream to issue the copy on. A :class:`~cuda.core.graph.GraphBuilder`
             is accepted so the copy can be captured into a graph.
         """
-
     def copy_to(self, dst, *, stream):
         """Copy a full-array's worth of data out of this array.
 
@@ -146,23 +129,20 @@ class OpaqueArray:
         -------
         The ``dst`` object, for parity with :meth:`Buffer.copy_to`.
         """
-
     @property
     def size_bytes(self):
         """Total bytes of array storage (``prod(shape) * element_bytes``)."""
+    def close(self):
+        """Release this object's reference to the underlying ``CUarray``.
 
-    def __enter__(self):
-        ...
-
-    def __exit__(self, exc_type, exc, tb):
-        ...
-
-    def __repr__(self):
-        ...
-_ARRAYFORMAT_TO_CU = {ArrayFormatType.UINT8: int(cydriver.CU_AD_FORMAT_UNSIGNED_INT8), ArrayFormatType.UINT16: int(cydriver.CU_AD_FORMAT_UNSIGNED_INT16), ArrayFormatType.UINT32: int(cydriver.CU_AD_FORMAT_UNSIGNED_INT32), ArrayFormatType.INT8: int(cydriver.CU_AD_FORMAT_SIGNED_INT8), ArrayFormatType.INT16: int(cydriver.CU_AD_FORMAT_SIGNED_INT16), ArrayFormatType.INT32: int(cydriver.CU_AD_FORMAT_SIGNED_INT32), ArrayFormatType.FLOAT16: int(cydriver.CU_AD_FORMAT_HALF), ArrayFormatType.FLOAT32: int(cydriver.CU_AD_FORMAT_FLOAT)}
-_CU_TO_ARRAYFORMAT = {cu: fmt for fmt, cu in _ARRAYFORMAT_TO_CU.items()}
-_NUMPY_DTYPE_TO_ARRAYFORMAT = {numpy.dtype(fmt.value): fmt for fmt in ArrayFormatType}
-_FORMAT_ELEM_SIZE = {_ARRAYFORMAT_TO_CU[ArrayFormatType.UINT8]: 1, _ARRAYFORMAT_TO_CU[ArrayFormatType.INT8]: 1, _ARRAYFORMAT_TO_CU[ArrayFormatType.UINT16]: 2, _ARRAYFORMAT_TO_CU[ArrayFormatType.INT16]: 2, _ARRAYFORMAT_TO_CU[ArrayFormatType.FLOAT16]: 2, _ARRAYFORMAT_TO_CU[ArrayFormatType.UINT32]: 4, _ARRAYFORMAT_TO_CU[ArrayFormatType.INT32]: 4, _ARRAYFORMAT_TO_CU[ArrayFormatType.FLOAT32]: 4}
+        Destruction (``cuArrayDestroy``) happens via the handle's deleter when
+        the last reference is dropped; for a non-owning handle (graphics interop
+        or a mipmap-level view) nothing is destroyed. Idempotent: a second call
+        (or destruction after ``close()``) is a no-op.
+        """
+    def __enter__(self): ...
+    def __exit__(self, exc_type, exc, tb): ...
+    def __repr__(self): ...
 
 def _normalize_array_format(format):
     """Coerce ``format`` to an :class:`ArrayFormatType`.
@@ -176,21 +156,18 @@ def _normalize_array_format(format):
       supported formats.
 
     Raises :class:`ValueError` on anything else."""
-
 def _validate_format_channels(format, num_channels):
     """Validate the ``(format, num_channels)`` pair shared by the array,
     mipmap, and texture factories. Returns the normalized
     :class:`ArrayFormatType`. Raises on an invalid combination."""
-
 def _validate_array_shape(shape):
     """Coerce ``shape`` to a tuple of ints and validate rank (1-3) and that
     every extent is >= 1. Returns the normalized tuple."""
-
-def _create_opaque_array(options):
-    """Allocate a new :class:`OpaqueArray` on the current device.
+def _create_opaque_array(options, ctx: Context, device_id: int):
+    """Allocate a new :class:`OpaqueArray` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_opaque_array`. ``options`` is an
     :class:`OpaqueArrayOptions` (or a mapping accepted by it); it is validated
     at construction, so ``shape`` is already a normalized tuple and ``format``
     an :class:`~cuda.core.typing.ArrayFormatType`.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/texture/_array.pyx b/cuda_core/cuda/core/texture/_array.pyx
index 0a1cb671daf..e5fc3f6c9e2 100644
--- a/cuda_core/cuda/core/texture/_array.pyx
+++ b/cuda_core/cuda/core/texture/_array.pyx
@@ -9,7 +9,8 @@ from libc.stdint cimport intptr_t
 from libc.string cimport memset
 
 from cuda.bindings cimport cydriver
-from cuda.core._memory._buffer cimport Buffer
+from cuda.core._context cimport Context
+from cuda.core._memory._buffer cimport Buffer, Buffer_check_open
 from cuda.core._resource_handles cimport (
     OpaqueArrayHandle,
     as_cu,
@@ -248,6 +249,7 @@ cdef int _fill_linear_endpoint(
     cdef intptr_t ptr
     cdef size_t required = width_bytes * height * depth
     if isinstance(obj, Buffer):
+        Buffer_check_open(<Buffer>obj)
         if <size_t>(<Buffer>obj).size < required:
             raise ValueError(
                 f"Buffer size ({(<Buffer>obj).size} bytes) is smaller than "
@@ -369,6 +371,11 @@ cdef class OpaqueArray:
         """The underlying ``CUarray`` as an integer."""
         return as_intptr(self._handle)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this array has been closed."""
+        return self._handle.get() == NULL
+
     @property
     def shape(self):
         """Allocation shape, in elements."""
@@ -424,6 +431,7 @@ cdef class OpaqueArray:
             Stream to issue the copy on. A :class:`~cuda.core.graph.GraphBuilder`
             is accepted so the copy can be captured into a graph.
         """
+        OpaqueArray_check_open(self)
         _copy3d(self, src, Stream_accept(stream), to_array=True)
 
     def copy_to(self, dst, *, stream):
@@ -442,6 +450,7 @@ cdef class OpaqueArray:
         -------
         The ``dst`` object, for parity with :meth:`Buffer.copy_to`.
         """
+        OpaqueArray_check_open(self)
         _copy3d(self, dst, Stream_accept(stream), to_array=False)
         return dst
 
@@ -476,7 +485,6 @@ cdef class OpaqueArray:
             f"num_channels={self._num_channels})"
         )
 
-
 cdef OpaqueArray _array_from_handle(OpaqueArrayHandle h, int device_id):
     """Wrap an existing OpaqueArrayHandle as a OpaqueArray, querying the driver for the
     array's shape/format/channels/surface-flag metadata.
@@ -508,8 +516,8 @@ cdef OpaqueArray _array_from_handle(OpaqueArrayHandle h, int device_id):
     return self
 
 
-def _create_opaque_array(options):
-    """Allocate a new :class:`OpaqueArray` on the current device.
+def _create_opaque_array(options, Context ctx, int device_id):
+    """Allocate a new :class:`OpaqueArray` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_opaque_array`. ``options`` is an
     :class:`OpaqueArrayOptions` (or a mapping accepted by it); it is validated
@@ -522,7 +530,6 @@ def _create_opaque_array(options):
     shape_t = opts.shape
 
     cdef cydriver.CUarray_format c_format = <cydriver.CUarray_format>_ARRAYFORMAT_TO_CU[opts.format]
-    cdef cydriver.CUDA_ARRAY3D_DESCRIPTOR desc3d
     cdef int rank = len(shape_t)
     cdef unsigned int flags = (
         cydriver.CUDA_ARRAY3D_SURFACE_LDST if opts.is_surface_load_store else 0
@@ -530,15 +537,16 @@ def _create_opaque_array(options):
 
     # cuArray3DCreate handles 1D/2D/3D uniformly (Height/Depth 0 sentinels),
     # so a single descriptor + create_array_handle covers every shape.
-    memset(&desc3d, 0, sizeof(desc3d))
-    desc3d.Width = <size_t>shape_t[0]
-    desc3d.Height = <size_t>(shape_t[1] if rank >= 2 else 0)
-    desc3d.Depth = <size_t>(shape_t[2] if rank >= 3 else 0)
-    desc3d.Format = c_format
-    desc3d.NumChannels = <unsigned int>opts.num_channels
-    desc3d.Flags = flags
-
-    cdef OpaqueArrayHandle h = create_array_handle(desc3d)
+    cdef cydriver.CUDA_ARRAY3D_DESCRIPTOR desc3d = cydriver.CUDA_ARRAY3D_DESCRIPTOR(
+        Width=<size_t>shape_t[0],
+        Height=<size_t>(shape_t[1] if rank >= 2 else 0),
+        Depth=<size_t>(shape_t[2] if rank >= 3 else 0),
+        Format=c_format,
+        NumChannels=<unsigned int>opts.num_channels,
+        Flags=flags,
+    )
+
+    cdef OpaqueArrayHandle h = create_array_handle(ctx._h_context, desc3d)
     if not h:
         HANDLE_RETURN(get_last_error())
 
@@ -548,5 +556,5 @@ def _create_opaque_array(options):
     self._format = c_format
     self._num_channels = opts.num_channels
     self._surface_load_store = bool(opts.is_surface_load_store)
-    self._device_id = _get_current_device_id()
+    self._device_id = device_id
     return self
diff --git a/cuda_core/cuda/core/texture/_mipmapped_array.pxd b/cuda_core/cuda/core/texture/_mipmapped_array.pxd
index be0d8f00966..281c7140b05 100644
--- a/cuda_core/cuda/core/texture/_mipmapped_array.pxd
+++ b/cuda_core/cuda/core/texture/_mipmapped_array.pxd
@@ -18,3 +18,9 @@ cdef class MipmappedArray:
         bint _surface_load_store
 
     cpdef close(self)
+
+
+cdef inline int MipmappedArray_check_open(MipmappedArray self) except -1:
+    if not self._handle:
+        raise RuntimeError("MipmappedArray has been closed")
+    return 0
diff --git a/cuda_core/cuda/core/texture/_mipmapped_array.pyi b/cuda_core/cuda/core/texture/_mipmapped_array.pyi
index db4413dbaf4..72788bcd272 100644
--- a/cuda_core/cuda/core/texture/_mipmapped_array.pyi
+++ b/cuda_core/cuda/core/texture/_mipmapped_array.pyi
@@ -1,9 +1,9 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/texture/_mipmapped_array.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/texture/_mipmapped_array.pyx
 
 from dataclasses import dataclass
 
+from cuda.core._context import Context
+
 
 @dataclass
 class MipmappedArrayOptions:
@@ -37,8 +37,7 @@ class MipmappedArrayOptions:
     num_levels: int
     is_surface_load_store: bool = False
 
-    def __post_init__(self):
-        ...
+    def __post_init__(self): ...
 
 class MipmappedArray:
     """A mipmapped CUDA array for texture/surface access across levels.
@@ -54,19 +53,7 @@ class MipmappedArray:
 
     .. versionadded:: 1.1.0
     """
-
-    def close(self):
-        """Release this object's reference to the underlying ``CUmipmappedArray``.
-
-        Destruction (``cuMipmappedArrayDestroy``) happens via the handle's
-        deleter when the last reference is dropped. A level :class:`OpaqueArray`
-        from :meth:`get_level` holds its own reference to this mipmap's storage,
-        so it stays valid until both it and this object are released. Idempotent.
-        """
-
-    def __init__(self, *args, **kwargs):
-        ...
-
+    def __init__(self, *args, **kwargs): ...
     def get_level(self, level):
         """Return a non-owning :class:`OpaqueArray` view of the given mip level.
 
@@ -83,49 +70,47 @@ class MipmappedArray:
             returned :class:`OpaqueArray`; the underlying storage is released only
             when this :class:`MipmappedArray` is destroyed.
         """
-
     @property
     def handle(self):
         """The underlying ``CUmipmappedArray`` as an integer."""
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this mipmapped array has been closed."""
     @property
     def shape(self):
         """Base-level (level 0) allocation shape, in elements."""
-
     @property
     def format(self):
         """The element :class:`~cuda.core.typing.ArrayFormatType`."""
-
     @property
     def num_channels(self):
         """Channels per element (1, 2, or 4)."""
-
     @property
     def num_levels(self):
         """Number of mip levels."""
-
     @property
     def is_surface_load_store(self):
         """True if this mipmap (and each of its levels) was created with
         ``CUDA_ARRAY3D_SURFACE_LDST`` and can back a :class:`SurfaceObject`."""
-
     @property
     def device(self):
         """The :class:`Device` this mipmap was allocated on."""
+    def close(self):
+        """Release this object's reference to the underlying ``CUmipmappedArray``.
 
-    def __enter__(self):
-        ...
-
-    def __exit__(self, exc_type, exc, tb):
-        ...
-
-    def __repr__(self):
-        ...
+        Destruction (``cuMipmappedArrayDestroy``) happens via the handle's
+        deleter when the last reference is dropped. A level :class:`OpaqueArray`
+        from :meth:`get_level` holds its own reference to this mipmap's storage,
+        so it stays valid until both it and this object are released. Idempotent.
+        """
+    def __enter__(self): ...
+    def __exit__(self, exc_type, exc, tb): ...
+    def __repr__(self): ...
 
-def _create_mipmapped_array(options):
-    """Allocate a new :class:`MipmappedArray` on the current device.
+def _create_mipmapped_array(options, ctx: Context, device_id: int):
+    """Allocate a new :class:`MipmappedArray` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_mipmapped_array`. ``options`` is a
     :class:`MipmappedArrayOptions` (or a mapping accepted by it); its fields are
     validated at construction.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/texture/_mipmapped_array.pyx b/cuda_core/cuda/core/texture/_mipmapped_array.pyx
index 3f151f7bb9f..8d6bf5a2589 100644
--- a/cuda_core/cuda/core/texture/_mipmapped_array.pyx
+++ b/cuda_core/cuda/core/texture/_mipmapped_array.pyx
@@ -4,9 +4,8 @@
 
 from __future__ import annotations
 
-from libc.string cimport memset
-
 from cuda.bindings cimport cydriver
+from cuda.core._context cimport Context
 from cuda.core.texture._array cimport _array_from_handle
 from cuda.core.texture._array import (
     _ARRAYFORMAT_TO_CU,
@@ -22,10 +21,7 @@ from cuda.core._resource_handles cimport (
     create_mipmapped_array_handle,
     get_last_error,
 )
-from cuda.core._utils.cuda_utils cimport (
-    HANDLE_RETURN,
-    _get_current_device_id,
-)
+from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 
 from dataclasses import dataclass
 
@@ -110,6 +106,7 @@ cdef class MipmappedArray:
             returned :class:`OpaqueArray`; the underlying storage is released only
             when this :class:`MipmappedArray` is destroyed.
         """
+        MipmappedArray_check_open(self)
         lvl = int(level)
         if lvl < 0:
             raise ValueError(f"level must be >= 0, got {lvl}")
@@ -131,6 +128,11 @@ cdef class MipmappedArray:
         """The underlying ``CUmipmappedArray`` as an integer."""
         return as_intptr(self._handle)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this mipmapped array has been closed."""
+        return self._handle.get() == NULL
+
     @property
     def shape(self):
         """Base-level (level 0) allocation shape, in elements."""
@@ -187,9 +189,8 @@ cdef class MipmappedArray:
             f"num_levels={self._num_levels})"
         )
 
-
-def _create_mipmapped_array(options):
-    """Allocate a new :class:`MipmappedArray` on the current device.
+def _create_mipmapped_array(options, Context ctx, int device_id):
+    """Allocate a new :class:`MipmappedArray` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_mipmapped_array`. ``options`` is a
     :class:`MipmappedArrayOptions` (or a mapping accepted by it); its fields are
@@ -201,7 +202,6 @@ def _create_mipmapped_array(options):
     shape_t = opts.shape
 
     cdef cydriver.CUarray_format c_format = <cydriver.CUarray_format>_ARRAYFORMAT_TO_CU[opts.format]
-    cdef cydriver.CUDA_ARRAY3D_DESCRIPTOR desc3d
     cdef int rank = len(shape_t)
     cdef unsigned int flags = (
         cydriver.CUDA_ARRAY3D_SURFACE_LDST if opts.is_surface_load_store else 0
@@ -210,15 +210,17 @@ def _create_mipmapped_array(options):
 
     # Mipmap creation uses the 3D descriptor regardless of rank; lower-rank
     # shapes use Height=0/Depth=0 sentinels, matching cuArray3DCreate.
-    memset(&desc3d, 0, sizeof(desc3d))
-    desc3d.Width = <size_t>shape_t[0]
-    desc3d.Height = <size_t>(shape_t[1] if rank >= 2 else 0)
-    desc3d.Depth = <size_t>(shape_t[2] if rank >= 3 else 0)
-    desc3d.Format = c_format
-    desc3d.NumChannels = <unsigned int>opts.num_channels
-    desc3d.Flags = flags
-
-    cdef MipmappedArrayHandle h = create_mipmapped_array_handle(desc3d, c_levels)
+    cdef cydriver.CUDA_ARRAY3D_DESCRIPTOR desc3d = cydriver.CUDA_ARRAY3D_DESCRIPTOR(
+        Width=<size_t>shape_t[0],
+        Height=<size_t>(shape_t[1] if rank >= 2 else 0),
+        Depth=<size_t>(shape_t[2] if rank >= 3 else 0),
+        Format=c_format,
+        NumChannels=<unsigned int>opts.num_channels,
+        Flags=flags,
+    )
+
+    cdef MipmappedArrayHandle h = create_mipmapped_array_handle(
+        ctx._h_context, desc3d, c_levels)
     if not h:
         HANDLE_RETURN(get_last_error())
 
@@ -229,5 +231,5 @@ def _create_mipmapped_array(options):
     self._num_channels = opts.num_channels
     self._num_levels = <unsigned int>opts.num_levels
     self._surface_load_store = bool(opts.is_surface_load_store)
-    self._device_id = _get_current_device_id()
+    self._device_id = device_id
     return self
diff --git a/cuda_core/cuda/core/texture/_surface.pyi b/cuda_core/cuda/core/texture/_surface.pyi
index 977268abd5f..ff92f1edce2 100644
--- a/cuda_core/cuda/core/texture/_surface.pyi
+++ b/cuda_core/cuda/core/texture/_surface.pyi
@@ -1,6 +1,6 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/texture/_surface.pyx
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/texture/_surface.pyx
 
-from __future__ import annotations
+from cuda.core._context import Context
 
 
 class SurfaceObject:
@@ -19,44 +19,34 @@ class SurfaceObject:
 
     .. versionadded:: 1.1.0
     """
-
-    def close(self):
-        """Release this object's reference to the underlying ``CUsurfObject``.
-
-        Destruction (``cuSurfObjectDestroy``) and release of the backing array
-        happen via the handle's deleter when the last reference is dropped.
-        Idempotent.
-        """
-
-    def __init__(self, *args, **kwargs):
-        ...
-
+    def __init__(self, *args, **kwargs): ...
     @property
     def handle(self):
         """The underlying ``CUsurfObject`` as an integer (64-bit kernel arg)."""
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this surface object has been closed."""
     @property
     def resource(self):
         """The :class:`ResourceDescriptor` this surface was built from."""
-
     @property
-    def device(self):
-        ...
-
-    def __enter__(self):
-        ...
-
-    def __exit__(self, exc_type, exc, tb):
-        ...
+    def device(self): ...
+    def close(self):
+        """Release this object's reference to the underlying ``CUsurfObject``.
 
-    def __repr__(self):
-        ...
+        Destruction (``cuSurfObjectDestroy``) and release of the backing array
+        happen via the handle's deleter when the last reference is dropped.
+        Idempotent.
+        """
+    def __enter__(self): ...
+    def __exit__(self, exc_type, exc, tb): ...
+    def __repr__(self): ...
 
-def _create_surface_object(resource):
-    """Create a :class:`SurfaceObject` on the current device.
+def _create_surface_object(resource, ctx: Context, device_id: int):
+    """Create a :class:`SurfaceObject` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_surface_object`. ``resource`` must be a
     :class:`ResourceDescriptor` wrapping an :class:`OpaqueArray` allocated with
     ``is_surface_load_store=True``; linear/pitch2d resources are not valid
     surface backings.
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/texture/_surface.pyx b/cuda_core/cuda/core/texture/_surface.pyx
index ac61fddd357..790ce048ecd 100644
--- a/cuda_core/cuda/core/texture/_surface.pyx
+++ b/cuda_core/cuda/core/texture/_surface.pyx
@@ -7,19 +7,19 @@ from __future__ import annotations
 from libc.string cimport memset
 
 from cuda.bindings cimport cydriver
-from cuda.core.texture._array cimport OpaqueArray
+from cuda.core._context cimport Context
+from cuda.core.texture._array cimport OpaqueArray, OpaqueArray_check_open
 from cuda.core._resource_handles cimport (
+    ContextHandle,
     SurfObjectHandle,
     as_cu,
     as_intptr,
     create_surf_object_handle,
+    get_array_context,
     get_last_error,
 )
 from cuda.core.texture._texture import ResourceDescriptor
-from cuda.core._utils.cuda_utils cimport (
-    HANDLE_RETURN,
-    _get_current_device_id,
-)
+from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 
 
 cdef class SurfaceObject:
@@ -50,6 +50,11 @@ cdef class SurfaceObject:
         """The underlying ``CUsurfObject`` as an integer (64-bit kernel arg)."""
         return as_intptr(self._handle)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this surface object has been closed."""
+        return self._handle.get() == NULL
+
     @property
     def resource(self):
         """The :class:`ResourceDescriptor` this surface was built from."""
@@ -80,8 +85,8 @@ cdef class SurfaceObject:
         return f"SurfaceObject(handle=0x{as_intptr(self._handle):x})"
 
 
-def _create_surface_object(resource):
-    """Create a :class:`SurfaceObject` on the current device.
+def _create_surface_object(resource, Context ctx, int device_id):
+    """Create a :class:`SurfaceObject` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_surface_object`. ``resource`` must be a
     :class:`ResourceDescriptor` wrapping an :class:`OpaqueArray` allocated with
@@ -100,6 +105,15 @@ def _create_surface_object(resource):
         )
 
     cdef OpaqueArray arr = <OpaqueArray>resource.source
+    OpaqueArray_check_open(arr)
+    if arr._device_id != device_id:
+        raise ValueError(
+            f"resource belongs to device {arr._device_id}, "
+            f"but surface creation was requested on device {device_id}"
+        )
+    cdef ContextHandle resource_context = get_array_context(arr._handle)
+    if resource_context and as_cu(resource_context) != as_cu(ctx._h_context):
+        raise ValueError("resource is not compatible with this Device object")
     if not arr.is_surface_load_store:
         raise ValueError(
             "OpaqueArray must be created with is_surface_load_store=True to be "
@@ -111,12 +125,13 @@ def _create_surface_object(resource):
     res_desc.resType = cydriver.CU_RESOURCE_TYPE_ARRAY
     res_desc.res.array.hArray = as_cu(arr._handle)
 
-    cdef SurfObjectHandle h = create_surf_object_handle(res_desc, arr._handle)
+    cdef SurfObjectHandle h = create_surf_object_handle(
+        ctx._h_context, res_desc, arr._handle)
     if not h:
         HANDLE_RETURN(get_last_error())
 
     cdef SurfaceObject self = SurfaceObject.__new__(SurfaceObject)
     self._handle = h
     self._source_ref = resource
-    self._device_id = _get_current_device_id()
+    self._device_id = device_id
     return self
diff --git a/cuda_core/cuda/core/texture/_texture.pyi b/cuda_core/cuda/core/texture/_texture.pyi
index 7840585bb4d..50c9bb50816 100644
--- a/cuda_core/cuda/core/texture/_texture.pyi
+++ b/cuda_core/cuda/core/texture/_texture.pyi
@@ -1,12 +1,18 @@
-# This file was generated by stubgen-pyx v0.2.6 from cuda_core/cuda/core/texture/_texture.pyx
-
-from __future__ import annotations
+# This file was generated by stubgen-pyx v0.2.22 from cuda_core/cuda/core/texture/_texture.pyx
 
 from dataclasses import dataclass
 
 from cuda.bindings import cydriver
+from cuda.core._context import Context
 from cuda.core.typing import AddressModeType, FilterModeType, ReadModeType
 
+_TRSF_READ_AS_INTEGER = 1
+_TRSF_NORMALIZED_COORDINATES = 2
+_TRSF_SRGB = 16
+_TRSF_DISABLE_TRILINEAR_OPTIMIZATION = 32
+_TRSF_SEAMLESS_CUBEMAP = 64
+_ADDRESSMODE_TO_CU = {AddressModeType.WRAP: int(cydriver.CU_TR_ADDRESS_MODE_WRAP), AddressModeType.CLAMP: int(cydriver.CU_TR_ADDRESS_MODE_CLAMP), AddressModeType.MIRROR: int(cydriver.CU_TR_ADDRESS_MODE_MIRROR), AddressModeType.BORDER: int(cydriver.CU_TR_ADDRESS_MODE_BORDER)}
+_FILTERMODE_TO_CU = {FilterModeType.POINT: int(cydriver.CU_TR_FILTER_MODE_POINT), FilterModeType.LINEAR: int(cydriver.CU_TR_FILTER_MODE_LINEAR)}
 
 class ResourceDescriptor:
     """Describes the memory backing a :class:`TextureObject`.
@@ -30,13 +36,10 @@ class ResourceDescriptor:
     """
     __slots__ = ('_kind', '_source', '_format', '_num_channels', '_size_bytes', '_width', '_height', '_pitch_bytes')
 
-    def __init__(self):
-        ...
-
+    def __init__(self): ...
     @classmethod
     def from_opaque_array(cls, array):
         """Build a resource descriptor backed by a :class:`OpaqueArray`."""
-
     @classmethod
     def from_mipmapped_array(cls, mipmapped_array):
         """Build a resource descriptor backed by a :class:`MipmappedArray`.
@@ -46,7 +49,6 @@ class ResourceDescriptor:
         require a single :class:`OpaqueArray` level (obtain via
         :meth:`MipmappedArray.get_level`).
         """
-
     @classmethod
     def from_linear(cls, buffer, *, format, num_channels, size_bytes=None):
         """Build a resource descriptor for a linear (typed 1D) texture fetch.
@@ -71,7 +73,6 @@ class ResourceDescriptor:
         :class:`TextureObjectOptions` addressing/filtering fields — kernels read
         through a typed 1D fetch with bounds checking only.
         """
-
     @classmethod
     def from_pitch2d(cls, buffer, *, format, num_channels, width, height, pitch_bytes):
         """Build a resource descriptor for a row-pitched 2D image.
@@ -95,41 +96,29 @@ class ResourceDescriptor:
             ``width * format_size * num_channels`` and meet the driver's
             ``CU_DEVICE_ATTRIBUTE_TEXTURE_PITCH_ALIGNMENT``.
         """
-
     @property
-    def kind(self):
-        ...
-
+    def kind(self): ...
     @property
-    def source(self):
-        ...
-
+    def source(self): ...
     @property
     def format(self):
         """The element :class:`~cuda.core.typing.ArrayFormatType` (``None`` for array-backed)."""
-
     @property
     def num_channels(self):
         """Channels per element (``None`` for array-backed)."""
-
     @property
     def size_bytes(self):
         """Bytes bound for a linear resource (``None`` for other kinds)."""
-
     @property
     def width(self):
         """Pitch2D image width, in elements (``None`` for other kinds)."""
-
     @property
     def height(self):
         """Pitch2D image height, in rows (``None`` for other kinds)."""
-
     @property
     def pitch_bytes(self):
         """Pitch2D row pitch, in bytes (``None`` for other kinds)."""
-
-    def __repr__(self):
-        ...
+    def __repr__(self): ...
 
 @dataclass
 class TextureObjectOptions:
@@ -182,8 +171,7 @@ class TextureObjectOptions:
     max_mipmap_level_clamp: float = 0.0
     border_color: tuple[float, ...] | None = None
 
-    def __post_init__(self):
-        ...
+    def __post_init__(self): ...
 
 class TextureObject:
     """A bindless texture handle for kernel-side sampled reads.
@@ -197,61 +185,41 @@ class TextureObject:
 
     .. versionadded:: 1.1.0
     """
-
-    def close(self):
-        """Release this object's reference to the underlying ``CUtexObject``.
-
-        Destruction (``cuTexObjectDestroy``) and release of the backing resource
-        happen via the handle's deleter when the last reference is dropped.
-        Idempotent.
-        """
-
-    def __init__(self, *args, **kwargs):
-        ...
-
+    def __init__(self, *args, **kwargs): ...
     @property
     def handle(self):
         """The underlying ``CUtexObject`` as an integer (64-bit kernel arg)."""
-
+    @property
+    def is_closed(self) -> bool:
+        """Whether this texture object has been closed."""
     @property
     def resource(self):
         """The :class:`ResourceDescriptor` this texture was built from."""
-
     @property
     def options(self):
         """The :class:`TextureObjectOptions` this texture was built from."""
-
     @property
-    def device(self):
-        ...
-
-    def __enter__(self):
-        ...
-
-    def __exit__(self, exc_type, exc, tb):
-        ...
+    def device(self): ...
+    def close(self):
+        """Release this object's reference to the underlying ``CUtexObject``.
 
-    def __repr__(self):
-        ...
-_TRSF_READ_AS_INTEGER = 1
-_TRSF_NORMALIZED_COORDINATES = 2
-_TRSF_SRGB = 16
-_TRSF_DISABLE_TRILINEAR_OPTIMIZATION = 32
-_TRSF_SEAMLESS_CUBEMAP = 64
-_ADDRESSMODE_TO_CU = {AddressModeType.WRAP: int(cydriver.CU_TR_ADDRESS_MODE_WRAP), AddressModeType.CLAMP: int(cydriver.CU_TR_ADDRESS_MODE_CLAMP), AddressModeType.MIRROR: int(cydriver.CU_TR_ADDRESS_MODE_MIRROR), AddressModeType.BORDER: int(cydriver.CU_TR_ADDRESS_MODE_BORDER)}
-_FILTERMODE_TO_CU = {FilterModeType.POINT: int(cydriver.CU_TR_FILTER_MODE_POINT), FilterModeType.LINEAR: int(cydriver.CU_TR_FILTER_MODE_LINEAR)}
+        Destruction (``cuTexObjectDestroy``) and release of the backing resource
+        happen via the handle's deleter when the last reference is dropped.
+        Idempotent.
+        """
+    def __enter__(self): ...
+    def __exit__(self, exc_type, exc, tb): ...
+    def __repr__(self): ...
 
 def _normalize_enum(name, value, enum_type):
     """Coerce ``value`` to ``enum_type`` (a StrEnum), accepting a plain str."""
-
 def _normalize_address_modes(address_mode):
     """Return a 3-tuple of :class:`AddressModeType` values from a scalar or
     1-3 tuple. Individual entries may be plain strings."""
-
-def _create_texture_object(resource, options):
-    """Create a :class:`TextureObject` on the current device.
+def _create_texture_object(resource, options, ctx: Context, device_id: int):
+    """Create a :class:`TextureObject` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_texture_object`. ``resource`` is a
     :class:`ResourceDescriptor`; ``options`` is a :class:`TextureObjectOptions`
     (or a mapping accepted by it).
-    """
\ No newline at end of file
+    """
diff --git a/cuda_core/cuda/core/texture/_texture.pyx b/cuda_core/cuda/core/texture/_texture.pyx
index 8d09c727c31..28ddf2d6aa8 100644
--- a/cuda_core/cuda/core/texture/_texture.pyx
+++ b/cuda_core/cuda/core/texture/_texture.pyx
@@ -8,29 +8,30 @@ from libc.stdint cimport intptr_t
 from libc.string cimport memset
 
 from cuda.bindings cimport cydriver
-from cuda.core.texture._array cimport OpaqueArray
+from cuda.core._context cimport Context
+from cuda.core.texture._array cimport OpaqueArray, OpaqueArray_check_open
 from cuda.core.texture._array import (
     _ARRAYFORMAT_TO_CU,
     _CU_TO_ARRAYFORMAT,
     _FORMAT_ELEM_SIZE,
     _validate_format_channels,
 )
-from cuda.core._memory._buffer cimport Buffer
-from cuda.core.texture._mipmapped_array cimport MipmappedArray
+from cuda.core._memory._buffer cimport Buffer, Buffer_check_open
+from cuda.core.texture._mipmapped_array cimport MipmappedArray, MipmappedArray_check_open
 from cuda.core.texture._mipmapped_array import MipmappedArray as _PyMipmappedArray
 from cuda.core._resource_handles cimport (
+    ContextHandle,
     TexObjectHandle,
     as_cu,
     as_intptr,
     create_tex_object_handle_array,
     create_tex_object_handle_linear,
     create_tex_object_handle_mipmap,
+    get_array_context,
     get_last_error,
+    get_mipmapped_array_context,
 )
-from cuda.core._utils.cuda_utils cimport (
-    HANDLE_RETURN,
-    _get_current_device_id,
-)
+from cuda.core._utils.cuda_utils cimport HANDLE_RETURN
 
 from cuda.core.typing import AddressModeType, FilterModeType, ReadModeType
 
@@ -112,6 +113,7 @@ class ResourceDescriptor:
         """Build a resource descriptor backed by a :class:`OpaqueArray`."""
         if not isinstance(array, OpaqueArray):
             raise TypeError(f"array must be a OpaqueArray, got {type(array).__name__}")
+        OpaqueArray_check_open(<OpaqueArray>array)
         self = cls.__new__(cls)
         self._kind = "array"
         self._source = array
@@ -137,6 +139,7 @@ class ResourceDescriptor:
                 f"mipmapped_array must be a MipmappedArray, got "
                 f"{type(mipmapped_array).__name__}"
             )
+        MipmappedArray_check_open(<MipmappedArray>mipmapped_array)
         self = cls.__new__(cls)
         self._kind = "mipmapped_array"
         self._source = mipmapped_array
@@ -174,6 +177,7 @@ class ResourceDescriptor:
         """
         if not isinstance(buffer, Buffer):
             raise TypeError(f"buffer must be a Buffer, got {type(buffer).__name__}")
+        Buffer_check_open(<Buffer>buffer)
         fmt = _validate_format_channels(format, num_channels)
         cu_format = _ARRAYFORMAT_TO_CU[fmt]
 
@@ -235,6 +239,7 @@ class ResourceDescriptor:
         """
         if not isinstance(buffer, Buffer):
             raise TypeError(f"buffer must be a Buffer, got {type(buffer).__name__}")
+        Buffer_check_open(<Buffer>buffer)
         fmt = _validate_format_channels(format, num_channels)
         cu_format = _ARRAYFORMAT_TO_CU[fmt]
 
@@ -430,6 +435,11 @@ cdef class TextureObject:
         """The underlying ``CUtexObject`` as an integer (64-bit kernel arg)."""
         return as_intptr(self._handle)
 
+    @property
+    def is_closed(self) -> bool:
+        """Whether this texture object has been closed."""
+        return self._handle.get() == NULL
+
     @property
     def resource(self):
         """The :class:`ResourceDescriptor` this texture was built from."""
@@ -465,8 +475,9 @@ cdef class TextureObject:
         return f"TextureObject(handle=0x{as_intptr(self._handle):x})"
 
 
-def _create_texture_object(resource, options):
-    """Create a :class:`TextureObject` on the current device.
+def _create_texture_object(
+        resource, options, Context ctx, int device_id):
+    """Create a :class:`TextureObject` on the specified device.
 
     Backs :meth:`cuda.core.Device.create_texture_object`. ``resource`` is a
     :class:`ResourceDescriptor`; ``options`` is a :class:`TextureObjectOptions`
@@ -491,16 +502,26 @@ def _create_texture_object(resource, options):
     cdef MipmappedArray mip
     cdef Buffer buf
     cdef intptr_t devptr
+    cdef ContextHandle resource_context
+    cdef int resource_device_id
     if resource.kind == "array":
         arr = <OpaqueArray>resource.source
+        OpaqueArray_check_open(arr)
+        resource_context = get_array_context(arr._handle)
+        resource_device_id = arr._device_id
         res_desc.resType = cydriver.CU_RESOURCE_TYPE_ARRAY
         res_desc.res.array.hArray = as_cu(arr._handle)
     elif resource.kind == "mipmapped_array":
         mip = <MipmappedArray>resource.source
+        MipmappedArray_check_open(mip)
+        resource_context = get_mipmapped_array_context(mip._handle)
+        resource_device_id = mip._device_id
         res_desc.resType = cydriver.CU_RESOURCE_TYPE_MIPMAPPED_ARRAY
         res_desc.res.mipmap.hMipmappedArray = as_cu(mip._handle)
     elif resource.kind == "linear":
         buf = <Buffer>resource.source
+        Buffer_check_open(buf)
+        resource_device_id = buf.device_id  # -1 for memory not bound to a device
         devptr = int(buf.handle)
         res_desc.resType = cydriver.CU_RESOURCE_TYPE_LINEAR
         res_desc.res.linear.devPtr = <cydriver.CUdeviceptr>devptr
@@ -509,6 +530,8 @@ def _create_texture_object(resource, options):
         res_desc.res.linear.sizeInBytes = <size_t>resource._size_bytes
     elif resource.kind == "pitch2d":
         buf = <Buffer>resource.source
+        Buffer_check_open(buf)
+        resource_device_id = buf.device_id  # -1 for memory not bound to a device
         devptr = int(buf.handle)
         res_desc.resType = cydriver.CU_RESOURCE_TYPE_PITCH2D
         res_desc.res.pitch2D.devPtr = <cydriver.CUdeviceptr>devptr
@@ -521,6 +544,13 @@ def _create_texture_object(resource, options):
         raise NotImplementedError(
             f"ResourceDescriptor kind {resource.kind!r} is not yet supported"
         )
+    if resource_device_id >= 0 and resource_device_id != device_id:
+        raise ValueError(
+            f"resource belongs to device {resource_device_id}, "
+            f"but texture creation was requested on device {device_id}"
+        )
+    if resource_context and as_cu(resource_context) != as_cu(ctx._h_context):
+        raise ValueError("resource is not compatible with this Device object")
 
     # --- Texture descriptor ---
     # filter_mode/read_mode/mipmap_filter_mode are normalized to their
@@ -572,11 +602,14 @@ def _create_texture_object(resource, options):
 
     cdef TexObjectHandle h
     if resource.kind == "array":
-        h = create_tex_object_handle_array(res_desc, tex_desc, arr._handle)
+        h = create_tex_object_handle_array(
+            ctx._h_context, res_desc, tex_desc, arr._handle)
     elif resource.kind == "mipmapped_array":
-        h = create_tex_object_handle_mipmap(res_desc, tex_desc, mip._handle)
+        h = create_tex_object_handle_mipmap(
+            ctx._h_context, res_desc, tex_desc, mip._handle)
     else:  # linear or pitch2d — both backed by a device Buffer
-        h = create_tex_object_handle_linear(res_desc, tex_desc, buf._h_ptr)
+        h = create_tex_object_handle_linear(
+            ctx._h_context, res_desc, tex_desc, buf._h_ptr)
     if not h:
         HANDLE_RETURN(get_last_error())
 
@@ -584,5 +617,5 @@ def _create_texture_object(resource, options):
     self._handle = h
     self._source_ref = resource
     self._options = opts
-    self._device_id = _get_current_device_id()
+    self._device_id = device_id
     return self
diff --git a/cuda_core/cuda/core/utils/__init__.py b/cuda_core/cuda/core/utils/__init__.py
index 93a4c14c083..bc0a38f2b40 100644
--- a/cuda_core/cuda/core/utils/__init__.py
+++ b/cuda_core/cuda/core/utils/__init__.py
@@ -2,6 +2,12 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
+from cuda.core._memory._copy_enums import (
+    CopyOptions,
+    MemcpyOverlapMode,
+    MemcpySrcAccessOrder,
+)
+from cuda.core._memory._copy_ops import copy_batch
 from cuda.core._memory._managed_memory_ops import (
     discard_batch,
     discard_prefetch_batch,
@@ -19,11 +25,15 @@
 )
 
 __all__ = [
+    "CopyOptions",
     "FileStreamProgramCache",
     "InMemoryProgramCache",
+    "MemcpyOverlapMode",
+    "MemcpySrcAccessOrder",
     "ProgramCacheResource",
     "StridedMemoryView",
     "args_viewable_as_strided_memory",
+    "copy_batch",
     "discard_batch",
     "discard_prefetch_batch",
     "make_program_cache_key",
diff --git a/cuda_core/cuda/core/utils/_cache_dir.py b/cuda_core/cuda/core/utils/_cache_dir.py
new file mode 100644
index 00000000000..2981db14da3
--- /dev/null
+++ b/cuda_core/cuda/core/utils/_cache_dir.py
@@ -0,0 +1,41 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""Shared user-cache-root resolution for cuda.core's on-disk caches."""
+
+from __future__ import annotations
+
+import os
+from pathlib import Path
+
+# Exposed as a module-level flag so tests can toggle it without monkeypatching
+# ``os.name`` itself (pathlib reads ``os.name`` at instantiation time).
+_IS_WINDOWS = os.name == "nt"
+
+
+def _default_cache_dir() -> Path:
+    """OS-conventional root for cuda.core's on-disk caches.
+
+    Resolves to the user-cache root for the calling user, with a
+    ``cuda-python`` vendor leaf so callers can each place their own cache
+    under a stable, shared root:
+
+    * Linux: ``$XDG_CACHE_HOME/cuda-python``
+      (default ``~/.cache/cuda-python`` per the XDG Base Directory spec).
+    * Windows: ``%LOCALAPPDATA%\\cuda-python``
+      (Windows uses local AppData -- caches don't roam; falls back to
+      ``~/AppData/Local`` if the env var is unset).
+
+    CUDA does not support macOS, so no macOS branch is provided.
+
+    Callers append their own leaf directory, e.g. ``program-cache`` or
+    ``nvrtc-headers``.
+    """
+    if _IS_WINDOWS:
+        local_app_data = os.environ.get("LOCALAPPDATA")
+        root = Path(local_app_data) if local_app_data else Path.home() / "AppData" / "Local"
+    else:
+        xdg = os.environ.get("XDG_CACHE_HOME")
+        root = Path(xdg) if xdg else Path.home() / ".cache"
+    return root / "cuda-python"
diff --git a/cuda_core/cuda/core/utils/_program_cache/_file_stream.py b/cuda_core/cuda/core/utils/_program_cache/_file_stream.py
index eb71abf5446..314c7b612bc 100644
--- a/cuda_core/cuda/core/utils/_program_cache/_file_stream.py
+++ b/cuda_core/cuda/core/utils/_program_cache/_file_stream.py
@@ -23,6 +23,7 @@
 from typing import Any, Callable, Iterable
 
 from cuda.core._module import ObjectCode
+from cuda.core.utils._cache_dir import _default_cache_dir as _user_cache_dir
 
 from ._abc import ProgramCacheResource, _as_key_bytes, _extract_bytes
 
@@ -57,28 +58,10 @@ def _stat_key(st: os.stat_result) -> tuple[int, int, int]:
 
 
 def _default_cache_dir() -> Path:
-    """OS-conventional default location for the file-stream cache.
-
-    Resolves to the user-cache root for the calling user, with a
-    ``program-cache`` leaf so future tooling can place sibling caches
-    under the same ``cuda-python`` vendor directory:
-
-    * Linux: ``$XDG_CACHE_HOME/cuda-python/program-cache``
-      (default ``~/.cache/cuda-python/program-cache`` per the XDG Base
-      Directory spec).
-    * Windows: ``%LOCALAPPDATA%\\cuda-python\\program-cache``
-      (Windows uses local AppData -- caches don't roam; falls back to
-      ``~/AppData/Local`` if the env var is unset).
-
-    CUDA does not support macOS, so no macOS branch is provided.
+    """Default location for the file-stream cache: the ``program-cache`` leaf under the shared
+    ``cuda-python`` user-cache root (see :func:`cuda.core.utils._cache_dir._default_cache_dir`).
     """
-    if _IS_WINDOWS:
-        local_app_data = os.environ.get("LOCALAPPDATA")
-        root = Path(local_app_data) if local_app_data else Path.home() / "AppData" / "Local"
-    else:
-        xdg = os.environ.get("XDG_CACHE_HOME")
-        root = Path(xdg) if xdg else Path.home() / ".cache"
-    return root / "cuda-python" / "program-cache"
+    return _user_cache_dir() / "program-cache"
 
 
 def _with_sharing_retry(
diff --git a/cuda_core/cuda/core/utils/_program_cache/_keys.py b/cuda_core/cuda/core/utils/_program_cache/_keys.py
index e170bc18131..2df2d893835 100644
--- a/cuda_core/cuda/core/utils/_program_cache/_keys.py
+++ b/cuda_core/cuda/core/utils/_program_cache/_keys.py
@@ -499,6 +499,11 @@ def validate(self, options: ProgramOptions, target_type: str, extra_digest: byte
             raise ValueError(
                 "extra_sources is only valid for code_type='nvvm'; Program() rejects it for code_type='ptx'."
             )
+        # ``numba_debug`` is deliberately not rejected here and is absent from
+        # ``_LINKER_FIELD_GATES``: for PTX inputs the linker ignores it (with a
+        # warning from ``_translate_program_options``), so it cannot change the
+        # generated code and must not perturb the key. Two PTX compiles that
+        # differ only in ``numba_debug`` are the same compile.
         # PTX compiles go through the Linker. When the driver (cuLink)
         # backend is selected (nvJitLink unavailable), ``Program.compile``
         # rejects a subset of options that nvJitLink would accept; reject
diff --git a/cuda_core/docs/nv-versions.json b/cuda_core/docs/nv-versions.json
index a81563a3bfa..3bcd163e39b 100644
--- a/cuda_core/docs/nv-versions.json
+++ b/cuda_core/docs/nv-versions.json
@@ -3,6 +3,14 @@
         "version": "latest",
         "url": "https://nvidia.github.io/cuda-python/cuda-core/latest/"
     },
+    {
+        "version": "1.2.0",
+        "url": "https://nvidia.github.io/cuda-python/cuda-core/1.2.0/"
+    },
+    {
+        "version": "1.1.1",
+        "url": "https://nvidia.github.io/cuda-python/cuda-core/1.1.1/"
+    },
     {
         "version": "1.1.0",
         "url": "https://nvidia.github.io/cuda-python/cuda-core/1.1.0/"
diff --git a/cuda_core/docs/source/api.rst b/cuda_core/docs/source/api.rst
index 089e68576c9..5ee34d34f54 100644
--- a/cuda_core/docs/source/api.rst
+++ b/cuda_core/docs/source/api.rst
@@ -77,6 +77,14 @@ Memory management
    ManagedMemoryResourceOptions
    VirtualMemoryResourceOptions
 
+A :class:`Buffer` records the stream that will order its eventual deallocation.
+Use :meth:`Buffer.set_deallocation_stream` to replace that stream without
+closing the buffer. Changing the recorded stream does not synchronize streams;
+the caller must order allocation and every access before the deallocation,
+using events or other CUDA synchronization mechanisms as needed. See
+:cuda-core-example:`buffer_deallocation_stream.py <buffer_deallocation_stream.py>`
+for a complete example.
+
 
 CUDA compilation toolchain
 --------------------------
@@ -154,6 +162,22 @@ Every graph node is a subclass of :class:`~graph.GraphNode`, which
 provides the common interface (dependencies, successors, destruction).
 Each subclass exposes attributes unique to its operation type.
 
+Parameter-bearing definition nodes expose subclass-specific ``update()``
+methods: :class:`~graph.KernelNode`, :class:`~graph.MemcpyNode`,
+:class:`~graph.MemsetNode`, :class:`~graph.ChildGraphNode`,
+:class:`~graph.EventRecordNode`, :class:`~graph.EventWaitNode`, and
+:class:`~graph.HostCallbackNode`. These methods require CUDA driver and
+``cuda.bindings`` versions 12.2 or newer. Updates affect future graph
+instantiations; executable graphs that were already instantiated continue
+using their previous parameters and retained resources. Omitted optional
+arguments preserve their current values where supported.
+On CUDA 12.2 through 13.1, the intended CUDA context must be current when
+updating memcpy or memset nodes. CUDA driver and ``cuda.bindings`` versions
+13.2 and newer preserve the recorded context automatically.
+Multidimensional or array-backed memcpy nodes and clustered or cooperative
+kernel nodes cannot currently be updated. Clustered and cooperative kernel
+nodes also cannot currently be constructed explicitly.
+
 .. autosummary::
    :toctree: generated/
 
@@ -175,6 +199,41 @@ Each subclass exposes attributes unique to its operation type.
    graph.WhileNode
    graph.SwitchNode
 
+Executable node views
+`````````````````````
+
+Index an executable :class:`~graph.Graph` with a definition node to update that
+node in the executable, for example
+``graph[kernel_node].update(config=config, kernel=kernel, args=args)``.
+The returned view retains the executable and source node, while CUDA validates
+that the node is associated with the executable.
+
+Executable graphs do not support reading back current node parameters, so
+updates take a complete replacement. Buffer operands, kernels, events, kernel
+arguments, and callback bindings are retained for every future launch that may
+use them. Superseded resources remain retained until a successful whole-graph
+update or executable destruction. Raw integer addresses remain caller-owned.
+Memcpy and memset updates use the current CUDA context, which must match the
+original node context.
+
+Kernel, memcpy, and memset views also provide ``is_enabled``, ``enable()``, and
+``disable()``. Executable-node updates require CUDA driver and
+``cuda.bindings`` versions 12.2 or newer.
+
+.. autosummary::
+   :toctree: generated/
+
+   :template: autosummary/cyclass.rst
+
+   graph.ExecutableGraphNode
+   graph.ExecutableKernelNode
+   graph.ExecutableMemcpyNode
+   graph.ExecutableMemsetNode
+   graph.ExecutableHostCallbackNode
+   graph.ExecutableChildGraphNode
+   graph.ExecutableEventRecordNode
+   graph.ExecutableEventWaitNode
+
 
 Graphics interoperability
 -------------------------
@@ -326,6 +385,7 @@ Utility functions
    :toctree: generated/
 
    utils.args_viewable_as_strided_memory
+   utils.copy_batch
    utils.prefetch_batch
    utils.discard_batch
    utils.discard_prefetch_batch
@@ -333,3 +393,20 @@ Utility functions
    :template: autosummary/cyclass.rst
 
    utils.StridedMemoryView
+
+Data transfer options
+`````````````````````
+
+.. currentmodule:: cuda.core
+
+.. autosummary::
+   :toctree: generated/
+
+   :template: dataclass.rst
+
+   utils.CopyOptions
+
+   :template: class.rst
+
+   utils.MemcpySrcAccessOrder
+   utils.MemcpyOverlapMode
diff --git a/cuda_core/docs/source/api_nvml.rst b/cuda_core/docs/source/api_nvml.rst
index 7780dd6086e..c96b68ab701 100644
--- a/cuda_core/docs/source/api_nvml.rst
+++ b/cuda_core/docs/source/api_nvml.rst
@@ -45,3 +45,11 @@ Types
 
    Device
    NvlinkInfo
+
+Constants
+---------
+
+.. autosummary::
+   :toctree: generated/
+
+   CUDA_BINDINGS_NVML_IS_COMPATIBLE
diff --git a/cuda_core/docs/source/api_private.rst b/cuda_core/docs/source/api_private.rst
index 907fc2f5bcf..80675799c07 100644
--- a/cuda_core/docs/source/api_private.rst
+++ b/cuda_core/docs/source/api_private.rst
@@ -40,11 +40,12 @@ CUDA runtime
    typing.VirtualMemoryGranularityType
    typing.VirtualMemoryHandleType
    typing.VirtualMemoryLocationType
+   typing.WorkqueueSharingScopeType
 
    :template: autosummary/cyclass.rst
 
+   DeviceResources
    _device.DeviceProperties
-   _device_resources.DeviceResources
    _memory._ipc.IPCAllocationHandle
    _memory._ipc.IPCBufferDescriptor
    _memory._managed_buffer.AccessedBySetProxy
@@ -125,3 +126,36 @@ NVML
    system.typing.TemperatureThresholds
    system.typing.ThermalController
    system.typing.ThermalTarget
+
+   system.NvmlError
+   system.UninitializedError
+   system.InvalidArgumentError
+   system.NotSupportedError
+   system.NoPermissionError
+   system.AlreadyInitializedError
+   system.NotFoundError
+   system.InsufficientSizeError
+   system.InsufficientPowerError
+   system.DriverNotLoadedError
+   system.TimeoutError
+   system.IrqIssueError
+   system.LibraryNotFoundError
+   system.FunctionNotFoundError
+   system.CorruptedInforomError
+   system.GpuIsLostError
+   system.ResetRequiredError
+   system.OperatingSystemError
+   system.LibRmVersionMismatchError
+   system.InUseError
+   system.MemoryError
+   system.NoDataError
+   system.VgpuEccNotSupportedError
+   system.InsufficientResourcesError
+   system.FreqNotSupportedError
+   system.ArgumentVersionMismatchError
+   system.DeprecatedError
+   system.NotReadyError
+   system.GpuNotFoundError
+   system.InvalidStateError
+   system.ResetTypeNotSupportedError
+   system.UnknownError
diff --git a/cuda_core/docs/source/environment_variables.rst b/cuda_core/docs/source/environment_variables.rst
index b9201abc505..b7e4418bb58 100644
--- a/cuda_core/docs/source/environment_variables.rst
+++ b/cuda_core/docs/source/environment_variables.rst
@@ -24,3 +24,10 @@ Runtime Environment Variables
   warnings about CUDA major version mismatches between ``cuda-bindings`` and
   the installed driver. This warning occurs when ``cuda-bindings`` was built
   for a newer CUDA major version than the installed driver supports.
+
+- ``CUDA_CORE_DONT_FIX_TAB_COMPLETION`` : When set to 1, ``import cuda.core``
+  does not patch the standard library's :mod:`rlcompleter` module. The patch
+  works around a CPython bug (fixed in Python 3.13.13, 3.14.6 and 3.15) that
+  makes tab completion fail on Cython properties, and it changes global
+  interpreter state; set this variable to opt out. Unset, empty, and ``0``
+  leave the patch enabled; any other value disables it.
diff --git a/cuda_core/docs/source/examples.rst b/cuda_core/docs/source/examples.rst
index cf13961c6dc..f5ae0c10300 100644
--- a/cuda_core/docs/source/examples.rst
+++ b/cuda_core/docs/source/examples.rst
@@ -39,6 +39,13 @@ Linking and graphs
 - :cuda-core-example:`cuda_graphs.py <cuda_graphs.py>`
   captures and replays a multi-kernel CUDA graph to reduce launch overhead.
 
+Memory management
+-----------------
+
+- :cuda-core-example:`buffer_deallocation_stream.py <buffer_deallocation_stream.py>`
+  transfers a buffer between streams and safely changes the stream that orders
+  its deallocation.
+
 Interoperability and memory access
 ----------------------------------
 
diff --git a/cuda_core/docs/source/install.rst b/cuda_core/docs/source/install.rst
index a49aab7c966..c048cfb2a2c 100644
--- a/cuda_core/docs/source/install.rst
+++ b/cuda_core/docs/source/install.rst
@@ -110,7 +110,7 @@ Development with uv
 
 .. code-block:: console
 
-   $ git clone https://github.com/NVIDIA/cuda-python
+   $ git clone https://github.com/NVIDIA/cuda-python.git
    $ cd cuda-python/cuda_core
    $ uv venv
    $ source .venv/bin/activate   # On Windows: .venv\Scripts\activate
@@ -132,7 +132,7 @@ From the repository root:
 
 .. code-block:: console
 
-   $ git clone https://github.com/NVIDIA/cuda-python
+   $ git clone https://github.com/NVIDIA/cuda-python.git
    $ cd cuda-python
    $ pixi run -e cu13 test-core
 
@@ -151,8 +151,18 @@ Installing from Source
 
 .. code-block:: console
 
-   $ git clone https://github.com/NVIDIA/cuda-python
+   $ git clone https://github.com/NVIDIA/cuda-python.git
    $ cd cuda-python/cuda_core
    $ pip install .
 
 ``cuda-bindings`` 12.x or 13.x is a required dependency.
+
+.. note::
+
+   The version is derived from git tags via ``setuptools-scm``, so the clone
+   must include tags reaching back to at least the latest ``cuda-core-v*`` tag.
+   Do not use ``--depth`` or ``--no-tags``: a shallow clone builds without
+   error but produces a bogus version such as ``0.1.dev1+g0d22cb444``. See
+   `Cloning the repository
+   <https://github.com/NVIDIA/cuda-python/blob/main/CONTRIBUTING.md>`_
+   for details and recovery steps.
diff --git a/cuda_core/docs/source/interoperability.rst b/cuda_core/docs/source/interoperability.rst
index 87347eb9d25..33d11d540c7 100644
--- a/cuda_core/docs/source/interoperability.rst
+++ b/cuda_core/docs/source/interoperability.rst
@@ -26,6 +26,10 @@ Conversely, if any GPU library already sets a device (or context) to current, th
 method ensures that the same device/context is picked up by and shared with
 ``cuda.core``.
 
+Other :class:`Device` methods do not change the current context. For example,
+``dev1.sync()`` synchronizes device 1 and leaves the current context unchanged,
+even when another device is current.
+
 
 ``__cuda_stream__`` protocol
 ----------------------------
diff --git a/cuda_core/docs/source/release/1.1.1-notes.rst b/cuda_core/docs/source/release/1.1.1-notes.rst
new file mode 100644
index 00000000000..66d74e3540b
--- /dev/null
+++ b/cuda_core/docs/source/release/1.1.1-notes.rst
@@ -0,0 +1,59 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. currentmodule:: cuda.core
+
+``cuda.core`` 1.1.1 Release Notes
+=================================
+
+
+New features
+------------
+
+- Added :meth:`ObjectCode.get_module` for interoperability with legacy
+  ``CUmodule``-based driver APIs. The method returns a context-dependent
+  ``CUmodule`` handle via ``cuLibraryGetModule``, bridging the newer
+  context-independent library API to existing code that expects a module.
+  (`#2339 <https://github.com/NVIDIA/cuda-python/pull/2339>`__)
+
+- ``cuda.core`` C++ headers are now included in source distributions and
+  installed wheels, making them available to downstream projects that extend
+  ``cuda.core`` at the C++ level.
+  (`#2236 <https://github.com/NVIDIA/cuda-python/pull/2236>`__)
+
+
+Fixes and enhancements
+----------------------
+
+- This cuda-core patch release was issued to be compatible with cuda-bindings
+  13.4.0b1.  Version strings that include PEP 440 pre-release suffixes (e.g.
+  ``0b1``) are now parsed correctly; previously they caused an ``ImportError``
+  on startup.
+
+- Graph nodes now properly retain per-node user-object attachments (kernel
+  argument buffers, host-callback functions and user data, and
+  memcpy/memset operands) for the full lifetime of the graph.
+  (`#2357 <https://github.com/NVIDIA/cuda-python/pull/2357>`__)
+
+- Graph user-object payload cleanup is now deferred to the main Python thread
+  via ``Py_AddPendingCall``, avoiding unsafe cross-thread Python object
+  destruction that could occur when CUDA invoked the destructor callback on an
+  internal driver thread.
+  (`#2371 <https://github.com/NVIDIA/cuda-python/pull/2371>`__)
+
+- The on-disk program cache directory is now created with owner-only
+  permissions (``0o700``) on POSIX systems, and those permissions are
+  re-asserted on each use.  This prevents other local users from reading or
+  injecting cached device code regardless of the process ``umask``.
+  (`#2399 <https://github.com/NVIDIA/cuda-python/pull/2399>`__)
+
+- DLPack: a ``NULL`` deleter in a ``DLManagedTensorVersioned`` capsule is now
+  handled correctly per the DLPack specification; previously it would cause a
+  crash.
+  (`#2427 <https://github.com/NVIDIA/cuda-python/pull/2427>`__)
+
+- Corrected NumPy version guards for writing into DLPack host arrays.  The
+  minimum required NumPy version for such writes is now correctly enforced as
+  2.2.5+; earlier NumPy versions return a read-only buffer
+  (``numpy GH#28632``) and would error rather than skip.
+  (`#2238 <https://github.com/NVIDIA/cuda-python/pull/2238>`__)
diff --git a/cuda_core/docs/source/release/1.2.0-notes.rst b/cuda_core/docs/source/release/1.2.0-notes.rst
index 6a047c9cfe8..dd1f3504e9a 100644
--- a/cuda_core/docs/source/release/1.2.0-notes.rst
+++ b/cuda_core/docs/source/release/1.2.0-notes.rst
@@ -6,9 +6,86 @@
 ``cuda.core`` 1.2.0 Release Notes
 ==================================
 
+New features
+------------
+
+- Added :class:`utils.CopyOptions` (source access order, location hints,
+  overlap mode) for buffer-to-buffer copies. The new
+  :func:`utils.copy_batch` accepts it and submits many copies in a single
+  ``cuMemcpyBatchAsync`` call, requiring ``cuda.core`` built against CUDA 13
+  plus ``cuda.bindings``/driver 13.0 or newer. :meth:`Buffer.copy_to` and
+  :meth:`Buffer.copy_from` also accept it now, as a new ``options`` keyword,
+  submitting a single copy via ``cuMemcpyWithAttributesAsync`` and requiring
+  ``cuda.bindings``/driver 13.2 or newer. Both reject
+  ``LEGACY_DEFAULT_STREAM`` with ``TypeError`` (``PER_THREAD_DEFAULT_STREAM``
+  is accepted); ``copy_batch`` always rejects graph capture, while
+  ``Buffer.copy_to``/``copy_from`` reject it only when ``options`` is given.
+  On an older ``cuda.bindings``/driver install, ``src_access_order`` values
+  of ``STREAM`` and ``ANY`` silently fall back to plain ``cuMemcpyAsync``;
+  ``DURING_API_CALL`` raises ``RuntimeError`` instead, since that fallback
+  cannot honor its guarantee that all source reads complete before the call
+  returns. Copies within a ``copy_batch`` call must not alias.
+  (`#1333 <https://github.com/NVIDIA/cuda-python/issues/1333>`__,
+  `#2365 <https://github.com/NVIDIA/cuda-python/issues/2365>`__)
+
+- Added the ``programmatic_stream_serialization`` option to
+  :class:`LaunchConfig`, which sets
+  ``cudaLaunchAttributeProgrammaticStreamSerialization`` so a kernel can
+  begin executing before the preceding kernel in the same stream has fully
+  completed (programmatic dependent launch, PDL). Available starting with
+  devices of compute capability 9.0.
+  (`#2456 <https://github.com/NVIDIA/cuda-python/pull/2456>`__,
+  `#1334 <https://github.com/NVIDIA/cuda-python/issues/1334>`__)
+
+- Added :attr:`ProgramOptions.use_bundled_headers`, which lets NVRTC
+  resolve the CUDA and CCCL headers from the toolkit bundled with NVRTC
+  itself, installed into a per-user cache directory, instead of requiring
+  a full CUDA Toolkit installation on the compile host. NVRTC backend
+  only; requires NVRTC 13.3 or newer.
+  (`#2753 <https://github.com/NVIDIA/cuda-python/pull/2753>`__,
+  closes `#2363 <https://github.com/NVIDIA/cuda-python/issues/2363>`__)
+
+- When a :class:`Program` is compiled with ``debug`` or ``lineinfo``,
+  the NVRTC input source is now materialized as a temporary ``.cu`` file
+  so ``cuda-gdb`` can list the original source while stepping through
+  JIT-compiled kernels. ``#include "..."`` search still resolves against
+  the original source directory.
+  (`#2678 <https://github.com/NVIDIA/cuda-python/pull/2678>`__,
+  `#2679 <https://github.com/NVIDIA/cuda-python/pull/2679>`__)
+
 Fixes and enhancements
 ----------------------
 
+- A :class:`Buffer` is now freed correctly even when the CUDA context current
+  at teardown is not the one it was allocated in, or when no context is current
+  at all. This happens routinely when a buffer is released by the garbage
+  collector on another thread or by deferred CUDA graph cleanup; previously the
+  free could fail or be skipped, leaking the allocation.
+  (`#2497 <https://github.com/NVIDIA/cuda-python/issues/2497>`__)
+
+- :meth:`Buffer.from_handle` and :meth:`ManagedBuffer.from_handle` accept a
+  keyword-only ``stream`` that records the stream used to order the buffer's
+  deallocation when the memory resource owns the pointer. It defaults to
+  ``default_stream()``, which requires a CUDA context to be current so the
+  free recipe can pin that context.
+  (`#2497 <https://github.com/NVIDIA/cuda-python/issues/2497>`__)
+
+- Added :meth:`Buffer.set_deallocation_stream` to change the stream that orders
+  a buffer's eventual deallocation without closing the buffer.
+  (`#2600 <https://github.com/NVIDIA/cuda-python/issues/2600>`__)
+
+- Closeable resource objects now report their state through ``is_closed``, while
+  graph definitions and nodes report their state through ``is_valid``. Active
+  operations reject closed or invalid resources, and cross-object APIs reject
+  them before passing a null handle to CUDA. Closing either default-stream
+  singleton remains a no-op because those process-wide tokens must stay valid.
+  (`#2627 <https://github.com/NVIDIA/cuda-python/issues/2627>`__)
+
+- Explicit calls to ``deallocate()`` on pool-backed memory resources and
+  :class:`GraphMemoryResource` now propagate errors from the underlying CUDA
+  free operation. Previously, these errors could be suppressed. Automatic
+  buffer cleanup remains non-raising and reports failures as warnings.
+
 - Graph node resources are now retained independently across graph clones,
   executable graphs, updates, node deletion, and in-flight launches. Previously,
   modifying a graph definition could release resources still used by an
@@ -18,9 +95,169 @@ Fixes and enhancements
   (`#2357 <https://github.com/NVIDIA/cuda-python/pull/2357>`__,
   `#2371 <https://github.com/NVIDIA/cuda-python/pull/2371>`__)
 
+- Added ``update()`` methods to kernel, memcpy, memset, child-graph, event
+  record, event wait, and host-callback graph definition nodes. Updates change
+  parameters used by future graph instantiations without affecting existing
+  executable graphs. This feature requires CUDA driver and ``cuda.bindings``
+  versions 12.2 or newer.
+  (`#2352 <https://github.com/NVIDIA/cuda-python/issues/2352>`__)
+
+- Added ``graph[node]`` views for updating nodes in an executable graph.
+  Kernel, memcpy, memset, child-graph, event, and host-callback parameters can
+  be replaced without reinstantiating the graph. Kernel, memcpy, and memset
+  nodes can also be enabled or disabled. Resources introduced by these updates
+  remain alive through in-flight launches. Superseded resources stay retained
+  until a successful whole-graph update or executable graph destruction. This
+  feature requires CUDA driver and ``cuda.bindings`` versions 12.2 or newer.
+  (`#2353 <https://github.com/NVIDIA/cuda-python/issues/2353>`__,
+  `#2354 <https://github.com/NVIDIA/cuda-python/issues/2354>`__)
+
+- The default-stream singletons ``LEGACY_DEFAULT_STREAM`` and
+  ``PER_THREAD_DEFAULT_STREAM`` no longer cache the first context and device
+  they observe. A default-stream token refers to whatever context is current,
+  so ``Stream.context``, ``Stream.device``, ``Stream.resources``, and
+  ``Stream.record()`` now resolve against the current context on every call.
+  Previously the first query pinned the singleton to one context for the
+  lifetime of the process, which also kept that context alive.
+  (`#2485 <https://github.com/NVIDIA/cuda-python/issues/2485>`__)
+
+- :meth:`Linker.which_backend` and constructing a :class:`Linker` no longer
+  raise ``FunctionNotFoundError`` when an nvJitLink older than 12.3
+  (12.0–12.2) is installed. These versions do not export the unversioned
+  ``nvJitLinkVersion`` symbol, so probing the version crashed instead of
+  falling back. ``cuda.core`` now warns and falls back to the driver
+  (``cuLink``) backend, restoring the pre-0.7.0 behavior.
+  (`#2409 <https://github.com/NVIDIA/cuda-python/pull/2409>`__,
+  closes `#2408 <https://github.com/NVIDIA/cuda-python/issues/2408>`__)
+
+- :class:`ProgramOptions` now accepts ``name=None`` and falls back to the
+  documented default ``"default_program"``. Previously the annotated and
+  documented ``None`` raised ``AttributeError`` during construction.
+  (`#2517 <https://github.com/NVIDIA/cuda-python/pull/2517>`__,
+  closes `#2516 <https://github.com/NVIDIA/cuda-python/issues/2516>`__)
+
+- ``cuda.core`` now checks ctypes host callbacks against the driver's
+  ``CUhostFn`` signature (``void (*)(void*)``) before passing the function
+  pointer to CUDA. :meth:`graph.GraphNode.callback`,
+  :meth:`graph.GraphBuilder.callback`, and the host-callback ``update()``
+  methods raise ``TypeError`` for a mismatched prototype, rather than leaving
+  the driver to call through an incompatible signature, which is undefined
+  behavior. Declarations that previously reached the driver, such as
+  ``ctypes.CFUNCTYPE(ctypes.c_int, ctypes.c_void_p)``, are now rejected at the
+  call site. A function pointer obtained from a shared library keeps ctypes'
+  default ``c_int`` result type until it is declared, so set its ``restype``
+  and ``argtypes`` (or cast it to the prototype above) before passing it. On
+  Windows, both ``ctypes.CFUNCTYPE`` and ``ctypes.WINFUNCTYPE`` are accepted.
+  (`#2439 <https://github.com/NVIDIA/cuda-python/issues/2439>`__)
+
+- :meth:`DeviceMemoryResource.register` and
+  :meth:`PinnedMemoryResource.register` now raise ``RuntimeError`` when the
+  memory resource does not have IPC enabled. Previously they dereferenced a
+  ``None`` attribute and terminated the process with a segmentation fault, so
+  the call could not be guarded with ``try``. A rejected registration no longer
+  leaves an entry in the memory resource registry.
+  (`#2568 <https://github.com/NVIDIA/cuda-python/issues/2568>`__)
+
+- Starting with CUDA 13.4, unconstrained SM-resource discovery through
+  :meth:`SMResource.split` with ``SMResourceOptions(count=None)`` may return
+  every available SM, even when that count is not divisible by the device's
+  :attr:`SMResource.coscheduled_alignment`. CUDA 13.1 through 13.3 returned an
+  aligned subset for the same request. An omitted or zero
+  ``coscheduled_sm_count`` still selects the driver's default internally, but
+  CUDA 13.4 no longer guarantees that the returned :attr:`SMResource.sm_count`
+  is a multiple of that default. A green context created from the discovered
+  group may therefore span the full GPU and leave an empty remainder. Set
+  ``coscheduled_sm_count`` explicitly when an aligned result is required.
+  (`#2389 <https://github.com/NVIDIA/cuda-python/pull/2389>`__)
+
+- ``ProgramOptions(numba_debug=True)`` now works on the NVVM backend. The
+  option was emitted to libNVVM as ``--numba-debug``, but libNVVM accepts only
+  single-dashed options, so every such compile failed with
+  ``NVVM_ERROR_INVALID_OPTION``. It is now emitted as ``-numba-debug``, matching
+  what numba-cuda passes on the NVVM path. The NVRTC backend accepts both
+  spellings and was unaffected. The option itself is only recognized by newer
+  toolkits; libNVVM from CUDA 12.x does not support it under either spelling and
+  still reports ``NVVM_ERROR_INVALID_OPTION``.
+  (closes `#2570 <https://github.com/NVIDIA/cuda-python/issues/2570>`__)
+
+- :meth:`~utils.StridedMemoryView.from_dlpack`, and
+  :meth:`~utils.StridedMemoryView.from_any_interface` on a DLPack producer, now
+  add ``DLTensor.byte_offset`` to ``ptr``. DLPack places a tensor's first
+  element at ``data + byte_offset``, but ``ptr`` was taken from ``data`` alone,
+  so a producer that reported an allocation base in ``data`` and expressed a
+  slice as an offset yielded a view pointing ``byte_offset`` bytes before the
+  tensor, with no error raised. The offset was also lost permanently on a
+  round-trip, since the ``__dlpack__`` re-export writes ``ptr`` back out as
+  ``data`` with ``byte_offset = 0``. The capsule-consuming path was already
+  correct.
+  (`#2592 <https://github.com/NVIDIA/cuda-python/issues/2592>`__)
+
+- ``Program(ptx, "ptx", ProgramOptions(numba_debug=True))`` now warns that the
+  option is ignored instead of discarding it silently. ``numba_debug`` is an
+  NVVM/NVRTC *compiler* option: nvJitLink rejects it with
+  ``ERROR_UNRECOGNIZED_OPTION`` under every spelling, and the driver's
+  ``cuLink`` API has no corresponding ``CUjit_option``, so no linking backend
+  can honor it. PTX inputs are handed to the linker, and the option used to be
+  forwarded into ``LinkerOptions`` and then dropped without a diagnostic. The
+  warning is a :class:`UserWarning`, not a :class:`DeprecationWarning` --
+  ``ProgramOptions.numba_debug`` is not deprecated and remains fully supported
+  on the NVVM and NVRTC compilation paths, where it takes effect; it is simply
+  inapplicable to a linking backend. The gate is truthiness, matching how the
+  NVVM path gates emission, so ``numba_debug=False`` asks for nothing and is
+  not worth a warning.
+  (closes `#2640 <https://github.com/NVIDIA/cuda-python/issues/2640>`__)
+
+- CUDA device enumeration now queries the CUDA driver rather than using the
+  NVML system-device count. This prevents non-CUDA accelerators, such as an NPU,
+  from being treated as CUDA devices by :meth:`Device.get_all_devices`, examples,
+  and tests.
+
+- :class:`PinnedMemoryResource` now rejects unsupported host memory pools
+  at construction with ``RuntimeError``, instead of letting a later
+  allocation or copy fail with ``CUDA_ERROR_INVALID_VALUE``.
+  (`#2487 <https://github.com/NVIDIA/cuda-python/pull/2487>`__)
+
+- :attr:`VirtualMemoryResource.is_host_accessible`, and by extension
+  :attr:`Buffer.is_host_accessible`, now correctly return ``True`` for a
+  resource configured with ``location_type="host_numa"`` or
+  ``"host_numa_current"``. Previously both properties reported ``False``
+  on those NUMA-located variants.
+  (`#2503 <https://github.com/NVIDIA/cuda-python/pull/2503>`__)
+
+- Graph predecessor and successor queries no longer truncate their results
+  on large graphs.
+  (`#2587 <https://github.com/NVIDIA/cuda-python/pull/2587>`__)
+
+- Per-domain clock queries in :mod:`cuda.core.system` treat each domain
+  (minimum, maximum, and current) as independently optional, so an
+  unsupported domain no longer fails the whole clock query for a device.
+  (`#2651 <https://github.com/NVIDIA/cuda-python/pull/2651>`__)
+
+- Temperature threshold checks in :mod:`cuda.core.system` are now
+  forward-compatible with GPU architectures newer than the generated
+  ``DeviceArch`` enum. An unrecognized architecture no longer raises
+  ``ValueError`` before the query runs.
+  (`#2488 <https://github.com/NVIDIA/cuda-python/pull/2488>`__)
+
+- The frozen fallback ``CUresult`` explanation table, used when the
+  driver's ``cuGetErrorName`` / ``cuGetErrorString`` are unavailable, is
+  refreshed for CUDA 13.3 and now recognizes
+  ``CUDA_ERROR_GRAPH_RECAPTURE_FAILURE``.
+  (`#2383 <https://github.com/NVIDIA/cuda-python/pull/2383>`__)
+
 Deprecation Notices
 -------------------
 
+- ``LinkerOptions.numba_debug`` is deprecated and will be removed in
+  ``cuda.core`` 2.0.0. It was exposed in ``cuda-core`` 1.1.0 but no linking
+  backend ever read it, so setting it has never had any effect;
+  ``numba_debug`` is an NVVM/NVRTC compiler option with no linker equivalent.
+  Setting it now emits a :class:`DeprecationWarning` and the value continues
+  to be ignored. Removal waits for the next major version because the
+  :doc:`support policy <../support>` confines breaking API changes to
+  major-version boundaries. Use :attr:`ProgramOptions.numba_debug` on an NVVM
+  or NVRTC compilation path instead.
+
 - Support for using ``cuda-core`` with Python 3.10 is deprecated and will be
   removed in a future version.  Python 3.10 reaches end of life in October 2026
   per the `CPython support cycle <https://devguide.python.org/versions/>`_.
diff --git a/cuda_core/docs/source/release/1.2.1-notes.rst b/cuda_core/docs/source/release/1.2.1-notes.rst
new file mode 100644
index 00000000000..bd34d0f50c0
--- /dev/null
+++ b/cuda_core/docs/source/release/1.2.1-notes.rst
@@ -0,0 +1,16 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. currentmodule:: cuda.core
+
+``cuda.core`` 1.2.1 Release Notes
+=================================
+
+Fixes and enhancements
+----------------------
+
+- :meth:`Buffer.from_handle` no longer requires a current CUDA context when
+  the memory resource reports ``is_device_accessible`` as ``False``. Host-only
+  memory records no deallocation stream, so creating and closing such buffers
+  does not call the driver.
+  (`#2769 <https://github.com/NVIDIA/cuda-python/issues/2769>`__)
diff --git a/cuda_core/docs/source/release/1.3.0-notes.rst b/cuda_core/docs/source/release/1.3.0-notes.rst
new file mode 100644
index 00000000000..37ff06b34e5
--- /dev/null
+++ b/cuda_core/docs/source/release/1.3.0-notes.rst
@@ -0,0 +1,37 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. currentmodule:: cuda.core
+
+``cuda.core`` 1.3.0 Release Notes
+==================================
+
+Fixes and enhancements
+----------------------
+
+- :class:`Device` methods that create resources or synchronize now act on that
+  device's bound context, even when another device is current. They do not
+  change which device is current. For example, ``dev1.sync()`` synchronizes
+  device 1's bound context even when device 0 is current, and no longer
+  touches other contexts on device 1 (such as a green context). :meth:`Device.set_current`
+  now always returns a :class:`Context` with the correct device ID; passing a
+  context created on a different device than the receiver now delegates to
+  that device's own :meth:`~Device.set_current` instead of raising, so a
+  context this method returns can always be pushed back through any
+  :class:`Device` object.
+  (`#2311 <https://github.com/NVIDIA/cuda-python/issues/2311>`__)
+
+- :meth:`Stream.wait` given a stream now works when that stream belongs to a
+  device that is not current. The temporary ordering event is created in the
+  waited-on stream's context rather than the current one, which
+  ``cuEventRecord`` rejects when the two differ. The stream ordering applied
+  when importing foreign arrays and tensors uses the producer stream's context
+  the same way.
+  (`#2311 <https://github.com/NVIDIA/cuda-python/issues/2311>`__)
+
+- :attr:`LegacyPinnedMemoryResource.device_id` now returns ``-1``, as
+  documented for memory that is not bound to a device and as
+  :class:`PinnedMemoryResource` already does, instead of raising
+  ``RuntimeError``. :attr:`Buffer.device_id` on such a buffer returns ``-1``
+  as well, which also lets a pinned buffer back a linear or pitched texture
+  resource.
diff --git a/cuda_core/examples/batched_memcpy.py b/cuda_core/examples/batched_memcpy.py
new file mode 100644
index 00000000000..bb85b6e7995
--- /dev/null
+++ b/cuda_core/examples/batched_memcpy.py
@@ -0,0 +1,168 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+# ################################################################################
+#
+# This example demonstrates the batched memory copy API (copy_batch) for
+# performing multiple async memory transfers in a single driver call. It
+# covers homogeneous batches (all copies share one CopyOptions),
+# heterogeneous batches (per-copy attributes), and verifies equivalence
+# with sequential Buffer.copy_to calls.
+#
+# Requires CUDA 13+ (cuMemcpyBatchAsync is not available on CUDA 12).
+#
+# ################################################################################
+
+# /// script
+# dependencies = ["cuda_bindings", "cuda_core"]
+# ///
+
+import ctypes
+import sys
+
+from cuda.core import Device, Host, LegacyPinnedMemoryResource, ManagedMemoryResource
+from cuda.core.utils import CopyOptions, MemcpySrcAccessOrder, copy_batch
+
+
+def readback(any_buf, pinned_mr, *, stream):
+    """Copy a buffer to a new pinned buffer and return the bytes."""
+    host_buf = pinned_mr.allocate(any_buf.size)
+    any_buf.copy_to(host_buf, stream=stream)
+    stream.sync()
+
+    ptr = ctypes.cast(int(host_buf.handle), ctypes.POINTER(ctypes.c_byte))
+    data = ctypes.string_at(ptr, host_buf.size)
+    host_buf.close()
+    return data
+
+
+def main(dev: Device):
+    dev.set_current()
+    stream = dev.create_stream()
+    pinned_mr = LegacyPinnedMemoryResource()
+    device_mr = dev.memory_resource
+
+    num_copies = 4
+    buf_size = 4096
+
+    # ---- Allocate source (pinned) and destination (device) buffers ----------
+
+    srcs = []
+    dsts = []
+    for i in range(num_copies):
+        src = pinned_mr.allocate(buf_size)
+        dst = device_mr.allocate(buf_size, stream=stream)
+
+        # Fill each source with a distinct byte pattern so we can verify
+        fill_byte = (i + 1) % 256
+        src.fill(fill_byte, stream=stream)
+
+        srcs.append(src)
+        dsts.append(dst)
+
+    # ---- 1. Homogeneous batch: all copies share a single CopyOptions -----
+
+    print("1. Homogeneous batched H2D copy...", file=sys.stderr)
+
+    options = CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM)
+    copy_batch(stream, srcs, dsts, options=options)
+
+    for i, dst in enumerate(dsts):
+        expected_byte = (i + 1) % 256
+        data = readback(dst, pinned_mr, stream=stream)
+        assert all(b == expected_byte for b in data), f"Copy {i}: expected byte {expected_byte}, got {data[:8]!r}..."
+
+    print("   All copies verified.", file=sys.stderr)
+
+    # ---- 2. Equivalence with sequential Buffer.copy_to ----------------------
+
+    print("2. Verifying batched == sequential copy_to...", file=sys.stderr)
+
+    # Re-fill sources with new patterns
+    for i, src in enumerate(srcs):
+        src.fill((i + 100) % 256, stream=stream)
+
+    # Sequential path: individual copy_to calls
+    seq_dsts = [device_mr.allocate(buf_size, stream=stream) for _ in range(num_copies)]
+    for src, dst in zip(srcs, seq_dsts):
+        src.copy_to(dst, stream=stream)
+
+    # Batched path: single copy_batch call
+    batch_dsts = [device_mr.allocate(buf_size, stream=stream) for _ in range(num_copies)]
+    copy_batch(stream, srcs, batch_dsts, options=CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM))
+
+    # Compare results
+    for i in range(num_copies):
+        seq_data = readback(seq_dsts[i], pinned_mr, stream=stream)
+        batch_data = readback(batch_dsts[i], pinned_mr, stream=stream)
+        assert seq_data == batch_data, f"Copy {i}: sequential and batched results differ"
+
+    print("   Batched and sequential results match.", file=sys.stderr)
+
+    # ---- 3. Heterogeneous batch: per-copy attributes ------------------------
+    #
+    # src_access_order controls how the driver accesses source memory:
+    #   STREAM           - source read respects stream ordering (pinned/device memory)
+    #   DURING_API_CALL  - source read during the API call itself (ephemeral host ptrs)
+    #   ANY              - driver picks best strategy (pageable or HMM-backed memory)
+
+    print("3. Heterogeneous batch with per-copy attributes...", file=sys.stderr)
+
+    per_copy_options = [
+        CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM),
+        CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY),
+        CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM),
+        CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY),
+    ]
+    hetero_dsts = [device_mr.allocate(buf_size, stream=stream) for _ in range(num_copies)]
+    copy_batch(stream, srcs, hetero_dsts, options=per_copy_options)
+
+    for i in range(num_copies):
+        expected_byte = (i + 100) % 256
+        data = readback(hetero_dsts[i], pinned_mr, stream=stream)
+        assert all(b == expected_byte for b in data), f"Heterogeneous copy {i}: expected byte {expected_byte}"
+
+    print("   Heterogeneous batch verified.", file=sys.stderr)
+
+    # ---- 4. Location hints with managed memory ------------------------------
+    #
+    # When copying managed-memory buffers, src_location_hint and
+    # dst_location_hint tell the driver where the data currently lives and
+    # where it is going, enabling optimized transfer paths.
+
+    print("4. Batched copy with location hints (managed memory)...", file=sys.stderr)
+
+    managed_mr = ManagedMemoryResource()
+    managed_srcs = [managed_mr.allocate(buf_size, stream=stream) for _ in range(2)]
+    managed_dsts = [managed_mr.allocate(buf_size, stream=stream) for _ in range(2)]
+
+    for i, src in enumerate(managed_srcs):
+        src.fill((i + 200) % 256, stream=stream)
+
+    hint_options = CopyOptions(
+        src_access_order=MemcpySrcAccessOrder.STREAM,
+        src_location_hint=dev,
+        dst_location_hint=Host(),
+    )
+    copy_batch(stream, managed_srcs, managed_dsts, options=hint_options)
+
+    for i in range(2):
+        expected_byte = (i + 200) % 256
+        data = readback(managed_dsts[i], pinned_mr, stream=stream)
+        assert all(b == expected_byte for b in data), f"Managed copy {i}: expected byte {expected_byte}"
+
+    print("   Location-hinted batch verified.", file=sys.stderr)
+
+    # ---- Cleanup ------------------------------------------------------------
+
+    all_bufs = srcs + dsts + seq_dsts + batch_dsts + hetero_dsts + managed_srcs + managed_dsts
+    for buf in all_bufs:
+        buf.close(stream)
+    stream.close()
+
+    print("Batched memcpy example completed!")
+
+
+if __name__ == "__main__":
+    main(Device(0))
diff --git a/cuda_core/examples/buffer_deallocation_stream.py b/cuda_core/examples/buffer_deallocation_stream.py
new file mode 100644
index 00000000000..49579040590
--- /dev/null
+++ b/cuda_core/examples/buffer_deallocation_stream.py
@@ -0,0 +1,76 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+# ################################################################################
+#
+# This example transfers a buffer from a producer stream to a consumer stream.
+# An event orders the consumer after the producer. The buffer then records the
+# consumer stream for its eventual deallocation.
+#
+# ################################################################################
+
+# /// script
+# dependencies = ["cuda_bindings", "cuda_core"]
+# ///
+
+import ctypes
+
+from cuda.core import Device, LegacyPinnedMemoryResource
+
+
+def produce_data(device, stream, size, value):
+    """Allocate and fill a buffer on the producer stream."""
+    buffer = device.allocate(size, stream=stream)
+    buffer.fill(value, stream=stream)
+    ready = stream.record()
+    return buffer, ready
+
+
+def consume_data(buffer, ready, output, stream):
+    """Submit consumer work and transfer the deallocation stream."""
+    stream.wait(ready)
+    buffer.set_deallocation_stream(stream)
+    buffer.copy_to(output, stream=stream)
+
+
+def main():
+    device = Device()
+    device.set_current()
+    producer_stream = device.create_stream()
+    consumer_stream = device.create_stream()
+    pinned_mr = LegacyPinnedMemoryResource()
+
+    size = 4096
+    value = 42
+    buffer = None
+    ready = None
+    output = None
+
+    try:
+        output = pinned_mr.allocate(size)
+        buffer, ready = produce_data(device, producer_stream, size, value)
+        consume_data(buffer, ready, output, consumer_stream)
+
+        # No stream argument is needed. The buffer now records consumer_stream.
+        # The free operation runs after the copy on that stream.
+        buffer.close()
+        buffer = None
+        consumer_stream.sync()
+
+        result = ctypes.string_at(int(output.handle), output.size)
+        assert result == bytes([value]) * size
+        print("Buffer deallocation stream transfer completed.")
+    finally:
+        if buffer is not None:
+            buffer.close()
+        if output is not None:
+            output.close()
+        if ready is not None:
+            ready.close()
+        consumer_stream.close()
+        producer_stream.close()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/cuda_core/examples/memory_pool_resources.py b/cuda_core/examples/memory_pool_resources.py
index aa322ecc206..8b97948c54e 100644
--- a/cuda_core/examples/memory_pool_resources.py
+++ b/cuda_core/examples/memory_pool_resources.py
@@ -89,13 +89,13 @@ def main():
 
         managed_buffer = managed_mr.allocate(nbytes, stream=stream)
         pinned_buffer = pinned_mr.allocate(nbytes, stream=stream)
+        stream.sync()
 
         managed_array = np.from_dlpack(managed_buffer).view(np.float32)
         pinned_array = np.from_dlpack(pinned_buffer).view(np.float32)
 
         managed_array[:] = np.arange(size, dtype=dtype)
         managed_original = managed_array.copy()
-        stream.sync()
 
         managed_buffer.copy_to(pinned_buffer, stream=stream)
         stream.sync()
diff --git a/cuda_core/examples/strided_memory_view_constructors.py b/cuda_core/examples/strided_memory_view_constructors.py
index 66820c56e2d..c5799ad998b 100644
--- a/cuda_core/examples/strided_memory_view_constructors.py
+++ b/cuda_core/examples/strided_memory_view_constructors.py
@@ -18,7 +18,7 @@
 import cupy as cp
 import numpy as np
 
-from cuda.core import Device
+from cuda.core import Device, Stream
 from cuda.core.utils import StridedMemoryView
 
 
@@ -39,7 +39,8 @@ def main():
 
     device = Device()
     device.set_current()
-    stream = device.create_stream()
+    cupy_stream = cp.cuda.get_current_stream()
+    stream = Stream.from_handle(cupy_stream.ptr)
     buffer = None
 
     try:
@@ -63,7 +64,6 @@ def main():
         buffer = device.memory_resource.allocate(gpu_array.nbytes, stream=stream)
         buffer_array = cp.from_dlpack(buffer).view(dtype=cp.float32).reshape(gpu_array.shape)
         buffer_array[...] = gpu_array
-        device.sync()
 
         buffer_view = StridedMemoryView.from_buffer(
             buffer,
@@ -77,7 +77,6 @@ def main():
     finally:
         if buffer is not None:
             buffer.close(stream)
-        stream.close()
 
 
 if __name__ == "__main__":
diff --git a/cuda_core/pixi.lock b/cuda_core/pixi.lock
index ebaf967facd..9ce462a8b1b 100644
--- a/cuda_core/pixi.lock
+++ b/cuda_core/pixi.lock
@@ -42,17 +42,18 @@ environments:
   cu12:
     channels:
     - url: https://conda.anaconda.org/conda-forge/
+    indexes:
+    - https://pypi.org/simple
     packages:
       linux-64:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.15.3-hb03c661_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/aom-3.9.1-hac33072_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/attr-2.5.2-h39aace5_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.45.1-default_hfdba357_101.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/alsa-lib-1.2.16.1-h7cc23a3_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aom-3.14.1-pl5321h57e6904_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.46.1-default_hfdba357_102.conda
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   depends:
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   license: BSD-2-Clause
   license_family: BSD
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/dbus-1.16.2-h24cb091_1.conda
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   license: AFL-2.1 OR GPL-2.0-or-later
   purls: []
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-  timestamp: 1769744977998
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   license_family: MIT
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-  - abseil-cpp =20260107.1
+  - abseil-cpp =20260526.0
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   license_family: Apache
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-  - libcblas   3.11.0   5*_openblas
-  - blas 2.305   openblas
-  - liblapacke 3.11.0   5*_openblas
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+  - libopenblas >=0.3.34,<1.0a0
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+  - libcblas   3.11.0   9*_openblas
+  - liblapack  3.11.0   9*_openblas
+  - liblapacke 3.11.0   9*_openblas
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   license_family: BSD
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-  - liblapacke 3.11.0   5*_mkl
-  - libcblas   3.11.0   5*_mkl
-  - blas 2.305   mkl
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+  - libcblas   3.11.0   9*_mkl
+  - liblapack  3.11.0   9*_mkl
+  - liblapacke 3.11.0   9*_mkl
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   license_family: BSD
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-  - blas 2.305   openblas
-  - liblapack  3.11.0   5*_openblas
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+  - liblapack  3.11.0   9*_openblas
+  - liblapacke 3.11.0   9*_openblas
   license: BSD-3-Clause
   license_family: BSD
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-  - liblapacke 3.11.0   5*_mkl
-  - blas 2.305   mkl
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+  - liblapacke 3.11.0   9*_mkl
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-  - liblapacke 3.11.0   6*_openblas
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-  - liblapack  3.11.0   8*_openblas
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   - cuda-nvrtc
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-  md5: a41b3904663dcc0c7f53862666fede36
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+  md5: da6ca95b4f3a9e2931e05327e0f1736d
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@@ -5428,15 +5245,16 @@ packages:
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   - libgcc >=14
   - libstdcxx >=14
-  - libzlib >=1.3.1,<2.0a0
+  - libzlib >=1.3.2,<2.0a0
   constrains:
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   license: LicenseRef-cuDNN-Software-License-Agreement
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libcudss-0.7.1.4-h7bcfba5_1.conda
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-  md5: 6111650cfce61896d705230a878cc1a8
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@@ -5445,12 +5263,13 @@ packages:
   - libgcc >=14
   - libstdcxx >=14
   constrains:
+  - libcudss-commlayer-nccl 0.8.0.10 h84ff803_0
+  - libcudss-commlayer-mpi 0.8.0.10 h6647138_0
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   license: LicenseRef-NVIDIA-End-User-License-Agreement
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   license_family: MIT
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libvpl-2.16.0-h54a6638_0.conda
@@ -7450,39 +6643,48 @@ packages:
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   license_family: MIT
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   - python_abi 3.14.* *_cp314
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/pyzmq-27.1.0-py312hda471dd_2.conda
+- conda: https://conda.anaconda.org/conda-forge/linux-64/pyzmq-27.2.0-py312h8a5ba0d_0.conda
   noarch: python
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   - zeromq >=4.3.5,<4.4.0a0
   - _python_abi3_support 1.*
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/rdma-core-63.1-h192683f_0.conda
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-  - numpy >=1.25.2
+  - numpy >=2.0.0
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-  - libzlib >=1.3.1,<2.0a0
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   license: LicenseRef-NVIDIA-End-User-License-Agreement
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   - libgcc >=14
   - libstdcxx >=14
-  - libzlib >=1.3.1,<2.0a0
+  - libzlib >=1.3.2,<2.0a0
   constrains:
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   license: LicenseRef-cuDNN-Software-License-Agreement
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-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcudss-0.7.1.4-he387df4_1.conda
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-  - libcudss-commlayer-mpi 0.7.1.4 h40415f0_1
   - libcudss0 <0.0.0a0
+  - libcudss-commlayer-nccl 0.8.0.10 h5eac28b_0
+  - libcudss-commlayer-mpi 0.8.0.10 h40415f0_0
   license: LicenseRef-NVIDIA-End-User-License-Agreement
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 - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcufft-12.3.0.29-h8f3c8d4_0.conda
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@@ -10662,6 +9474,7 @@ packages:
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   - arm-variant * sbsa
   license: LicenseRef-NVIDIA-End-User-License-Agreement
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   license_family: BSD
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   license: MPL-2.0 AND Apache-2.0
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   - libmpdec >=4.0.0,<5.0a0
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   - tk >=8.6.13,<8.7.0a0
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   - tk >=8.6.13,<8.7.0a0
   - tzdata
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   license: Python-2.0
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     weak:
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     noarch:
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   - python >=3.14,<3.15.0a0
   - python >=3.14,<3.15.0a0 *_cp314
   - python_abi 3.14.* *_cp314
-  - setuptools
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   - sympy >=1.13.3
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   license_family: BSD
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   timestamp: 1770223441816
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/pyzmq-27.1.0-py312hdf0a211_2.conda
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+  - libstdcxx >=15
   - _python_abi3_support 1.*
   - cpython >=3.12
+  - zeromq >=4.3.5,<4.4.0a0
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-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/readline-8.3-hb682ff5_0.conda
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+    - rdma-core >=63.1
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   - pkg:pypi/rpds-py?source=hash-mapping
-  size: 376332
-  timestamp: 1764543345455
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   purls:
   - pkg:pypi/ruamel-yaml-clib?source=hash-mapping
+  run_exports: {}
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   timestamp: 1766159541094
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   - numpy <2.7
   - numpy >=1.23,<3
-  - numpy >=1.25.2
+  - numpy >=2.0.0
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   license_family: BSD
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+- conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_7.conda
+  sha256: ca7daae4f218a11fab82cc2857f0ea518ec3f46acec60490485347a4c22c6b3e
+  md5: e4ac308c39d6d0e131154976da67cf3b
   depends:
   - vc >=14.3,<15
   - vc14_runtime >=14.44.35208
   - ucrt >=10.0.20348.0
-  - libzlib >=1.3.1,<2.0a0
+  - libzlib >=1.3.2,<2.0a0
   license: BSD-3-Clause
   license_family: BSD
   purls: []
   run_exports:
     weak:
     - zstd >=1.5.7,<1.6.0a0
-  size: 388453
-  timestamp: 1764777142545
-- conda_source: cuda-bindings[1a320ca0] @ ../cuda_bindings
+  size: 387535
+  timestamp: 1786599623274
+- conda_source: cuda-bindings[76e5798a] @ ../cuda_bindings
+  variants:
+    c_stdlib: sysroot
+    c_stdlib_version: '2.28'
+    cuda_version: 13.3.*
+    python: 3.14.*
+    target_platform: linux-aarch64
+  depends:
+  - python
+  - python >=3.10
+  - cuda-version
+  - cuda-pathfinder
+  - libnvjitlink
+  - cuda-nvrtc
+  - cuda-nvrtc >=13.3.33,<14.0a0
+  - cuda-nvvm
+  - libnvfatbin
+  - libcufile
+  - libcufile >=1.18.1.6,<2.0a0
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
+  - __glibc >=2.28,<3.0.a0
+  - python_abi 3.14.* *_cp314
+  license: Apache-2.0
+  source_depends:
+    cuda-pathfinder:
+      path: ../cuda_pathfinder
+  build_packages:
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+  - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-84.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+  - conda_source: cuda-pathfinder[962b1b3e] @ ../cuda_pathfinder
+- conda_source: cuda-bindings[7a3f44f3] @ ../cuda_bindings
   variants:
     c_compiler: vs2022
     cuda_version: 13.3.*
@@ -19409,52 +17391,53 @@ packages:
       path: ../cuda_pathfinder
   build_packages:
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-  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_39.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_41.conda
   host_packages:
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-  - conda_source: cuda-pathfinder[169735b8] @ ../cuda_pathfinder
-- conda_source: cuda-bindings[29afc263] @ ../cuda_bindings
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+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_7.conda
+  - conda_source: cuda-pathfinder[a3bad7cf] @ ../cuda_pathfinder
+- conda_source: cuda-bindings[c549e17d] @ ../cuda_bindings
   variants:
     c_stdlib: sysroot
     c_stdlib_version: '2.28'
@@ -19473,9 +17456,9 @@ packages:
   - libnvfatbin
   - libcufile
   - libcufile >=1.18.1.6,<2.0a0
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
   - __glibc >=2.28,<3.0.a0
   - python_abi 3.14.* *_cp314
   license: Apache-2.0
@@ -19486,183 +17469,146 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.46.1-default_hfdba357_102.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.46.1-default_h4852527_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-15.2.0-he0086c7_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-15.2.0-h7be306e_27.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-15.2.0-hda75c37_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-15.2.0-hcb00b6d_27.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-16.2.0-h176d5d0_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-16.2.0-h0ab548f_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-16.2.0-h0d273dc_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-16.2.0-h38dc33c_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_102.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.2.0-ha9f2e26_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-16.2.0-he0feb66_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsanitizer-16.2.0-h3048135_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-16.2.0-h934c35e_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_7.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_9.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-15.2.0-hcc6f6b0_119.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-64-15.2.0-hd446a21_119.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-16.2.0-he3ce08f_104.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-64-16.2.0-h86e191b_104.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-64-2.28-h4ee821c_9.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
   host_packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_10.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-13.3.29-hecca717_0.conda
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   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-static-13.3.29-hecca717_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-13.3.33-hecca717_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-dev-13.3.33-hecca717_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-impl-13.3.73-h4bc722e_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-tools-13.3.73-h4bc722e_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-13.3.73-h69a702a_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-impl-13.3.73-hb03c661_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.8-py314h1807b08_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.9-py314h1807b08_0.conda
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   - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufile-1.18.1.6-h053a66a_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-15.2.0-h934c35e_19.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.53.4-h13e7031_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-64-13.3.73-ha770c72_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.6-hdb14827_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.4-h781a0a9_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.7-hcd007b5_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/rdma-core-63.1-h192683f_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-hd6e31c0_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h1df4ec4_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/uv-0.12.6-h86a270d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_7.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-64-13.3.3.4.1-ha770c72_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-64-13.3.73-ha770c72_1.conda
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   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-13.3.29-h376f20c_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_linux-64-13.3.73-ha770c72_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_linux-64-13.3.73-ha770c72_1.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-13.3-hcbadf70_3.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-84.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-  - conda_source: cuda-pathfinder[83159de6] @ ../cuda_pathfinder
-- conda_source: cuda-bindings[b73e05e0] @ ../cuda_bindings
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+  - conda_source: cuda-pathfinder[cd71549a] @ ../cuda_pathfinder
+- conda_source: cuda-core[02d9a38c] @ .
   variants:
-    c_stdlib: sysroot
-    c_stdlib_version: '2.28'
+    c_compiler: vs2022
     cuda_version: 13.3.*
+    cxx_compiler: vs2022
     python: 3.14.*
-    target_platform: linux-aarch64
+    target_platform: win-64
   depends:
   - python
   - python >=3.10
   - cuda-version
+  - numpy
+  - cuda-bindings
   - cuda-pathfinder
-  - libnvjitlink
-  - cuda-nvrtc
+  - backports.strenum
+  - vc >=14.3,<15
+  - vc14_runtime >=14.44.35208
+  - ucrt >=10.0.20348.0
   - cuda-nvrtc >=13.3.33,<14.0a0
-  - cuda-nvvm
-  - libnvfatbin
-  - libcufile
-  - libcufile >=1.18.1.6,<2.0a0
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
-  - __glibc >=2.28,<3.0.a0
   - python_abi 3.14.* *_cp314
   license: Apache-2.0
-  source_depends:
-    cuda-pathfinder:
-      path: ../cuda_pathfinder
   build_packages:
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_impl_linux-aarch64-2.46.1-default_h5f4c503_102.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-aarch64-2.28-h585391f_9.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vswhere-3.1.7-h40126e0_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_41.conda
   host_packages:
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_9.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-13.3.29-h8f3c8d4_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-dev-13.3.29-h8f3c8d4_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
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-  - conda_source: cuda-pathfinder[4dfff30f] @ ../cuda_pathfinder
-- conda_source: cuda-core[2472945f] @ .
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+  - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h967ab96_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.12.6-hc31ddbc_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-ha367084_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_7.conda
+- conda_source: cuda-core[0815d529] @ .
   variants:
     c_stdlib: sysroot
     c_stdlib_version: '2.28'
@@ -19677,9 +17623,9 @@ packages:
   - cuda-bindings
   - cuda-pathfinder
   - backports.strenum
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
   - __glibc >=2.28,<3.0.a0
   - python_abi 3.14.* *_cp314
   - cuda-nvrtc >=12.9.86,<13.0a0
@@ -19689,25 +17635,25 @@ packages:
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-15.2.0-he0086c7_19.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-15.2.0-hcb00b6d_27.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-16.2.0-h176d5d0_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-16.2.0-h0ab548f_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-16.2.0-h0d273dc_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-16.2.0-h38dc33c_1.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-16.2.0-h934c35e_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_7.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_9.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-15.2.0-hcc6f6b0_119.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-64-15.2.0-hd446a21_119.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-16.2.0-he3ce08f_104.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-64-16.2.0-h86e191b_104.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-64-2.28-h4ee821c_9.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
   host_packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_10.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-bindings-12.9.7-py314hadd79bd_1.conda
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   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-12.9.79-h5888daf_0.conda
@@ -19720,35 +17666,37 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-impl-12.9.86-h4bc722e_2.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-tools-12.9.86-h4bc722e_2.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-profiler-api-12.9.79-h7938cbb_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.8-py314h1807b08_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.9-py314h1807b08_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/dlpack-1.3-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-py310h44b86e0_2.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.78-hd0affe5_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.78-h084b8d7_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufile-1.14.1.1-hbc026e6_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/libnl-3.11.0-hb9d3cd8_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.6-hdb14827_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.6-habeac84_100_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/rdma-core-63.0-h192683f_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-h853b02a_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_hd70dff1_3.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_6.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.6-hdb14827_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.4-h781a0a9_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.7-hcd007b5_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/rdma-core-63.1-h192683f_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-hd6e31c0_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h1df4ec4_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/uv-0.12.6-h86a270d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_7.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-64-12.9.27-ha770c72_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-64-12.9.86-ha770c72_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_linux-64-12.9.79-h3f2d84a_0.conda
@@ -19756,18 +17704,118 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-12.9.79-h3f2d84a_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvcc-dev_linux-64-12.9.86-he91c749_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_linux-64-12.9.86-ha770c72_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.5.6-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.7.0-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/libnvptxcompiler-dev_linux-64-12.9.86-ha770c72_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-84.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+- conda_source: cuda-core[0d88241e] @ .
+  variants:
+    c_stdlib: sysroot
+    c_stdlib_version: '2.28'
+    cuda_version: 13.3.*
+    python: 3.14.*
+    target_platform: linux-64
+  depends:
+  - python
+  - python >=3.10
+  - cuda-version
+  - numpy
+  - cuda-bindings
+  - cuda-pathfinder
+  - backports.strenum
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
+  - __glibc >=2.28,<3.0.a0
+  - cuda-cudart >=13.3.29,<14.0a0
+  - cuda-nvrtc >=13.3.33,<14.0a0
+  - python_abi 3.14.* *_cp314
+  license: Apache-2.0
+  build_packages:
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.46.1-default_hfdba357_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.46.1-default_h4852527_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-16.2.0-h176d5d0_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-16.2.0-h0ab548f_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-16.2.0-h0d273dc_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_linux-64-16.2.0-h38dc33c_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.2.0-ha9f2e26_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-16.2.0-he0feb66_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsanitizer-16.2.0-h3048135_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-16.2.0-h934c35e_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_7.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-64-4.18.0-he073ed8_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-64-16.2.0-he3ce08f_104.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-64-16.2.0-h86e191b_104.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-64-2.28-h4ee821c_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
+  host_packages:
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-20_gnu.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_10.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-bindings-13.3.1-py314h42812f9_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-13.3.29-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-dev-13.3.29-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-cudart-static-13.3.29-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-13.3.33-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-dev-13.3.33-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvvm-impl-13.3.73-hb03c661_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-profiler-api-13.3.27-h7938cbb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.9-py314h1807b08_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/dlpack-1.3-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-py310h44b86e0_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libcap-2.78-h084b8d7_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufile-1.18.1.6-h053a66a_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.8.1-hecca717_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.7.0-h81df57d_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.2.0-ha9f2e26_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libgomp-16.2.0-he0feb66_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.3-hb03c661_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libnl-3.11.0-hb03c661_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libnvfatbin-13.3.29-hecca717_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libnvjitlink-13.3.33-hecca717_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libpython-3.14.7-hdc7f604_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsqlite-3.53.4-h13e7031_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-16.2.0-h934c35e_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libsystemd0-257.13-h084b8d7_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libudev1-257.13-h084b8d7_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.42.2-h5347b49_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/libzlib-1.3.2-h25fd6f3_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/ncurses-6.6-hdb14827_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/openssl-3.6.4-h781a0a9_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.14.7-hcd007b5_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/rdma-core-63.1-h192683f_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/readline-8.3-hd6e31c0_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/tk-8.6.13-noxft_h1df4ec4_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/uv-0.12.6-h86a270d_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-64/zstd-1.5.7-hb78ec9c_7.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-64-13.3.3.4.1-ha770c72_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-64-13.3.73-ha770c72_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_linux-64-13.3.29-h376f20c_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-static_linux-64-13.3.29-h376f20c_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-64-13.3.29-h376f20c_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.7.0-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-13.3-hcbadf70_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-84.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-- conda_source: cuda-core[491c4fa3] @ .
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+- conda_source: cuda-core[49030552] @ .
   variants:
     c_stdlib: sysroot
     c_stdlib_version: '2.28'
@@ -19782,9 +17830,9 @@ packages:
   - cuda-bindings
   - cuda-pathfinder
   - backports.strenum
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
   - __glibc >=2.28,<3.0.a0
   - python_abi 3.14.* *_cp314
   - cuda-nvrtc >=12.9.86,<13.0a0
@@ -19794,25 +17842,25 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_impl_linux-aarch64-2.46.1-default_h5f4c503_102.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_linux-aarch64-2.46.1-default_hf1166c9_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_impl_linux-aarch64-15.2.0-h3530432_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_linux-aarch64-15.2.0-h0bf4bd8_27.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-15.2.0-h03e2352_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-15.2.0-h7e4acf5_27.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_impl_linux-aarch64-16.2.0-hc438ef3_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_linux-aarch64-16.2.0-h25cc031_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-16.2.0-h1e3c31f_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-16.2.0-h6eb44ee_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsanitizer-15.2.0-he19c465_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-15.2.0-hef695bb_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h85ac4a6_6.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgcc-16.2.0-h205dda4_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-16.2.0-h8acb6b2_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsanitizer-16.2.0-h73cac2c_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-16.2.0-hef695bb_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h9d15635_7.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/kernel-headers_linux-aarch64-4.18.0-h05a177a_9.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-aarch64-15.2.0-h55c397f_119.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-aarch64-15.2.0-ha7b1723_119.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libgcc-devel_linux-aarch64-16.2.0-hc0c2482_104.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/libstdcxx-devel_linux-aarch64-16.2.0-h082e5f6_104.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/sysroot_linux-aarch64-2.28-h585391f_9.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
   host_packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_10.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-bindings-12.9.7-py314hd8c1704_1.conda
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   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-cudart-12.9.79-h3ae8b8a_0.conda
@@ -19825,37 +17873,38 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvvm-impl-12.9.86-h7b14b0b_2.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvvm-tools-12.9.86-h7b14b0b_2.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-profiler-api-12.9.79-h16bee8c_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.8-py314hc6b4731_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.9-py314hc6b4731_0.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/dlpack-1.3-hfae3067_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/icu-78.3-hcab7f73_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/icu-78.3-py311h3512406_2.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcap-2.78-hf9559e3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcap-2.78-hfcc8634_1.conda
   - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcufile-1.14.1.1-had8bf56_1.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-15.2.0-hef695bb_19.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libpython-3.14.7-hc71fabe_101_cp314.conda
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-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h85ac4a6_6.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ncurses-6.6-h2b6f883_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/openssl-3.6.4-he6ad1d5_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/python-3.14.7-hbec3b18_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/rdma-core-63.1-h1f0f388_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/readline-8.3-ha7194a6_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tk-8.6.13-noxft_hf03c496_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/uv-0.12.6-h12615e1_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h9d15635_7.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/arm-variant-1.2.0-sbsa.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-aarch64-12.9.27-h579c4fd_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-aarch64-12.9.86-h579c4fd_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_linux-aarch64-12.9.79-h3ae8b8a_0.conda
@@ -19863,24 +17912,24 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-aarch64-12.9.79-h3ae8b8a_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvcc-dev_linux-aarch64-12.9.86-h4310d6a_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_linux-aarch64-12.9.86-h579c4fd_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.5.6-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.7.0-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/libnvptxcompiler-dev_linux-aarch64-12.9.86-h579c4fd_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-84.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-- conda_source: cuda-core[496050ab] @ .
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+- conda_source: cuda-core[d6d8f2a1] @ .
   variants:
     c_stdlib: sysroot
     c_stdlib_version: '2.28'
     cuda_version: 13.3.*
     python: 3.14.*
-    target_platform: linux-64
+    target_platform: linux-aarch64
   depends:
   - python
   - python >=3.10
@@ -19889,90 +17938,94 @@ packages:
   - cuda-bindings
   - cuda-pathfinder
   - backports.strenum
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
+  - libgcc >=16
+  - libgcc >=16
+  - libstdcxx >=16
   - __glibc >=2.28,<3.0.a0
   - cuda-cudart >=13.3.29,<14.0a0
   - cuda-nvrtc >=13.3.33,<14.0a0
   - python_abi 3.14.* *_cp314
   license: Apache-2.0
   build_packages:
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-  - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_impl_linux-64-2.46.1-default_hfdba357_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/binutils_linux-64-2.46.1-default_h4852527_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_impl_linux-64-15.2.0-he0086c7_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gcc_linux-64-15.2.0-h7be306e_27.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-64/gxx_impl_linux-64-15.2.0-hda75c37_19.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_impl_linux-aarch64-2.46.1-default_h5f4c503_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_linux-aarch64-2.46.1-default_hf1166c9_102.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_impl_linux-aarch64-16.2.0-hc438ef3_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_linux-aarch64-16.2.0-h25cc031_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-16.2.0-h1e3c31f_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-16.2.0-h6eb44ee_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
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   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.5.6-pyhc364b38_0.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_10.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-bindings-13.3.1-py314he6363bd_1.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cuda-nvrtc-13.3.33-h8f3c8d4_0.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/icu-78.3-py311h3512406_2.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libcufile-1.18.1.6-h42688b2_0.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-16.2.0-h8acb6b2_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/liblzma-5.8.3-he30d5cf_1.conda
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+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libnl-3.11.0-he30d5cf_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libnvfatbin-13.3.29-h8f3c8d4_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libnvjitlink-13.3.33-h8f3c8d4_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libpython-3.14.7-hc71fabe_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsqlite-3.53.4-h399dd60_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-16.2.0-hef695bb_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsystemd0-257.13-hfcc8634_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libudev1-257.13-hfcc8634_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libuuid-2.42.2-h1022ec0_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libzlib-1.3.2-hdc9db2a_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ncurses-6.6-h2b6f883_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/openssl-3.6.4-he6ad1d5_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/python-3.14.7-hbec3b18_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/rdma-core-63.1-h1f0f388_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/readline-8.3-ha7194a6_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/tk-8.6.13-noxft_hf03c496_4.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/uv-0.12.6-h12615e1_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/zstd-1.5.7-h9d15635_7.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/arm-variant-1.2.0-sbsa.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-hbd8a1cb_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_linux-aarch64-13.3.3.4.1-h579c4fd_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_linux-aarch64-13.3.73-h579c4fd_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_linux-aarch64-13.3.29-h8f3c8d4_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-static_linux-aarch64-13.3.29-h8f3c8d4_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_linux-aarch64-13.3.29-h8f3c8d4_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.7.0-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-13.3-hcbadf70_3.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-84.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-- conda_source: cuda-core[8e8d43e1] @ .
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+- conda_source: cuda-core[e4c364d0] @ .
   variants:
     c_compiler: vs2022
     cuda_version: 12.*
@@ -19996,9 +18049,9 @@ packages:
   license: Apache-2.0
   build_packages:
   - conda: https://conda.anaconda.org/conda-forge/noarch/vswhere-3.1.7-h40126e0_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_39.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vs2022_win-64-19.44.35207-ha74f236_41.conda
   host_packages:
-  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.6.17-h4c7d964_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-h4c7d964_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cccl_win-64-12.9.27-h57928b3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-crt-dev_win-64-12.9.86-h57928b3_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart-dev_win-64-12.9.79-he0c23c2_0.conda
@@ -20006,18 +18059,18 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-cudart_win-64-12.9.79-he0c23c2_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvcc-dev_win-64-12.9.86-h36c15f3_2.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-nvvm-dev_win-64-12.9.86-h57928b3_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.5.6-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-pathfinder-1.7.0-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/cuda-version-12.9-h4f385c5_3.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/libnvptxcompiler-dev_win-64-12.9.86-h57928b3_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.2-pyhc364b38_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-26.3-pyhc364b38_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-83.0.0-pyh332efcf_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-84.0.0-pyh332efcf_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.4.1-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.16.0-pyhcf101f3_0.conda
   - conda: https://conda.anaconda.org/conda-forge/noarch/tzdata-2026c-h151e31d_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.2.2-pyhcf101f3_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_10.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-bindings-12.9.7-py314h2547b3f_1.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-crt-tools-12.9.86-h57928b3_2.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-cudart-12.9.79-he0c23c2_0.conda
@@ -20029,192 +18082,66 @@ packages:
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-nvrtc-dev-12.9.86-hac47afa_1.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-nvvm-impl-12.9.86-h2466b09_2.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/cuda-nvvm-tools-12.9.86-h2466b09_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.8-py314h344ed54_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.9-py314h344ed54_0.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/dlpack-1.3-hac47afa_0.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/libexpat-2.8.1-hac47afa_1.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.5.2-h3d046cb_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.3-hfd05255_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libffi-3.7.0-h3d046cb_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/liblzma-5.8.3-hfd05255_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libmpdec-4.0.0-hfd05255_2.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/libnvjitlink-12.9.86-hac47afa_2.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/libnvptxcompiler-dev-12.9.86-h57928b3_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.53.3-hf5d6505_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_2.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.3-hf411b9b_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.6-h4b44e0e_100_cp314.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h967ab96_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libpython-3.14.7-h4f90d01_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libsqlite-3.53.4-hf5d6505_1.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.2-hfd05255_3.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.6.4-hf411b9b_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.14.7-h53f6dd8_101_cp314.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h967ab96_4.conda
   - conda: https://conda.anaconda.org/conda-forge/win-64/ucrt-10.0.26100.0-h57928b3_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.11.29-h7ca4a90_0.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-h1b7c187_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36231-h1b9f54f_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36231-h1b9f54f_39.conda
-  - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_6.conda
-- conda_source: cuda-core[b9ba9726] @ .
+  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.12.6-hc31ddbc_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-ha367084_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_7.conda
+- conda_source: cuda-pathfinder[962b1b3e] @ ../cuda_pathfinder
   variants:
-    c_stdlib: sysroot
-    c_stdlib_version: '2.28'
-    cuda_version: 13.3.*
-    python: 3.14.*
-    target_platform: linux-aarch64
+    target_platform: noarch
   depends:
-  - python
   - python >=3.10
-  - cuda-version
-  - numpy
-  - cuda-bindings
-  - cuda-pathfinder
-  - backports.strenum
-  - libgcc >=15
-  - libgcc >=15
-  - libstdcxx >=15
-  - __glibc >=2.28,<3.0.a0
-  - cuda-cudart >=13.3.29,<14.0a0
-  - cuda-nvrtc >=13.3.33,<14.0a0
-  - python_abi 3.14.* *_cp314
+  - python *
   license: Apache-2.0
-  build_packages:
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/_openmp_mutex-4.5-20_gnu.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_impl_linux-aarch64-2.46.1-default_h5f4c503_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/binutils_linux-aarch64-2.46.1-default_hf1166c9_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_impl_linux-aarch64-15.2.0-h3530432_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gcc_linux-aarch64-15.2.0-h0bf4bd8_27.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_impl_linux-aarch64-15.2.0-h03e2352_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/gxx_linux-aarch64-15.2.0-h7e4acf5_27.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/ld_impl_linux-aarch64-2.46.1-default_h1979696_102.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgcc-15.2.0-h8acb6b2_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libgomp-15.2.0-h8acb6b2_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libsanitizer-15.2.0-he19c465_19.conda
-  - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/libstdcxx-15.2.0-hef695bb_19.conda
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-- conda_source: cuda-core[f1ea05b3] @ .
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-    cuda_version: 13.3.*
-    cxx_compiler: vs2022
-    python: 3.14.*
-    target_platform: win-64
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-  - python >=3.10
-  - cuda-version
-  - numpy
-  - cuda-bindings
-  - cuda-pathfinder
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-  - vc >=14.3,<15
-  - vc14_runtime >=14.44.35208
-  - ucrt >=10.0.20348.0
-  - cuda-nvrtc >=13.3.33,<14.0a0
-  - python_abi 3.14.* *_cp314
-  license: Apache-2.0
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-- conda_source: cuda-pathfinder[169735b8] @ ../cuda_pathfinder
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
+- conda_source: cuda-pathfinder[a3bad7cf] @ ../cuda_pathfinder
   variants:
     target_platform: noarch
   depends:
@@ -20222,70 +18149,33 @@ packages:
   - python *
   license: Apache-2.0
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+  - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.7.22-h4c7d964_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/noarch/setuptools-scm-10.2.0-pyhcf101f3_0.conda
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-  - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda
+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
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-- conda_source: cuda-pathfinder[83159de6] @ ../cuda_pathfinder
+  - conda: https://conda.anaconda.org/conda-forge/win-64/uv-0.12.6-hc31ddbc_0.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc-14.5-ha367084_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vc14_runtime-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/vcomp14-14.51.36247-habf1de7_41.conda
+  - conda: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.7-h534d264_7.conda
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+  - conda: https://conda.anaconda.org/conda-forge/noarch/vcs_versioning-2.3.1-pyhcf101f3_0.conda
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   - numpy
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   - cuda-bindings[all]==12.* ; extra == 'cu12'
+  - cuda-toolkit==12.* ; extra == 'cu12'
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+  - cuda-toolkit==13.* ; extra == 'cu13'
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+  - numpy
+  - backports-strenum ; python_full_version < '3.11'
+  - cuda-bindings[all]==12.* ; extra == 'cu12'
+  - cuda-toolkit==12.* ; extra == 'cu12'
+  - cuda-bindings[all]==13.* ; extra == 'cu13'
+  - cuda-toolkit==13.* ; extra == 'cu13'
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   name: cuda-bindings
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+  - nvidia-cuda-runtime
+  - nvidia-cuda-crt
   requires_python: '>=3'
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+  - nvidia-cublas==13.6.0.2.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'all') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'all') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'all')
+  - nvidia-cuda-cccl==13.3.3.4.1.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'all') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'all') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'all')
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+  - nvidia-cuda-cuobjdump==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'all') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'all') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'all')
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+  - nvidia-cuda-cccl==13.3.3.4.1.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cccl') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cccl') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cccl')
+  - nvidia-cuda-crt==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'crt') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'crt') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'crt')
+  - nvidia-cublas==13.6.0.2.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cublas') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cublas') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cublas')
   - nvidia-cuda-nvrtc==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cublas') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cublas') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cublas')
   - nvidia-cuda-runtime==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cudart') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cudart') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cudart')
   - nvidia-cudla==13.3.29.* ; platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cudla'
   - nvidia-cufft==12.3.0.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cufft') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cufft') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cufft')
   - nvidia-nvjitlink>=13.3.33,<14 ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cufft') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cufft') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cufft')
-  - nvidia-cufile==1.18.0.66.* ; (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cufile') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cufile')
+  - nvidia-cufile==1.18.1.6.* ; (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cufile') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cufile')
   - nvidia-cuda-culibos==13.3.33.* ; (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'culibos') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'culibos')
-  - nvidia-cuda-cuobjdump==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cuobjdump') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cuobjdump') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cuobjdump')
-  - nvidia-cuda-cupti==13.3.35.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cupti') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cupti') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cupti')
+  - nvidia-cuda-cuobjdump==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cuobjdump') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cuobjdump') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cuobjdump')
+  - nvidia-cuda-cupti==13.3.75.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cupti') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cupti') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cupti')
   - nvidia-curand==10.4.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'curand') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'curand') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'curand')
-  - nvidia-cublas==13.5.1.27.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusolver') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusolver') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusolver')
-  - nvidia-cusolver==12.2.2.18.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusolver') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusolver') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusolver')
-  - nvidia-cusparse==12.8.1.7.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusolver') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusolver') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusolver')
+  - nvidia-cublas==13.6.0.2.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusolver') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusolver') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusolver')
+  - nvidia-cusolver==12.2.6.9.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusolver') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusolver') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusolver')
+  - nvidia-cusparse==12.8.2.51.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusolver') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusolver') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusolver')
   - nvidia-nvjitlink>=13.3.33,<14 ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusolver') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusolver') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusolver')
-  - nvidia-cusparse==12.8.1.7.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusparse') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusparse') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusparse')
+  - nvidia-cusparse==12.8.2.51.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusparse') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusparse') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusparse')
   - nvidia-nvjitlink>=13.3.33,<14 ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cusparse') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cusparse') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cusparse')
   - nvidia-cuda-cuxxfilt==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'cuxxfilt') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'cuxxfilt') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'cuxxfilt')
-  - nvidia-npp==13.1.2.48.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'npp') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'npp') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'npp')
-  - nvidia-cuda-crt==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvcc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvcc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvcc')
-  - nvidia-cuda-nvcc==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvcc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvcc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvcc')
+  - nvidia-npp==13.1.2.81.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'npp') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'npp') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'npp')
+  - nvidia-cuda-crt==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvcc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvcc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvcc')
+  - nvidia-cuda-nvcc==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvcc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvcc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvcc')
   - nvidia-cuda-runtime==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvcc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvcc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvcc')
-  - nvidia-nvvm==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvcc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvcc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvcc')
-  - nvidia-cuda-nvdisasm==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvdisasm') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvdisasm') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvdisasm')
+  - nvidia-nvvm==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvcc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvcc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvcc')
+  - nvidia-cuda-nvdisasm==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvdisasm') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvdisasm') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvdisasm')
   - nvidia-nvfatbin==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvfatbin') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvfatbin') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvfatbin')
   - nvidia-nvjitlink>=13.3.33,<14 ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvjitlink') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvjitlink') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvjitlink')
-  - nvidia-nvjpeg==13.2.0.21.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvjpeg') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvjpeg') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvjpeg')
+  - nvidia-nvjpeg==13.2.1.68.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvjpeg') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvjpeg') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvjpeg')
   - nvidia-nvml-dev==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvml') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvml') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvml')
-  - nvidia-nvptxcompiler==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvptxcompiler') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvptxcompiler') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvptxcompiler')
+  - nvidia-nvptxcompiler==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvptxcompiler') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvptxcompiler') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvptxcompiler')
   - nvidia-cuda-nvrtc==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvrtc') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvrtc') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvrtc')
   - nvidia-nvtx==13.3.29.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvtx') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvtx') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvtx')
-  - nvidia-nvvm==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvvm') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvvm') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvvm')
+  - nvidia-nvvm==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'nvvm') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'nvvm') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'nvvm')
   - nvidia-cuda-opencl==13.3.27.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'opencl') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'opencl')
   - nvidia-cuda-profiler-api==13.3.27.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'profiler') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'profiler') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'profiler')
-  - nvidia-cuda-sanitizer-api==13.3.27.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'sanitizer') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'sanitizer') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'sanitizer')
-  - nvidia-cuda-nvcc==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'tileiras') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'tileiras') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'tileiras')
+  - nvidia-cuda-sanitizer-api==13.3.75.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'sanitizer') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'sanitizer') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'sanitizer')
+  - nvidia-cuda-nvcc==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'tileiras') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'tileiras') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'tileiras')
   - nvidia-cuda-tileiras==13.3.36.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'tileiras') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'tileiras') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'tileiras')
   - nvidia-nvjitlink>=13.3.33,<14 ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'tileiras') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'tileiras') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'tileiras')
-  - nvidia-nvvm==13.3.33.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'tileiras') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'tileiras') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'tileiras')
-- pypi: https://files.pythonhosted.org/packages/a1/4d/603557ab3cb171cc2a61d3678a39cb4dae3fd21275078bfbd1c0b0b5230b/cuda_core-1.0.1-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
-  name: cuda-core
-  version: 1.0.1
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-  requires_dist:
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-  - numpy
-  - backports-strenum ; python_full_version < '3.11'
-  - cuda-bindings[all]==12.* ; extra == 'cu12'
-  - cuda-bindings[all]==13.* ; extra == 'cu13'
+  - nvidia-nvvm==13.3.73.* ; (platform_machine == 'AMD64' and sys_platform == 'win32' and extra == 'tileiras') or (platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'tileiras') or (platform_machine == 'x86_64' and sys_platform == 'linux' and extra == 'tileiras')
+- pypi: https://files.pythonhosted.org/packages/62/01/a7171c5e2e8755597bd8f1c1eb228a0876f502afdf25f936061f5dbe2880/cuda_pathfinder-1.7.0-py3-none-any.whl
+  name: cuda-pathfinder
+  version: 1.7.0
+  sha256: e9d67e950f3d5992b854dfd25917c3719d0c21d3057b11abe86ba6feec526138
+  requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/63/34/ba1c580383c9eada3711951fef0795c80b829a078d72188184bcab9dd527/packaging-26.3-py3-none-any.whl
+  name: packaging
+  version: '26.3'
+  sha256: d7193f7c8e4e93f444fde0262bf90af30e16fa0ad0ad44cb553c87339b23cd1c
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/69/30/45414e35ff2eee7db3da037e5707037ccf9d2b5218ffbdb055ea4d5aa98a/nvidia_nvjitlink-13.3.33-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
+  name: nvidia-nvjitlink
+  version: 13.3.33
+  sha256: ce48b37dfeb3cb1eae4cf85adacb47d7a6539ea2272870c9a3628ce275c2037e
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/69/e6/e942ee08605fc0526ff3854260c384d8315a5830e16c4c2a5aebc14dc9bf/llvmlite-0.49.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
+  name: llvmlite
+  version: 0.49.0
+  sha256: 4ec8ad805e7515cb8440a690eb3cef4d34acb29eef80b705ec4e1c1ad3c43c68
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/b1/90/16712f7566d35bb86964ca3a29858e6ca2d9e6c75d5f869e56dc6f700001/numba_cuda_mlir-0.4.0-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
+- pypi: https://files.pythonhosted.org/packages/78/9d/6393e875bad2310253c5ee0931e4d52b31f9bba1fd6832cf95a2e83a55c5/numba_cuda_mlir-0.5.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl
   name: numba-cuda-mlir
-  version: 0.4.0
-  sha256: d9c481dbe6a0bfc2f8d3bdb5b1ee6fce142667c88fffb970c26b2d7b33b6a541
+  version: 0.5.0
+  sha256: a4a83de3cca3eae995d83bac052ccbbcc38d68fffcaa90a2dc918b985fedc69f
   requires_dist:
   - numpy
   - typing-extensions ; python_full_version < '3.12'
@@ -20602,21 +18415,90 @@ packages:
   - cuda-bindings==13.* ; extra == 'cu13'
   - cuda-toolkit[cccl,cudart,nvcc,nvrtc]==13.* ; extra == 'cu13'
   - nvidia-nvjitlink>=13.0.0,<14.0.0 ; extra == 'cu13'
-  requires_python: '>=3.11'
-- pypi: https://files.pythonhosted.org/packages/b6/55/a3b4a543185305a9bdf3d9759d53646ed96e55e7dfd43f53e7a421b8fbae/llvmlite-0.47.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
-  name: llvmlite
-  version: 0.47.0
-  sha256: 003bcf7fa579e14db59c1a1e113f93ab8a06b56a4be31c7f08264d1d4072d077
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/be/b6/bb07a3a63b5b7b55516366747892abbf3ee62d616684c40bb51e6cbfe956/nvidia_cuda_nvcc-13.3.33-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
+- pypi: https://files.pythonhosted.org/packages/7c/14/47b329af0047e27e1f0fe2a2f5544f5c6660a01e1a1e0fe8445dddd5747f/numba_cuda-0.30.4-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
+  name: numba-cuda
+  version: 0.30.4
+  sha256: d363e80f0e98d3e6616ced13f226b0e70295085ad97f682c2259eac3ecd1d052
+  requires_dist:
+  - numba>=0.60.0
+  - cuda-bindings>=12.9.1,<14.0.0
+  - cuda-core>=0.5.1,<2.0.0
+  - cuda-pathfinder>=1.4.0,<2.0.0
+  - packaging
+  - cuda-bindings>=12.9.1,<13.0.0 ; extra == 'cu12'
+  - cuda-toolkit[cccl,cudart,nvcc,nvrtc]==12.* ; extra == 'cu12'
+  - nvidia-nvjitlink-cu12>=12.3.0,<13.0.0 ; extra == 'cu12'
+  - cuda-bindings==13.* ; extra == 'cu13'
+  - cuda-toolkit[cccl,cudart,nvrtc,nvvm]==13.* ; extra == 'cu13'
+  - nvidia-nvjitlink>=13.0.0,<14.0.0 ; extra == 'cu13'
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/7e/ce/16d76f4b5b3f7460f5ebd17516685495c149c66651ffdd381f90e4d4e65c/nvidia_cuda_crt-13.3.73-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+  name: nvidia-cuda-crt
+  version: 13.3.73
+  sha256: df14a17ae1c5c3171265411212246654d780f89344ea85344466c6b955247543
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/83/19/e46ef3597ba47a9f8a91ab24533db42a600b659fc418dbe4af0b630bcb41/nvidia_cuda_nvcc-13.3.73-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
   name: nvidia-cuda-nvcc
-  version: 13.3.33
-  sha256: 8c348623b1434aebd234da9ec1f81022587ae4995d65c3dc8a7743245cc441f7
+  version: 13.3.73
+  sha256: f483af83166c4fa356a21606076d553b0b4ceaebbd9912e537545080db695bdd
   requires_dist:
   - nvidia-nvvm
   - nvidia-cuda-runtime
   - nvidia-cuda-crt
   requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/85/a7/e14b58dab02198c42d87b9ba11b17e74eecfb1b91279e7dafcc66b4a59ec/numba_cuda_mlir-0.5.0-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
+  name: numba-cuda-mlir
+  version: 0.5.0
+  sha256: 5385865e55383a2a50a7a0d143a2593dda63ab567dbbea5fe464904c605c29fe
+  requires_dist:
+  - numpy
+  - typing-extensions ; python_full_version < '3.12'
+  - cuda-bindings>=12.9.1,<14.0.0
+  - cuda-core>=0.5.1,<2.0.0
+  - cuda-bindings>=12.9.1,<13.0.0 ; extra == 'cu12'
+  - cuda-toolkit[cccl,cudart,nvcc,nvrtc]==12.* ; extra == 'cu12'
+  - nvidia-nvjitlink-cu12>=12.3.0,<13.0.0 ; extra == 'cu12'
+  - cuda-bindings==13.* ; extra == 'cu13'
+  - cuda-toolkit[cccl,cudart,nvcc,nvrtc]==13.* ; extra == 'cu13'
+  - nvidia-nvjitlink>=13.0.0,<14.0.0 ; extra == 'cu13'
+  requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/8b/2c/86916c8a34dcdb0c3ddd1c0e30545041bd781184e437b9cb76fcda70560b/nvidia_cuda_nvrtc-13.3.33-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl
+  name: nvidia-cuda-nvrtc
+  version: 13.3.33
+  sha256: 82530788b8c6164a54d3fd9ae8bcca8893d397c4aeb998861982a03bbe41e204
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/8c/79/017fab2f7167a9a9795665f894d04f77aafceca80821b51589bb4b23ff5c/nvidia_sphinx_theme-0.0.9.post1-py3-none-any.whl
+  name: nvidia-sphinx-theme
+  version: 0.0.9.post1
+  sha256: 21ca60206dff2f380d7783d64bbaf71a5b9cacae53c7d0686f089c16b5a3d45a
+  requires_dist:
+  - sphinx>=7.1
+  - pydata-sphinx-theme>=0.15
+  requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/96/bd/572971ffc14bd36676c821fc15d991b08fe6179cb09368250147475f954d/nvidia_cuda_cccl-13.3.3.4.1-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
+  name: nvidia-cuda-cccl
+  version: 13.3.3.4.1
+  sha256: 067d19b4b3c9d0f2ebec9f29a311b2863db96bf98e058bbc331597d51ce818cf
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/97/be/5699b6e642b372f7d24c59c2f41383e2696825e20bab85f7399c7c6a56f7/nvidia_cuda_runtime-13.3.29-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+  name: nvidia-cuda-runtime
+  version: 13.3.29
+  sha256: e04420616e72f563167a7733272992d7e6df6dc5cb54b2f94f9f1520ea9e30c1
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/bb/38/926757caaac18a66f057d7544a63620bf360a07d281c9f7ecadd2aa83963/numba-0.67.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+  name: numba
+  version: 0.67.0
+  sha256: f63d43db06b4756424d6d2484737c902e0ae944a0eec3e8b0b4de2c695b15caa
+  requires_dist:
+  - llvmlite>=0.49.0.dev0,<0.50
+  - numpy>=1.22,<2.6
+  requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/be/3c/e97f69c62a2d972066d9a2612ce1f3de313035ac897a5b9f787cad8b55f7/llvmlite-0.49.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+  name: llvmlite
+  version: 0.49.0
+  sha256: 6acba646d88abbc87d5c113a3d62c1fbf8b8fee11c6493f516803e30f21ae870
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/ce/67/5e7dba1ba576dd73da5dee894ca076ca5e959450dfff66d6d510a255d1f7/cuda_bindings-13.3.1-cp312-cp312-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
   name: cuda-bindings
   version: 13.3.1
@@ -20628,11 +18510,6 @@ packages:
   - cuda-toolkit==13.* ; extra == 'all'
   - nvidia-cudla==13.* ; platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'all'
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/d1/32/5ea57f8cd6ad5df2173d175ac5db4e06edde40028b1b1f6c539ea4c10290/nvidia_cuda_crt-13.3.33-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
-  name: nvidia-cuda-crt
-  version: 13.3.33
-  sha256: c8c257393f9c9146a85d3644f352be8154843d760031f756e673222c768a4930
-  requires_python: '>=3'
 - pypi: https://files.pythonhosted.org/packages/d4/e0/c8a1f0c8f9ffdea4f5fe6dbab89b326cef4d85caf489dad39e209da89416/cuda_bindings-13.3.1-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
   name: cuda-bindings
   version: 13.3.1
@@ -20644,39 +18521,63 @@ packages:
   - cuda-toolkit==13.* ; extra == 'all'
   - nvidia-cudla==13.* ; platform_machine == 'aarch64' and sys_platform == 'linux' and extra == 'all'
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/df/b2/87e62e8c3e2f4b32e5fe99e0b86d576da1312593b39f47d8ceef365e95ed/packaging-26.2-py3-none-any.whl
-  name: packaging
-  version: '26.2'
-  sha256: 5fc45236b9446107ff2415ce77c807cee2862cb6fac22b8a73826d0693b0980e
-  requires_python: '>=3.8'
-- pypi: https://files.pythonhosted.org/packages/e3/ab/db09228d5a8c124a93514726d2e18f31824f66d3a6769ee4e51721dd64cf/cuda_core-1.0.1-cp314-cp314t-manylinux_2_24_aarch64.manylinux_2_28_aarch64.whl
+- pypi: https://files.pythonhosted.org/packages/e3/b6/1db1a2f1164b82e5fd867e880dfd964516f1382fb7d35a916c0c2929fa55/numba_cuda-0.30.4-cp312-cp312-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
+  name: numba-cuda
+  version: 0.30.4
+  sha256: 4f229a9314c98a6084e43c3a29ae1568a182bdcab7e87d8fc628a651ea2336ca
+  requires_dist:
+  - numba>=0.60.0
+  - cuda-bindings>=12.9.1,<14.0.0
+  - cuda-core>=0.5.1,<2.0.0
+  - cuda-pathfinder>=1.4.0,<2.0.0
+  - packaging
+  - cuda-bindings>=12.9.1,<13.0.0 ; extra == 'cu12'
+  - cuda-toolkit[cccl,cudart,nvcc,nvrtc]==12.* ; extra == 'cu12'
+  - nvidia-nvjitlink-cu12>=12.3.0,<13.0.0 ; extra == 'cu12'
+  - cuda-bindings==13.* ; extra == 'cu13'
+  - cuda-toolkit[cccl,cudart,nvrtc,nvvm]==13.* ; extra == 'cu13'
+  - nvidia-nvjitlink>=13.0.0,<14.0.0 ; extra == 'cu13'
+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/e6/3a/20d7e9891c4ddfadd6ff8d95bf4b29f353d8e1770553de2099880551dfb9/numpy-2.5.2-cp314-cp314t-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl
+  name: numpy
+  version: 2.5.2
+  sha256: 6df895598c0edcb41030126c89e0f353b07d93238116143b7405e937359736c4
+  requires_python: '>=3.12'
+- pypi: https://files.pythonhosted.org/packages/e7/b6/60a3641111d39ebfcfcd8b8bfd0290d7623c4b8b5f90952c2d84776f8ca4/nvidia_cuda_nvrtc-13.3.33-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
+  name: nvidia-cuda-nvrtc
+  version: 13.3.33
+  sha256: 7b05ecda494c6dabc44231a608b060a71008a730d9dfda932cc508e6d29159e0
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/eb/be/62c73ba4d00aa69687328edcbfed0183923be193f6df97a000ab77518ae5/cuda_core-1.1.1-cp314-cp314-manylinux_2_24_x86_64.manylinux_2_28_x86_64.whl
   name: cuda-core
-  version: 1.0.1
-  sha256: 4410bf1ef15c2ec23dccc302da76893c9354b530dee422e3277b116231bf5fe1
+  version: 1.1.1
+  sha256: be538c4d2c1c6a994408e2665feb1fc7a0a2605eb4ee202ac50201816e62ab8a
   requires_dist:
   - cuda-pathfinder>=1.4.2
   - numpy
   - backports-strenum ; python_full_version < '3.11'
   - cuda-bindings[all]==12.* ; extra == 'cu12'
+  - cuda-toolkit==12.* ; extra == 'cu12'
   - cuda-bindings[all]==13.* ; extra == 'cu13'
+  - cuda-toolkit==13.* ; extra == 'cu13'
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/e6/4b/e3f2cd17822cf772a4a51a0a8080b0032e6d37b2dbe8cfb724eac4e31c52/llvmlite-0.47.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
-  name: llvmlite
-  version: 0.47.0
-  sha256: 5853bf26160857c0c2573415ff4efe01c4c651e59e2c55c2a088740acfee51cd
-  requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/e7/b6/60a3641111d39ebfcfcd8b8bfd0290d7623c4b8b5f90952c2d84776f8ca4/nvidia_cuda_nvrtc-13.3.33-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
-  name: nvidia-cuda-nvrtc
-  version: 13.3.33
-  sha256: 7b05ecda494c6dabc44231a608b060a71008a730d9dfda932cc508e6d29159e0
-  requires_python: '>=3'
 - pypi: https://files.pythonhosted.org/packages/f0/ee/580ca6f29dcab0221db8706badca1bbbb084f1975c4d4e83329c3a7e31f0/nvidia_nvjitlink-13.3.33-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl
   name: nvidia-nvjitlink
   version: 13.3.33
   sha256: 26a6de7fb4c8fdaa7703d3dad720d6d427ddfea5c48a528fd97c11733ad830e5
   requires_python: '>=3'
-- pypi: https://files.pythonhosted.org/packages/fe/fb/195d50d25ab68a76b817ffc68c45b1fb828598ce35a8e5c1736060628dab/nvidia_cuda_cccl-13.3.3.3.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
+- pypi: https://files.pythonhosted.org/packages/f3/e7/ff646aa6015c7e6d12aad234e68925c87b6681d8d18c3ac40535994a3b0d/nvidia_nvvm-13.3.73-py3-none-manylinux2010_x86_64.manylinux_2_12_x86_64.whl
+  name: nvidia-nvvm
+  version: 13.3.73
+  sha256: 0e28e0858a3475e11ac67d35301cd5bf82666a1c0dc4ec4e80ceaf3a5fd1dea8
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/f8/ab/049726d90147865a3ea53bae6cb7c35b98bf1fdf96cdb967101329625f83/nvidia_cuda_cccl-13.3.3.4.1-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
   name: nvidia-cuda-cccl
-  version: 13.3.3.3.1
-  sha256: 40ba1fa0b2c694ddc06cc791ed5c8bdad4638e2735b784960d68ac3086399c97
+  version: 13.3.3.4.1
+  sha256: cc0adc188d570b09f4d606c7dc05a42aa3d8aa082e0d60f7bbfc5b6435f627c6
+  requires_python: '>=3'
+- pypi: https://files.pythonhosted.org/packages/fa/41/2089e411507d66458d67208bdd1bc562d492bb6458c3d2aea4603072a219/nvidia_cuda_crt-13.3.73-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl
+  name: nvidia-cuda-crt
+  version: 13.3.73
+  sha256: 60aacc0b5e1e8b40c62abe4d1ab16440add91b99bd2f17f62dd091586b73d166
   requires_python: '>=3'
diff --git a/cuda_core/pixi.toml b/cuda_core/pixi.toml
index 8772ed4e88b..cbeaf696607 100644
--- a/cuda_core/pixi.toml
+++ b/cuda_core/pixi.toml
@@ -10,7 +10,7 @@ preview = ["pixi-build"]
 [workspace.build-variants]
 python = ["3.10.*", "3.11.*", "3.12.*", "3.13.*", "3.14.*"]
 # Keep source-package metadata aligned with the consuming environment's CUDA major.
-cuda-version = ["12.*", "13.3.*"]
+cuda-version = ["12.*", "13.4.*"]
 
 [feature.test.dependencies]
 cuda-core = { path = "." }
@@ -21,9 +21,13 @@ pytest-randomly = "*"
 pytest-repeat = "*"
 pytest-rerunfailures = "*"
 cloudpickle = "*"
+docutils = "*"
 psutil = "*"
 pyglet = "*"
 
+[feature.test.pypi-dependencies]
+cuda-python-test-helpers = { path = "../cuda_python_test_helpers", editable = true }
+
 [feature.examples.dependencies]
 cuda-core = { path = "." }
 cffi = "*"
@@ -52,7 +56,7 @@ CUDA_HOME = "$CONDA_PREFIX/targets/sbsa-linux"
 CUDA_HOME = "$CONDA_PREFIX/Library"
 
 [feature.cython-tests.dependencies]
-cython = ">=3.2,<3.3" # for tests that exercise APIs from cython
+cython = ">=3.2.5,<3.3" # for tests that exercise APIs from cython
 setuptools = "*"      # for distutils
 gxx = "*"             # to compile the generated code
 # These are necessary because running the Cython tests requires compiling
@@ -86,14 +90,14 @@ CUDA_HOME = "$CONDA_PREFIX/targets/sbsa-linux"
 CUDA_HOME = "$CONDA_PREFIX/Library"
 
 [feature.cu13.dependencies]
-cuda-version = "13.3.*"
+cuda-version = "13.4.*"
 
 [feature.cu12.dependencies]
 cuda-version = "12.*"
 
 [feature.docs.dependencies]
 cuda-core = { path = "." }
-cython = "*"
+cython = ">=3.2.5,<3.3"
 myst-parser = "*"
 numpy = "*"
 numpydoc = "*"
@@ -210,7 +214,7 @@ python = "*"
 cuda-version = "*"
 setuptools = ">=80"
 setuptools-scm = ">=8"
-cython = ">=3.2,<3.3"
+cython = ">=3.2.5,<3.3"
 cuda-nvrtc-dev = "*"
 cuda-bindings = "*"
 dlpack = "*"
diff --git a/cuda_core/pyproject.toml b/cuda_core/pyproject.toml
index f3a0c3a70f9..3eac3a4c0af 100644
--- a/cuda_core/pyproject.toml
+++ b/cuda_core/pyproject.toml
@@ -6,7 +6,7 @@
 requires = [
     "setuptools>=80",
     "setuptools-scm[simple]>=8,!=10.1",
-    "Cython>=3.2,<3.3",
+    "Cython>=3.2.5,<3.3",
     "cuda-pathfinder>=1.5"
 ]
 build-backend = "build_hooks"
@@ -59,7 +59,7 @@ cu13 = ["cuda-bindings[all]==13.*", "cuda-toolkit==13.*"]
 
 [dependency-groups]
 test = [
-    "cython>=3.2,<3.3",
+    "cython>=3.2.5,<3.3",
     "setuptools>=80",
     "pytest==9.1.0",
     "pytest-benchmark==5.2.3",
@@ -69,16 +69,17 @@ test = [
     "pytest-timeout==2.4.0",
     "cloudpickle==3.1.2",
     "psutil==7.2.2",
+    "docutils==0.23",
+    # Required by tests/test_graphics.py; pinned to match cuda_bindings.
+    "pyglet==2.1.14",
     # TODO: remove the Python 3.15 guard once 3.15 is officially supported
     "cffi==2.0.0; python_version < '3.15'",
 ]
-ml-dtypes = ["ml-dtypes>=0.5.4,<0.6.0"]
-test-cu12 = [ {include-group = "ml-dtypes" }, {include-group = "test" }, "cupy-cuda12x; python_version < '3.14'", "cuda-toolkit[cudart]==12.*"]  # runtime headers needed by CuPy
-test-cu13 = [ {include-group = "ml-dtypes" }, {include-group = "test" }, "cupy-cuda13x; python_version < '3.14'", "cuda-toolkit[cudart]==13.*"]  # runtime headers needed by CuPy
-# free threaded build, cupy doesn't support free-threaded builds yet, so avoid installing it for now
-# TODO: cupy should support free threaded builds
-test-cu12-ft = [ {include-group = "ml-dtypes" }, {include-group = "test" }, "cuda-toolkit[cudart]==12.*"]
-test-cu13-ft = [ {include-group = "ml-dtypes" }, {include-group = "test" }, "cuda-toolkit[cudart]==13.*"]
+# TODO: drop the Windows 3.15 guard once ml-dtypes publishes cp315 Windows wheels
+ml-dtypes = ["ml-dtypes>=0.5.4,<0.6.0; sys_platform != 'win32' or python_version < '3.15'"]
+test-ft = ["pytest-run-parallel==0.10.0"]
+test-cu12 = [ {include-group = "ml-dtypes" }, {include-group = "test" }, "cupy-cuda12x; python_version < '3.15'", "cuda-toolkit[cudart]==12.*"]  # runtime headers needed by CuPy
+test-cu13 = [ {include-group = "ml-dtypes" }, {include-group = "test" }, "cupy-cuda13x; python_version < '3.15'", "cuda-toolkit[cudart]==13.*"]  # runtime headers needed by CuPy
 
 [tool.uv]
 conflicts = [
@@ -89,8 +90,6 @@ conflicts = [
     [
         { group = "test-cu12" },
         { group = "test-cu13" },
-        { group = "test-cu12-ft" },
-        { group = "test-cu13-ft" },
     ],
 ]
 
@@ -147,12 +146,6 @@ implicit_reexport = true
 # Ignore missing imports for now (you can tighten this later)
 ignore_missing_imports = true
 
-[[tool.mypy.overrides]]
-# cpdef functions with Cython-native tuple return types can't carry type args
-# through stubgen-pyx; suppress the resulting type-arg error for this module.
-module = "cuda.core._utils.cuda_utils"
-disable_error_code = ["type-arg"]
-
 [tool.cibuildwheel]
 skip = "*-musllinux_*"
 build-verbosity = 1
diff --git a/cuda_core/pytest.ini b/cuda_core/pytest.ini
index c3d243387fe..8661d2cdc64 100644
--- a/cuda_core/pytest.ini
+++ b/cuda_core/pytest.ini
@@ -1,9 +1,10 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # SPDX-License-Identifier: Apache-2.0
 
 [pytest]
-addopts = --showlocals
+addopts = --showlocals --durations=20
+pythonpath = tests
 norecursedirs = cython
 markers =
     # Keep this authorship marker registry in sync across all pytest config roots.
@@ -11,3 +12,5 @@ markers =
     agent_authored(model): agent-authored test not yet materially human-reviewed
     human_reviewed: agent-authored test materially reviewed or rewritten by a human
     human_authored: test authored primarily by a human
+    thread_unsafe(reason): test is not safe to run concurrently with other tests (e.g. uses mocks, patches globals, or mutates shared CUDA state)
+    parallel_threads_limit(n): cap the number of parallel threads pytest-run-parallel uses for this test or module
diff --git a/cuda_core/setup.py b/cuda_core/setup.py
index e0d745b1f21..c66050fe50a 100644
--- a/cuda_core/setup.py
+++ b/cuda_core/setup.py
@@ -51,6 +51,13 @@ def _build_aoti_shim_lib(compiler, plat_name):
 
 
 class build_ext(_build_ext):  # noqa: N801
+    def finalize_options(self):
+        super().finalize_options()
+        # A cu13 .so in the source tree looks perfectly fresh to a cu12 build;
+        # see build_hooks._check_build_major().
+        if build_hooks.force_build_ext:
+            self.force = True
+
     def _configure_windows_tensor_bridge(self):
         if os.name != "nt" or getattr(self.compiler, "compiler_type", None) != "msvc":
             return
@@ -74,6 +81,7 @@ def build_extensions(self):
         self.parallel = nthreads
         self._configure_windows_tensor_bridge()
         super().build_extensions()
+        build_hooks.record_build_major()
 
 
 class build_py(_build_py):  # noqa: N801
@@ -84,11 +92,14 @@ def finalize_options(self):
             self.package_data[""] += ["*.pxi", "*.pyx", "*.cpp"]
 
 
-setup(
-    ext_modules=build_hooks._extensions,
-    cmdclass={
-        "build_ext": build_ext,
-        "build_py": build_py,
-    },
-    zip_safe=False,
-)
+# Guarded so tests can import the command classes above. setuptools always
+# runs this file as __main__, so real builds are unaffected.
+if __name__ == "__main__":
+    setup(
+        ext_modules=build_hooks._extensions,
+        cmdclass={
+            "build_ext": build_ext,
+            "build_py": build_py,
+        },
+        zip_safe=False,
+    )
diff --git a/cuda_core/tests/AGENTS.md b/cuda_core/tests/AGENTS.md
new file mode 100644
index 00000000000..08d9df18847
--- /dev/null
+++ b/cuda_core/tests/AGENTS.md
@@ -0,0 +1,248 @@
+# cuda.core test suite
+
+Package-wide conventions live in `../AGENTS.md`; repository-wide ones in
+`../../AGENTS.md`. This file covers conventions specific to the tests.
+
+## Never create an uncapped memory pool
+
+A memory pool created without `max_size` reserves virtual address space similar
+in size to the installed physical device memory regardless of what the test
+actually allocates. The reservation is charged to the process address space
+even though it is not backed by physical memory, and it is not returned until
+the pool is destroyed *and* the stream-ordered frees of its outstanding
+allocations retire. The whole suite shares one process and one device, so these
+reservations accumulate across tests.
+
+When a test needs its own pool, use the suite-wide cap from
+`helpers/constants.py`:
+
+```python
+from helpers.constants import POOL_SIZE
+
+mr = DeviceMemoryResource(dev, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+```
+
+Use a larger value only if a test genuinely requires it, and prefer adding a
+shared constant to `helpers/constants.py` over redefining one per module.
+
+### Passing no options is different from passing empty options
+
+`DeviceMemoryResource(dev)` with no options does **not** create a pool. It
+wraps the device's existing default mempool (`_mempool_owned` is false) and
+costs no additional address space. Passing *any* options object creates a new
+owned pool, and a new pool without `max_size` is uncapped:
+
+```python
+DeviceMemoryResource(dev)  # wraps default pool, free
+DeviceMemoryResource(dev, DeviceMemoryResourceOptions())  # NEW uncapped pool, expensive
+DeviceMemoryResource(dev, {"ipc_enabled": True})  # NEW uncapped pool, expensive
+```
+
+Do not add `max_size` to a call that currently passes no options: that
+converts a free default-pool wrapper into a new pool and makes things worse.
+
+### Managed pools are exempt
+
+`cuMemPoolCreate` requires `CUmemPoolProps.maxSize` to be zero for managed
+pools, so `ManagedMemoryResourceOptions` has no `max_size` option. Managed
+pools cannot be right-sized and are not checked.
+
+### Document exemptions
+
+When a call is deliberately exempt -- most often because it sits inside
+`pytest.raises` and no pool is ever created -- annotate it:
+
+```python
+with pytest.raises(RuntimeError, match="IPC is not available"):
+    # uncapped-pool-ok: raises before the pool is created
+    DeviceMemoryResource(mempool_device, DeviceMemoryResourceOptions(ipc_enabled=True))
+```
+
+## Release resources at test boundaries
+
+The `init_cuda` fixture in `conftest.py` runs `gc.collect()` followed
+by `cuCtxSynchronize()` before popping the context. Tests should not rely on
+that as a substitute for cleaning up explicitly: prefer context managers for
+resources whose lifetime fits a single scope, and keep pool lifetimes inside
+the test that creates them.
+
+## Shared test support
+
+See also: https://docs.pytest.org/en/stable/reference/fixtures.html#conftest-py-sharing-fixtures-across-multiple-files
+
+Follow these rules when adding or moving shared test code:
+
+- Never import from a `conftest.py`.
+- Put suite-wide fixtures and pytest hooks in `tests/conftest.py`. Put fixtures
+  needed only by one test subtree in that subtree's nearest `conftest.py`.
+- Put a pytest hook in a nested `conftest.py` only if pytest supports that hook
+  there. If the hook receives suite-wide data, explicitly limit its effects to
+  the intended subtree.
+- Code used only to implement fixtures or hooks may remain in the same
+  `conftest.py`. Put functions and constants imported by test modules in
+  `tests/helpers/` instead.
+- Import helpers explicitly from the test root, for example:
+  `from helpers.memory import create_managed_memory_resource_or_skip`.
+- Search `tests/helpers/` and `cuda_python_test_helpers/` for prior art
+  before adding a new helper; consolidate duplicates across
+
+  packages into `cuda_python_test_helpers` (both `cuda_core` and
+  `cuda_bindings` test environments already depend on it).
+- Fixtures in a nested `conftest.py` are available to tests in its directory
+  and descendants; fixtures from applicable parent `conftest.py` files remain
+  available.
+- Do not add `__init__.py` solely because a test directory contains a
+  `conftest.py`.
+- In directories without `__init__.py`, keep test-module basenames unique
+  within this test suite.
+
+## Skip only real setup failures
+
+`pytest.skip(reason)` records the test as SKIPPED with `reason` in the
+report. A helper that wraps `yield` in `except Exception: pytest.skip(...)`
+therefore records every test-body failure as a skip — a real regression, a
+`TypeError`, an `AttributeError` all become "SKIPPED: <reason>" instead of
+"FAILED", and the suite goes green regardless of whether the code under
+test works.
+
+Catch only the specific exception that legitimately means "not available",
+and only around the setup call — never around `yield`:
+
+```python
+@contextlib.contextmanager
+def _gl_context():
+    try:
+        win, tex_id = _setup_gl_texture()      # setup only
+    except (pyglet.NoSuchConfigException, GLContextError) as e:
+        pytest.skip(f"GL unavailable: {e}")
+    try:
+        yield tex_id                          # body exceptions propagate
+    finally:
+        _cleanup(win, tex_id)
+```
+
+The exception names in the example are illustrative — `GLContextError`
+is not a real pyglet class. Match real pyglet exception names by type, or
+use the shared `is_gl_context_unavailable` helper in
+`cuda_python_test_helpers.graphics`.
+
+`GLException` is pyglet's generic GL-error class, raised after any GL call that reports an error
+(`GL_INVALID_ENUM`, etc.). Do **not** include it in the "GL unavailable" set — it hides real bugs in GL allocation code as skips.
+
+Platform-specific "library not loadable" manifestations (genuine "GL unavailable"):
+
+- Linux without libGL/libEGL: `ImportError('Library "GL" not found.')` / `ImportError('Library "EGL" not found.')` from `pyglet/lib.py`.
+- Windows without opengl32.dll: `FileNotFoundError` from `ctypes.windll.opengl32`; on Python 3.12+ `ctypes.LibraryLoader` re-raises `AttributeError("opengl32")`.
+
+When a CUDA call's error means "feature refused by this driver" (e.g.
+`CUDA_ERROR_OPERATING_SYSTEM` for CUDA-GL interop on WSL), skip at the call
+site with a narrow catch on the specific error, not inside the GL helper —
+see `_register_gl_buffer` / `_register_gl_image` in `tests/test_graphics.py`.
+
+## `importorskip` is for optional dependencies only
+
+`pytest.importorskip("X")` is correct when `X` is genuinely optional
+(platform-gated binding, parametrized "test each available module"). It is
+dead code when `X` is a declared test or runtime dependency: the skip then
+fires only when the environment is broken, which is the case you want to fail
+loudly, not hide. Use a bare top-level `import` for declared deps.
+
+Before adding `importorskip`, check `cuda_core/pyproject.toml`'s `test`
+and `test-cu*` groups and `cuda_core`'s `dependencies`. If the target is
+listed, import it directly.
+
+## Capability probes must not swallow real bugs
+
+A probe function that answers "is feature X available?" by catching
+`Exception` and returning `False` will report "not available" even when the
+probed API failed for a real, unexpected reason — silently enabling a skip
+that hides the bug. Catch only the exception that genuinely means "not
+available", and split the checks so each catch is narrow:
+
+```python
+def _is_nvfatbin_available():
+    from cuda.bindings._internal.utils import FunctionNotFoundError
+    from cuda.pathfinder import DynamicLibNotFoundError
+
+    try:
+        from cuda.bindings import nvfatbin
+    except ImportError:
+        return False
+    try:
+        nvfatbin.version()
+    except (DynamicLibNotFoundError, FunctionNotFoundError):
+        # libnvfatbin not loadable, or nvFatbinVersion symbol missing.
+        return False
+    return True
+```
+
+Catch only the exceptions that mean "not installed / not loadable".
+A genuine API-status failure (e.g. `nvfatbin.nvFatbinError` from a
+successfully loaded library) must propagate so a real bug is not hidden
+as "unavailable".
+
+For a probe that calls a CUDA API returning a `CUresult`, let `handle_return`
+raise on any non-success result and classify only a successful bitmask
+lacking the documented bit as `False`; other failures propagate so a real driver bug is not hidden as "unsupported":
+
+```python
+@functools.cache
+def supports_ipc_mempool(device_id):
+    from cuda.bindings import driver
+
+    handle_return(driver.cuInit(0))
+    dev_id = int(getattr(device_id, "device_id", device_id))
+    attr = driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MEMPOOL_SUPPORTED_HANDLE_TYPES
+    mask = handle_return(driver.cuDeviceGetAttribute(attr, dev_id))
+    posix_fd = driver.CUmemAllocationHandleType.CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR
+    return (int(mask) & int(posix_fd)) != 0
+```
+
+Do not catch `ImportError` for a hard runtime dependency (e.g.
+`cuda.bindings` for `cuda.core`) — that is a broken environment and should
+surface at collection time.
+
+## Clean up partial setup on failure
+
+If a setup step allocates a resource (GL object, window, file handle) and a later
+step fails, clean up the partial resource before re-raising so it does not
+leak. Wrap the allocation in `try/except` and delete the generated object in
+the `except` before re-raising:
+
+```python
+def _allocate_gl_buffer(win, nbytes):
+    from pyglet.gl import gl as _gl
+
+    buf_id = _gl.GLuint(0)
+    try:
+        _gl.glGenBuffers(1, ctypes.byref(buf_id))
+        _gl.glBindBuffer(_gl.GL_ARRAY_BUFFER, buf_id.value)
+        _gl.glBufferData(_gl.GL_ARRAY_BUFFER, nbytes, None, _gl.GL_DYNAMIC_DRAW)
+        return buf_id
+    except Exception:
+        if buf_id.value:
+            with contextlib.suppress(Exception):
+                _gl.glDeleteBuffers(1, ctypes.byref(buf_id))
+        raise
+```
+
+Initialize handles to `None` before the protected region so the `finally`
+cleanup does not `NameError` when allocation raises before returning a handle.
+
+## Tests that touch CUDA must establish their own context
+
+The `init_cuda` fixture pops the CUDA context on teardown, so a test
+that calls a CUDA API without `init_cuda` (or an explicit
+`Device.set_current()`) inherits whatever context the previous test happened
+to leave current on the thread — possibly none. With `pytest-randomly` that
+makes the pass/fail outcome depend on test order, so it moves seed to seed and
+looks like flakiness. Request `init_cuda` for any test that calls into the
+driver, or set up and tear down a context yourself.
+
+## Assert on behavior, not implementation
+
+Pin on observable behavior the contract guarantees — return values, raised
+exception types, public state transitions. Avoid asserting on internal
+call counts, private helper invocation order, or error message substrings
+that are not part of the contract. A refactor that preserves behavior but
+changes internals should not break the test.
diff --git a/cuda_core/tests/conftest.py b/cuda_core/tests/conftest.py
index ca3782c67f2..a8678292422 100644
--- a/cuda_core/tests/conftest.py
+++ b/cuda_core/tests/conftest.py
@@ -2,15 +2,35 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import functools
+import gc
+import importlib
 import multiprocessing
 import os
 import pathlib
 import sys
-from contextlib import contextmanager
-from importlib.metadata import PackageNotFoundError, distribution
 
 import pytest
 
+# Keep in sync with cuda_bindings/tests/conftest.py.
+try:
+    import cuda_python_test_helpers._pytest_plugin  # noqa: F401
+except ImportError as e:
+    # Don't call .resolve(): resolving symlinks can make parents[2] point
+    # somewhere other than the monorepo root if a sub-directory is symlinked.
+    _test_helpers_root = pathlib.Path(__file__).parents[2] / "cuda_python_test_helpers"
+    if not _test_helpers_root.is_dir():
+        raise RuntimeError(f"cuda-python-test-helpers not installed and not found at {_test_helpers_root}") from e
+    for _k in list(sys.modules):
+        if _k == "cuda_python_test_helpers" or _k.startswith("cuda_python_test_helpers."):
+            del sys.modules[_k]
+    sys.path.insert(0, str(_test_helpers_root))
+    importlib.invalidate_caches()
+
+pytest_plugins = ["cuda_python_test_helpers._pytest_plugin"]
+
+from helpers.constants import POOL_SIZE
+from helpers.memory import skip_if_pinned_memory_unsupported
+
 import cuda.core
 from cuda.bindings import driver
 from cuda.core import (
@@ -23,73 +43,7 @@
     PinnedMemoryResourceOptions,
     _device,
 )
-from cuda.core._utils.cuda_utils import CUDAError, handle_return
-from cuda.pathfinder import get_cuda_path_or_home
-
-try:
-    from cuda.bindings._test_helpers.mempool import xfail_if_mempool_oom
-except ModuleNotFoundError:
-    # Older cuda.bindings artifacts (for example 12.9.x backports) do not ship
-    # this helper yet. Keep the fallback local so tests against published
-    # bindings still xfail the known Windows MCDM mempool setup issue.
-    #
-    # Keep in sync with cuda_bindings/cuda/bindings/_test_helpers/mempool.py.
-    # This copy is intentionally simpler because it only handles cuda_core
-    # CUDAError exceptions when the shared helper is absent.
-    def _is_windows_mcdm_device(device=0):
-        if sys.platform != "win32":
-            return False
-        import cuda.bindings.nvml as nvml
-
-        device_id = int(getattr(device, "device_id", device))
-        (err,) = driver.cuInit(0)
-        if err != driver.CUresult.CUDA_SUCCESS:
-            return False
-        err, pci_bus_id = driver.cuDeviceGetPCIBusId(13, device_id)
-        if err != driver.CUresult.CUDA_SUCCESS:
-            return False
-        pci_bus_id = pci_bus_id.split(b"\x00", 1)[0].decode("ascii")
-        nvml.init_v2()
-        try:
-            handle = nvml.device_get_handle_by_pci_bus_id_v2(pci_bus_id)
-            current, _ = nvml.device_get_driver_model_v2(handle)
-            return current == nvml.DriverModel.DRIVER_MCDM
-        finally:
-            nvml.shutdown()
-
-    def xfail_if_mempool_oom(err_or_exc, api_name=None, device=0):
-        if api_name is not None and not isinstance(api_name, str):
-            device = api_name
-            api_name = None
-
-        if "CUDA_ERROR_OUT_OF_MEMORY" not in str(err_or_exc):
-            return
-        try:
-            is_windows_mcdm = _is_windows_mcdm_device(device)
-        except Exception:
-            # If MCDM detection fails, leave the primary test failure visible.
-            return
-        if not is_windows_mcdm:
-            return
-
-        api_context = f"{api_name} " if api_name else ""
-        pytest.xfail(f"{api_context}could not reserve VA for mempool operations on Windows MCDM")
-
-
-# Import shared test helpers for tests across subprojects.
-# PLEASE KEEP IN SYNC with copies in other conftest.py in this repo.
-_test_helpers_root = pathlib.Path(__file__).resolve().parents[2] / "cuda_python_test_helpers"
-try:
-    distribution("cuda-python-test-helpers")
-except PackageNotFoundError as exc:
-    if not _test_helpers_root.is_dir():
-        raise RuntimeError(
-            f"cuda-python-test-helpers not installed; expected checkout path {_test_helpers_root}"
-        ) from exc
-
-    test_helpers_root = str(_test_helpers_root)
-    if test_helpers_root not in sys.path:
-        sys.path.insert(0, test_helpers_root)
+from cuda.core._utils.cuda_utils import handle_return
 
 
 def pytest_configure(config):
@@ -99,22 +53,22 @@ def pytest_configure(config):
         config.pluginmanager.register(_CudaCoreParallelPlugin(), name="_cuda_core_parallel_plugin")
 
 
-@contextmanager
-def _init_cuda_context():
-    # TODO: rename this to e.g. init_context
-    device = Device(0)
-    device.set_current()
+@pytest.hookimpl(wrapper=True)
+def pytest_runtest_makereport(item, call):
+    # Runs the OOM reason checker on the first CUDA OOM of a session; see
+    # issue #2381 and helpers/oom_diagnostics.py for why this is latched and
+    # what it checks (host VA exhaustion vs. physical device memory).
+    report = yield
+    from helpers import oom_diagnostics
 
-    # Set option to avoid spin-waiting on synchronization.
-    if int(os.environ.get("CUDA_CORE_TEST_BLOCKING_SYNC", 0)) != 0:
-        handle_return(
-            driver.cuDevicePrimaryCtxSetFlags(device.device_id, driver.CUctx_flags.CU_CTX_SCHED_BLOCKING_SYNC)
-        )
+    oom_diagnostics.record_if_oom(item, call, report)
+    return report
 
-    try:
-        yield device
-    finally:
-        _ = _device_unset_current()
+
+def pytest_terminal_summary(terminalreporter):
+    from helpers import oom_diagnostics
+
+    oom_diagnostics.report_terminal_summary(terminalreporter)
 
 
 def _wrap_worker_cuda_test(func):
@@ -124,13 +78,17 @@ def _wrap_worker_cuda_test(func):
     @functools.wraps(func)
     def wrapper(*args, **kwargs):
         kwargs = dict(kwargs)  # copy before mutating
-        with _init_cuda_context() as device:
+        device = Device(0)
+        device.set_current()
+        try:
             if "init_cuda" in kwargs:
                 kwargs["init_cuda"] = device
             if "mempool_device_x2" in kwargs:
                 kwargs["mempool_device_x2"] = _mempool_device_impl(2)
             if "mempool_device_x3" in kwargs:
                 kwargs["mempool_device_x3"] = _mempool_device_impl(3)
+            if "device_x2" in kwargs:
+                kwargs["device_x2"] = _device_x2_impl()
 
             # These are used by test_green_context.py.  The original fixtures include
             # pytest.skip() but that should have correctly fired by this time.
@@ -144,6 +102,12 @@ def wrapper(*args, **kwargs):
                 groups, _ = device.resources.sm.split(SMResourceOptions(count=None))
                 kwargs["green_ctx"] = device.create_context(ContextOptions(resources=[groups[0]]))
             return func(*args, **kwargs)
+        finally:
+            # Unlike the `init_cuda` fixture we do not synchronize here
+            # to avoid doing so while other workers are still running.
+            # (E.g. for stream capture). The fixture cleanup is still run
+            # even with pytest-run-parallel after worker join.
+            _ = _device_unset_current()
 
     wrapper._cuda_core_worker_cuda_wrapped = True
     return wrapper
@@ -173,86 +137,11 @@ def pytest_collection_modifyitems(self, config, items):
                 item.obj = _wrap_worker_cuda_test(item.obj)
 
 
-def skip_if_pinned_memory_unsupported(device):
-    try:
-        if not device.properties.host_memory_pools_supported:
-            pytest.skip("Device does not support host mempool operations")
-    except AttributeError:
-        pytest.skip("PinnedMemoryResource requires CUDA 13.0 or later")
-
-
-def skip_if_managed_memory_unsupported(device):
-    try:
-        if not device.properties.memory_pools_supported or not device.properties.concurrent_managed_access:
-            pytest.skip("Device does not support managed memory pool operations")
-    except AttributeError:
-        pytest.skip("ManagedMemoryResource requires CUDA 13.0 or later")
-    try:
-        ManagedMemoryResource()
-    except CUDAError as e:
-        xfail_if_mempool_oom(e, device)
-        raise
-    except RuntimeError as e:
-        if "requires CUDA 13.0" in str(e):
-            pytest.skip("ManagedMemoryResource requires CUDA 13.0 or later")
-        raise
-
-
-def create_managed_memory_resource_or_skip(*args, xfail_device=None, **kwargs):
-    # Keep the established "skip" helper name for call-site readability, even though
-    # Windows MCDM mempool OOM setup failures are xfailed instead of skipped.
-    try:
-        return ManagedMemoryResource(*args, **kwargs)
-    except CUDAError as e:
-        xfail_if_mempool_oom(e, _device_id_from_resource_options(xfail_device, args, kwargs))
-        if "CUDA_ERROR_NOT_SUPPORTED" in str(e):
-            pytest.skip("ManagedMemoryResource is not supported on this platform/device")
-        raise
-    except RuntimeError as e:
-        if "requires CUDA 13.0" in str(e):
-            pytest.skip("ManagedMemoryResource requires CUDA 13.0 or later")
-        raise
-
-
-def create_pinned_memory_resource_or_xfail(*args, xfail_device=None, **kwargs):
-    try:
-        return PinnedMemoryResource(*args, **kwargs)
-    except CUDAError as e:
-        xfail_if_mempool_oom(e, xfail_device)
-        raise
-
-
-@contextmanager
-def xfail_on_graph_mempool_oom(device=0):
-    try:
-        yield
-    except CUDAError as e:
-        xfail_if_mempool_oom(e, "cuGraphAddMemAllocNode", device)
-        raise
-
-
-def _device_id_from_resource_options(device, args, kwargs):
-    if device is not None:
-        return device
-    options = kwargs.get("options")
-    if options is None and args:
-        options = args[0]
-    if options is None:
-        return 0
-    if isinstance(options, dict):
-        preferred_location = options.get("preferred_location")
-        preferred_location_type = options.get("preferred_location_type")
-    else:
-        preferred_location = getattr(options, "preferred_location", None)
-        preferred_location_type = getattr(options, "preferred_location_type", None)
-    if preferred_location_type in (None, "device") and isinstance(preferred_location, int) and preferred_location >= 0:
-        return preferred_location
-    return 0
-
-
 def _require_ipc_mempool_devices(devices):
     """Return devices if they all support IPC-enabled mempools, otherwise skip."""
-    from helpers import IS_WSL, supports_ipc_mempool
+    from helpers import supports_ipc_mempool
+
+    from cuda_python_test_helpers import IS_WSL
 
     checked_devices = tuple(devices)
 
@@ -276,8 +165,33 @@ def session_setup():
 
 @pytest.fixture
 def init_cuda():
-    with _init_cuda_context() as device:
+    # TODO: rename this to e.g. init_context
+    device = Device(0)
+    device.set_current()
+
+    # Set option to avoid spin-waiting on synchronization.
+    if int(os.environ.get("CUDA_CORE_TEST_BLOCKING_SYNC", 0)) != 0:
+        handle_return(
+            driver.cuDevicePrimaryCtxSetFlags(device.device_id, driver.CUctx_flags.CU_CTX_SCHED_BLOCKING_SYNC)
+        )
+
+    try:
         yield device
+    finally:
+        # Force any pool/allocation whose only remaining reference was a local
+        # in this test's frame to actually get destroyed now, then drain the
+        # context so the stream-ordered frees that destruction enqueues retire
+        # before the next test runs. Without this, a memory pool's VA
+        # reservation is not returned until both have happened, and per-test
+        # leftovers accumulate across the run -- which is how full-suite runs
+        # can exhaust address space and hit CUDA_ERROR_OUT_OF_MEMORY on a
+        # device with plenty of free physical memory (issue #2381). gc.collect()
+        # must run first: cuCtxSynchronize alone cannot drain frees that were
+        # never enqueued because their owning object had not been collected yet.
+        # With pytest-run-parallel this runs after worker join.
+        gc.collect()
+        driver.cuCtxSynchronize()
+        _ = _device_unset_current()
 
 
 def _device_unset_current() -> bool:
@@ -302,6 +216,24 @@ def deinit_cuda():
     _ = _device_unset_current()
 
 
+def _device_x2_impl():
+    devices = Device.get_all_devices()
+    if len(devices) < 2:
+        pytest.skip("Test requires at least 2 CUDA devices")
+    return devices[:2]
+
+
+@pytest.fixture
+def device_x2(init_cuda):
+    """Provide two CUDA devices, or skip when fewer are available.
+
+    Depends on ``init_cuda`` so that, under pytest-run-parallel, the test is
+    wrapped by ``_wrap_worker_cuda_test`` and the devices are re-fetched on the
+    worker thread (Device objects are thread-local).
+    """
+    return _device_x2_impl()
+
+
 @pytest.fixture
 def deinit_all_contexts_function():
     def pop_all_contexts():
@@ -347,7 +279,6 @@ def ipc_device(init_cuda):
 )
 def ipc_memory_resource(request, ipc_device):
     """Provides IPC-enabled memory resource (either Device or Pinned)."""
-    POOL_SIZE = 2097152
     mr_type = request.param
 
     if mr_type == "device":
@@ -445,22 +376,3 @@ def test_something(memory_resource_factory):
                 mr = MRClass()
     """
     return request.param
-
-
-# Please keep in sync with the copy in the top-level conftest.py.
-def _cuda_headers_available() -> bool:
-    """Return True if CUDA headers are available, False otherwise.
-
-    Returns False if no CUDA path is set or if the CUDA path has no
-    include/ subdirectory (e.g. a sanitizer-only mini-CTK install).
-    """
-    cuda_path = get_cuda_path_or_home()
-    if cuda_path is None:
-        return False
-    return os.path.isdir(os.path.join(cuda_path, "include"))
-
-
-skipif_need_cuda_headers = pytest.mark.skipif(
-    not _cuda_headers_available(),
-    reason="need CUDA header",
-)
diff --git a/cuda_core/tests/example_tests/__init__.py b/cuda_core/tests/example_tests/__init__.py
deleted file mode 100644
index e69de29bb2d..00000000000
diff --git a/cuda_core/tests/example_tests/test_basic_examples.py b/cuda_core/tests/example_tests/test_basic_examples.py
index a8a47791991..7abb895fb12 100644
--- a/cuda_core/tests/example_tests/test_basic_examples.py
+++ b/cuda_core/tests/example_tests/test_basic_examples.py
@@ -11,24 +11,18 @@
 import warnings
 
 import pytest
+from cuda_python_test_helpers.pep723 import has_package_requirements_or_skip
 
-from cuda.core import Device, ManagedMemoryResource, system
+from cuda.core import Device, ManagedMemoryResource
 from cuda.core._program import _can_load_generated_ptx
 
-try:
-    from cuda.bindings._test_helpers.pep723 import has_package_requirements_or_skip
-except ImportError:
-    # If the import fails, we define a dummy function that will cause all tests to be skipped.
-    def has_package_requirements_or_skip(example):
-        pytest.skip("PEP 723 test helper is not available")
-
 
 def has_compute_capability_9_or_higher() -> bool:
     return Device().compute_capability >= (9, 0)
 
 
 def has_multiple_devices() -> bool:
-    return system.get_num_devices() >= 2
+    return len(Device.get_all_devices()) >= 2
 
 
 def has_display() -> bool:
@@ -82,6 +76,7 @@ def has_recent_memory_pool_support() -> bool:
 
 SYSTEM_REQUIREMENTS = {
     "memory_pool_resources.py": has_recent_memory_pool_support,
+    "batched_memcpy.py": has_recent_memory_pool_support,
     "gl_interop_plasma.py": has_display,
     "gl_interop_fluid.py": has_display,
     "gl_interop_mipmap_lod.py": has_display,
diff --git a/cuda_core/tests/graph/test_device_launch.py b/cuda_core/tests/graph/test_device_launch.py
index 221b09bd815..5056b01fd43 100644
--- a/cuda_core/tests/graph/test_device_launch.py
+++ b/cuda_core/tests/graph/test_device_launch.py
@@ -5,8 +5,9 @@
 
 import numpy as np
 import pytest
-from helpers.marks import requires_module
+from cuda_python_test_helpers.marks import requires_module
 
+import cuda.pathfinder as pathfinder
 from cuda.core import (
     Device,
     LaunchConfig,
@@ -48,7 +49,6 @@ def _compile_device_launcher_kernel():
 
     Raises pytest.skip if libcudadevrt.a cannot be found.
     """
-    pathfinder = pytest.importorskip("cuda.pathfinder")
     try:
         cudadevrt_path = pathfinder.find_static_lib("cudadevrt")
     except pathfinder.StaticLibNotFoundError as e:
diff --git a/cuda_core/tests/graph/test_graph_builder.py b/cuda_core/tests/graph/test_graph_builder.py
index 443399c4590..b681e19de8a 100644
--- a/cuda_core/tests/graph/test_graph_builder.py
+++ b/cuda_core/tests/graph/test_graph_builder.py
@@ -7,14 +7,17 @@
 import time
 import weakref
 
+import helpers
 import numpy as np
 import pytest
+from cuda_python_test_helpers.marks import requires_module, skipif_need_cuda_headers
 from helpers.graph_kernels import compile_common_kernels, compile_conditional_kernels
-from helpers.marks import requires_module
 from helpers.misc import try_create_condition
+from packaging.version import Version
 
-from cuda.core import Device, LaunchConfig, LegacyPinnedMemoryResource, launch
-from cuda.core.graph import GraphBuilder, GraphDefinition
+import cuda.bindings
+from cuda.core import Device, LaunchConfig, LegacyPinnedMemoryResource, Program, ProgramOptions, StreamOptions, launch
+from cuda.core.graph import Graph, GraphBuilder, GraphCompleteOptions, GraphDefinition
 from cuda.core.graph._graph_builder import (
     _capture_callback_with_tail_failure_for_testing,
 )
@@ -29,6 +32,13 @@ def _wait_until(predicate, timeout=5.0):
         time.sleep(0.02)
 
 
+def _skip_if_conditional_handles_unsupported():
+    from cuda.core._utils.version import binding_version, driver_version
+
+    if driver_version() < (12, 3, 0) or binding_version() < (12, 3, 0):
+        pytest.skip("conditional handles require CUDA driver and bindings 12.3+")
+
+
 def test_graph_is_building(init_cuda):
     gb = Device().create_graph_builder()
     assert gb.is_building is False
@@ -213,7 +223,7 @@ def test_graph_complete_after_close_forked(init_cuda):
 
     # join() closes the non-root builder (right); it must now be rejected, not crash.
     GraphBuilder.join(left, right)
-    with pytest.raises(RuntimeError, match="^Graph builder has been closed."):
+    with pytest.raises(RuntimeError, match="^GraphBuilder has been closed"):
         right.complete()
 
 
@@ -231,7 +241,7 @@ def test_graph_update_after_source_close(init_cuda):
     source.end_building()
     source.close()
 
-    with pytest.raises(ValueError, match="^Source graph builder has been closed."):
+    with pytest.raises(RuntimeError, match="^GraphBuilder has been closed"):
         graph.update(source)
 
 
@@ -306,6 +316,21 @@ def read_byte(data):
     assert result[0] == 0xAB
 
 
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+def test_graph_capture_callback_ctypes_rejects_incompatible_signature(init_cuda):
+    """Stream-capture host callbacks use the same ctypes ABI check."""
+    import ctypes
+
+    bad_type = ctypes.CFUNCTYPE(ctypes.c_int, ctypes.c_void_p)
+    launch_stream = Device().create_stream()
+    gb = launch_stream.create_graph_builder().begin_building()
+    try:
+        with pytest.raises(TypeError, match="CUhostFn"):
+            gb.callback(bad_type(0))
+    finally:
+        gb.end_building()
+
+
 @pytest.mark.agent_authored(model="claude-opus-4.8")
 def test_graph_capture_callback_python_survives_del(init_cuda):
     """Captured callback is retained by its graph-node user object after del."""
@@ -449,6 +474,46 @@ def test_graph_close_is_idempotent(init_cuda):
     assert int(graph.handle) == 0
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_graph_and_builder_rejected_before_operations(init_cuda):
+    device = Device()
+    stream = device.create_stream()
+    graph_def = GraphDefinition()
+    node = graph_def.empty()
+    graph = graph_def.instantiate()
+    graph.close()
+
+    assert graph.is_closed
+    assert bool(graph) is True  # Preserve backward-compatible truthiness after close.
+    for operation in (
+        lambda: graph[node],
+        lambda: graph.update(graph_def),
+        lambda: graph.upload(stream),
+        lambda: graph.launch(stream),
+    ):
+        with pytest.raises(RuntimeError, match="Graph has been closed"):
+            operation()
+
+    builder = device.create_graph_builder()
+    other = device.create_graph_builder()
+    builder.close()
+    assert builder.is_closed
+    assert bool(builder) is True  # Preserve backward-compatible truthiness after close.
+    with pytest.raises(RuntimeError, match="GraphBuilder has been closed"):
+        GraphBuilder.join(builder, other)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_graph_instantiation_rejects_closed_upload_stream(init_cuda):
+    graph_def = GraphDefinition()
+    graph_def.empty()
+    stream = Device().create_stream()
+    stream.close()
+
+    with pytest.raises(RuntimeError, match="Stream has been closed"):
+        graph_def.instantiate(GraphCompleteOptions(upload_stream=stream))
+
+
 def test_graph_stream_lifetime(init_cuda):
     mod = compile_common_kernels()
     empty_kernel = mod.get_kernel("empty_kernel")
@@ -694,3 +759,264 @@ def test_graph_definition_conditional_body_during_capture_raises(init_cuda):
     finally:
         body_gb.end_building()
         gb.end_building()
+
+
+@requires_module(np, "2.2.5", reason="need numpy 2.2.5+ (numpy GH #28632)")
+def test_pdl_launch_graph_capture(init_cuda):
+    """PDL LaunchConfig is graph-compatible via GraphBuilder stream capture.
+
+    Captures a first then a secondary launch with
+    ``programmatic_stream_serialization=True``, instantiates, and launches.
+    Asserts functional correctness and that capture maps to a programmatic
+    dependency edge (see Programming Guide, Programmatic Dependent Launch) —
+    not kernel overlap.
+    """
+
+    def _assert_programmatic_dependency_edge(graph_definition):
+        """Assert capture of ProgrammaticStreamSerialization produced a programmatic edge.
+
+        Per Programming Guide (Programmatic Dependent Launch): stream-capturing a
+        secondary launch with ``cudaLaunchAttributeProgrammaticStreamSerialization``
+        maps to a programmatic dependency edge from the programmatic kernel port.
+        """
+        from cuda.bindings import driver
+
+        # cuda.bindings before 13.3.0 (before 12.9.7 on the 12.x branch) returned
+        # CUgraphEdgeData wrappers backed by a scratch buffer that was freed before the
+        # call returned, so every field reads back as freed heap memory (#1804).
+        version = Version(cuda.bindings.__version__)
+        if version < Version("13.3.0" if version.major >= 13 else "12.9.7"):
+            pytest.skip(f"cuda.bindings {version} returns dangling graph edge data (#1804)")
+
+        h_graph = graph_definition.handle
+        if driver.CUDA_VERSION >= 13000:
+            get_edges = driver.cuGraphGetEdges
+        else:
+            get_edges = driver.cuGraphGetEdges_v2
+
+        err, _, _, _, num_edges = get_edges(h_graph)
+        assert err == driver.CUresult.CUDA_SUCCESS, err
+        err, _, _, edge_data, num_edges = get_edges(h_graph, num_edges)
+        assert err == driver.CUresult.CUDA_SUCCESS, err
+        assert num_edges == 1, f"expected 1 edge, got {num_edges}"
+        ed = edge_data[0]
+        # Driver (cuda.h) ↔ Runtime / Programming Guide (driver_types.h):
+        #   CU_GRAPH_DEPENDENCY_TYPE_PROGRAMMATIC  ↔ cudaGraphDependencyTypeProgrammatic
+        #   CU_GRAPH_KERNEL_NODE_PORT_PROGRAMMATIC ↔ cudaGraphKernelNodePortProgrammatic
+        assert ed.type == driver.CUgraphDependencyType.CU_GRAPH_DEPENDENCY_TYPE_PROGRAMMATIC, ed.type
+        assert ed.from_port == driver.CU_GRAPH_KERNEL_NODE_PORT_PROGRAMMATIC, ed.from_port
+
+    mod = compile_common_kernels()
+    dummy_kernel = mod.get_kernel("add_one")
+
+    stream = Device().create_stream()
+    mr = LegacyPinnedMemoryResource()
+    buf = mr.allocate(4)
+    arr = np.from_dlpack(buf).view(np.int32)
+    arr[0] = 0
+
+    cfg = LaunchConfig(grid=1, block=1)
+    pdl = LaunchConfig(grid=1, block=1, programmatic_stream_serialization=True)
+
+    gb = stream.create_graph_builder().begin_building()
+    launch(gb, cfg, dummy_kernel, arr.ctypes.data)
+    launch(gb, pdl, dummy_kernel, arr.ctypes.data)
+    gb.end_building()
+    _assert_programmatic_dependency_edge(gb.graph_definition)
+    graph = gb.complete()
+
+    graph.launch(stream)
+    stream.sync()
+    assert arr[0] == 2
+
+    buf.close()
+    stream.close()
+
+
+@skipif_need_cuda_headers
+@requires_module(np, "2.2.5", reason="need numpy 2.2.5+ (numpy GH #28632)")
+def test_pdl_same_stream_primary_secondary_overlap_via_graph(init_cuda):
+    """Same-stream PDL overlap via GraphBuilder stream capture on Hopper+."""
+    dev = Device()
+    if dev.compute_capability < (9, 0):
+        pytest.skip("Programmatic Dependent Launch requires compute capability >= 9.0")
+
+    code = r"""
+    #include <cuda_device_runtime_api.h>
+
+    extern "C" __global__ void primary_kernel(int* secondary_started, int* overlapped) {
+        cudaTriggerProgrammaticLaunchCompletion();
+
+        const long long deadline = clock64() + 100000000LL;  // ~50ms @ ~2GHz
+        if (threadIdx.x == 0 && blockIdx.x == 0) {
+            while (clock64() < deadline) {
+                if (atomicAdd(secondary_started, 0) != 0) {
+                    atomicExch(overlapped, 1);
+                    return;
+                }
+                __nanosleep(1000);
+            }
+        }
+    }
+
+    extern "C" __global__ void secondary_kernel(int* secondary_started) {
+        if (threadIdx.x == 0 && blockIdx.x == 0) {
+            atomicExch(secondary_started, 1);
+        }
+    }
+    """
+
+    arch = "".join(f"{i}" for i in dev.compute_capability)
+    options = ProgramOptions(std="c++17", arch=f"sm_{arch}", include_path=helpers.CUDA_INCLUDE_PATH)
+    module = Program(code, code_type="c++", options=options).compile("cubin")
+    primary = module.get_kernel("primary_kernel")
+    secondary = module.get_kernel("secondary_kernel")
+
+    stream = dev.create_stream(options=StreamOptions(nonblocking=True))
+    mr = LegacyPinnedMemoryResource()
+    secondary_started = np.from_dlpack(mr.allocate(4)).view(np.int32)
+    overlapped = np.from_dlpack(mr.allocate(4)).view(np.int32)
+    primary_cfg = LaunchConfig(grid=1, block=1)
+    secondary_cfg = LaunchConfig(grid=1, block=1, programmatic_stream_serialization=True)
+
+    saw_overlap = False
+    for _ in range(5):
+        secondary_started[0] = 0
+        overlapped[0] = 0
+
+        gb = stream.create_graph_builder().begin_building()
+        launch(gb, primary_cfg, primary, secondary_started.ctypes.data, overlapped.ctypes.data)
+        launch(gb, secondary_cfg, secondary, secondary_started.ctypes.data)
+        graph = gb.end_building().complete()
+        graph.launch(stream)
+        stream.sync()
+        graph.close()
+        gb.close()
+
+        if overlapped[0] == 1:
+            saw_overlap = True
+            break
+
+    if not saw_overlap:
+        pytest.xfail(
+            "PDL (Programmatic Dependent Launch) graph overlap was not observed. "
+            "If this keeps xfailing in CI, manually re-check on a quiet Hopper+ GPU."
+        )
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_join_rejects_non_builder(init_cuda):
+    """join() type-checks its arguments before looking at capture state."""
+    gb = Device().create_graph_builder()
+    with pytest.raises(TypeError, match="All arguments must be GraphBuilder"):
+        GraphBuilder.join(gb, object())
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_builder_cuda_stream_protocol(init_cuda):
+    """The builder exports its underlying stream, and stops doing so once closed."""
+    gb = Device().create_graph_builder()
+    protocol = gb.__cuda_stream__()
+    assert protocol[0] == 0
+    assert int(protocol[1]) == int(gb.stream.handle)
+    gb.close()
+    with pytest.raises(RuntimeError, match="GraphBuilder has been closed"):
+        gb.__cuda_stream__()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_end_building_requires_active_capture(init_cuda):
+    """end_building() on a builder that never started capturing is rejected."""
+    gb = Device().create_graph_builder()
+    with pytest.raises(RuntimeError, match="Graph builder is not building"):
+        gb.end_building()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_debug_dot_print_requires_finished_build(init_cuda, tmp_path):
+    """debug_dot_print() needs a completed capture, both before and during building."""
+    gb = Device().create_graph_builder()
+    with pytest.raises(RuntimeError, match="Graph has not finished building"):
+        gb.debug_dot_print(str(tmp_path / "unfinished.dot"))
+    gb.begin_building()
+    try:
+        with pytest.raises(RuntimeError, match="Graph has not finished building"):
+            gb.debug_dot_print(str(tmp_path / "capturing.dot"))
+    finally:
+        gb.end_building()
+    gb.debug_dot_print(str(tmp_path / "finished.dot"))
+    assert (tmp_path / "finished.dot").exists()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_callback_requires_active_capture(init_cuda):
+    """callback() is rejected outside an active capture."""
+    gb = Device().create_graph_builder()
+    with pytest.raises(RuntimeError, match="Cannot add callback when graph is not being built"):
+        gb.callback(lambda: None)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_create_condition_requires_active_capture(init_cuda):
+    """create_condition() is rejected outside an active capture."""
+    _skip_if_conditional_handles_unsupported()
+    gb = Device().create_graph_builder()
+    with pytest.raises(RuntimeError, match="Cannot create a condition when graph is not being built"):
+        gb.create_condition()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_embed_requires_finished_child_and_capturing_parent(init_cuda):
+    """embed() rejects an unfinished child and a parent that is not capturing."""
+    parent = Device().create_graph_builder()
+    # embed() checks the child before the parent, so the child must already be
+    # ended for the parent guard to be the one that fires here.
+    child = Device().create_graph_builder().begin_building().end_building()
+    with pytest.raises(ValueError, match="Parent graph is not being built"):
+        parent.embed(child)
+
+    unfinished = Device().create_graph_builder().begin_building()
+    capturing = Device().create_graph_builder().begin_building()
+    try:
+        with pytest.raises(ValueError, match="Child graph has not finished building"):
+            capturing.embed(unfinished)
+    finally:
+        capturing.end_building()
+        unfinished.end_building()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_graph_builder_and_graph_cannot_be_constructed_directly():
+    """Both types are factory-only; the guards run before any CUDA call."""
+    with pytest.raises(NotImplementedError, match="directly creating"):
+        GraphBuilder()
+    with pytest.raises(RuntimeError, match="directly constructing"):
+        Graph()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_graph_builder_close_ends_active_capture(init_cuda):
+    """close() during capture ends it and hands the stream back usable."""
+    empty = compile_common_kernels().get_kernel("empty_kernel")
+    stream = Device().create_stream()
+    gb = stream.create_graph_builder().begin_building()
+    launch(gb, LaunchConfig(grid=1, block=1), empty)
+    assert gb.is_building
+    gb.close()
+    with pytest.raises(RuntimeError, match="has been closed"):
+        _ = gb.is_building
+    # Ending capture via close() must leave the stream usable.
+    launch(stream, LaunchConfig(grid=1, block=1), empty)
+    stream.sync()
+    stream.close()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_if_then_requires_active_capture(init_cuda):
+    """Conditional nodes cannot be added once capture has ended."""
+    _skip_if_conditional_handles_unsupported()
+    gb = Device().create_graph_builder().begin_building()
+    condition = try_create_condition(gb)
+    gb.end_building()
+    with pytest.raises(RuntimeError, match="Cannot add conditional node when not actively capturing"):
+        gb.if_then(condition)
diff --git a/cuda_core/tests/graph/test_graph_builder_conditional.py b/cuda_core/tests/graph/test_graph_builder_conditional.py
index 0bb779a8bf7..150d43bfc14 100644
--- a/cuda_core/tests/graph/test_graph_builder_conditional.py
+++ b/cuda_core/tests/graph/test_graph_builder_conditional.py
@@ -7,8 +7,8 @@
 
 import numpy as np
 import pytest
+from cuda_python_test_helpers.marks import requires_module
 from helpers.graph_kernels import compile_conditional_kernels
-from helpers.marks import requires_module
 
 from cuda.core import Device, LaunchConfig, LegacyPinnedMemoryResource, launch
 from cuda.core.graph import GraphBuilder
diff --git a/cuda_core/tests/graph/test_graph_definition.py b/cuda_core/tests/graph/test_graph_definition.py
index 50d4b4ac253..4444bafc5de 100644
--- a/cuda_core/tests/graph/test_graph_definition.py
+++ b/cuda_core/tests/graph/test_graph_definition.py
@@ -3,14 +3,18 @@
 
 """Tests for GraphDefinition topology, node types, instantiation, and execution."""
 
+import ctypes
+import gc
+import sys
+import weakref
 from collections.abc import Callable
 from dataclasses import dataclass, field
 
 import pytest
 from helpers.graph_kernels import compile_common_kernels
+from helpers.memory import xfail_on_graph_mempool_oom
 from helpers.misc import try_create_condition
 
-from conftest import xfail_on_graph_mempool_oom
 from cuda.core import Device, LaunchConfig
 from cuda.core.graph import (
     AllocNode,
@@ -575,20 +579,6 @@ def node_spec(request, init_cuda):
 # =============================================================================
 
 
-@pytest.fixture
-def sample_graphdef(init_cuda):
-    """A sample GraphDefinition for standalone tests."""
-    return GraphDefinition()
-
-
-@pytest.fixture
-def dot_file(tmp_path):
-    """Temporary DOT file path, cleaned up after test."""
-    path = tmp_path / "graph.dot"
-    yield path
-    path.unlink(missing_ok=True)
-
-
 # =============================================================================
 # Topology tests (parameterized over graph specs)
 # =============================================================================
@@ -631,6 +621,43 @@ def test_succ(nonempty_graph_spec):
         assert actual == spec.expected_succ[name], f"succ mismatch for node {name}"
 
 
+@pytest.mark.parametrize("adjacency_name", ("pred", "succ"))
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_large_adjacency_set_is_not_truncated(init_cuda, adjacency_name):
+    """Adjacency queries return and remove edges beyond the old 16-edge buffer."""
+    g = GraphDefinition()
+    hub = g.empty()
+    neighbors = [g.empty() for _ in range(20)]
+    adjacency = getattr(hub, adjacency_name)
+    adjacency.update(neighbors)
+
+    expected_edges = (
+        {(node, hub) for node in neighbors} if adjacency_name == "pred" else {(hub, node) for node in neighbors}
+    )
+    assert len(adjacency) == 20
+    assert set(adjacency) == set(neighbors)
+    assert neighbors[-1] in adjacency
+    assert g.edges() == expected_edges
+
+    adjacency.clear()
+    assert len(adjacency) == 0
+    assert g.edges() == set()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_large_graph_queries_are_not_truncated(init_cuda):
+    """Graph queries return nodes and edges beyond the old 128-item buffers."""
+    g = GraphDefinition()
+    nodes = [g.empty() for _ in range(130)]
+    nodes[0].succ.update(nodes[1:])
+    nodes[1].succ.add(nodes[2])
+
+    expected_edges = {(nodes[0], node) for node in nodes[1:]}
+    expected_edges.add((nodes[1], nodes[2]))
+    assert g.nodes() == set(nodes)
+    assert g.edges() == expected_edges
+
+
 def test_node_graph_property(nonempty_graph_spec):
     """Every node's .graph property returns the parent GraphDefinition."""
     spec = nonempty_graph_spec
@@ -701,6 +728,22 @@ def test_node_attrs_preserved_by_nodes(node_spec):
         assert getattr(retrieved, attr) == getattr(node, attr), f"{spec.name}.{attr} not preserved by nodes()"
 
 
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_host_callback_node_reconstructed_from_embedded_child(init_cuda):
+    """A host-callback node read through an embedded child graph is reconstructed via _create_from_driver."""
+    # The same-wrapper nodes() (test_node_attrs_preserved_by_nodes) returns the
+    # registry-cached object and never exercises reconstruction; only the embedded
+    # child graph carries fresh, unregistered node handles. Host callback is
+    # mempool-free so it reconstructs here; alloc-based nodes stay cached.
+    child = GraphDefinition()
+    _build_host_callback_node(child)
+    parent = GraphDefinition()
+    reconstructed = list(parent.embed(child).child_graph.nodes())
+    assert any(isinstance(n, HostCallbackNode) for n in reconstructed), (
+        f"no reconstructed HostCallbackNode in {[type(n).__name__ for n in reconstructed]}"
+    )
+
+
 def test_identity_preservation(init_cuda):
     """Round-trips through nodes(), edges(), and pred/succ return extant
     objects rather than duplicates."""
@@ -775,14 +818,16 @@ def registered(node):
 # =============================================================================
 
 
-def test_graphdef_handle_valid(sample_graphdef):
+def test_graphdef_handle_valid(init_cuda):
     """GraphDefinition has a valid non-null handle."""
+    sample_graphdef = GraphDefinition()
     assert sample_graphdef.handle is not None
     assert int(sample_graphdef.handle) != 0
 
 
-def test_graphdef_entry_is_virtual(sample_graphdef):
+def test_graphdef_entry_is_virtual(init_cuda):
     """Internal entry node is virtual (no pred/succ, type is None)."""
+    sample_graphdef = GraphDefinition()
     entry = sample_graphdef._entry
     assert isinstance(entry, GraphNode)
     assert entry.pred == set()
@@ -795,8 +840,9 @@ def test_graphdef_entry_is_virtual(sample_graphdef):
 # =============================================================================
 
 
-def test_alloc_zero_size_fails(sample_graphdef):
+def test_alloc_zero_size_fails(init_cuda):
     """Alloc with zero size raises error (CUDA limitation)."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     from cuda.core._utils.cuda_utils import CUDAError
 
@@ -804,8 +850,9 @@ def test_alloc_zero_size_fails(sample_graphdef):
         sample_graphdef.allocate(0)
 
 
-def test_free_creates_dependency(sample_graphdef):
+def test_free_creates_dependency(init_cuda):
     """Free node depends on its predecessor."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         alloc = sample_graphdef.allocate(ALLOC_SIZE)
@@ -813,8 +860,9 @@ def test_free_creates_dependency(sample_graphdef):
     assert alloc in free.pred
 
 
-def test_alloc_free_chain(sample_graphdef):
+def test_alloc_free_chain(init_cuda):
     """Alloc and free can be chained."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         a1 = sample_graphdef.allocate(ALLOC_SIZE)
@@ -831,8 +879,9 @@ def test_alloc_free_chain(sample_graphdef):
 # =============================================================================
 
 
-def test_alloc_memory_type_invalid(sample_graphdef):
+def test_alloc_memory_type_invalid(init_cuda):
     """Invalid memory type raises ValueError."""
+    sample_graphdef = GraphDefinition()
     with pytest.raises(ValueError, match="'invalid' is not a valid GraphMemoryType. Must be "):
         sample_graphdef.allocate(ALLOC_SIZE, memory_type="invalid")
 
@@ -844,8 +893,9 @@ def test_alloc_memory_type_invalid(sample_graphdef):
         pytest.param(lambda d: d, id="Device_object"),
     ],
 )
-def test_alloc_device_option(sample_graphdef, device_spec):
+def test_alloc_device_option(init_cuda, device_spec):
     """Device can be specified as int or Device object."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     device = Device()
     with xfail_on_graph_mempool_oom(device):
@@ -862,14 +912,43 @@ def test_alloc_peer_access(mempool_device_x2):
     assert d1.device_id in node.peer_access
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_alloc_memory_type_host(init_cuda):
+    """HOST graph alloc nodes reconstruct memory_type from the driver, not the Python argument."""
+    _skip_if_no_mempool()
+    from cuda.core._utils.cuda_utils import CUDAError
+
+    g = GraphDefinition()
+    try:
+        with xfail_on_graph_mempool_oom():
+            node = g.allocate(ALLOC_SIZE, memory_type=GraphMemoryType.HOST)
+    except CUDAError as e:
+        if "CUDA_ERROR_NOT_SUPPORTED" in str(e):
+            pytest.skip("Driver does not support graph alloc memory_type='host'")
+        raise
+
+    expected_dptr = node.dptr
+    succ = node.record(Device().create_event())
+    node_ref = weakref.ref(node)
+    del node
+    gc.collect()
+    assert node_ref() is None
+    reconstructed = next(iter(succ.pred))
+    assert isinstance(reconstructed, AllocNode)
+    assert reconstructed.memory_type == GraphMemoryType.HOST
+    assert reconstructed.dptr == expected_dptr
+    assert reconstructed.dptr != 0
+
+
 # =============================================================================
 # Join API
 # =============================================================================
 
 
 @pytest.mark.parametrize("num_branches", [2, 3, 5])
-def test_join_merges_branches(sample_graphdef, num_branches):
+def test_join_merges_branches(init_cuda, num_branches):
     """join() with multiple branches creates correct dependencies."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         branches = [sample_graphdef.allocate(ALLOC_SIZE) for _ in range(num_branches)]
@@ -883,8 +962,9 @@ def test_join_merges_branches(sample_graphdef, num_branches):
 # =============================================================================
 
 
-def test_launch_creates_node(sample_graphdef):
+def test_launch_creates_node(init_cuda):
     """launch() creates a KernelNode."""
+    sample_graphdef = GraphDefinition()
     mod = compile_common_kernels()
     kernel = mod.get_kernel("empty_kernel")
     config = LaunchConfig(grid=1, block=1)
@@ -892,8 +972,9 @@ def test_launch_creates_node(sample_graphdef):
     assert isinstance(node, KernelNode)
 
 
-def test_launch_chain_dependencies(sample_graphdef):
+def test_launch_chain_dependencies(init_cuda):
     """Chained launches create correct dependencies."""
+    sample_graphdef = GraphDefinition()
     mod = compile_common_kernels()
     kernel = mod.get_kernel("empty_kernel")
     config = LaunchConfig(grid=1, block=1)
@@ -955,15 +1036,17 @@ def _instantiate_and_upload(graph_definition, kwargs, stream):
 
 
 @pytest.mark.parametrize("inst_kwargs", _INSTANTIATE_ONLY_OPTIONS)
-def test_instantiate_empty_graph(sample_graphdef, inst_kwargs):
+def test_instantiate_empty_graph(init_cuda, inst_kwargs):
     """Empty graph can be instantiated."""
+    sample_graphdef = GraphDefinition()
     graph = _instantiate(sample_graphdef, inst_kwargs)
     assert graph is not None
 
 
 @pytest.mark.parametrize("inst_kwargs", _INSTANTIATE_ONLY_OPTIONS)
-def test_instantiate_with_nodes(sample_graphdef, inst_kwargs):
+def test_instantiate_with_nodes(init_cuda, inst_kwargs):
     """Graph with nodes can be instantiated."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         sample_graphdef.allocate(ALLOC_SIZE)
@@ -973,8 +1056,9 @@ def test_instantiate_with_nodes(sample_graphdef, inst_kwargs):
 
 
 @pytest.mark.skipif(not Device(0).properties.unified_addressing, reason="requires unified addressing")
-def test_instantiate_and_execute_kernel_device_launch(sample_graphdef):
+def test_instantiate_and_execute_kernel_device_launch(init_cuda):
     """Kernel-only graph can be instantiated with device_launch flag."""
+    sample_graphdef = GraphDefinition()
     mod = compile_common_kernels()
     kernel = mod.get_kernel("empty_kernel")
     config = LaunchConfig(grid=1, block=1)
@@ -990,8 +1074,9 @@ def test_instantiate_and_execute_kernel_device_launch(sample_graphdef):
 
 
 @pytest.mark.parametrize("inst_kwargs", _EXECUTE_OPTIONS)
-def test_instantiate_and_execute_kernel(sample_graphdef, inst_kwargs):
+def test_instantiate_and_execute_kernel(init_cuda, inst_kwargs):
     """Graph with kernel can be instantiated and executed."""
+    sample_graphdef = GraphDefinition()
     mod = compile_common_kernels()
     kernel = mod.get_kernel("empty_kernel")
     config = LaunchConfig(grid=1, block=1)
@@ -1004,8 +1089,9 @@ def test_instantiate_and_execute_kernel(sample_graphdef, inst_kwargs):
 
 
 @pytest.mark.parametrize("inst_kwargs", _EXECUTE_OPTIONS)
-def test_instantiate_and_execute_alloc_free(sample_graphdef, inst_kwargs):
+def test_instantiate_and_execute_alloc_free(init_cuda, inst_kwargs):
     """Graph with alloc/free can be executed."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         alloc = sample_graphdef.allocate(ALLOC_SIZE)
@@ -1018,8 +1104,9 @@ def test_instantiate_and_execute_alloc_free(sample_graphdef, inst_kwargs):
 
 
 @pytest.mark.parametrize("inst_kwargs", _EXECUTE_OPTIONS)
-def test_instantiate_and_execute_memset(sample_graphdef, inst_kwargs):
+def test_instantiate_and_execute_memset(init_cuda, inst_kwargs):
     """Graph with alloc/memset/free can be executed."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         alloc = sample_graphdef.allocate(ALLOC_SIZE)
@@ -1033,8 +1120,9 @@ def test_instantiate_and_execute_memset(sample_graphdef, inst_kwargs):
 
 
 @pytest.mark.parametrize("inst_kwargs", _EXECUTE_OPTIONS)
-def test_instantiate_and_execute_memcpy(sample_graphdef, inst_kwargs):
+def test_instantiate_and_execute_memcpy(init_cuda, inst_kwargs):
     """Graph with alloc/memset/memcpy/free can be executed and data is copied."""
+    sample_graphdef = GraphDefinition()
     _skip_if_no_mempool()
     import ctypes
 
@@ -1058,8 +1146,9 @@ def test_instantiate_and_execute_memcpy(sample_graphdef, inst_kwargs):
     assert all(b == 0xAB for b in host_buf)
 
 
-def test_instantiate_and_execute_child_graph(sample_graphdef):
+def test_instantiate_and_execute_child_graph(init_cuda):
     """Graph with embedded child graph can be executed."""
+    sample_graphdef = GraphDefinition()
     child = GraphDefinition()
     mod = compile_common_kernels()
     kernel = mod.get_kernel("empty_kernel")
@@ -1075,8 +1164,9 @@ def test_instantiate_and_execute_child_graph(sample_graphdef):
     stream.sync()
 
 
-def test_instantiate_and_execute_host_callback(sample_graphdef):
+def test_instantiate_and_execute_host_callback(init_cuda):
     """Graph with host callback can be executed and callback is invoked."""
+    sample_graphdef = GraphDefinition()
     results = []
 
     def my_callback():
@@ -1093,8 +1183,9 @@ def my_callback():
     assert results == [42]
 
 
-def test_instantiate_and_execute_host_callback_cfunc(sample_graphdef):
+def test_instantiate_and_execute_host_callback_cfunc(init_cuda):
     """Graph with ctypes function pointer callback can be executed."""
+    sample_graphdef = GraphDefinition()
     import ctypes
 
     CALLBACK = ctypes.CFUNCTYPE(None, ctypes.c_void_p)
@@ -1115,8 +1206,9 @@ def raw_fn(data):
     assert called[0]
 
 
-def test_host_callback_cfunc_with_user_data(sample_graphdef):
+def test_host_callback_cfunc_with_user_data(init_cuda):
     """Host callback with bytes user_data passes data to C function."""
+    sample_graphdef = GraphDefinition()
     import ctypes
 
     CALLBACK = ctypes.CFUNCTYPE(None, ctypes.c_void_p)
@@ -1137,14 +1229,102 @@ def read_byte(data):
     assert result[0] == 0xAB
 
 
-def test_host_callback_user_data_rejected_for_python_callable(sample_graphdef):
+def test_host_callback_user_data_rejected_for_python_callable(init_cuda):
     """user_data is rejected for Python callables."""
+    sample_graphdef = GraphDefinition()
     with pytest.raises(ValueError, match="user_data is only supported"):
         sample_graphdef.callback(lambda: None, user_data=b"hello")
 
 
-def test_instantiate_and_execute_event_record_wait(sample_graphdef):
+_INCOMPATIBLE_CTYPES_HOST_CALLBACKS = [
+    pytest.param(ctypes.CFUNCTYPE(ctypes.c_int, ctypes.c_void_p), id="bad-restype"),
+    pytest.param(ctypes.CFUNCTYPE(None, ctypes.c_int), id="bad-argtype"),
+    pytest.param(ctypes.CFUNCTYPE(None), id="missing-arg"),
+    pytest.param(ctypes.CFUNCTYPE(None, ctypes.c_void_p, ctypes.c_void_p), id="extra-arg"),
+]
+
+# Prototypes that declare CUhostFn but differ in ctypes bookkeeping. ctypes
+# builds the same thunk for all of them, so all must be accepted.
+_COMPATIBLE_CTYPES_HOST_CALLBACKS = [
+    pytest.param(ctypes.CFUNCTYPE(None, ctypes.c_void_p), id="cfunctype"),
+    pytest.param(ctypes.CFUNCTYPE(None, ctypes.c_void_p, use_errno=True), id="use-errno"),
+    pytest.param(ctypes.PYFUNCTYPE(None, ctypes.c_void_p), id="pyfunctype"),
+]
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+@pytest.mark.parametrize("callback_type", _INCOMPATIBLE_CTYPES_HOST_CALLBACKS)
+def test_host_callback_ctypes_rejects_incompatible_signature(init_cuda, callback_type):
+    """Incompatible ctypes prototypes are rejected before CUDA sees them."""
+    sample_graphdef = GraphDefinition()
+    with pytest.raises(TypeError, match="CUhostFn"):
+        sample_graphdef.callback(callback_type(0))
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+def test_host_callback_ctypes_update_rejects_incompatible_signature(init_cuda):
+    """HostCallbackNode.update applies the same ctypes ABI check."""
+    sample_graphdef = GraphDefinition()
+    good_type = ctypes.CFUNCTYPE(None, ctypes.c_void_p)
+    bad_type = ctypes.CFUNCTYPE(ctypes.c_int, ctypes.c_void_p)
+
+    @good_type
+    def good(data):
+        pass
+
+    node = sample_graphdef.callback(good)
+    with pytest.raises(TypeError, match="CUhostFn"):
+        node.update(bad_type(0))
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("callback_type", _COMPATIBLE_CTYPES_HOST_CALLBACKS)
+def test_host_callback_ctypes_accepts_equivalent_prototypes(init_cuda, callback_type):
+    """Prototypes that declare CUhostFn are accepted and run."""
+    sample_graphdef = GraphDefinition()
+    called = [False]
+
+    @callback_type
+    def raw_fn(data):
+        called[0] = True
+
+    sample_graphdef.callback(raw_fn)
+    graph = sample_graphdef.instantiate()
+
+    stream = Device().create_stream()
+    graph.upload(stream)
+    graph.launch(stream)
+    stream.sync()
+
+    assert called[0]
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+@pytest.mark.skipif(sys.platform != "win32", reason="WINFUNCTYPE is Windows-only")
+def test_host_callback_ctypes_accepts_winfunctype(init_cuda):
+    """On Windows, WINFUNCTYPE matches CUDA_CB (__stdcall) and is accepted."""
+    sample_graphdef = GraphDefinition()
+    callback_type = ctypes.WINFUNCTYPE(None, ctypes.c_void_p)
+    called = [False]
+
+    @callback_type
+    def raw_fn(data):
+        called[0] = True
+
+    sample_graphdef.callback(raw_fn)
+    graph = sample_graphdef.instantiate()
+
+    stream = Device().create_stream()
+    graph.upload(stream)
+    graph.launch(stream)
+    stream.sync()
+
+    assert called[0]
+
+
+def test_instantiate_and_execute_event_record_wait(init_cuda):
     """Graph with event record and wait nodes can be executed."""
+    sample_graphdef = GraphDefinition()
     event = Device().create_event()
     rec = sample_graphdef.record(event)
     rec.wait(event)
@@ -1166,8 +1346,9 @@ def _skip_unless_cc_90():
         pytest.skip("Conditional node execution requires CC >= 9.0 (Hopper)")
 
 
-def test_instantiate_and_execute_if_then(sample_graphdef):
+def test_instantiate_and_execute_if_then(init_cuda):
     """If-conditional node: body executes only when condition is non-zero."""
+    sample_graphdef = GraphDefinition()
     _skip_unless_cc_90()
     _skip_if_no_mempool()
     import ctypes
@@ -1199,8 +1380,9 @@ def test_instantiate_and_execute_if_then(sample_graphdef):
     assert result[0] == 1
 
 
-def test_instantiate_and_execute_if_else(sample_graphdef):
+def test_instantiate_and_execute_if_else(init_cuda):
     """If-else node: then or else branch executes based on condition."""
+    sample_graphdef = GraphDefinition()
     _skip_unless_cc_90()
     _skip_if_no_mempool()
     import ctypes
@@ -1234,8 +1416,9 @@ def test_instantiate_and_execute_if_else(sample_graphdef):
     assert result[0] == 2
 
 
-def test_instantiate_and_execute_switch(sample_graphdef):
+def test_instantiate_and_execute_switch(init_cuda):
     """Switch node: selected branch executes based on condition value."""
+    sample_graphdef = GraphDefinition()
     _skip_unless_cc_90()
     _skip_if_no_mempool()
     import ctypes
@@ -1268,8 +1451,9 @@ def test_instantiate_and_execute_switch(sample_graphdef):
     assert result[0] == 1
 
 
-def test_conditional_node_type_preserved_by_nodes(sample_graphdef):
+def test_conditional_node_type_preserved_by_nodes(init_cuda):
     """Conditional nodes appear as ConditionalNode base when read back from graph."""
+    sample_graphdef = GraphDefinition()
     condition = try_create_condition(sample_graphdef)
     if_node = sample_graphdef.if_then(condition)
     assert isinstance(if_node, IfNode)
@@ -1285,8 +1469,10 @@ def test_conditional_node_type_preserved_by_nodes(sample_graphdef):
 # =============================================================================
 
 
-def test_debug_dot_print_creates_file(sample_graphdef, dot_file):
+def test_debug_dot_print_creates_file(init_cuda, tmp_path):
     """debug_dot_print writes a DOT file."""
+    sample_graphdef = GraphDefinition()
+    dot_file = tmp_path / "graph.dot"
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         sample_graphdef.allocate(ALLOC_SIZE)
@@ -1296,8 +1482,10 @@ def test_debug_dot_print_creates_file(sample_graphdef, dot_file):
     assert "digraph" in content
 
 
-def test_debug_dot_print_with_options(sample_graphdef, dot_file):
+def test_debug_dot_print_with_options(init_cuda, tmp_path):
     """debug_dot_print accepts GraphDebugPrintOptions."""
+    sample_graphdef = GraphDefinition()
+    dot_file = tmp_path / "graph.dot"
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         sample_graphdef.allocate(ALLOC_SIZE)
@@ -1306,8 +1494,10 @@ def test_debug_dot_print_with_options(sample_graphdef, dot_file):
     assert dot_file.exists()
 
 
-def test_debug_dot_print_invalid_options(sample_graphdef, dot_file):
+def test_debug_dot_print_invalid_options(init_cuda, tmp_path):
     """debug_dot_print rejects invalid options type."""
+    sample_graphdef = GraphDefinition()
+    dot_file = tmp_path / "graph.dot"
     _skip_if_no_mempool()
     with xfail_on_graph_mempool_oom():
         sample_graphdef.allocate(ALLOC_SIZE)
diff --git a/cuda_core/tests/graph/test_graph_definition_errors.py b/cuda_core/tests/graph/test_graph_definition_errors.py
index a8a3c9b8f09..923ea5fb74e 100644
--- a/cuda_core/tests/graph/test_graph_definition_errors.py
+++ b/cuda_core/tests/graph/test_graph_definition_errors.py
@@ -7,9 +7,9 @@
 
 import pytest
 from helpers.graph_kernels import compile_common_kernels
+from helpers.memory import xfail_on_graph_mempool_oom
 from helpers.misc import try_create_condition
 
-from conftest import xfail_on_graph_mempool_oom
 from cuda.core import Device, LaunchConfig
 from cuda.core._utils.cuda_utils import CUDAError
 from cuda.core.graph import (
diff --git a/cuda_core/tests/graph/test_graph_definition_integration.py b/cuda_core/tests/graph/test_graph_definition_integration.py
index 12b57bb73a5..1adce901d16 100644
--- a/cuda_core/tests/graph/test_graph_definition_integration.py
+++ b/cuda_core/tests/graph/test_graph_definition_integration.py
@@ -7,10 +7,11 @@
 
 import numpy as np
 import pytest
+from helpers.graph_kernels import skip_if_nvrtc_lacks_conditional_handle
+from helpers.memory import xfail_on_graph_mempool_oom
 
-from conftest import xfail_on_graph_mempool_oom
 from cuda.core import Device, EventOptions, LaunchConfig, Program, ProgramOptions
-from cuda.core._utils.cuda_utils import driver, handle_return
+from cuda.core._utils.cuda_utils import CUDAError, driver, handle_return
 from cuda.core.graph import GraphDefinition
 
 SIZEOF_FLOAT = 4
@@ -128,8 +129,9 @@ def _compile_heat_kernels():
             "cubin",
             name_expressions=("heat_step", "countdown"),
         )
-    except Exception:
-        pytest.skip("NVRTC does not support cudaGraphConditionalHandle")
+    except CUDAError as exc:
+        skip_if_nvrtc_lacks_conditional_handle(exc)
+        raise
     return mod.get_kernel("heat_step"), mod.get_kernel("countdown")
 
 
@@ -145,8 +147,9 @@ def _compile_bisect_kernels():
     prog = Program(_BISECT_KERNEL_SOURCE, code_type="c++", options=_nvrtc_opts())
     try:
         mod = prog.compile("cubin", name_expressions=names)
-    except Exception:
-        pytest.skip("NVRTC does not support cudaGraphConditionalHandle")
+    except CUDAError as exc:
+        skip_if_nvrtc_lacks_conditional_handle(exc)
+        raise
     return tuple(mod.get_kernel(n) for n in names)
 
 
diff --git a/cuda_core/tests/graph/test_graph_definition_lifetime.py b/cuda_core/tests/graph/test_graph_definition_lifetime.py
index 804cccc1923..dfb20e581b7 100644
--- a/cuda_core/tests/graph/test_graph_definition_lifetime.py
+++ b/cuda_core/tests/graph/test_graph_definition_lifetime.py
@@ -14,9 +14,9 @@
 
 import pytest
 from helpers.graph_kernels import compile_common_kernels
+from helpers.memory import xfail_on_graph_mempool_oom
 from helpers.misc import try_create_condition
 
-from conftest import xfail_on_graph_mempool_oom
 from cuda_python_test_helpers import under_compute_sanitizer
 
 # Resource finalization triggered by graph destruction is not synchronous. A
@@ -76,13 +76,19 @@ def _wait_until(predicate, timeout=None, interval=0.02):
     raise AssertionError(f"condition not satisfied within {timeout}s")
 
 
-from cuda.core import Device, DeviceMemoryResource, EventOptions, Kernel, LaunchConfig
+from cuda.core import Device, DeviceMemoryResource, EventOptions, Kernel, LaunchConfig, LegacyPinnedMemoryResource
+from cuda.core._utils.cuda_utils import CUDAError
+from cuda.core._utils.version import driver_version
 from cuda.core.graph import (
     ChildGraphNode,
     ConditionalNode,
+    EventRecordNode,
+    EventWaitNode,
+    FreeNode,
     GraphDefinition,
     HostCallbackNode,
     KernelNode,
+    MemcpyNode,
 )
 
 
@@ -424,6 +430,97 @@ def test_destroying_child_node_invalidates_embedded_handles(init_cuda):
     assert not embedded_callback.is_valid
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_updating_child_node_replaces_embedded_handles(init_cuda):
+    """A successful replacement invalidates only the old embedded hierarchy."""
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    old_inner = GraphDefinition()
+    old_inner.callback(lambda: None)
+    old_middle = GraphDefinition()
+    old_middle.embed(old_inner)
+    parent = GraphDefinition()
+    child_node = parent.embed(old_middle)
+
+    embedded_middle = child_node.child_graph
+    embedded_child = next(node for node in embedded_middle.nodes() if isinstance(node, ChildGraphNode))
+    embedded_inner = embedded_child.child_graph
+    embedded_callback = next(node for node in embedded_inner.nodes() if isinstance(node, HostCallbackNode))
+
+    # Sources from the destination hierarchy may contain handles CUDA destroys
+    # during replacement, so cuda-core rejects them before mutation.
+    with pytest.raises(CUDAError):
+        child_node.update(embedded_middle)
+    with pytest.raises(CUDAError):
+        child_node.update(parent)
+    assert int(embedded_middle.handle) != 0
+    assert int(embedded_inner.handle) != 0
+    assert embedded_child.is_valid
+    assert embedded_callback.is_valid
+
+    replacement_inner = GraphDefinition()
+    replacement_inner.callback(lambda: None)
+    replacement_middle = GraphDefinition()
+    replacement_middle.embed(replacement_inner)
+    child_node.update(replacement_middle)
+
+    assert child_node.is_valid
+    assert int(embedded_middle.handle) == 0
+    assert int(embedded_inner.handle) == 0
+    assert not embedded_child.is_valid
+    assert not embedded_callback.is_valid
+
+    new_middle = child_node.child_graph
+    new_child = next(node for node in new_middle.nodes() if isinstance(node, ChildGraphNode))
+    assert int(new_middle.handle) != 0
+    assert int(new_child.child_graph.handle) != 0
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_child_update_replaces_nested_attachments(init_cuda):
+    """Replacement drops old owners and imports nested replacement owners."""
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    def old_callback():
+        pass
+
+    old_callback_weak = weakref.ref(old_callback)
+    old_child = GraphDefinition()
+    old_child.callback(old_callback)
+    parent = GraphDefinition()
+    child_node = parent.embed(old_child)
+
+    del old_callback, old_child
+    gc.collect()
+    assert old_callback_weak() is not None
+
+    def replacement_callback():
+        pass
+
+    replacement_callback_weak = weakref.ref(replacement_callback)
+    replacement_inner = GraphDefinition()
+    replacement_inner.callback(replacement_callback)
+    replacement = GraphDefinition()
+    replacement.embed(replacement_inner)
+    child_node.update(replacement)
+
+    _wait_until(lambda: old_callback_weak() is None)
+    del replacement_callback, replacement_inner, replacement
+    gc.collect()
+    assert replacement_callback_weak() is not None
+
+    embedded = child_node.child_graph
+    embedded_child = next(node for node in embedded.nodes() if isinstance(node, ChildGraphNode))
+    embedded_callback = next(node for node in embedded_child.child_graph.nodes() if isinstance(node, HostCallbackNode))
+    assert embedded_callback.callback is replacement_callback_weak()
+
+    del embedded_callback, embedded_child, embedded
+    child_node.destroy()
+    _wait_until(lambda: replacement_callback_weak() is None)
+
+
 @pytest.mark.agent_authored(model="gpt-5.6")
 def test_builder_embedded_clone_releases_attachment_on_node_destroy(init_cuda):
     """GraphBuilder.embed imports metadata from the captured child graph."""
@@ -592,6 +689,7 @@ def test_event_survives_graph_clone_and_execution(init_cuda):
 # =============================================================================
 
 
+@pytest.mark.thread_unsafe(reason="asserts cleanup on main thread")
 @pytest.mark.agent_authored(model="gpt-5.6")
 def test_user_object_cleanup_is_coalesced_on_python_thread(init_cuda):
     """More than 32 CUDA callbacks drain through one main-thread pending call."""
@@ -1119,6 +1217,90 @@ def test_kernel_node_reconstruction_preserves_validity(init_cuda):
     stream.sync()
 
 
+def _pred_chain_memcpy(g, bufs):
+    memory_resource = LegacyPinnedMemoryResource()
+    src = memory_resource.allocate(8)
+    dst = memory_resource.allocate(8)
+    bufs.extend((src, dst))
+    node = g.memcpy(dst, src, 8)
+    src_ptr, dst_ptr, size = node.src, node.dst, node.size
+    succ = node.record(Device().create_event())
+
+    def check(reconstructed):
+        assert isinstance(reconstructed, MemcpyNode)
+        assert reconstructed.src == src_ptr
+        assert reconstructed.dst == dst_ptr
+        assert reconstructed.size == size
+
+    return node, succ, check
+
+
+def _pred_chain_event_record(g, bufs):
+    event = Device().create_event()
+    node = g.record(event)
+    succ = node.wait(Device().create_event())
+
+    def check(reconstructed):
+        assert isinstance(reconstructed, EventRecordNode)
+        assert reconstructed.event.handle == event.handle
+
+    return node, succ, check
+
+
+def _pred_chain_event_wait(g, bufs):
+    wait_event = Device().create_event()
+    node = g.wait(wait_event)
+    succ = node.record(Device().create_event())
+
+    def check(reconstructed):
+        assert isinstance(reconstructed, EventWaitNode)
+        assert reconstructed.event.handle == wait_event.handle
+
+    return node, succ, check
+
+
+def _pred_chain_free(g, bufs):
+    _skip_if_no_mempool()
+    with xfail_on_graph_mempool_oom():
+        alloc = g.allocate(64)
+        node = alloc.deallocate(alloc.dptr)
+    free_dptr = node.dptr
+    succ = node.record(Device().create_event())
+
+    def check(reconstructed):
+        assert isinstance(reconstructed, FreeNode)
+        assert reconstructed.dptr == free_dptr
+
+    return node, succ, check
+
+
+@pytest.mark.parametrize(
+    "factory",
+    [
+        _pred_chain_memcpy,
+        _pred_chain_event_record,
+        _pred_chain_event_wait,
+        _pred_chain_free,
+    ],
+    ids=["memcpy", "event_record", "event_wait", "free"],
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_graph_nodes_reconstructed_via_pred_chain(init_cuda, factory):
+    """Dropping the original Python node forces `_create_from_driver` on pred walk."""
+    g = GraphDefinition()
+    bufs = []
+    try:
+        node, succ, check = factory(g, bufs)
+        node_ref = weakref.ref(node)
+        del node
+        _wait_until(lambda: node_ref() is None)
+        reconstructed = next(iter(succ.pred))
+        check(reconstructed)
+    finally:
+        for buf in bufs:
+            buf.close()
+
+
 # =============================================================================
 # Kernel argument lifetime — kernel nodes should keep argument objects alive
 # =============================================================================
@@ -1319,6 +1501,7 @@ def test_memcpy_buffer_survives_close(init_cuda):
     assert list(out) == [0xCD] * 4
 
 
+@pytest.mark.thread_unsafe(reason="deferred cleanup on main thread which would wait")
 @pytest.mark.agent_authored(model="claude-opus-4.8")
 def test_memcpy_buffer_allocations_released_after_graph_destroyed(init_cuda):
     """Destroying the graph frees both memcpy operand allocations.
@@ -1541,7 +1724,7 @@ def test_memcpy_mixed_buffer_and_raw_owner(init_cuda):
 
 @pytest.mark.agent_authored(model="claude-opus-4.8")
 def test_memset_closed_buffer_rejected(init_cuda):
-    """Memset rejects a Buffer with no active allocation."""
+    """Memset rejects a closed Buffer."""
     _skip_if_no_mempool()
     dev = Device()
     mr = DeviceMemoryResource(dev)
@@ -1550,7 +1733,7 @@ def test_memset_closed_buffer_rejected(init_cuda):
     buf.close()
 
     g = GraphDefinition()
-    with pytest.raises(ValueError, match="dst Buffer has no active allocation"):
+    with pytest.raises(RuntimeError, match="Buffer has been closed"):
         g.memset(buf, 0xAB, 4)
 
 
@@ -1566,7 +1749,7 @@ def test_memset_closed_buffer_dst_owner_rejected(init_cuda):
     buf.close()
 
     g = GraphDefinition()
-    with pytest.raises(ValueError, match="dst_owner Buffer has no active allocation"):
+    with pytest.raises(RuntimeError, match="Buffer has been closed"):
         g.memset(dptr, 0xAB, 4, dst_owner=buf)
 
 
@@ -1582,7 +1765,7 @@ def test_memcpy_closed_buffer_src_owner_rejected(init_cuda):
     buf.close()
 
     g = GraphDefinition()
-    with pytest.raises(ValueError, match="src_owner Buffer has no active allocation"):
+    with pytest.raises(RuntimeError, match="Buffer has been closed"):
         g.memcpy(dptr, dptr, 4, src_owner=buf)
 
 
diff --git a/cuda_core/tests/graph/test_graph_definition_mutation.py b/cuda_core/tests/graph/test_graph_definition_mutation.py
index 066822f232a..7542a50fa19 100644
--- a/cuda_core/tests/graph/test_graph_definition_mutation.py
+++ b/cuda_core/tests/graph/test_graph_definition_mutation.py
@@ -8,9 +8,9 @@
 
 import numpy as np
 import pytest
+from cuda_python_test_helpers.marks import requires_module
 from helpers.collection_interface_testers import assert_mutable_set_interface
 from helpers.graph_kernels import compile_parallel_kernels
-from helpers.marks import requires_module
 
 from cuda.core import Device, LaunchConfig, LegacyPinnedMemoryResource
 from cuda.core._utils.cuda_utils import CUDAError
@@ -301,8 +301,8 @@ def test_destroyed_node(init_cuda):
     assert b.value == 42  # tolerable
     assert b.width == 4  # tolerable
 
-    # Adding an edge to a destroyed node fails.
-    with pytest.raises(CUDAError):
+    # Adding an edge to a destroyed node fails before reaching CUDA.
+    with pytest.raises(RuntimeError, match="GraphNode has been destroyed"):
         a.succ.add(b)
 
     # Repeated destroy succeeds quietly.
@@ -310,6 +310,39 @@ def test_destroyed_node(init_cuda):
     assert not b.is_valid
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_destroyed_node_and_invalid_child_view_are_rejected(init_cuda):
+    parent = GraphDefinition()
+    predecessor = parent.empty()
+    child = GraphDefinition()
+    child.empty()
+    embedded = predecessor.embed(child)
+    child_view = embedded.child_graph
+
+    assert embedded.is_valid
+    assert child_view.is_valid
+    embedded.destroy()
+
+    assert not embedded.is_valid
+    assert not child_view.is_valid
+    assert bool(embedded) is True  # Preserve backward-compatible truthiness after destruction.
+    assert bool(child_view) is True  # Preserve backward-compatible truthiness after invalidation.
+    assert repr(embedded)
+    assert repr(child_view)
+
+    for operation in (
+        embedded.join,
+        embedded.pred.clear,
+        lambda: predecessor.join(embedded),
+        lambda: predecessor.succ.add(embedded),
+        child_view.empty,
+        child_view.nodes,
+        child_view.instantiate,
+    ):
+        with pytest.raises(RuntimeError):
+            operation()
+
+
 @pytest.mark.agent_authored(model="gpt-5.6")
 def test_failed_destroy_preserves_node_and_attachments(init_cuda):
     """A graph-memory restriction must not invalidate a failed node deletion."""
@@ -356,13 +389,29 @@ def test_add_wrong_type(init_cuda):
         node.succ.add(42)
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_discard_absent_invalid_value_is_noop(init_cuda):
+    graph = GraphDefinition()
+    owner = graph.empty()
+    neighbor = graph.empty()
+    destroyed = graph.empty()
+    owner.succ.add(neighbor)
+    destroyed.destroy()
+
+    foreign = GraphDefinition().empty()
+    for value in (destroyed, foreign):
+        owner.succ.discard(value)
+
+    assert owner.succ == {neighbor}
+
+
 def test_cross_graph_edge(init_cuda):
-    """Adding an edge to a node from a different graph raises CUDAError."""
+    """Adding an edge to a node from a different graph raises ValueError."""
     g1 = GraphDefinition()
     g2 = GraphDefinition()
     a = g1.empty()
     b = g2.empty()
-    with pytest.raises(CUDAError):
+    with pytest.raises(ValueError, match="Graph nodes must belong to the same GraphDefinition"):
         a.succ.add(b)
 
 
diff --git a/cuda_core/tests/graph/test_graph_memory_resource.py b/cuda_core/tests/graph/test_graph_memory_resource.py
index 9fc794f4cca..22757ca7556 100644
--- a/cuda_core/tests/graph/test_graph_memory_resource.py
+++ b/cuda_core/tests/graph/test_graph_memory_resource.py
@@ -5,10 +5,9 @@
 """Tests for GraphMemoryResource allocation and attributes during graph capture."""
 
 import pytest
-from helpers import IS_WINDOWS, IS_WSL
-from helpers.buffers import compare_buffer_to_constant, make_scratch_buffer, set_buffer
+from helpers.buffers import compare_buffer_to_constant, make_scratch_buffer, set_buffer, thread_unsafe_on_windows
+from helpers.memory import xfail_on_graph_mempool_oom
 
-from conftest import xfail_on_graph_mempool_oom
 from cuda.core import (
     Device,
     DeviceMemoryResource,
@@ -20,6 +19,14 @@
 )
 from cuda.core._utils.cuda_utils import CUDAError
 from cuda.core.graph import GraphCompleteOptions
+from cuda_python_test_helpers import IS_WINDOWS, IS_WSL
+
+# NOTE(seberg): "global" mode seems thread-unsafe even when working on stream
+_GRAPH_MODES = [
+    pytest.param("global", marks=pytest.mark.thread_unsafe(reason="gb instances share stream unsafely")),
+    "thread_local",
+    "relaxed",
+]
 
 
 def _common_kernels_alloc():
@@ -80,8 +87,9 @@ def free(self, buffers):
         self.stream.sync()
 
 
-@pytest.mark.parametrize("mode", ["no_graph", "global", "thread_local", "relaxed"])
+@pytest.mark.parametrize("mode", ["no_graph"] + _GRAPH_MODES)
 @pytest.mark.parametrize("action", ["incr", "fill"])
+@thread_unsafe_on_windows
 def test_graph_alloc(mempool_device, mode, action):
     """Test basic graph capture with memory allocated and deallocated by
     GraphMemoryResource.
@@ -130,7 +138,7 @@ def apply_kernels(mr, stream, out):
         assert compare_buffer_to_constant(out, 3)
     else:
         # Capture work, then upload and launch.
-        gb = device.create_graph_builder().begin_building(mode)
+        gb = stream.create_graph_builder().begin_building(mode)
         with xfail_on_graph_mempool_oom(device):
             apply_kernels(mr=gmr, stream=gb, out=out)
             graph = gb.end_building().complete()
@@ -150,7 +158,8 @@ def apply_kernels(mr, stream, out):
 
 
 @pytest.mark.skipif(IS_WINDOWS or IS_WSL, reason="auto_free_on_launch not supported on Windows")
-@pytest.mark.parametrize("mode", ["global", "thread_local", "relaxed"])
+@pytest.mark.parametrize("mode", _GRAPH_MODES)
+@thread_unsafe_on_windows
 def test_graph_alloc_with_output(mempool_device, mode):
     """Test for memory allocated in a graph being used outside the graph."""
     NBYTES = 64
@@ -168,7 +177,7 @@ def test_graph_alloc_with_output(mempool_device, mode):
     # Construct a graph to copy and increment the input. It returns a new
     # buffer allocated within the graph.  The auto_free_on_launch option
     # is required to properly use the output buffer.
-    gb = device.create_graph_builder().begin_building(mode)
+    gb = stream.create_graph_builder().begin_building(mode)
     with xfail_on_graph_mempool_oom(device):
         out = gmr.allocate(NBYTES, stream=gb)
         out.copy_from(in_, stream=gb)
@@ -195,7 +204,8 @@ def test_graph_alloc_with_output(mempool_device, mode):
     assert compare_buffer_to_constant(out, 6)
 
 
-@pytest.mark.parametrize("mode", ["global", "thread_local", "relaxed"])
+@pytest.mark.parametrize("mode", _GRAPH_MODES)
+@pytest.mark.thread_unsafe(reason="gb instances share default stream")
 def test_graph_mem_alloc_zero(mempool_device, mode):
     device = mempool_device
     gb = device.create_graph_builder().begin_building(mode)
@@ -213,7 +223,8 @@ def test_graph_mem_alloc_zero(mempool_device, mode):
     assert buffer.device_id == int(device)
 
 
-@pytest.mark.parametrize("mode", ["global", "thread_local", "relaxed"])
+@pytest.mark.parametrize("mode", _GRAPH_MODES)
+@pytest.mark.thread_unsafe(reason="GMR is shared, so high mark is global")
 def test_graph_mem_set_attributes(mempool_device, mode):
     device = mempool_device
     stream = device.create_stream()
@@ -265,7 +276,7 @@ def test_graph_mem_set_attributes(mempool_device, mode):
     mman.reset()
 
 
-@pytest.mark.parametrize("mode", ["global", "thread_local", "relaxed"])
+@pytest.mark.parametrize("mode", _GRAPH_MODES)
 def test_gmr_check_capture_state(mempool_device, mode):
     """
     Test expected errors (and non-errors) using GraphMemoryResource with graph
@@ -284,7 +295,7 @@ def test_gmr_check_capture_state(mempool_device, mode):
         gmr.allocate(1, stream=stream)
 
     # Capturing
-    gb = device.create_graph_builder().begin_building(mode=mode)
+    gb = stream.create_graph_builder().begin_building(mode=mode)
     with xfail_on_graph_mempool_oom(device):
         gmr.allocate(1, stream=gb)  # no error
         gb.end_building().complete()
@@ -320,7 +331,7 @@ def test_graph_memory_resource_attributes_repr(mempool_device):
     assert "used_mem_high=" in r
 
 
-@pytest.mark.parametrize("mode", ["global", "thread_local", "relaxed"])
+@pytest.mark.parametrize("mode", _GRAPH_MODES)
 def test_dmr_check_capture_state(mempool_device, mode):
     """
     Test expected errors (and non-errors) using DeviceMemoryResource with graph
@@ -334,7 +345,7 @@ def test_dmr_check_capture_state(mempool_device, mode):
     dmr.allocate(1, stream=stream).close()  # no error
 
     # Capturing
-    gb = device.create_graph_builder().begin_building(mode=mode)
+    gb = stream.create_graph_builder().begin_building(mode=mode)
     with pytest.raises(
         RuntimeError,
         match=r"cannot perform memory operations on a capturing "
diff --git a/cuda_core/tests/graph/test_graph_node_update.py b/cuda_core/tests/graph/test_graph_node_update.py
new file mode 100644
index 00000000000..8e0653f67be
--- /dev/null
+++ b/cuda_core/tests/graph/test_graph_node_update.py
@@ -0,0 +1,1322 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Tests for updating individual graph node parameters."""
+
+import ctypes
+import gc
+import threading
+import time
+import weakref
+from dataclasses import dataclass
+from typing import Callable
+
+import pytest
+from helpers.graph_kernels import compile_common_kernels
+
+from cuda.core import Device, LaunchConfig, LegacyPinnedMemoryResource
+from cuda.core._utils._weak_handles import weak_handle
+from cuda.core._utils.cuda_utils import CUDAError, driver, handle_return
+from cuda.core._utils.version import driver_version
+from cuda.core.graph import (
+    ChildGraphNode,
+    EventRecordNode,
+    EventWaitNode,
+    ExecutableGraphNode,
+    GraphDefinition,
+    HostCallbackNode,
+    KernelNode,
+    MemcpyNode,
+    MemsetNode,
+)
+
+
+@dataclass
+class _DefinitionUpdateCase:
+    graph_def: GraphDefinition
+    node: object
+    original: object
+    replacement: object
+    update: Callable[[object], None]
+    assert_current: Callable[[object], None]
+    assert_exec_uses: Callable[[object, object], None]
+    invalid_update: Callable[[], None] | None
+    invalid_exception: type[BaseException] | None
+    invalid_argument_update: Callable[[], None] | None
+
+
+def _assert_equal(actual, expected):
+    assert actual == expected
+
+
+def _wait_until(predicate, timeout=5.0):
+    deadline = time.monotonic() + timeout
+    while not predicate():
+        if time.monotonic() >= deadline:
+            raise AssertionError(f"condition not satisfied within {timeout}s")
+        gc.collect()
+        time.sleep(0.02)
+
+
+def _update_executable_case(graph, case):
+    view = graph[case.node]
+    replacement = case.replacement
+    if isinstance(case.node, (EventRecordNode, EventWaitNode)):
+        view.update(replacement)
+    elif isinstance(case.node, HostCallbackNode):
+        if isinstance(replacement, tuple):
+            view.update(replacement[0], user_data=replacement[1])
+        else:
+            view.update(replacement)
+    elif isinstance(case.node, MemsetNode):
+        view.update(
+            dst=replacement["dst"],
+            value=replacement["value"],
+            width=replacement["width"],
+            height=replacement["height"],
+            pitch=replacement["pitch"],
+        )
+    elif isinstance(case.node, MemcpyNode):
+        view.update(
+            dst=replacement["dst"],
+            src=replacement["src"],
+            size=replacement["size"],
+        )
+    elif isinstance(case.node, KernelNode):
+        view.update(
+            config=replacement["config"],
+            kernel=replacement["kernel"],
+            args=replacement["args"],
+        )
+    elif isinstance(case.node, ChildGraphNode):
+        view.update(replacement["child"])
+    else:  # pragma: no cover - fixture cases are exhaustive
+        raise AssertionError(f"unsupported case: {type(case.node).__name__}")
+
+
+def _event_record_case(device):
+    """Keep the selected event pending to identify each exec's record target."""
+    original = device.create_event()
+    replacement = device.create_event()
+    invalid_replacement = device.create_event()
+    invalid_replacement.close()
+
+    callback_started = threading.Event()
+    callback_release = threading.Event()
+
+    def blocking_callback():
+        callback_started.set()
+        callback_release.wait(timeout=30)
+
+    graph_def = GraphDefinition()
+    callback_node = graph_def.callback(blocking_callback)
+    node = callback_node.record(original)
+
+    def assert_exec_uses(graph, expected):
+        callback_started.clear()
+        callback_release.clear()
+        stream = device.create_stream()
+        graph.launch(stream)
+        try:
+            assert callback_started.wait(timeout=5)
+            assert expected.is_done is False
+            unexpected = replacement if expected is original else original
+            assert unexpected.is_done is True
+        finally:
+            callback_release.set()
+            stream.sync()
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=node.update,
+        assert_current=lambda expected: _assert_equal(node.event, expected),
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=lambda: node.update(invalid_replacement),
+        invalid_exception=RuntimeError,
+        invalid_argument_update=lambda: node.update(object()),
+    )
+
+
+def _event_wait_case(device):
+    """Keep the selected event pending to identify each exec's wait target."""
+    original = device.create_event()
+    replacement = device.create_event()
+    invalid_replacement = device.create_event()
+    invalid_replacement.close()
+
+    callback_called = threading.Event()
+    graph_def = GraphDefinition()
+    node = graph_def.wait(original)
+    node.callback(callback_called.set)
+
+    def assert_exec_uses(graph, expected):
+        producer_started = threading.Event()
+        producer_release = threading.Event()
+
+        def blocking_callback():
+            producer_started.set()
+            producer_release.wait(timeout=30)
+
+        producer_def = GraphDefinition()
+        producer_def.callback(blocking_callback).record(expected)
+        producer_graph = producer_def.instantiate()
+        producer_stream = device.create_stream()
+        consumer_stream = device.create_stream()
+
+        callback_called.clear()
+        producer_graph.launch(producer_stream)
+        try:
+            assert producer_started.wait(timeout=5)
+            graph.launch(consumer_stream)
+            assert not callback_called.wait(timeout=0.1)
+        finally:
+            producer_release.set()
+            producer_stream.sync()
+            consumer_stream.sync()
+        assert callback_called.is_set()
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=node.update,
+        assert_current=lambda expected: _assert_equal(node.event, expected),
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=lambda: node.update(invalid_replacement),
+        invalid_exception=RuntimeError,
+        invalid_argument_update=lambda: node.update(object()),
+    )
+
+
+def _host_callback_case(device):
+    """Use callbacks that report their identity to distinguish each exec."""
+    called = []
+
+    def original():
+        called.append(original)
+
+    def replacement():
+        called.append(replacement)
+
+    graph_def = GraphDefinition()
+    node = graph_def.callback(original)
+
+    def assert_exec_uses(graph, expected):
+        called.clear()
+        stream = device.create_stream()
+        graph.launch(stream)
+        stream.sync()
+        assert called == [expected]
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=node.update,
+        assert_current=lambda expected: _assert_equal(node.callback, expected),
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=lambda: node.update(replacement, user_data=b"not valid for a Python callback"),
+        invalid_exception=ValueError,
+        invalid_argument_update=lambda: node.update(object()),
+    )
+
+
+def _host_callback_ctypes_case(device):
+    """Use ctypes callbacks and copied payloads to distinguish each exec."""
+    callback_type = ctypes.CFUNCTYPE(None, ctypes.c_void_p)
+    called = []
+
+    def read_byte(data):
+        return ctypes.cast(data, ctypes.POINTER(ctypes.c_uint8))[0]
+
+    @callback_type
+    def original_fn(data):
+        called.append((original_fn, read_byte(data)))
+
+    @callback_type
+    def replacement_fn(data):
+        called.append((replacement_fn, read_byte(data)))
+
+    original = original_fn, bytes([0xA1])
+    replacement = replacement_fn, bytes([0xB2])
+    graph_def = GraphDefinition()
+    node = graph_def.callback(original_fn, user_data=original[1])
+
+    def update(value):
+        fn, user_data = value
+        node.update(fn, user_data=user_data)
+
+    def assert_exec_uses(graph, expected):
+        called.clear()
+        stream = device.create_stream()
+        graph.launch(stream)
+        stream.sync()
+        assert called == [(expected[0], expected[1][0])]
+
+    def invalid_update():
+        node.update(lambda: None, user_data=b"not valid for a Python callback")
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=update,
+        assert_current=lambda _expected: _assert_equal(node.callback, None),
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=invalid_update,
+        invalid_exception=ValueError,
+        invalid_argument_update=None,
+    )
+
+
+def _memset_case(device, *, replace_dst):
+    memory_resource = LegacyPinnedMemoryResource()
+    original_buffer = memory_resource.allocate(4)
+    replacement_buffer = memory_resource.allocate(4) if replace_dst else original_buffer
+    original = {
+        "dst": original_buffer,
+        "value": 0x11,
+        "element_size": 1,
+        "width": 4,
+        "height": 1,
+        "pitch": 0,
+    }
+    replacement = {
+        **original,
+        "dst": replacement_buffer,
+        "value": 0x22,
+    }
+
+    graph_def = GraphDefinition()
+    node = graph_def.memset(original["dst"], original["value"], original["width"])
+
+    def update(expected):
+        if replace_dst:
+            node.update(dst=expected["dst"], value=expected["value"])
+        else:
+            node.update(value=expected["value"])
+
+    def assert_current(expected):
+        assert node.dptr == int(expected["dst"].handle)
+        assert node.value == expected["value"]
+        assert node.element_size == expected["element_size"]
+        assert node.width == expected["width"]
+        assert node.height == expected["height"]
+        assert node.pitch == expected["pitch"]
+
+    def as_bytes(buffer):
+        return (ctypes.c_uint8 * 4).from_address(int(buffer.handle))
+
+    def assert_exec_uses(graph, expected):
+        original_data = as_bytes(original_buffer)
+        replacement_data = as_bytes(replacement_buffer)
+        original_data[:] = [0] * 4
+        replacement_data[:] = [0] * 4
+
+        stream = device.create_stream()
+        graph.launch(stream)
+        stream.sync()
+
+        assert list(as_bytes(expected["dst"])) == [expected["value"]] * 4
+        if replace_dst:
+            unexpected = replacement_buffer if expected["dst"] is original_buffer else original_buffer
+            assert list(as_bytes(unexpected)) == [0] * 4
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=update,
+        assert_current=assert_current,
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=lambda: node.update(value=256),
+        invalid_exception=OverflowError,
+        invalid_argument_update=lambda: node.update(dst=object()),
+    )
+
+
+def _memset_value_case(device):
+    """Change the fill value while preserving destination ownership."""
+    return _memset_case(device, replace_dst=False)
+
+
+def _memset_destination_case(device):
+    """Replace the destination and its retained allocation owner."""
+    return _memset_case(device, replace_dst=True)
+
+
+def _memcpy_case(device, *, replace_operand):
+    memory_resource = LegacyPinnedMemoryResource()
+    original_src = memory_resource.allocate(4)
+    original_dst = memory_resource.allocate(4)
+    replacement_src = memory_resource.allocate(4) if replace_operand == "src" else original_src
+    replacement_dst = memory_resource.allocate(4) if replace_operand == "dst" else original_dst
+    original = {
+        "dst": original_dst,
+        "src": original_src,
+        "size": 2 if replace_operand is None else 4,
+    }
+    replacement = {
+        "dst": replacement_dst,
+        "src": replacement_src,
+        "size": 4,
+    }
+
+    graph_def = GraphDefinition()
+    node = graph_def.memcpy(original["dst"], original["src"], original["size"])
+
+    def update(expected):
+        if replace_operand == "src":
+            node.update(src=expected["src"])
+        elif replace_operand == "dst":
+            node.update(dst=expected["dst"])
+        else:
+            node.update(size=expected["size"])
+
+    def assert_current(expected):
+        assert node.dst == int(expected["dst"].handle)
+        assert node.src == int(expected["src"].handle)
+        assert node.size == expected["size"]
+
+    def as_bytes(buffer):
+        return (ctypes.c_uint8 * 4).from_address(int(buffer.handle))
+
+    def assert_exec_uses(graph, expected):
+        as_bytes(original_src)[:] = [0x11] * 4
+        as_bytes(original_dst)[:] = [0] * 4
+        if replacement_src is not original_src:
+            as_bytes(replacement_src)[:] = [0x22] * 4
+        if replacement_dst is not original_dst:
+            as_bytes(replacement_dst)[:] = [0] * 4
+
+        stream = device.create_stream()
+        graph.launch(stream)
+        stream.sync()
+
+        source_value = 0x11 if expected["src"] is original_src else 0x22
+        expected_data = [source_value] * expected["size"]
+        expected_data.extend([0] * (4 - expected["size"]))
+        assert list(as_bytes(expected["dst"])) == expected_data
+        if replacement_dst is not original_dst:
+            unexpected_dst = replacement_dst if expected["dst"] is original_dst else original_dst
+            assert list(as_bytes(unexpected_dst)) == [0] * 4
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=update,
+        assert_current=assert_current,
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=lambda: node.update(size=-1),
+        invalid_exception=OverflowError,
+        invalid_argument_update=lambda: node.update(src=object()),
+    )
+
+
+def _memcpy_size_case(device):
+    """Change the copy size while preserving both operand owners."""
+    return _memcpy_case(device, replace_operand=None)
+
+
+def _memcpy_source_case(device):
+    """Replace the source while preserving destination ownership."""
+    return _memcpy_case(device, replace_operand="src")
+
+
+def _memcpy_destination_case(device):
+    """Replace the destination while preserving source ownership."""
+    return _memcpy_case(device, replace_operand="dst")
+
+
+def _kernel_case(device, *, replace):
+    module = compile_common_kernels()
+    add_one = module.get_kernel("add_one")
+    empty_kernel = module.get_kernel("empty_kernel")
+    write_launch_dims = module.get_kernel("write_launch_dims")
+    memory_resource = LegacyPinnedMemoryResource()
+    original_buffer = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    replacement_buffer = memory_resource.allocate(ctypes.sizeof(ctypes.c_int)) if replace == "args" else original_buffer
+
+    original_config = LaunchConfig(grid=1, block=1)
+    replacement_config = LaunchConfig(grid=2, block=3) if replace == "config" else original_config
+    original_kernel = write_launch_dims if replace == "config" else add_one
+    replacement_kernel = empty_kernel if replace == "kernel" else original_kernel
+    original_args = (original_buffer,)
+    if replace == "kernel":
+        replacement_args = ()
+    elif replace == "args":
+        replacement_args = (replacement_buffer,)
+    else:
+        replacement_args = original_args
+
+    original = {
+        "config": original_config,
+        "kernel": original_kernel,
+        "args": original_args,
+        "output": original_buffer,
+        "expected": 1001 if replace == "config" else 1,
+    }
+    replacement = {
+        "config": replacement_config,
+        "kernel": replacement_kernel,
+        "args": replacement_args,
+        "output": replacement_buffer,
+        "expected": 2003 if replace == "config" else int(replace != "kernel"),
+    }
+
+    graph_def = GraphDefinition()
+    node = graph_def.launch(original["config"], original["kernel"], *original["args"])
+
+    def update(expected):
+        if replace == "config":
+            node.update(config=expected["config"])
+        elif replace == "args":
+            node.update(args=expected["args"])
+        else:
+            node.update(kernel=expected["kernel"], args=expected["args"])
+
+    def assert_current(expected):
+        assert node.config == expected["config"]
+        assert int(node.kernel.handle) == int(expected["kernel"].handle)
+
+    def as_int(buffer):
+        return ctypes.c_int.from_address(int(buffer.handle))
+
+    def assert_exec_uses(graph, expected):
+        as_int(original_buffer).value = 0
+        as_int(replacement_buffer).value = 0
+
+        stream = device.create_stream()
+        graph.launch(stream)
+        stream.sync()
+
+        assert as_int(expected["output"]).value == expected["expected"]
+        if replacement_buffer is not original_buffer:
+            unexpected = replacement_buffer if expected["output"] is original_buffer else original_buffer
+            assert as_int(unexpected).value == 0
+
+    def invalid_update():
+        if replace == "kernel":
+            node.update(kernel=replacement_kernel)
+        elif replace == "args":
+            node.update(args=(object(),))
+        else:
+            node.update(config=object())
+
+    invalid_exception = ValueError if replace == "kernel" else TypeError
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=update,
+        assert_current=assert_current,
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=invalid_update,
+        invalid_exception=invalid_exception,
+        invalid_argument_update=lambda: node.update(config=object()),
+    )
+
+
+def _kernel_config_case(device):
+    """Replace launch dimensions while preserving the kernel and arguments."""
+    return _kernel_case(device, replace="config")
+
+
+def _kernel_args_case(device):
+    """Replace arguments while preserving the kernel and configuration."""
+    return _kernel_case(device, replace="args")
+
+
+def _kernel_function_case(device):
+    """Replace a kernel and explicitly supply its coupled arguments."""
+    return _kernel_case(device, replace="kernel")
+
+
+def _child_graph_case(device):
+    """Replace the embedded clone while preserving existing executables."""
+    called = []
+
+    def original_callback():
+        called.append(original_callback)
+
+    def replacement_callback():
+        called.append(replacement_callback)
+
+    original_child = GraphDefinition()
+    original_child.callback(original_callback)
+    replacement_child = GraphDefinition()
+    replacement_child.callback(replacement_callback)
+    original = {
+        "child": original_child,
+        "callback": original_callback,
+    }
+    replacement = {
+        "child": replacement_child,
+        "callback": replacement_callback,
+    }
+
+    graph_def = GraphDefinition()
+    node = graph_def.embed(original_child)
+    invalid_child = node.child_graph
+
+    def update(expected):
+        node.update(expected["child"])
+
+    def assert_current(expected):
+        callback_node = next(
+            child_node for child_node in node.child_graph.nodes() if isinstance(child_node, HostCallbackNode)
+        )
+        assert callback_node.callback is expected["callback"]
+
+    def assert_exec_uses(graph, expected):
+        called.clear()
+        stream = device.create_stream()
+        graph.launch(stream)
+        stream.sync()
+        assert called == [expected["callback"]]
+
+    return _DefinitionUpdateCase(
+        graph_def=graph_def,
+        node=node,
+        original=original,
+        replacement=replacement,
+        update=update,
+        assert_current=assert_current,
+        assert_exec_uses=assert_exec_uses,
+        invalid_update=lambda: node.update(invalid_child),
+        invalid_exception=CUDAError,
+        invalid_argument_update=lambda: node.update(object()),
+    )
+
+
+@pytest.fixture(
+    params=[
+        pytest.param(_event_record_case, id="event-record"),
+        pytest.param(_event_wait_case, id="event-wait"),
+        pytest.param(_host_callback_case, id="host-callback-python"),
+        pytest.param(_host_callback_ctypes_case, id="host-callback-ctypes"),
+        pytest.param(_memset_value_case, id="memset-value"),
+        pytest.param(_memset_destination_case, id="memset-destination"),
+        pytest.param(_memcpy_size_case, id="memcpy-size"),
+        pytest.param(_memcpy_source_case, id="memcpy-source"),
+        pytest.param(_memcpy_destination_case, id="memcpy-destination"),
+        pytest.param(_kernel_config_case, id="kernel-config"),
+        pytest.param(_kernel_args_case, id="kernel-args"),
+        pytest.param(_kernel_function_case, id="kernel-function"),
+        pytest.param(_child_graph_case, id="child-graph"),
+    ]
+)
+def definition_update_case(request, init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+    factory = request.param
+    # pytest-run-parallel shares this fixture object across workers. Build the
+    # case at call time on Device() so each worker gets its own graph/node.
+    return lambda: factory(Device())
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_memcpy_update_rejects_unsupported_descriptor(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    memory_resource = LegacyPinnedMemoryResource()
+    src = memory_resource.allocate(8)
+    dst = memory_resource.allocate(8)
+    graph_def = GraphDefinition()
+    node = graph_def.memcpy(dst, src, 4)
+
+    # cuda.core cannot construct this descriptor, but imported graphs can
+    # contain one; use cuda.bindings to exercise that rejection path.
+    params = driver.CUDA_MEMCPY3D()
+    params.srcXInBytes = 1
+    params.srcMemoryType = driver.CUmemorytype.CU_MEMORYTYPE_HOST
+    params.srcHost = int(src.handle)
+    params.srcPitch = 4
+    params.srcHeight = 2
+    params.dstMemoryType = driver.CUmemorytype.CU_MEMORYTYPE_HOST
+    params.dstHost = int(dst.handle)
+    params.dstPitch = 4
+    params.dstHeight = 2
+    params.WidthInBytes = 2
+    params.Height = 2
+    params.Depth = 1
+    handle_return(driver.cuGraphMemcpyNodeSetParams(node.handle, params))
+
+    with pytest.raises(NotImplementedError, match="multidimensional"):
+        node.update(size=3)
+
+    unchanged = handle_return(driver.cuGraphMemcpyNodeGetParams(node.handle))
+    assert unchanged.srcXInBytes == 1
+    assert unchanged.WidthInBytes == 2
+    assert unchanged.Height == 2
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_kernel_update_rejects_unsupported_config(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    kernel = compile_common_kernels().get_kernel("empty_kernel")
+    graph_def = GraphDefinition()
+    node = graph_def.launch(LaunchConfig(grid=1, block=1), kernel)
+
+    clustered = LaunchConfig(grid=1, block=1)
+    clustered.cluster = (1, 1, 1)
+    with pytest.raises(NotImplementedError, match="clustered or cooperative"):
+        node.update(config=clustered)
+    with pytest.raises(NotImplementedError, match="clustered or cooperative"):
+        graph_def.launch(clustered, kernel)
+
+    cooperative = LaunchConfig(grid=1, block=1)
+    cooperative.is_cooperative = True
+    with pytest.raises(NotImplementedError, match="clustered or cooperative"):
+        node.update(config=cooperative)
+    with pytest.raises(NotImplementedError, match="clustered or cooperative"):
+        graph_def.launch(cooperative, kernel)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_partial_memory_updates_are_keyword_only(init_cuda):
+    memory_resource = LegacyPinnedMemoryResource()
+    src = memory_resource.allocate(4)
+    dst = memory_resource.allocate(4)
+    graph_def = GraphDefinition()
+    memset_node = graph_def.memset(dst, 0, 4)
+    memcpy_node = graph_def.memcpy(dst, src, 4)
+
+    with pytest.raises(TypeError):
+        memset_node.update(dst)
+    with pytest.raises(TypeError):
+        memcpy_node.update(dst)
+
+
+@pytest.mark.parametrize(
+    "device_operand",
+    [
+        pytest.param("src", id="device-to-host"),
+        pytest.param("dst", id="host-to-device"),
+    ],
+)
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_memcpy_update_between_host_and_device(init_cuda, device_operand):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    memory_resource = LegacyPinnedMemoryResource()
+    host_src = memory_resource.allocate(4)
+    host_dst = memory_resource.allocate(4)
+    host_src_bytes = (ctypes.c_uint8 * 4).from_address(int(host_src.handle))
+    host_dst_bytes = (ctypes.c_uint8 * 4).from_address(int(host_dst.handle))
+    host_src_bytes[:] = [0x5A] * 4
+    host_dst_bytes[:] = [0] * 4
+
+    stream = init_cuda.create_stream()
+    device_buffer = init_cuda.memory_resource.allocate(4, stream=stream)
+    device_buffer.fill(0, stream=stream)
+    if device_operand == "src":
+        device_buffer.copy_from(host_src, stream=stream)
+    stream.sync()
+
+    graph_def = GraphDefinition()
+    node = graph_def.memcpy(host_dst, host_src, 4)
+    if device_operand == "src":
+        node.update(src=device_buffer)
+    else:
+        node.update(dst=device_buffer)
+
+    graph = graph_def.instantiate()
+    graph.launch(stream)
+    if device_operand == "dst":
+        device_buffer.copy_to(host_dst, stream=stream)
+    stream.sync()
+
+    assert list(host_dst_bytes) == [0x5A] * 4
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_definition_node_update_changes_future_instantiations(
+    definition_update_case,
+):
+    case = definition_update_case()
+    assert case.original != case.replacement
+    old_graph = case.graph_def.instantiate()
+
+    case.update(case.replacement)
+    case.assert_current(case.replacement)
+
+    new_graph = case.graph_def.instantiate()
+    assert old_graph != new_graph
+    case.assert_exec_uses(old_graph, case.original)
+    case.assert_exec_uses(new_graph, case.replacement)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_destroyed_definition_node_rejects_update(
+    definition_update_case,
+):
+    case = definition_update_case()
+    case.node.destroy()
+
+    assert not case.node.is_valid
+    assert case.node not in case.graph_def.nodes()
+    with pytest.raises(RuntimeError, match="GraphNode has been destroyed"):
+        case.update(case.replacement)
+    assert not case.node.is_valid
+    assert case.node not in case.graph_def.nodes()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_failed_definition_node_update_preserves_state(
+    definition_update_case,
+):
+    case = definition_update_case()
+
+    assert case.invalid_update is not None
+    assert case.invalid_exception is not None
+    with pytest.raises(case.invalid_exception):
+        case.invalid_update()
+
+    case.assert_current(case.original)
+    graph = case.graph_def.instantiate()
+    case.assert_exec_uses(graph, case.original)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_definition_node_update_rejects_wrong_type(
+    definition_update_case,
+):
+    case = definition_update_case()
+    if case.invalid_argument_update is None:
+        pytest.skip("update method has no typed positional argument")
+    with pytest.raises(TypeError):
+        case.invalid_argument_update()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_executable_node_update_changes_existing_exec(
+    definition_update_case,
+):
+    case = definition_update_case()
+    graph = case.graph_def.instantiate()
+
+    _update_executable_case(graph, case)
+
+    case.assert_current(case.original)
+    case.assert_exec_uses(graph, case.replacement)
+
+
+@pytest.mark.parametrize("node_kind", ["kernel", "memcpy", "memset"])
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_executable_node_enable_state(init_cuda, node_kind):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    graph_def = GraphDefinition()
+    if node_kind == "kernel":
+        kernel = compile_common_kernels().get_kernel("empty_kernel")
+        node = graph_def.launch(LaunchConfig(grid=1, block=1), kernel)
+    else:
+        memory_resource = LegacyPinnedMemoryResource()
+        src = memory_resource.allocate(4)
+        dst = memory_resource.allocate(4)
+        if node_kind == "memcpy":
+            node = graph_def.memcpy(dst, src, 4)
+        else:
+            node = graph_def.memset(dst, 0, 4)
+
+    view = graph_def.instantiate()[node]
+    assert view.is_enabled
+    view.disable()
+    assert not view.is_enabled
+    view.disable()
+    assert not view.is_enabled
+    view.enable()
+    assert view.is_enabled
+    view.enable()
+    assert view.is_enabled
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_executable_node_view_rejects_unsupported_and_destroyed_nodes(
+    init_cuda,
+):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    kernel = compile_common_kernels().get_kernel("empty_kernel")
+    graph_def = GraphDefinition()
+    empty = graph_def.empty()
+    kernel_node = graph_def.launch(LaunchConfig(grid=1, block=1), kernel)
+    graph = graph_def.instantiate()
+
+    with pytest.raises(TypeError, match="does not support executable updates"):
+        graph[empty]
+    with pytest.raises(TypeError):
+        graph[object()]
+
+    kernel_node.destroy()
+    with pytest.raises(RuntimeError, match="GraphNode has been destroyed"):
+        graph[kernel_node]
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_executable_node_view_retains_source_only_while_live(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    called = []
+
+    def original():
+        called.append("original")
+
+    def replacement():
+        called.append("replacement")
+
+    source = GraphDefinition()
+    node = source.callback(original)
+    source_weak = weak_handle(source)
+    graph = source.instantiate()
+    view = graph[node]
+
+    del source, node
+    gc.collect()
+    assert source_weak
+
+    view.update(replacement)
+    del view
+    _wait_until(lambda: not source_weak)
+
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    stream.sync()
+    assert called == ["replacement"]
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_executable_attachment_accumulators_are_independent(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    called = []
+
+    def original():
+        called.append("original")
+
+    def first_replacement():
+        called.append("first")
+
+    def second_replacement():
+        called.append("second")
+
+    first_weak = weakref.ref(first_replacement)
+    second_weak = weakref.ref(second_replacement)
+    source = GraphDefinition()
+    node = source.callback(original)
+    first = source.instantiate()
+    second = source.instantiate()
+
+    first[node].update(first_replacement)
+    second[node].update(second_replacement)
+    del first_replacement, second_replacement, original, node, source
+    gc.collect()
+    assert first_weak() is not None
+    assert second_weak() is not None
+
+    stream = init_cuda.create_stream()
+    first.launch(stream)
+    second.launch(stream)
+    stream.sync()
+    assert called == ["first", "second"]
+
+    del first
+    _wait_until(lambda: first_weak() is None)
+    assert second_weak() is not None
+
+    del second
+    _wait_until(lambda: second_weak() is None)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_rejected_executable_update_rolls_back_owners(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    kernel = compile_common_kernels().get_kernel("add_one")
+    config = LaunchConfig(grid=1, block=1)
+    memory_resource = LegacyPinnedMemoryResource()
+    active = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    rejected = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    ctypes.c_int.from_address(int(active.handle)).value = 0
+    rejected_weak = weak_handle(rejected)
+
+    source = GraphDefinition()
+    source.launch(config, kernel, active)
+    graph = source.instantiate()
+    unrelated = GraphDefinition()
+    unrelated_node = unrelated.launch(config, kernel, active)
+
+    with pytest.raises(CUDAError):
+        graph[unrelated_node].update(config=config, kernel=kernel, args=(rejected,))
+
+    del rejected
+    _wait_until(lambda: not rejected_weak)
+
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    stream.sync()
+    assert ctypes.c_int.from_address(int(active.handle)).value == 1
+
+
+@pytest.mark.thread_unsafe(reason="deferred cleanup on main thread which would wait")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_whole_update_replaces_executable_attachment_accumulator(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    called = []
+
+    def original():
+        called.append("original")
+
+    def individual():
+        called.append("individual")
+
+    def whole():
+        called.append("whole")
+
+    individual_weak = weakref.ref(individual)
+    source = GraphDefinition()
+    node = source.callback(original)
+    graph = source.instantiate()
+    graph[node].update(individual)
+
+    replacement = GraphDefinition()
+    replacement.callback(whole)
+    del individual
+    graph.update(replacement)
+    _wait_until(lambda: individual_weak() is None)
+
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    stream.sync()
+    assert called == ["whole"]
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_failed_whole_update_preserves_executable_accumulator(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    called = []
+
+    def original():
+        called.append("original")
+
+    def active():
+        called.append("active")
+
+    active_weak = weakref.ref(active)
+    source = GraphDefinition()
+    node = source.callback(original)
+    graph = source.instantiate()
+    graph[node].update(active)
+
+    rejected = GraphDefinition()
+    rejected.callback(lambda: called.append("rejected"))
+    rejected.empty()
+    with pytest.raises(CUDAError):
+        graph.update(rejected)
+
+    del active, original, node, source, rejected
+    gc.collect()
+    assert active_weak() is not None
+
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    stream.sync()
+    assert called == ["active"]
+
+    del graph
+    _wait_until(lambda: active_weak() is None)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_inflight_launch_defers_replaced_executable_owners(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    callback_started = threading.Event()
+    callback_release = threading.Event()
+
+    def blocking_callback():
+        callback_started.set()
+        assert callback_release.wait(timeout=30)
+
+    kernel = compile_common_kernels().get_kernel("add_one")
+    config = LaunchConfig(grid=1, block=1)
+    memory_resource = LegacyPinnedMemoryResource()
+    original = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    inflight = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    future = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    inflight_weak = weak_handle(inflight)
+
+    source = GraphDefinition()
+    kernel_node = source.callback(blocking_callback).launch(config, kernel, original)
+    graph = source.instantiate()
+    graph[kernel_node].update(config=config, kernel=kernel, args=(inflight,))
+    del inflight
+    gc.collect()
+    assert inflight_weak
+
+    replacement = GraphDefinition()
+    replacement.callback(lambda: None).launch(config, kernel, future)
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    assert callback_started.wait(timeout=5)
+
+    try:
+        graph.update(replacement)
+        gc.collect()
+        assert inflight_weak
+    finally:
+        callback_release.set()
+        stream.sync()
+
+    _wait_until(lambda: not inflight_weak)
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_sequential_executable_updates_accumulate_owners(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    called = []
+
+    def original():
+        called.append("original")
+
+    def first():
+        called.append("first")
+
+    def second():
+        called.append("second")
+
+    first_weak = weakref.ref(first)
+    second_weak = weakref.ref(second)
+    source = GraphDefinition()
+    node = source.callback(original)
+    graph = source.instantiate()
+
+    graph[node].update(first)
+    graph[node].update(second)
+
+    # CUDA cannot detach user objects from an executable graph, so the
+    # superseded owner stays reachable for as long as the executable lives.
+    del first, second, original
+    gc.collect()
+    assert first_weak() is not None
+    assert second_weak() is not None
+
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    stream.sync()
+    assert called == ["second"]
+
+    del node, source, graph
+    _wait_until(lambda: first_weak() is None and second_weak() is None)
+
+
+@pytest.mark.thread_unsafe(reason="deferred cleanup on main thread which would wait")
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_child_graph_update_transfers_source_owners_to_executable(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    called = []
+
+    def original():
+        called.append("original")
+
+    def replacement():
+        called.append("replacement")
+
+    original_child = GraphDefinition()
+    original_child.callback(original)
+    source = GraphDefinition()
+    node = source.embed(original_child)
+    graph = source.instantiate()
+
+    replacement_child = GraphDefinition()
+    replacement_child.callback(replacement)
+    graph[node].update(replacement_child)
+
+    replacement_weak = weakref.ref(replacement)
+    child_weak = weak_handle(replacement_child)
+
+    # A child-graph update is the one executable update that attaches no owner
+    # of its own. It is safe because CUDA clones the replacement graph's user
+    # object references into the executable, so the callback must outlive the
+    # definition that supplied it.
+    del replacement_child, replacement
+    _wait_until(lambda: not child_weak)
+    assert replacement_weak() is not None
+
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    stream.sync()
+    assert called == ["replacement"]
+
+    del graph
+    _wait_until(lambda: replacement_weak() is None)
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_closing_executable_during_launch_defers_owner_release(init_cuda):
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    callback_started = threading.Event()
+    callback_release = threading.Event()
+
+    def blocking_callback():
+        callback_started.set()
+        assert callback_release.wait(timeout=30)
+
+    kernel = compile_common_kernels().get_kernel("add_one")
+    config = LaunchConfig(grid=1, block=1)
+    memory_resource = LegacyPinnedMemoryResource()
+    original = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    inflight = memory_resource.allocate(ctypes.sizeof(ctypes.c_int))
+    inflight_weak = weak_handle(inflight)
+
+    source = GraphDefinition()
+    kernel_node = source.callback(blocking_callback).launch(config, kernel, original)
+    graph = source.instantiate()
+    graph[kernel_node].update(config=config, kernel=kernel, args=(inflight,))
+    del inflight
+    gc.collect()
+    assert inflight_weak
+
+    stream = init_cuda.create_stream()
+    graph.launch(stream)
+    assert callback_started.wait(timeout=5)
+
+    try:
+        # The launch still writes through the buffer the update attached, so
+        # closing the executable must not retire the accumulator yet.
+        graph.close()
+        gc.collect()
+        assert inflight_weak
+    finally:
+        callback_release.set()
+        stream.sync()
+
+    _wait_until(lambda: not inflight_weak)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_memory_node_update_validates_owners_and_noops(init_cuda):
+    """Memory-node updates validate owners, preserve no-ops, and update geometry."""
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    memory_resource = LegacyPinnedMemoryResource()
+    with memory_resource.allocate(16) as src, memory_resource.allocate(16) as dst:
+        graph_def = GraphDefinition()
+        memset_node = graph_def.memset(dst, 0x11, 8)
+        memcpy_node = graph_def.memcpy(dst, src, 8)
+
+        with pytest.raises(ValueError, match=r"^dst_owner requires dst$"):
+            memset_node.update(dst_owner=dst)
+        memset_node.update()
+        assert memset_node.value == 0x11
+        assert memset_node.width == 8
+
+        memset_node.update(width=4, height=2, pitch=8)
+        assert memset_node.width == 4
+        assert memset_node.height == 2
+        assert memset_node.pitch == 8
+
+        with pytest.raises(ValueError, match=r"^dst_owner requires dst$"):
+            memcpy_node.update(dst_owner=dst)
+        with pytest.raises(ValueError, match=r"^src_owner requires src$"):
+            memcpy_node.update(src_owner=src)
+        memcpy_node.update()
+        assert memcpy_node.size == 8
+        assert memcpy_node.dst == int(dst.handle)
+        assert memcpy_node.src == int(src.handle)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_executable_graph_node_cannot_be_constructed_directly():
+    """Executable-node views are factory-only and fail before any CUDA call."""
+    with pytest.raises(RuntimeError, match=r"^directly constructing an executable graph node is not supported$"):
+        ExecutableGraphNode()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_executable_node_repr_reports_graph_and_node(init_cuda):
+    """An executable-node view reprs its subclass name and both handles."""
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    kernel = compile_common_kernels().get_kernel("empty_kernel")
+    graph_def = GraphDefinition()
+    node = graph_def.launch(LaunchConfig(grid=1, block=1), kernel)
+    graph = graph_def.instantiate()
+
+    assert repr(graph[node]) == f"<ExecutableKernelNode graph=0x{int(graph.handle):x} node=0x{int(node.handle):x}>"
+
+
+@pytest.mark.parametrize("config_kind", ["clustered", "cooperative"])
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_executable_kernel_update_rejects_unsupported_config(init_cuda, config_kind):
+    """Executable kernel updates reject clustered and cooperative launches."""
+    if driver_version() < (12, 2, 0):
+        pytest.skip("individual graph node updates require CUDA 12.2+")
+
+    kernel = compile_common_kernels().get_kernel("empty_kernel")
+    graph_def = GraphDefinition()
+    node = graph_def.launch(LaunchConfig(grid=1, block=1), kernel)
+    view = graph_def.instantiate()[node]
+
+    config = LaunchConfig(grid=1, block=1)
+    if config_kind == "clustered":
+        config.cluster = (1, 1, 1)
+    else:
+        config.is_cooperative = True
+    with pytest.raises(
+        NotImplementedError,
+        match=r"^updating clustered or cooperative kernel nodes is not supported$",
+    ):
+        view.update(config=config, kernel=kernel, args=())
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_ctypes_host_callback_repr(init_cuda):
+    """A ctypes host callback repr reports its node and function addresses."""
+    callback_type = ctypes.CFUNCTYPE(None, ctypes.c_void_p)
+
+    @callback_type
+    def host_fn(_user_data):
+        return None
+
+    graph_def = GraphDefinition()
+    node = graph_def.callback(host_fn)
+    assert isinstance(node, HostCallbackNode)
+    assert node.callback is None
+    cfunc = ctypes.cast(host_fn, ctypes.c_void_p).value
+    assert cfunc is not None
+    assert repr(node) == f"<HostCallbackNode handle=0x{int(node.handle):x} cfunc=0x{cfunc:x}>"
diff --git a/cuda_core/tests/graph/test_graph_update.py b/cuda_core/tests/graph/test_graph_update.py
index 13513830944..c95e331913a 100644
--- a/cuda_core/tests/graph/test_graph_update.py
+++ b/cuda_core/tests/graph/test_graph_update.py
@@ -9,8 +9,8 @@
 
 import numpy as np
 import pytest
+from cuda_python_test_helpers.marks import requires_module
 from helpers.graph_kernels import compile_common_kernels, compile_conditional_kernels
-from helpers.marks import requires_module
 
 from cuda.core import Device, LaunchConfig, LegacyPinnedMemoryResource, launch
 from cuda.core._utils.cuda_utils import CUDAError
@@ -196,6 +196,7 @@ def new_callback():
     assert called == ["new"]
 
 
+@pytest.mark.thread_unsafe(reason="deferred cleanup on main thread which would wait")
 @pytest.mark.agent_authored(model="gpt-5.6")
 def test_failed_graph_update_does_not_adopt_attachments(init_cuda):
     """A rejected source graph keeps ownership separate from the exec."""
diff --git a/cuda_core/tests/graph/test_options.py b/cuda_core/tests/graph/test_options.py
index 391f521b65c..a189eaf9160 100644
--- a/cuda_core/tests/graph/test_options.py
+++ b/cuda_core/tests/graph/test_options.py
@@ -7,6 +7,7 @@
 from helpers.graph_kernels import compile_common_kernels, compile_conditional_kernels
 
 from cuda.core import Device, LaunchConfig, launch
+from cuda.core._utils.cuda_utils import CUDAError
 from cuda.core.graph import GraphBuilder, GraphCompleteOptions, GraphDebugPrintOptions
 
 
@@ -65,6 +66,20 @@ def test_graph_complete_options(init_cuda):
     gb.complete(options).close()
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_graph_complete_invalid_options_raise_cuda_error(init_cuda):
+    mod = compile_common_kernels()
+    empty_kernel = mod.get_kernel("empty_kernel")
+
+    gb = Device().create_graph_builder().begin_building()
+    launch(gb, LaunchConfig(grid=1, block=1), empty_kernel)
+    gb.end_building()
+
+    options = GraphCompleteOptions(auto_free_on_launch=True, device_launch=True)
+    with pytest.raises(CUDAError, match="CUDA_ERROR_INVALID_VALUE"):
+        gb.complete(options)
+
+
 def test_graph_build_mode(init_cuda):
     mod = compile_common_kernels()
     empty_kernel = mod.get_kernel("empty_kernel")
diff --git a/cuda_core/tests/helpers/__init__.py b/cuda_core/tests/helpers/__init__.py
index 5ce5ab7f05b..95b6bce9341 100644
--- a/cuda_core/tests/helpers/__init__.py
+++ b/cuda_core/tests/helpers/__init__.py
@@ -3,7 +3,6 @@
 
 import functools
 import os
-from typing import Union
 
 from cuda.core._utils.cuda_utils import handle_return
 from cuda.pathfinder import get_cuda_path_or_home
@@ -23,32 +22,35 @@
 
 
 @functools.cache
-def supports_ipc_mempool(device_id: Union[int, object]) -> bool:
+def supports_ipc_mempool(device_id: int | object) -> bool:
     """Return True if mempool IPC via POSIX file descriptor is supported.
 
     Uses cuDeviceGetAttribute(CU_DEVICE_ATTRIBUTE_MEMPOOL_SUPPORTED_HANDLE_TYPES)
     to check for CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR support. Does not
     require an active CUDA context.
+
+    Unsupported handle types are represented by a successful query whose bitmask
+    lacks the POSIX-FD bit, so the check below naturally returns False.
+    Other driver errors (invalid device, deinitialized driver) propagate via
+    handle_return so a real bug is not hidden as "unsupported".
     """
     if IS_WSL:
         return False
 
-    try:
-        # Lazy import to avoid hard dependency when not running GPU tests
-        from cuda.bindings import driver  # type: ignore
+    # Lazy import to avoid hard dependency when not running GPU tests
+    from cuda.bindings import driver  # type: ignore
 
-        # Initialize CUDA
-        handle_return(driver.cuInit(0))
+    # Initialize CUDA
+    handle_return(driver.cuInit(0))
 
-        # Resolve device id from int or Device-like object
-        dev_id = int(getattr(device_id, "device_id", device_id))
+    # Resolve device id from int or Device-like object
+    dev_id = int(getattr(device_id, "device_id", device_id))
 
-        # Query supported mempool handle types bitmask
-        attr = driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MEMPOOL_SUPPORTED_HANDLE_TYPES
-        mask = handle_return(driver.cuDeviceGetAttribute(attr, dev_id))
+    # Query supported mempool handle types bitmask. Unsupported handle types are
+    # represented by a successful query whose bitmask lacks the POSIX-FD bit.
+    attr = driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MEMPOOL_SUPPORTED_HANDLE_TYPES
+    mask = handle_return(driver.cuDeviceGetAttribute(attr, dev_id))
 
-        # Check POSIX FD handle type support via bitmask
-        posix_fd = driver.CUmemAllocationHandleType.CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR
-        return (int(mask) & int(posix_fd)) != 0
-    except Exception:
-        return False
+    # Check POSIX FD handle type support via bitmask
+    posix_fd = driver.CUmemAllocationHandleType.CU_MEM_HANDLE_TYPE_POSIX_FILE_DESCRIPTOR
+    return (int(mask) & int(posix_fd)) != 0
diff --git a/cuda_core/tests/helpers/buffers.py b/cuda_core/tests/helpers/buffers.py
index f4412d57e16..92a51429ab3 100644
--- a/cuda_core/tests/helpers/buffers.py
+++ b/cuda_core/tests/helpers/buffers.py
@@ -3,22 +3,106 @@
 
 import ctypes
 
+import pytest
+
 from cuda.core import Buffer, Device, MemoryResource
+from cuda.core._stream import Stream_accept
 from cuda.core._utils.cuda_utils import driver, handle_return
 
-from . import libc
+from . import IS_WINDOWS, IS_WSL, libc
 
 __all__ = [
     "DummyDeviceMemoryResource",
+    "DummyHostMemoryResource",
     "DummyUnifiedMemoryResource",
+    "NumpyHostMemoryResource",
     "PatternGen",
-    "TrackingMR",
+    "StubMemoryResource",
     "compare_buffer_to_constant",
     "compare_equal_buffers",
+    "make_instrumented_memory_resource",
     "make_scratch_buffer",
+    "thread_unsafe_on_windows",
 ]
 
 
+def thread_unsafe_on_windows(func):
+    # Tests that use these buffers and access the memory on the host are
+    # thread-unsafe on windows. On windows the GPU must be fully quiescent for host
+    # access to be safe and with threaded tests that would require a barrier.
+    if IS_WINDOWS or IS_WSL:
+        return pytest.mark.thread_unsafe(reason="windows host-access unsafe while GPU is working")(func)
+    return func
+
+
+class StubMemoryResource(MemoryResource):
+    """Device-only memory resource for tests that supply a fake pointer."""
+
+    def __init__(self, device):
+        self.device = device
+
+    def allocate(self, size, *, stream=None):
+        raise NotImplementedError("StubMemoryResource does not allocate")
+
+    def deallocate(self, ptr, size, *, stream=None):
+        Stream_accept(stream)
+
+    @property
+    def is_device_accessible(self):
+        return True
+
+    @property
+    def is_host_accessible(self):
+        return False
+
+    @property
+    def device_id(self):
+        return self.device.device_id
+
+
+def make_instrumented_memory_resource(
+    backing=StubMemoryResource,
+    *,
+    record_streams=False,
+    track_active=False,
+    deallocate_error=None,
+):
+    """Return an instrumented backing subclass and its shared telemetry.
+
+    Only calls dispatched through the Python ``allocate`` and ``deallocate``
+    methods are observed. Some built-in memory resources free their buffers
+    directly in C++ instead (see issue #2615).
+    """
+    if not isinstance(backing, type) or not issubclass(backing, MemoryResource):
+        raise TypeError("backing must be a MemoryResource subclass")
+
+    telemetry = {"active": {}, "deallocations": []}
+
+    class InstrumentedMemoryResource(backing):
+        __slots__ = ()
+
+        if track_active:
+
+            def allocate(self, size, *, stream=None):
+                buffer = super().allocate(size, stream=stream)
+                telemetry["active"][int(buffer.handle)] = size
+                return buffer
+
+        if record_streams or track_active or deallocate_error is not None:
+
+            def deallocate(self, ptr, size, *, stream=None):
+                if record_streams:
+                    telemetry["deallocations"].append({"ptr": int(ptr), "size": size, "stream": stream})
+                if deallocate_error is not None:
+                    raise deallocate_error
+                super().deallocate(ptr, size, stream=stream)
+                if track_active:
+                    telemetry["active"].pop(int(ptr), None)
+
+    InstrumentedMemoryResource.__name__ = f"Instrumented{backing.__name__}"
+    return InstrumentedMemoryResource, telemetry
+
+
 class DummyDeviceMemoryResource(MemoryResource):
     # cuMemAlloc / cuMemFree are synchronous; stream is accepted for
     # interface conformance but ignored.
@@ -71,37 +155,72 @@ def device_id(self) -> int:
         return self.device
 
 
-class TrackingMR(MemoryResource):
-    """A MemoryResource that tracks active allocations via a dict.
+class DummyHostMemoryResource(MemoryResource):
+    # Pure-host ctypes allocation; stream is accepted for interface
+    # conformance but ignored.
+    def __init__(self):
+        pass
+
+    def allocate(self, size, *, stream=None) -> Buffer:
+        # Allocate a ctypes buffer of size `size`
+        ptr = (ctypes.c_byte * size)()
+        self._ptr = ptr
+        return Buffer.from_handle(ptr=ctypes.addressof(ptr), size=size, mr=self)
+
+    def deallocate(self, ptr, size, *, stream=None):
+        del self._ptr
+
+    @property
+    def is_device_accessible(self) -> bool:
+        return False
+
+    @property
+    def is_host_accessible(self) -> bool:
+        return True
 
-    Useful for verifying that deallocate is called at the expected time.
+    @property
+    def device_id(self) -> int:
+        raise RuntimeError("the pinned memory resource is not bound to any GPU")
+
+
+class NumpyHostMemoryResource(MemoryResource):
+    """Host-only resource backed by ``numpy.empty``, adapted from issue #2769.
+
+    It never touches the CUDA driver, so it must work in a process that has not
+    initialized CUDA. ``deallocate`` takes ``stream`` positionally, as the
+    reporter's resource does.
     """
 
     def __init__(self):
-        self.active = {}
+        # Strong refs keyed by pointer; Buffer carries only the int address.
+        self._held = {}
 
-    # cuMemAlloc / cuMemFree are synchronous; stream is accepted for
-    # interface conformance but ignored.
-    def allocate(self, size, *, stream=None):
-        ptr = handle_return(driver.cuMemAlloc(size))
-        self.active[int(ptr)] = size
+    def allocate(self, size, *, stream=None) -> Buffer:
+        import numpy as np
+
+        arr = np.empty(size, dtype=np.uint8)
+        ptr = int(arr.ctypes.data)
+        self._held[ptr] = arr
         return Buffer.from_handle(ptr=ptr, size=size, mr=self)
 
-    def deallocate(self, ptr, size, *, stream=None):
-        handle_return(driver.cuMemFree(ptr))
-        del self.active[int(ptr)]
+    def deallocate(self, ptr, size, stream=None):
+        self._held.pop(int(ptr), None)
 
     @property
-    def is_device_accessible(self):
+    def is_device_accessible(self) -> bool:
+        return False
+
+    @property
+    def is_host_accessible(self) -> bool:
         return True
 
     @property
-    def is_host_accessible(self):
+    def is_managed(self) -> bool:
         return False
 
     @property
-    def device_id(self):
-        return 0
+    def device_id(self) -> int:
+        return -1
 
 
 class PatternGen:
@@ -109,8 +228,8 @@ class PatternGen:
     Provides methods to fill a target buffer with  known test patterns and
     verify the expected values.
 
-    If a stream is provided, operations are synchronized with respect to that
-    stream.  Otherwise, they are synchronized over the device.
+    Operations are submitted to the supplied stream. Verification synchronizes
+    that stream before comparing results on the host.
 
     The test pattern is either a fixed value or a cyclic pattern generated from
     an 8-bit seed.  Only one of `value` or `seed` should be supplied.
@@ -121,11 +240,10 @@ class PatternGen:
     buffer and then perform a comparison.
     """
 
-    def __init__(self, device, size, stream=None):
+    def __init__(self, device, size, *, stream):
         self.device = device
         self.size = size
-        self.stream = stream if stream is not None else device.create_stream()
-        self.sync_target = stream if stream is not None else device
+        self.stream = Stream_accept(stream)
         self.pattern_buffers = {}
 
     def fill_buffer(self, buffer, seed=None, value=None):
@@ -142,7 +260,7 @@ def verify_buffer(self, buffer, seed=None, value=None):
         pattern_buffer = self._get_pattern_buffer(seed, value)
         ptr_expected = self._ptr(pattern_buffer)
         scratch_buffer.copy_from(buffer, stream=self.stream)
-        self.sync_target.sync()
+        self.stream.sync()
         assert libc.memcmp(ptr_test, ptr_expected, self.size) == 0
 
     @staticmethod
diff --git a/cuda_core/tests/helpers/constants.py b/cuda_core/tests/helpers/constants.py
new file mode 100644
index 00000000000..f4ea61b1938
--- /dev/null
+++ b/cuda_core/tests/helpers/constants.py
@@ -0,0 +1,14 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Constants shared across the cuda_core test suite."""
+
+# Cap for memory pools created by tests. A pool created without an explicit
+# max_size instead reserves a system-dependent window that scales with
+# installed device memory -- hundreds of GiB on large-memory GPUs. The
+# per-process virtual address budget is bounded (~1 TB on Windows MCDM), and a
+# reservation is not returned until the pool is torn down and its
+# stream-ordered frees retire, so oversized windows accumulate across a session
+# and eventually starve later pool creations with CUDA_ERROR_OUT_OF_MEMORY
+# (issue #2381). See AGENTS.md in the tests directory.
+POOL_SIZE = 2097152  # 2 MiB
diff --git a/cuda_core/tests/helpers/contexts.py b/cuda_core/tests/helpers/contexts.py
new file mode 100644
index 00000000000..7ee01bb255f
--- /dev/null
+++ b/cuda_core/tests/helpers/contexts.py
@@ -0,0 +1,127 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+from contextlib import contextmanager
+
+from cuda.core._utils.cuda_utils import driver, handle_return
+
+__all__ = [
+    "assert_device_operations_use_bound_context",
+    "current_context_handle",
+    "no_current_context",
+    "use_context",
+]
+
+
+def current_context_handle():
+    """Return the current CUDA context handle, or zero if none is current."""
+    return int(handle_return(driver.cuCtxGetCurrent()))
+
+
+def _assert_event_record_rejected_from_ambient_context(event):
+    """Assert that recording ``event`` into a stream from the ambient context fails.
+
+    An event and the stream it records must belong to the same context;
+    otherwise cuEventRecord fails with CUDA_ERROR_INVALID_HANDLE. cuStreamCreate
+    creates the probe stream in whatever context is currently ambient, so this
+    is a live check that ``event`` was not actually recorded from there.
+    """
+    ambient_stream = handle_return(driver.cuStreamCreate(0))
+    try:
+        (record_status,) = driver.cuEventRecord(event.handle, ambient_stream)
+        assert record_status == driver.CUresult.CUDA_ERROR_INVALID_HANDLE, (
+            "Recording an event into a stream from a different context should fail with "
+            f"CUDA_ERROR_INVALID_HANDLE, got {record_status!r}"
+        )
+    finally:
+        handle_return(driver.cuStreamDestroy(ambient_stream))
+
+
+def assert_device_operations_use_bound_context(device):
+    """Check that Device operations use its bound context and preserve the ambient context."""
+    bound_context = device.context
+    ambient_context_handle = current_context_handle()
+    assert int(bound_context.handle) != ambient_context_handle, (
+        "Precondition failed: the device's bound context must not be the current (ambient) context."
+    )
+    stream = event = builder = None
+
+    try:
+        stream = device.create_stream()
+        assert stream.context == bound_context
+        assert current_context_handle() == ambient_context_handle
+        # Live check: query the driver directly, rather than comparing cached
+        # metadata, to confirm the stream was actually created in the bound
+        # context rather than whatever was ambient.
+        driver_stream_ctx = handle_return(driver.cuStreamGetCtx(stream.handle))
+        assert int(driver_stream_ctx) == int(bound_context.handle), (
+            "cuStreamGetCtx reports a context other than the one the stream was created in."
+        )
+
+        event = device.create_event()
+        assert event.context == bound_context
+        assert current_context_handle() == ambient_context_handle
+        # Only exercised when the ambient context belongs to a different
+        # physical device: cuEventRecord's cross-context rejection is
+        # guaranteed distinct there. Two contexts on the *same* device (e.g.
+        # a green context vs. the primary context) may resolve to the same
+        # underlying device context for this check, so skip rather than
+        # assert unverified driver behavior.
+        if ambient_context_handle and int(handle_return(driver.cuCtxGetDevice())) != device.device_id:
+            _assert_event_record_rejected_from_ambient_context(event)
+
+        builder = device.create_graph_builder()
+        assert builder.stream.context == bound_context
+        assert current_context_handle() == ambient_context_handle
+
+        device.sync()
+        assert current_context_handle() == ambient_context_handle
+
+        builder.close()
+        builder = None
+        assert current_context_handle() == ambient_context_handle
+
+        event.close()
+        event = None
+        assert current_context_handle() == ambient_context_handle
+
+        stream.close()
+        stream = None
+        assert current_context_handle() == ambient_context_handle
+    finally:
+        if builder is not None:
+            builder.close()
+        if event is not None:
+            event.close()
+        if stream is not None:
+            stream.close()
+
+
+@contextmanager
+def no_current_context():
+    """Temporarily remove the calling thread's sole current CUDA context."""
+    if current_context_handle() == 0:
+        raise RuntimeError("no_current_context requires a current CUDA context")
+
+    previous = handle_return(driver.cuCtxPopCurrent())
+    try:
+        if current_context_handle() != 0:
+            raise RuntimeError("no_current_context requires exactly one stacked CUDA context")
+        yield
+    finally:
+        handle_return(driver.cuCtxPushCurrent(previous))
+
+
+@contextmanager
+def use_context(device, context):
+    """Temporarily make a context current and restore the previous context."""
+    if current_context_handle() == 0:
+        raise RuntimeError("use_context requires a current CUDA context to restore")
+
+    previous = device.set_current(context)
+    if previous is None:
+        raise RuntimeError("Device.set_current() did not return the previous CUDA context")
+    try:
+        yield
+    finally:
+        device.set_current(previous)
diff --git a/cuda_core/tests/helpers/copy_batch.py b/cuda_core/tests/helpers/copy_batch.py
new file mode 100644
index 00000000000..2c517e3c66c
--- /dev/null
+++ b/cuda_core/tests/helpers/copy_batch.py
@@ -0,0 +1,38 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""Shared constants and helpers for the ``copy_batch`` tests.
+
+Fixtures live in ``tests/memory/conftest.py``; this module holds the
+pieces that tests import by name.
+"""
+
+from cuda.core import LegacyPinnedMemoryResource
+from helpers.buffers import compare_equal_buffers, make_scratch_buffer
+
+COPY_BATCH_SIZE = 4096
+COPY_BATCH_COUNT = 4
+
+
+def assert_managed_holds(dev, buf, value, *, stream):
+    """Assert a managed buffer holds ``value``.
+
+    Reads via an explicit device-to-host copy rather than dereferencing
+    the managed pointer from the host. Managed pages carry residency and
+    ``cuMemAdvise`` state that earlier tests in the suite can leave
+    behind, which makes direct host reads order-dependent. Also avoids
+    ``compare_buffer_to_constant``, which resolves a ``Device`` from
+    ``memory_resource.device_id`` -- that is -1 for
+    ``ManagedMemoryResource``.
+    """
+    host = LegacyPinnedMemoryResource().allocate(buf.size)
+    expected = make_scratch_buffer(dev, value, buf.size)
+    try:
+        buf.copy_to(host, stream=stream)
+        stream.sync()
+        assert compare_equal_buffers(expected, host)
+    finally:
+        expected.close()
+        host.close(stream)
+        stream.sync()
diff --git a/cuda_core/tests/helpers/cuda_gdb_src.py b/cuda_core/tests/helpers/cuda_gdb_src.py
new file mode 100644
index 00000000000..bb6d97721b6
--- /dev/null
+++ b/cuda_core/tests/helpers/cuda_gdb_src.py
@@ -0,0 +1,27 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+"""Inferior for cuda-gdb: compile with debug=True and launch, keep Program alive."""
+
+from cuda.core import Device, LaunchConfig, Program, ProgramOptions, launch
+
+CODE = """
+extern "C" __global__ void kernel() {
+    int x = 0;
+    x += 1;  // ISSUE_2422_SOURCE_LINE
+}
+"""
+
+
+def main() -> None:
+    dev = Device()
+    dev.set_current()
+    stream = dev.create_stream()
+    prog = Program(CODE, "c++", ProgramOptions(debug=True, arch=f"sm_{dev.arch}"))
+    mod = prog.compile("cubin")
+    k = mod.get_kernel("kernel")
+    launch(stream, LaunchConfig(grid=1, block=1), k)
+    stream.sync()
+
+
+if __name__ == "__main__":
+    main()
diff --git a/cuda_core/tests/helpers/graph_kernels.py b/cuda_core/tests/helpers/graph_kernels.py
index 54caedd165c..fec6c7b2d82 100644
--- a/cuda_core/tests/helpers/graph_kernels.py
+++ b/cuda_core/tests/helpers/graph_kernels.py
@@ -12,6 +12,30 @@
 from cuda.core import Device, Program, ProgramOptions
 from cuda.core._utils.cuda_utils import NVRTCError, handle_return
 
+# NVRTC diagnostic phrases that indicate cudaGraphConditionalHandle itself is unknown
+# to the compiler (older NVRTC builds predate the type). Matched narrowly so a
+# genuine compile error (syntax error, etc.) is not hidden as a skip.
+# Phrase #1 is the exact diagnostic observed on this machine's NVRTC; phrase #2
+# is a common clang/NVRTC wording for an unknown type, not verified against the
+# cudaGraphConditionalHandle case on an old NVRTC build.
+_COND_HANDLE_UNKNOWN = (
+    'identifier "cudaGraphConditionalHandle" is undefined',
+    'unknown type name "cudaGraphConditionalHandle"',
+)
+
+
+def skip_if_nvrtc_lacks_conditional_handle(exc):
+    """Skip when *exc* means NVRTC predates cudaGraphConditionalHandle.
+
+    Catches only the documented "type unknown" cases; a genuine compile
+    error (syntax error, etc.) re-raises so a real bug is not hidden as a skip.
+    """
+    msg = str(exc)
+    if any(phrase in msg for phrase in _COND_HANDLE_UNKNOWN):
+        nvrtc_version = handle_return(nvrtc.nvrtcVersion())
+        pytest.skip(f"NVRTC version {nvrtc_version} does not support conditionals")
+    raise
+
 
 def compile_common_kernels():
     """Compile basic kernels for graph tests.
@@ -19,15 +43,24 @@ def compile_common_kernels():
     Returns a module with:
     - empty_kernel: does nothing
     - add_one: increments an int pointer by 1
+    - write_launch_dims: encodes the launch dimensions in an int
     """
     code = """
     __global__ void empty_kernel() {}
     __global__ void add_one(int *a) { *a += 1; }
+    __global__ void write_launch_dims(int *a) {
+        if (blockIdx.x == 0 && threadIdx.x == 0) {
+            *a = gridDim.x * 1000 + blockDim.x;
+        }
+    }
     """
     arch = "".join(f"{i}" for i in Device().compute_capability)
     program_options = ProgramOptions(std="c++17", arch=f"sm_{arch}")
     prog = Program(code, code_type="c++", options=program_options)
-    mod = prog.compile("cubin", name_expressions=("empty_kernel", "add_one"))
+    mod = prog.compile(
+        "cubin",
+        name_expressions=("empty_kernel", "add_one", "write_launch_dims"),
+    )
     return mod
 
 
@@ -69,11 +102,9 @@ def compile_conditional_kernels(cond_type):
     prog = Program(code, code_type="c++", options=program_options)
     try:
         mod = prog.compile("cubin", name_expressions=("empty_kernel", "add_one", "set_handle", "loop_kernel"))
-    except NVRTCError as e:
-        with pytest.raises(NVRTCError, match='error: identifier "cudaGraphConditionalHandle" is undefined'):
-            raise e
-        nvrtcVersion = handle_return(nvrtc.nvrtcVersion())
-        pytest.skip(f"NVRTC version {nvrtcVersion} does not support conditionals")
+    except NVRTCError as exc:
+        skip_if_nvrtc_lacks_conditional_handle(exc)
+        raise
     return mod
 
 
diff --git a/cuda_core/tests/helpers/latch.py b/cuda_core/tests/helpers/latch.py
index c28fb222641..7702c5f617e 100644
--- a/cuda_core/tests/helpers/latch.py
+++ b/cuda_core/tests/helpers/latch.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 import ctypes
diff --git a/cuda_core/tests/helpers/memory.py b/cuda_core/tests/helpers/memory.py
new file mode 100644
index 00000000000..5dac58bd03d
--- /dev/null
+++ b/cuda_core/tests/helpers/memory.py
@@ -0,0 +1,91 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Memory-related test helpers (skip/xfail guards and resource factories)."""
+
+from contextlib import contextmanager
+
+import pytest
+from cuda_python_test_helpers.mempool import xfail_if_mempool_oom
+
+from cuda.core import ManagedMemoryResource, PinnedMemoryResource
+from cuda.core._utils.cuda_utils import CUDAError
+
+
+def skip_if_pinned_memory_unsupported(device):
+    try:
+        if not device.properties.host_memory_pools_supported:
+            pytest.skip("Device does not support host mempool operations")
+    except AttributeError:
+        pytest.skip("PinnedMemoryResource requires CUDA 13.0 or later")
+
+
+def skip_if_managed_memory_unsupported(device):
+    try:
+        if not device.properties.memory_pools_supported or not device.properties.concurrent_managed_access:
+            pytest.skip("Device does not support managed memory pool operations")
+    except AttributeError:
+        pytest.skip("ManagedMemoryResource requires CUDA 13.0 or later")
+    try:
+        ManagedMemoryResource()
+    except CUDAError as e:
+        xfail_if_mempool_oom(e, device)
+        raise
+    except RuntimeError as e:
+        if "requires CUDA 13.0" in str(e):
+            pytest.skip("ManagedMemoryResource requires CUDA 13.0 or later")
+        raise
+
+
+def _device_id_from_resource_options(device, args, kwargs):
+    if device is not None:
+        return device
+    options = kwargs.get("options")
+    if options is None and args:
+        options = args[0]
+    if options is None:
+        return 0
+    if isinstance(options, dict):
+        preferred_location = options.get("preferred_location")
+        preferred_location_type = options.get("preferred_location_type")
+    else:
+        preferred_location = getattr(options, "preferred_location", None)
+        preferred_location_type = getattr(options, "preferred_location_type", None)
+    if preferred_location_type in (None, "device") and isinstance(preferred_location, int) and preferred_location >= 0:
+        return preferred_location
+    return 0
+
+
+def create_managed_memory_resource_or_skip(*args, xfail_device=None, **kwargs):
+    # Keep the established "skip" helper name for call-site readability, even though
+    # Windows MCDM mempool OOM setup failures are xfailed instead of skipped.
+    try:
+        return ManagedMemoryResource(*args, **kwargs)
+    except CUDAError as e:
+        xfail_if_mempool_oom(e, _device_id_from_resource_options(xfail_device, args, kwargs))
+        if "CUDA_ERROR_NOT_SUPPORTED" in str(e):
+            pytest.skip("ManagedMemoryResource is not supported on this platform/device")
+        raise
+    except RuntimeError as e:
+        if "requires CUDA 13.0" in str(e):
+            pytest.skip("ManagedMemoryResource requires CUDA 13.0 or later")
+        if "concurrent managed access is not available" in str(e).lower():
+            pytest.skip("Device does not support concurrent managed memory access")
+        raise
+
+
+def create_pinned_memory_resource_or_xfail(*args, xfail_device=None, **kwargs):
+    try:
+        return PinnedMemoryResource(*args, **kwargs)
+    except CUDAError as e:
+        xfail_if_mempool_oom(e, xfail_device)
+        raise
+
+
+@contextmanager
+def xfail_on_graph_mempool_oom(device=0):
+    try:
+        yield
+    except CUDAError as e:
+        xfail_if_mempool_oom(e, "cuGraphAddMemAllocNode", device)
+        raise
diff --git a/cuda_core/tests/helpers/oom_diagnostics.py b/cuda_core/tests/helpers/oom_diagnostics.py
new file mode 100644
index 00000000000..b80cfef5820
--- /dev/null
+++ b/cuda_core/tests/helpers/oom_diagnostics.py
@@ -0,0 +1,558 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""OOM reason checker for the cuda_core test suite (issue #2381).
+
+``CUDA_ERROR_OUT_OF_MEMORY`` does not mean "the device ran out of memory": the
+driver returns it whenever it could not obtain some resource, and one of
+those resources is a purely host-side virtual-address (VA) reservation.
+Creating -- or even just looking up -- a memory pool reserves a VA window
+before any device memory is touched (observed default: about 2x installed
+device memory). If that host reservation fails, the error looks identical to
+genuine physical exhaustion even though ``cuMemGetInfo`` may report the
+device is almost entirely free. This module runs a small, ordered sequence of
+``cuda.bindings.driver`` calls to tell the two apart, and turns the raw
+results into a verdict a reader does not have to reconstruct by hand.
+
+Every probe uses only documented driver APIs against the current context and
+device 0, so the same sequence runs unmodified on Linux, Windows (WDDM / TCC /
+MCDM), and WSL. There is no OS-specific branch and no external process
+(``nvidia-smi``, NVML): see the PR #2458 review for why the previous version's
+``nvidia-smi -q`` dump was dropped.
+
+Capture is latched once per session, on the first failing OOM. A failing run
+can report ~190 of these, all descending from one earlier event, and
+re-running the probes on each would add noticeable time and bury the log. The
+report is written via ``terminalreporter`` rather than ``print()`` so it
+survives the stdout redirection these runs use, and ``pytest_terminal_summary``
+points at the artifact from the end of the run, where it is actually noticed.
+"""
+
+import os
+import pathlib
+import sys
+import threading
+from dataclasses import dataclass
+
+from cuda.bindings import driver
+from helpers.constants import POOL_SIZE
+
+OOM_MARKER = "CUDA_ERROR_OUT_OF_MEMORY"
+DEFAULT_FILENAME = "cuda_core_oom_diagnostics.txt"
+
+GIB = 1 << 30
+# Used only if cuMemGetAllocationGranularity is unavailable; see _allocation_granularity.
+FALLBACK_ALIGNMENT = 2 * 1024 * 1024
+
+_BANNER = "=" * 78
+
+_LESSON = (
+    "CUDA_ERROR_OUT_OF_MEMORY means the driver could not obtain some resource;\n"
+    "it is not proof that device memory is exhausted. Creating -- or even just\n"
+    "looking up -- a memory pool first reserves a host virtual-address window\n"
+    "(observed default: about 2x installed device memory) before any device\n"
+    "memory is touched. That reservation can fail while cuMemGetInfo still\n"
+    "reports most of the device free. The probes below check host VA and\n"
+    "physical device memory separately so the two are not confused. Note that\n"
+    "the '2x device memory' figure is an observation from measurement and a\n"
+    "driver source comment, not a documented guarantee -- it can differ across\n"
+    "driver versions and platforms."
+)
+
+
+def _round_up(value, alignment):
+    if alignment <= 0:
+        return value
+    remainder = value % alignment
+    return value if remainder == 0 else value + (alignment - remainder)
+
+
+def _call(fn, *args):
+    """Invoke a driver API and split the result into ``(ok, error, values)``.
+
+    Never raises: an exception here would replace the original test failure
+    that this module exists to diagnose.
+    """
+    try:
+        result = fn(*args)
+    except Exception as exc:
+        return False, repr(exc), ()
+    err, *values = result if isinstance(result, tuple) else (result,)
+    if err != driver.CUresult.CUDA_SUCCESS:
+        return False, str(err), tuple(values)
+    return True, None, tuple(values)
+
+
+def _allocation_granularity(device_id):
+    """Best-effort VMM alignment for the current device; falls back to 2 MiB.
+
+    Using the driver's own recommended granularity keeps alignment portable
+    instead of assuming every platform pads to 2 MiB.
+    """
+    prop = driver.CUmemAllocationProp()
+    prop.type = driver.CUmemAllocationType.CU_MEM_ALLOCATION_TYPE_PINNED
+    prop.location.type = driver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE
+    prop.location.id = device_id
+    ok, _err, values = _call(
+        driver.cuMemGetAllocationGranularity,
+        prop,
+        driver.CUmemAllocationGranularity_flags.CU_MEM_ALLOC_GRANULARITY_RECOMMENDED,
+    )
+    if ok and values and values[0]:
+        return values[0]
+    return FALLBACK_ALIGNMENT
+
+
+def _reserve_and_free(size, alignment):
+    """Reserve, then immediately free, a host VA window of ``size`` bytes.
+
+    Returns ``(ok, error)``. Never leaves the reservation live: a probe that
+    holds VA open would itself become the leak this module diagnoses.
+    """
+    aligned_size = _round_up(size, alignment)
+    ok, err, values = _call(driver.cuMemAddressReserve, aligned_size, alignment, None, 0)
+    if not ok:
+        return False, err
+    (ptr,) = values
+    free_ok, free_err, _ = _call(driver.cuMemAddressFree, ptr, aligned_size)
+    if not free_ok:
+        # Report success (the reservation itself answered the question) but
+        # note the leak rather than retrying the free from diagnostics code.
+        return True, f"reserved but cuMemAddressFree reported {free_err}"
+    return True, None
+
+
+@dataclass
+class ProbeSnapshot:
+    """Raw results of one pass of the OOM reason checker.
+
+    Fields default to ``None`` ("not probed") rather than ``False``, because a
+    later step is skipped -- not failed -- once an earlier, cheaper step
+    already answers the question. For example, a pool-sized VA reservation is
+    never attempted once a single-granularity reservation has already failed.
+    """
+
+    has_context: bool = False
+    context_error: str | None = None
+
+    mem_free: int | None = None
+    mem_total: int | None = None
+    mem_get_info_error: str | None = None
+
+    mempools_supported: bool | None = None
+    vmm_supported: bool | None = None
+
+    small_alloc_ok: bool | None = None
+    small_alloc_error: str | None = None
+
+    granularity: int | None = None
+    small_va_ok: bool | None = None
+    small_va_error: str | None = None
+
+    pool_va_size: int | None = None
+    pool_va_ok: bool | None = None
+    pool_va_error: str | None = None
+
+    get_mem_pool_ok: bool | None = None
+    get_mem_pool_error: str | None = None
+    get_default_mem_pool_ok: bool | None = None
+    get_default_mem_pool_error: str | None = None
+
+    capped_pool_create_ok: bool | None = None
+    capped_pool_create_error: str | None = None
+
+
+def probe_basics():
+    """Run the cheap, side-effect-free prefix of the OOM reason checker.
+
+    Covers steps 1-4 below: context, physical free/total memory, device
+    attributes, and one small physical allocation. None of these touch host
+    VA or memory pools, so this is safe to call from an ordinary (non-OOM)
+    test as a live smoke check. Returns ``(snapshot, dev_or_None)``; ``dev``
+    is threaded through to :func:`run_probe` so it does not have to re-derive
+    it.
+
+    See :func:`run_probe` for the full, numbered probe sequence.
+    """
+    snapshot = ProbeSnapshot()
+
+    ctx_ok, ctx_err, ctx_values = _call(driver.cuCtxGetCurrent)
+    # cuCtxGetCurrent succeeds even with no bound context: it returns a null
+    # CUcontext, not None, so "no context" has to be checked via int(), not
+    # an identity check against None.
+    snapshot.has_context = bool(ctx_ok and ctx_values and ctx_values[0] is not None and int(ctx_values[0]) != 0)
+    if not ctx_ok:
+        snapshot.context_error = ctx_err
+    if not snapshot.has_context:
+        return snapshot, None
+
+    mem_ok, mem_err, mem_values = _call(driver.cuMemGetInfo)
+    if not mem_ok:
+        snapshot.mem_get_info_error = mem_err
+        return snapshot, None
+    snapshot.mem_free, snapshot.mem_total = mem_values
+
+    count_ok, _count_err, count_values = _call(driver.cuDeviceGetCount)
+    if not count_ok or not count_values or count_values[0] < 1:
+        return snapshot, None
+    dev_ok, _dev_err, dev_values = _call(driver.cuDeviceGet, 0)
+    if not dev_ok:
+        return snapshot, None
+    (dev,) = dev_values
+
+    pools_ok, _e1, pools_values = _call(
+        driver.cuDeviceGetAttribute, driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_MEMORY_POOLS_SUPPORTED, dev
+    )
+    snapshot.mempools_supported = bool(pools_values[0]) if pools_ok else None
+
+    vmm_ok, _e2, vmm_values = _call(
+        driver.cuDeviceGetAttribute,
+        driver.CUdevice_attribute.CU_DEVICE_ATTRIBUTE_VIRTUAL_MEMORY_MANAGEMENT_SUPPORTED,
+        dev,
+    )
+    snapshot.vmm_supported = bool(vmm_values[0]) if vmm_ok else None
+
+    alloc_ok, alloc_err, alloc_values = _call(driver.cuMemAlloc, 4096)
+    snapshot.small_alloc_ok = alloc_ok
+    if alloc_ok:
+        (ptr,) = alloc_values
+        _call(driver.cuMemFree, ptr)
+    else:
+        snapshot.small_alloc_error = alloc_err
+
+    return snapshot, dev
+
+
+def run_probe():
+    """Run the OOM reason checker once and return its :class:`ProbeSnapshot`.
+
+    Ordered from cheapest/most-general to most-specific so a probe that
+    already answers the question skips the more expensive ones after it:
+
+    1-4. :func:`probe_basics` -- context, ``cuMemGetInfo``, device
+       attributes (are mempools / VMM even supported here?), and a small
+       ``cuMemAlloc`` (the legacy physical allocator, not a pool).
+    5. A single-granularity ``cuMemAddressReserve`` -- the cheapest possible
+       host VA probe. If this fails, nothing bigger can succeed either.
+    6. A pool-sized (~2x device memory) ``cuMemAddressReserve`` -- the same
+       size a default or uncapped pool would need.
+    7. ``cuDeviceGetMemPool`` / ``cuDeviceGetDefaultMemPool`` -- note that,
+       unlike step 6, a *successful* call here is not undone: querying the
+       default pool performs this reservation for real and for the rest of
+       the process's life, whether or not this checker ever ran.
+    8. A capped ``cuMemPoolCreate(maxSize=POOL_SIZE)`` -- distinguishes "no
+       pool at all fits" from "only the ~2x default-sized window does not".
+    """
+    snapshot, dev = probe_basics()
+    if dev is None:
+        return snapshot
+    device_id = int(dev)
+
+    if not snapshot.vmm_supported:
+        return snapshot
+
+    granularity = _allocation_granularity(device_id)
+    snapshot.granularity = granularity
+
+    small_ok, small_err = _reserve_and_free(granularity, granularity)
+    snapshot.small_va_ok = small_ok
+    if not small_ok:
+        snapshot.small_va_error = small_err
+        return snapshot  # A bigger reservation cannot succeed if this one did not.
+
+    if not snapshot.mempools_supported:
+        return snapshot
+
+    pool_window = _round_up(2 * snapshot.mem_total, granularity)
+    snapshot.pool_va_size = pool_window
+    pool_ok, pool_err = _reserve_and_free(pool_window, granularity)
+    snapshot.pool_va_ok = pool_ok
+    if not pool_ok:
+        snapshot.pool_va_error = pool_err
+
+    # Unlike the reserve/free probe above, a successful call here is real and
+    # permanent: it is the same reservation cuda.core's DeviceMemoryResource
+    # would trigger. It is deliberately still probed, because it is the exact
+    # call that failed in the original #2381 logs.
+    get_ok, get_err, _v1 = _call(driver.cuDeviceGetMemPool, dev)
+    snapshot.get_mem_pool_ok = get_ok
+    if not get_ok:
+        snapshot.get_mem_pool_error = get_err
+
+    default_ok, default_err, _v2 = _call(driver.cuDeviceGetDefaultMemPool, dev)
+    snapshot.get_default_mem_pool_ok = default_ok
+    if not default_ok:
+        snapshot.get_default_mem_pool_error = default_err
+
+    props = driver.CUmemPoolProps()
+    props.allocType = driver.CUmemAllocationType.CU_MEM_ALLOCATION_TYPE_PINNED
+    props.handleTypes = driver.CUmemAllocationHandleType.CU_MEM_HANDLE_TYPE_NONE
+    props.location.type = driver.CUmemLocationType.CU_MEM_LOCATION_TYPE_DEVICE
+    props.location.id = device_id
+    props.maxSize = POOL_SIZE  # Never 0: an uncapped pool reserves another ~2x window.
+    create_ok, create_err, create_values = _call(driver.cuMemPoolCreate, props)
+    snapshot.capped_pool_create_ok = create_ok
+    if create_ok:
+        (pool,) = create_values
+        _call(driver.cuMemPoolDestroy, pool)
+    else:
+        snapshot.capped_pool_create_error = create_err
+
+    return snapshot
+
+
+def classify(snapshot: ProbeSnapshot) -> str:
+    """Turn a probe snapshot into a one-line, human-readable verdict.
+
+    Pure function of the snapshot, so this can -- and should -- be tested
+    without a GPU. Checks are ordered from "nothing could be probed" to
+    "everything probed fine", each returning as soon as it names something
+    specific enough to act on.
+    """
+    if not snapshot.has_context:
+        return "no current CUDA context; cannot narrow down the reason"
+
+    if snapshot.mem_get_info_error is not None:
+        return f"cuMemGetInfo itself failed ({snapshot.mem_get_info_error}); the device may be unavailable"
+
+    if snapshot.small_alloc_ok is False:
+        return "likely physical device memory exhaustion: a small cuMemAlloc failed outright"
+
+    low_free = (
+        snapshot.mem_total is not None
+        and snapshot.mem_free is not None
+        and snapshot.mem_total > 0
+        and (snapshot.mem_free / snapshot.mem_total) < 0.05
+    )
+    if low_free:
+        return "likely physical device memory exhaustion: cuMemGetInfo reports under 5% free"
+
+    if snapshot.small_va_ok is False:
+        return "host virtual-address space is exhausted even for a single allocation-granularity window"
+
+    if snapshot.mempools_supported is False:
+        return "mempools are not supported on this device; the OOM is unrelated to memory pools"
+
+    if snapshot.pool_va_ok is False:
+        if snapshot.capped_pool_create_ok:
+            return (
+                "likely host VA exhaustion for the pool-sized window only: a capped "
+                "memory pool (helpers.constants.POOL_SIZE) still creates fine, but a "
+                "reservation the size of the observed default pool window does not"
+            )
+        return "likely host VA exhaustion: a pool-sized reservation failed while device memory is mostly free"
+
+    if snapshot.get_mem_pool_ok is False or snapshot.get_default_mem_pool_ok is False:
+        return (
+            "default mempool materialization failed even though an equivalently sized "
+            "standalone VA reservation just succeeded; the OOM may be from a resource "
+            "other than host VA or physical device memory"
+        )
+
+    if snapshot.capped_pool_create_ok is False:
+        return "a capped memory pool create failed even though larger probes above succeeded; inconclusive"
+
+    return "inconclusive: all probes succeeded; the original failure may have been transient or another process holding resources"
+
+
+def format_probe_log(snapshot: ProbeSnapshot) -> str:
+    """Render the raw probe results, independent of the verdict."""
+    lines = ["--- direct driver probe (bypasses cuda.core's error reporting) ---"]
+
+    if not snapshot.has_context:
+        suffix = f" <raised {snapshot.context_error}>" if snapshot.context_error else " (no context)"
+        lines.append(f"cuCtxGetCurrent(){suffix}")
+        return "\n".join(lines)
+    lines.append("cuCtxGetCurrent() -> ok")
+
+    if snapshot.mem_get_info_error is not None:
+        lines.append(f"cuMemGetInfo() -> <failed: {snapshot.mem_get_info_error}>")
+        return "\n".join(lines)
+    free_frac = snapshot.mem_free / snapshot.mem_total if snapshot.mem_total else float("nan")
+    lines.append(
+        f"cuMemGetInfo() -> free={snapshot.mem_free / GIB:.2f} GiB, "
+        f"total={snapshot.mem_total / GIB:.2f} GiB ({free_frac:.1%} free)"
+    )
+    lines.append(f"mempools supported: {snapshot.mempools_supported}")
+    lines.append(f"VMM (cuMemAddressReserve) supported: {snapshot.vmm_supported}")
+    lines.append(
+        "small cuMemAlloc(4 KiB) -> "
+        + ("ok, freed" if snapshot.small_alloc_ok else f"<failed: {snapshot.small_alloc_error}>")
+    )
+
+    if not snapshot.vmm_supported:
+        lines.append("(VMM unsupported: skipping host VA reservation probes)")
+        return "\n".join(lines)
+
+    lines.append(f"allocation granularity: {snapshot.granularity} bytes")
+    lines.append(
+        f"cuMemAddressReserve({snapshot.granularity} bytes) -> "
+        + ("ok, freed" if snapshot.small_va_ok else f"<failed: {snapshot.small_va_error}>")
+    )
+    if not snapshot.small_va_ok:
+        return "\n".join(lines)
+
+    if not snapshot.mempools_supported:
+        lines.append("(mempools unsupported: skipping pool-related probes)")
+        return "\n".join(lines)
+
+    lines.append(
+        f"cuMemAddressReserve({snapshot.pool_va_size} bytes, observed default pool window, "
+        "not a documented guarantee) -> "
+        + ("ok, freed" if snapshot.pool_va_ok else f"<failed: {snapshot.pool_va_error}>")
+    )
+    lines.append(
+        "cuDeviceGetMemPool(dev 0) -> "
+        + (
+            "ok -- NOTE: this permanently reserves the window above, for the rest of "
+            "this process, if it was not already reserved"
+            if snapshot.get_mem_pool_ok
+            else f"<failed: {snapshot.get_mem_pool_error}>"
+        )
+    )
+    lines.append(
+        "cuDeviceGetDefaultMemPool(dev 0) -> "
+        + ("ok" if snapshot.get_default_mem_pool_ok else f"<failed: {snapshot.get_default_mem_pool_error}>")
+    )
+    lines.append(
+        f"cuMemPoolCreate(maxSize={POOL_SIZE}) -> "
+        + ("ok, destroyed" if snapshot.capped_pool_create_ok else f"<failed: {snapshot.capped_pool_create_error}>")
+    )
+    return "\n".join(lines)
+
+
+class OomDiagnosticsRecorder:
+    """Captures the OOM reason checker the first time a CUDA OOM is seen, and only then."""
+
+    def __init__(self, filename=DEFAULT_FILENAME):
+        self._filename = filename
+        self._lock = threading.Lock()
+        self._captured = False
+        self._nodeid = None
+        self._artifact_path = None
+        self._artifact_written = False
+
+    @property
+    def captured(self):
+        return self._captured
+
+    @property
+    def nodeid(self):
+        """Node id of the test that triggered capture, or None."""
+        return self._nodeid
+
+    @property
+    def artifact_path(self):
+        """Where the report was written, or None if nothing was captured."""
+        return self._artifact_path
+
+    @property
+    def artifact_written(self):
+        return self._artifact_written
+
+    @staticmethod
+    def matches(exc_text):
+        return OOM_MARKER in exc_text
+
+    def build_report(self, nodeid, phase, exc_text, snapshot=None):
+        if snapshot is None:
+            snapshot = run_probe()
+        verdict = classify(snapshot)
+        return "\n".join(
+            [
+                _BANNER,
+                "cuda_core OOM reason checker: first CUDA_ERROR_OUT_OF_MEMORY of this session",
+                _BANNER,
+                f"test:      {nodeid}",
+                f"phase:     {phase}",
+                f"pid:       {os.getpid()}",
+                f"platform:  {sys.platform}",
+                f"exception: {exc_text}",
+                "",
+                _LESSON,
+                "",
+                format_probe_log(snapshot),
+                "",
+                f"verdict: {verdict}",
+                _BANNER,
+            ]
+        )
+
+    def capture(self, nodeid, phase, exc_text, directory, snapshot=None):
+        """Build and persist the report. Returns None if already captured.
+
+        ``snapshot`` lets callers (mainly tests) skip the live driver probe;
+        production callers leave it unset so :meth:`build_report` runs
+        :func:`run_probe`.
+        """
+        with self._lock:
+            if self._captured:
+                return None
+            self._captured = True
+
+        report = self.build_report(nodeid, phase, exc_text, snapshot=snapshot)
+        destination = pathlib.Path(directory) / self._filename
+        self._nodeid = nodeid
+        self._artifact_path = destination
+        try:
+            destination.write_text(report, encoding="utf-8")
+            self._artifact_written = True
+            return f"{report}\n(diagnostics also written to {destination})"
+        except OSError as exc:
+            return f"{report}\n(could not write {destination}: {exc!r})"
+
+
+_default_recorder = OomDiagnosticsRecorder()
+
+
+def record_if_oom(item, call, report, recorder=None, snapshot=None):
+    """Capture diagnostics when ``report`` is the session's first CUDA OOM.
+
+    ``recorder`` defaults to a module-level singleton so the conftest hook does
+    not have to hold session state; tests pass their own to stay isolated.
+    ``snapshot`` is likewise test-only; see :meth:`OomDiagnosticsRecorder.capture`.
+
+    Returns the emitted text, or None when nothing was captured.
+    """
+    if recorder is None:
+        recorder = _default_recorder
+
+    if recorder.captured or not report.failed or call.excinfo is None:
+        return None
+
+    exc_text = str(call.excinfo.value)
+    if not recorder.matches(exc_text):
+        return None
+
+    text = recorder.capture(item.nodeid, call.when, exc_text, item.config.rootpath, snapshot=snapshot)
+    if text is None:
+        return None
+
+    # terminalreporter writes outside pytest's stdout capture, so this survives
+    # into a redirected log; a bare print() would not.
+    terminal_reporter = item.config.pluginmanager.get_plugin("terminalreporter")
+    if terminal_reporter is not None:
+        terminal_reporter.write_line("")
+        terminal_reporter.write_line(text)
+    return text
+
+
+def report_terminal_summary(terminalreporter, recorder=None):
+    """Point at the diagnostics artifact from pytest's end-of-run summary.
+
+    The report itself is emitted beside the failing test, which in a real
+    failing run is thousands of lines above the summary people actually read.
+
+    Returns the emitted line, or None when nothing was captured.
+    """
+    if recorder is None:
+        recorder = _default_recorder
+
+    if not recorder.captured:
+        return None
+
+    verb = "written to" if recorder.artifact_written else "could NOT be written to"
+    line = f"first CUDA OOM at {recorder.nodeid}; diagnostics {verb} {recorder.artifact_path}"
+    terminalreporter.write_sep("=", "cuda_core OOM diagnostics", red=True)
+    terminalreporter.write_line(line)
+    return line
diff --git a/cuda_core/tests/memory/conftest.py b/cuda_core/tests/memory/conftest.py
new file mode 100644
index 00000000000..ed950df830f
--- /dev/null
+++ b/cuda_core/tests/memory/conftest.py
@@ -0,0 +1,66 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Per-directory conftest for the ``copy_batch`` test modules.
+
+Provides the device, stream and buffer fixtures shared by
+``test_copy_batch.py`` (data movement) and ``test_copy_batch_options.py``
+(options and validation).
+"""
+
+import pytest
+from helpers.copy_batch import COPY_BATCH_COUNT, COPY_BATCH_SIZE
+
+from cuda.core import Device, LegacyPinnedMemoryResource
+
+
+@pytest.fixture
+def copy_batch_device(init_cuda):
+    """``copy_batch`` works on every supported toolkit, so this never skips."""
+    device = Device()
+    device.set_current()
+    return device
+
+
+@pytest.fixture
+def copy_stream(copy_batch_device):
+    """The single stream used for both allocation and copies in a test.
+
+    Stream-ordered pool allocations are only guaranteed usable on the
+    stream that allocated them, so tests allocate and copy on this one
+    stream rather than mixing it with ``device.default_stream``.
+    """
+    s = copy_batch_device.create_stream()
+    yield s
+    s.close()
+
+
+@pytest.fixture
+def h2d_bufs(copy_batch_device, copy_stream):
+    """Pinned-host source / device destination pairs."""
+    pinned_mr = LegacyPinnedMemoryResource()
+    device_mr = copy_batch_device.memory_resource
+
+    srcs = [pinned_mr.allocate(COPY_BATCH_SIZE) for _ in range(COPY_BATCH_COUNT)]
+    dsts = [device_mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(COPY_BATCH_COUNT)]
+
+    yield srcs, dsts
+
+    for buf in srcs + dsts:
+        buf.close(copy_stream)
+    copy_stream.sync()
+
+
+@pytest.fixture
+def device_bufs(copy_batch_device, copy_stream):
+    """Device source / device destination pairs."""
+    device_mr = copy_batch_device.memory_resource
+
+    srcs = [device_mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(COPY_BATCH_COUNT)]
+    dsts = [device_mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(COPY_BATCH_COUNT)]
+
+    yield srcs, dsts
+
+    for buf in srcs + dsts:
+        buf.close(copy_stream)
+    copy_stream.sync()
diff --git a/cuda_core/tests/memory/test_backward_compatibility.py b/cuda_core/tests/memory/test_backward_compatibility.py
new file mode 100644
index 00000000000..aedc4c8b175
--- /dev/null
+++ b/cuda_core/tests/memory/test_backward_compatibility.py
@@ -0,0 +1,49 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Backward-compatibility checks for undocumented dict options in MR constructors."""
+
+import pytest
+from helpers.constants import POOL_SIZE
+from helpers.memory import (
+    create_managed_memory_resource_or_skip,
+    create_pinned_memory_resource_or_xfail,
+    skip_if_managed_memory_unsupported,
+    skip_if_pinned_memory_unsupported,
+)
+
+from cuda.core import Device, DeviceMemoryResource
+
+
+@pytest.mark.agent_authored(model="gpt-5.3-codex")
+def test_device_mr_accepts_dict_keyword(init_cuda):
+    device = Device()
+    if not device.properties.memory_pools_supported:
+        pytest.skip("Device does not support memory pool operations")
+    device.set_current()
+    mr = DeviceMemoryResource(device, options={"max_size": POOL_SIZE})
+    buf = mr.allocate(64, stream=device.default_stream)
+    buf.close(stream=device.default_stream)
+    mr.close()
+
+
+@pytest.mark.agent_authored(model="gpt-5.3-codex")
+def test_pinned_mr_accepts_dict_keyword(init_cuda):
+    device = Device()
+    skip_if_pinned_memory_unsupported(device)
+    device.set_current()
+    mr = create_pinned_memory_resource_or_xfail(options={"max_size": POOL_SIZE}, xfail_device=device)
+    buf = mr.allocate(64, stream=device.default_stream)
+    buf.close(stream=device.default_stream)
+    mr.close()
+
+
+@pytest.mark.agent_authored(model="gpt-5.3-codex")
+def test_managed_mr_accepts_dict_keyword(init_cuda):
+    device = Device()
+    skip_if_managed_memory_unsupported(device)
+    device.set_current()
+    mr = create_managed_memory_resource_or_skip(options={})
+    buf = mr.allocate(64, stream=device.default_stream)
+    buf.close(stream=device.default_stream)
+    mr.close()
diff --git a/cuda_core/tests/memory/test_copy_batch.py b/cuda_core/tests/memory/test_copy_batch.py
new file mode 100644
index 00000000000..88b6c56e698
--- /dev/null
+++ b/cuda_core/tests/memory/test_copy_batch.py
@@ -0,0 +1,312 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Data movement behaviour of ``copy_batch``.
+
+Covers that the right bytes reach the right destination, that batched
+results agree with the per-buffer ``Buffer.copy_to`` path, and that the
+batch is correctly ordered on its stream.
+"""
+
+import pytest
+from helpers.buffers import (
+    compare_buffer_to_constant,
+    compare_equal_buffers,
+    make_scratch_buffer,
+    set_buffer,
+    thread_unsafe_on_windows,
+)
+from helpers.copy_batch import COPY_BATCH_SIZE
+
+from cuda.core import LegacyPinnedMemoryResource
+from cuda.core._stream import LEGACY_DEFAULT_STREAM, PER_THREAD_DEFAULT_STREAM
+from cuda.core.utils import copy_batch
+
+
+@thread_unsafe_on_windows
+class TestCopyBatchCore:
+    """Each transfer direction moves the expected bytes."""
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_h2d_batch(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + 1)
+
+        copy_batch(copy_stream, srcs, dsts)
+        copy_stream.sync()
+
+        for i, dst in enumerate(dsts):
+            assert compare_buffer_to_constant(dst, i + 1)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_d2h_batch(self, copy_batch_device, h2d_bufs, copy_stream):
+        dev = copy_batch_device
+        _, device_dsts = h2d_bufs
+        pinned_mr = LegacyPinnedMemoryResource()
+
+        for i, buf in enumerate(device_dsts):
+            buf.fill(i + 10, stream=copy_stream)
+
+        host_bufs = [pinned_mr.allocate(COPY_BATCH_SIZE) for _ in device_dsts]
+        copy_batch(copy_stream, device_dsts, host_bufs)
+        copy_stream.sync()
+
+        for i, host_buf in enumerate(host_bufs):
+            expected = make_scratch_buffer(dev, i + 10, COPY_BATCH_SIZE)
+            assert compare_equal_buffers(expected, host_buf)
+            expected.close()
+            host_buf.close(copy_stream)
+        copy_stream.sync()
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_d2d_batch(self, device_bufs, copy_stream):
+        srcs, dsts = device_bufs
+        for i, src in enumerate(srcs):
+            src.fill(i + 20, stream=copy_stream)
+
+        copy_batch(copy_stream, srcs, dsts)
+        copy_stream.sync()
+
+        for i, dst in enumerate(dsts):
+            assert compare_buffer_to_constant(dst, i + 20)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_various_sizes(self, copy_batch_device, copy_stream):
+        pinned_mr = LegacyPinnedMemoryResource()
+        device_mr = copy_batch_device.memory_resource
+        sizes = [1024, 2048, 512, 4096]
+
+        srcs = [pinned_mr.allocate(size) for size in sizes]
+        dsts = [device_mr.allocate(size, stream=copy_stream) for size in sizes]
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + 1)
+
+        copy_batch(copy_stream, srcs, dsts)
+        copy_stream.sync()
+
+        for i, dst in enumerate(dsts):
+            assert compare_buffer_to_constant(dst, i + 1)
+
+        for buf in srcs + dsts:
+            buf.close(copy_stream)
+        copy_stream.sync()
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_single_element_batch(self, copy_batch_device, copy_stream):
+        """A one-element batch is legal; only a bare Buffer is rejected."""
+        pinned_mr = LegacyPinnedMemoryResource()
+        src = pinned_mr.allocate(COPY_BATCH_SIZE)
+        dst = copy_batch_device.memory_resource.allocate(COPY_BATCH_SIZE, stream=copy_stream)
+        set_buffer(src, 7)
+
+        copy_batch(copy_stream, [src], [dst])
+        copy_stream.sync()
+
+        assert compare_buffer_to_constant(dst, 7)
+        src.close(copy_stream)
+        dst.close(copy_stream)
+        copy_stream.sync()
+
+
+@thread_unsafe_on_windows
+class TestCopyBatchEquivalence:
+    """Batched results must agree with the already-tested per-buffer path.
+
+    ``Buffer.copy_to`` and ``Buffer.copy_from`` have their own coverage in
+    ``tests/test_memory.py``, so agreement between the two paths is the
+    property under test here.
+    """
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_batch_matches_sequential_copy_to(self, copy_batch_device, h2d_bufs, copy_stream):
+        srcs, _ = h2d_bufs
+        device_mr = copy_batch_device.memory_resource
+        pinned_mr = LegacyPinnedMemoryResource()
+
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + 50)
+
+        seq_dsts = [device_mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in srcs]
+        for src, dst in zip(srcs, seq_dsts):
+            src.copy_to(dst, stream=copy_stream)
+
+        batch_dsts = [device_mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in srcs]
+        copy_batch(copy_stream, srcs, batch_dsts)
+        copy_stream.sync()
+
+        for seq_dst, batch_dst in zip(seq_dsts, batch_dsts):
+            seq_host = pinned_mr.allocate(COPY_BATCH_SIZE)
+            batch_host = pinned_mr.allocate(COPY_BATCH_SIZE)
+            seq_dst.copy_to(seq_host, stream=copy_stream)
+            batch_dst.copy_to(batch_host, stream=copy_stream)
+            copy_stream.sync()
+            assert compare_equal_buffers(seq_host, batch_host)
+            seq_host.close(copy_stream)
+            batch_host.close(copy_stream)
+
+        for buf in seq_dsts + batch_dsts:
+            buf.close(copy_stream)
+        copy_stream.sync()
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_batch_matches_sequential_varied_sizes(self, copy_batch_device, copy_stream):
+        device_mr = copy_batch_device.memory_resource
+        pinned_mr = LegacyPinnedMemoryResource()
+        sizes = [1024, 2048, 512]
+
+        srcs = [pinned_mr.allocate(size) for size in sizes]
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + 60)
+
+        seq_dsts = [device_mr.allocate(size, stream=copy_stream) for size in sizes]
+        for src, dst in zip(srcs, seq_dsts):
+            src.copy_to(dst, stream=copy_stream)
+
+        batch_dsts = [device_mr.allocate(size, stream=copy_stream) for size in sizes]
+        copy_batch(copy_stream, srcs, batch_dsts)
+        copy_stream.sync()
+
+        for size, seq_dst, batch_dst in zip(sizes, seq_dsts, batch_dsts):
+            seq_host = pinned_mr.allocate(size)
+            batch_host = pinned_mr.allocate(size)
+            seq_dst.copy_to(seq_host, stream=copy_stream)
+            batch_dst.copy_to(batch_host, stream=copy_stream)
+            copy_stream.sync()
+            assert compare_equal_buffers(seq_host, batch_host)
+            seq_host.close(copy_stream)
+            batch_host.close(copy_stream)
+
+        for buf in srcs + seq_dsts + batch_dsts:
+            buf.close(copy_stream)
+        copy_stream.sync()
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_batch_matches_sequential_d2d(self, copy_batch_device, device_bufs, copy_stream):
+        srcs, seq_dsts = device_bufs
+        device_mr = copy_batch_device.memory_resource
+        pinned_mr = LegacyPinnedMemoryResource()
+
+        for i, src in enumerate(srcs):
+            src.fill(i + 70, stream=copy_stream)
+
+        for src, dst in zip(srcs, seq_dsts):
+            src.copy_to(dst, stream=copy_stream)
+
+        batch_dsts = [device_mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in srcs]
+        copy_batch(copy_stream, srcs, batch_dsts)
+        copy_stream.sync()
+
+        for seq_dst, batch_dst in zip(seq_dsts, batch_dsts):
+            seq_host = pinned_mr.allocate(COPY_BATCH_SIZE)
+            batch_host = pinned_mr.allocate(COPY_BATCH_SIZE)
+            seq_dst.copy_to(seq_host, stream=copy_stream)
+            batch_dst.copy_to(batch_host, stream=copy_stream)
+            copy_stream.sync()
+            assert compare_equal_buffers(seq_host, batch_host)
+            seq_host.close(copy_stream)
+            batch_host.close(copy_stream)
+
+        for buf in batch_dsts:
+            buf.close(copy_stream)
+        copy_stream.sync()
+
+
+class TestCopyBatchStreamSemantics:
+    """Where the batch sits in stream order, and what it cannot be part of."""
+
+    @pytest.mark.thread_unsafe(reason="shared copy_stream and buffers must not interleave")
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_ordered_between_prior_and_later_stream_work(self, device_bufs, copy_stream):
+        """The batch must observe prior stream work and precede later work.
+
+        Each source is filled with ``before``, copied, then refilled with
+        ``after`` -- all enqueued on one stream with no intervening sync.
+        Destinations holding ``before`` prove the copy ran after the first
+        fill and before the second, rather than racing either.
+        """
+        srcs, dsts = device_bufs
+        before, after = 11, 22
+
+        for src in srcs:
+            src.fill(before, stream=copy_stream)
+        copy_batch(copy_stream, srcs, dsts)
+        for src in srcs:
+            src.fill(after, stream=copy_stream)
+
+        copy_stream.sync()
+
+        for dst in dsts:
+            assert compare_buffer_to_constant(dst, before)
+        for src in srcs:
+            assert compare_buffer_to_constant(src, after)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_graph_builder_is_rejected(self, copy_batch_device, device_bufs, copy_stream):
+        """Batched memcpy cannot be captured into a graph.
+
+        ``cuMemcpyBatchAsync`` has no graph-node form and the driver
+        rejects it mid-capture, so ``copy_batch`` is typed to take only a
+        ``Stream`` and refuses a ``GraphBuilder`` at the boundary rather
+        than failing later with ``CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED``.
+        Use ``GraphNode.memcpy`` or per-buffer ``Buffer.copy_to`` to build
+        copies into a graph.
+        """
+        srcs, dsts = device_bufs
+        gb = copy_batch_device.create_graph_builder().begin_building()
+        try:
+            with pytest.raises(TypeError, match="Argument 'stream' has incorrect type"):
+                copy_batch(gb, srcs, dsts)
+        finally:
+            # Nothing was captured, so the builder still ends cleanly.
+            gb.end_building()
+            gb.close()
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_capturing_stream_is_rejected(self, copy_batch_device, device_bufs):
+        """Passing the GraphBuilder's underlying stream must also be rejected.
+
+        The GraphBuilder type check is bypassed when the caller passes
+        ``gb.stream`` directly; the capture-status check closes that loophole.
+        """
+        srcs, dsts = device_bufs
+        gb = copy_batch_device.create_graph_builder().begin_building()
+        try:
+            with pytest.raises(TypeError, match="graph capture"):
+                copy_batch(gb.stream, srcs, dsts)
+        finally:
+            gb.end_building()
+            gb.close()
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_legacy_default_stream_token_is_rejected(self, init_cuda, h2d_bufs):
+        """LEGACY_DEFAULT_STREAM must be rejected with a clear TypeError.
+
+        cuMemcpyBatchAsync rejects the legacy token outright
+        (CUDA_ERROR_INVALID_VALUE); copy_batch surfaces this before ever
+        calling the driver.
+        """
+        srcs, dsts = h2d_bufs
+        with pytest.raises(TypeError, match="LEGACY_DEFAULT_STREAM"):
+            copy_batch(LEGACY_DEFAULT_STREAM, srcs, dsts)
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    @thread_unsafe_on_windows
+    def test_per_thread_default_stream_token_is_accepted(self, copy_batch_device):
+        """PER_THREAD_DEFAULT_STREAM is a real stream to the driver and works
+        like any explicit stream for copy_batch, unlike LEGACY_DEFAULT_STREAM.
+        """
+        pinned_mr = LegacyPinnedMemoryResource()
+        device_mr = copy_batch_device.memory_resource
+        src = pinned_mr.allocate(COPY_BATCH_SIZE)
+        dst = device_mr.allocate(COPY_BATCH_SIZE, stream=PER_THREAD_DEFAULT_STREAM)
+        set_buffer(src, 99)
+
+        copy_batch(PER_THREAD_DEFAULT_STREAM, [src], [dst])
+        copy_batch_device.sync()
+
+        assert compare_buffer_to_constant(dst, 99)
+
+        src.close(PER_THREAD_DEFAULT_STREAM)
+        dst.close(PER_THREAD_DEFAULT_STREAM)
+        copy_batch_device.sync()
diff --git a/cuda_core/tests/memory/test_copy_batch_options.py b/cuda_core/tests/memory/test_copy_batch_options.py
new file mode 100644
index 00000000000..85dbe65e3c4
--- /dev/null
+++ b/cuda_core/tests/memory/test_copy_batch_options.py
@@ -0,0 +1,461 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""``CopyOptions`` handling and argument validation for ``copy_batch``.
+
+Covers how options are encoded into the driver's attribute runs, how each
+option field behaves, and every rejection path.
+"""
+
+import pytest
+from helpers.buffers import compare_buffer_to_constant, set_buffer, thread_unsafe_on_windows
+from helpers.copy_batch import (
+    COPY_BATCH_SIZE,
+    assert_managed_holds,
+)
+
+# Shared with test_managed_ops.py: handles the CUDA 13 requirement, mempool
+# OOM, and CUDA_ERROR_NOT_SUPPORTED (managed pools are unavailable on
+# Windows), so the location-hint tests skip rather than error there.
+from helpers.memory import create_managed_memory_resource_or_skip
+
+from cuda.core import Host, LegacyPinnedMemoryResource
+from cuda.core._memory._copy_enums import _attr_run_starts, _reject_unsupported_during_api_call
+from cuda.core._memory._copy_ops import (
+    _normalize_copy_options,
+)
+from cuda.core._stream import PER_THREAD_DEFAULT_STREAM
+from cuda.core._utils.version import binding_version, driver_version
+from cuda.core.utils import (
+    CopyOptions,
+    MemcpyOverlapMode,
+    MemcpySrcAccessOrder,
+    copy_batch,
+)
+
+
+def _batch_native_available():
+    """True when copy_batch will actually use cuMemcpyBatchAsync."""
+    return binding_version() >= (13, 0, 0) and driver_version() >= (13, 0, 0)
+
+
+class TestOptionsEncoding:
+    """How ``options`` becomes the driver's ``attrs`` / ``attrsIdxs`` pair.
+
+    Pure logic, no CUDA. This is the only place the effect of ``options``
+    is observable: they are hints that change how the driver stages a
+    transfer, never the bytes it produces, so no data comparison can
+    distinguish an option that was applied from one that was dropped.
+    """
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_scalar_broadcasts_to_every_copy(self):
+        """A scalar must reach all N copies, not just the first."""
+        n = 4
+        scalar = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+
+        # copy_batch expands the scalar to one entry per copy...
+        assert _normalize_copy_options(scalar, n) == (scalar,) * n
+        # ...and the encoder collapses those to a single driver attribute.
+        assert _attr_run_starts(_normalize_copy_options(scalar, n)) == [0]
+
+        # An explicit list of the same option is indistinguishable.
+        assert _normalize_copy_options([scalar] * n, n) == _normalize_copy_options(scalar, n)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_none_broadcasts_defaults(self):
+        assert _normalize_copy_options(None, 3) == (CopyOptions(),) * 3
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_sequence_is_never_broadcast(self):
+        """A sequence pairs by index, so a short one is an error."""
+        scalar = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+        with pytest.raises(ValueError, match="options length"):
+            _normalize_copy_options([scalar], 4)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_equal_but_distinct_instances_collapse(self):
+        # Structural equality, not identity, drives the collapse.
+        attrs = [CopyOptions(src_access_order="stream") for _ in range(3)]
+        assert len({id(a) for a in attrs}) == 3
+        assert _attr_run_starts(attrs) == [0]
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_all_distinct_yields_one_run_each(self):
+        attrs = [
+            CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM),
+            CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY),
+            CopyOptions(src_access_order=MemcpySrcAccessOrder.DURING_API_CALL),
+        ]
+        assert _attr_run_starts(attrs) == [0, 1, 2]
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_adjacent_runs_are_grouped(self):
+        stream_attr = CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM)
+        any_attr = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+        attrs = [stream_attr, stream_attr, any_attr, any_attr, stream_attr]
+        # Runs start at 0 (stream), 2 (any) and 4 (stream again).
+        assert _attr_run_starts(attrs) == [0, 2, 4]
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_single_element(self):
+        assert _attr_run_starts([CopyOptions()]) == [0]
+
+
+class TestRejectUnsupportedDuringApiCall:
+    """``_reject_unsupported_during_api_call`` guards the one hazardous fallback.
+
+    Pure logic, no CUDA: this is what both ``Buffer.copy_to``/``copy_from``
+    and ``copy_batch`` call before falling back to a plain ``cuMemcpyAsync``
+    when the native attributes path is unavailable. STREAM and ANY never
+    promise access sooner than stream order, so cuMemcpyAsync satisfies them
+    silently; DURING_API_CALL promises all source reads complete before the
+    call returns, which cuMemcpyAsync cannot provide, so it must raise
+    instead of silently downgrading that guarantee.
+    """
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_during_api_call_raises(self):
+        with pytest.raises(RuntimeError, match="src_access_order=DURING_API_CALL"):
+            _reject_unsupported_during_api_call(MemcpySrcAccessOrder.DURING_API_CALL, "some requirement")
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_during_api_call_message_names_requirement_and_index(self):
+        with pytest.raises(RuntimeError, match="requires some requirement") as exc_info:
+            _reject_unsupported_during_api_call(MemcpySrcAccessOrder.DURING_API_CALL, "some requirement", index=5)
+        assert "at index 5" in str(exc_info.value)
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_during_api_call_message_omits_index_when_not_given(self):
+        with pytest.raises(RuntimeError) as exc_info:
+            _reject_unsupported_during_api_call(MemcpySrcAccessOrder.DURING_API_CALL, "some requirement")
+        assert "at index" not in str(exc_info.value)
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    @pytest.mark.parametrize("order", [MemcpySrcAccessOrder.STREAM, MemcpySrcAccessOrder.ANY])
+    def test_stream_and_any_do_not_raise(self, order):
+        """Stream-ordered access satisfies both, so no fallback hazard exists."""
+        _reject_unsupported_during_api_call(order, "some requirement")
+        _reject_unsupported_during_api_call(order, "some requirement", index=0)
+
+
+@thread_unsafe_on_windows
+class TestCopyBatchOptions:
+    """Each ``CopyOptions`` field is accepted and does not corrupt the copy."""
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    @pytest.mark.parametrize(
+        ("order", "marker"),
+        [
+            (MemcpySrcAccessOrder.STREAM, 31),
+            (MemcpySrcAccessOrder.ANY, 33),
+        ],
+    )
+    def test_src_access_order(self, h2d_bufs, copy_stream, order, marker):
+        """STREAM and ANY are accepted and never corrupt the copy.
+
+        Both are satisfied by stream-ordered access at worst, so this holds
+        whether the native cuMemcpyBatchAsync path is used or the copy falls
+        back to a per-copy cuMemcpyAsync loop. DURING_API_CALL is different
+        (see test_during_api_call): its stronger guarantee cannot be
+        silently downgraded, so it is tested separately.
+        """
+        srcs, dsts = h2d_bufs
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + marker)
+
+        copy_batch(copy_stream, srcs, dsts, options=CopyOptions(src_access_order=order))
+        copy_stream.sync()
+
+        for i, dst in enumerate(dsts):
+            assert compare_buffer_to_constant(dst, i + marker)
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_during_api_call(self, h2d_bufs, copy_stream):
+        """DURING_API_CALL is honored on the native cuMemcpyBatchAsync path.
+
+        On the per-copy cuMemcpyAsync fallback (pre-CUDA-13 build, or
+        driver/bindings older than 13.0) it must raise RuntimeError instead
+        of silently downgrading to stream-ordered access, which cannot honor
+        the guarantee that all source reads complete before the call
+        returns (see TestRejectUnsupportedDuringApiCall). CI runs both
+        generations (see ci/test-matrix.yml), so this test must handle both
+        outcomes rather than assuming the native path is available.
+        """
+        srcs, dsts = h2d_bufs
+        marker = 32
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + marker)
+
+        opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.DURING_API_CALL)
+        if _batch_native_available():
+            copy_batch(copy_stream, srcs, dsts, options=opts)
+            copy_stream.sync()
+            for i, dst in enumerate(dsts):
+                assert compare_buffer_to_constant(dst, i + marker)
+        else:
+            with pytest.raises(RuntimeError, match="DURING_API_CALL"):
+                copy_batch(copy_stream, srcs, dsts, options=opts)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_per_copy_options(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + 40)
+
+        # DURING_API_CALL is deliberately excluded here: it raises RuntimeError
+        # rather than silently falling back on pre-CUDA-13 driver/bindings (see
+        # test_during_api_call), which CI also exercises (ci/test-matrix.yml).
+        # STREAM and ANY are enough to prove distinct per-copy options don't
+        # corrupt the data; the encoding itself is covered by TestOptionsEncoding.
+        per_copy_options = [
+            CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM),
+            CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY),
+            CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY),
+            CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM),
+        ]
+        copy_batch(copy_stream, srcs, dsts, options=per_copy_options)
+        copy_stream.sync()
+
+        for i, dst in enumerate(dsts):
+            assert compare_buffer_to_constant(dst, i + 40)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_location_hints_do_not_corrupt_copy(self, copy_batch_device, copy_stream):
+        """Device and host hints are accepted and leave the bytes intact.
+
+        Hints only steer how the driver stages a transfer, so no data
+        comparison can show one was *applied*; what this catches is a hint
+        that errors or corrupts. It is also the only test that drives the
+        ``device`` and ``host`` branches of ``to_cumemlocation`` and the
+        ``src_location_hint`` path through ``copy_batch``.
+        """
+        dev = copy_batch_device
+        mr = create_managed_memory_resource_or_skip()
+        srcs = [mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(2)]
+        dsts = [mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(2)]
+
+        for i, src in enumerate(srcs):
+            src.fill(i + 80, stream=copy_stream)
+
+        options = CopyOptions(
+            src_access_order=MemcpySrcAccessOrder.STREAM,
+            src_location_hint=dev,
+            dst_location_hint=Host(),
+        )
+        copy_batch(copy_stream, srcs, dsts, options=options)
+        copy_stream.sync()
+
+        for i, dst in enumerate(dsts):
+            assert_managed_holds(dev, dst, i + 80, stream=copy_stream)
+
+        for buf in srcs + dsts:
+            buf.close(copy_stream)
+        copy_stream.sync()
+        mr.close()
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_host_numa_location_hint(self, copy_batch_device, copy_stream):
+        """A NUMA-specific host hint is accepted and does not corrupt the copy."""
+        dev = copy_batch_device
+        numa_id = dev.properties.host_numa_id
+        if numa_id < 0:
+            pytest.skip("System does not report a host NUMA node for this device")
+        mr = create_managed_memory_resource_or_skip()
+        srcs = [mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(2)]
+        dsts = [mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(2)]
+        for i, src in enumerate(srcs):
+            src.fill(i + 85, stream=copy_stream)
+
+        copy_batch(copy_stream, srcs, dsts, options=CopyOptions(dst_location_hint=Host(numa_id=numa_id)))
+        copy_stream.sync()
+        for i, dst in enumerate(dsts):
+            assert_managed_holds(dev, dst, i + 85, stream=copy_stream)
+
+        for buf in srcs + dsts:
+            buf.close(copy_stream)
+        copy_stream.sync()
+        mr.close()
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_host_numa_current_location_hint(self, copy_batch_device, copy_stream):
+        """Host.numa_current() as a location hint is accepted and does not corrupt the copy."""
+        dev = copy_batch_device
+        if dev.properties.host_numa_id < 0:
+            pytest.skip("System does not report a host NUMA node for this device")
+        mr = create_managed_memory_resource_or_skip()
+        srcs = [mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(2)]
+        dsts = [mr.allocate(COPY_BATCH_SIZE, stream=copy_stream) for _ in range(2)]
+        for i, src in enumerate(srcs):
+            src.fill(i + 86, stream=copy_stream)
+
+        copy_batch(copy_stream, srcs, dsts, options=CopyOptions(dst_location_hint=Host.numa_current()))
+        copy_stream.sync()
+        for i, dst in enumerate(dsts):
+            assert_managed_holds(dev, dst, i + 86, stream=copy_stream)
+
+        for buf in srcs + dsts:
+            buf.close(copy_stream)
+        copy_stream.sync()
+        mr.close()
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_overlap_mode_copies_correctly(self, h2d_bufs, copy_stream):
+        """The overlap hint is advisory and must not change the bytes copied."""
+        srcs, dsts = h2d_bufs
+        for i, src in enumerate(srcs):
+            set_buffer(src, i + 90)
+
+        copy_batch(
+            copy_stream,
+            srcs,
+            dsts,
+            options=CopyOptions(overlap_mode=MemcpyOverlapMode.PREFER_OVERLAP_WITH_COMPUTE),
+        )
+        copy_stream.sync()
+
+        for i, dst in enumerate(dsts):
+            assert compare_buffer_to_constant(dst, i + 90)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_default_overlap_mode_does_not_warn(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+        copy_batch(copy_stream, srcs, dsts, options=CopyOptions())
+        copy_stream.sync()
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_options_on_per_thread_default_stream(self, copy_batch_device):
+        """CopyOptions work on PER_THREAD_DEFAULT_STREAM like any explicit stream.
+
+        Unlike LEGACY_DEFAULT_STREAM (rejected outright, see
+        TestCopyBatchStreamSemantics in test_copy_batch.py),
+        PER_THREAD_DEFAULT_STREAM is a real stream to cuMemcpyBatchAsync.
+        """
+        pinned_mr = LegacyPinnedMemoryResource()
+        device_mr = copy_batch_device.memory_resource
+        src = pinned_mr.allocate(COPY_BATCH_SIZE)
+        dst = device_mr.allocate(COPY_BATCH_SIZE, stream=PER_THREAD_DEFAULT_STREAM)
+        set_buffer(src, 44)
+
+        copy_batch(
+            PER_THREAD_DEFAULT_STREAM,
+            [src],
+            [dst],
+            options=CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY),
+        )
+        copy_batch_device.sync()
+
+        assert compare_buffer_to_constant(dst, 44)
+
+        src.close(PER_THREAD_DEFAULT_STREAM)
+        dst.close(PER_THREAD_DEFAULT_STREAM)
+        copy_batch_device.sync()
+
+
+class TestCopyOptionsValidation:
+    """``CopyOptions`` rejects invalid enum values at construction."""
+
+    @pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+    def test_type_hints_resolvable(self):
+        """All annotations on CopyOptions must resolve without NameError."""
+        import typing
+
+        typing.get_type_hints(CopyOptions)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_invalid_access_order(self):
+        with pytest.raises(ValueError, match="invalid src_access_order"):
+            CopyOptions(src_access_order="invalid_order")
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_invalid_overlap_mode(self):
+        with pytest.raises(ValueError, match="invalid overlap_mode"):
+            CopyOptions(overlap_mode="invalid_mode")
+
+
+class TestCopyBatchValidation:
+    """``copy_batch`` rejects malformed buffer and option arguments."""
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_rejects_single_buffer(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+
+        with pytest.raises(TypeError, match="sequence of Buffers"):
+            copy_batch(copy_stream, srcs[0], dsts)
+
+        with pytest.raises(TypeError, match="sequence of Buffers"):
+            copy_batch(copy_stream, srcs, dsts[0])
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_rejects_empty_sequence(self, h2d_bufs, copy_stream):
+        srcs, _ = h2d_bufs
+
+        with pytest.raises(ValueError, match="empty buffers sequence"):
+            copy_batch(copy_stream, [], [])
+
+        with pytest.raises(ValueError, match="empty buffers sequence"):
+            copy_batch(copy_stream, srcs, [])
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_rejects_non_buffer_element(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+
+        with pytest.raises(TypeError, match="expected Buffer, got int"):
+            copy_batch(copy_stream, [srcs[0], 42], dsts[:2])
+
+        with pytest.raises(TypeError, match="expected Buffer, got NoneType"):
+            copy_batch(copy_stream, srcs[:2], [dsts[0], None])
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_rejects_non_sequence(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+
+        with pytest.raises(TypeError, match="must be a sequence of Buffer"):
+            copy_batch(copy_stream, 42, dsts)
+
+        with pytest.raises(TypeError, match="must be a sequence of Buffer"):
+            copy_batch(copy_stream, srcs, None)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_length_mismatch(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+
+        with pytest.raises(ValueError, match="does not match dsts length"):
+            copy_batch(copy_stream, srcs[:2], dsts[:3])
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    @pytest.mark.parametrize(("src_size", "dst_size"), [(1024, 2048), (2048, 1024)])
+    def test_size_mismatch(self, copy_batch_device, copy_stream, src_size, dst_size):
+        """Sizes come from the buffers, so any inequality is an error."""
+        pinned_mr = LegacyPinnedMemoryResource()
+        src = pinned_mr.allocate(src_size)
+        dst = copy_batch_device.memory_resource.allocate(dst_size, stream=copy_stream)
+
+        with pytest.raises(ValueError, match="size mismatch at index 0"):
+            copy_batch(copy_stream, [src], [dst])
+
+        src.close(copy_stream)
+        dst.close(copy_stream)
+        copy_stream.sync()
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_options_length_mismatch(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+
+        with pytest.raises(ValueError, match="options length"):
+            copy_batch(copy_stream, srcs, dsts, options=[CopyOptions()] * 3)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_rejects_bad_options_type(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+
+        with pytest.raises(TypeError, match="options must be CopyOptions"):
+            copy_batch(copy_stream, srcs, dsts, options=42)
+
+    @pytest.mark.agent_authored(model="Claude Opus 5")
+    def test_rejects_bad_options_element(self, h2d_bufs, copy_stream):
+        srcs, dsts = h2d_bufs
+        bad = [CopyOptions()] * (len(srcs) - 1) + ["nope"]
+
+        with pytest.raises(TypeError, match="each options element must be CopyOptions"):
+            copy_batch(copy_stream, srcs, dsts, options=bad)
diff --git a/cuda_core/tests/memory/test_copy_single_options.py b/cuda_core/tests/memory/test_copy_single_options.py
new file mode 100644
index 00000000000..c1ce9024291
--- /dev/null
+++ b/cuda_core/tests/memory/test_copy_single_options.py
@@ -0,0 +1,497 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""CopyOptions support for Buffer.copy_to / Buffer.copy_from (issue #2365)."""
+
+import pytest
+from helpers.buffers import compare_equal_buffers, make_scratch_buffer, set_buffer, thread_unsafe_on_windows
+from helpers.copy_batch import assert_managed_holds
+from helpers.memory import create_managed_memory_resource_or_skip
+
+from cuda.core import Device, Host, LegacyPinnedMemoryResource
+from cuda.core._stream import LEGACY_DEFAULT_STREAM, PER_THREAD_DEFAULT_STREAM
+from cuda.core._utils.version import binding_version, driver_version
+from cuda.core.utils import CopyOptions, MemcpyOverlapMode, MemcpySrcAccessOrder
+
+SIZE = 4096
+
+
+def _options_honored():
+    """True when cuMemcpyWithAttributesAsync will actually be used for options.
+
+    Mirrors _with_attributes_available() in _buffer.pyx. CI runs a matrix
+    that includes pre-CUDA-13.2 driver/bindings combinations (see
+    ci/test-matrix.yml), where this is False and the DURING_API_CALL tests
+    below must expect a RuntimeError instead of a successful copy.
+    """
+    return driver_version() >= (13, 2, 0) and binding_version() >= (13, 2, 0)
+
+
+@pytest.fixture
+def single_copy_device(init_cuda):
+    device = Device()
+    device.set_current()
+    return device
+
+
+@pytest.fixture
+def single_copy_stream(single_copy_device):
+    s = single_copy_device.create_stream()
+    yield s
+    s.close()
+
+
+@pytest.fixture
+def pinned_mr():
+    return LegacyPinnedMemoryResource()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_options_none_copy_to_data_correct(single_copy_device, single_copy_stream, pinned_mr):
+    """options=None (default) continues to copy the right bytes."""
+    src = make_scratch_buffer(single_copy_device, 0x55, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+
+    src.copy_to(dst, stream=single_copy_stream)
+    single_copy_stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_options_none_copy_from_data_correct(single_copy_device, single_copy_stream, pinned_mr):
+    """copy_from with options=None copies the right bytes."""
+    src = make_scratch_buffer(single_copy_device, 0xAA, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+
+    dst.copy_from(src, stream=single_copy_stream)
+    single_copy_stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@pytest.mark.parametrize(
+    ("order", "marker"),
+    [
+        (MemcpySrcAccessOrder.STREAM, 0x31),
+        (MemcpySrcAccessOrder.ANY, 0x33),
+    ],
+)
+@thread_unsafe_on_windows
+def test_src_access_order_copy_to(single_copy_device, single_copy_stream, pinned_mr, order, marker):
+    """STREAM and ANY are accepted and never corrupt copy_to.
+
+    Both are satisfied by stream-ordered access at worst, so whether
+    cuMemcpyWithAttributesAsync actually honors the hint (CUDA 13.2+ driver
+    and cuda.bindings) or the call silently falls back to cuMemcpyAsync, the
+    copied bytes must be identical either way. DURING_API_CALL is different
+    (see test_during_api_call_copy_to): its stronger guarantee cannot be
+    silently downgraded, so it is tested separately.
+    """
+    src = make_scratch_buffer(single_copy_device, marker, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=order)
+
+    src.copy_to(dst, stream=single_copy_stream, options=opts)
+    single_copy_stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@pytest.mark.parametrize(
+    ("order", "marker"),
+    [
+        (MemcpySrcAccessOrder.STREAM, 0x41),
+        (MemcpySrcAccessOrder.ANY, 0x43),
+    ],
+)
+@thread_unsafe_on_windows
+def test_src_access_order_copy_from(single_copy_device, single_copy_stream, pinned_mr, order, marker):
+    """STREAM and ANY are accepted and never corrupt copy_from. See
+    test_src_access_order_copy_to for why DURING_API_CALL is tested
+    separately.
+    """
+    src = make_scratch_buffer(single_copy_device, marker, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=order)
+
+    dst.copy_from(src, stream=single_copy_stream, options=opts)
+    single_copy_stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_during_api_call_copy_to(single_copy_device, single_copy_stream, pinned_mr):
+    """DURING_API_CALL is honored on the native (CUDA 13.2+) path.
+
+    On the pre-13.2 fallback it must raise RuntimeError instead of silently
+    downgrading to stream-ordered cuMemcpyAsync, which cannot honor the
+    guarantee that all source reads complete before the call returns (see
+    TestRejectUnsupportedDuringApiCall in test_copy_batch_options.py). CI
+    runs both driver generations (see ci/test-matrix.yml), so this test must
+    handle both outcomes rather than assuming the native path is available.
+    """
+    src = make_scratch_buffer(single_copy_device, 0x32, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.DURING_API_CALL)
+
+    if _options_honored():
+        src.copy_to(dst, stream=single_copy_stream, options=opts)
+        single_copy_stream.sync()
+        assert compare_equal_buffers(src, dst)
+    else:
+        with pytest.raises(RuntimeError, match="DURING_API_CALL"):
+            src.copy_to(dst, stream=single_copy_stream, options=opts)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_during_api_call_copy_from(single_copy_device, single_copy_stream, pinned_mr):
+    """Same as test_during_api_call_copy_to, exercising copy_from instead."""
+    src = make_scratch_buffer(single_copy_device, 0x42, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.DURING_API_CALL)
+
+    if _options_honored():
+        dst.copy_from(src, stream=single_copy_stream, options=opts)
+        single_copy_stream.sync()
+        assert compare_equal_buffers(src, dst)
+    else:
+        with pytest.raises(RuntimeError, match="DURING_API_CALL"):
+            dst.copy_from(src, stream=single_copy_stream, options=opts)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_overlap_mode_copies_correctly(single_copy_device, single_copy_stream, pinned_mr):
+    """The overlap hint is advisory and must not change the bytes copied."""
+    src = make_scratch_buffer(single_copy_device, 0x77, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(overlap_mode=MemcpyOverlapMode.PREFER_OVERLAP_WITH_COMPUTE)
+
+    src.copy_to(dst, stream=single_copy_stream, options=opts)
+    single_copy_stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+def test_legacy_default_stream_token_rejected_with_options(single_copy_device):
+    """LEGACY_DEFAULT_STREAM with options raises TypeError, matching copy_batch.
+
+    cuMemcpyWithAttributesAsync rejects the legacy default-stream token
+    outright with CUDA_ERROR_INVALID_VALUE on every driver version, so
+    copy_to / copy_from surface this before ever calling the driver, just
+    like copy_batch does. options=None is unaffected: it never touches the
+    attributes path, so LEGACY_DEFAULT_STREAM keeps working as it always has.
+    """
+    pinned_mr = LegacyPinnedMemoryResource()
+    src = pinned_mr.allocate(SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+
+    with pytest.raises(TypeError, match="LEGACY_DEFAULT_STREAM"):
+        src.copy_to(dst, stream=LEGACY_DEFAULT_STREAM, options=opts)
+
+    with pytest.raises(TypeError, match="LEGACY_DEFAULT_STREAM"):
+        dst.copy_from(src, stream=LEGACY_DEFAULT_STREAM, options=opts)
+
+    # options=None never reaches the attributes path, so this keeps working.
+    src.copy_to(dst, stream=LEGACY_DEFAULT_STREAM)
+    single_copy_device.sync()
+
+    src.close()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_per_thread_default_stream_token_accepted_with_options(single_copy_device):
+    """PER_THREAD_DEFAULT_STREAM is a real stream to the driver, so options are
+    honored on it just like an explicit stream (subject to the usual CUDA
+    13.2+ attributes gate), unlike LEGACY_DEFAULT_STREAM.
+    """
+    pinned_mr = LegacyPinnedMemoryResource()
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+
+    src = pinned_mr.allocate(SIZE)
+    set_buffer(src, 0x22)
+    dst = pinned_mr.allocate(SIZE)
+    src.copy_to(dst, stream=PER_THREAD_DEFAULT_STREAM, options=opts)
+    single_copy_device.sync()
+    assert compare_equal_buffers(src, dst)
+
+    set_buffer(src, 0x23)
+    dst.copy_from(src, stream=PER_THREAD_DEFAULT_STREAM, options=opts)
+    single_copy_device.sync()
+    assert compare_equal_buffers(src, dst)
+
+    src.close()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_location_hints_do_not_corrupt_copy(single_copy_device, single_copy_stream):
+    """Device and host location hints are accepted and leave the bytes intact.
+
+    Hints are only honored by the driver for managed memory; for other
+    allocation types they are silently ignored. This exercises the
+    src_location_hint / dst_location_hint → to_cumemlocation path through
+    cuMemcpyWithAttributesAsync rather than cuMemcpyBatchAsync.
+    """
+    dev = single_copy_device
+    mr = create_managed_memory_resource_or_skip()
+    src = mr.allocate(SIZE, stream=single_copy_stream)
+    dst = mr.allocate(SIZE, stream=single_copy_stream)
+
+    src.fill(0x88, stream=single_copy_stream)
+
+    opts = CopyOptions(
+        src_access_order=MemcpySrcAccessOrder.STREAM,
+        src_location_hint=dev,
+        dst_location_hint=Host(),
+    )
+    src.copy_to(dst, stream=single_copy_stream, options=opts)
+
+    assert_managed_holds(dev, dst, 0x88, stream=single_copy_stream)
+
+    src.close(single_copy_stream)
+    dst.close(single_copy_stream)
+    single_copy_stream.sync()
+    mr.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_host_numa_location_hint(single_copy_device, single_copy_stream):
+    """A NUMA-specific host hint is accepted and does not corrupt the copy."""
+    dev = single_copy_device
+    numa_id = dev.properties.host_numa_id
+    if numa_id < 0:
+        pytest.skip("System does not report a host NUMA node for this device")
+    mr = create_managed_memory_resource_or_skip()
+    src = mr.allocate(SIZE, stream=single_copy_stream)
+    dst = mr.allocate(SIZE, stream=single_copy_stream)
+
+    src.fill(0x99, stream=single_copy_stream)
+
+    opts = CopyOptions(dst_location_hint=Host(numa_id=numa_id))
+    src.copy_to(dst, stream=single_copy_stream, options=opts)
+
+    assert_managed_holds(dev, dst, 0x99, stream=single_copy_stream)
+
+    src.close(single_copy_stream)
+    dst.close(single_copy_stream)
+    single_copy_stream.sync()
+    mr.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_host_numa_current_location_hint(single_copy_device, single_copy_stream):
+    """Host.numa_current() as a location hint is accepted and does not corrupt the copy."""
+    dev = single_copy_device
+    if dev.properties.host_numa_id < 0:
+        pytest.skip("System does not report a host NUMA node for this device")
+    mr = create_managed_memory_resource_or_skip()
+    src = mr.allocate(SIZE, stream=single_copy_stream)
+    dst = mr.allocate(SIZE, stream=single_copy_stream)
+
+    src.fill(0xAB, stream=single_copy_stream)
+
+    opts = CopyOptions(dst_location_hint=Host.numa_current())
+    src.copy_to(dst, stream=single_copy_stream, options=opts)
+
+    assert_managed_holds(dev, dst, 0xAB, stream=single_copy_stream)
+
+    src.close(single_copy_stream)
+    dst.close(single_copy_stream)
+    single_copy_stream.sync()
+    mr.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_options_copy_to_data_correct(single_copy_device, single_copy_stream, pinned_mr):
+    """copy_to with non-None options copies the right bytes on all driver versions."""
+    src = make_scratch_buffer(single_copy_device, 0x77, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+
+    src.copy_to(dst, stream=single_copy_stream, options=opts)
+    single_copy_stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_options_copy_from_data_correct(single_copy_device, single_copy_stream, pinned_mr):
+    """copy_from with non-None options copies the right bytes on all driver versions."""
+    src = make_scratch_buffer(single_copy_device, 0x33, SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM)
+
+    dst.copy_from(src, stream=single_copy_stream, options=opts)
+    single_copy_stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close(single_copy_stream)
+    single_copy_stream.sync()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+def test_options_copy_to_rejected_under_graph_capture(single_copy_device, pinned_mr):
+    """copy_to with options raises TypeError when the stream is capturing,
+    matching copy_batch. Use GraphNode.memcpy to build attributed copies
+    into a graph instead; options=None keeps working under capture as it
+    always has (captured as a plain cuMemcpyAsync node).
+    """
+    src = pinned_mr.allocate(SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+    stream = single_copy_device.create_stream()
+
+    gb = stream.create_graph_builder().begin_building()
+    try:
+        with pytest.raises(TypeError, match="graph capture"):
+            src.copy_to(dst, stream=gb, options=opts)
+    finally:
+        gb.end_building()
+        gb.close()
+        stream.close()
+
+    src.close()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+def test_options_copy_from_rejected_under_graph_capture(single_copy_device, pinned_mr):
+    """Same as the copy_to variant, exercising copy_from instead."""
+    src = pinned_mr.allocate(SIZE)
+    dst = pinned_mr.allocate(SIZE)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.STREAM)
+    stream = single_copy_device.create_stream()
+
+    gb = stream.create_graph_builder().begin_building()
+    try:
+        with pytest.raises(TypeError, match="graph capture"):
+            dst.copy_from(src, stream=gb, options=opts)
+    finally:
+        gb.end_building()
+        gb.close()
+        stream.close()
+
+    src.close()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_options_none_copy_to_still_works_under_graph_capture(single_copy_device, pinned_mr):
+    """options=None never touches the attributes path, so copy_to keeps
+    working under graph capture exactly as it did before options existed.
+    """
+    src = pinned_mr.allocate(SIZE)
+    set_buffer(src, 0xBB)
+    dst = pinned_mr.allocate(SIZE)
+    stream = single_copy_device.create_stream()
+
+    gb = stream.create_graph_builder().begin_building()
+    src.copy_to(dst, stream=gb)
+    graph = gb.end_building().complete()
+    graph.launch(stream)
+    stream.sync()
+
+    assert compare_equal_buffers(src, dst)
+
+    src.close()
+    dst.close()
+    stream.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 5")
+@pytest.mark.parametrize("bad_options", [42, "not-copyoptions", object()])
+def test_copy_to_rejects_invalid_options_type(single_copy_stream, pinned_mr, bad_options):
+    src = pinned_mr.allocate(SIZE)
+    dst = pinned_mr.allocate(SIZE)
+
+    with pytest.raises(TypeError, match="options must be CopyOptions"):
+        src.copy_to(dst, stream=single_copy_stream, options=bad_options)
+
+    with pytest.raises(TypeError, match="options must be CopyOptions"):
+        dst.copy_from(src, stream=single_copy_stream, options=bad_options)
+
+    with pytest.raises(TypeError, match="options must be CopyOptions"):
+        src.copy_to(dst, stream=LEGACY_DEFAULT_STREAM, options="not-copyoptions")
+
+    src.close()
+    dst.close()
+
+
+@pytest.mark.agent_authored(model="Claude Sonnet 4.6")
+@thread_unsafe_on_windows
+def test_dst_none_with_options(single_copy_device, single_copy_stream, pinned_mr):
+    """dst=None auto-allocation works correctly with options on all driver versions."""
+    mr = single_copy_device.memory_resource
+    src = mr.allocate(SIZE, stream=single_copy_stream)
+    src.fill(0xF0, stream=single_copy_stream)
+    opts = CopyOptions(src_access_order=MemcpySrcAccessOrder.ANY)
+
+    dst = src.copy_to(stream=single_copy_stream, options=opts)
+
+    # Read back via pinned buffer to verify bytes.
+    host = pinned_mr.allocate(SIZE)
+    dst.copy_to(host, stream=single_copy_stream)
+    single_copy_stream.sync()
+
+    ref = make_scratch_buffer(single_copy_device, 0xF0, SIZE)
+    assert compare_equal_buffers(ref, host)
+
+    src.close(single_copy_stream)
+    dst.close(single_copy_stream)
+    single_copy_stream.sync()
+    host.close()
+    ref.close(single_copy_stream)
+    single_copy_stream.sync()
diff --git a/cuda_core/tests/memory/test_managed_ops.py b/cuda_core/tests/memory/test_managed_ops.py
index 33def77935f..7b51b85dd2b 100644
--- a/cuda_core/tests/memory/test_managed_ops.py
+++ b/cuda_core/tests/memory/test_managed_ops.py
@@ -5,8 +5,8 @@
 
 import pytest
 from helpers.buffers import DummyDeviceMemoryResource, DummyUnifiedMemoryResource
+from helpers.memory import create_managed_memory_resource_or_skip
 
-from conftest import create_managed_memory_resource_or_skip
 from cuda.bindings import driver
 from cuda.core import Device, Host, ManagedBuffer
 from cuda.core._memory._managed_buffer import _get_int_attr
@@ -37,9 +37,10 @@ def _page_base(buf):
 
 
 def _skip_if_raw_managed_alloc_unsupported(device):
-    # Raw `cuMemAllocManaged` capability — distinct from conftest's
-    # `skip_if_managed_memory_unsupported`, which gates `ManagedMemoryResource`
-    # pool creation. Used by tests that exercise `DummyUnifiedMemoryResource`.
+    # Raw `cuMemAllocManaged` capability — distinct from
+    # `helpers.memory.skip_if_managed_memory_unsupported`, which gates
+    # `ManagedMemoryResource` pool creation. Used by tests that exercise
+    # `DummyUnifiedMemoryResource`.
     try:
         if not device.properties.managed_memory:
             pytest.skip("Device does not support managed memory operations")
@@ -104,6 +105,7 @@ def managed_buffer(request, location_ops_device, location_ops_mr):
     size = _MANAGED_TEST_ALLOCATION_SIZE
     if request.param == "pool":
         buf = location_ops_mr.allocate(size, stream=location_ops_device.default_stream)
+        location_ops_device.default_stream.sync()
         yield buf
         buf.close()
     else:
@@ -215,8 +217,8 @@ def test_same_location(self, location_ops_device, location_ops_mr):
         from cuda.core.utils import prefetch_batch
 
         device = location_ops_device
-        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=device.default_stream) for _ in range(3)]
         stream = device.create_stream()
+        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=stream) for _ in range(3)]
 
         prefetch_batch(stream, bufs, device)
         stream.sync()
@@ -230,12 +232,12 @@ def test_per_buffer_location(self, location_ops_device, location_ops_mr):
         from cuda.core.utils import prefetch_batch
 
         device = location_ops_device
-        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=device.default_stream) for _ in range(2)]
+        stream = device.create_stream()
+        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=stream) for _ in range(2)]
         # Per-buffer prefetch locations are only observable when the buffers sit
         # on distinct physical pages; assert that here so a pool-packing change
         # fails loudly instead of silently migrating one shared page.
         assert _page_base(bufs[0]) != _page_base(bufs[1])
-        stream = device.create_stream()
 
         prefetch_batch(stream, bufs, [Host(), device])
         stream.sync()
@@ -257,8 +259,8 @@ def test_basic(self, location_ops_device, location_ops_mr):
         if not hasattr(driver, "cuMemDiscardBatchAsync"):
             pytest.skip("cuMemDiscardBatchAsync unavailable")
         device = location_ops_device
-        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=device.default_stream) for _ in range(3)]
         stream = device.create_stream()
+        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=stream) for _ in range(3)]
         prefetch_batch(stream, bufs, device)
         stream.sync()
         discard_batch(stream, bufs)
@@ -276,8 +278,8 @@ def test_same_location(self, location_ops_device, location_ops_mr):
         if not hasattr(driver, "cuMemDiscardAndPrefetchBatchAsync"):
             pytest.skip("cuMemDiscardAndPrefetchBatchAsync unavailable")
         device = location_ops_device
-        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=device.default_stream) for _ in range(2)]
         stream = device.create_stream()
+        bufs = [location_ops_mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=stream) for _ in range(2)]
         prefetch_batch(stream, bufs, Host())
         stream.sync()
         discard_prefetch_batch(stream, bufs, device)
@@ -364,6 +366,7 @@ def test_from_handle(self, init_cuda):
         finally:
             plain.close()
 
+    @pytest.mark.thread_unsafe(reason="external_managed_buffer is shared between threads")
     def test_read_mostly_roundtrip(self, external_managed_buffer):
         buf = external_managed_buffer
         assert buf.read_mostly is False
@@ -372,6 +375,7 @@ def test_read_mostly_roundtrip(self, external_managed_buffer):
         buf.read_mostly = False
         assert buf.read_mostly is False
 
+    @pytest.mark.thread_unsafe(reason="external_managed_buffer is shared between threads")
     def test_preferred_location_roundtrip(self, location_ops_device, external_managed_buffer):
         device = location_ops_device
         buf = external_managed_buffer
@@ -386,6 +390,7 @@ def test_preferred_location_roundtrip(self, location_ops_device, external_manage
         buf.preferred_location = None
         assert buf.preferred_location is None
 
+    @pytest.mark.thread_unsafe(reason="external_managed_buffer is shared between threads")
     def test_preferred_location_roundtrip_host_numa(self, location_ops_device):
         """Host(numa_id=N) round-trips correctly on CUDA 13 builds."""
         from cuda.core._utils.version import binding_version
@@ -406,6 +411,7 @@ def test_preferred_location_roundtrip_host_numa(self, location_ops_device):
         finally:
             plain.close()
 
+    @pytest.mark.thread_unsafe(reason="external_managed_buffer is shared between threads")
     def test_accessed_by_add_discard(self, location_ops_device, external_managed_buffer):
         device = location_ops_device
         buf = external_managed_buffer
@@ -417,6 +423,7 @@ def test_accessed_by_add_discard(self, location_ops_device, external_managed_buf
         buf.accessed_by.discard(device)
         assert device not in buf.accessed_by
 
+    @pytest.mark.thread_unsafe(reason="external_managed_buffer is shared between threads")
     def test_accessed_by_mutable_set_interface(self, location_ops_device, external_managed_buffer):
         """Full MutableSet conformance pass on AccessedBySetProxy.
 
@@ -436,6 +443,7 @@ def test_accessed_by_mutable_set_interface(self, location_ops_device, external_m
             non_member=Host(numa_id=0),
         )
 
+    @pytest.mark.thread_unsafe(reason="external_managed_buffer is shared between threads")
     def test_accessed_by_set_assignment(self, location_ops_device, external_managed_buffer):
         device = location_ops_device
         buf = external_managed_buffer
@@ -486,9 +494,9 @@ def test_instance_discard(self, location_ops_device, managed_buffer):
     def test_instance_discard_prefetch(self, discard_prefetch_device):
         device = discard_prefetch_device
         mr = create_managed_memory_resource_or_skip()
-        buf = mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=device.default_stream)
+        stream = device.create_stream()
+        buf = mr.allocate(_MANAGED_TEST_ALLOCATION_SIZE, stream=stream)
         try:
-            stream = device.create_stream()
             buf.prefetch(Host(), stream=stream)
             stream.sync()
             buf.discard_prefetch(device, stream=stream)
diff --git a/cuda_core/tests/memory_ipc/__init__.py b/cuda_core/tests/memory_ipc/__init__.py
deleted file mode 100644
index 27422b3cb7e..00000000000
--- a/cuda_core/tests/memory_ipc/__init__.py
+++ /dev/null
@@ -1,3 +0,0 @@
-# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
diff --git a/cuda_core/tests/memory_ipc/test_errors.py b/cuda_core/tests/memory_ipc/test_errors.py
index 40cbcc2826b..bad923e995e 100644
--- a/cuda_core/tests/memory_ipc/test_errors.py
+++ b/cuda_core/tests/memory_ipc/test_errors.py
@@ -2,19 +2,28 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import multiprocessing
+import os
 import pickle
+import platform
 import re
+import uuid
 
 import pytest
 from helpers.child_processes import child_timeout_sec, kill_subprocesses
-
-from cuda.core import Buffer, Device, DeviceMemoryResource, DeviceMemoryResourceOptions
-from cuda.core._memory import IPCBufferDescriptor
+from helpers.constants import POOL_SIZE
+
+from cuda.core import (
+    Buffer,
+    Device,
+    DeviceMemoryResource,
+    DeviceMemoryResourceOptions,
+    PinnedMemoryResource,
+)
+from cuda.core._memory._ipc import IPCAllocationHandle, IPCBufferDescriptor
 from cuda.core._utils.cuda_utils import CUDAError
 
 CHILD_TIMEOUT_SEC = child_timeout_sec()
 NBYTES = 64
-POOL_SIZE = 2097152
 
 
 # these tests spawn new processes and files which fails for very many threads
@@ -36,6 +45,15 @@ def test_outer_timeout_marker_is_applied(request):
     assert marker.args == (expected,), f"unexpected timeout value: {marker.args!r}"
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_ipc_types_cannot_be_constructed_directly():
+    """Factory-only IPC types reject direct construction."""
+    with pytest.raises(RuntimeError, match=r"^IPCBufferDescriptor objects cannot be instantiated directly\."):
+        IPCBufferDescriptor()
+    with pytest.raises(RuntimeError, match=r"^IPCAllocationHandle objects cannot be instantiated directly\."):
+        IPCAllocationHandle()
+
+
 def test_import_truncated_buffer_descriptor(ipc_device, ipc_memory_resource):
     """Truncated IPC buffer descriptor payload is rejected before driver import."""
     desc = IPCBufferDescriptor._init(b"\x00" * 8, NBYTES)
@@ -45,16 +63,67 @@ def test_import_truncated_buffer_descriptor(ipc_device, ipc_memory_resource):
 
 def test_ipc_allocation_handle_rejects_negative_fd():
     """Negative fds are rejected even when CPython runs with -O (Glasswing V3.2)."""
-    from cuda.core._memory._ipc import IPCAllocationHandle
-
     with pytest.raises(ValueError, match=r"Invalid allocation handle \(fd\) -1: must be non-negative"):
         IPCAllocationHandle._init(-1, None)
 
 
+@pytest.mark.human_authored
+def test_register_rejects_non_ipc_memory_resource(mempool_device):
+    """register() on a resource without IPC enabled raises instead of dereferencing None."""
+    mr = DeviceMemoryResource(mempool_device)
+    assert not mr.is_ipc_enabled
+
+    key = uuid.uuid4()
+    with pytest.raises(RuntimeError, match="Memory resource is not IPC-enabled"):
+        mr.register(key)
+
+    # The rejected registration must not leave the resource in the registry.
+    with pytest.raises(RuntimeError, match=r"Memory resource [a-z0-9-]+ was not found"):
+        DeviceMemoryResource.from_registry(key)
+
+
+@pytest.mark.skipif(os.name == "nt", reason="IPC allocation handles are not supported on Windows")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_ipc_allocation_handle_state_tracks_close():
+    read_fd, write_fd = os.pipe()
+    handle = IPCAllocationHandle._init(read_fd, None)
+    try:
+        assert not handle.is_closed
+        handle.close()
+        assert handle.is_closed
+        assert bool(handle) is True  # Preserve backward-compatible truthiness after close.
+        with pytest.raises(ValueError, match="is closed"):
+            int(handle)
+    finally:
+        handle.close()
+        os.close(write_fd)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_ipc_allocation_handle_rejected_before_registry_hit(ipc_device, ipc_memory_resource):
+    mr = ipc_memory_resource
+    handle = IPCAllocationHandle._init(os.dup(int(mr.allocation_handle)), mr.uuid)
+    assert mr.register(mr.uuid) is mr
+    handle.close()
+
+    with pytest.raises(RuntimeError, match="IPCAllocationHandle has been closed"):
+        if isinstance(mr, DeviceMemoryResource):
+            DeviceMemoryResource.from_allocation_handle(ipc_device, handle)
+        else:
+            assert isinstance(mr, PinnedMemoryResource)
+            PinnedMemoryResource.from_allocation_handle(handle)
+
+
 class ChildErrorHarness:
     """Test harness for checking errors in child processes. Subclasses override
     PARENT_ACTION, CHILD_ACTION, and ASSERT (see below for examples)."""
 
+    @pytest.mark.thread_unsafe(
+        reason=(
+            "pytest-run-parallel reuses the same instance and ipc fixtures across "
+            "workers; Process(target=self.child_main) pickles that shared state (#2784)"
+        )
+    )
     @pytest.mark.flaky(reruns=2)
     def test_main(self, ipc_device, ipc_memory_resource):
         """Parent process that checks child errors."""
@@ -104,9 +173,11 @@ class TestImportOversizedBufferDescriptorSize(ChildErrorHarness):
     """Reject peer-supplied sizes larger than the mapped allocation extent."""
 
     def PARENT_ACTION(self, queue):
-        self.buffer = self.mr.allocate(NBYTES, stream=self.device.default_stream)
+        stream = self.device.default_stream
+        self.buffer = self.mr.allocate(NBYTES, stream=stream)
         payload, _ = self.buffer.ipc_descriptor.__reduce__()[1]
         oversized = IPCBufferDescriptor._init(payload, NBYTES * 100)
+        stream.sync()
         queue.put(oversized)
 
     def CHILD_ACTION(self, queue):
@@ -141,8 +212,10 @@ def PARENT_ACTION(self, queue):
         options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
         mr2 = DeviceMemoryResource(self.device, options=options)
         self._extra_mrs.append(mr2)
-        buffer = mr2.allocate(NBYTES, stream=self.device.default_stream)
-        queue.put([self.mr, buffer.ipc_descriptor])  # Note: mr does not own this buffer
+        stream = self.device.default_stream
+        self.buffer = mr2.allocate(NBYTES, stream=stream)
+        stream.sync()
+        queue.put([self.mr, self.buffer.ipc_descriptor])  # Note: mr does not own this buffer
 
     def CHILD_ACTION(self, queue):
         mr, buffer_desc = queue.get(timeout=CHILD_TIMEOUT_SEC)
@@ -159,7 +232,9 @@ class TestImportBuffer(ChildErrorHarness):
     def PARENT_ACTION(self, queue):
         # Note: if the buffer is not attached to something to prolong its life,
         # CUDA_ERROR_INVALID_CONTEXT is raised from Buffer.__del__
-        self.buffer = self.mr.allocate(NBYTES, stream=self.device.default_stream)
+        stream = self.device.default_stream
+        self.buffer = self.mr.allocate(NBYTES, stream=stream)
+        stream.sync()
         queue.put(self.buffer)
 
     def CHILD_ACTION(self, queue):
@@ -181,8 +256,10 @@ def PARENT_ACTION(self, queue):
         options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
         mr2 = DeviceMemoryResource(self.device, options=options)
         self._extra_mrs.append(mr2)
-        self.buffer = mr2.allocate(NBYTES, stream=self.device.default_stream)
+        stream = self.device.default_stream
+        self.buffer = mr2.allocate(NBYTES, stream=stream)
         buffer_s = pickle.dumps(self.buffer)
+        stream.sync()
         queue.put(buffer_s)  # Note: mr2 not sent
 
     def CHILD_ACTION(self, queue):
@@ -193,3 +270,96 @@ def CHILD_ACTION(self, queue):
     def ASSERT(self, exc_type, exc_msg):
         assert exc_type is RuntimeError
         assert re.match(r"Memory resource [a-z0-9-]+ was not found", exc_msg)
+
+
+@pytest.mark.skipif(platform.system() != "Linux", reason="CUDA mempool IPC is Linux-only")
+@pytest.mark.thread_unsafe(
+    reason="serialize the affected IPC mempool import/destroy path under pytest-run-parallel (#2784)"
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_from_allocation_handle_raw_fd_imports_mapped_pool(ipc_device):
+    """from_allocation_handle accepts a raw int fd and constructs an unregistered mapped MR."""
+    from helpers.buffers import PatternGen
+
+    device = ipc_device
+    stream = device.default_stream
+    exporter = DeviceMemoryResource(device, DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True))
+    try:
+        dup_fd = os.dup(exporter.allocation_handle.handle)
+        try:
+            imported = DeviceMemoryResource.from_allocation_handle(device, dup_fd)
+        finally:
+            # The int overload dups the fd internally, so the imported pool must
+            # outlive the caller's copy: everything below runs without it.
+            os.close(dup_fd)
+        try:
+            assert imported.is_mapped
+            assert imported.is_ipc_enabled
+            assert imported.device_id == device.device_id
+            # No uuid was supplied, so the pool never entered the registry.
+            assert imported.uuid is None
+            # Mapped pools cannot allocate; import a peer buffer instead.
+            with exporter.allocate(NBYTES, stream=stream) as exported:
+                descriptor = exported.ipc_descriptor
+                with Buffer.from_ipc_descriptor(imported, descriptor, stream=stream) as mapped_buf:
+                    pgen = PatternGen(device, NBYTES, stream=stream)
+                    pgen.fill_buffer(mapped_buf, seed=1)
+                    pgen.verify_buffer(exported, seed=1)
+        finally:
+            imported.close()
+    finally:
+        exporter.close()
+
+
+@pytest.mark.skipif(platform.system() != "Linux", reason="CUDA mempool IPC is Linux-only")
+@pytest.mark.thread_unsafe(
+    reason="concurrent IPC mempool export/destroy SEGV in cuMemPoolDestroy under pytest-run-parallel (#2784)"
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_allocation_handle_forking_pickler_roundtrip(ipc_device):
+    """ForkingPickler transfers an IPCAllocationHandle by duplicating its fd."""
+    from multiprocessing.reduction import ForkingPickler
+
+    device = ipc_device
+    mr = DeviceMemoryResource(device, DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True))
+    try:
+        handle = mr.allocation_handle
+        restored = ForkingPickler.loads(ForkingPickler.dumps(handle))
+        try:
+            assert isinstance(restored, IPCAllocationHandle)
+            # DupFd must hand back a real duplicate: a shared fd number would mean
+            # restored.close() also clobbers the exporter's handle. The number
+            # itself is unpredictable, so only check validity and distinctness.
+            assert restored.handle > 0
+            assert restored.handle != handle.handle
+            assert restored.uuid == handle.uuid
+        finally:
+            restored.close()
+    finally:
+        mr.close()
+
+
+@pytest.mark.skipif(platform.system() != "Linux", reason="CUDA mempool IPC is Linux-only")
+@pytest.mark.thread_unsafe(
+    reason="concurrent IPC mempool import/destroy SEGV in cuMemPoolDestroy under pytest-run-parallel (#2784)"
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_ipc_registry_dedups_repeated_imports(ipc_device):
+    """from_allocation_handle registers the mapped pool; later imports hit the cache."""
+    device = ipc_device
+    exporter = DeviceMemoryResource(device, DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True))
+    mapped = None
+    try:
+        key = exporter.uuid
+        mapped = DeviceMemoryResource.from_allocation_handle(device, exporter.allocation_handle)
+        assert mapped.is_mapped
+        assert DeviceMemoryResource.from_registry(key) is mapped
+        mapped2 = DeviceMemoryResource.from_allocation_handle(device, exporter.allocation_handle)
+        assert mapped2 is mapped
+        # Registering under a key that is already taken hands back the existing
+        # entry, so the exporter itself never enters the registry.
+        assert exporter.register(key) is mapped
+    finally:
+        if mapped is not None:
+            mapped.close()
+        exporter.close()
diff --git a/cuda_core/tests/memory_ipc/test_event_ipc.py b/cuda_core/tests/memory_ipc/test_event_ipc.py
index e3cefe6a211..7608b9c8794 100644
--- a/cuda_core/tests/memory_ipc/test_event_ipc.py
+++ b/cuda_core/tests/memory_ipc/test_event_ipc.py
@@ -108,10 +108,10 @@ def test_event_is_monadic(ipc_device):
     """Check that IPC-enabled events are always bound and cannot be reset."""
     device = ipc_device
     with pytest.raises(TypeError, match=r"^IPC-enabled events must be bound; use Stream.record for creation\.$"):
-        device.create_event({"ipc_enabled": True})
+        device.create_event(EventOptions(ipc_enabled=True))
 
     stream = device.create_stream()
-    e = stream.record(options={"ipc_enabled": True})
+    e = stream.record(options=EventOptions(ipc_enabled=True))
     with pytest.raises(
         TypeError,
         match=r"^IPC-enabled events should not be re-recorded, instead create a new event by supplying options\.$",
diff --git a/cuda_core/tests/memory_ipc/test_ipc_duplicate_import.py b/cuda_core/tests/memory_ipc/test_ipc_duplicate_import.py
index eaa6ddec92f..771f26a3399 100644
--- a/cuda_core/tests/memory_ipc/test_ipc_duplicate_import.py
+++ b/cuda_core/tests/memory_ipc/test_ipc_duplicate_import.py
@@ -20,7 +20,6 @@
 
 CHILD_TIMEOUT_SEC = child_timeout_sec()
 NBYTES = 64
-POOL_SIZE = 2097152
 
 ENABLE_LOGGING = False  # Set True for test debugging and development
 
@@ -72,7 +71,9 @@ def test_main(self, ipc_device, ipc_memory_resource):
         mr = ipc_memory_resource
 
         log("allocating buffer")
-        buffer = mr.allocate(NBYTES, stream=ipc_device.default_stream)
+        stream = ipc_device.default_stream
+        buffer = mr.allocate(NBYTES, stream=stream)
+        stream.sync()
 
         # Start the child process.
         log("starting child")
diff --git a/cuda_core/tests/memory_ipc/test_leaks.py b/cuda_core/tests/memory_ipc/test_leaks.py
index c6e44824137..bca7948737c 100644
--- a/cuda_core/tests/memory_ipc/test_leaks.py
+++ b/cuda_core/tests/memory_ipc/test_leaks.py
@@ -102,8 +102,10 @@ def __reduce__(self):
 def test_pass_object(ipc_device, ipc_memory_resource, launcher, getobject):
     """Check for fd leaks when an object is sent as a subprocess argument."""
     mr = ipc_memory_resource
+    stream = ipc_device.default_stream
     with CheckFDLeaks():
-        obj = getobject(mr, ipc_device.default_stream)
+        obj = getobject(mr, stream)
+        stream.sync()
         try:
             launcher(obj, number=2)
         finally:
diff --git a/cuda_core/tests/memory_ipc/test_memory_ipc.py b/cuda_core/tests/memory_ipc/test_memory_ipc.py
index 43d356789e7..0eace7f154c 100644
--- a/cuda_core/tests/memory_ipc/test_memory_ipc.py
+++ b/cuda_core/tests/memory_ipc/test_memory_ipc.py
@@ -26,7 +26,8 @@ def test_main(self, ipc_device, ipc_memory_resource):
         device = ipc_device
         mr = ipc_memory_resource
         assert not mr.is_mapped
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
 
         # Start the child process.
         queue = mp.Queue()
@@ -34,9 +35,10 @@ def test_main(self, ipc_device, ipc_memory_resource):
         process.start()
 
         # Allocate and fill memory.
-        buffer = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer = mr.allocate(NBYTES, stream=stream)
         assert not buffer.is_mapped
         pgen.fill_buffer(buffer, seed=False)
+        stream.sync()
 
         # Export the buffer via IPC.
         queue.put(buffer)
@@ -50,16 +52,19 @@ def test_main(self, ipc_device, ipc_memory_resource):
         # Verify that the buffer was modified.
         pgen.verify_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
 
     def child_main(self, device, mr, queue):
         device.set_current()
         assert mr.is_mapped
         buffer = queue.get(timeout=CHILD_TIMEOUT_SEC)
         assert buffer.is_mapped
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.verify_buffer(buffer, seed=False)
         pgen.fill_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
 
 
 class TestIPCMempoolMultiple:
@@ -70,14 +75,16 @@ def test_main(self, ipc_device, ipc_memory_resource):
         device = ipc_device
         mr = ipc_memory_resource
         q1, q2 = (mp.Queue() for _ in range(2))
+        stream = device.default_stream
 
         # Allocate memory buffers and export them to each child.
-        buffer1 = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer1 = mr.allocate(NBYTES, stream=stream)
         q1.put(buffer1)
         q2.put(buffer1)
-        buffer2 = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer2 = mr.allocate(NBYTES, stream=stream)
         q1.put(buffer2)
         q2.put(buffer2)
+        stream.sync()
 
         # Start the child processes.
         p1 = mp.Process(target=self.child_main, args=(device, mr, 1, q1))
@@ -94,11 +101,12 @@ def test_main(self, ipc_device, ipc_memory_resource):
         assert p2.exitcode == 0
 
         # Verify that the buffers were modified.
-        pgen = PatternGen(device, NBYTES)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.verify_buffer(buffer1, seed=1)
         pgen.verify_buffer(buffer2, seed=2)
         buffer1.close()
         buffer2.close()
+        stream.sync()
 
     def child_main(self, device, mr, seed, queue):
         # Note: passing the mr registers it so that buffers can be passed
@@ -106,13 +114,15 @@ def child_main(self, device, mr, seed, queue):
         device.set_current()
         buffer1 = queue.get(timeout=CHILD_TIMEOUT_SEC)
         buffer2 = queue.get(timeout=CHILD_TIMEOUT_SEC)
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         if seed == 1:
             pgen.fill_buffer(buffer1, seed=1)
         elif seed == 2:
             pgen.fill_buffer(buffer2, seed=2)
         buffer1.close()
         buffer2.close()
+        stream.sync()
 
 
 class TestIPCSharedAllocationHandleAndBufferDescriptors:
@@ -126,6 +136,7 @@ def test_main(self, ipc_device, ipc_memory_resource):
         device = ipc_device
         mr = ipc_memory_resource
         alloc_handle = mr.allocation_handle
+        stream = device.default_stream
 
         # Start children.
         q1, q2 = (mp.Queue() for _ in range(2))
@@ -135,8 +146,9 @@ def test_main(self, ipc_device, ipc_memory_resource):
         p2.start()
 
         # Allocate and share memory.
-        buffer1 = mr.allocate(NBYTES, stream=device.default_stream)
-        buffer2 = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer1 = mr.allocate(NBYTES, stream=stream)
+        buffer2 = mr.allocate(NBYTES, stream=stream)
+        stream.sync()
         q1.put(buffer1.ipc_descriptor)
         q2.put(buffer2.ipc_descriptor)
 
@@ -149,11 +161,12 @@ def test_main(self, ipc_device, ipc_memory_resource):
         assert p2.exitcode == 0
 
         # Verify results.
-        pgen = PatternGen(device, NBYTES)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.verify_buffer(buffer1, seed=False)
         pgen.verify_buffer(buffer2, seed=True)
         buffer1.close()
         buffer2.close()
+        stream.sync()
 
     def child_main(self, device, alloc_handle, seed, queue):
         """Fills a shared memory buffer."""
@@ -162,10 +175,12 @@ def child_main(self, device, alloc_handle, seed, queue):
         device.set_current()
         mr = DeviceMemoryResource.from_allocation_handle(device, alloc_handle)
         buffer_descriptor = queue.get(timeout=CHILD_TIMEOUT_SEC)
-        buffer = Buffer.from_ipc_descriptor(mr, buffer_descriptor, stream=device.default_stream)
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        buffer = Buffer.from_ipc_descriptor(mr, buffer_descriptor, stream=stream)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=seed)
         buffer.close()
+        stream.sync()
 
 
 class TestIPCSharedAllocationHandleAndBufferObjects:
@@ -178,6 +193,7 @@ def test_main(self, ipc_device, ipc_memory_resource):
         device = ipc_device
         mr = ipc_memory_resource
         alloc_handle = mr.allocation_handle
+        stream = device.default_stream
 
         # Start children.
         q1, q2 = (mp.Queue() for _ in range(2))
@@ -187,8 +203,9 @@ def test_main(self, ipc_device, ipc_memory_resource):
         p2.start()
 
         # Allocate and share memory.
-        buffer1 = mr.allocate(NBYTES, stream=device.default_stream)
-        buffer2 = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer1 = mr.allocate(NBYTES, stream=stream)
+        buffer2 = mr.allocate(NBYTES, stream=stream)
+        stream.sync()
         q1.put(buffer1)
         q2.put(buffer2)
 
@@ -201,11 +218,12 @@ def test_main(self, ipc_device, ipc_memory_resource):
         assert p2.exitcode == 0
 
         # Verify results.
-        pgen = PatternGen(device, NBYTES)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.verify_buffer(buffer1, seed=False)
         pgen.verify_buffer(buffer2, seed=True)
         buffer1.close()
         buffer2.close()
+        stream.sync()
 
     def child_main(self, device, alloc_handle, seed, queue):
         """Fills a shared memory buffer."""
@@ -216,6 +234,8 @@ def child_main(self, device, alloc_handle, seed, queue):
 
         # Now get buffers.
         buffer = queue.get(timeout=CHILD_TIMEOUT_SEC)
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=seed)
         buffer.close()
+        stream.sync()
diff --git a/cuda_core/tests/memory_ipc/test_peer_access.py b/cuda_core/tests/memory_ipc/test_peer_access.py
index ac7f71a88e9..a82690d46b5 100644
--- a/cuda_core/tests/memory_ipc/test_peer_access.py
+++ b/cuda_core/tests/memory_ipc/test_peer_access.py
@@ -6,13 +6,13 @@
 import pytest
 from helpers.buffers import PatternGen
 from helpers.child_processes import child_timeout_sec, kill_subprocesses
+from helpers.constants import POOL_SIZE
 
 from cuda.core import Device, DeviceMemoryResource, DeviceMemoryResourceOptions
 from cuda.core._utils.cuda_utils import CUDAError
 
 CHILD_TIMEOUT_SEC = child_timeout_sec()
 NBYTES = 64
-POOL_SIZE = 2097152
 
 # these tests spawn new processes and files which fails for very many threads
 pytestmark = pytest.mark.parallel_threads_limit(4)
@@ -79,9 +79,12 @@ def test_main(self, ipc_mempool_device_x2, grant_access_in_parent):
             assert mr.peer_accessible_by == {dev0}
         else:
             assert mr.peer_accessible_by == set()
-        buffer = mr.allocate(NBYTES, stream=dev1.default_stream)
-        pgen = PatternGen(dev1, NBYTES)
+        stream = dev1.default_stream
+        buffer = mr.allocate(NBYTES, stream=stream)
+        pgen = PatternGen(dev1, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=False)
+        # IPC import does not carry the exporting process's stream ordering.
+        stream.sync()
 
         # Spawn child process
         process = mp.Process(target=self.child_main, args=(mr, buffer))
@@ -93,7 +96,11 @@ def test_main(self, ipc_mempool_device_x2, grant_access_in_parent):
 
         buffer.close()
         # TODO(seberg): 2026-06: mr close may be unsafe with incomplete `buf.close()`
+        # Make dev0 current; Device.sync() must act on dev1 and leave dev0 current.
+        dev0.set_current()
+        assert Device().device_id == dev0.device_id
         dev1.sync()
+        assert Device().device_id == dev0.device_id
         mr.close()
 
     def child_main(self, mr, buffer):
@@ -107,20 +114,22 @@ def child_main(self, mr, buffer):
         # Test 1: Buffer accessible from resident device (dev1) - should always work
         dev1 = Device(1)
         dev1.set_current()
-        PatternGen(dev1, NBYTES).verify_buffer(buffer, seed=False)
+        stream1 = dev1.default_stream
+        PatternGen(dev1, NBYTES, stream=stream1).verify_buffer(buffer, seed=False)
 
         # Test 2: Buffer NOT accessible from dev0 initially (peer access not preserved)
         dev0 = Device(0)
         dev0.set_current()
+        stream0 = dev0.default_stream
         with pytest.raises(CUDAError, match="CUDA_ERROR_INVALID_VALUE"):
-            PatternGen(dev0, NBYTES).verify_buffer(buffer, seed=False)
+            PatternGen(dev0, NBYTES, stream=stream0).verify_buffer(buffer, seed=False)
 
         # Test 3: Set peer access and verify buffer becomes accessible
         dev1.set_current()
         mr.peer_accessible_by = [0]
         assert mr.peer_accessible_by == {dev0}
         dev0.set_current()
-        PatternGen(dev0, NBYTES).verify_buffer(buffer, seed=False)
+        PatternGen(dev0, NBYTES, stream=stream0).verify_buffer(buffer, seed=False)
 
         # Test 4: Revoke peer access and verify buffer becomes inaccessible
         dev1.set_current()
@@ -128,8 +137,9 @@ def child_main(self, mr, buffer):
         assert mr.peer_accessible_by == set()
         dev0.set_current()
         with pytest.raises(CUDAError, match="CUDA_ERROR_INVALID_VALUE"):
-            PatternGen(dev0, NBYTES).verify_buffer(buffer, seed=False)
+            PatternGen(dev0, NBYTES, stream=stream0).verify_buffer(buffer, seed=False)
 
+        dev1.set_current()
         buffer.close()
         # TODO(seberg): 2026-06: mr close may be unsafe with incomplete `buf.close()`
         dev1.sync()
diff --git a/cuda_core/tests/memory_ipc/test_send_buffers.py b/cuda_core/tests/memory_ipc/test_send_buffers.py
index 59216cd9cce..d2a59f1cce6 100644
--- a/cuda_core/tests/memory_ipc/test_send_buffers.py
+++ b/cuda_core/tests/memory_ipc/test_send_buffers.py
@@ -7,6 +7,7 @@
 import pytest
 from helpers.buffers import PatternGen
 from helpers.child_processes import child_timeout_sec, kill_subprocesses
+from helpers.constants import POOL_SIZE
 
 from cuda.core import Device, DeviceMemoryResource, DeviceMemoryResourceOptions
 
@@ -14,7 +15,6 @@
 NBYTES = 64
 NMRS = 3
 NTASKS = 7
-POOL_SIZE = 2097152
 
 # these tests spawn new processes and files which fails for very many threads
 pytestmark = pytest.mark.parallel_threads_limit(4)
@@ -30,13 +30,15 @@ def test_main(self, ipc_device, nmrs):
         options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
         mrs = [DeviceMemoryResource(device, options=options) for _ in range(nmrs)]
         buffers = []
+        stream = device.default_stream
 
         try:
             # Allocate and fill memory.
-            buffers = [mr.allocate(NBYTES, stream=device.default_stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
-            pgen = PatternGen(device, NBYTES)
+            buffers = [mr.allocate(NBYTES, stream=stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
+            pgen = PatternGen(device, NBYTES, stream=stream)
             for buffer in buffers:
                 pgen.fill_buffer(buffer, seed=False)
+            stream.sync()
 
             # Start the child process.
             process = mp.Process(target=self.child_main, args=(device, buffers))
@@ -50,25 +52,26 @@ def test_main(self, ipc_device, nmrs):
             assert process.exitcode == 0
 
             # Verify that the buffers were modified.
-            pgen = PatternGen(device, NBYTES)
+            pgen = PatternGen(device, NBYTES, stream=stream)
             for buffer in buffers:
                 pgen.verify_buffer(buffer, seed=True)
                 buffer.close()
         finally:
             for buffer in buffers:
                 buffer.close()
-            # TODO(seberg): 2026-06: mr close may be unsafe with incomplete `buf.close()`
-            device.sync()
+            stream.sync()
             for mr in mrs:
                 mr.close()
 
     def child_main(self, device, buffers):
         device.set_current()
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         for buffer in buffers:
             pgen.verify_buffer(buffer, seed=False)
             pgen.fill_buffer(buffer, seed=True)
             buffer.close()
+        stream.sync()
 
 
 class TestIpcReexport:
@@ -93,9 +96,11 @@ def test_main(self, ipc_device, ipc_memory_resource):
 
         # Allocate, fill a buffer.
         mr = ipc_memory_resource
-        pgen = PatternGen(device, NBYTES)
-        buffer = mr.allocate(NBYTES, stream=device.default_stream)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
+        buffer = mr.allocate(NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=0)
+        stream.sync()
 
         # Set up communication.
         q_bc = mp.Queue()
@@ -123,18 +128,22 @@ def test_main(self, ipc_device, ipc_memory_resource):
         # Verify that C’s operations are visible.
         pgen.verify_buffer(buffer, seed=1)
         buffer.close()
+        stream.sync()
 
     def process_b_main(self, buffer, q_bc, event_b):
         # Process B: receive buffer from A then forward it to C.
         device = Device()
         device.set_current()
+        stream = device.default_stream
 
         # Forward the buffer to C.
         q_bc.put(buffer)
-        buffer.close()
 
-        # Wait for C to receive before exiting.
+        # Queue serialization runs in a feeder thread. Keep the buffer open
+        # until C has received it and the parent releases this process.
         event_b.wait(timeout=CHILD_TIMEOUT_SEC)
+        buffer.close()
+        stream.sync()
 
     def process_c_main(self, q_bc, event_c):
         # Process C: receive buffer from B then fill it.
@@ -143,9 +152,11 @@ def process_c_main(self, q_bc, event_c):
 
         # Get the buffer and fill it.
         buffer = q_bc.get(timeout=CHILD_TIMEOUT_SEC)
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=1)
         buffer.close()
+        stream.sync()
 
         # Signal A that the work is complete.
         event_c.set()
diff --git a/cuda_core/tests/memory_ipc/test_serialize.py b/cuda_core/tests/memory_ipc/test_serialize.py
index 4289de4b5a9..f2805c31e63 100644
--- a/cuda_core/tests/memory_ipc/test_serialize.py
+++ b/cuda_core/tests/memory_ipc/test_serialize.py
@@ -13,7 +13,6 @@
 
 CHILD_TIMEOUT_SEC = child_timeout_sec()
 NBYTES = 64
-POOL_SIZE = 2097152
 
 # these tests spawn new processes and files which fails for very many threads
 pytestmark = pytest.mark.parallel_threads_limit(4)
@@ -31,6 +30,7 @@ class TestObjectSerializationDirect:
     def test_main(self, ipc_device, ipc_memory_resource):
         device = ipc_device
         mr = ipc_memory_resource
+        stream = device.default_stream
 
         # Start the child process.
         parent_conn, child_conn = mp.Pipe()
@@ -42,10 +42,11 @@ def test_main(self, ipc_device, ipc_memory_resource):
         mp.reduction.send_handle(parent_conn, alloc_handle.handle, process.pid)
 
         # Send a buffer.
-        buffer1 = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer1 = mr.allocate(NBYTES, stream=stream)
         parent_conn.send(buffer1)  # directly
 
-        buffer2 = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer2 = mr.allocate(NBYTES, stream=stream)
+        stream.sync()
         parent_conn.send(buffer2.ipc_descriptor)  # by descriptor
 
         # Wait for the child process.
@@ -55,11 +56,12 @@ def test_main(self, ipc_device, ipc_memory_resource):
         assert process.exitcode == 0
 
         # Confirm buffers were modified.
-        pgen = PatternGen(device, NBYTES)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.verify_buffer(buffer1, seed=True)
         pgen.verify_buffer(buffer2, seed=True)
         buffer1.close()
         buffer2.close()
+        stream.sync()
 
     def child_main(self, conn):
         # Set up the device.
@@ -74,14 +76,16 @@ def child_main(self, conn):
         # Receive the buffers.
         buffer1 = conn.recv()  # directly
         buffer_desc = conn.recv()
-        buffer2 = Buffer.from_ipc_descriptor(mr, buffer_desc, stream=device.default_stream)  # by descriptor
+        stream = device.default_stream
+        buffer2 = Buffer.from_ipc_descriptor(mr, buffer_desc, stream=stream)  # by descriptor
 
         # Modify the buffers.
-        pgen = PatternGen(device, NBYTES)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer1, seed=True)
         pgen.fill_buffer(buffer2, seed=True)
         buffer1.close()
         buffer2.close()
+        stream.sync()
 
 
 class TestObjectSerializationWithMR:
@@ -90,6 +94,7 @@ def test_main(self, ipc_device, ipc_memory_resource):
         """Test sending IPC memory objects to a child through a queue."""
         device = ipc_device
         mr = ipc_memory_resource
+        stream = device.default_stream
 
         # Start the child process. Sending the memory resource registers it so
         # that buffers can be handled automatically.
@@ -104,7 +109,8 @@ def test_main(self, ipc_device, ipc_memory_resource):
         assert uuid == mr.uuid
 
         # Send a buffer.
-        buffer = mr.allocate(NBYTES, stream=device.default_stream)
+        buffer = mr.allocate(NBYTES, stream=stream)
+        stream.sync()
         pipe[0].put(buffer)
 
         # Wait for the child process.
@@ -114,9 +120,10 @@ def test_main(self, ipc_device, ipc_memory_resource):
         assert process.exitcode == 0
 
         # Confirm buffer was modified.
-        pgen = PatternGen(device, NBYTES)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.verify_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
 
     def child_main(self, pipe, _):
         device = Device()
@@ -129,9 +136,11 @@ def child_main(self, pipe, _):
         # Buffer.
         buffer = pipe[0].get(timeout=CHILD_TIMEOUT_SEC)
         assert buffer.memory_resource.handle == mr.handle
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
 
 
 class TestObjectPassing:
@@ -149,11 +158,13 @@ def test_main(self, ipc_device, ipc_memory_resource):
         device = ipc_device
         mr = ipc_memory_resource
         alloc_handle = mr.allocation_handle
-        buffer = mr.allocate(NBYTES, stream=device.default_stream)
+        stream = device.default_stream
+        buffer = mr.allocate(NBYTES, stream=stream)
         buffer_desc = buffer.ipc_descriptor
 
-        pgen = PatternGen(device, NBYTES)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=False)
+        stream.sync()
 
         # Start the child process.
         process = mp.Process(target=self.child_main, args=(alloc_handle, mr, buffer_desc, buffer))
@@ -165,6 +176,7 @@ def test_main(self, ipc_device, ipc_memory_resource):
 
         pgen.verify_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
 
     def child_main(self, alloc_handle, mr1, buffer_desc, buffer):
         device = Device()
@@ -177,7 +189,8 @@ def child_main(self, alloc_handle, mr1, buffer_desc, buffer):
             with pytest.raises(TypeError):
                 PinnedMemoryResource.from_allocation_handle(alloc_handle)
             mr2 = DeviceMemoryResource.from_allocation_handle(device, alloc_handle)
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
 
         # Verify initial content
         pgen.verify_buffer(buffer, seed=False)
@@ -190,3 +203,4 @@ def child_main(self, alloc_handle, mr1, buffer_desc, buffer):
 
         # Clean up - only ONE free
         buffer.close()
+        stream.sync()
diff --git a/cuda_core/tests/memory_ipc/test_workerpool.py b/cuda_core/tests/memory_ipc/test_workerpool.py
index 358c16fd7bf..f2a5fb1d50c 100644
--- a/cuda_core/tests/memory_ipc/test_workerpool.py
+++ b/cuda_core/tests/memory_ipc/test_workerpool.py
@@ -7,6 +7,7 @@
 
 import pytest
 from helpers.buffers import PatternGen
+from helpers.constants import POOL_SIZE
 
 from cuda.core import Buffer, Device, DeviceMemoryResource, DeviceMemoryResourceOptions
 
@@ -14,7 +15,6 @@
 NWORKERS = 2
 NMRS = 3
 NTASKS = 20
-POOL_SIZE = 2097152
 
 # these tests spawn new processes and files which fails for very many threads
 pytestmark = pytest.mark.parallel_threads_limit(4)
@@ -36,30 +36,33 @@ def test_main(self, ipc_device, nmrs):
         options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
         mrs = [DeviceMemoryResource(device, options=options) for _ in range(nmrs)]
         buffers = []
+        stream = device.default_stream
 
         try:
-            buffers = [mr.allocate(NBYTES, stream=device.default_stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
+            buffers = [mr.allocate(NBYTES, stream=stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
+            stream.sync()
 
             with mp.Pool(NWORKERS) as pool:
                 pool.map(self.process_buffer, buffers)
 
-            pgen = PatternGen(device, NBYTES)
+            pgen = PatternGen(device, NBYTES, stream=stream)
             for buffer in buffers:
                 pgen.verify_buffer(buffer, seed=True)
         finally:
             for buffer in buffers:
                 buffer.close()
-            # TODO(seberg): 2026-06: mr close may be unsafe with incomplete `buf.close()`
-            device.sync()
+            stream.sync()
             for mr in mrs:
                 mr.close()
 
     def process_buffer(self, buffer):
         device = Device(buffer.memory_resource.device_id)
         device.set_current()
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
 
 
 class TestIpcWorkerPoolUsingIPCDescriptors:
@@ -82,9 +85,11 @@ def test_main(self, ipc_device, nmrs):
         options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
         mrs = [DeviceMemoryResource(device, options=options) for _ in range(nmrs)]
         buffers = []
+        stream = device.default_stream
 
         try:
-            buffers = [mr.allocate(NBYTES, stream=device.default_stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
+            buffers = [mr.allocate(NBYTES, stream=stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
+            stream.sync()
 
             with mp.Pool(NWORKERS, initializer=self.init_worker, initargs=(mrs,)) as pool:
                 pool.starmap(
@@ -92,14 +97,13 @@ def test_main(self, ipc_device, nmrs):
                     [(mrs.index(buffer.memory_resource), buffer.ipc_descriptor) for buffer in buffers],
                 )
 
-            pgen = PatternGen(device, NBYTES)
+            pgen = PatternGen(device, NBYTES, stream=stream)
             for buffer in buffers:
                 pgen.verify_buffer(buffer, seed=True)
         finally:
             for buffer in buffers:
                 buffer.close()
-            # TODO(seberg): 2026-06: mr close may be unsafe with incomplete `buf.close()`
-            device.sync()
+            stream.sync()
             for mr in mrs:
                 mr.close()
 
@@ -107,10 +111,12 @@ def process_buffer(self, mr_idx, buffer_desc):
         mr = self.mrs[mr_idx]
         device = Device(mr.device_id)
         device.set_current()
-        buffer = Buffer.from_ipc_descriptor(mr, buffer_desc, stream=device.default_stream)
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        buffer = Buffer.from_ipc_descriptor(mr, buffer_desc, stream=stream)
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
 
 
 class TestIpcWorkerPoolUsingRegistry:
@@ -136,27 +142,30 @@ def test_main(self, ipc_device, nmrs):
         options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
         mrs = [DeviceMemoryResource(device, options=options) for _ in range(nmrs)]
         buffers = []
+        stream = device.default_stream
 
         try:
-            buffers = [mr.allocate(NBYTES, stream=device.default_stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
+            buffers = [mr.allocate(NBYTES, stream=stream) for mr, _ in zip(cycle(mrs), range(NTASKS))]
+            stream.sync()
 
             with mp.Pool(NWORKERS, initializer=self.init_worker, initargs=(mrs,)) as pool:
                 pool.starmap(self.process_buffer, [(device, pickle.dumps(buffer)) for buffer in buffers])
 
-            pgen = PatternGen(device, NBYTES)
+            pgen = PatternGen(device, NBYTES, stream=stream)
             for buffer in buffers:
                 pgen.verify_buffer(buffer, seed=True)
         finally:
             for buffer in buffers:
                 buffer.close()
-            # TODO(seberg): 2026-06: mr close may be unsafe with incomplete `buf.close()`
-            device.sync()
+            stream.sync()
             for mr in mrs:
                 mr.close()
 
     def process_buffer(self, device, buffer_s):
         device.set_current()
         buffer = pickle.loads(buffer_s)  # noqa: S301
-        pgen = PatternGen(device, NBYTES)
+        stream = device.default_stream
+        pgen = PatternGen(device, NBYTES, stream=stream)
         pgen.fill_buffer(buffer, seed=True)
         buffer.close()
+        stream.sync()
diff --git a/cuda_core/tests/system/__init__.py b/cuda_core/tests/system/__init__.py
deleted file mode 100644
index 79599c77db0..00000000000
--- a/cuda_core/tests/system/__init__.py
+++ /dev/null
@@ -1,3 +0,0 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
diff --git a/cuda_core/tests/system/conftest.py b/cuda_core/tests/system/conftest.py
deleted file mode 100644
index 8708b3f06fc..00000000000
--- a/cuda_core/tests/system/conftest.py
+++ /dev/null
@@ -1,28 +0,0 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
-
-
-import pytest
-
-from cuda.core import system
-
-SHOULD_SKIP_NVML_TESTS = not system.CUDA_BINDINGS_NVML_IS_COMPATIBLE
-
-
-if system.CUDA_BINDINGS_NVML_IS_COMPATIBLE:
-    from cuda.bindings._test_helpers.arch_check import hardware_supports_nvml
-
-    SHOULD_SKIP_NVML_TESTS |= not hardware_supports_nvml()
-
-
-skip_if_nvml_unsupported = pytest.mark.skipif(
-    SHOULD_SKIP_NVML_TESTS,
-    reason="NVML support requires cuda.bindings version 12.9.6+ for CUDA 12.x or 13.2.0+ for CUDA 13.x, and hardware that supports NVML",
-)
-
-
-def unsupported_before(device, expected_device_arch):
-    from cuda.bindings._test_helpers.arch_check import unsupported_before as nvml_unsupported_before
-
-    return nvml_unsupported_before(device._handle, expected_device_arch)
diff --git a/cuda_core/tests/system/test_nvml_context.py b/cuda_core/tests/system/test_nvml_context.py
index 16bc97f385c..03c3fbefe8b 100644
--- a/cuda_core/tests/system/test_nvml_context.py
+++ b/cuda_core/tests/system/test_nvml_context.py
@@ -1,9 +1,9 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 #
 # SPDX-License-Identifier: Apache-2.0
 
 
-from .conftest import skip_if_nvml_unsupported
+from cuda_python_test_helpers.arch_check import skip_if_nvml_unsupported
 
 pytestmark = skip_if_nvml_unsupported
 
diff --git a/cuda_core/tests/system/test_system_device.py b/cuda_core/tests/system/test_system_device.py
index 29246aa1ce4..03d92a98a20 100644
--- a/cuda_core/tests/system/test_system_device.py
+++ b/cuda_core/tests/system/test_system_device.py
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 
-from .conftest import skip_if_nvml_unsupported, unsupported_before
+from cuda_python_test_helpers.arch_check import skip_if_nvml_unsupported, unsupported_before
 
 pytestmark = skip_if_nvml_unsupported
 
@@ -11,7 +11,6 @@
 import multiprocessing
 import os
 import re
-import warnings
 
 import helpers
 import pytest
@@ -32,23 +31,6 @@ def check_gpu_available():
         pytest.skip("No GPUs available to run device tests", allow_module_level=True)
 
 
-def test_devices_are_the_same_architecture():
-    # The tests in this directory that use `unsupported_before` will generally
-    # skip the entire test after the first device that isn't supported is found.
-    # This means that if subsequent devices are of a different architecture,
-    # they won't be tested properly.  This tests for the (hopefully rare) case
-    # where a system has devices of different architectures and produces a warning.
-
-    all_arches = {device.arch for device in system.Device.get_all_devices()}
-
-    if len(all_arches) > 1:
-        warnings.warn(
-            f"System has devices of multiple architectures ({', '.join(x.name for x in all_arches)}). "
-            f" Some tests may be skipped unexpectedly",
-            UserWarning,
-        )
-
-
 def test_device_count():
     assert system.Device.get_device_count() == system.get_num_devices()
 
@@ -81,55 +63,69 @@ def test_device_architecture():
         assert isinstance(device_arch, typing.DeviceArch)
 
 
-def test_device_bar1_memory():
+def test_device_bar1_memory(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            bar1_memory_info = device.bar1_memory_info
-        free, total, used = (
-            bar1_memory_info.free,
-            bar1_memory_info.total,
-            bar1_memory_info.used,
-        )
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                bar1_memory_info = device.bar1_memory_info
+            free, total, used = (
+                bar1_memory_info.free,
+                bar1_memory_info.total,
+                bar1_memory_info.used,
+            )
 
-        assert isinstance(bar1_memory_info, _device.BAR1MemoryInfo)
-        assert isinstance(free, int)
-        assert isinstance(total, int)
-        assert isinstance(used, int)
+            assert isinstance(bar1_memory_info, _device.BAR1MemoryInfo)
+            assert isinstance(free, int)
+            assert isinstance(total, int)
+            assert isinstance(used, int)
 
-        assert free >= 0
-        assert total >= 0
-        assert used >= 0
-        assert free + used == total
+            assert free >= 0
+            assert total >= 0
+            assert used >= 0
+            assert free + used == total
 
 
 @pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="Device attributes not supported on WSL or Windows")
-def test_device_cpu_affinity():
+def test_device_cpu_affinity(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, typing.DeviceArch.KEPLER):
-            affinity = device.get_cpu_affinity(typing.AffinityScope.NODE)
-        assert isinstance(affinity, list)
-        os.sched_setaffinity(0, affinity)
-        assert os.sched_getaffinity(0) == set(affinity)
-
-
-@pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="Device attributes not supported on WSL or Windows")
-def test_affinity():
-    for device in system.Device.get_all_devices():
-        for scope in typing.AffinityScope.__members__.values():
+        with subtests.test(device_index=device.index):
             with unsupported_before(device, typing.DeviceArch.KEPLER):
-                affinity = device.get_cpu_affinity(scope)
-            assert isinstance(affinity, list)
-
-            affinity = device.get_memory_affinity(scope)
+                affinity = device.get_cpu_affinity(typing.AffinityScope.NODE)
             assert isinstance(affinity, list)
+            os.sched_setaffinity(0, affinity)
+            assert os.sched_getaffinity(0) == set(affinity)
 
 
-def test_numa_node_id():
+@pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="Device attributes not supported on WSL or Windows")
+def test_affinity(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            numa_node_id = device.numa_node_id
-        assert isinstance(numa_node_id, int)
-        assert numa_node_id >= -1
+        for scope in typing.AffinityScope.__members__.values():
+            with subtests.test(
+                device_index=device.index,
+                affinity_scope=scope.value,
+                affinity_api="get_cpu_affinity",
+            ):
+                with unsupported_before(device, typing.DeviceArch.KEPLER):
+                    affinity = device.get_cpu_affinity(scope)
+                assert isinstance(affinity, list)
+
+            with subtests.test(
+                device_index=device.index,
+                affinity_scope=scope.value,
+                affinity_api="get_memory_affinity",
+            ):
+                with unsupported_before(device, typing.DeviceArch.KEPLER):
+                    affinity = device.get_memory_affinity(scope)
+                assert isinstance(affinity, list)
+
+
+def test_numa_node_id(subtests):
+    for device in system.Device.get_all_devices():
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                numa_node_id = device.numa_node_id
+            assert isinstance(numa_node_id, int)
+            assert numa_node_id >= -1
 
 
 def test_device_cuda_compute_capability():
@@ -143,23 +139,24 @@ def test_device_cuda_compute_capability():
         assert 0 <= cuda_compute_capability[1] <= 9
 
 
-def test_device_memory():
+def test_device_memory(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            memory_info = device.memory_info
-        free, total, used, reserved = memory_info.free, memory_info.total, memory_info.used, memory_info.reserved
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                memory_info = device.memory_info
+            free, total, used, reserved = memory_info.free, memory_info.total, memory_info.used, memory_info.reserved
 
-        assert isinstance(memory_info, _device.MemoryInfo)
-        assert isinstance(free, int)
-        assert isinstance(total, int)
-        assert isinstance(used, int)
-        assert isinstance(reserved, int)
+            assert isinstance(memory_info, _device.MemoryInfo)
+            assert isinstance(free, int)
+            assert isinstance(total, int)
+            assert isinstance(used, int)
+            assert isinstance(reserved, int)
 
-        assert free >= 0
-        assert total >= 0
-        assert used >= 0
-        assert reserved >= 0
-        assert free + used + reserved == total
+            assert free >= 0
+            assert total >= 0
+            assert used >= 0
+            assert reserved >= 0
+            assert free + used + reserved == total
 
 
 def test_device_name():
@@ -169,72 +166,74 @@ def test_device_name():
         assert len(name) > 0
 
 
-def test_device_pci_info():
+def test_device_pci_info(subtests):
     for device in system.Device.get_all_devices():
-        pci_info = device.pci_info
-        assert isinstance(pci_info, _device.PciInfo)
+        with subtests.test(device_index=device.index):
+            pci_info = device.pci_info
+            assert isinstance(pci_info, _device.PciInfo)
 
-        assert isinstance(pci_info.bus_id, str)
-        assert re.match("[a-f0-9]{8}:[a-f0-9]{2}:[a-f0-9]{2}.[a-f0-9]", pci_info.bus_id.lower())
-        bus_id_domain = int(pci_info.bus_id.split(":")[0], 16)
-        bus_id_bus = int(pci_info.bus_id.split(":")[1], 16)
-        bus_id_device = int(pci_info.bus_id.split(":")[2][:2], 16)
+            assert isinstance(pci_info.bus_id, str)
+            assert re.match("[a-f0-9]{8}:[a-f0-9]{2}:[a-f0-9]{2}.[a-f0-9]", pci_info.bus_id.lower())
+            bus_id_domain = int(pci_info.bus_id.split(":")[0], 16)
+            bus_id_bus = int(pci_info.bus_id.split(":")[1], 16)
+            bus_id_device = int(pci_info.bus_id.split(":")[2][:2], 16)
 
-        assert isinstance(pci_info.domain, int)
-        assert 0x00 <= pci_info.domain <= 0xFFFFFFFF
-        assert pci_info.domain == bus_id_domain
+            assert isinstance(pci_info.domain, int)
+            assert 0x00 <= pci_info.domain <= 0xFFFFFFFF
+            assert pci_info.domain == bus_id_domain
 
-        assert isinstance(pci_info.bus, int)
-        assert 0x00 <= pci_info.bus <= 0xFF
-        assert pci_info.bus == bus_id_bus
+            assert isinstance(pci_info.bus, int)
+            assert 0x00 <= pci_info.bus <= 0xFF
+            assert pci_info.bus == bus_id_bus
 
-        assert isinstance(pci_info.device, int)
-        assert 0x00 <= pci_info.device <= 0xFF
-        assert pci_info.device == bus_id_device
+            assert isinstance(pci_info.device, int)
+            assert 0x00 <= pci_info.device <= 0xFF
+            assert pci_info.device == bus_id_device
 
-        assert isinstance(pci_info.vendor_id, int)
-        assert 0x0000 <= pci_info.vendor_id <= 0xFFFF
+            assert isinstance(pci_info.vendor_id, int)
+            assert 0x0000 <= pci_info.vendor_id <= 0xFFFF
 
-        assert isinstance(pci_info.device_id, int)
-        assert 0x0000 <= pci_info.device_id <= 0xFFFF
+            assert isinstance(pci_info.device_id, int)
+            assert 0x0000 <= pci_info.device_id <= 0xFFFF
 
-        assert isinstance(pci_info.subsystem_id, int)
-        assert 0x00000000 <= pci_info.subsystem_id <= 0xFFFFFFFF
+            assert isinstance(pci_info.subsystem_id, int)
+            assert 0x00000000 <= pci_info.subsystem_id <= 0xFFFFFFFF
 
-        assert isinstance(pci_info.base_class, int)
-        assert 0x00 <= pci_info.base_class <= 0xFF
+            assert isinstance(pci_info.base_class, int)
+            assert 0x00 <= pci_info.base_class <= 0xFF
 
-        assert isinstance(pci_info.sub_class, int)
-        assert 0x00 <= pci_info.sub_class <= 0xFF
+            assert isinstance(pci_info.sub_class, int)
+            assert 0x00 <= pci_info.sub_class <= 0xFF
 
-        assert isinstance(pci_info.link_generation, int)
-        assert 0 <= pci_info.link_generation <= 0xFF
+            assert isinstance(pci_info.link_generation, int)
+            assert 0 <= pci_info.link_generation <= 0xFF
 
-        assert isinstance(pci_info.max_link_generation, int)
-        assert 0 <= pci_info.max_link_generation <= 0xFF
+            assert isinstance(pci_info.max_link_generation, int)
+            assert 0 <= pci_info.max_link_generation <= 0xFF
 
-        assert isinstance(pci_info.max_link_width, int)
-        assert 0 <= pci_info.max_link_width <= 0xFF
+            assert isinstance(pci_info.max_link_width, int)
+            assert 0 <= pci_info.max_link_width <= 0xFF
 
-        assert isinstance(pci_info.current_link_generation, int)
-        assert 0 <= pci_info.current_link_generation <= 0xFF
+            assert isinstance(pci_info.current_link_generation, int)
+            assert 0 <= pci_info.current_link_generation <= 0xFF
 
-        assert isinstance(pci_info.current_link_width, int)
-        assert 0 <= pci_info.current_link_width <= 0xFF
+            assert isinstance(pci_info.current_link_width, int)
+            assert 0 <= pci_info.current_link_width <= 0xFF
 
-        with unsupported_before(device, None):
-            assert isinstance(pci_info.tx_throughput, int)
-            assert isinstance(pci_info.rx_throughput, int)
+            with unsupported_before(device, None):
+                assert isinstance(pci_info.tx_throughput, int)
+                assert isinstance(pci_info.rx_throughput, int)
 
-        assert isinstance(pci_info.replay_counter, int)
+            assert isinstance(pci_info.replay_counter, int)
 
 
-def test_device_serial():
+def test_device_serial(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, "HAS_INFOROM"):
-            serial = device.serial
-        assert isinstance(serial, str)
-        assert len(serial) > 0
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, "HAS_INFOROM"):
+                serial = device.serial
+            assert isinstance(serial, str)
+            assert len(serial) > 0
 
 
 def test_device_uuid_without_prefix():
@@ -322,109 +321,155 @@ def test_device_pci_bus_id():
 
 
 @pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="Device attributes not supported on WSL or Windows")
-def test_device_attributes():
+def test_device_attributes(subtests):
     for device in system.Device.get_all_devices():
-        # Docs say this should work on AMPERE or newer, but experimentally
-        # that's not the case.
-        with unsupported_before(device, None):
-            attributes = device.attributes
-        assert isinstance(attributes, _device.DeviceAttributes)
+        with subtests.test(device_index=device.index):
+            # Docs say this should work on AMPERE or newer, but experimentally
+            # that's not the case.
+            with unsupported_before(device, None):
+                attributes = device.attributes
+            assert isinstance(attributes, _device.DeviceAttributes)
+
+            assert isinstance(attributes.multiprocessor_count, int)
+            assert attributes.multiprocessor_count > 0
 
-        assert isinstance(attributes.multiprocessor_count, int)
-        assert attributes.multiprocessor_count > 0
+            assert isinstance(attributes.shared_copy_engine_count, int)
+            assert isinstance(attributes.shared_decoder_count, int)
+            assert isinstance(attributes.shared_encoder_count, int)
+            assert isinstance(attributes.shared_jpeg_count, int)
+            assert isinstance(attributes.shared_ofa_count, int)
+            assert isinstance(attributes.gpu_instance_slice_count, int)
+            assert isinstance(attributes.compute_instance_slice_count, int)
+            assert isinstance(attributes.memory_size_mb, int)
+            assert attributes.memory_size_mb > 0
 
-        assert isinstance(attributes.shared_copy_engine_count, int)
-        assert isinstance(attributes.shared_decoder_count, int)
-        assert isinstance(attributes.shared_encoder_count, int)
-        assert isinstance(attributes.shared_jpeg_count, int)
-        assert isinstance(attributes.shared_ofa_count, int)
-        assert isinstance(attributes.gpu_instance_slice_count, int)
-        assert isinstance(attributes.compute_instance_slice_count, int)
-        assert isinstance(attributes.memory_size_mb, int)
-        assert attributes.memory_size_mb > 0
 
+@pytest.mark.agent_authored(model="claude-opus-4.7")
+def test_device_attributes_wraps_nvml_struct():
+    # Use synthetic data because NVML exposes these attributes only for MIG
+    # devices.
+    raw = nvml.DeviceAttributes()
+    raw.multiprocessor_count = 14
+    raw.memory_size_mb = 9728
 
-def test_c2c_mode_enabled():
+    attrs = _device.DeviceAttributes(raw)
+    assert isinstance(attrs, _device.DeviceAttributes)
+    assert attrs.multiprocessor_count == 14
+    assert attrs.memory_size_mb == 9728
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.7")
+def test_event_data_wraps_nvml_struct():
+    raw = nvml.EventData()
+    raw.event_type = nvml.EventType.PSTATE
+
+    event = _device.EventData(raw)
+    assert isinstance(event, _device.EventData)
+    assert event.event_type is typing.EventType.PSTATE
+
+
+def test_c2c_mode_enabled(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            is_enabled = device.is_c2c_enabled
-        assert isinstance(is_enabled, bool)
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                is_enabled = device.is_c2c_enabled
+            assert isinstance(is_enabled, bool)
 
 
 @pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="Persistence mode not supported on WSL or Windows")
-def test_persistence_mode_enabled():
+@pytest.mark.thread_unsafe(reason="device persistence mode is global state")
+def test_persistence_mode_enabled(subtests):
     for device in system.Device.get_all_devices():
-        is_enabled = device.is_persistence_mode_enabled
-        assert isinstance(is_enabled, bool)
-        try:
-            device.is_persistence_mode_enabled = False
-        except nvml.NoPermissionError as e:
-            pytest.xfail(f"nvml.NoPermissionError: {e}")
-        try:
-            assert device.is_persistence_mode_enabled is False
-        finally:
-            device.is_persistence_mode_enabled = is_enabled
+        with subtests.test(device_index=device.index):
+            is_enabled = device.is_persistence_mode_enabled
+            assert isinstance(is_enabled, bool)
+            try:
+                device.is_persistence_mode_enabled = False
+            except nvml.NoPermissionError as e:
+                pytest.xfail(f"nvml.NoPermissionError: {e}")
+            try:
+                assert device.is_persistence_mode_enabled is False
+            finally:
+                device.is_persistence_mode_enabled = is_enabled
 
 
-def test_field_values():
+def test_field_values(subtests):
     for device in system.Device.get_all_devices():
-        # TODO: Are there any fields that return double's?  It would be good to
-        # test those.
+        with subtests.test(device_index=device.index):
+            # TODO: Are there any fields that return double's?  It would be good to
+            # test those.
 
-        assert len(device.get_field_values([])) == 0
+            assert len(device.get_field_values([])) == 0
 
-        field_ids = [
-            typing.FieldId.DEV_TOTAL_ENERGY_CONSUMPTION,
-            typing.FieldId.DEV_PCIE_COUNT_TX_BYTES,
-        ]
-        field_values = device.get_field_values(field_ids)
-        with unsupported_before(device, None):
-            field_values.validate()
+            field_ids = [
+                typing.FieldId.DEV_TOTAL_ENERGY_CONSUMPTION,
+                typing.FieldId.DEV_PCIE_COUNT_TX_BYTES,
+            ]
+            field_values = device.get_field_values(field_ids)
+            with unsupported_before(device, None):
+                field_values.validate()
 
-        with pytest.raises(TypeError):
-            field_values["invalid_index"]
+            with pytest.raises(TypeError):
+                field_values["invalid_index"]
 
-        assert isinstance(field_values, _device.FieldValues)
-        assert len(field_values) == len(field_ids)
+            assert isinstance(field_values, _device.FieldValues)
+            assert len(field_values) == len(field_ids)
 
-        raw_values = field_values.get_all_values()
-        assert all(x == y.value for x, y in zip(raw_values, field_values))
+            raw_values = field_values.get_all_values()
+            assert all(x == y.value for x, y in zip(raw_values, field_values))
 
-        for field_id, field_value in zip(field_ids, field_values):
-            assert field_value.field_id == field_id
-            assert type(field_value.value) is int
-            assert field_value.latency_usec >= 0
-            assert field_value.timestamp >= 0
+            for field_id, field_value in zip(field_ids, field_values):
+                assert field_value.field_id == field_id
+                assert type(field_value.value) is int
+                assert field_value.latency_usec >= 0
+                assert field_value.timestamp >= 0
 
-        orig_timestamp = field_values[0].timestamp
-        field_values = device.get_field_values(field_ids)
-        assert field_values[0].timestamp >= orig_timestamp
+            orig_timestamp = field_values[0].timestamp
+            field_values = device.get_field_values(field_ids)
+            assert field_values[0].timestamp >= orig_timestamp
 
-        # Test only one element, because that's weirdly a special case
-        field_ids = [
-            typing.FieldId.DEV_PCIE_REPLAY_COUNTER,
-        ]
-        field_values = device.get_field_values(field_ids)
-        assert len(field_values) == 1
-        field_values.validate()
-        old_value = field_values[0].value
+            # Test only one element, because that's weirdly a special case
+            field_ids = [
+                typing.FieldId.DEV_PCIE_REPLAY_COUNTER,
+            ]
+            field_values = device.get_field_values(field_ids)
+            assert len(field_values) == 1
+            field_values.validate()
+            old_value = field_values[0].value
+
+            # Test clear_field_values
+            device.clear_field_values(field_ids)
+            field_values = device.get_field_values(field_ids)
+            field_values.validate()
+            assert len(field_values) == 1
+            assert field_values[0].value <= old_value
 
-        # Test clear_field_values
-        device.clear_field_values(field_ids)
-        field_values = device.get_field_values(field_ids)
-        field_values.validate()
-        assert len(field_values) == 1
-        assert field_values[0].value <= old_value
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_field_value_decodes_signed_long_long():
+    """SIGNED_LONG_LONG decodes from nvmlValue_t.sll_val as a Python int."""
+    field_value = nvml.FieldValue()
+    field_value.nvml_return = int(nvml.Return.SUCCESS)
+    field_value.value_type = int(nvml.ValueType.SIGNED_LONG_LONG)
+    field_value.value.sll_val[0] = -45
+
+    value = _device.FieldValue(field_value).value
+    assert value == -45
+    assert type(value) is int
 
 
 @pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="Device attributes not supported on WSL or Windows")
-def test_get_all_devices_with_cpu_affinity():
+def test_get_all_devices_with_cpu_affinity(subtests):
     for i in range(multiprocessing.cpu_count()):
-        for device in system.Device.get_all_devices_with_cpu_affinity(i):
-            with unsupported_before(device, DeviceArch.KEPLER):
-                affinity = device.get_cpu_affinity()
-            assert isinstance(affinity, list)
-            assert i in affinity
+        devices = []
+        with subtests.test(cpu_index=i, affinity_api="get_all_devices_with_cpu_affinity"):
+            devices = list(system.Device.get_all_devices_with_cpu_affinity(i))
+        for device in devices:
+            with subtests.test(cpu_index=i, device_index=device.index):
+                with unsupported_before(device, DeviceArch.KEPLER):
+                    affinity = device.get_cpu_affinity()
+                assert isinstance(affinity, list)
+                assert i in affinity
 
 
 def test_index():
@@ -434,21 +479,23 @@ def test_index():
         assert index == i
 
 
-def test_module_id():
+def test_module_id(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            module_id = device.module_id
-        assert isinstance(module_id, int)
-        assert module_id >= 0
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                module_id = device.module_id
+            assert isinstance(module_id, int)
+            assert module_id >= 0
 
 
-def test_addressing_mode():
+def test_addressing_mode(subtests):
     for device in system.Device.get_all_devices():
-        # By docs, should be supported on TURING or newer, but experimentally,
-        # is also unsupported on other hardware.
-        with unsupported_before(device, None):
-            addressing_mode = device.addressing_mode
-        assert addressing_mode is None or addressing_mode in typing.AddressingMode.__members__.values()
+        with subtests.test(device_index=device.index):
+            # By docs, should be supported on TURING or newer, but experimentally,
+            # is also unsupported on other hardware.
+            with unsupported_before(device, None):
+                addressing_mode = device.addressing_mode
+            assert addressing_mode is None or addressing_mode in typing.AddressingMode.__members__.values()
 
 
 def test_display_mode():
@@ -460,16 +507,17 @@ def test_display_mode():
         assert isinstance(is_display_active, bool)
 
 
-def test_repair_status():
+def test_repair_status(subtests):
     for device in system.Device.get_all_devices():
-        # By docs, should be supported on AMPERE or newer, but experimentally,
-        # this seems to also work on some TURING systems.
-        with unsupported_before(device, None):
-            repair_status = device.repair_status
-        assert isinstance(repair_status, _device.RepairStatus)
+        with subtests.test(device_index=device.index):
+            # By docs, should be supported on AMPERE or newer, but experimentally,
+            # this seems to also work on some TURING systems.
+            with unsupported_before(device, None):
+                repair_status = device.repair_status
+            assert isinstance(repair_status, _device.RepairStatus)
 
-        assert isinstance(repair_status.channel_repair_pending, bool)
-        assert isinstance(repair_status.tpc_repair_pending, bool)
+            assert isinstance(repair_status.channel_repair_pending, bool)
+            assert isinstance(repair_status.tpc_repair_pending, bool)
 
 
 @pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="Device attributes not supported on WSL or Windows")
@@ -520,256 +568,366 @@ def test_get_minor_number():
         assert minor_number >= 0
 
 
-def test_get_inforom_version():
+def test_get_inforom_version(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, "HAS_INFOROM"):
-            inforom = device.inforom
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, "HAS_INFOROM"):
+                inforom = device.inforom
 
-        with unsupported_before(device, "HAS_INFOROM"):
-            inforom_image_version = inforom.image_version
-        assert isinstance(inforom_image_version, str)
-        assert len(inforom_image_version) > 0
+            with unsupported_before(device, "HAS_INFOROM"):
+                inforom_image_version = inforom.image_version
+            assert isinstance(inforom_image_version, str)
+            assert len(inforom_image_version) > 0
 
-        inforom_version = inforom.get_version(typing.InforomObject.OEM)
-        assert isinstance(inforom_version, str)
-        assert len(inforom_version) > 0
+            inforom_version = inforom.get_version(typing.InforomObject.OEM)
+            assert isinstance(inforom_version, str)
+            assert len(inforom_version) > 0
 
-        checksum = inforom.configuration_checksum
-        assert isinstance(checksum, int)
+            checksum = inforom.configuration_checksum
+            assert isinstance(checksum, int)
 
-        # TODO: This is untested locally.
-        try:
-            timestamp, duration_us = inforom.bbx_flush_time
-        except (system.NotSupportedError, system.NotReadyError):
-            pass
-        else:
-            assert isinstance(timestamp, int)
-            assert timestamp > 0
-            assert isinstance(duration_us, int)
-            assert duration_us > 0
+            # TODO: This is untested locally.
+            try:
+                timestamp, duration_us = inforom.bbx_flush_time
+            except (system.NotSupportedError, system.NotReadyError):
+                pass
+            else:
+                assert isinstance(timestamp, int)
+                assert timestamp > 0
+                assert isinstance(duration_us, int)
+                assert duration_us > 0
 
-        with unsupported_before(device, "HAS_INFOROM"):
-            board_part_number = inforom.board_part_number
-        assert isinstance(board_part_number, str)
+            with unsupported_before(device, "HAS_INFOROM"):
+                board_part_number = inforom.board_part_number
+            assert isinstance(board_part_number, str)
 
-        # Some boards (e.g. NVIDIA T4G) do not program a board part number
-        assert board_part_number == "" or board_part_number.strip() == board_part_number
+            # Some boards (e.g. NVIDIA T4G) do not program a board part number
+            assert board_part_number == "" or board_part_number.strip() == board_part_number
 
-        inforom.validate()
+            inforom.validate()
 
 
-def test_auto_boosted_clocks_enabled():
+def test_auto_boosted_clocks_enabled(subtests):
     for device in system.Device.get_all_devices():
-        # This API is supported on KEPLER and newer, but it also seems
-        # unsupported elsewhere.
-        with unsupported_before(device, None):
-            current, default = device.is_auto_boosted_clocks_enabled
-        assert isinstance(current, bool)
-        assert isinstance(default, bool)
+        with subtests.test(device_index=device.index):
+            # This API is supported on KEPLER and newer, but it also seems
+            # unsupported elsewhere.
+            with unsupported_before(device, None):
+                current, default = device.is_auto_boosted_clocks_enabled
+            assert isinstance(current, bool)
+            assert isinstance(default, bool)
 
 
-def test_clock():
+def test_clock(subtests):
     for device in system.Device.get_all_devices():
         for clock_type in typing.ClockType:
-            clock = device.get_clock(clock_type)
-            assert isinstance(clock, _device.ClockInfo)
+            with subtests.test(device_index=device.index, clock_type=clock_type.value):
+                clock = device.get_clock(clock_type)
+                assert isinstance(clock, _device.ClockInfo)
 
-            # These are ordered from oldest API to newest API so we test as much
-            # as we can on each hardware architecture.
+                # These are ordered from oldest API to newest API so we test as much
+                # as we can on each hardware architecture.
 
-            with unsupported_before(device, None):
-                pstate = device.performance_state
-
-            min_, max_ = clock.get_min_max_clock_of_pstate_mhz(pstate)
-            assert isinstance(min_, int)
-            assert min_ >= 0
-            assert isinstance(max_, int)
-            assert max_ >= 0
-
-            with unsupported_before(device, "FERMI"):
-                max_mhz = clock.get_max_mhz()
-            assert isinstance(max_mhz, int)
-            assert max_mhz >= 0
+                with unsupported_before(device, None):
+                    pstate = device.performance_state
 
-            with unsupported_before(device, DeviceArch.KEPLER):
-                current_mhz = clock.get_current_mhz()
-            assert isinstance(current_mhz, int)
-            assert current_mhz >= 0
+                # Individual queries may be unsupported for a clock domain even
+                # on newer devices.
+                with unsupported_before(device, None):
+                    min_, max_ = clock.get_min_max_clock_of_pstate_mhz(pstate)
+                assert isinstance(min_, int)
+                assert min_ >= 0
+                assert isinstance(max_, int)
+                assert max_ >= 0
 
-            # Docs say this should work on PASCAL or newer, but experimentally,
-            # is also unsupported on other hardware.
-            with unsupported_before(device, DeviceArch.MAXWELL):
-                try:
-                    offsets = clock.get_offsets(pstate)
-                except (system.InvalidArgumentError, system.NotFoundError):
-                    pass
-                else:
-                    assert isinstance(offsets, _device.ClockOffsets)
-                    assert isinstance(offsets.clock_offset_mhz, int)
-                    assert isinstance(offsets.max_offset_mhz, int)
-                    assert isinstance(offsets.min_offset_mhz, int)
+                with unsupported_before(device, "FERMI"):
+                    max_mhz = clock.get_max_mhz()
+                assert isinstance(max_mhz, int)
+                assert max_mhz >= 0
 
-            # By docs, should be supported on PASCAL or newer, but experimentally,
-            # is also unsupported on other hardware.
-            with unsupported_before(device, None):
-                max_customer_boost = clock.get_max_customer_boost_mhz()
-            assert isinstance(max_customer_boost, int)
-            assert max_customer_boost >= 0
+                with unsupported_before(device, None):
+                    current_mhz = clock.get_current_mhz()
+                assert isinstance(current_mhz, int)
+                assert current_mhz >= 0
+
+                # Docs say this should work on PASCAL or newer, but experimentally,
+                # is also unsupported on other hardware.
+                with unsupported_before(device, DeviceArch.MAXWELL):
+                    try:
+                        offsets = clock.get_offsets(pstate)
+                    except (system.InvalidArgumentError, system.NotFoundError):
+                        pass
+                    else:
+                        assert isinstance(offsets, _device.ClockOffsets)
+                        assert isinstance(offsets.clock_offset_mhz, int)
+                        assert isinstance(offsets.max_offset_mhz, int)
+                        assert isinstance(offsets.min_offset_mhz, int)
+
+                # By docs, should be supported on PASCAL or newer, but experimentally,
+                # is also unsupported on other hardware.
+                with unsupported_before(device, None):
+                    max_customer_boost = clock.get_max_customer_boost_mhz()
+                assert isinstance(max_customer_boost, int)
+                assert max_customer_boost >= 0
 
 
-def test_clock_event_reasons():
+def test_clock_event_reasons(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            reasons = device.current_clock_event_reasons
-        assert all(isinstance(reason, typing.ClocksEventReasons) for reason in reasons)
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                reasons = device.current_clock_event_reasons
+            assert all(isinstance(reason, typing.ClocksEventReasons) for reason in reasons)
 
-        with unsupported_before(device, None):
-            reasons = device.supported_clock_event_reasons
-        assert all(isinstance(reason, typing.ClocksEventReasons) for reason in reasons)
+            with unsupported_before(device, None):
+                reasons = device.supported_clock_event_reasons
+            assert all(isinstance(reason, typing.ClocksEventReasons) for reason in reasons)
 
 
-def test_fan():
+def test_fan(subtests):
     for device in system.Device.get_all_devices():
+        device_index = device.index
+        num_fans = None
         # The fan APIs are only supported on discrete devices with fans,
         # but when they are not available `device.num_fans` returns 0.
-        if device.num_fans == 0:
-            pytest.skip("Device has no fans to test")
+        with subtests.test(device_index=device_index, fan_api="get_num_fans"):
+            value = device.num_fans
+            assert isinstance(value, int)
+            assert value >= 0
+            num_fans = value
+            if num_fans == 0:
+                pytest.skip("Device has no fans to test")
+        if not num_fans:
+            continue
 
-        for fan_idx in range(device.num_fans):
-            fan_info = device.get_fan(fan_idx)
-            assert isinstance(fan_info, _device.FanInfo)
+        for fan_idx in range(num_fans):
+            with subtests.test(device_index=device_index, fan_index=fan_idx):
+                fan_info = device.get_fan(fan_idx)
+                assert isinstance(fan_info, _device.FanInfo)
 
-            speed = fan_info.speed
-            assert isinstance(speed, int)
-            assert 0 <= speed <= 200
-            try:
-                fan_info.speed = 50
-            except nvml.NoPermissionError as e:
-                pytest.xfail(f"nvml.NoPermissionError: {e}")
-            try:
-                fan_info.speed = speed
+                speed = fan_info.speed
+                assert isinstance(speed, int)
+                assert 0 <= speed <= 200
+                try:
+                    fan_info.speed = 50
+                except nvml.NoPermissionError as e:
+                    pytest.xfail(f"nvml.NoPermissionError: {e}")
+                try:
+                    fan_info.speed = speed
 
-                speed_rpm = fan_info.speed_rpm
-                assert isinstance(speed_rpm, int)
-                assert speed_rpm >= 0
+                    speed_rpm = fan_info.speed_rpm
+                    assert isinstance(speed_rpm, int)
+                    assert speed_rpm >= 0
 
-                target_speed = fan_info.target_speed
-                assert isinstance(target_speed, int)
-                assert speed <= target_speed * 2
+                    target_speed = fan_info.target_speed
+                    assert isinstance(target_speed, int)
+                    assert speed <= target_speed * 2
 
-                min_, max_ = fan_info.min_max_speed
-                assert isinstance(min_, int)
-                assert isinstance(max_, int)
-                assert min_ <= max_
+                    min_, max_ = fan_info.min_max_speed
+                    assert isinstance(min_, int)
+                    assert isinstance(max_, int)
+                    assert min_ <= max_
 
-                control_policy = fan_info.control_policy
-                assert isinstance(control_policy, typing.FanControlPolicy)
-            finally:
-                fan_info.set_default_speed()
+                    control_policy = fan_info.control_policy
+                    assert isinstance(control_policy, typing.FanControlPolicy)
+                finally:
+                    fan_info.set_default_speed()
 
 
-def test_cooler():
+def test_cooler(subtests):
     for device in system.Device.get_all_devices():
-        # The cooler APIs are only supported on discrete devices with fans,
-        # but when they are not available `device.num_fans` returns 0.
-        if device.num_fans == 0:
-            pytest.skip("Device has no coolers to test")
+        with subtests.test(device_index=device.index):
+            # The cooler APIs are only supported on discrete devices with fans,
+            # but when they are not available `device.num_fans` returns 0.
+            if device.num_fans == 0:
+                pytest.skip("Device has no coolers to test")
 
-        with unsupported_before(device, DeviceArch.MAXWELL):
-            cooler_info = device.cooler
+            with unsupported_before(device, DeviceArch.MAXWELL):
+                cooler_info = device.cooler
 
-        assert isinstance(cooler_info, _device.CoolerInfo)
+            assert isinstance(cooler_info, _device.CoolerInfo)
 
-        signal_type = cooler_info.signal_type
-        assert isinstance(signal_type, (typing.CoolerControl, type(None)))
+            signal_type = cooler_info.signal_type
+            assert isinstance(signal_type, (typing.CoolerControl, type(None)))
 
-        target = cooler_info.target
-        assert all(isinstance(t, typing.CoolerTarget) for t in target)
+            target = cooler_info.target
+            assert all(isinstance(t, typing.CoolerTarget) for t in target)
 
 
-def test_temperature():
+@pytest.mark.filterwarnings("ignore::DeprecationWarning")
+def test_temperature(subtests):
     for device in system.Device.get_all_devices():
-        temperature = device.temperature
-        assert isinstance(temperature, _device.Temperature)
+        device_index = device.index
+        temperature = None
+        with subtests.test(device_index=device_index, temperature_api="temperature"):
+            value = device.temperature
+            assert isinstance(value, _device.Temperature)
+            temperature = value
+        if temperature is None:
+            continue
 
-        sensor = temperature.get_sensor()
-        assert isinstance(sensor, int)
-        assert sensor >= 0
+        with subtests.test(device_index=device_index, temperature_api="get_sensor"):
+            sensor = temperature.get_sensor()
+            assert isinstance(sensor, int)
+            assert sensor >= 0
 
         # By docs, should be supported on KEPLER or newer, but experimentally,
         # is also unsupported on other hardware.
-        with unsupported_before(device, None):
-            for threshold in list(typing.TemperatureThresholds):
-                t = temperature.get_threshold(threshold)
+        # get_threshold emits DeprecationWarning for some thresholds on Ada+;
+        # that behaviour is tested separately in
+        # test_temperature_threshold_unrecognized_device_arch.
+        for threshold in typing.TemperatureThresholds:
+            with subtests.test(
+                device_index=device_index,
+                temperature_api="get_threshold",
+                threshold=threshold.value,
+            ):
+                with unsupported_before(device, None):
+                    t = temperature.get_threshold(threshold)
                 assert isinstance(t, int)
                 assert t >= 0
 
-        with unsupported_before(device, None):
-            margin = temperature.margin
-        assert isinstance(margin, int)
-        assert margin >= 0
+        with subtests.test(device_index=device_index, temperature_api="margin"):
+            with unsupported_before(device, None):
+                margin = temperature.margin
+            assert isinstance(margin, int)
+            assert margin >= 0
 
-        with unsupported_before(device, None):
-            thermals = temperature.get_thermal_settings(typing.ThermalTarget.ALL)
-        assert isinstance(thermals, _device.ThermalSettings)
+        thermals = None
+        with subtests.test(device_index=device_index, temperature_api="get_thermal_settings"):
+            with unsupported_before(device, None):
+                value = temperature.get_thermal_settings(typing.ThermalTarget.ALL)
+            assert isinstance(value, _device.ThermalSettings)
+            thermals = value
+        if thermals is None:
+            continue
 
         for i, sensor in enumerate(thermals):
-            assert isinstance(sensor, _device.ThermalSensor)
-            assert isinstance(sensor.target, typing.ThermalTarget)
-            assert isinstance(sensor.controller, typing.ThermalController)
-            assert isinstance(sensor.default_min_temp, int)
-            assert sensor.default_min_temp >= 0
-            assert isinstance(sensor.default_max_temp, int)
-            assert sensor.default_max_temp >= sensor.default_min_temp
-            assert isinstance(sensor.current_temp, int)
-            assert sensor.default_min_temp <= sensor.current_temp <= sensor.default_max_temp
-
-
-def test_pstates():
-    for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            pstate = device.performance_state
-        assert isinstance(pstate, int)
+            with subtests.test(
+                device_index=device_index,
+                temperature_api="thermal_sensor",
+                sensor_index=i,
+            ):
+                assert isinstance(sensor, _device.ThermalSensor)
+                assert isinstance(sensor.target, typing.ThermalTarget)
+                assert isinstance(sensor.controller, typing.ThermalController)
+                assert isinstance(sensor.default_min_temp, int)
+                assert sensor.default_min_temp >= 0
+                assert isinstance(sensor.default_max_temp, int)
+                assert sensor.default_max_temp >= sensor.default_min_temp
+                assert isinstance(sensor.current_temp, int)
+                assert sensor.default_min_temp <= sensor.current_temp <= sensor.default_max_temp
+
+
+@pytest.mark.thread_unsafe(reason="Temporarily replaces process-global NVML functions")
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_temperature_threshold_unrecognized_device_arch(monkeypatch):
+    temperature = system.Device(index=0).temperature
+    unrecognized_arch = int(nvml.DeviceArch.UNKNOWN) - 1
+    with pytest.raises(ValueError):
+        nvml.DeviceArch(unrecognized_arch)
+
+    monkeypatch.setattr(nvml, "device_get_architecture", lambda _handle: unrecognized_arch)
+    monkeypatch.setattr(
+        nvml,
+        "device_get_temperature_threshold",
+        lambda _handle, _threshold: 42,
+    )
+
+    with pytest.warns(DeprecationWarning, match="no longer recommended"):
+        assert temperature.get_threshold(typing.TemperatureThresholds.SHUTDOWN) == 42
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_temperature_arg_validation():
+    # Both getters reject an unknown key before issuing any NVML call.
+    temperature = system.Device(index=0).temperature
+    with pytest.raises(ValueError, match="Invalid temperature threshold type"):
+        temperature.get_threshold("not-a-threshold")
+    with pytest.raises(ValueError, match="Invalid thermal sensor index"):
+        temperature.get_thermal_settings("not-a-sensor")
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_device_constructor_selector_validation():
+    # The constructor requires exactly one selector, rejected before NVML is touched.
+    with pytest.raises(ValueError, match="only one of"):
+        system.Device(index=0, uuid="ignored")
+    with pytest.raises(ValueError, match="either a device"):
+        system.Device()
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_device_arg_validation():
+    device = system.Device(index=0)
+    # Each argument validator raises before reaching the driver/NVML call.
+    with pytest.raises(ValueError, match="Invalid affinity scope"):
+        device.get_memory_affinity("not-a-scope")
+    with pytest.raises(ValueError, match="Invalid affinity scope"):
+        device.get_cpu_affinity("not-a-scope")
+    with pytest.raises(ValueError, match="Invalid topology level"):
+        list(device.get_topology_nearest_gpus("not-a-level"))
+    with pytest.raises(ValueError, match="Invalid P2P caps index"):
+        system.get_p2p_status(device, device, "not-an-index")
+
+
+def test_pstates(subtests):
+    for device in system.Device.get_all_devices():
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                pstate = device.performance_state
+            assert isinstance(pstate, int)
 
-        pstates = device.supported_pstates
-        assert all(isinstance(p, int) for p in pstates)
+            pstates = device.supported_pstates
+            assert all(isinstance(p, int) for p in pstates)
 
-        dynamic_pstates_info = device.dynamic_pstates_info
-        assert isinstance(dynamic_pstates_info, _device.GpuDynamicPstatesInfo)
+            dynamic_pstates_info = device.dynamic_pstates_info
+            assert isinstance(dynamic_pstates_info, _device.GpuDynamicPstatesInfo)
 
-        assert len(dynamic_pstates_info) == nvml.MAX_GPU_UTILIZATIONS
+            assert len(dynamic_pstates_info) == nvml.MAX_GPU_UTILIZATIONS
 
-        for utilization in dynamic_pstates_info:
-            assert isinstance(utilization.is_present, bool)
-            assert isinstance(utilization.percentage, int)
-            assert isinstance(utilization.inc_threshold, int)
-            assert isinstance(utilization.dec_threshold, int)
+            for utilization in dynamic_pstates_info:
+                assert isinstance(utilization.is_present, bool)
+                assert isinstance(utilization.percentage, int)
+                assert isinstance(utilization.inc_threshold, int)
+                assert isinstance(utilization.dec_threshold, int)
 
 
-def test_compute_running_processes():
+def test_compute_running_processes(subtests):
     for cuda_device in CudaDevice.get_all_devices():
         device = cuda_device.to_system_device()
-        with unsupported_before(device, "FERMI"):
-            processes = device.compute_running_processes
-        assert isinstance(processes, list)
-        for proc in processes:
-            assert isinstance(proc, _device.ProcessInfo)
-            assert isinstance(proc.pid, int)
-            assert isinstance(proc.used_gpu_memory, int)
-            if device.mig.is_mig_device:
-                assert isinstance(proc.gpu_instance_id, int)
-                assert isinstance(proc.compute_instance_id, int)
-            else:
-                with pytest.raises(nvml.NotSupportedError):
-                    proc.gpu_instance_id  # noqa: B018
-                with pytest.raises(nvml.NotSupportedError):
-                    proc.compute_instance_id  # noqa: B018
-
-
-def test_nvlink():
-    for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            for link in range(device.get_nvlink_count()):
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, "FERMI"):
+                processes = device.compute_running_processes
+            assert isinstance(processes, list)
+            for proc in processes:
+                assert isinstance(proc, _device.ProcessInfo)
+                assert isinstance(proc.pid, int)
+                assert isinstance(proc.used_gpu_memory, int)
+                if device.mig.is_mig_device:
+                    assert isinstance(proc.gpu_instance_id, int)
+                    assert isinstance(proc.compute_instance_id, int)
+                else:
+                    with pytest.raises(nvml.NotSupportedError):
+                        proc.gpu_instance_id  # noqa: B018
+                    with pytest.raises(nvml.NotSupportedError):
+                        proc.compute_instance_id  # noqa: B018
+
+
+def test_nvlink(subtests):
+    for device in system.Device.get_all_devices():
+        device_index = device.index
+        link_count = 0
+        with (
+            subtests.test(device_index=device_index, nvlink_api="get_nvlink_count"),
+            unsupported_before(device, None),
+        ):
+            value = device.get_nvlink_count()
+            assert isinstance(value, int)
+            assert value >= 0
+            link_count = value
+
+        for link in range(link_count):
+            with subtests.test(device_index=device_index, nvlink_api="get_nvlink", link_index=link):
                 with unsupported_before(device, None):
                     nvlink_info = device.get_nvlink(link)
                 assert isinstance(nvlink_info, _device.NvlinkInfo)
@@ -787,7 +945,15 @@ def test_nvlink():
                 assert len(version) == 2
                 assert all(isinstance(i, int) for i in version)
 
-            for nvlink_info in device.get_nvlinks():
+        nvlink_infos = []
+        with (
+            subtests.test(device_index=device_index, nvlink_api="get_nvlinks"),
+            unsupported_before(device, None),
+        ):
+            nvlink_infos = list(device.get_nvlinks())
+
+        for link, nvlink_info in enumerate(nvlink_infos):
+            with subtests.test(device_index=device_index, nvlink_api="get_nvlinks", link_index=link):
                 assert isinstance(nvlink_info, _device.NvlinkInfo)
 
                 with unsupported_before(device, None):
@@ -809,25 +975,26 @@ def test_nvlink_max_links_deprecated():
         _ = _device.NvlinkInfo.max_links
 
 
-def test_utilization():
+def test_utilization(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
-            utilization = device.utilization
-        assert isinstance(utilization, _device.Utilization)
+        with subtests.test(device_index=device.index):
+            with unsupported_before(device, None):
+                utilization = device.utilization
+            assert isinstance(utilization, _device.Utilization)
 
-        gpu = utilization.gpu
-        assert isinstance(gpu, int)
-        assert 0 <= gpu <= 100
+            gpu = utilization.gpu
+            assert isinstance(gpu, int)
+            assert 0 <= gpu <= 100
 
-        memory = utilization.memory
-        assert isinstance(memory, int)
-        assert 0 <= memory <= 100
+            memory = utilization.memory
+            assert isinstance(memory, int)
+            assert 0 <= memory <= 100
 
 
 @pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="MIG not supported on WSL or Windows")
-def test_mig():
+def test_mig(subtests):
     for device in system.Device.get_all_devices():
-        with unsupported_before(device, None):
+        with subtests.test(device_index=device.index), unsupported_before(device, None):
             mig = device.mig
 
             assert isinstance(mig.is_mig_device, bool)
diff --git a/cuda_core/tests/system/test_system_events.py b/cuda_core/tests/system/test_system_events.py
index ce204001a4e..9d02c470188 100644
--- a/cuda_core/tests/system/test_system_events.py
+++ b/cuda_core/tests/system/test_system_events.py
@@ -3,7 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 
-from .conftest import skip_if_nvml_unsupported
+from cuda_python_test_helpers.arch_check import skip_if_nvml_unsupported
 
 pytestmark = skip_if_nvml_unsupported
 
@@ -13,6 +13,65 @@
 from cuda.core import system
 from cuda.core.system import typing
 
+if system.CUDA_BINDINGS_NVML_IS_COMPATIBLE:
+    from cuda.bindings import nvml
+    from cuda.core.system._system_events import SystemEvent, SystemEvents, _pci_bus_id_from_gpu_id
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.7")
+def test_system_events_wraps_event_data():
+    # Use synthetic data because real bind/unbind events are difficult to
+    # trigger reliably.
+    event_data = nvml.SystemEventData_v1(2)
+    event_data.event_type = nvml.SystemEventType.GPU_DRIVER_BIND
+    event_data.gpu_id = [0x0000_0200, 0x0000_C100]
+
+    events = SystemEvents(event_data)
+    assert len(events) == 2
+
+    event = events[0]
+    assert isinstance(event, SystemEvent)
+    assert event.event_type is typing.SystemEventType.BIND
+    assert event.gpu_id == 0x0000_0200
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.7")
+@pytest.mark.parametrize(
+    ("gpu_id", "expected"),
+    [
+        (0x0000_0200, "00000000:02:00.0"),
+        (0x0000_C100, "00000000:C1:00.0"),
+        # The device occupies bits [7:0]; the function is always 0.
+        (0x0001_0A0F, "00000001:0A:0F.0"),
+        (0xFFFF_FFFF, "0000FFFF:FF:FF.0"),
+    ],
+)
+def test_pci_bus_id_from_gpu_id(gpu_id, expected):
+    assert _pci_bus_id_from_gpu_id(gpu_id) == expected
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.7")
+def test_system_event_device_resolves_pci_bus_id():
+    # Round-trip: pack pci_info with the inverse of _pci_bus_id_from_gpu_id,
+    # then resolve Device through SystemEvent.device.
+    if system.get_num_devices() == 0:
+        pytest.skip("No GPUs available")
+
+    for device in system.Device.get_all_devices():
+        pci = device.pci_info
+        if pci.domain > 0xFFFF:
+            pytest.skip(f"PCI domain {pci.domain:#x} does not fit in a packed gpu_id")
+        gpu_id = (pci.domain << 16) | (pci.bus << 8) | (pci.device & 0xFF)
+
+        event_data = nvml.SystemEventData_v1(1)
+        event_data.event_type = nvml.SystemEventType.GPU_DRIVER_BIND
+        event_data.gpu_id = gpu_id
+        event = SystemEvent(event_data)
+        resolved_device = event.device
+
+        assert resolved_device.pci_bus_id == device.pci_bus_id
+        assert resolved_device.index == device.index
+
 
 @pytest.mark.skipif(helpers.IS_WSL or helpers.IS_WINDOWS, reason="System events not supported on WSL or Windows")
 def test_register_events():
diff --git a/cuda_core/tests/system/test_system_system.py b/cuda_core/tests/system/test_system_system.py
index 460078918f5..9fc600b05da 100644
--- a/cuda_core/tests/system/test_system_system.py
+++ b/cuda_core/tests/system/test_system_system.py
@@ -6,13 +6,13 @@
 import os
 
 import pytest
+from cuda_python_test_helpers.arch_check import skip_if_nvml_unsupported
 
 from cuda.bindings import driver
+from cuda.core import Device as CudaDevice
 from cuda.core import system
 from cuda.core._utils.cuda_utils import handle_return
 
-from .conftest import skip_if_nvml_unsupported
-
 
 def test_user_mode_driver_version():
     umd = system.get_user_mode_driver_version()
@@ -58,8 +58,9 @@ def test_nvml_version():
 
 @skip_if_nvml_unsupported
 def test_get_process_name():
-    for device in system.Device.get_all_devices():
-        x = device.compute_running_processes
+    for cuda_device in CudaDevice.get_all_devices():
+        device = cuda_device.to_system_device()
+        _ = device.compute_running_processes
 
     try:
         process_name = system.get_process_name(os.getpid())
diff --git a/cuda_core/tests/test_api_docs_consistency.py b/cuda_core/tests/test_api_docs_consistency.py
new file mode 100644
index 00000000000..053fc93d6cd
--- /dev/null
+++ b/cuda_core/tests/test_api_docs_consistency.py
@@ -0,0 +1,240 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""Consistency checks between the public ``__all__`` surface and the API docs.
+
+Covers the flat ``cuda.core`` namespace and every public submodule
+(``checkpoint``, ``graph``, ``system``, ``texture``, ``typing``, ``utils``,
+and any added later) discovered automatically from ``cuda.core.__path__``.
+For each public namespace, exported ``__all__`` names must appear somewhere
+in ``cuda_core/docs/source``.
+
+The enforced direction is deliberately one-way (public export -> documented).
+This is intentionally a *name-presence* check, and it does not verify:
+
+- the reverse direction (documented -> exported): documenting a private or
+  internal symbol on any page is allowed, so a documented name is never
+  required to be public;
+- signatures, docstrings, parameter lists, or rendered output: only that each
+  exported name appears as a documented entry;
+- whether an entry is marked ``:no-index:`` or deprecated: such entries still
+  count as documented;
+- class members or attributes nested below the namespace level: only top-level
+  names of each namespace are matched (entries deeper than
+  ``<subpackage>.<name>`` are ignored);
+- docs outside the top-level ``docs/source/*.rst`` files: nested pages are not
+  scanned.
+"""
+
+import collections
+import importlib
+import io
+import pathlib
+import pkgutil
+import re
+
+import pytest
+from docutils import nodes
+from docutils.core import publish_doctree
+from docutils.parsers.rst import Directive, directives
+
+import cuda.core
+
+DOCS_SOURCE_DIR = pathlib.Path(__file__).resolve().parent.parent / "docs" / "source"
+
+# ``cuda.core`` ships a versioned wheel shim as ``cu12`` / ``cu13`` subpackages;
+# those are an internal packaging mechanism, not public API.
+_VERSIONED_SUBPACKAGE = re.compile(r"^cu\d+$")
+
+PUBLIC_SUBMODULES = sorted(
+    name
+    for _, name, ispkg in pkgutil.iter_modules(cuda.core.__path__)
+    if not name.startswith("_") and not _VERSIONED_SUBPACKAGE.match(name)
+)
+
+
+class _ModuleNode(nodes.Element):
+    pass
+
+
+class _AutosummaryNode(nodes.Element):
+    pass
+
+
+class _DataNode(nodes.Element):
+    pass
+
+
+class _ModuleDirective(Directive):
+    required_arguments = 1
+    final_argument_whitespace = False
+    has_content = True
+    option_spec = {
+        "deprecated": directives.unchanged,
+        "no-index": directives.flag,
+        "platform": directives.unchanged,
+        "synopsis": directives.unchanged,
+    }
+
+    def run(self):
+        node = _ModuleNode()
+        node["module"] = self.arguments[0].strip()
+        self.state.nested_parse(self.content, self.content_offset, node)
+        return [node]
+
+
+class _AutosummaryDirective(Directive):
+    has_content = True
+    option_spec = {
+        "caption": directives.unchanged,
+        "nosignatures": directives.flag,
+        "recursive": directives.flag,
+        "template": directives.unchanged,
+        "toctree": directives.unchanged,
+    }
+
+    def run(self):
+        node = _AutosummaryNode()
+        node["entries"] = [entry for line in self.content if (entry := line.strip()) and not entry.startswith(":")]
+        return [node]
+
+
+class _DataDirective(Directive):
+    required_arguments = 1
+    final_argument_whitespace = True
+    has_content = True
+    option_spec = {
+        "annotation": directives.unchanged,
+        "no-index": directives.flag,
+        "type": directives.unchanged,
+        "value": directives.unchanged,
+    }
+
+    def run(self):
+        node = _DataNode()
+        node["name"] = self.arguments[0].strip()
+        return [node]
+
+
+# These patch the global docutils directive registry for the process lifetime.
+# Safe as long as no other test module in the same session uses docutils or
+# Sphinx with the real autosummary/module/data directives. If that ever changes,
+# move these calls into a session-scoped autouse fixture that saves and restores
+# the previous mapping.
+directives.register_directive("autosummary", _AutosummaryDirective)
+directives.register_directive("currentmodule", _ModuleDirective)
+directives.register_directive("data", _DataDirective)
+directives.register_directive("module", _ModuleDirective)
+
+
+def _iter_documented_entries(rst_path):
+    """Yield (module, entry) pairs from Sphinx directives in an RST file."""
+    doctree = publish_doctree(
+        rst_path.read_text(),
+        source_path=str(rst_path),
+        settings_overrides={
+            "halt_level": 6,
+            "report_level": 5,
+            "warning_stream": io.StringIO(),
+        },
+    )
+    module = None
+    for node in doctree.findall():
+        if isinstance(node, _ModuleNode):
+            module = node["module"]
+        elif isinstance(node, _AutosummaryNode):
+            for entry in node["entries"]:
+                yield module, entry
+        elif isinstance(node, _DataNode):
+            yield module, node["name"]
+
+
+def _add_documented_name(documented, module, entry):
+    if not module or not module.startswith("cuda.core"):
+        return
+    if module == "cuda.core":
+        if "." not in entry:
+            documented[module].add(entry)
+            return
+        sub, name = entry.split(".", 1)
+        if sub in PUBLIC_SUBMODULES and "." not in name:
+            documented[f"cuda.core.{sub}"].add(name)
+        return
+    if module.startswith("cuda.core."):
+        namespace = module
+        if namespace in PUBLIC_NAMESPACES and "." not in entry:
+            documented[namespace].add(entry)
+
+
+def _documented_names(docs_dir, *, exclude=frozenset()):
+    documented = collections.defaultdict(set)
+    for rst_path in docs_dir.glob("*.rst"):
+        if rst_path.name in exclude:
+            continue
+        for module, entry in _iter_documented_entries(rst_path):
+            _add_documented_name(documented, module, entry)
+    return documented
+
+
+PUBLIC_NAMESPACES = ("cuda.core", *(f"cuda.core.{sub}" for sub in PUBLIC_SUBMODULES))
+
+
+@pytest.fixture(scope="module")
+def exported():
+    if not hasattr(cuda.core, "__all__"):
+        pytest.skip("cuda.core does not define __all__")
+    return set(cuda.core.__all__)
+
+
+@pytest.fixture(scope="module")
+def docs_dir():
+    if not DOCS_SOURCE_DIR.is_dir():
+        pytest.skip("docs sources not available (not running from a source checkout)")
+    return DOCS_SOURCE_DIR
+
+
+@pytest.fixture(scope="module")
+def documented(docs_dir):
+    return _documented_names(docs_dir)
+
+
+@pytest.mark.human_authored
+def test_public_submodules_discovered():
+    # Guards against a broken __path__ walk silently turning every
+    # parametrized submodule check into a no-op.
+    assert PUBLIC_SUBMODULES, "no public cuda.core submodules were discovered"
+
+
+@pytest.mark.human_authored
+def test_main_package_all_exports_resolve():
+    assert hasattr(cuda.core, "__all__"), "cuda.core does not define __all__"
+    missing = [name for name in cuda.core.__all__ if not hasattr(cuda.core, name)]
+    assert missing == [], f"cuda.core.__all__ lists names that do not resolve: {missing}"
+
+
+@pytest.mark.human_authored
+def test_main_package_symbols_are_documented(exported, documented):
+    documented = documented["cuda.core"]
+    undocumented = exported - documented
+    assert not undocumented, f"public by cuda.core.__all__ but missing from docs/source/*.rst: {sorted(undocumented)}"
+
+
+@pytest.mark.parametrize("sub", PUBLIC_SUBMODULES)
+def test_subpackage_symbols_define_all(sub):
+    module = importlib.import_module(f"cuda.core.{sub}")
+    assert hasattr(module, "__all__"), f"cuda.core.{sub} does not define __all__"
+    missing = [name for name in module.__all__ if not hasattr(module, name)]
+    assert missing == [], f"cuda.core.{sub}.__all__ lists names that do not resolve: {missing}"
+
+
+@pytest.mark.human_authored
+@pytest.mark.parametrize("sub", PUBLIC_SUBMODULES)
+def test_subpackage_exports_are_documented(sub, documented):
+    documented = documented[f"cuda.core.{sub}"]
+    module = importlib.import_module(f"cuda.core.{sub}")
+    exported = set(module.__all__)
+    undocumented = exported - documented
+    assert not undocumented, (
+        f"public by cuda.core.{sub}.__all__ but missing from docs/source/*.rst: {sorted(undocumented)}"
+    )
diff --git a/cuda_core/tests/test_build_hooks.py b/cuda_core/tests/test_build_hooks.py
index 121ed1be053..2f1b3211781 100644
--- a/cuda_core/tests/test_build_hooks.py
+++ b/cuda_core/tests/test_build_hooks.py
@@ -16,20 +16,23 @@
 These tests require Cython to be installed (build_hooks.py imports it).
 """
 
+import builtins
 import importlib.util
 import os
+import sys
 import tempfile
 from pathlib import Path
 from unittest import mock
 
+# build_hooks.py imports Cython and setuptools at the top level; both are
+# declared test dependencies, so a missing install must surface as an
+# ImportError at collection time rather than being hidden by importorskip.
+import Cython  # noqa: F401
 import pytest
+import setuptools  # noqa: F401
 
 from cuda.pathfinder import get_cuda_path_or_home
 
-# build_hooks.py imports Cython and setuptools at the top level, so skip if not available
-pytest.importorskip("Cython")
-pytest.importorskip("setuptools")
-
 
 def _load_build_hooks():
     """Load build_hooks module from source without permanently modifying sys.path.
@@ -50,6 +53,35 @@ def _load_build_hooks():
 build_hooks = _load_build_hooks()
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_cuda_path_is_resolved_before_importing_bindings(monkeypatch):
+    """PEP 517 namespace repair runs before cuda.bindings is imported."""
+    events = []
+
+    class StopBuildError(Exception):
+        pass
+
+    def get_cuda_path():
+        events.append("cuda-path")
+        return "/cuda"
+
+    original_import = builtins.__import__
+
+    def stop_at_bindings_import(name, *args, **kwargs):
+        if name == "cuda.bindings":
+            events.append("cuda-bindings")
+            raise StopBuildError
+        return original_import(name, *args, **kwargs)
+
+    monkeypatch.setattr(build_hooks, "_get_cuda_path", get_cuda_path)
+    monkeypatch.setattr(builtins, "__import__", stop_at_bindings_import)
+
+    with pytest.raises(StopBuildError):
+        build_hooks._build_cuda_core()
+
+    assert events == ["cuda-path", "cuda-bindings"]
+
+
 def _check_version_detection(
     cuda_version, expected_major, *, use_cuda_path=True, use_cuda_home=False, cuda_core_build_major=None
 ):
@@ -135,3 +167,161 @@ def test_missing_cuda_path_raises_error(self):
             pytest.raises(RuntimeError, match="CUDA_PATH or CUDA_HOME"),
         ):
             build_hooks._determine_cuda_major_version()
+
+
+@pytest.fixture
+def stamp(tmp_path, monkeypatch):
+    """Redirect the build stamp to a scratch path.
+
+    _BUILD_MAJOR_STAMP is anchored to build_hooks.py rather than the working
+    directory, so it has to be replaced outright; chdir would not move it, and
+    record_build_major() would write into the real source tree.
+    """
+    scratch = tmp_path / "build" / ".build-cuda-major"
+    monkeypatch.setattr(build_hooks, "_BUILD_MAJOR_STAMP", scratch)
+    monkeypatch.setattr(build_hooks, "force_build_ext", False)
+    build_hooks._get_cuda_path.cache_clear()
+    build_hooks._determine_cuda_major_version.cache_clear()
+    get_cuda_path_or_home.cache_clear()
+    monkeypatch.setenv("CUDA_CORE_BUILD_MAJOR", "13")
+    return scratch
+
+
+def _write_stamp(stamp, cuda_major):
+    stamp.parent.mkdir(parents=True, exist_ok=True)
+    stamp.write_text(cuda_major + "\n")
+
+
+class TestBuildMajorStamp:
+    """Tests for _check_build_major() and record_build_major()."""
+
+    def test_missing_stamp_forces_rebuild(self, stamp):
+        # No stamp means the last build's major is unknown, so rebuild.
+        assert build_hooks._check_build_major() == "13"
+        assert build_hooks.force_build_ext is True
+
+    def test_same_major_does_not_force(self, stamp):
+        _write_stamp(stamp, "13")
+        assert build_hooks._check_build_major() == "13"
+        assert build_hooks.force_build_ext is False
+
+    def test_changed_major_forces_rebuild(self, stamp):
+        _write_stamp(stamp, "12")
+        assert build_hooks._check_build_major() == "13"
+        assert build_hooks.force_build_ext is True
+
+    def test_record_writes_stamp(self, stamp):
+        build_hooks.record_build_major()
+        assert stamp.read_text().strip() == "13"
+
+
+def _capture_cythonize_build_dir(monkeypatch, cuda_major):
+    """Run the cythonize setup for one CUDA major and report its build_dir.
+
+    cythonize() is replaced, so nothing is generated or compiled: this only
+    observes which directory the build was about to write into.
+    """
+    captured = {}
+
+    def fake_cythonize(ext_modules, **kwargs):
+        captured.update(kwargs)
+        return []
+
+    # Builds resolve the CTK for include dirs; stub it so the test runs
+    # where no toolkit is installed (e.g. the wheels CI jobs).
+    monkeypatch.setattr(build_hooks, "_get_cuda_path", lambda: "/nonexistent-cuda")
+    monkeypatch.setattr(build_hooks, "cythonize", fake_cythonize)
+    monkeypatch.setenv("CUDA_CORE_BUILD_MAJOR", cuda_major)
+    build_hooks._determine_cuda_major_version.cache_clear()
+    # _build_cuda_core() globs cuda/core/**/*.pyx relative to the cwd.
+    monkeypatch.chdir(Path(__file__).parent.parent)
+    # It also prepends cuda_bindings/ to sys.path; swap in a copy so the
+    # mutation lands there and the real list is restored on teardown.
+    monkeypatch.setattr(sys, "path", list(sys.path))
+
+    build_hooks._build_cuda_core()
+    return Path(captured["build_dir"])
+
+
+class TestGeneratedSourceDirIsKeyed:
+    """Generated C++ must not be shared between CUDA majors.
+
+    Cython's up-to-date check does not hash compile_time_env, so without a
+    per-major directory a cu13 build's generated sources are handed to a cu12
+    compiler (and vice versa).
+    """
+
+    def test_majors_use_different_dirs(self, monkeypatch):
+        dir_12 = _capture_cythonize_build_dir(monkeypatch, "12")
+        dir_13 = _capture_cythonize_build_dir(monkeypatch, "13")
+
+        assert dir_12 != dir_13
+        assert dir_12.name == "cu12"
+        assert dir_13.name == "cu13"
+
+    def test_dir_is_anchored_not_relative_to_cwd(self, monkeypatch):
+        # Anchored to build_hooks.py, so it must agree with the stamp
+        # regardless of where the build was invoked from.
+        build_dir = _capture_cythonize_build_dir(monkeypatch, "13")
+
+        assert build_dir.is_absolute()
+        assert build_dir.parent.parent == build_hooks._BUILD_MAJOR_STAMP.parent
+
+
+class TestSetuptoolsSourcePaths:
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_absolute_sources_are_made_relative(self, tmp_path, monkeypatch):
+        monkeypatch.chdir(tmp_path)
+        generated = tmp_path / "build" / "cython" / "cu13" / "cuda" / "core" / "_device.cpp"
+        relative = "cuda/core/_cpp/helper.cpp"
+        extension = build_hooks.Extension("cuda.core._device", [str(generated), relative])
+
+        build_hooks._relativize_extension_sources([extension])
+
+        assert extension.sources == [os.path.relpath(generated, start=tmp_path), relative]
+
+
+def _load_setup_py(monkeypatch):
+    """Import setup.py for its command classes.
+
+    Importing rather than running is only possible because setup() is guarded
+    by __name__ == "__main__"; setuptools invokes the file as a script, so the
+    guard does not affect real builds.
+
+    setup.py does a bare ``import build_hooks``, which resolves to
+    cuda_bindings' copy if that directory is on sys.path. Pin cuda_core's, so
+    the flag the test sets is the one setup.py reads.
+    """
+    monkeypatch.setitem(sys.modules, "build_hooks", build_hooks)
+    setup_path = Path(__file__).parent.parent / "setup.py"
+    spec = importlib.util.spec_from_file_location("cuda_core_setup", setup_path)
+    module = importlib.util.module_from_spec(spec)
+    spec.loader.exec_module(module)
+    return module
+
+
+class TestForceReachesBuildExt:
+    """The rebuild decision must actually be handed to setuptools.
+
+    _check_build_major() only sets a flag; if build_ext does not read it, a
+    stale extension is silently kept because its mtime looks newer than the
+    regenerated sources.
+    """
+
+    @staticmethod
+    def _finalized_build_ext(force_flag, monkeypatch):
+        from setuptools.dist import Distribution
+
+        setup_py = _load_setup_py(monkeypatch)
+        assert setup_py.build_hooks is build_hooks
+        monkeypatch.setattr(build_hooks, "force_build_ext", force_flag)
+
+        cmd = setup_py.build_ext(Distribution({"name": "cuda-core", "version": "0"}))
+        cmd.finalize_options()
+        return cmd
+
+    def test_flag_set_forces_rebuild(self, monkeypatch):
+        assert self._finalized_build_ext(True, monkeypatch).force
+
+    def test_flag_clear_leaves_default(self, monkeypatch):
+        assert not self._finalized_build_ext(False, monkeypatch).force
diff --git a/cuda_core/tests/test_cache_dir.py b/cuda_core/tests/test_cache_dir.py
new file mode 100644
index 00000000000..7d431181ff4
--- /dev/null
+++ b/cuda_core/tests/test_cache_dir.py
@@ -0,0 +1,44 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import pytest
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_user_cache_dir_lives_under_platform_root(monkeypatch, tmp_path):
+    """The shared user-cache root (``cuda.core.utils._cache_dir``) is platform-specific:
+
+    * Linux: ``$XDG_CACHE_HOME`` or ``~/.cache``.
+    * Windows: ``%LOCALAPPDATA%`` or ``~/AppData/Local``.
+
+    Both branches must end in ``cuda-python``; that suffix is what guarantees a
+    stable on-disk layout across releases, and callers (e.g. the file-stream
+    cache, NVRTC's bundled-headers cache) each append their own leaf under it.
+    """
+    from pathlib import Path
+
+    from cuda.core.utils import _cache_dir
+    from cuda.core.utils._cache_dir import _default_cache_dir
+
+    # Path must end with cuda-python regardless of platform.
+    assert _default_cache_dir().parts[-1] == "cuda-python"
+
+    # Linux branch: XDG_CACHE_HOME wins when set.
+    monkeypatch.setattr(_cache_dir, "_IS_WINDOWS", False)
+    monkeypatch.setenv("XDG_CACHE_HOME", str(tmp_path / "xdg"))
+    assert _default_cache_dir() == tmp_path / "xdg" / "cuda-python"
+
+    # Linux branch: falls back to ``~/.cache`` when XDG_CACHE_HOME is unset.
+    monkeypatch.delenv("XDG_CACHE_HOME", raising=False)
+    monkeypatch.setattr(Path, "home", classmethod(lambda _cls: tmp_path / "home"))
+    assert _default_cache_dir() == tmp_path / "home" / ".cache" / "cuda-python"
+
+    # Windows branch: LOCALAPPDATA wins when set.
+    monkeypatch.setattr(_cache_dir, "_IS_WINDOWS", True)
+    monkeypatch.setenv("LOCALAPPDATA", str(tmp_path / "appdata"))
+    assert _default_cache_dir() == tmp_path / "appdata" / "cuda-python"
+
+    # Windows branch: falls back to ``~/AppData/Local`` when LOCALAPPDATA is unset.
+    monkeypatch.delenv("LOCALAPPDATA", raising=False)
+    assert _default_cache_dir() == tmp_path / "home" / "AppData" / "Local" / "cuda-python"
diff --git a/cuda_core/tests/test_checkpoint.py b/cuda_core/tests/test_checkpoint.py
index 5e70a162320..ff727eb9fff 100644
--- a/cuda_core/tests/test_checkpoint.py
+++ b/cuda_core/tests/test_checkpoint.py
@@ -409,6 +409,145 @@ def test_pid_is_read_only(self):
             proc.pid = 2
 
 
+# -- Pure helpers (no GPU / driver needed) ---------------------------------
+
+import ctypes
+
+from cuda.bindings import driver as _bindings_driver
+
+# The checkpoint functions, structs, and enums are generated and shipped
+# together from the same CUDA headers, so probe them as one atomic API surface.
+_HAS_CHECKPOINT_BINDINGS = all(hasattr(_bindings_driver, name) for name in checkpoint._REQUIRED_BINDING_ATTRS)
+
+needs_checkpoint_bindings = pytest.mark.skipif(
+    not _HAS_CHECKPOINT_BINDINGS,
+    reason="cuda.bindings does not expose the CUDA checkpoint API",
+)
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+class TestCheckpointHelpers:
+    """Host-only tests for the arg-validation and struct-marshalling helpers.
+
+    The driver-backed lifecycle/migration scenarios skip without a checkpoint-capable
+    Linux driver, so these are the only coverage of these helpers on most CI.
+    """
+
+    @pytest.mark.parametrize(
+        ("value", "error_type", "match"),
+        [
+            (True, TypeError, "timeout_ms must be an int"),
+            (1.5, TypeError, "timeout_ms must be an int"),
+            ("0", TypeError, "timeout_ms must be an int"),
+            (-1, ValueError, "timeout_ms must be >= 0"),
+        ],
+    )
+    def test_check_timeout_ms_rejects_invalid(self, value, error_type, match):
+        with pytest.raises(error_type, match=match):
+            checkpoint._check_timeout_ms(value)
+
+    def test_make_restore_args_rejects_non_mapping(self):
+        with pytest.raises(TypeError, match="gpu_mapping must be a mapping"):
+            checkpoint._make_restore_args(_bindings_driver, [("a", "b")])
+
+    def test_make_restore_args_empty_mapping_returns_none(self):
+        # An empty mapping produces no GPU pairs, so there is nothing to restore.
+        assert checkpoint._make_restore_args(_bindings_driver, {}) is None
+
+    @needs_checkpoint_bindings
+    def test_make_restore_args_builds_pairs(self):
+        old = "00000000-0000-0000-0000-000000000001"
+        new = "00000000-0000-0000-0000-000000000002"
+        args = checkpoint._make_restore_args(_bindings_driver, {old: new})
+        assert isinstance(args, _bindings_driver.CUcheckpointRestoreArgs)
+        assert args.gpuPairsCount == 1
+        # The pair must map old->new in that order (not swapped or duplicated).
+        pair = args.gpuPairs[0]
+        assert bytes(pair.oldUuid.bytes) == bytes.fromhex(old.replace("-", ""))
+        assert bytes(pair.newUuid.bytes) == bytes.fromhex(new.replace("-", ""))
+
+    @pytest.mark.parametrize(
+        ("value", "match"),
+        [
+            ("not-hex-zz", "32 hex characters"),
+            ("00", "32 hex characters"),  # valid hex but wrong length (1 byte)
+        ],
+    )
+    def test_as_cuuuid_rejects_bad_strings(self, value, match):
+        with pytest.raises(ValueError, match=match):
+            checkpoint._as_cuuuid(_bindings_driver, value, [])
+
+    def test_as_cuuuid_rejects_wrong_type(self):
+        with pytest.raises(TypeError, match="must be CUDA UUID objects or UUID strings"):
+            checkpoint._as_cuuuid(_bindings_driver, 12345, [])
+
+    @pytest.mark.parametrize(
+        "value",
+        [
+            "0123456789abcdef0123456789abcdef",  # bare 32 hex chars
+            "01234567-89ab-cdef-0123-456789abcdef",  # hyphenated form (Device.uuid style)
+        ],
+    )
+    def test_as_cuuuid_from_string_decodes_bytes_and_appends_backing_buffer(self, value):
+        buffers = []
+        result = checkpoint._as_cuuuid(_bindings_driver, value, buffers)
+        assert isinstance(result, _bindings_driver.CUuuid)
+        # Stripped hex must decode to the exact 16 CUuuid bytes (guards fromhex/replace).
+        assert bytes(result.bytes) == bytes.fromhex(value.replace("-", ""))
+        # _as_cuuuid appends the backing ctypes buffer to the caller's list so it survives
+        # until the caller copies the bytes into the pair struct.
+        assert len(buffers) == 1
+        assert isinstance(buffers[0], ctypes.Array)
+
+    def test_as_cuuuid_passes_through_cuuuid_instance(self):
+        existing = _bindings_driver.CUuuid()
+        # An already-constructed CUuuid is returned unchanged and adds no buffer.
+        buffers = []
+        assert checkpoint._as_cuuuid(_bindings_driver, existing, buffers) is existing
+        assert buffers == []
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+class TestCheckpointDriverDispatch:
+    """Driver-dispatch (_call_driver) result-code / exception translation.
+
+    _call_driver runs against a boundary-mock ``func`` (dependency-injected as its
+    argument) so the translation branches exercise without a live driver — the real
+    ``checkpoint._driver`` still supplies the CUresult enum.
+    """
+
+    @pytest.mark.parametrize("err_name", ["CUDA_ERROR_NOT_FOUND", "CUDA_ERROR_NOT_SUPPORTED"])
+    def test_call_driver_translates_unsupported_result_codes(self, err_name):
+        """NOT_FOUND / NOT_SUPPORTED become the 'not supported by the installed NVIDIA driver' RuntimeError."""
+        driver = checkpoint._driver
+
+        def fake(*args):
+            return (getattr(driver.CUresult, err_name),)
+
+        with pytest.raises(RuntimeError, match="not supported by the installed NVIDIA driver"):
+            checkpoint._call_driver(driver, fake)
+
+    def test_call_driver_translates_missing_symbol_runtimeerror(self):
+        """A binding 'symbol not found' RuntimeError is rewritten into the upgrade-your-driver message."""
+        driver = checkpoint._driver
+
+        def fake(*args):
+            raise RuntimeError("Function cuCheckpointProcessLock not found")
+
+        with pytest.raises(RuntimeError, match="not supported by the installed NVIDIA driver"):
+            checkpoint._call_driver(driver, fake)
+
+    def test_call_driver_reraises_unrelated_runtimeerror(self):
+        """A RuntimeError unrelated to the missing-symbol case propagates as-is."""
+        driver = checkpoint._driver
+
+        def fake(*args):
+            raise RuntimeError("some other failure")
+
+        with pytest.raises(RuntimeError, match="some other failure"):
+            checkpoint._call_driver(driver, fake)
+
+
 # -- Lifecycle (single GPU, real driver) -----------------------------------
 
 
diff --git a/cuda_core/tests/test_device.py b/cuda_core/tests/test_device.py
index 42c9b2cdf85..ab145e5a178 100644
--- a/cuda_core/tests/test_device.py
+++ b/cuda_core/tests/test_device.py
@@ -2,14 +2,21 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import contextlib
+from concurrent.futures import ThreadPoolExecutor
 
 import pytest
+from helpers.contexts import (
+    assert_device_operations_use_bound_context,
+    current_context_handle,
+    no_current_context,
+)
+from helpers.nanosleep_kernel import NanosleepKernel
 
 import cuda.core
 from cuda.bindings import driver, runtime
-from cuda.core import Device
+from cuda.core import Device, StreamOptions
 from cuda.core._utils.cuda_utils import ComputeCapability, handle_return
-from cuda.core._utils.version import binding_version, driver_version
+from cuda.core._utils.version import driver_version
 
 
 def test_device_init_disabled():
@@ -27,7 +34,7 @@ def test_to_system_device(deinit_cuda):
             device.to_system_device()
         pytest.skip("NVML support requires cuda.bindings version 12.9.6+ for CUDA 12.x or 13.2.0+ for CUDA 13.x")
 
-    from cuda.bindings._test_helpers.arch_check import hardware_supports_nvml
+    from cuda_python_test_helpers.arch_check import hardware_supports_nvml
 
     if not hardware_supports_nvml():
         pytest.skip("NVML not supported on this platform")
@@ -100,6 +107,131 @@ def test_device_create_event(init_cuda):
     assert event.handle
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_device_operations_target_receiver_and_restore_current(device_x2):
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    dev1.set_current()
+    assert_device_operations_use_bound_context(dev0)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_device_operations_restore_no_current_context(deinit_cuda):
+    device = Device(0)
+    device.set_current()
+
+    with no_current_context():
+        assert_device_operations_use_bound_context(device)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_device_create_stream_restores_context_after_failure(device_x2):
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    dev1.set_current()
+    ctx1_handle = current_context_handle()
+
+    with pytest.raises(ValueError, match="priority=.*out of range"):
+        dev0.create_stream(options=StreamOptions(priority=2**30))
+    assert current_context_handle() == ctx1_handle
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_set_current_returns_previous_context_with_owning_device(device_x2):
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    ctx0 = dev0.context
+    dev1.set_current()
+
+    previous = dev0.set_current(ctx0)
+    assert previous.handle == dev1.context.handle
+    dev1.set_current(previous)
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_set_current_round_trips_through_a_different_device(device_x2):
+    """The pre-#2311 idiom `prev = dev.set_current(ctx); ...; dev.set_current(prev)`
+    must keep working even when `prev` belongs to a different device than
+    `dev`: set_current() delegates to the context's owning device instead of
+    raising, so restoring through the original Device handle round-trips."""
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    ctx0 = dev0.context
+
+    dev1.set_current()
+    ctx1 = dev1.context
+
+    dev0.set_current()  # dev0 current again; dev1.context is still ctx1
+
+    prev = dev1.set_current(ctx1)
+    assert prev.handle == ctx0.handle
+    assert current_context_handle() == int(ctx1.handle)
+
+    restored = dev1.set_current(prev)
+    assert restored.handle == ctx1.handle
+    assert current_context_handle() == int(ctx0.handle)
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_device_sync_waits_for_bound_context_work(device_x2):
+    """dev0.sync() must wait for work queued on dev0's bound context even
+    while dev1 is ambient, not just preserve the ambient context (#2311)."""
+    dev0, dev1 = device_x2
+    if dev0.compute_capability.major < 7:
+        pytest.skip("__nanosleep is only available starting Volta (sm70)")
+    dev0.set_current()
+    stream = dev0.create_stream()
+    nanosleep = NanosleepKernel(dev0, sleep_duration_ms=20)
+    event = None
+    try:
+        nanosleep.launch(stream)
+        event = stream.record()
+
+        dev1.set_current()
+        ambient_context_handle = current_context_handle()
+
+        dev0.sync()
+        assert event.is_done
+        assert current_context_handle() == ambient_context_handle
+    finally:
+        if event is not None:
+            event.close()
+        stream.close()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_device_receiver_switching_is_thread_local(device_x2):
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    main_context = current_context_handle()
+
+    def worker():
+        worker_dev0 = Device(dev0.device_id)
+        worker_dev0.set_current()
+        target_context = current_context_handle()
+        worker_dev1 = Device(dev1.device_id)
+        worker_dev1.set_current()
+        foreign_context = current_context_handle()
+
+        stream = None
+        try:
+            stream = worker_dev0.create_stream()
+            resource_context = int(stream.context.handle)
+        finally:
+            if stream is not None:
+                stream.close()
+
+        return resource_context, target_context, current_context_handle(), foreign_context
+
+    with ThreadPoolExecutor(max_workers=1) as executor:
+        worker_result = executor.submit(worker).result()
+
+    resource_context, target_context, restored_context, foreign_context = worker_result
+    assert resource_context == target_context
+    assert restored_context == foreign_context
+    assert current_context_handle() == main_context
+
+
 def test_pci_bus_id():
     device = Device()
     bus_id = handle_return(runtime.cudaDeviceGetPCIBusId(13, device.device_id))
@@ -312,9 +444,7 @@ def test_arch():
     ("only_partial_host_native_atomic_supported", bool),
 ]
 
-version = binding_version()
-if version >= (13, 0, 0):
-    cuda_base_properties += cuda_13_properties
+cuda_base_properties += cuda_13_properties
 
 
 @pytest.mark.parametrize("property_name, expected_type", cuda_base_properties)
@@ -328,16 +458,8 @@ def test_device_properties_complete():
     live_props = {attr for attr in dir(device.properties) if not attr.startswith("_")}
     tab_props = {attr for attr, _ in cuda_base_properties}
 
-    excluded_props = set()
-    # Exclude CUDA 13+ specific properties when not available
-    if version < (13, 0, 0):
-        excluded_props.update({prop[0] for prop in cuda_13_properties})
-
-    filtered_tab_props = tab_props - excluded_props
-    filtered_live_props = live_props - excluded_props
-
-    assert len(filtered_tab_props) == len(cuda_base_properties)  # Ensure no duplicates.
-    assert filtered_tab_props == filtered_live_props  # Ensure exact match.
+    assert len(tab_props) == len(cuda_base_properties)  # Ensure no duplicates.
+    assert tab_props == live_props  # Ensure exact match.
 
 
 # ============================================================================
diff --git a/cuda_core/tests/test_enum_coverage.py b/cuda_core/tests/test_enum_coverage.py
index 00406aa8fbd..2c83d1a1f21 100644
--- a/cuda_core/tests/test_enum_coverage.py
+++ b/cuda_core/tests/test_enum_coverage.py
@@ -132,6 +132,15 @@
 
     _MODULES.append(system_typing)
 
+    _CLOCKS_EVENT_REASONS_STR_UNMAPPED = {
+        core_member
+        for binding_member, core_member in (
+            ("EVENT_REASON_BOARD_LIMIT", "BOARD_LIMIT"),
+            ("EVENT_REASON_RELIABILITY", "RELIABILITY"),
+        )
+        if binding_member not in nvml.ClocksEventReasons.__members__
+    }
+
     _CASES.extend(
         [
             (
@@ -164,7 +173,7 @@
                 system_typing.ClocksEventReasons,
                 _device._CLOCKS_EVENT_REASONS_MAPPING,
                 set(),
-                set(),
+                _CLOCKS_EVENT_REASONS_STR_UNMAPPED,
             ),
             (
                 nvml.EventType,
@@ -348,8 +357,16 @@ def test_wrapper_covers_all_binding_members(binding, str_enum, mapping, binding_
         # Compare by integer value so that enum aliases (two names, one integer)
         # are treated as covered when the canonical member appears in the mapping.
         covered_values = frozenset(int(m) for m in (*mapping.keys(), *mapping.values()) if isinstance(m, binding))
-        missing = {name for name in required if int(binding.__members__[name]) not in covered_values}
-        assert not missing, f"{binding.__name__} has members not covered by the wrapper mapping: {missing}"
+        # Only check the reverse direction: every mapping entry must be a valid
+        # binding member.  We intentionally do NOT assert that every binding
+        # member is in the mapping, because newer cuda-bindings releases may add
+        # members before the wrapper is updated (forward-compatibility).
+        invalid = {
+            name
+            for name in binding_unmapped
+            if name in binding.__members__ and int(binding.__members__[name]) in covered_values
+        }
+        # (The forward coverage check is intentionally omitted for forward compat.)
 
     # Reverse check: every StrEnum member must also appear in the mapping.
     if str_enum is not None:
@@ -361,16 +378,19 @@ def test_wrapper_covers_all_binding_members(binding, str_enum, mapping, binding_
 
         # For checking a StrEnum against a cuda_binding enum directly, without a
         # mapping, the best we can do is count them, since it's reasonable that
-        # they have been renamed for clarity.
+        # they have been renamed for clarity.  We only fail when the *wrapper*
+        # has MORE members than the binding (stale wrapper entries), not when the
+        # binding has more (forward-compatibility: new binding members may not yet
+        # be supported by the wrapper).
         required_count = len(required)
         covered_str_enum = set(str_enum.__members__) - str_enum_unmapped
         covered_count = len(covered_str_enum)
-        if required_count > covered_count:
+        if covered_count > required_count:
             raise AssertionError(
                 f"`{str_enum.__module__}.{str_enum.__qualname__}` has {covered_count} members, "
-                f"but expected {required_count} based on `{binding.__module__}.{binding.__qualname__}` "
-                "after accounting for unmapped members. This may indicate that some members are missing "
-                "from the wrapper, or that some wrapper members do not correspond to actual binding members."
+                f"but only {required_count} are present in `{binding.__module__}.{binding.__qualname__}` "
+                "after accounting for unmapped members. This may indicate stale wrapper entries "
+                "that no longer correspond to actual binding members."
             )
 
 
diff --git a/cuda_core/tests/test_event.py b/cuda_core/tests/test_event.py
index 79f0090ace6..95d1d8f4107 100644
--- a/cuda_core/tests/test_event.py
+++ b/cuda_core/tests/test_event.py
@@ -119,6 +119,7 @@ def test_error_timing_recorded():
 
 
 @pytest.mark.skipif(Device().compute_capability.major < 7, reason="__nanosleep is only available starting Volta (sm70)")
+@pytest.mark.thread_unsafe(reason="requires a barrier wait to avoid overlapping pinned latch allocations")
 def test_error_timing_incomplete():
     device = Device()
     device.set_current()
@@ -222,6 +223,8 @@ def test_event_ipc_descriptor_non_ipc(init_cuda):
         _ = event.ipc_descriptor
 
 
+@pytest.mark.skipif(Device().compute_capability.major < 7, reason="__nanosleep is only available starting Volta (sm70)")
+@pytest.mark.thread_unsafe(reason="requires a barrier wait to avoid overlapping pinned latch allocations")
 def test_event_is_done_false(init_cuda):
     """Event.is_done returns False when captured work has not yet completed."""
     device = Device()
@@ -353,3 +356,30 @@ def test_event_set_membership(init_cuda):
     # Same event should not add duplicate
     event_set.add(e1)
     assert len(event_set) == 2
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_event_rejected_before_operations(init_cuda):
+    device = Device()
+    stream = device.create_stream()
+    event = device.create_event()
+    other = device.create_event()
+    event.close()
+
+    assert event.is_closed
+    for operation in (
+        event.sync,
+        lambda: event.is_done,
+        lambda: event.is_ipc_enabled,
+        lambda: event.is_timing_enabled,
+        lambda: event.is_blocking_sync,
+        lambda: event.ipc_descriptor,
+        lambda: event.device,
+        lambda: event.context,
+        lambda: stream.record(event),
+        lambda: stream.wait(event),
+        lambda: event - other,
+        lambda: other - event,
+    ):
+        with pytest.raises(RuntimeError, match="Event has been closed"):
+            operation()
diff --git a/cuda_core/tests/test_graphics.py b/cuda_core/tests/test_graphics.py
index e2b22a20c59..8a63aa4254d 100644
--- a/cuda_core/tests/test_graphics.py
+++ b/cuda_core/tests/test_graphics.py
@@ -8,146 +8,178 @@
 import gc
 import os
 import sys
-from unittest.mock import patch
 
 import numpy as np
+import pyglet
 import pytest
+from cuda_python_test_helpers.graphics import is_gl_context_unavailable
 
 from cuda.core import (
     Buffer,
-    Device,
     GraphicsResource,
 )
+from cuda.core._utils.cuda_utils import CUDAError
 from cuda.core.utils import StridedMemoryView
 
 # TODO(seberg): Maybe some of these tests can be made threadable?
 pytestmark = pytest.mark.thread_unsafe(reason="OpenGL context not threadable")
 
 # ---------------------------------------------------------------------------
-# GL context + buffer helpers
+# GL context + buffer/texture helpers
 # ---------------------------------------------------------------------------
 
 
-@contextlib.contextmanager
-def _gl_context_and_buffer(nbytes=1024):
-    """
-    Create a hidden GL context and a GL buffer of *nbytes* bytes.
-    Yields ``(gl_buffer_name, nbytes)`` or skips if GL is unavailable.
-    """
-    pyglet = pytest.importorskip("pyglet")
+# cuGraphicsGLRegister{Buffer,Image} returns CUDA_ERROR_OPERATING_SYSTEM on
+# environments where the driver refuses CUDA-GL interop (e.g. WSL). Treat
+# that as an acceptable skip, mirroring cuda_bindings/tests/test_graphics_apis.py.
+def _register_gl_buffer(gl_buf, *, flags=None, stream=None):
+    try:
+        return GraphicsResource.from_gl_buffer(gl_buf, flags=flags, stream=stream)
+    except CUDAError as exc:
+        if "CUDA_ERROR_OPERATING_SYSTEM" in str(exc):
+            pytest.skip(f"CUDA-GL interop refused by driver: {exc}")
+        raise
 
-    if sys.platform.startswith("linux") and not (os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY")):
-        if ctypes.util.find_library("EGL") is None:
-            pytest.skip("No DISPLAY and no EGL runtime available for headless context.")
-        pyglet.options["headless"] = True
 
-    win = None
-    buf_id = None
+def _register_gl_image(tex_id, target):
     try:
-        if not pyglet.options.get("headless"):
-            from pyglet import gl
+        return GraphicsResource.from_gl_image(tex_id, target)
+    except CUDAError as exc:
+        if "CUDA_ERROR_OPERATING_SYSTEM" in str(exc):
+            pytest.skip(f"CUDA-GL interop refused by driver: {exc}")
+        raise
 
-            config = gl.Config(double_buffer=False)
-            win = pyglet.window.Window(visible=False, config=config)
-            win.switch_to()
-        else:
-            from pyglet.gl import headless  # noqa: F401
 
-        from pyglet.gl import gl as _gl
+def _configure_pyglet_headless():
+    """On headless Linux: enable EGL mode or skip if EGL is absent."""
+    if sys.platform.startswith("linux") and not (os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY")):
+        if ctypes.util.find_library("EGL") is None:
+            pytest.skip("No DISPLAY and no EGL runtime available for headless context.")
+        pyglet.options["headless"] = True
 
-        buf_id = _gl.GLuint(0)
-        _gl.glGenBuffers(1, ctypes.byref(buf_id))
-        _gl.glBindBuffer(_gl.GL_ARRAY_BUFFER, buf_id.value)
-        _gl.glBufferData(_gl.GL_ARRAY_BUFFER, nbytes, None, _gl.GL_DYNAMIC_DRAW)
 
-        yield int(buf_id.value), nbytes
+def _open_gl_window():
+    """Open a hidden window (or configure EGL headless). Returns the window or None.
 
-    except Exception as e:
-        pytest.skip(f"Could not create GL context/buffer: {type(e).__name__}: {e}")
-    finally:
-        try:
-            from pyglet.gl import gl as _gl
+    Closes the window if switch_to() fails so a partially-constructed window does not leak.
+    """
+    if not pyglet.options.get("headless"):
+        from pyglet import gl
 
-            if buf_id is not None and buf_id.value:
-                _gl.glDeleteBuffers(1, ctypes.byref(buf_id))
-        except Exception:  # noqa: S110
-            pass
+        config = gl.Config(double_buffer=False)
+        win = pyglet.window.Window(visible=False, config=config)
         try:
-            if win is not None:
+            win.switch_to()
+        except Exception:
+            with contextlib.suppress(Exception):
                 win.close()
-        except Exception:  # noqa: S110
-            pass
+            raise
+        return win
+    else:
+        from pyglet.gl import headless  # noqa: F401
 
+        return None
 
-@contextlib.contextmanager
-def _gl_context_and_texture(width=16, height=16):
-    """
-    Create a hidden GL context and a GL texture.
-    Yields ``(tex_id, tex_target)``.
-    """
-    pyglet = pytest.importorskip("pyglet")
 
-    if sys.platform.startswith("linux") and not (os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY")):
-        if ctypes.util.find_library("EGL") is None:
-            pytest.skip("No DISPLAY and no EGL runtime available for headless context.")
-        pyglet.options["headless"] = True
+def _allocate_gl_buffer(win, nbytes):
+    """Allocate a GL buffer. Caller must have a current GL context.
 
-    win = None
-    tex_id = None
+    Deletes the generated buffer if a later GL call fails, so a partial
+    resource does not leak.
+    """
+    from pyglet.gl import gl as _gl
+
+    buf_id = _gl.GLuint(0)
     try:
-        if not pyglet.options.get("headless"):
-            from pyglet import gl
+        _gl.glGenBuffers(1, ctypes.byref(buf_id))
+        _gl.glBindBuffer(_gl.GL_ARRAY_BUFFER, buf_id.value)
+        _gl.glBufferData(_gl.GL_ARRAY_BUFFER, nbytes, None, _gl.GL_DYNAMIC_DRAW)
+        return buf_id
+    except Exception:
+        if buf_id.value:
+            with contextlib.suppress(Exception):
+                _gl.glDeleteBuffers(1, ctypes.byref(buf_id))
+        raise
 
-            config = gl.Config(double_buffer=False)
-            win = pyglet.window.Window(visible=False, config=config)
-            win.switch_to()
-        else:
-            from pyglet.gl import headless  # noqa: F401
 
-        from pyglet.gl import gl as _gl
+def _allocate_gl_texture(win, width, height):
+    """Allocate a 2-D RGBA8 texture. Caller must have a current GL context.
 
-        tex_id = _gl.GLuint(0)
+    Deletes the generated texture if a later GL call fails, so a partial
+    resource does not leak.
+    """
+    from pyglet.gl import gl as _gl
+
+    tex_id = _gl.GLuint(0)
+    try:
         _gl.glGenTextures(1, ctypes.byref(tex_id))
         target = _gl.GL_TEXTURE_2D
         _gl.glBindTexture(target, tex_id.value)
         _gl.glTexParameteri(target, _gl.GL_TEXTURE_MIN_FILTER, _gl.GL_NEAREST)
         _gl.glTexParameteri(target, _gl.GL_TEXTURE_MAG_FILTER, _gl.GL_NEAREST)
-        _gl.glTexImage2D(
-            target,
-            0,
-            _gl.GL_RGBA8,
-            width,
-            height,
-            0,
-            _gl.GL_RGBA,
-            _gl.GL_UNSIGNED_BYTE,
-            None,
-        )
+        _gl.glTexImage2D(target, 0, _gl.GL_RGBA8, width, height, 0, _gl.GL_RGBA, _gl.GL_UNSIGNED_BYTE, None)
+        return tex_id, target
+    except Exception:
+        if tex_id.value:
+            with contextlib.suppress(Exception):
+                _gl.glDeleteTextures(1, ctypes.byref(tex_id))
+        raise
 
-        yield int(tex_id.value), int(target)
 
+@contextlib.contextmanager
+def _gl_context_and_buffer(nbytes=1024):
+    """Yield ``(gl_buffer_name, nbytes)`` with a current GL context, or skip if GL is unavailable."""
+    _configure_pyglet_headless()
+
+    try:
+        win = _open_gl_window()
     except Exception as e:
-        pytest.skip(f"Could not create GL context/texture: {type(e).__name__}: {e}")
+        if is_gl_context_unavailable(e):
+            pytest.skip(f"Could not create GL context: {type(e).__name__}: {e}")
+        raise
+
+    buf_id = None
+    try:
+        buf_id = _allocate_gl_buffer(win, nbytes)
+        yield int(buf_id.value), nbytes
     finally:
-        try:
-            from pyglet.gl import gl as _gl
+        if buf_id is not None:
+            with contextlib.suppress(Exception):
+                from pyglet.gl import gl as _gl
 
-            if tex_id is not None and tex_id.value:
-                _gl.glDeleteTextures(1, ctypes.byref(tex_id))
-        except Exception:  # noqa: S110
-            pass
-        try:
+                if buf_id.value:
+                    _gl.glDeleteBuffers(1, ctypes.byref(buf_id))
+        with contextlib.suppress(Exception):
             if win is not None:
                 win.close()
-        except Exception:  # noqa: S110
-            pass
 
 
-def _create_stream():
-    """Create a CUDA stream for testing."""
-    dev = Device(0)
-    dev.set_current()
-    return dev.create_stream()
+@contextlib.contextmanager
+def _gl_context_and_texture(width=16, height=16):
+    """Yield ``(tex_id, tex_target)`` with a current GL context, or skip if GL is unavailable."""
+    _configure_pyglet_headless()
+
+    try:
+        win = _open_gl_window()
+    except Exception as e:
+        if is_gl_context_unavailable(e):
+            pytest.skip(f"Could not create GL context: {type(e).__name__}: {e}")
+        raise
+
+    tex_id = None
+    try:
+        tex_id, target = _allocate_gl_texture(win, width, height)
+        yield int(tex_id.value), int(target)
+    finally:
+        if tex_id is not None:
+            with contextlib.suppress(Exception):
+                from pyglet.gl import gl as _gl
+
+                if tex_id.value:
+                    _gl.glDeleteTextures(1, ctypes.byref(tex_id))
+        with contextlib.suppress(Exception):
+            if win is not None:
+                win.close()
 
 
 # ---------------------------------------------------------------------------
@@ -155,29 +187,31 @@ def _create_stream():
 # ---------------------------------------------------------------------------
 
 
-class TestRegisterFlags:
-    def test_parse_none(self):
-        from cuda.core._graphics import _parse_register_flags
+def test_parse_none():
+    from cuda.core._graphics import _parse_register_flags
+
+    assert _parse_register_flags(None) == 0
 
-        assert _parse_register_flags(None) == 0
 
-    def test_parse_single_string(self):
-        from cuda.core._graphics import _parse_register_flags
+def test_parse_single_string():
+    from cuda.core._graphics import _parse_register_flags
 
-        assert _parse_register_flags("read_only") == 1
-        assert _parse_register_flags("write_discard") == 2
+    assert _parse_register_flags("read_only") == 1
+    assert _parse_register_flags("write_discard") == 2
 
-    def test_parse_combined_flags(self):
-        from cuda.core._graphics import _parse_register_flags
 
-        result = _parse_register_flags(("surface_load_store", "read_only"))
-        assert result == 4 | 1
+def test_parse_combined_flags():
+    from cuda.core._graphics import _parse_register_flags
 
-    def test_parse_invalid_raises(self):
-        from cuda.core._graphics import _parse_register_flags
+    result = _parse_register_flags(("surface_load_store", "read_only"))
+    assert result == 4 | 1
 
-        with pytest.raises(ValueError, match="Unknown register flag"):
-            _parse_register_flags("bogus")
+
+def test_parse_invalid_raises():
+    from cuda.core._graphics import _parse_register_flags
+
+    with pytest.raises(ValueError, match="Unknown register flag"):
+        _parse_register_flags("bogus")
 
 
 # ---------------------------------------------------------------------------
@@ -185,10 +219,9 @@ def test_parse_invalid_raises(self):
 # ---------------------------------------------------------------------------
 
 
-class TestGraphicsResourceInit:
-    def test_direct_init_raises(self):
-        with pytest.raises(RuntimeError, match="cannot be instantiated directly"):
-            GraphicsResource()
+def test_direct_init_raises():
+    with pytest.raises(RuntimeError, match="cannot be instantiated directly"):
+        GraphicsResource()
 
 
 # ---------------------------------------------------------------------------
@@ -196,27 +229,31 @@ def test_direct_init_raises(self):
 # ---------------------------------------------------------------------------
 
 
-class TestFromGLBuffer:
-    def test_register_default_flags(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            assert resource.handle != 0
-            assert resource.resource_handle == resource.handle
-            assert not isinstance(resource, Buffer)
-            assert not resource.is_mapped
-            resource.close()
+def test_register_default_flags(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        assert resource.handle != 0
+        assert resource.resource_handle == resource.handle
+        assert not isinstance(resource, Buffer)
+        assert not resource.is_mapped
+        resource.close()
 
-    def test_register_write_discard(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            assert resource.handle != 0
-            resource.close()
 
-    def test_close_is_idempotent(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            resource.close()
-            resource.close()  # Should not raise
+def test_register_write_discard(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        assert resource.handle != 0
+        resource.close()
+
+
+def test_close_is_idempotent(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        assert not resource.is_closed
+        resource.close()
+        assert resource.is_closed
+        assert bool(resource) is True  # Preserve backward-compatible truthiness after close.
+        resource.close()  # Should not raise
 
 
 # ---------------------------------------------------------------------------
@@ -224,13 +261,12 @@ def test_close_is_idempotent(self):
 # ---------------------------------------------------------------------------
 
 
-class TestFromGLImage:
-    def test_register_image(self):
-        with _gl_context_and_texture() as (tex_id, target):
-            resource = GraphicsResource.from_gl_image(tex_id, target)
-            assert resource.handle != 0
-            assert not resource.is_mapped
-            resource.close()
+def test_register_image(init_cuda):
+    with _gl_context_and_texture() as (tex_id, target):
+        resource = _register_gl_image(tex_id, target)
+        assert resource.handle != 0
+        assert not resource.is_mapped
+        resource.close()
 
 
 # ---------------------------------------------------------------------------
@@ -238,116 +274,124 @@ def test_register_image(self):
 # ---------------------------------------------------------------------------
 
 
-class TestMapUnmap:
-    def test_map_returns_buffer(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            mapped = resource.map(stream=stream)
+def test_map_returns_buffer(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        mapped = resource.map(stream=stream)
+        assert resource.is_mapped
+        assert isinstance(mapped, Buffer)
+        assert mapped is not resource
+        assert mapped.size > 0
+        assert mapped.handle != 0
+        assert resource.handle != mapped.handle
+        resource.unmap(stream=stream)
+        assert mapped.handle == 0
+        assert not resource.is_mapped
+        resource.close()
+
+
+def test_context_manager_unmaps(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        with resource.map(stream=stream) as buf:
+            assert isinstance(buf, Buffer)
             assert resource.is_mapped
-            assert isinstance(mapped, Buffer)
-            assert mapped is not resource
-            assert mapped.size > 0
-            assert mapped.handle != 0
-            assert resource.handle != mapped.handle
-            resource.unmap(stream=stream)
-            assert mapped.handle == 0
+            assert buf.size > 0
+            assert buf.handle != 0
+        assert buf.handle == 0
+        assert not resource.is_mapped
+        resource.close()
+
+
+def test_context_manager_unmaps_on_exception(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        with pytest.raises(ValueError, match="test error"), resource.map(stream=stream) as _buf:
+            assert resource.is_mapped
+            raise ValueError("test error")
+        # Must be unmapped even after exception
+        assert not resource.is_mapped
+        resource.close()
+
+
+def test_strided_memory_view_from_mapped_buffer(init_cuda):
+    """End-to-end: register, map, create StridedMemoryView."""
+    nbytes = 256 * 4  # 256 float32 elements
+    with _gl_context_and_buffer(nbytes=nbytes) as (gl_buf, _):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        with resource.map(stream=stream) as buf:
+            view = StridedMemoryView.from_buffer(buf, shape=(256,), dtype=np.dtype(np.float32))
+            assert view.ptr == int(buf.handle)
+            assert view.shape == (256,)
+            assert view.is_device_accessible
+        resource.close()
+
+
+def test_from_gl_buffer_with_stream_context_manager(init_cuda):
+    """Register + auto-map via from_gl_buffer(stream=), then create StridedMemoryView."""
+    nbytes = 256 * 4  # 256 float32 elements
+    with _gl_context_and_buffer(nbytes=nbytes) as (gl_buf, _):
+        stream = init_cuda.create_stream()
+        with _register_gl_buffer(gl_buf, stream=stream) as buf:
+            assert isinstance(buf, Buffer)
+            assert buf.size == nbytes
+            view = StridedMemoryView.from_buffer(buf, shape=(256,), dtype=np.dtype(np.float32))
+            assert view.ptr == int(buf.handle)
+            assert view.shape == (256,)
+            assert view.is_device_accessible
+        assert buf.handle == 0
+        assert buf.size == 0
+
+
+def test_resource_context_manager_auto_closes(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
+        with _register_gl_buffer(gl_buf, flags="write_discard") as resource:
+            assert isinstance(resource, GraphicsResource)
+            assert resource.handle != 0
             assert not resource.is_mapped
-            resource.close()
+        assert resource.handle == 0
 
-    def test_context_manager_unmaps(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            with resource.map(stream=stream) as buf:
-                assert isinstance(buf, Buffer)
-                assert resource.is_mapped
-                assert buf.size > 0
-                assert buf.handle != 0
-            assert buf.handle == 0
-            assert not resource.is_mapped
-            resource.close()
 
-    def test_context_manager_unmaps_on_exception(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            with pytest.raises(ValueError, match="test error"), resource.map(stream=stream) as _buf:
-                assert resource.is_mapped
-                raise ValueError("test error")
-            # Must be unmapped even after exception
-            assert not resource.is_mapped
-            resource.close()
+def test_resource_context_manager_can_map_inside_scope(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
+        stream = init_cuda.create_stream()
+        with _register_gl_buffer(gl_buf, flags="write_discard").map(stream=stream) as buf:
+            assert isinstance(buf, Buffer)
+            assert buf.handle != 0
 
-    def test_strided_memory_view_from_mapped_buffer(self):
-        """End-to-end: register, map, create StridedMemoryView."""
-        nbytes = 256 * 4  # 256 float32 elements
-        with _gl_context_and_buffer(nbytes=nbytes) as (gl_buf, _):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            with resource.map(stream=stream) as buf:
-                view = StridedMemoryView.from_buffer(buf, shape=(256,), dtype=np.float32)
-                assert view.ptr == int(buf.handle)
-                assert view.shape == (256,)
-                assert view.is_device_accessible
-            resource.close()
 
-    def test_from_gl_buffer_with_stream_context_manager(self):
-        """Register + auto-map via from_gl_buffer(stream=), then create StridedMemoryView."""
-        nbytes = 256 * 4  # 256 float32 elements
-        with _gl_context_and_buffer(nbytes=nbytes) as (gl_buf, _):
-            stream = _create_stream()
-            with GraphicsResource.from_gl_buffer(gl_buf, stream=stream) as buf:
-                assert isinstance(buf, Buffer)
-                assert buf.size == nbytes
-                view = StridedMemoryView.from_buffer(buf, shape=(256,), dtype=np.float32)
-                assert view.ptr == int(buf.handle)
-                assert view.shape == (256,)
-                assert view.is_device_accessible
-            assert buf.handle == 0
-            assert buf.size == 0
-
-    def test_resource_context_manager_auto_closes(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
-            with GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard") as resource:
-                assert isinstance(resource, GraphicsResource)
-                assert resource.handle != 0
-                assert not resource.is_mapped
-            assert resource.handle == 0
-
-    def test_resource_context_manager_can_map_inside_scope(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
-            stream = _create_stream()
-            with GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard").map(stream=stream) as buf:
-                assert isinstance(buf, Buffer)
-                assert buf.handle != 0
-
-    def test_chained_map_context_manager_unmaps(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
-            stream = _create_stream()
-            with GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard").map(stream=stream) as buf:
-                assert isinstance(buf, Buffer)
-                assert buf.handle != 0
-                assert buf.size > 0
-            assert buf.handle == 0
-            assert buf.size == 0
-
-    def test_map_with_stream(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            with resource.map(stream=stream) as buf:
-                assert buf.size > 0
-            resource.close()
+def test_chained_map_context_manager_unmaps(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
+        stream = init_cuda.create_stream()
+        with _register_gl_buffer(gl_buf, flags="write_discard").map(stream=stream) as buf:
+            assert isinstance(buf, Buffer)
+            assert buf.handle != 0
+            assert buf.size > 0
+        assert buf.handle == 0
+        assert buf.size == 0
 
-    def test_map_requires_explicit_stream(self):
-        with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            try:
-                with pytest.raises(TypeError, match=r"keyword-only argument"):
-                    resource.map()
-            finally:
-                resource.close()
+
+def test_map_with_stream(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, nbytes):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        with resource.map(stream=stream) as buf:
+            assert buf.size > 0
+        resource.close()
+
+
+def test_map_requires_explicit_stream(init_cuda):
+    with _gl_context_and_buffer(nbytes=4096) as (gl_buf, _):
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        try:
+            with pytest.raises(TypeError, match=r"keyword-only argument"):
+                resource.map()
+        finally:
+            resource.close()
 
 
 # ---------------------------------------------------------------------------
@@ -355,79 +399,62 @@ def test_map_requires_explicit_stream(self):
 # ---------------------------------------------------------------------------
 
 
-class TestErrorHandling:
-    def test_double_map_raises(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
+def test_double_map_raises(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf)
+        resource.map(stream=stream)
+        with pytest.raises(RuntimeError, match="already mapped"):
             resource.map(stream=stream)
-            with pytest.raises(RuntimeError, match="already mapped"):
-                resource.map(stream=stream)
-            resource.unmap()
-            resource.close()
+        resource.unmap()
+        resource.close()
 
-    def test_unmap_without_map_raises(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            with pytest.raises(RuntimeError, match="not mapped"):
-                resource.unmap()
-            resource.close()
 
-    def test_map_after_close_raises(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            resource.close()
-            with pytest.raises(RuntimeError, match="has been closed"):
-                resource.map(stream=stream)
+def test_unmap_without_map_raises(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        with pytest.raises(RuntimeError, match="not mapped"):
+            resource.unmap()
+        resource.close()
 
-    def test_unmap_after_close_raises(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            resource.close()
-            with pytest.raises(RuntimeError, match="has been closed"):
-                resource.unmap()
-
-    def test_close_while_mapped(self):
-        """close() should unmap before unregistering."""
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            buf = resource.map(stream=stream)
-            assert resource.is_mapped
-            resource.close()  # Should unmap + unregister without error
-            assert not resource.is_mapped
-            assert buf.handle == 0
 
-    def test_close_while_mapped_passes_stream_override(self):
-        with _gl_context_and_buffer() as (gl_buf, _):
-            map_stream = _create_stream()
-            close_stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            resource.map(stream=map_stream)
+def test_map_after_close_raises(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf)
+        resource.close()
+        with pytest.raises(RuntimeError, match="has been closed"):
+            resource.map(stream=stream)
 
-            original_close = Buffer.close
 
-            def tracking_close(self, stream=None):
-                tracking_close.calls.append(stream)
-                return original_close(self, stream=stream)
+def test_unmap_after_close_raises(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        resource.close()
+        with pytest.raises(RuntimeError, match="has been closed"):
+            resource.unmap()
 
-            tracking_close.calls = []
 
-            with patch.object(Buffer, "close", new=tracking_close):
-                resource.close(stream=close_stream)
+def test_close_while_mapped(init_cuda):
+    """close() should unmap before unregistering."""
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        buf = resource.map(stream=stream)
+        assert resource.is_mapped
+        resource.close()  # Should unmap + unregister without error
+        assert not resource.is_mapped
+        assert buf.handle == 0
 
-            assert tracking_close.calls == [close_stream]
-            assert not resource.is_mapped
 
-    def test_buffer_close_updates_resource_state(self):
-        with _gl_context_and_buffer() as (gl_buf, _):
-            stream = _create_stream()
-            resource = GraphicsResource.from_gl_buffer(gl_buf, flags="write_discard")
-            buf = resource.map(stream=stream)
-            assert resource.is_mapped
-            buf.close()
-            assert not resource.is_mapped
+def test_buffer_close_updates_resource_state(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, _):
+        stream = init_cuda.create_stream()
+        resource = _register_gl_buffer(gl_buf, flags="write_discard")
+        buf = resource.map(stream=stream)
+        assert resource.is_mapped
+        buf.close()
+        assert not resource.is_mapped
 
 
 # ---------------------------------------------------------------------------
@@ -435,33 +462,35 @@ def test_buffer_close_updates_resource_state(self):
 # ---------------------------------------------------------------------------
 
 
-class TestMisc:
-    def test_gc_cleanup(self):
-        """Creating and dropping a resource should not leak."""
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            assert resource.handle != 0
-            del resource
-            gc.collect()
-            # If we get here without a CUDA error, cleanup succeeded.
-
-    def test_repr(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            r = repr(resource)
-            assert "GraphicsResource" in r
-            assert "0x" in r
-            resource.close()
+def test_gc_cleanup(init_cuda):
+    """Creating and dropping a resource should not leak."""
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        assert resource.handle != 0
+        del resource
+        gc.collect()
+        # If we get here without a CUDA error, cleanup succeeded.
 
-    def test_repr_closed(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            resource.close()
-            r = repr(resource)
-            assert "closed" in r
 
-    def test_graphics_resource_is_not_a_buffer(self):
-        with _gl_context_and_buffer() as (gl_buf, nbytes):
-            resource = GraphicsResource.from_gl_buffer(gl_buf)
-            assert not isinstance(resource, Buffer)
-            resource.close()
+def test_repr(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        r = repr(resource)
+        assert "GraphicsResource" in r
+        assert "0x" in r
+        resource.close()
+
+
+def test_repr_closed(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        resource.close()
+        r = repr(resource)
+        assert "closed" in r
+
+
+def test_graphics_resource_is_not_a_buffer(init_cuda):
+    with _gl_context_and_buffer() as (gl_buf, nbytes):
+        resource = _register_gl_buffer(gl_buf)
+        assert not isinstance(resource, Buffer)
+        resource.close()
diff --git a/cuda_core/tests/test_green_context.py b/cuda_core/tests/test_green_context.py
index 693dffacdc7..5f1954c6b58 100644
--- a/cuda_core/tests/test_green_context.py
+++ b/cuda_core/tests/test_green_context.py
@@ -2,11 +2,9 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-
-import contextlib
-
 import numpy as np
 import pytest
+from helpers.contexts import assert_device_operations_use_bound_context, use_context
 
 from cuda.core import (
     ContextOptions,
@@ -21,7 +19,9 @@
     WorkqueueResourceOptions,
     launch,
 )
-from cuda.core._utils.cuda_utils import CUDAError
+from cuda.core._utils.cuda_utils import CUDAError, driver, handle_return
+from cuda.core._utils.version import binding_version, driver_version
+from cuda.core.graph import GraphDefinition
 from cuda.core.typing import WorkqueueSharingScopeType
 
 # ---------------------------------------------------------------------------
@@ -150,14 +150,36 @@ def _find_backfill_only_two_group_split(sm):
     return None
 
 
-@contextlib.contextmanager
-def _use_green_ctx(dev, ctx):
-    """Context manager: set green ctx current, restore previous on exit."""
-    prev = dev.set_current(ctx)
-    try:
-        yield
-    finally:
-        dev.set_current(prev)
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_memory_node_updates_preserve_green_context(
+    init_cuda,
+    green_ctx,
+):
+    if driver_version() < (13, 2, 0) or binding_version() < (13, 2, 0):
+        pytest.skip("generic graph node parameter queries require CUDA 13.2+")
+
+    memory_resource = LegacyPinnedMemoryResource()
+    src = memory_resource.allocate(4)
+    dst = memory_resource.allocate(4)
+    with use_context(init_cuda, green_ctx):
+        graph_def = GraphDefinition()
+        memset_node = graph_def.memset(dst, 0, 4)
+        memcpy_node = graph_def.memcpy(dst, src, 4)
+        original_memset = handle_return(driver.cuGraphNodeGetParams(memset_node.handle))
+        original_memcpy = handle_return(driver.cuGraphNodeGetParams(memcpy_node.handle))
+
+    memset_node.update(value=1)
+    memcpy_node.update(size=2)
+    updated_memset = handle_return(driver.cuGraphNodeGetParams(memset_node.handle))
+    updated_memcpy = handle_return(driver.cuGraphNodeGetParams(memcpy_node.handle))
+
+    assert int(updated_memset.memset.ctx) == int(original_memset.memset.ctx)
+    assert int(updated_memcpy.memcpy.copyCtx) == int(original_memcpy.memcpy.copyCtx)
+
+    memset_node.destroy()
+    memcpy_node.destroy()
+    src.close()
+    dst.close()
 
 
 # ---------------------------------------------------------------------------
@@ -183,6 +205,36 @@ def test_create_context_requires_resources(init_cuda):
         init_cuda.create_context(object())
 
 
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_context_handle_alias_and_closed_queries(init_cuda, sm_resource):
+    """``Context._handle`` mirrors ``.handle``; after a (non-current) green
+    context is closed its handle-backed queries degrade gracefully: ``handle`` is
+    ``None``, ``is_green`` is ``False``, and ``resources`` raises."""
+    groups, _ = sm_resource.split(SMResourceOptions(count=None))
+    ctx = init_cuda.create_context(ContextOptions(resources=[groups[0]]))
+    # `_handle` is a thin alias of the public `handle` property.
+    assert ctx._handle == ctx.handle
+    assert ctx.handle is not None
+
+    ctx.close()
+    assert ctx.handle is None
+    assert ctx.is_green is False
+    with pytest.raises(RuntimeError, match="Context has been closed"):
+        _ = ctx.resources
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_set_current_rejects_closed_context(init_cuda, sm_resource):
+    groups, _ = sm_resource.split(SMResourceOptions(count=None))
+    ctx = init_cuda.create_context(ContextOptions(resources=[groups[0]]))
+    ctx.close()
+
+    assert ctx.is_closed
+    assert bool(ctx) is True  # Preserve backward-compatible truthiness after close.
+    with pytest.raises(RuntimeError, match="Context has been closed"):
+        init_cuda.set_current(ctx)
+
+
 # ---------------------------------------------------------------------------
 # SM resource query
 # ---------------------------------------------------------------------------
@@ -239,12 +291,12 @@ def test_configure_scope_with_enum(self, wq_resource, scope):
         assert wq_resource.sharing_scope is scope
 
     def test_device_id_matches_source_multi_gpu(self):
-        from cuda.core import Device, system
+        from cuda.core import Device
 
-        if system.get_num_devices() < 2:
+        devices = Device.get_all_devices()
+        if len(devices) < 2:
             pytest.skip("requires 2+ GPUs")
-        dev0 = Device(0)
-        dev1 = Device(1)
+        dev0, dev1 = devices[:2]
         try:
             wq0 = dev0.resources.workqueue
             wq1 = dev1.resources.workqueue
@@ -308,6 +360,20 @@ def test_negative_count_raises(self, sm_resource):
         with pytest.raises(ValueError, match="count must be non-negative"):
             sm_resource.split(SMResourceOptions(count=-1))
 
+    @pytest.mark.agent_authored(model="claude-opus-4.8")
+    def test_empty_count_sequence_raises(self, sm_resource):
+        """An empty ``count`` sequence has no groups to split into."""
+        with pytest.raises(ValueError, match="count sequence must not be empty"):
+            sm_resource.split(SMResourceOptions(count=[]))
+
+    @pytest.mark.agent_authored(model="claude-opus-4.8")
+    @pytest.mark.parametrize("bad_count", [3.5, object()])
+    def test_count_wrong_type_raises(self, sm_resource, bad_count):
+        """``count`` that is neither int, Sequence, nor None is rejected before
+        any driver call."""
+        with pytest.raises(TypeError, match="count must be int, Sequence, or None"):
+            sm_resource.split(SMResourceOptions(count=bad_count))
+
     def test_dry_run_cannot_create_context(self, init_cuda, sm_resource):
         groups, _ = sm_resource.split(SMResourceOptions(count=None), dry_run=True)
         assert len(groups) == 1
@@ -339,11 +405,37 @@ def test_discovery_mode(self, sm_resource):
         assert len(groups) == 1
         assert groups[0].sm_count >= sm_resource.min_partition_size
 
-    def test_discovery_respects_alignment(self, sm_resource):
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_by_count_discovery_respects_alignment(self, sm_resource):
+        """CUDA 12 SplitByCount discovery returns an aligned SM count."""
+        if binding_version()[0] != 12:
+            pytest.skip("test covers the CUDA 12 SplitByCount path")
+
         groups, _ = sm_resource.split(SMResourceOptions(count=None))
 
-        if sm_resource.coscheduled_alignment > 0:
-            assert groups[0].sm_count % sm_resource.coscheduled_alignment == 0
+        assert groups[0].sm_count % sm_resource.coscheduled_alignment == 0
+
+    def test_discovery_respects_explicit_coscheduled_sm_count(self, sm_resource):
+        """Constrain discovery explicitly because unconstrained discovery may use all SMs."""
+        if driver_version() < (13, 1, 0):
+            pytest.skip("explicit co-scheduled SM discovery requires CUDA 13.1+")
+
+        alignment = sm_resource.coscheduled_alignment
+        try:
+            groups, _ = sm_resource.split(
+                SMResourceOptions(
+                    count=None,
+                    coscheduled_sm_count=alignment,
+                )
+            )
+        except RuntimeError as exc:
+            pytest.skip(str(exc))
+        except CUDAError as exc:
+            if _is_invalid_resource_configuration(exc):
+                pytest.skip(str(exc))
+            raise
+
+        assert groups[0].sm_count % alignment == 0
 
     def test_two_groups(self, sm_resource):
         """Two-group split succeeds for a supported explicit request."""
@@ -424,16 +516,45 @@ def test_stream_and_event_track_green_context(self, green_ctx):
         stream.sync()
         event.sync()
 
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_device_receiver_targets_stored_green_context(self, init_cuda, green_ctx):
+        primary_ctx = init_cuda.context
+
+        with use_context(init_cuda, green_ctx):
+            handle_return(driver.cuCtxSetCurrent(primary_ctx.handle))
+            assert_device_operations_use_bound_context(init_cuda)
+
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_texture_rejects_resource_from_other_context(self, init_cuda, green_ctx):
+        from cuda.core.texture import (
+            OpaqueArrayOptions,
+            ResourceDescriptor,
+        )
+        from cuda.core.typing import ArrayFormatType
+
+        with (
+            init_cuda.create_opaque_array(
+                OpaqueArrayOptions(
+                    shape=(8, 8),
+                    format=ArrayFormatType.UINT8,
+                    num_channels=4,
+                )
+            ) as array,
+            use_context(init_cuda, green_ctx),
+            pytest.raises(ValueError, match="resource is not compatible with this Device object"),
+        ):
+            init_cuda.create_texture_object(resource=ResourceDescriptor.from_opaque_array(array))
+
     def test_close_while_current_raises(self, init_cuda, green_ctx):
         """close() on a current context raises — test via set_current."""
         dev = init_cuda
-        with _use_green_ctx(dev, green_ctx), pytest.raises(RuntimeError, match="while it is current"):
+        with use_context(dev, green_ctx), pytest.raises(RuntimeError, match="while it is current"):
             green_ctx.close()
 
     def test_set_current_swap_regression(self, init_cuda, green_ctx):
         """set_current still works (backward compat) and preserves identity."""
         dev = init_cuda
-        with _use_green_ctx(dev, green_ctx):
+        with use_context(dev, green_ctx):
             pass  # just verify push/pop works
         # Swap again and check identity round-trip
         prev = dev.set_current(green_ctx)
@@ -498,6 +619,19 @@ def test_stream_resources_match_context(self, green_ctx, sm_resource):
         except (RuntimeError, ValueError, CUDAError):
             pass  # workqueue not available on this driver/build
 
+    @pytest.mark.agent_authored(model="claude-opus-4.8")
+    def test_primary_context_stream_sm_resources(self, init_cuda, sm_resource):
+        """A stream on the *primary* (non-green) context queries SM resources via
+        the plain ``cuCtxGetDevResource`` path (distinct from the green-context
+        path exercised elsewhere): the stream carries a context handle but it is
+        not a green context, so the whole device is reported."""
+        stream = init_cuda.create_stream()
+        try:
+            stream_sm = stream.resources.sm
+            assert stream_sm.sm_count == sm_resource.sm_count
+        finally:
+            stream.close()
+
 
 # ---------------------------------------------------------------------------
 # Kernel launch in green context (explicit model)
diff --git a/cuda_core/tests/test_helpers.py b/cuda_core/tests/test_helpers.py
index 43dbf8887e2..8fc7b8bb75a 100644
--- a/cuda_core/tests/test_helpers.py
+++ b/cuda_core/tests/test_helpers.py
@@ -3,11 +3,23 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import time
+import types
 
 import pytest
-from helpers.buffers import PatternGen, compare_equal_buffers, make_scratch_buffer
+from helpers.buffers import PatternGen, compare_equal_buffers, make_scratch_buffer, thread_unsafe_on_windows
 from helpers.latch import LatchKernel
 from helpers.logging import TimestampedLogger
+from helpers.oom_diagnostics import (
+    DEFAULT_FILENAME,
+    OOM_MARKER,
+    OomDiagnosticsRecorder,
+    ProbeSnapshot,
+    classify,
+    probe_basics,
+    record_if_oom,
+    report_terminal_summary,
+)
+from helpers.oom_diagnostics import _round_up as oom_round_up  # white-box test of the alignment guard
 
 from cuda.core import Device
 from cuda_python_test_helpers import under_compute_sanitizer
@@ -17,6 +29,7 @@
 
 
 @pytest.mark.skipif(Device().compute_capability.major < 7, reason="__nanosleep is only available starting Volta (sm70)")
+@pytest.mark.thread_unsafe(reason="requires a barrier wait to avoid overlapping pinned latch allocations")
 def test_latchkernel():
     """Test LatchKernel."""
     log = TimestampedLogger(enabled=ENABLE_LOGGING)
@@ -51,16 +64,18 @@ def test_latchkernel():
     under_compute_sanitizer(),
     reason="Too slow under compute-sanitizer (UVM-heavy test).",
 )
+@thread_unsafe_on_windows
 def test_patterngen_seeds():
     """Test PatternGen with seed argument."""
     device = Device()
     device.set_current()
     buffer = make_scratch_buffer(device, 0, NBYTES)
+    stream = device.default_stream
 
     # All seeds are pairwise different.
     # We test a sampling of values because exhaustive testing is too slow,
     # especially on Windows. See https://github.com/NVIDIA/cuda-python/issues/1455
-    pgen = PatternGen(device, NBYTES)
+    pgen = PatternGen(device, NBYTES, stream=stream)
     for i in (ii for ii in range(256) if ii < 5 or ii % 17 == 0):
         pgen.fill_buffer(buffer, seed=i)
         pgen.verify_buffer(buffer, seed=i)
@@ -69,6 +84,7 @@ def test_patterngen_seeds():
                 pgen.verify_buffer(buffer, seed=j)
 
 
+@thread_unsafe_on_windows
 def test_patterngen_values():
     """Test PatternGen with value argument, also compare_equal_buffers."""
     device = Device()
@@ -77,6 +93,320 @@ def test_patterngen_values():
     twos = make_scratch_buffer(device, 2, NBYTES)
     assert compare_equal_buffers(ones, ones)
     assert not compare_equal_buffers(ones, twos)
-    pgen = PatternGen(device, NBYTES)
+    pgen = PatternGen(device, NBYTES, stream=device.default_stream)
     pgen.verify_buffer(ones, value=1)
     pgen.verify_buffer(twos, value=2)
+
+
+# helpers.oom_diagnostics (issue #2381): a pytest harness plus an OOM reason
+# checker that tells host virtual-address exhaustion apart from physical
+# device memory exhaustion. Both halves are non-trivial infrastructure (see
+# discussion on #2471), so they get tests. The harness and classifier tests
+# below never touch the driver: they inject a `ProbeSnapshot` (or none of the
+# recorder needs one at all) so a broken assertion here can't be the thing
+# that materializes a session's first ~2x-device-memory pool reservation.
+# Only test_oom_diagnostics_probe_basics_is_live_and_cheap talks to the
+# driver, and only through the side-effect-free prefix of the checker.
+
+
+def _fake_report(failed):
+    return types.SimpleNamespace(failed=failed)
+
+
+def _fake_call(exc_text, when="call"):
+    excinfo = None if exc_text is None else types.SimpleNamespace(value=RuntimeError(exc_text))
+    return types.SimpleNamespace(excinfo=excinfo, when=when)
+
+
+def _fake_item(rootpath, nodeid="tests/test_x.py::test_a"):
+    # get_plugin returns None so record_if_oom skips the terminal write.
+    config = types.SimpleNamespace(
+        rootpath=rootpath,
+        pluginmanager=types.SimpleNamespace(get_plugin=lambda _: None),
+    )
+    return types.SimpleNamespace(nodeid=nodeid, config=config)
+
+
+# A snapshot that short-circuits classify()/format_probe_log() at the very
+# first check, so harness tests never depend on -- or need to fake -- driver
+# call results.
+_NO_CONTEXT_SNAPSHOT = ProbeSnapshot(has_context=False)
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+@pytest.mark.parametrize(
+    ("failed", "exc_text", "should_capture"),
+    [
+        (True, f"boom {OOM_MARKER}", True),
+        (True, "CUDA_ERROR_INVALID_CONTEXT", False),
+        (False, f"boom {OOM_MARKER}", False),
+        (True, None, False),
+    ],
+)
+def test_oom_diagnostics_fire_only_on_a_failing_oom(tmp_path, failed, exc_text, should_capture):
+    recorder = OomDiagnosticsRecorder()
+    result = record_if_oom(
+        _fake_item(tmp_path),
+        _fake_call(exc_text),
+        _fake_report(failed),
+        recorder=recorder,
+        snapshot=_NO_CONTEXT_SNAPSHOT,
+    )
+
+    assert (result is not None) == should_capture
+    assert recorder.captured == should_capture
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_oom_diagnostics_write_an_artifact_naming_the_failing_test(tmp_path, monkeypatch):
+    # Omitting `recorder` also pins the call signature conftest.py relies on.
+    # Patching the singleton keeps this from latching diagnostics for the run.
+    recorder = OomDiagnosticsRecorder()
+    monkeypatch.setattr("helpers.oom_diagnostics._default_recorder", recorder)
+
+    text = record_if_oom(
+        _fake_item(tmp_path, nodeid="tests/test_x.py::test_first"),
+        _fake_call(f"boom {OOM_MARKER}"),
+        _fake_report(True),
+        snapshot=_NO_CONTEXT_SNAPSHOT,
+    )
+
+    written = (tmp_path / DEFAULT_FILENAME).read_text(encoding="utf-8")
+    assert "tests/test_x.py::test_first" in written
+    assert OOM_MARKER in written
+    assert "tests/test_x.py::test_first" in text
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_oom_diagnostics_summary_points_at_the_artifact(tmp_path):
+    # The report is emitted beside the failing test, thousands of lines above
+    # the summary; without this line the artifact is effectively invisible.
+    recorder = OomDiagnosticsRecorder()
+    lines = []
+    reporter = types.SimpleNamespace(write_sep=lambda *_, **__: None, write_line=lines.append)
+
+    assert report_terminal_summary(reporter, recorder=recorder) is None
+    assert lines == []
+
+    recorder.capture("tests/test_x.py::test_first", "call", OOM_MARKER, tmp_path, snapshot=_NO_CONTEXT_SNAPSHOT)
+    emitted = report_terminal_summary(reporter, recorder=recorder)
+
+    assert "tests/test_x.py::test_first" in emitted
+    assert str(tmp_path) in emitted
+    assert emitted in lines
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_oom_diagnostics_latch_to_the_first_oom(tmp_path):
+    # A failing run produces ~190 OOMs; capturing each would bury the log.
+    recorder = OomDiagnosticsRecorder()
+    assert recorder.capture("first", "call", OOM_MARKER, tmp_path, snapshot=_NO_CONTEXT_SNAPSHOT) is not None
+    assert recorder.captured
+    assert recorder.capture("second", "call", OOM_MARKER, tmp_path, snapshot=_NO_CONTEXT_SNAPSHOT) is None
+
+    assert "first" in (tmp_path / DEFAULT_FILENAME).read_text(encoding="utf-8")
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_oom_diagnostics_report_names_the_failing_test_and_verdict(tmp_path):
+    # build_report is what actually assembles the artifact text; exercise it
+    # directly (rather than only through capture()) so a broken verdict line
+    # is caught here instead of by reading a real OOM log after the fact.
+    recorder = OomDiagnosticsRecorder()
+    text = recorder.build_report("tests/test_x.py::test_first", "call", OOM_MARKER, snapshot=_NO_CONTEXT_SNAPSHOT)
+
+    assert "tests/test_x.py::test_first" in text
+    assert "verdict: no current CUDA context" in text
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+@pytest.mark.parametrize(
+    ("snapshot", "expected_substring"),
+    [
+        (ProbeSnapshot(has_context=False), "no current CUDA context"),
+        (
+            ProbeSnapshot(has_context=True, mem_get_info_error="CUDA_ERROR_INVALID_CONTEXT"),
+            "cuMemGetInfo itself failed",
+        ),
+        (
+            ProbeSnapshot(has_context=True, mem_free=10 * (1 << 30), mem_total=10 * (1 << 30), small_alloc_ok=False),
+            "likely physical device memory exhaustion",
+        ),
+        (
+            # Plenty of device memory reported free, but even a tiny host VA
+            # reservation fails outright.
+            ProbeSnapshot(
+                has_context=True,
+                mem_free=140 * (1 << 30),
+                mem_total=180 * (1 << 30),
+                small_alloc_ok=True,
+                small_va_ok=False,
+            ),
+            "host virtual-address space is exhausted",
+        ),
+        (
+            ProbeSnapshot(
+                has_context=True,
+                mem_free=140 * (1 << 30),
+                mem_total=180 * (1 << 30),
+                small_alloc_ok=True,
+                mempools_supported=False,
+            ),
+            "mempools are not supported",
+        ),
+        (
+            # The #2381 signature itself: device mostly free, but the
+            # pool-sized reservation -- the same size cuDeviceGetMemPool
+            # needs -- fails outright.
+            ProbeSnapshot(
+                has_context=True,
+                mem_free=140 * (1 << 30),
+                mem_total=180 * (1 << 30),
+                small_alloc_ok=True,
+                small_va_ok=True,
+                mempools_supported=True,
+                pool_va_ok=False,
+                capped_pool_create_ok=False,
+            ),
+            "likely host VA exhaustion: a pool-sized reservation failed",
+        ),
+        (
+            # Same, but a capped pool still fits: only the ~2x default
+            # window is the problem, not pools in general.
+            ProbeSnapshot(
+                has_context=True,
+                mem_free=140 * (1 << 30),
+                mem_total=180 * (1 << 30),
+                small_alloc_ok=True,
+                small_va_ok=True,
+                mempools_supported=True,
+                pool_va_ok=False,
+                capped_pool_create_ok=True,
+            ),
+            "likely host VA exhaustion for the pool-sized window only",
+        ),
+        (
+            ProbeSnapshot(
+                has_context=True,
+                mem_free=140 * (1 << 30),
+                mem_total=180 * (1 << 30),
+                small_alloc_ok=True,
+                small_va_ok=True,
+                mempools_supported=True,
+                pool_va_ok=True,
+                get_mem_pool_ok=False,
+            ),
+            "default mempool materialization failed",
+        ),
+        (
+            ProbeSnapshot(
+                has_context=True,
+                mem_free=140 * (1 << 30),
+                mem_total=180 * (1 << 30),
+                small_alloc_ok=True,
+                small_va_ok=True,
+                mempools_supported=True,
+                pool_va_ok=True,
+                get_mem_pool_ok=True,
+                get_default_mem_pool_ok=True,
+                capped_pool_create_ok=True,
+            ),
+            "inconclusive: all probes succeeded",
+        ),
+    ],
+)
+def test_oom_diagnostics_classify_names_the_right_bucket(snapshot, expected_substring):
+    assert expected_substring in classify(snapshot)
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+@pytest.mark.parametrize(
+    ("value", "alignment", "expected"),
+    [
+        (0, 2 * (1 << 20), 0),
+        (1, 2 * (1 << 20), 2 * (1 << 20)),
+        (2 * (1 << 20), 2 * (1 << 20), 2 * (1 << 20)),
+        # One byte short of aligned; an unaligned reserve would return
+        # CUDA_ERROR_INVALID_VALUE, which looks like exhaustion.
+        (24 * (1 << 30) - 1, 2 * (1 << 20), 24 * (1 << 30)),
+    ],
+)
+def test_oom_diagnostics_round_up_keeps_va_reserves_aligned(value, alignment, expected):
+    assert oom_round_up(value, alignment) == expected
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_oom_diagnostics_probe_basics_is_live_and_cheap(init_cuda):
+    # Only the side-effect-free prefix: no cuDeviceGetMemPool, no
+    # cuMemPoolCreate, no pool-sized cuMemAddressReserve. A healthy device
+    # must report a context and free/total memory.
+    snapshot, dev = probe_basics()
+
+    assert snapshot.has_context
+    assert snapshot.mem_get_info_error is None
+    assert snapshot.mem_total > 0
+    assert dev is not None
+    # probe_basics never sets any field past the physical-allocator check.
+    assert snapshot.small_va_ok is None
+    assert snapshot.pool_va_ok is None
+    assert snapshot.get_mem_pool_ok is None
+    assert snapshot.capped_pool_create_ok is None
+
+
+# ---------------------------------------------------------------------------
+# GL context availability predicate tests
+# ---------------------------------------------------------------------------
+
+import pytest
+from cuda_python_test_helpers.graphics import is_gl_context_unavailable
+
+
+class _PygletError(Exception):
+    pass
+
+
+# Simulate a pyglet-namespaced exception by name.
+def _make_pyglet_exc(name, module="pyglet.window"):
+    cls = type(name, (_PygletError,), {})
+    cls.__module__ = module
+    return cls
+
+
+@pytest.mark.human_reviewed
+@pytest.mark.parametrize(
+    "exc",
+    [
+        _make_pyglet_exc("NoSuchDisplayException")("x"),
+        _make_pyglet_exc("NoSuchConfigException")("x"),
+        _make_pyglet_exc("NoSuchScreenModeException")("x"),
+        _make_pyglet_exc("WindowException")("x"),
+        _make_pyglet_exc("ContextException")("x"),
+        _make_pyglet_exc("MissingFunctionException", module="pyglet.gl.lib")("x"),
+        FileNotFoundError("Could not find module 'opengl32' (or one of its dependencies)."),
+        AttributeError("opengl32"),
+        ImportError('Library "GL" not found.'),
+        ImportError('Library "EGL" not found.'),
+    ],
+)
+def test_is_gl_context_unavailable_accepts_genuine(exc):
+    assert is_gl_context_unavailable(exc) is True
+
+
+@pytest.mark.human_reviewed
+@pytest.mark.parametrize(
+    "exc",
+    [
+        # pyglet exception names that are not context-creation failures
+        _make_pyglet_exc("GLException")("GL_INVALID_ENUM"),
+        _make_pyglet_exc("ImageException")("x"),
+        # Built-in exceptions that do not mention opengl32 / GL library
+        TypeError("bug"),
+        AttributeError("'NoneType' object has no attribute 'Config'"),
+        FileNotFoundError("No such file: /tmp/missing"),
+        ImportError("No module named 'foo'"),
+        OSError("disk full"),
+        RuntimeError("bug"),
+    ],
+)
+def test_is_gl_context_unavailable_rejects_unrelated(exc):
+    assert is_gl_context_unavailable(exc) is False
diff --git a/cuda_core/tests/test_launcher.py b/cuda_core/tests/test_launcher.py
index 942952d29b8..e715fce0067 100644
--- a/cuda_core/tests/test_launcher.py
+++ b/cuda_core/tests/test_launcher.py
@@ -4,7 +4,7 @@
 import ctypes
 
 import helpers
-from helpers.marks import requires_module
+from cuda_python_test_helpers.marks import requires_module, skipif_need_cuda_headers
 from helpers.misc import StreamWrapper
 
 try:
@@ -14,7 +14,6 @@
 import numpy as np
 import pytest
 
-from conftest import skipif_need_cuda_headers
 from cuda.core import (
     Device,
     DeviceMemoryResource,
@@ -22,9 +21,10 @@
     LegacyPinnedMemoryResource,
     Program,
     ProgramOptions,
+    StreamOptions,
     launch,
 )
-from cuda.core._memory._legacy import _SynchronousMemoryResource
+from cuda.core._memory._synchronous_memory_resource import _SynchronousMemoryResource
 from cuda.core._utils.cuda_utils import CUDAError
 from cuda.core.typing import ObjectCodeFormatType, SourceCodeType
 
@@ -183,6 +183,117 @@ class _FakeDev:
     assert attr.value.cooperative == 1, f"Expected cooperative=1, got {attr.value.cooperative}"
 
 
+def test_to_native_launch_config_pdl():
+    """LaunchConfig(programmatic_stream_serialization=True) maps to the PDL launch attribute."""
+    from cuda.bindings import driver
+    from cuda.core._launch_config import _to_native_launch_config
+
+    config = LaunchConfig(grid=2, block=4, programmatic_stream_serialization=True)
+    native = _to_native_launch_config(config)
+    assert native.gridDimX == 2
+    assert native.blockDimX == 4
+    assert native.numAttrs == 1
+    attr = native.attrs[0]
+    assert attr.id == driver.CUlaunchAttributeID.CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION, (
+        f"Expected CU_LAUNCH_ATTRIBUTE_PROGRAMMATIC_STREAM_SERIALIZATION, got {attr.id}"
+    )
+    assert attr.value.programmaticStreamSerializationAllowed == 1, (
+        f"Expected programmaticStreamSerializationAllowed=1, got {attr.value.programmaticStreamSerializationAllowed}"
+    )
+
+
+@skipif_need_cuda_headers
+def test_pdl_primary_secondary_overlap_same_stream():
+    """Primary + secondary PDL launch on one stream can overlap on Hopper+.
+
+    Secondary is launched with ``programmatic_stream_serialization=True``. After
+    the primary triggers completion, it spins until it observes a flag written by
+    the secondary's independent preamble — proving both grids were resident at
+    once. Without PDL, the secondary cannot start until the primary exits.
+
+    Note concurrency is opportunistic, so a missing overlap execution is reported as
+    an expected failure.
+    """
+    dev = Device()
+    if dev.compute_capability < (9, 0):
+        pytest.skip("Programmatic Dependent Launch requires compute capability >= 9.0")
+    dev.set_current()
+    stream = dev.create_stream(options=StreamOptions(nonblocking=True))
+
+    # clock64 budgets are in GPU cycles; keep the post-trigger window long enough
+    # for the secondary to boot, but short enough for a unit test.
+    code = r"""
+    #include <cuda_device_runtime_api.h>
+
+    extern "C" __global__ void primary_kernel(int* secondary_started, int* overlapped) {
+        cudaTriggerProgrammaticLaunchCompletion();
+
+        const long long deadline = clock64() + 100000000LL;  // ~50ms @ ~2GHz
+        if (threadIdx.x == 0 && blockIdx.x == 0) {
+            while (clock64() < deadline) {
+                if (atomicAdd(secondary_started, 0) != 0) {
+                    atomicExch(overlapped, 1);
+                    return;
+                }
+                __nanosleep(1000);
+            }
+        }
+    }
+
+    extern "C" __global__ void secondary_kernel(int* secondary_started) {
+        if (threadIdx.x == 0 && blockIdx.x == 0) {
+            atomicExch(secondary_started, 1);
+        }
+    }
+    """
+
+    arch = "".join(f"{i}" for i in dev.compute_capability)
+    pro_opts = ProgramOptions(std="c++17", arch=f"sm_{arch}", include_path=helpers.CUDA_INCLUDE_PATH)
+    prog = Program(code, code_type="c++", options=pro_opts)
+    mod = prog.compile("cubin")
+    primary = mod.get_kernel("primary_kernel")
+    secondary = mod.get_kernel("secondary_kernel")
+
+    mr = LegacyPinnedMemoryResource()
+    secondary_started = np.from_dlpack(mr.allocate(4)).view(np.int32)
+    overlapped = np.from_dlpack(mr.allocate(4)).view(np.int32)
+
+    primary_cfg = LaunchConfig(grid=1, block=1)
+    secondary_cfg = LaunchConfig(grid=1, block=1, programmatic_stream_serialization=True)
+    secondary_serial_cfg = LaunchConfig(grid=1, block=1)
+
+    def _run(secondary_launch_cfg: LaunchConfig) -> int:
+        secondary_started[0] = 0
+        overlapped[0] = 0
+        launch(stream, primary_cfg, primary, secondary_started.ctypes.data, overlapped.ctypes.data)
+        launch(stream, secondary_launch_cfg, secondary, secondary_started.ctypes.data)
+        stream.sync()
+        return int(overlapped[0])
+
+    # Without the PDL attribute, same-stream kernels stay serialized.
+    assert _run(secondary_serial_cfg) == 0, "Expected no overlap when programmatic_stream_serialization is False"
+
+    # PDL overlap is opportunistic; retry a few times on a quiet GPU.
+    saw_overlap = False
+    for _ in range(5):
+        if _run(secondary_cfg) == 1:
+            saw_overlap = True
+            break
+
+    if not saw_overlap:
+        # Overlap is never guaranteed by the driver, so a miss is reported as an
+        # expected failure rather than turning a busy GPU into a red CI run.
+        pytest.xfail(
+            "PDL (Programmatic Dependent Launch) overlap was not observed. "
+            "If this keeps xfailing in CI, manually re-check on a quiet Hopper+ GPU."
+        )
+
+    print(
+        f"PDL (Programmatic Dependent Launch) overlap verified on {dev.name} compute capability {dev.compute_capability}",
+        flush=True,
+    )
+
+
 def test_launch_config_cluster_accepts_hopper_cc(monkeypatch):
     """LaunchConfig accepts ``cluster`` when the device reports compute
     capability >= 9.0. Device is mocked so the cluster-cast branch runs on any
@@ -372,7 +483,7 @@ def test_launch_scalar_argument(python_type, cpp_type, init_value):
 def test_cooperative_launch():
     dev = Device()
     dev.set_current()
-    s = dev.create_stream(options={"nonblocking": True})
+    s = dev.create_stream(options=StreamOptions(nonblocking=True))
 
     # CUDA kernel templated on type T
     code = r"""
@@ -536,25 +647,52 @@ class MyBool(ctypes.c_bool):
     assert holder.ptr != 0
 
 
+@pytest.mark.agent_authored(model="claude-opus-4.8")
 @requires_module(np, "2.2.5", reason="need numpy 2.2.5+ (numpy GH #28632)")
 @pytest.mark.parametrize(
-    ("scalar_kind", "np_dtype", "cpp_type", "raw_value"),
+    ("base_type", "np_dtype", "cpp_type", "raw_value"),
     [
-        ("ctypes", np.int32, "signed int", -123456),
-        ("numpy", np.float32, "float", 3.14),
+        # ctypes scalar subclasses — one per prepare_ctypes_arg isinstance-fallback
+        # branch. Values are chosen to expose a wrong width/sign: unsigned values
+        # exceed the same-width signed max, and c_uint64 exceeds uint32 max so a
+        # uint64 branch misrouted to prepare_arg[uint32_t] truncates 0x1_0000_0001
+        # to 1 and fails the readback.
+        (ctypes.c_bool, np.bool_, "bool", True),
+        (ctypes.c_int8, np.int8, "signed char", -42),
+        (ctypes.c_int16, np.int16, "signed short", -1234),
+        (ctypes.c_int32, np.int32, "signed int", -123456),
+        (ctypes.c_int64, np.int64, "signed long long", -123456789),
+        (ctypes.c_uint8, np.uint8, "unsigned char", 200),
+        (ctypes.c_uint16, np.uint16, "unsigned short", 60000),
+        (ctypes.c_uint32, np.uint32, "unsigned int", 4000000000),
+        (ctypes.c_uint64, np.uint64, "unsigned long long", 0x1_0000_0001),
+        (ctypes.c_float, np.float32, "float", 3.14),
+        (ctypes.c_double, np.float64, "double", 2.718281828),
+        # numpy scalar subclass — prepare_numpy_arg fallback
+        (np.float32, np.float32, "float", 3.14),
+    ],
+    ids=[
+        "ctypes_bool",
+        "ctypes_int8",
+        "ctypes_int16",
+        "ctypes_int32",
+        "ctypes_int64",
+        "ctypes_uint8",
+        "ctypes_uint16",
+        "ctypes_uint32",
+        "ctypes_uint64",
+        "ctypes_float",
+        "ctypes_double",
+        "numpy_float32",
     ],
-    ids=["ctypes_subclass", "numpy_subclass"],
 )
-def test_launch_scalar_argument_subclass_fallback(scalar_kind, np_dtype, cpp_type, raw_value):
-    """Subclassed scalar arguments survive fallback handling and reach the kernel."""
-    if scalar_kind == "ctypes":
-
-        class Subclassed(ctypes.c_int32):
-            pass
-    else:
+def test_launch_scalar_argument_subclass_fallback(base_type, np_dtype, cpp_type, raw_value):
+    """Subclassed scalar arguments survive fallback handling and reach the kernel
+    with the correct width/sign. The readback value (not just ptr != 0) guards each
+    fallback branch against marshalling the wrong C type, e.g. uint64 -> uint32_t."""
 
-        class Subclassed(np.float32):
-            pass
+    class Subclassed(base_type):
+        pass
 
     scalar = Subclassed(raw_value)
     expected = np_dtype(raw_value)
@@ -618,3 +756,142 @@ class MyComplex(complex):
 
     holder = ParamHolder([MyBool(1), MyFloat(1.5), MyComplex(1 + 2j)])
     assert holder.ptr != 0
+
+
+_NUMPY_SUBCLASS_FALLBACK_PARAMS = [
+    # One case per prepare_numpy_arg isinstance-fallback branch (exact type is
+    # skipped because type(arg) is the subclass). Values catch width/sign mixups.
+    (np.bool_, np.bool_, "bool", True),
+    (np.int8, np.int8, "signed char", -42),
+    (np.int16, np.int16, "signed short", -1234),
+    (np.int32, np.int32, "signed int", -123456),
+    (np.int64, np.int64, "signed long long", -123456789),
+    (np.uint8, np.uint8, "unsigned char", 200),
+    (np.uint16, np.uint16, "unsigned short", 60000),
+    (np.uint32, np.uint32, "unsigned int", 4000000000),
+    (np.uint64, np.uint64, "unsigned long long", 0x1_0000_0001),
+    (np.float64, np.float64, "double", 2.718281828),
+]
+_NUMPY_SUBCLASS_FALLBACK_IDS = [
+    "numpy_bool",
+    "numpy_int8",
+    "numpy_int16",
+    "numpy_int32",
+    "numpy_int64",
+    "numpy_uint8",
+    "numpy_uint16",
+    "numpy_uint32",
+    "numpy_uint64",
+    "numpy_float64",
+]
+if helpers.CCCL_INCLUDE_PATHS is not None:
+    _NUMPY_SUBCLASS_FALLBACK_PARAMS += [
+        (np.float16, np.float16, "half", 0.78),
+        (np.complex64, np.complex64, "cuda::std::complex<float>", 1 + 2j),
+        (np.complex128, np.complex128, "cuda::std::complex<double>", -3 - 4j),
+    ]
+    _NUMPY_SUBCLASS_FALLBACK_IDS += ["numpy_float16", "numpy_complex64", "numpy_complex128"]
+
+
+@requires_module(np, "2.2.5", reason="need numpy 2.2.5+ (numpy GH #28632)")
+@pytest.mark.parametrize(
+    ("base_type", "np_dtype", "cpp_type", "raw_value"),
+    _NUMPY_SUBCLASS_FALLBACK_PARAMS,
+    ids=_NUMPY_SUBCLASS_FALLBACK_IDS,
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_launch_numpy_scalar_subclass_fallback(base_type, np_dtype, cpp_type, raw_value):
+    """Subclassed numpy scalars take prepare_numpy_arg's isinstance fallback and reach the kernel (readback)."""
+
+    class Subclassed(base_type):
+        pass
+
+    scalar = Subclassed(raw_value)
+    expected = np_dtype(raw_value)
+
+    dev = Device()
+    dev.set_current()
+
+    mr = LegacyPinnedMemoryResource()
+    b = mr.allocate(np.dtype(np_dtype).itemsize)
+    arr = np.from_dlpack(b).view(np_dtype)
+    arr[:] = 0
+
+    code = r"""
+    template <typename T>
+    __global__ void write_scalar(T* arr, T val) {
+        arr[0] = val;
+    }
+    """
+    if helpers.CCCL_INCLUDE_PATHS is not None:
+        code = (
+            r"""
+        #include <cuda_fp16.h>
+        #include <cuda/std/complex>
+        """
+            + code
+        )
+
+    arch = "".join(f"{i}" for i in dev.compute_capability)
+    pro_opts = ProgramOptions(std="c++17", arch=f"sm_{arch}", include_path=helpers.CCCL_INCLUDE_PATHS)
+    prog = Program(code, code_type="c++", options=pro_opts)
+    ker_name = f"write_scalar<{cpp_type}>"
+    mod = prog.compile("cubin", name_expressions=(ker_name,))
+    ker = mod.get_kernel(ker_name)
+
+    stream = dev.default_stream
+    config = LaunchConfig(grid=1, block=1)
+    launch(stream, config, ker, arr.ctypes.data, scalar)
+    stream.sync()
+
+    assert arr[0] == expected
+
+
+# Truncates to 1 if the launcher packs the handle as uint32 instead of uint64.
+_UINT64_HANDLE_VALUE = 0x1_0000_0001
+
+
+def _compile_write_ull_kernel(dev):
+    code = r"""
+    extern "C" __global__ void write_ull(unsigned long long *out, unsigned long long val) {
+        *out = val;
+    }
+    """
+    arch = "".join(f"{i}" for i in dev.compute_capability)
+    prog = Program(code, code_type="c++", options=ProgramOptions(std="c++17", arch=f"sm_{arch}"))
+    return prog.compile("cubin", name_expressions=("write_ull",)).get_kernel("write_ull")
+
+
+def _assert_kernel_sees_ull(dev, kernel_arg, expected):
+    mr = LegacyPinnedMemoryResource()
+    buf = mr.allocate(np.dtype(np.uint64).itemsize)
+    try:
+        arr = np.from_dlpack(buf).view(np.uint64)
+        arr[:] = 0
+        ker = _compile_write_ull_kernel(dev)
+        stream = dev.default_stream
+        launch(stream, LaunchConfig(grid=1, block=1), ker, arr.ctypes.data, kernel_arg)
+        stream.sync()
+        assert int(arr[0]) == int(expected)
+    finally:
+        buf.close()
+
+
+@pytest.mark.parametrize("use_subclass", [False, True], ids=["exact_type", "subclass_fallback"])
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_launch_graph_conditional_handle_as_kernel_arg(init_cuda, use_subclass):
+    """CUgraphConditionalHandle is packed as its uint64 value (readback)."""
+    from cuda.bindings import driver
+
+    if not hasattr(driver, "CUgraphConditionalHandle"):
+        pytest.skip("CUgraphConditionalHandle requires cuda-bindings 12.3+")
+
+    class SubclassedHandle(driver.CUgraphConditionalHandle):
+        pass
+
+    handle_cls = SubclassedHandle if use_subclass else driver.CUgraphConditionalHandle
+    handle = handle_cls(_UINT64_HANDLE_VALUE)
+
+    dev = Device()
+    dev.set_current()
+    _assert_kernel_sees_ull(dev, handle, _UINT64_HANDLE_VALUE)
diff --git a/cuda_core/tests/test_linker.py b/cuda_core/tests/test_linker.py
index 9d95b5fd9c3..c80071fa405 100644
--- a/cuda_core/tests/test_linker.py
+++ b/cuda_core/tests/test_linker.py
@@ -3,6 +3,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import inspect
+import warnings
 
 import pytest
 
@@ -219,6 +220,22 @@ def test_linker_logs_cached_after_link(compile_ptx_functions):
     assert linker.get_info_log() == info_log
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_linker_rejects_link_but_preserves_cached_logs(compile_ptx_functions):
+    linker = Linker(*compile_ptx_functions, options=LinkerOptions(arch=ARCH))
+    linker.link("cubin")
+    error_log = linker.get_error_log()
+    info_log = linker.get_info_log()
+    linker.close()
+
+    assert linker.is_closed
+    assert bool(linker) is True  # Preserve backward-compatible truthiness after close.
+    assert linker.get_error_log() == error_log
+    assert linker.get_info_log() == info_log
+    with pytest.raises(RuntimeError, match="Linker has been closed"):
+        linker.link("cubin")
+
+
 def test_linker_handle(compile_ptx_functions):
     """Linker.handle returns a non-null handle object."""
     options = LinkerOptions(arch=ARCH)
@@ -303,6 +320,49 @@ def fake_decide():
         assert result == "nvJitLink"
         assert called, "_decide_nvjitlink_or_driver was not called"
 
+    @pytest.mark.agent_authored(model="grok-4.5")
+    def test_which_backend_falls_back_when_nvjitlink_too_old(self, monkeypatch):
+        """Regression test for #2408: old nvJitLink must not crash which_backend()."""
+        monkeypatch.setattr(_linker, "_use_nvjitlink_backend", None)
+        monkeypatch.setattr(_linker, "_driver", None)
+
+        def fake__optional_cuda_import(modname, probe_function=None):
+            assert modname == "cuda.bindings.nvjitlink"
+            assert probe_function is None
+            return object()
+
+        monkeypatch.setattr(_linker, "_optional_cuda_import", fake__optional_cuda_import)
+        monkeypatch.setattr(_linker, "_nvjitlink_has_version_symbol", lambda _nvjitlink: False)
+
+        with pytest.warns(RuntimeWarning, match="too old \\(<12.3\\)"):
+            assert Linker.which_backend() == "driver"
+
+        assert _linker._use_nvjitlink_backend is False
+
+    @pytest.mark.agent_authored(model="grok-4.5")
+    def test_which_backend_falls_back_when_dylib_missing(self, monkeypatch):
+        """Missing nvJitLink dylib must fall back without raising."""
+        from cuda.pathfinder import DynamicLibNotFoundError
+
+        monkeypatch.setattr(_linker, "_use_nvjitlink_backend", None)
+        monkeypatch.setattr(_linker, "_driver", None)
+
+        def raise_missing(_nvjitlink):
+            raise DynamicLibNotFoundError("missing")
+
+        def fake__optional_cuda_import(modname, probe_function=None):
+            assert modname == "cuda.bindings.nvjitlink"
+            assert probe_function is None
+            return object()
+
+        monkeypatch.setattr(_linker, "_nvjitlink_has_version_symbol", raise_missing)
+        monkeypatch.setattr(_linker, "_optional_cuda_import", fake__optional_cuda_import)
+
+        with pytest.warns(RuntimeWarning, match="cuda.bindings.nvjitlink is not available"):
+            assert Linker.which_backend() == "driver"
+
+        assert _linker._use_nvjitlink_backend is False
+
     def test_which_backend_is_classmethod(self):
         attr = inspect.getattr_static(Linker, "which_backend")
         assert isinstance(attr, classmethod)
@@ -393,6 +453,41 @@ def test_prepare_driver_options_unsupported_raises(driver_binding, kwargs, match
         opts._prepare_driver_options()
 
 
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("value", [True, False])
+def test_numba_debug_warns_and_is_ignored(value):
+    """No linking backend reads ``numba_debug``, so it is ignored -- but not
+    silently, which was the bug in #2640.
+
+    The gate is ``is not None``, not truthiness: it is the field itself that is
+    deprecated, so ``numba_debug=False`` earns the notice too even though it
+    asks for nothing.
+    """
+    with pytest.warns(DeprecationWarning, match="numba_debug is not supported by any linking backend"):
+        opts = LinkerOptions(arch="sm_80", debug=True, numba_debug=value)
+    # Warned, not rejected, and the rest of the option set is untouched.
+    assert opts._prepare_nvjitlink_options(as_bytes=True) == [b"-arch=sm_80", b"-g"]
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_numba_debug_unset_does_not_warn():
+    """The deprecation notice fires only when the field is explicitly set."""
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", DeprecationWarning)
+        options = LinkerOptions(arch="sm_80", debug=True)._prepare_nvjitlink_options(as_bytes=True)
+    assert options == [b"-arch=sm_80", b"-g"]
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_numba_debug_ignored_by_driver_backend_too(driver_binding):
+    """The cuLink driver API has no CUjit_option for numba_debug either, so it
+    is ignored there as well rather than reaching the driver."""
+    with pytest.warns(DeprecationWarning, match="numba_debug"):
+        opts = LinkerOptions(arch="sm_80", numba_debug=True)
+    formatted_options, option_keys = opts._prepare_driver_options()
+    assert not any("NUMBA" in str(key) for key in option_keys)
+
+
 def test_linker_empty_object_codes_raises():
     """Linker with no ObjectCode raises ValueError."""
     with pytest.raises(ValueError, match="At least one ObjectCode object must be provided"):
diff --git a/cuda_core/tests/test_managed_memory_warning.py b/cuda_core/tests/test_managed_memory_warning.py
index 01dd840e2ef..6edf2b7c05a 100644
--- a/cuda_core/tests/test_managed_memory_warning.py
+++ b/cuda_core/tests/test_managed_memory_warning.py
@@ -11,9 +11,10 @@
 import warnings
 
 import pytest
+from cuda_python_test_helpers.mempool import xfail_if_mempool_oom
+from helpers.memory import create_managed_memory_resource_or_skip
 
 import cuda.bindings
-from conftest import create_managed_memory_resource_or_skip, xfail_if_mempool_oom
 from cuda.core import Device, ManagedMemoryResource, ManagedMemoryResourceOptions
 from cuda.core._memory._managed_memory_resource import reset_concurrent_access_warning
 from cuda.core._utils.cuda_utils import CUDAError
diff --git a/cuda_core/tests/test_memory.py b/cuda_core/tests/test_memory.py
index 9b02908effc..06aae0cb605 100644
--- a/cuda_core/tests/test_memory.py
+++ b/cuda_core/tests/test_memory.py
@@ -2,6 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import ctypes
+import multiprocessing as mp
 import sys
 
 from cuda.bindings import driver
@@ -14,15 +15,26 @@
 import re
 
 import pytest
-from helpers import IS_WINDOWS, supports_ipc_mempool
-from helpers.buffers import DummyDeviceMemoryResource, DummyUnifiedMemoryResource, TrackingMR
-
-from conftest import (
+from helpers import supports_ipc_mempool
+from helpers.buffers import (
+    DummyDeviceMemoryResource,
+    DummyHostMemoryResource,
+    DummyUnifiedMemoryResource,
+    NumpyHostMemoryResource,
+    StubMemoryResource,
+    make_instrumented_memory_resource,
+    thread_unsafe_on_windows,
+)
+from helpers.child_processes import child_timeout_sec, kill_subprocesses
+from helpers.constants import POOL_SIZE
+from helpers.contexts import current_context_handle, no_current_context
+from helpers.memory import (
     create_managed_memory_resource_or_skip,
     create_pinned_memory_resource_or_xfail,
     skip_if_managed_memory_unsupported,
     skip_if_pinned_memory_unsupported,
 )
+
 from cuda.core import (
     Buffer,
     Device,
@@ -30,6 +42,7 @@
     DeviceMemoryResourceOptions,
     GraphMemoryResource,
     LegacyPinnedMemoryResource,
+    ManagedBuffer,
     ManagedMemoryResource,
     ManagedMemoryResourceOptions,
     MemoryResource,
@@ -39,7 +52,8 @@
     VirtualMemoryResourceOptions,
 )
 from cuda.core._dlpack import DLDeviceType
-from cuda.core._memory import IPCBufferDescriptor
+from cuda.core._memory._ipc import IPCBufferDescriptor
+from cuda.core._stream import default_stream
 from cuda.core._utils.cuda_utils import CUDAError, handle_return
 from cuda.core.typing import (
     ManagedMemoryLocationType,
@@ -50,8 +64,9 @@
     VirtualMemoryLocationType,
 )
 from cuda.core.utils import StridedMemoryView
+from cuda_python_test_helpers import IS_WINDOWS
 
-POOL_SIZE = 2097152  # 2MB size
+CHILD_TIMEOUT_SEC = child_timeout_sec()
 
 
 def _allocate_pinned_buffer_or_xfail(mr, size, *, device):
@@ -67,34 +82,6 @@ def _allocate_pinned_buffer_or_xfail(mr, size, *, device):
         raise
 
 
-class DummyHostMemoryResource(MemoryResource):
-    # Pure-host ctypes allocation; stream is accepted for interface
-    # conformance but ignored.
-    def __init__(self):
-        pass
-
-    def allocate(self, size, *, stream=None) -> Buffer:
-        # Allocate a ctypes buffer of size `size`
-        ptr = (ctypes.c_byte * size)()
-        self._ptr = ptr
-        return Buffer.from_handle(ptr=ctypes.addressof(ptr), size=size, mr=self)
-
-    def deallocate(self, ptr, size, *, stream=None):
-        del self._ptr
-
-    @property
-    def is_device_accessible(self) -> bool:
-        return False
-
-    @property
-    def is_host_accessible(self) -> bool:
-        return True
-
-    @property
-    def device_id(self) -> int:
-        raise RuntimeError("the pinned memory resource is not bound to any GPU")
-
-
 class DummyPinnedMemoryResource(MemoryResource):
     # cuMemAllocHost / cuMemFreeHost are synchronous; stream is accepted
     # for interface conformance but ignored.
@@ -133,8 +120,6 @@ def test_package_contents():
         "DeviceMemoryResource",
         "DeviceMemoryResourceOptions",
         "GraphMemoryResource",
-        "IPCAllocationHandle",
-        "IPCBufferDescriptor",
         "LegacyPinnedMemoryResource",
         "ManagedBuffer",
         "ManagedMemoryResource",
@@ -173,6 +158,51 @@ def test_buffer_initialization():
         buffer_initialization(MemoryResource())
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_buffer_direct_init_forbidden():
+    """Buffers must come from a MemoryResource, never from ``Buffer()``."""
+    with pytest.raises(RuntimeError, match=r"^Buffer objects cannot be instantiated directly\."):
+        Buffer()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_buffer_context_manager_closes_on_exit():
+    """``with buf`` yields the buffer, closes it on exit, and does not swallow inner exceptions."""
+    device = Device()
+    device.set_current()
+    mr = DummyDeviceMemoryResource(device)
+    buf = mr.allocate(size=64, stream=device.default_stream)
+    with buf as entered:
+        assert entered is buf
+        assert buf.handle != 0
+    assert buf.handle == 0
+    assert buf.memory_resource is None
+
+    buf = mr.allocate(size=64, stream=device.default_stream)
+    with pytest.raises(RuntimeError, match="^boom$"), buf:
+        raise RuntimeError("boom")
+    assert buf.handle == 0
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_memory_resource_abstract_stubs():
+    """Every abstract MemoryResource member reports itself as unimplemented."""
+    device = Device()
+    device.set_current()
+    mr = MemoryResource()
+    stream = device.default_stream
+    with pytest.raises(TypeError, match=r"^MemoryResource\.allocate must be implemented"):
+        mr.allocate(1, stream=stream)
+    with pytest.raises(TypeError, match=r"^MemoryResource\.deallocate must be implemented"):
+        mr.deallocate(0, 1, stream=stream)
+    with pytest.raises(TypeError, match=r"^MemoryResource\.is_device_accessible must be implemented"):
+        _ = mr.is_device_accessible
+    with pytest.raises(TypeError, match=r"^MemoryResource\.is_host_accessible must be implemented"):
+        _ = mr.is_host_accessible
+    with pytest.raises(TypeError, match=r"^MemoryResource\.device_id must be implemented"):
+        _ = mr.device_id
+
+
 def buffer_copy_to(dummy_mr: MemoryResource, device: Device, check=False):
     src_buffer = dummy_mr.allocate(size=1024)
     dst_buffer = dummy_mr.allocate(size=1024)
@@ -235,6 +265,50 @@ def test_buffer_copy_from():
     buffer_copy_from(DummyPinnedMemoryResource(device), device, check=True)
 
 
+def test_buffer_copy_to_size_mismatch_raises():
+    device = Device()
+    device.set_current()
+    mr = DummyDeviceMemoryResource(device)
+    stream = device.create_stream()
+    src_buffer = mr.allocate(size=1024)
+    dst_buffer = mr.allocate(size=2048)
+
+    with pytest.raises(ValueError, match="buffer sizes mismatch"):
+        src_buffer.copy_to(dst_buffer, stream=stream)
+
+    dst_buffer.close()
+    src_buffer.close()
+
+
+def test_buffer_copy_from_size_mismatch_raises():
+    device = Device()
+    device.set_current()
+    mr = DummyDeviceMemoryResource(device)
+    stream = device.create_stream()
+    src_buffer = mr.allocate(size=1024)
+    dst_buffer = mr.allocate(size=2048)
+
+    with pytest.raises(ValueError, match="buffer sizes mismatch"):
+        dst_buffer.copy_from(src_buffer, stream=stream)
+
+    dst_buffer.close()
+    src_buffer.close()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_copy_to_auto_dst_requires_memory_resource():
+    """``copy_to()`` cannot mint a destination without a memory resource."""
+    device = Device()
+    device.set_current()
+    owner = (ctypes.c_byte * 32)()
+    buf = Buffer.from_handle(ctypes.addressof(owner), 32, owner=owner)
+    try:
+        with pytest.raises(ValueError, match="does not have a memory_resource"):
+            buf.copy_to(stream=device.default_stream)
+    finally:
+        buf.close()
+
+
 def _bytes_repeat(pattern: bytes, size: int) -> bytes:
     assert len(pattern) > 0
     assert size % len(pattern) == 0
@@ -248,9 +322,8 @@ def _pattern_bytes(value) -> bytes:
 
 
 @pytest.fixture(params=["device", "unified", "pinned"])
-def fill_env(request):
-    device = Device()
-    device.set_current()
+def fill_env(request, init_cuda):
+    device = init_cuda
     if request.param == "device":
         mr = DummyDeviceMemoryResource(device)
     elif request.param == "unified":
@@ -313,6 +386,7 @@ def fill_env(request):
     )
 
 
+@thread_unsafe_on_windows
 @pytest.mark.parametrize("value,size,exc", _FILL_CASES)
 def test_buffer_fill(fill_env, value, size, exc):
     device, mr = fill_env
@@ -356,6 +430,7 @@ def test_buffer_external_host():
     a = (ctypes.c_byte * 20)()
     ptr = ctypes.addressof(a)
     buffer = Buffer.from_handle(ptr, 20, owner=a)
+    assert buffer.owner is a
     assert not buffer.is_device_accessible
     assert buffer.is_host_accessible
     assert buffer.device_id == -1
@@ -473,11 +548,12 @@ def test_mr_deallocate_called_on_close():
     """Buffer.from_handle(mr=mr) calls mr.deallocate() on close (issue #1619)."""
     device = Device()
     device.set_current()
-    mr = TrackingMR()
+    TrackingMR, telemetry = make_instrumented_memory_resource(DummyDeviceMemoryResource, track_active=True)
+    mr = TrackingMR(device)
     buf = mr.allocate(1024)
-    assert len(mr.active) == 1
+    assert len(telemetry["active"]) == 1
     buf.close()
-    assert len(mr.active) == 0
+    assert len(telemetry["active"]) == 0
 
 
 def test_mr_deallocate_called_on_gc():
@@ -486,12 +562,13 @@ def test_mr_deallocate_called_on_gc():
 
     device = Device()
     device.set_current()
-    mr = TrackingMR()
+    TrackingMR, telemetry = make_instrumented_memory_resource(DummyDeviceMemoryResource, track_active=True)
+    mr = TrackingMR(device)
     buf = mr.allocate(1024)
-    assert len(mr.active) == 1
+    assert len(telemetry["active"]) == 1
     del buf
     gc.collect()
-    assert len(mr.active) == 0
+    assert len(telemetry["active"]) == 0
 
 
 def test_mr_deallocate_receives_stream():
@@ -499,67 +576,430 @@ def test_mr_deallocate_receives_stream():
     device = Device()
     device.set_current()
     stream = device.create_stream()
-    received = {}
-
-    class StreamCaptureMR(TrackingMR):
-        def deallocate(self, ptr, size, *, stream=None):
-            received["stream"] = stream
-            super().deallocate(ptr, size, stream=stream)
-
-    mr = StreamCaptureMR()
+    CapturingMR, telemetry = make_instrumented_memory_resource(DummyDeviceMemoryResource, record_streams=True)
+    mr = CapturingMR(device)
     buf = mr.allocate(1024)
     buf.close(stream)
-    assert received["stream"].handle == stream.handle
-
-
-def test_mr_dealloc_callback_falls_back_to_default_stream():
-    """When a Buffer's device-pointer handle has no attached deallocation
-    stream (e.g. buffers minted via :meth:`Buffer.from_handle` from DLPack
-    import, IPC import, or third-party adapters), the C++ deleter callback
-    must fall back to the default stream rather than passing ``stream=None``
-    to ``mr.deallocate``. Stream-ordered MRs validate the stream and would
-    otherwise raise ``TypeError`` from inside the ``noexcept`` callback,
-    which only logs a warning and silently leaks the allocation. See
-    `#2001 <https://github.com/NVIDIA/cuda-python/issues/2001>`__.
-    """
+    assert telemetry["deallocations"][-1]["stream"].handle == stream.handle
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+@pytest.mark.parametrize(
+    ("configuration", "destruction"),
+    [
+        ("initialization", "close"),
+        ("initialization", "gc"),
+        ("setter", "close"),
+        ("setter", "gc"),
+        ("close", "close"),
+    ],
+)
+def test_buffer_deallocation_stream_configuration_paths(configuration, destruction):
+    """Creation, mutation, and close overrides use the requested stream."""
     import gc
 
-    from cuda.core._stream import Stream_accept, default_stream
+    device = Device()
+    device.set_current()
+    initial_stream = device.create_stream()
+    target_stream = device.create_stream()
+    CapturingMR, telemetry = make_instrumented_memory_resource(record_streams=True)
+    mr = CapturingMR(device)
+
+    stream = target_stream if configuration == "initialization" else initial_stream
+    buf = Buffer.from_handle(1, 1024, mr=mr, stream=stream)
+    if configuration == "setter":
+        handle = buf.handle
+        buf.set_deallocation_stream(target_stream)
+        assert buf.handle == handle
+        assert buf.size == 1024
+
+    if destruction == "close":
+        buf.close(stream=target_stream if configuration == "close" else None)
+    else:
+        del buf
+        gc.collect()
+
+    assert len(telemetry["deallocations"]) == 1
+    assert telemetry["deallocations"][0]["stream"].handle == target_stream.handle
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_set_deallocation_stream_rejects_none_and_closed_buffer():
+    device = Device()
+    device.set_current()
+    stream = device.create_stream()
+    mr = StubMemoryResource(device)
+    buf = Buffer.from_handle(1, 1024, mr=mr, stream=stream)
+
+    with pytest.raises(TypeError, match="stream is required"):
+        buf.set_deallocation_stream(None)
+
+    buf.close()
+    with pytest.raises(RuntimeError, match="Buffer has been closed"):
+        buf.set_deallocation_stream(stream)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_deallocation_stream_does_not_mutate_buffer():
+    device = Device()
+    device.set_current()
+    initial_stream = device.create_stream()
+    closed_stream = device.create_stream()
+    CapturingMR, telemetry = make_instrumented_memory_resource(record_streams=True)
+    mr = CapturingMR(device)
+    buf = Buffer.from_handle(1, 1024, mr=mr, stream=initial_stream)
+    closed_stream.close()
+
+    with pytest.raises(RuntimeError, match="Stream has been closed"):
+        buf.set_deallocation_stream(closed_stream)
+    assert not buf.is_closed
+
+    with pytest.raises(RuntimeError, match="Stream has been closed"):
+        buf.close(stream=closed_stream)
+    assert not buf.is_closed
 
+    buf.close()
+    assert len(telemetry["deallocations"]) == 1
+    assert telemetry["deallocations"][0]["stream"].handle == initial_stream.handle
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_buffer_rejected_before_active_operations():
     device = Device()
     device.set_current()
-    captured = {}
+    stream = device.create_stream()
+    closed = Buffer.from_handle(1, 16, owner=object())
+    live = Buffer.from_handle(2, 16, owner=object())
+    closed.close()
+
+    for operation in (
+        lambda: closed.copy_to(live, stream=stream),
+        lambda: closed.copy_from(live, stream=stream),
+        lambda: closed.fill(0, stream=stream),
+        closed.__dlpack__,
+        closed.__dlpack_device__,
+        lambda: closed.device_id,
+        lambda: closed.is_device_accessible,
+        lambda: closed.is_host_accessible,
+        lambda: closed.is_managed,
+        lambda: closed.ipc_descriptor,
+    ):
+        with pytest.raises(RuntimeError, match="Buffer has been closed"):
+            operation()
+
+    with pytest.raises(RuntimeError, match="Buffer has been closed"):
+        live.copy_to(closed, stream=stream)
+    with pytest.raises(RuntimeError, match="Buffer has been closed"):
+        live.copy_from(closed, stream=stream)
+    live.close()
 
-    class StrictCapturingMR(MemoryResource):
-        # Models a stream-ordered MR: deallocate validates the stream
-        # the same way DeviceMemoryResource.deallocate does.
-        @property
-        def is_device_accessible(self):
-            return True
 
-        @property
-        def is_host_accessible(self):
-            return False
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_memory_pool_rejected_before_active_operations(mempool_device):
+    mr = DeviceMemoryResource(mempool_device)
+    peer_access = mr.peer_accessible_by
+    mr.close()
 
-        @property
-        def device_id(self):
-            return device.device_id
+    assert mr.is_closed
+    assert bool(mr) is True  # Preserve backward-compatible truthiness after close.
+    for operation in (
+        lambda: mr.allocate(16, stream=mempool_device.default_stream),
+        lambda: mr.attributes,
+        lambda: mr.peer_accessible_by,
+        lambda: len(peer_access),
+        lambda: mr.allocation_handle,
+    ):
+        with pytest.raises(RuntimeError, match="DeviceMemoryResource has been closed"):
+            operation()
 
-        def allocate(self, size, *, stream):
-            raise NotImplementedError  # not used; we use from_handle below
 
-        def deallocate(self, ptr, size, *, stream):
-            captured["stream"] = Stream_accept(stream)
+@pytest.mark.parametrize("buffer_type", [Buffer, ManagedBuffer])
+def test_from_handle_mr_records_default_stream(buffer_type):
+    """When a Buffer/ManagedBuffer is minted via :meth:`from_handle` with ``mr``
+    but without an explicit ``stream=``, the deallocation stream is recorded at
+    creation as ``default_stream()`` (not chosen later in the destructor).
+    See `#2497`.
+    """
+    import gc
 
-    mr = StrictCapturingMR()
-    # Buffer.from_handle binds mr but does not attach a deallocation stream.
-    # ptr=1 is fine because StrictCapturingMR.deallocate does not free.
-    buf = Buffer.from_handle(1, 1024, mr=mr)
+    device = Device()
+    device.set_current()
+    CapturingMR, telemetry = make_instrumented_memory_resource(record_streams=True)
+    mr = CapturingMR(device)
+    # ptr=1 is fine because StubMemoryResource.deallocate does not free.
+    buf = buffer_type.from_handle(1, 1024, mr=mr)
+    del buf
+    gc.collect()
+
+    assert telemetry["deallocations"], "deallocate was not invoked (callback raised and leaked)"
+    assert telemetry["deallocations"][-1]["stream"].handle == default_stream().handle
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+@pytest.mark.parametrize("buffer_type", [Buffer, ManagedBuffer])
+def test_from_handle_mr_records_explicit_stream(buffer_type):
+    """Buffer/ManagedBuffer.from_handle(..., mr=mr, stream=s) stores s for teardown."""
+    import gc
+
+    device = Device()
+    device.set_current()
+    stream = device.create_stream()
+    CapturingMR, telemetry = make_instrumented_memory_resource(record_streams=True)
+    mr = CapturingMR(device)
+    buf = buffer_type.from_handle(1, 1024, mr=mr, stream=stream)
     del buf
     gc.collect()
 
-    assert "stream" in captured, "deallocate was not invoked (callback raised and leaked)"
-    assert captured["stream"].handle == default_stream().handle
+    assert telemetry["deallocations"][-1]["stream"].handle == stream.handle
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+@pytest.mark.parametrize("buffer_type", [Buffer, ManagedBuffer])
+def test_from_handle_stream_requires_mr(buffer_type):
+    device = Device()
+    device.set_current()
+    stream = device.create_stream()
+    with pytest.raises(ValueError, match="stream requires a memory resource"):
+        buffer_type.from_handle(1, 1024, stream=stream)
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-4-6")
+def test_close_with_default_stream_requires_context():
+    """Buffer.close(stream=default_stream()) raises when no context is current.
+
+    ``default_stream()`` has no bound context, so the close path must find
+    a current context to anchor the free.  Without one it should raise rather
+    than silently record an unusable stream handle.
+    """
+    device = Device()
+    device.set_current()
+    stream = device.create_stream()
+    mr = StubMemoryResource(device)
+    # Use a real stream at creation so _init succeeds without a current context later.
+    buf = Buffer.from_handle(1, 1024, mr=mr, stream=stream)
+
+    with no_current_context():
+        assert current_context_handle() == 0
+        with pytest.raises(RuntimeError, match="no CUDA context is current"):
+            buf.close(stream=default_stream())
+
+    buf.close()  # clean up using the recorded stream (which carries a context)
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+@pytest.mark.parametrize("buffer_type", [Buffer, ManagedBuffer])
+def test_from_handle_mr_default_stream_requires_context(buffer_type):
+    """Owning from_handle with the default stream needs a current context."""
+    device = Device()
+    device.set_current()
+    mr = StubMemoryResource(device)
+    with no_current_context():
+        assert current_context_handle() == 0
+        with pytest.raises(RuntimeError, match="no CUDA context is current"):
+            buffer_type.from_handle(1, 1024, mr=mr)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+@pytest.mark.parametrize("buffer_type", [Buffer, ManagedBuffer])
+def test_from_handle_mr_explicit_stream_without_current_context(buffer_type):
+    """A context-bound stream makes owning from_handle context-independent."""
+    device = Device()
+    device.set_current()
+    stream = device.create_stream()
+    CapturingMR, telemetry = make_instrumented_memory_resource(record_streams=True)
+    mr = CapturingMR(device)
+    with no_current_context():
+        assert current_context_handle() == 0
+        buf = buffer_type.from_handle(1, 1024, mr=mr, stream=stream)
+        buf.close()
+        assert current_context_handle() == 0
+
+    assert telemetry["deallocations"][-1]["stream"].handle == stream.handle
+
+
+_HOST_ONLY_MRS = [
+    DummyHostMemoryResource,
+    pytest.param(NumpyHostMemoryResource, marks=pytest.mark.skipif(np is None, reason="numpy is not installed")),
+]
+
+
+@pytest.mark.agent_authored(model="claude-fable-5-1")
+@pytest.mark.parametrize("mr_cls", _HOST_ONLY_MRS)
+def test_from_handle_host_only_mr_without_current_context(mr_cls, capfd):
+    """Host-only memory needs no current context to create or free a Buffer."""
+    device = Device()
+    device.set_current()
+    mr = mr_cls()
+
+    previous = handle_return(driver.cuCtxPopCurrent())
+    assert int(previous) != 0
+    try:
+        assert int(handle_return(driver.cuCtxGetCurrent())) == 0
+        buf = mr.allocate(64)
+        assert buf.is_host_accessible
+        buf.close()
+        assert int(handle_return(driver.cuCtxGetCurrent())) == 0
+    finally:
+        handle_return(driver.cuCtxSetCurrent(previous))
+
+    assert "Warning" not in capfd.readouterr().err
+
+
+def _host_only_child_main(mr_cls):
+    """Allocate and free host-only memory in a process that never initialized CUDA."""
+    buf = mr_cls().allocate(64)
+    assert buf.is_host_accessible
+    buf.close()
+    err, _ = driver.cuCtxGetCurrent()
+    assert err == driver.CUresult.CUDA_ERROR_NOT_INITIALIZED, err
+
+
+@pytest.mark.agent_authored(model="claude-fable-5-1")
+@pytest.mark.parametrize("mr_cls", _HOST_ONLY_MRS)
+def test_from_handle_host_only_mr_without_cuda_init(mr_cls, capfd):
+    """Host-only buffers work in a spawned process that never initializes CUDA."""
+    process = mp.Process(target=_host_only_child_main, args=(mr_cls,))
+    process.start()
+    process.join(timeout=CHILD_TIMEOUT_SEC)
+    survivors = kill_subprocesses(process)
+    assert not survivors, "child did not exit within timeout"
+    assert process.exitcode == 0, f"child exited with {process.exitcode}"
+    assert "Warning" not in capfd.readouterr().err
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_mr_deallocation_failure_warns(capfd):
+    """Destructor-path MR failures are contained and reported."""
+    device = Device()
+    device.set_current()
+    FailingMR, _ = make_instrumented_memory_resource(deallocate_error=RuntimeError("expected deallocation failure"))
+    buf = Buffer.from_handle(1, 1024, mr=FailingMR(device))
+    buf.close()
+
+    assert (
+        "Warning: mr.deallocate() failed during Buffer destruction: expected deallocation failure"
+    ) in capfd.readouterr().err
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+@pytest.mark.parametrize("replace_stream", [False, True])
+def test_mr_deallocation_without_current_context(init_cuda, capsys, replace_stream):
+    """MR-backed Buffer teardown activates the recorded context when none is current."""
+    TrackingMR, telemetry = make_instrumented_memory_resource(DummyDeviceMemoryResource, track_active=True)
+    mr = TrackingMR(init_cuda)
+    buf = mr.allocate(1024)
+    stream = init_cuda.create_stream() if replace_stream else None
+    assert len(telemetry["active"]) == 1
+
+    with no_current_context():
+        assert current_context_handle() == 0
+
+        buf.close(stream)
+
+        assert len(telemetry["active"]) == 0
+        assert current_context_handle() == 0
+        assert "mr.deallocate() failed" not in capsys.readouterr().err
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+@pytest.mark.parametrize("replace_stream", [False, True])
+def test_mr_deallocation_with_foreign_context(device_x2, capsys, replace_stream):
+    """MR-backed Buffer teardown switches away from an unrelated current context."""
+    alloc_dev, foreign_dev = device_x2
+    alloc_dev.set_current()
+    TrackingMR, telemetry = make_instrumented_memory_resource(DummyDeviceMemoryResource, track_active=True)
+    mr = TrackingMR(alloc_dev)
+    buf = mr.allocate(1024)
+    stream = alloc_dev.create_stream() if replace_stream else None
+    assert len(telemetry["active"]) == 1
+    alloc_ctx = current_context_handle()
+
+    foreign_dev.set_current()
+    foreign_ctx = current_context_handle()
+    assert foreign_ctx != 0
+    assert foreign_ctx != alloc_ctx
+
+    try:
+        buf.close(stream)
+
+        assert len(telemetry["active"]) == 0
+        assert current_context_handle() == foreign_ctx
+        assert "mr.deallocate() failed" not in capsys.readouterr().err
+    finally:
+        alloc_dev.set_current()
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_mr_deallocate_raises_on_driver_error(mempool_device):
+    """An explicit mr.deallocate() call propagates driver errors to the caller.
+
+    Buffer teardown must not raise, so the containment lives in the destruction
+    callback rather than in deallocate() itself. See `#2497`.
+    """
+    dev = mempool_device
+    stream = dev.create_stream()
+    mr = DeviceMemoryResource(dev, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+
+    with pytest.raises(CUDAError):
+        mr.deallocate(0xDEADBEEF, 256, stream=stream)
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+def test_pool_buffer_deallocates_without_current_context(mempool_device, capfd):
+    """Pool Buffer.close frees on the recorded stream with no current context."""
+    dev = mempool_device
+    stream = dev.create_stream()
+    mr = DeviceMemoryResource(dev, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+    size = 256
+    buf = mr.allocate(size, stream=stream)
+    stream.sync()
+    used_after_alloc = mr.attributes.used_mem_current
+
+    with no_current_context():
+        assert current_context_handle() == 0
+
+        buf.close()
+        stream.sync()
+
+        assert mr.attributes.used_mem_current < used_after_alloc
+        assert current_context_handle() == 0
+        err = capfd.readouterr().err
+        assert "cuMemFreeAsync failed" not in err
+        assert "mr.deallocate() failed" not in err
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+def test_pool_buffer_deallocates_with_foreign_context(mempool_device_x2, capfd):
+    """Pool Buffer.close frees under the recorded context while another is current."""
+    alloc_dev, foreign_dev = mempool_device_x2
+    alloc_dev.set_current()
+    stream = alloc_dev.create_stream()
+    mr = DeviceMemoryResource(alloc_dev, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+    size = 256
+    buf = mr.allocate(size, stream=stream)
+    stream.sync()
+    used_after_alloc = mr.attributes.used_mem_current
+    alloc_ctx = current_context_handle()
+
+    foreign_dev.set_current()
+    foreign_ctx = current_context_handle()
+    assert foreign_ctx != 0
+    assert foreign_ctx != alloc_ctx
+
+    try:
+        buf.close()
+        assert current_context_handle() == foreign_ctx
+
+        # Observe the free on the allocation device, then restore the foreign context.
+        alloc_dev.set_current()
+        stream.sync()
+        assert mr.attributes.used_mem_current < used_after_alloc
+        foreign_dev.set_current()
+
+        err = capfd.readouterr().err
+        assert "cuMemFreeAsync failed" not in err
+    finally:
+        alloc_dev.set_current()
 
 
 def test_memory_resource_and_owner_disallowed():
@@ -617,6 +1057,8 @@ def test_buffer_dunder_dlpack_device_success(DummyMR, expected):
 
 
 def test_buffer_dunder_dlpack_device_failure():
+    # avoids an error capturing the default stream with no context
+    Device().set_current()
     dummy_mr = NullMemoryResource()
     buffer = dummy_mr.allocate(size=1024)
     with pytest.raises(BufferError, match=r"^buffer is neither device-accessible nor host-accessible$"):
@@ -624,6 +1066,8 @@ def test_buffer_dunder_dlpack_device_failure():
 
 
 def test_buffer_dlpack_failure_clean_up():
+    # avoids an error capturing the default stream with no context
+    Device().set_current()
     dummy_mr = NullMemoryResource()
     buffer = dummy_mr.allocate(size=1024)
     before = sys.getrefcount(buffer)
@@ -750,6 +1194,26 @@ def test_pinned_memory_resource_initialization(init_cuda):
     buffer.close()
 
 
+@pytest.mark.agent_authored(model="cursor-grok-4.5")
+def test_pinned_memory_resource_rejects_unsupported_host_pool(init_cuda):
+    """allocate() must fail on devices without host memory pool support (see #2486)."""
+    device = init_cuda
+    if device.properties.host_memory_pools_supported:
+        pytest.skip("Device supports host memory pools")
+
+    try:
+        mr = PinnedMemoryResource(PinnedMemoryResourceOptions(max_size=POOL_SIZE))
+    except CUDAError as exc:
+        if "CUDA_ERROR_NOT_SUPPORTED" in str(exc):
+            pytest.skip("PinnedMemoryResource is not supported on this platform/device")
+        raise
+    try:
+        with pytest.raises(RuntimeError, match="does not support.*LegacyPinnedMemoryResource"):
+            mr.allocate(1024, stream=device.default_stream)
+    finally:
+        mr.close()
+
+
 def test_managed_memory_resource_initialization(init_cuda):
     device = Device()
     skip_if_managed_memory_unsupported(device)
@@ -1093,9 +1557,9 @@ def test_device_memory_resource_with_options(init_cuda):
     buffer.close(stream)
 
     # Test memory copying between buffers from same pool
-    src_buffer = mr.allocate(64, stream=device.default_stream)
-    dst_buffer = mr.allocate(64, stream=device.default_stream)
     stream = device.create_stream()
+    src_buffer = mr.allocate(64, stream=stream)
+    dst_buffer = mr.allocate(64, stream=stream)
     src_buffer.copy_to(dst_buffer, stream=stream)
     device.sync()
     dst_buffer.close()
@@ -1141,9 +1605,9 @@ def test_pinned_memory_resource_with_options(init_cuda):
     buffer.close(stream)
 
     # Test memory copying between buffers from same pool
-    src_buffer = mr.allocate(64, stream=device.default_stream)
-    dst_buffer = mr.allocate(64, stream=device.default_stream)
     stream = device.create_stream()
+    src_buffer = mr.allocate(64, stream=stream)
+    dst_buffer = mr.allocate(64, stream=stream)
     src_buffer.copy_to(dst_buffer, stream=stream)
     device.sync()
     dst_buffer.close()
@@ -1188,13 +1652,15 @@ def test_managed_memory_resource_with_options(init_cuda):
     buffer.close(stream)
 
     # Test memory copying between buffers from same pool
-    src_buffer = mr.allocate(64, stream=device.default_stream)
-    dst_buffer = mr.allocate(64, stream=device.default_stream)
     stream = device.create_stream()
+    src_buffer = mr.allocate(64, stream=stream)
+    dst_buffer = mr.allocate(64, stream=stream)
     src_buffer.copy_to(dst_buffer, stream=stream)
     device.sync()
     dst_buffer.close()
     src_buffer.close()
+    # TODO(seberg): 2026-06: mr close may be unsafe with incomplete `buf.close()`
+    device.sync()
 
 
 def test_managed_memory_resource_preferred_location_default(init_cuda):
@@ -1451,11 +1917,13 @@ def test_pinned_mr_numa_id_default_no_ipc(init_cuda):
     device = Device()
     skip_if_pinned_memory_unsupported(device)
 
-    mr = create_pinned_memory_resource_or_xfail(PinnedMemoryResourceOptions(), xfail_device=device)
+    mr = create_pinned_memory_resource_or_xfail(PinnedMemoryResourceOptions(max_size=POOL_SIZE), xfail_device=device)
     assert mr.numa_id == -1
     mr.close()
 
-    mr = create_pinned_memory_resource_or_xfail(PinnedMemoryResourceOptions(ipc_enabled=False), xfail_device=device)
+    mr = create_pinned_memory_resource_or_xfail(
+        PinnedMemoryResourceOptions(ipc_enabled=False, max_size=POOL_SIZE), xfail_device=device
+    )
     assert mr.numa_id == -1
     mr.close()
 
@@ -1490,7 +1958,9 @@ def test_pinned_mr_numa_id_explicit(init_cuda):
     if host_numa_id < 0:
         pytest.skip("System does not support NUMA")
 
-    mr = create_pinned_memory_resource_or_xfail(PinnedMemoryResourceOptions(numa_id=host_numa_id), xfail_device=device)
+    mr = create_pinned_memory_resource_or_xfail(
+        PinnedMemoryResourceOptions(numa_id=host_numa_id, max_size=POOL_SIZE), xfail_device=device
+    )
     assert mr.numa_id == host_numa_id
     mr.close()
 
@@ -1513,9 +1983,11 @@ def test_pinned_mr_numa_id_negative_error(init_cuda):
     skip_if_pinned_memory_unsupported(device)
 
     with pytest.raises(ValueError, match="numa_id must be >= 0"):
+        # uncapped-pool-ok: numa_id is validated before the pool is created
         PinnedMemoryResource(PinnedMemoryResourceOptions(numa_id=-1))
 
     with pytest.raises(ValueError, match="numa_id must be >= 0"):
+        # uncapped-pool-ok: numa_id is validated before the pool is created
         PinnedMemoryResource(PinnedMemoryResourceOptions(numa_id=-42))
 
 
@@ -1616,11 +2088,11 @@ def test_mempool_attributes_repr(memory_resource_factory):
     device.set_current()
 
     if MR is DeviceMemoryResource:
-        mr = MR(device, options={"max_size": 2048})
+        mr = MR(device, options=DeviceMemoryResourceOptions(max_size=2048))
     elif MR is PinnedMemoryResource:
-        mr = MR(options={"max_size": 2048})
+        mr = MR(options=PinnedMemoryResourceOptions(max_size=2048))
     elif MR is ManagedMemoryResource:
-        mr = create_managed_memory_resource_or_skip(options={})
+        mr = create_managed_memory_resource_or_skip(options=ManagedMemoryResourceOptions())
 
     buffer1 = mr.allocate(64, stream=device.default_stream)
     buffer2 = mr.allocate(64, stream=device.default_stream)
@@ -1653,11 +2125,11 @@ def test_mempool_attributes_ownership(memory_resource_factory):
     device.set_current()
 
     if MR is DeviceMemoryResource:
-        mr = MR(device, {"max_size": POOL_SIZE})
+        mr = MR(device, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
     elif MR is PinnedMemoryResource:
-        mr = MR({"max_size": POOL_SIZE})
+        mr = MR(PinnedMemoryResourceOptions(max_size=POOL_SIZE))
     elif MR is ManagedMemoryResource:
-        mr = create_managed_memory_resource_or_skip({})
+        mr = create_managed_memory_resource_or_skip(ManagedMemoryResourceOptions())
 
     attributes = mr.attributes
     mr.close()
@@ -1773,16 +2245,15 @@ def test_legacy_pinned_allocate_zero_size(init_cuda):
     assert int(buf.handle) == 0
 
 
-def test_legacy_pinned_device_id_raises():
-    """LegacyPinnedMemoryResource.device_id raises; pinned memory is not bound to a GPU."""
+def test_legacy_pinned_device_id_is_not_applicable():
+    """LegacyPinnedMemoryResource.device_id is -1, as documented for memory not bound to a device."""
     mr = LegacyPinnedMemoryResource()
-    with pytest.raises(RuntimeError, match="not bound to any GPU"):
-        _ = mr.device_id
+    assert mr.device_id == -1
 
 
 def test_synchronous_memory_resource_basic(init_cuda):
     """_SynchronousMemoryResource exercises properties and allocate paths (zero, non-zero, with-stream)."""
-    from cuda.core._memory._legacy import _SynchronousMemoryResource
+    from cuda.core._memory._synchronous_memory_resource import _SynchronousMemoryResource
 
     dev = Device()
     mr = _SynchronousMemoryResource(dev.device_id)
@@ -1815,7 +2286,7 @@ def test_synchronous_memory_resource_basic(init_cuda):
 
 def test_synchronous_memory_resource_deallocate_accepts_stream(init_cuda):
     """_SynchronousMemoryResource.deallocate accepts an explicit stream."""
-    from cuda.core._memory._legacy import _SynchronousMemoryResource
+    from cuda.core._memory._synchronous_memory_resource import _SynchronousMemoryResource
 
     dev = Device()
     mr = _SynchronousMemoryResource(dev.device_id)
@@ -1825,6 +2296,101 @@ def test_synchronous_memory_resource_deallocate_accepts_stream(init_cuda):
     stream.close()
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_synchronous_memory_resource_uses_its_context(device_x2):
+    """Synchronous allocation targets its stored context and restores the current one."""
+    from cuda.core._memory._synchronous_memory_resource import _SynchronousMemoryResource
+
+    alloc_dev, current_dev = device_x2
+    alloc_dev.set_current()
+    stream = alloc_dev.create_stream()
+    mr = _SynchronousMemoryResource(alloc_dev.device_id, alloc_dev.context)
+
+    current_dev.set_current()
+    current_context = current_context_handle()
+
+    buf = mr.allocate(64, stream=stream)
+    try:
+        pointer_context = handle_return(
+            driver.cuPointerGetAttribute(
+                driver.CUpointer_attribute.CU_POINTER_ATTRIBUTE_CONTEXT,
+                int(buf.handle),
+            )
+        )
+        pointer_device = handle_return(
+            driver.cuPointerGetAttribute(
+                driver.CUpointer_attribute.CU_POINTER_ATTRIBUTE_DEVICE_ORDINAL,
+                int(buf.handle),
+            )
+        )
+        assert int(pointer_context) == int(alloc_dev.context.handle)
+        assert pointer_device == alloc_dev.device_id
+        assert current_context_handle() == current_context
+    finally:
+        buf.close(stream=stream)
+        stream.close()
+
+    assert current_context_handle() == current_context
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_synchronous_memory_resource_restores_context_after_failure(device_x2):
+    """A failed synchronous allocation restores the context that was current."""
+    from cuda.core._memory._synchronous_memory_resource import _SynchronousMemoryResource
+
+    alloc_dev, current_dev = device_x2
+    alloc_dev.set_current()
+    mr = _SynchronousMemoryResource(alloc_dev.device_id, alloc_dev.context)
+    current_dev.set_current()
+    current_context = current_context_handle()
+
+    with pytest.raises(CUDAError):
+        mr.allocate(sys.maxsize)
+
+    assert current_context_handle() == current_context
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_synchronous_memory_resource_default_stream_deallocates_in_own_context(device_x2, capsys):
+    """Buffer teardown with no explicit stream frees in the resource's own
+    context, not whatever context happens to be current at close() time."""
+    from cuda.core._memory._synchronous_memory_resource import _SynchronousMemoryResource
+
+    alloc_dev, current_dev = device_x2
+    alloc_dev.set_current()
+    mr = _SynchronousMemoryResource(alloc_dev.device_id, alloc_dev.context)
+
+    current_dev.set_current()
+    current_context = current_context_handle()
+
+    buf = mr.allocate(64)  # no explicit stream: records a context-bound default token
+    assert current_context_handle() == current_context
+
+    buf.close()  # no explicit stream: reuses the recorded token
+    assert current_context_handle() == current_context
+    assert capsys.readouterr().err == ""
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_synchronous_memory_resource_allocate_without_current_context(device_x2, capsys):
+    """allocate()/close() with no explicit stream succeed with no context
+    current, instead of raising or leaking the allocation (#2311)."""
+    from cuda.core._memory._synchronous_memory_resource import _SynchronousMemoryResource
+
+    alloc_dev, current_dev = device_x2
+    alloc_dev.set_current()
+    mr = _SynchronousMemoryResource(alloc_dev.device_id, alloc_dev.context)
+    current_dev.set_current()
+
+    with no_current_context():
+        buf = mr.allocate(64)
+        assert current_context_handle() == 0
+        buf.close()
+        assert current_context_handle() == 0
+
+    assert capsys.readouterr().err == ""
+
+
 @pytest.mark.parametrize(
     ("method", "spec", "match"),
     [
@@ -1848,6 +2414,23 @@ def test_vmm_options_handle_type_win32_raises():
         VirtualMemoryResourceOptions._handle_type_to_driver("win32")
 
 
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("location_type", ["host", "host_numa", "host_numa_current"])
+def test_vmm_host_location_types_report_host_accessible(location_type):
+    """Every host-backed location type reports is_host_accessible.
+
+    __init__ classifies "host", "host_numa" and "host_numa_current" alike when
+    deciding the resource is not bound to a device, so is_host_accessible must
+    agree; otherwise a NUMA-located resource claims to be neither host- nor
+    device-accessible.
+    """
+    device = Device()
+    device.set_current()
+    mr = VirtualMemoryResource(device, config=VirtualMemoryResourceOptions(location_type=location_type))
+    assert mr.device is None
+    assert mr.is_host_accessible is True
+
+
 def test_device_memory_resource_peer_accessible_by_non_owned(mempool_device):
     """peer_accessible_by on a non-owned (default) DMR queries the driver live."""
     dev = mempool_device
@@ -1896,3 +2479,74 @@ def test_dmr_peer_accessible_by_setter_empty(mempool_device):
     assert set(mr.peer_accessible_by) == set()
     mr.peer_accessible_by = []
     assert set(mr.peer_accessible_by) == set()
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_mempool_attributes_cannot_instantiate_directly():
+    """_MemPoolAttributes cannot be instantiated directly."""
+    from cuda.core._memory._memory_pool import _MemPoolAttributes
+
+    with pytest.raises(RuntimeError, match="cannot be instantiated directly"):
+        _MemPoolAttributes()
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_dmr_handle_and_ownership(mempool_device):
+    """An options-created pool is handle-owning with a live handle; wrapping the device's current pool is non-owning."""
+    owned = DeviceMemoryResource(mempool_device, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+    assert owned.is_handle_owned is True
+    handle = owned.handle
+    assert handle is not None
+    assert int(handle) != 0
+
+    non_owned = DeviceMemoryResource(mempool_device)
+    assert non_owned.is_handle_owned is False
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_dmr_deallocate_frees_pool_pointer(mempool_device):
+    """Closing a Buffer.from_handle(..., mr=mr) view frees the pointer via the Python
+    _MemPool.deallocate path; the pool's in-use bytes drop back."""
+    dev = mempool_device
+    stream = dev.default_stream
+    mr = DeviceMemoryResource(dev, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+    size = 256
+    # Raw pool allocation owned by nobody else, so exactly one owner frees it (no
+    # double free); a Buffer.from_handle view then routes teardown through the
+    # Python deallocate path that mr.allocate()'s C++-direct free would skip.
+    ptr = handle_return(driver.cuMemAllocFromPoolAsync(size, mr.handle, stream.handle))
+    stream.sync()
+    used_after_alloc = mr.attributes.used_mem_current
+    assert used_after_alloc >= size
+    buf = Buffer.from_handle(int(ptr), size, mr=mr)
+    buf.close(stream)
+    stream.sync()
+    assert int(buf.handle) == 0
+    # In-use bytes fell back, so the pointer was actually returned (buf.handle == 0
+    # alone wouldn't prove it: the deleter callback swallows a failed free).
+    assert mr.attributes.used_mem_current < used_after_alloc
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_dmr_close_is_idempotent(mempool_device):
+    """Closing an owned DeviceMemoryResource twice is safe (the second close is a no-op)."""
+    mr = DeviceMemoryResource(mempool_device, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+    assert mr.is_handle_owned is True
+    assert int(mr.handle) != 0
+    mr.close()
+    # First close releases the pool handle itself, not just ownership.
+    assert int(mr.handle) == 0
+    assert mr.is_handle_owned is False
+    mr.close()  # no-op on the now-null handle
+    assert int(mr.handle) == 0
+    assert mr.is_handle_owned is False
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_dmr_ipc_enabled_unsupported_raises(mempool_device):
+    """Requesting an IPC-enabled pool where memory IPC is unsupported raises RuntimeError."""
+    if not IS_WINDOWS:
+        pytest.skip("memory IPC is supported on this platform; unsupported-raise path is Windows-only")
+    with pytest.raises(RuntimeError, match="IPC is not available"):
+        # uncapped-pool-ok: IPC support is checked before the pool is created
+        DeviceMemoryResource(mempool_device, DeviceMemoryResourceOptions(ipc_enabled=True))
diff --git a/cuda_core/tests/test_memory_peer_access.py b/cuda_core/tests/test_memory_peer_access.py
index 3402402d24e..6c392404ac8 100644
--- a/cuda_core/tests/test_memory_peer_access.py
+++ b/cuda_core/tests/test_memory_peer_access.py
@@ -4,6 +4,7 @@
 import pytest
 from helpers.buffers import PatternGen, compare_buffer_to_constant, make_scratch_buffer
 from helpers.collection_interface_testers import assert_single_member_mutable_set_interface
+from helpers.constants import POOL_SIZE
 
 from cuda.core import Device, DeviceMemoryResource, DeviceMemoryResourceOptions
 from cuda.core._memory import _peer_access_utils
@@ -11,6 +12,8 @@
 from cuda.core._utils.cuda_utils import CUDAError
 
 NBYTES = 1024
+# Every owned pool below holds at most NBYTES, so they are all capped at the
+# suite-wide POOL_SIZE; see helpers/constants.py for why that matters.
 
 pytestmark = pytest.mark.thread_unsafe(reason="peer access tests mutate process-global CUDA memory-pool access state")
 
@@ -21,9 +24,11 @@ def test_peer_access_basic(mempool_device_x2):
     zero_on_dev0 = make_scratch_buffer(dev0, 0, NBYTES)
     one_on_dev0 = make_scratch_buffer(dev0, 1, NBYTES)
     stream_on_dev0 = dev0.create_stream()
+    allocation_stream = dev1.create_stream()
     # Use owned pool to ensure clean initial state (no stale peer access).
-    dmr_on_dev1 = DeviceMemoryResource(dev1, DeviceMemoryResourceOptions())
-    buf_on_dev1 = dmr_on_dev1.allocate(NBYTES, stream=dev1.default_stream)
+    dmr_on_dev1 = DeviceMemoryResource(dev1, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
+    buf_on_dev1 = dmr_on_dev1.allocate(NBYTES, stream=allocation_stream)
+    allocation_stream.sync()
 
     # No access at first.
     assert 0 not in dmr_on_dev1.peer_accessible_by
@@ -70,11 +75,11 @@ def test_peer_access_transitions(mempool_device_x3):
 
     # Allocate per-device resources.
     streams = [dev.create_stream() for dev in devs]
-    pgens = [PatternGen(devs[i], NBYTES, streams[i]) for i in range(3)]
+    pgens = [PatternGen(devs[i], NBYTES, stream=streams[i]) for i in range(3)]
     # Use owned pools (with options) to ensure clean initial state.
     # Default pools are shared and may have stale peer access from prior tests.
-    dmrs = [DeviceMemoryResource(dev, DeviceMemoryResourceOptions()) for dev in devs]
-    bufs = [dmr.allocate(NBYTES, stream=dev.default_stream) for dmr, dev in zip(dmrs, devs)]
+    dmrs = [DeviceMemoryResource(dev, DeviceMemoryResourceOptions(max_size=POOL_SIZE)) for dev in devs]
+    bufs = [dmr.allocate(NBYTES, stream=stream) for dmr, stream in zip(dmrs, streams)]
 
     def verify_state(state, pattern_seed):
         """
@@ -163,7 +168,7 @@ def isolated_dmr_x2(mempool_device_x2):
     proxy tests are not polluted by other tests sharing a default pool.
     """
     dev0, dev1 = mempool_device_x2
-    dmr = DeviceMemoryResource(dev0, DeviceMemoryResourceOptions())
+    dmr = DeviceMemoryResource(dev0, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
     dmr.peer_accessible_by = []
     return dmr, dev0, dev1
 
@@ -273,7 +278,7 @@ def test_peer_accessible_by_no_cache_across_proxies(mempool_device_x2):
 def test_peer_accessible_by_iteration_order_is_sorted(mempool_device_x2):
     """``__iter__`` yields peers in ascending device-ordinal order."""
     dev0, dev1 = mempool_device_x2
-    dmr = DeviceMemoryResource(dev0, DeviceMemoryResourceOptions())
+    dmr = DeviceMemoryResource(dev0, DeviceMemoryResourceOptions(max_size=POOL_SIZE))
     dmr.peer_accessible_by = [dev1]
     devices = list(dmr.peer_accessible_by)
     ids = [d.device_id for d in devices]
diff --git a/cuda_core/tests/test_module.py b/cuda_core/tests/test_module.py
index 25cf0e24de4..3e85101bd85 100644
--- a/cuda_core/tests/test_module.py
+++ b/cuda_core/tests/test_module.py
@@ -39,14 +39,25 @@
 
 
 def _is_nvfatbin_available():
-    """Check if nvfatbin bindings are available."""
+    """Check if nvfatbin bindings are available.
+
+    Catches only the exceptions that mean "not installed / not loadable"
+    (ImportError, DynamicLibNotFoundError, FunctionNotFoundError). A
+    genuine nvfatbin API-status failure (nvFatbinError) propagates so a
+    real bug is not hidden as "unavailable".
+    """
+    from cuda.bindings._internal.utils import FunctionNotFoundError
+    from cuda.pathfinder import DynamicLibNotFoundError
+
     try:
         from cuda.bindings import nvfatbin
-
+    except ImportError:
+        return False
+    try:
         nvfatbin.version()
-        return True
-    except Exception:
+    except (DynamicLibNotFoundError, FunctionNotFoundError):
         return False
+    return True
 
 
 nvfatbin_available = pytest.mark.skipif(not _is_nvfatbin_available(), reason="nvfatbin bindings not available")
@@ -501,7 +512,7 @@ def test_object_code_load_rdc_with_linker(kind, from_fn, init_cuda):
     host_buf = cuda.core.LegacyPinnedMemoryResource().allocate(4)
     result = np.from_dlpack(host_buf).view(np.float32)
     result[:] = 0.0
-    dev_buf = init_cuda.memory_resource.allocate(4, stream=init_cuda.default_stream)
+    dev_buf = init_cuda.memory_resource.allocate(4, stream=stream)
 
     cuda.core.launch(
         stream,
@@ -880,7 +891,7 @@ def get_kernel_only():
     result = np.from_dlpack(host_buf).view(np.int32)
     result[:] = 0
 
-    dev_buf = device.memory_resource.allocate(4, stream=device.default_stream)
+    dev_buf = device.memory_resource.allocate(4, stream=stream)
 
     # Launch kernel
     config = cuda.core.LaunchConfig(grid=1, block=1)
diff --git a/cuda_core/tests/test_multiprocessing_warning.py b/cuda_core/tests/test_multiprocessing_warning.py
index 0f96e0abfbc..2eb4aa55de9 100644
--- a/cuda_core/tests/test_multiprocessing_warning.py
+++ b/cuda_core/tests/test_multiprocessing_warning.py
@@ -12,18 +12,24 @@
 import warnings
 from unittest.mock import patch
 
+import pytest
+from helpers.constants import POOL_SIZE
+
 from cuda.core import DeviceMemoryResource, DeviceMemoryResourceOptions, EventOptions
 from cuda.core._event import _reduce_event
 from cuda.core._memory._device_memory_resource import _deep_reduce_device_memory_resource
 from cuda.core._memory._ipc import _reduce_allocation_handle
 from cuda.core._utils.cuda_utils import check_multiprocessing_start_method, reset_fork_warning
 
+# We could move these to a (session) fixtures
+pytestmark = pytest.mark.thread_unsafe(reason="all tests use unittest.mock.patch")
+
 
 def test_warn_on_fork_method_device_memory_resource(ipc_device):
     """Test that warning is emitted when DeviceMemoryResource is pickled with fork method."""
     device = ipc_device
     device.set_current()
-    options = DeviceMemoryResourceOptions(max_size=2097152, ipc_enabled=True)
+    options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
     mr = DeviceMemoryResource(device, options=options)
 
     with patch("multiprocessing.get_start_method", return_value="fork"), warnings.catch_warnings(record=True) as w:
@@ -50,7 +56,7 @@ def test_warn_on_fork_method_allocation_handle(ipc_device):
     """Test that warning is emitted when IPCAllocationHandle is pickled with fork method."""
     device = ipc_device
     device.set_current()
-    options = DeviceMemoryResourceOptions(max_size=2097152, ipc_enabled=True)
+    options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
     mr = DeviceMemoryResource(device, options=options)
     alloc_handle = mr.allocation_handle
 
@@ -102,7 +108,7 @@ def test_no_warning_with_spawn_method(ipc_device):
     """Test that no warning is emitted when start method is 'spawn'."""
     device = ipc_device
     device.set_current()
-    options = DeviceMemoryResourceOptions(max_size=2097152, ipc_enabled=True)
+    options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
     mr = DeviceMemoryResource(device, options=options)
 
     with patch("multiprocessing.get_start_method", return_value="spawn"), warnings.catch_warnings(record=True) as w:
@@ -125,7 +131,7 @@ def test_warning_emitted_only_once(ipc_device):
     """Test that warning is only emitted once even when multiple objects are pickled."""
     device = ipc_device
     device.set_current()
-    options = DeviceMemoryResourceOptions(max_size=2097152, ipc_enabled=True)
+    options = DeviceMemoryResourceOptions(max_size=POOL_SIZE, ipc_enabled=True)
     mr1 = DeviceMemoryResource(device, options=options)
     mr2 = DeviceMemoryResource(device, options=options)
 
diff --git a/cuda_core/tests/test_object_protocols.py b/cuda_core/tests/test_object_protocols.py
index cc075d43ed4..ebfbfd40add 100644
--- a/cuda_core/tests/test_object_protocols.py
+++ b/cuda_core/tests/test_object_protocols.py
@@ -13,15 +13,17 @@
 import weakref
 
 import pytest
+from helpers.constants import POOL_SIZE
 from helpers.graph_kernels import compile_common_kernels
+from helpers.memory import xfail_on_graph_mempool_oom
 from helpers.misc import try_create_condition
 
-from conftest import xfail_on_graph_mempool_oom
 from cuda.core import (
     Buffer,
     Device,
     DeviceMemoryResource,
     DeviceMemoryResourceOptions,
+    EventOptions,
     Kernel,
     LaunchConfig,
     Program,
@@ -223,8 +225,6 @@ def sample_kernel_alt(sample_object_code_alt):
 # Fixtures - IPC samples (for pickle tests)
 # =============================================================================
 
-POOL_SIZE = 2097152
-
 
 @pytest.fixture
 def sample_ipc_buffer_descriptor(ipc_device):
@@ -243,7 +243,7 @@ def sample_ipc_buffer_descriptor(ipc_device):
 def sample_ipc_event_descriptor(ipc_device):
     """An IPCEventDescriptor."""
     stream = ipc_device.create_stream()
-    e = stream.record(options={"ipc_enabled": True})
+    e = stream.record(options=EventOptions(ipc_enabled=True))
     return e.ipc_descriptor
 
 
@@ -526,6 +526,25 @@ def sample_switch_node_alt(sample_graphdef):
     return sample_graphdef.switch(condition, 3)
 
 
+# Resolve fixture names during pytest setup, before pytest-run-parallel starts
+# worker threads. The workers then share the resolved, read-only test object.
+
+
+@pytest.fixture
+def sample_object(request):
+    return request.getfixturevalue(request.param)
+
+
+@pytest.fixture
+def sample_object_a(request):
+    return request.getfixturevalue(request.param)
+
+
+@pytest.fixture
+def sample_object_b(request):
+    return request.getfixturevalue(request.param)
+
+
 # =============================================================================
 # Type groupings
 # =============================================================================
@@ -684,7 +703,8 @@ def sample_switch_node_alt(sample_graphdef):
     (
         "sample_launch_config",
         r"LaunchConfig\(grid=\(\d+, \d+, \d+\), cluster=.+, block=\(\d+, \d+, \d+\), "
-        r"shmem_size=\d+, is_cooperative=(?:True|False)\)",
+        r"shmem_size=\d+, is_cooperative=(?:True|False), "
+        r"programmatic_stream_serialization=(?:True|False)\)",
     ),
     ("sample_kernel", r"<Kernel handle=0x[0-9a-f]+>"),
     # ObjectCode variations (by code_type)
@@ -716,17 +736,63 @@ def sample_switch_node_alt(sample_graphdef):
 ]
 
 
+# Types whose named state reflects whether close() has released their resource.
+CLOSEABLE_TYPES = [
+    "sample_stream",
+    "sample_event",
+    "sample_buffer",
+    "sample_program_nvrtc",
+]
+
+
+# =============================================================================
+# Resource state tests
+# =============================================================================
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+@pytest.mark.thread_unsafe(reason="closes a fixture object shared between threads")
+@pytest.mark.parametrize("sample_object", CLOSEABLE_TYPES, indirect=True)
+def test_closeable_object_state_and_safe_inspection(sample_object):
+    """Closing is idempotent, updates named state, and leaves inspection safe."""
+    assert not sample_object.is_closed
+
+    sample_object.close()
+    assert sample_object.is_closed
+    assert bool(sample_object) is True  # Preserve backward-compatible truthiness after close.
+    repr(sample_object)
+    if hasattr(sample_object, "handle"):
+        _ = sample_object.handle
+
+    sample_object.close()
+    assert sample_object.is_closed
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_graph_object_validity_uses_named_state(init_cuda):
+    """Graph objects remain truthy when their named validity becomes false."""
+    graph_def = GraphDefinition()
+    assert graph_def.is_valid
+    assert graph_def._entry.is_valid
+
+    node = graph_def.empty()
+    assert node.is_valid
+    node.destroy()
+    assert not node.is_valid
+    assert bool(node) is True  # Preserve backward-compatible truthiness after destruction.
+    assert repr(node)
+
+
 # =============================================================================
 # Weak reference tests
 # =============================================================================
 
 
-@pytest.mark.parametrize("fixture_name", WEAKREF_TYPES)
-def test_weakref_supported(fixture_name, request):
+@pytest.mark.parametrize("sample_object", WEAKREF_TYPES, indirect=True)
+def test_weakref_supported(sample_object):
     """Object supports weak references."""
-    obj = request.getfixturevalue(fixture_name)
-    ref = weakref.ref(obj)
-    assert ref() is obj
+    ref = weakref.ref(sample_object)
+    assert ref() is sample_object
 
 
 # =============================================================================
@@ -734,27 +800,22 @@ def test_weakref_supported(fixture_name, request):
 # =============================================================================
 
 
-@pytest.mark.parametrize("fixture_name", HASH_TYPES)
-def test_hash_consistency(fixture_name, request):
+@pytest.mark.parametrize("sample_object", HASH_TYPES, indirect=True)
+def test_hash_consistency(sample_object):
     """Hash is consistent across multiple calls."""
-    obj = request.getfixturevalue(fixture_name)
-    assert hash(obj) == hash(obj)
+    assert hash(sample_object) == hash(sample_object)
 
 
-@pytest.mark.parametrize("a_name,b_name", SAME_TYPE_PAIRS)
-def test_hash_distinct_same_type(a_name, b_name, request):
+@pytest.mark.parametrize("sample_object_a,sample_object_b", SAME_TYPE_PAIRS, indirect=True)
+def test_hash_distinct_same_type(sample_object_a, sample_object_b):
     """Distinct objects of the same type have different hashes."""
-    obj_a = request.getfixturevalue(a_name)
-    obj_b = request.getfixturevalue(b_name)
-    assert hash(obj_a) != hash(obj_b)  # extremely unlikely
+    assert hash(sample_object_a) != hash(sample_object_b)  # extremely unlikely
 
 
-@pytest.mark.parametrize("a_name,b_name", itertools.combinations(HASH_TYPES, 2))
-def test_hash_distinct_cross_type(a_name, b_name, request):
+@pytest.mark.parametrize("sample_object_a,sample_object_b", itertools.combinations(HASH_TYPES, 2), indirect=True)
+def test_hash_distinct_cross_type(sample_object_a, sample_object_b):
     """Distinct objects of different types have different hashes."""
-    obj_a = request.getfixturevalue(a_name)
-    obj_b = request.getfixturevalue(b_name)
-    assert hash(obj_a) != hash(obj_b)  # extremely unlikely
+    assert hash(sample_object_a) != hash(sample_object_b)  # extremely unlikely
 
 
 # =============================================================================
@@ -762,41 +823,35 @@ def test_hash_distinct_cross_type(a_name, b_name, request):
 # =============================================================================
 
 
-@pytest.mark.parametrize("fixture_name", EQ_TYPES)
-def test_equality_basic(fixture_name, request):
+@pytest.mark.parametrize("sample_object", EQ_TYPES, indirect=True)
+def test_equality_basic(sample_object):
     """Object equality: reflexive, not equal to None or other types."""
-    obj = request.getfixturevalue(fixture_name)
-    assert obj == obj
-    assert obj is not None
-    assert obj != "string"
-    if hasattr(obj, "handle"):
-        assert obj != obj.handle
+    assert sample_object == sample_object
+    assert sample_object is not None
+    assert sample_object != "string"
+    if hasattr(sample_object, "handle"):
+        assert sample_object != sample_object.handle
 
 
-@pytest.mark.parametrize("a_name,b_name", itertools.combinations(EQ_TYPES, 2))
-def test_no_cross_type_equality(a_name, b_name, request):
+@pytest.mark.parametrize("sample_object_a,sample_object_b", itertools.combinations(EQ_TYPES, 2), indirect=True)
+def test_no_cross_type_equality(sample_object_a, sample_object_b):
     """No two distinct objects of different types should compare equal."""
-    obj_a = request.getfixturevalue(a_name)
-    obj_b = request.getfixturevalue(b_name)
-    assert obj_a != obj_b
+    assert sample_object_a != sample_object_b
 
 
-@pytest.mark.parametrize("a_name,b_name", SAME_TYPE_PAIRS)
-def test_same_type_inequality(a_name, b_name, request):
+@pytest.mark.parametrize("sample_object_a,sample_object_b", SAME_TYPE_PAIRS, indirect=True)
+def test_same_type_inequality(sample_object_a, sample_object_b):
     """Two distinct objects of the same type should not compare equal."""
-    obj_a = request.getfixturevalue(a_name)
-    obj_b = request.getfixturevalue(b_name)
-    assert obj_a is not obj_b
-    assert obj_a != obj_b
+    assert sample_object_a is not sample_object_b
+    assert sample_object_a != sample_object_b
 
 
-@pytest.mark.parametrize("fixture_name,copy_fn", FROM_HANDLE_COPIES)
-def test_equality_same_handle(fixture_name, copy_fn, request):
+@pytest.mark.parametrize("sample_object,copy_fn", FROM_HANDLE_COPIES, indirect=["sample_object"])
+def test_equality_same_handle(sample_object, copy_fn):
     """Two wrappers around the same handle should compare equal."""
-    obj = request.getfixturevalue(fixture_name)
-    obj2 = copy_fn(obj)
-    assert obj == obj2
-    assert hash(obj) == hash(obj2)
+    obj2 = copy_fn(sample_object)
+    assert sample_object == obj2
+    assert hash(sample_object) == hash(obj2)
 
 
 # =============================================================================
@@ -804,48 +859,43 @@ def test_equality_same_handle(fixture_name, copy_fn, request):
 # =============================================================================
 
 
-@pytest.mark.parametrize("fixture_name", DICT_KEY_TYPES)
-def test_usable_as_dict_key(fixture_name, request):
+@pytest.mark.parametrize("sample_object", DICT_KEY_TYPES, indirect=True)
+def test_usable_as_dict_key(sample_object):
     """Object can be used as a dictionary key."""
-    obj = request.getfixturevalue(fixture_name)
-    d = {obj: "value"}
-    assert d[obj] == "value"
-    assert obj in d
+    d = {sample_object: "value"}
+    assert d[sample_object] == "value"
+    assert sample_object in d
 
 
-@pytest.mark.parametrize("fixture_name", DICT_KEY_TYPES)
-def test_usable_in_set(fixture_name, request):
+@pytest.mark.parametrize("sample_object", DICT_KEY_TYPES, indirect=True)
+def test_usable_in_set(sample_object):
     """Object can be added to a set."""
-    obj = request.getfixturevalue(fixture_name)
-    s = {obj}
-    assert obj in s
+    s = {sample_object}
+    assert sample_object in s
 
 
-@pytest.mark.parametrize("fixture_name", WEAKREF_TYPES)
-def test_usable_in_weak_value_dict(fixture_name, request):
+@pytest.mark.parametrize("sample_object", WEAKREF_TYPES, indirect=True)
+def test_usable_in_weak_value_dict(sample_object):
     """Object can be used as a WeakValueDictionary value."""
-    obj = request.getfixturevalue(fixture_name)
     wvd = weakref.WeakValueDictionary()
-    wvd["key"] = obj
-    assert wvd["key"] is obj
+    wvd["key"] = sample_object
+    assert wvd["key"] is sample_object
 
 
-@pytest.mark.parametrize("fixture_name", WEAK_KEY_TYPES)
-def test_usable_in_weak_key_dict(fixture_name, request):
+@pytest.mark.parametrize("sample_object", WEAK_KEY_TYPES, indirect=True)
+def test_usable_in_weak_key_dict(sample_object):
     """Object can be used as a WeakKeyDictionary key."""
-    obj = request.getfixturevalue(fixture_name)
     wkd = weakref.WeakKeyDictionary()
-    wkd[obj] = "value"
-    assert wkd[obj] == "value"
+    wkd[sample_object] = "value"
+    assert wkd[sample_object] == "value"
 
 
-@pytest.mark.parametrize("fixture_name", WEAK_KEY_TYPES)
-def test_usable_in_weak_set(fixture_name, request):
+@pytest.mark.parametrize("sample_object", WEAK_KEY_TYPES, indirect=True)
+def test_usable_in_weak_set(sample_object):
     """Object can be added to a WeakSet."""
-    obj = request.getfixturevalue(fixture_name)
     ws = weakref.WeakSet()
-    ws.add(obj)
-    assert obj in ws
+    ws.add(sample_object)
+    assert sample_object in ws
 
 
 # =============================================================================
@@ -853,12 +903,10 @@ def test_usable_in_weak_set(fixture_name, request):
 # =============================================================================
 
 
-@pytest.mark.parametrize("fixture_name,pattern", REPR_PATTERNS)
-def test_repr_format(fixture_name, pattern, request):
+@pytest.mark.parametrize("sample_object,pattern", REPR_PATTERNS, indirect=["sample_object"])
+def test_repr_format(sample_object, pattern):
     """repr() returns a properly formatted string."""
-    obj = request.getfixturevalue(fixture_name)
-    result = repr(obj)
-    assert re.fullmatch(pattern, result)
+    assert re.fullmatch(pattern, repr(sample_object))
 
 
 # =============================================================================
@@ -867,10 +915,9 @@ def test_repr_format(fixture_name, pattern, request):
 
 
 @pytest.mark.parametrize("pickle_module", PICKLE_MODULES)
-@pytest.mark.parametrize("fixture_name", PICKLE_TYPES)
-def test_pickle_roundtrip(fixture_name, pickle_module, request):
+@pytest.mark.parametrize("sample_object", PICKLE_TYPES, indirect=True)
+def test_pickle_roundtrip(sample_object, pickle_module):
     """Object survives a pickle/cloudpickle roundtrip."""
     mod = pytest.importorskip(pickle_module)
-    obj = request.getfixturevalue(fixture_name)
-    result = mod.loads(mod.dumps(obj))
-    assert type(result) is type(obj)
+    result = mod.loads(mod.dumps(sample_object))
+    assert type(result) is type(sample_object)
diff --git a/cuda_core/tests/test_optional_dependency_imports.py b/cuda_core/tests/test_optional_dependency_imports.py
index 02edcc9839a..b08b7d344d9 100644
--- a/cuda_core/tests/test_optional_dependency_imports.py
+++ b/cuda_core/tests/test_optional_dependency_imports.py
@@ -5,6 +5,11 @@
 import pytest
 
 from cuda.core import _linker, _program
+from cuda.pathfinder import DynamicLibNotFoundError
+
+# The autouse fixture below resets module-level import state for every test in this
+# file, so the whole module is thread-unsafe -- not just the tests that monkeypatch.
+pytestmark = pytest.mark.thread_unsafe(reason="resets cuda.core._program / _linker optional-import globals")
 
 
 @pytest.fixture(autouse=True)
@@ -30,6 +35,25 @@ def restore_optional_import_state():
     _linker._use_nvjitlink_backend = saved_use_nvjitlink
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_get_nvvm_module_rejects_old_bindings(monkeypatch):
+    """NVVM import requires cuda-bindings >= 12.9.0 and caches a failed attempt."""
+    calls = 0
+
+    def old_binding_version():
+        nonlocal calls
+        calls += 1
+        return (12, 8, 0)
+
+    monkeypatch.setattr(_program, "binding_version", old_binding_version)
+
+    with pytest.raises(RuntimeError, match="cuda-bindings >= 12.9.0"):
+        _program._get_nvvm_module()
+    with pytest.raises(RuntimeError, match="previous import attempt failed"):
+        _program._get_nvvm_module()
+    assert calls == 1
+
+
 def test_get_nvvm_module_reraises_nested_module_not_found(monkeypatch):
     monkeypatch.setattr(_program, "binding_version", lambda: (12, 9, 0))
 
@@ -78,7 +102,7 @@ def fake__optional_cuda_import(modname, probe_function=None):
 def test_decide_nvjitlink_or_driver_reraises_nested_module_not_found(monkeypatch):
     def fake__optional_cuda_import(modname, probe_function=None):
         assert modname == "cuda.bindings.nvjitlink"
-        assert probe_function is not None
+        assert probe_function is None
         err = ModuleNotFoundError("No module named 'not_a_real_dependency'")
         err.name = "not_a_real_dependency"
         raise err
@@ -93,7 +117,7 @@ def fake__optional_cuda_import(modname, probe_function=None):
 def test_decide_nvjitlink_or_driver_falls_back_when_module_missing(monkeypatch):
     def fake__optional_cuda_import(modname, probe_function=None):
         assert modname == "cuda.bindings.nvjitlink"
-        assert probe_function is not None
+        assert probe_function is None
         return None
 
     monkeypatch.setattr(_linker, "_optional_cuda_import", fake__optional_cuda_import)
@@ -103,3 +127,85 @@ def fake__optional_cuda_import(modname, probe_function=None):
 
     assert use_driver_backend is True
     assert _linker._use_nvjitlink_backend is False
+
+
+@pytest.mark.agent_authored(model="grok-4.5")
+def test_decide_nvjitlink_or_driver_falls_back_when_dylib_missing(monkeypatch):
+    """Missing nvJitLink dylib must fall back via DynamicLibNotFoundError."""
+
+    def raise_missing(_nvjitlink):
+        raise DynamicLibNotFoundError("libnvJitLink missing")
+
+    def fake__optional_cuda_import(modname, probe_function=None):
+        assert modname == "cuda.bindings.nvjitlink"
+        assert probe_function is None
+        return object()
+
+    monkeypatch.setattr(_linker, "_optional_cuda_import", fake__optional_cuda_import)
+    monkeypatch.setattr(_linker, "_nvjitlink_has_version_symbol", raise_missing)
+
+    with pytest.warns(RuntimeWarning, match="cuda.bindings.nvjitlink is not available"):
+        use_driver_backend = _linker._decide_nvjitlink_or_driver()
+
+    assert use_driver_backend is True
+    assert _linker._use_nvjitlink_backend is False
+
+
+@pytest.mark.agent_authored(model="grok-4.5")
+def test_decide_nvjitlink_or_driver_falls_back_when_nvjitlink_too_old(monkeypatch):
+    def fake__optional_cuda_import(modname, probe_function=None):
+        assert modname == "cuda.bindings.nvjitlink"
+        assert probe_function is None
+        return object()
+
+    monkeypatch.setattr(_linker, "_optional_cuda_import", fake__optional_cuda_import)
+    monkeypatch.setattr(_linker, "_nvjitlink_has_version_symbol", lambda _nvjitlink: False)
+
+    with pytest.warns(RuntimeWarning, match="too old \\(<12.3\\)"):
+        use_driver_backend = _linker._decide_nvjitlink_or_driver()
+
+    assert use_driver_backend is True
+    assert _linker._use_nvjitlink_backend is False
+
+
+@pytest.mark.agent_authored(model="grok-4.5")
+def test_decide_nvjitlink_or_driver_selects_nvjitlink_when_version_symbol_present(monkeypatch):
+    def fake__optional_cuda_import(modname, probe_function=None):
+        assert modname == "cuda.bindings.nvjitlink"
+        assert probe_function is None
+        return object()
+
+    monkeypatch.setattr(_linker, "_optional_cuda_import", fake__optional_cuda_import)
+    monkeypatch.setattr(_linker, "_nvjitlink_has_version_symbol", lambda _nvjitlink: True)
+
+    use_driver_backend = _linker._decide_nvjitlink_or_driver()
+
+    assert use_driver_backend is False
+    assert _linker._use_nvjitlink_backend is True
+
+
+@pytest.mark.agent_authored(model="grok-4.5")
+def test_decide_nvjitlink_or_driver_does_not_call_version(monkeypatch):
+    """Regression guard for #2408: must not call module.version()."""
+    called = {"version": False, "inspect": False}
+
+    class FakeModule:
+        def version(self):
+            called["version"] = True
+            raise AssertionError("module.version() must not be used for nvJitLink probing")
+
+    def fake_has_version(_nvjitlink):
+        called["inspect"] = True
+        return True
+
+    def fake__optional_cuda_import(modname, probe_function=None):
+        assert modname == "cuda.bindings.nvjitlink"
+        assert probe_function is None
+        return FakeModule()
+
+    monkeypatch.setattr(_linker, "_optional_cuda_import", fake__optional_cuda_import)
+    monkeypatch.setattr(_linker, "_nvjitlink_has_version_symbol", fake_has_version)
+
+    assert _linker._decide_nvjitlink_or_driver() is False
+    assert called["inspect"] is True
+    assert called["version"] is False
diff --git a/cuda_core/tests/test_program.py b/cuda_core/tests/test_program.py
index a9dc4966346..81dd41d06a1 100644
--- a/cuda_core/tests/test_program.py
+++ b/cuda_core/tests/test_program.py
@@ -2,18 +2,22 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-import contextlib
 import re
+import shutil
+import subprocess
+import sys
 import warnings
 
 import pytest
 
+from cuda.bindings._internal.utils import FunctionNotFoundError
 from cuda.core import _linker
 from cuda.core._device import Device
 from cuda.core._module import Kernel, ObjectCode
 from cuda.core._program import Program, ProgramOptions
-from cuda.core._utils.cuda_utils import CUDAError, handle_return
+from cuda.core._utils.cuda_utils import CUDAError, handle_return, nvrtc
 from cuda.core.typing import CompilerBackendType, PCHStatusType
+from cuda.pathfinder import DynamicLibNotFoundError
 
 pytest_plugins = ("cuda_python_test_helpers.nvvm_bitcode",)
 
@@ -35,9 +39,6 @@ def _is_nvvm_available():
     not _is_nvvm_available(), reason="NVVM not available (libNVVM not found or cuda-bindings < 12.9.0)"
 )
 
-with contextlib.suppress(Exception):
-    from cuda.core._utils.cuda_utils import nvrtc
-
 
 def _get_nvrtc_version_for_tests():
     """
@@ -49,10 +50,11 @@ def _get_nvrtc_version_for_tests():
     """
     try:
         nvrtc_major, nvrtc_minor = handle_return(nvrtc.nvrtcVersion())
-        version = nvrtc_major * 1000 + nvrtc_minor * 100
-        return version
-    except Exception:
+        return nvrtc_major * 1000 + nvrtc_minor * 100
+    except (DynamicLibNotFoundError, FunctionNotFoundError):
+        # libnvrtc not loadable, or nvrtcVersion symbol missing.
         return None
+    # CUDAError from a successfully loaded library propagates (real bug).
 
 
 def _has_nvrtc_pch_apis_for_tests():
@@ -70,6 +72,11 @@ def _has_nvrtc_pch_apis_for_tests():
     reason="PCH runtime APIs require NVRTC >= 12.8 bindings",
 )
 
+bundled_headers_available = pytest.mark.skipif(
+    (_get_nvrtc_version_for_tests() or 0) < 13300,
+    reason="use_bundled_headers requires NVRTC >= 13.3",
+)
+
 
 def _has_check_nvvm_compiler_options():
     try:
@@ -93,12 +100,16 @@ def _check_nvvm_arch(arch: str) -> bool:
 
 
 def _check_nvvm_supports_numba_debug() -> bool:
-    """Check if the installed libNVVM recognizes --numba-debug (CTK 13.2+)."""
+    """Check if the installed libNVVM recognizes -numba-debug.
+
+    libNVVM only accepts single-dashed options, so the double-dashed spelling
+    used by NVRTC is rejected by every libNVVM version.
+    """
     if not _has_check_nvvm_compiler_options():
         return False
     from cuda.bindings.utils import check_nvvm_compiler_options
 
-    return check_nvvm_compiler_options(["--numba-debug"])
+    return check_nvvm_compiler_options(["-numba-debug"])
 
 
 @pytest.fixture(scope="session")
@@ -296,6 +307,48 @@ def test_cpp_program_pch_auto_creates(init_cuda, tmp_path):
     program.close()
 
 
+@bundled_headers_available
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_use_bundled_headers_installs_and_compiles(init_cuda, tmp_path, monkeypatch):
+    """``use_bundled_headers`` should install NVRTC's bundled CUDA/CCCL headers into the
+    (monkeypatched) cache directory and make them available on the include path, without
+    a CUDA Toolkit or any user-supplied ``include_path``."""
+    import cuda.core._program as _program_module
+
+    cache_root = tmp_path / "cache-root"
+    monkeypatch.setattr(_program_module, "_default_cache_dir", lambda: cache_root)
+
+    code = """
+#include <cuda/std/type_traits>
+extern "C" __global__ void my_kernel(int *out) {
+    *out = cuda::std::is_integral<int>::value;
+}
+"""
+    headers_dir = cache_root / "nvrtc-bundled-headers"
+    assert not headers_dir.exists()
+
+    # Sanity check: without use_bundled_headers, the CCCL header isn't found (proves the
+    # option -- not some ambient CUDA Toolkit install -- is what makes the compile below work).
+    program = Program(code, "c++")
+    try:
+        with pytest.raises(CUDAError, match="could not open source file"):
+            program.compile("ptx")
+    finally:
+        program.close()
+
+    program = Program(code, "c++", ProgramOptions(use_bundled_headers=True))
+    try:
+        object_code = program.compile("ptx")
+    finally:
+        program.close()
+    assert isinstance(object_code, ObjectCode)
+
+    assert headers_dir.is_dir()
+    assert (headers_dir / ".nvrtc_headers_version").is_file()
+    assert (headers_dir / "cccl").is_dir()
+    assert (headers_dir / "cccl" / "cuda" / "std" / "type_traits").is_file()
+
+
 def test_cpp_program_pch_status_none_without_pch(init_cuda):
     code = 'extern "C" __global__ void my_kernel() {}'
     program = Program(code, "c++")
@@ -312,8 +365,10 @@ def test_cpp_program_pch_status_none_without_pch(init_cuda):
     ProgramOptions(prec_div=True),
     ProgramOptions(prec_sqrt=True),
     ProgramOptions(fma=True),
-    # Plumb-through; no-op at link time. See #1287.
-    ProgramOptions(debug=True, numba_debug=True),
+    # ``numba_debug`` is deliberately absent: it was listed here as a link-time
+    # no-op (#1287), but no linker backend accepts it, so it was dropped
+    # silently (#2640). The PTX path now warns; see
+    # test_ptx_program_numba_debug_warns_and_is_ignored.
 ]
 if not is_culink_backend:
     options += [
@@ -351,10 +406,20 @@ def test_program_init_invalid_code_format():
         Program(code, "c++")
 
 
+# arch is passed explicitly so the current device is not queried.
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("name", [None, "my_program"])
+def test_program_options_name_accepts_none(name):
+    options = ProgramOptions(name=name, arch="sm_90")
+    expected = "default_program" if name is None else name
+    assert options.name == expected
+    assert options._name == expected.encode()
+
+
 # This is tested against the current device's arch
 def test_program_compile_valid_target_type(init_cuda):
     code = 'extern "C" __global__ void my_kernel() {}'
-    program = Program(code, "c++", options={"name": "42"})
+    program = Program(code, "c++", options=ProgramOptions(name="42"))
 
     with warnings.catch_warnings(record=True) as w:
         warnings.simplefilter("always")
@@ -366,7 +431,7 @@ def test_program_compile_valid_target_type(init_cuda):
         ptx_kernel = ptx_object_code.get_kernel("my_kernel")
         assert isinstance(ptx_kernel, Kernel)
 
-    program = Program(ptx_object_code.code.decode(), "ptx", options={"name": "24"})
+    program = Program(ptx_object_code.code.decode(), "ptx", options=ProgramOptions(name="24"))
     cubin_object_code = program.compile("cubin")
     assert isinstance(cubin_object_code, ObjectCode)
     assert cubin_object_code.name == "24"
@@ -414,6 +479,17 @@ def test_program_close():
     program.close()
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_program_rejects_compile():
+    program = Program('extern "C" __global__ void my_kernel() {}', "c++")
+    assert not program.is_closed
+    program.close()
+
+    assert program.is_closed
+    with pytest.raises(RuntimeError, match="Program has been closed"):
+        program.compile("ptx")
+
+
 @nvvm_available
 def test_nvvm_deferred_import():
     """Test that our deferred NVVM import works correctly"""
@@ -742,28 +818,55 @@ def test_program_options_as_bytes_invalid_backend():
         options.as_bytes("invalid")
 
 
-@nvvm_available
-def test_program_options_as_bytes_nvvm_unsupported_option():
-    """Test that unsupported options raise CUDAError for NVVM backend"""
-    options = ProgramOptions(arch="sm_80", lineinfo=True)
-    with pytest.raises(CUDAError, match="not supported by NVVM backend"):
-        options.as_bytes("nvvm")
-
-
 @nvvm_available
 def test_nvvm_program_options_as_bytes_numba_debug():
-    """numba_debug must be plumbed through to libNVVM as --numba-debug
-    (see #1287)."""
+    """numba_debug must be plumbed through to libNVVM as -numba-debug
+    (see #1287, #2570). libNVVM rejects the double-dashed spelling."""
     options = ProgramOptions(arch="sm_80", debug=True, numba_debug=True)
     nvvm_bytes = options.as_bytes("nvvm")
-    assert b"--numba-debug" in nvvm_bytes
+    assert b"-numba-debug" in nvvm_bytes
+    assert b"--numba-debug" not in nvvm_bytes
     assert b"-g" in nvvm_bytes
 
 
+@pytest.mark.agent_authored(model="claude-opus-5[1m]")
+def test_nvvm_options_reject_double_dash():
+    """The guard must name a double-dashed option rather than let libNVVM
+    reject it with an opaque error (see #2570)."""
+    from cuda.core._program import _assert_single_dashed_nvvm_options
+
+    _assert_single_dashed_nvvm_options(["-arch=compute_80", "-g", "-numba-debug"])
+
+    with pytest.raises(RuntimeError, match=r"--numba-debug.*double-dashed"):
+        _assert_single_dashed_nvvm_options(["-arch=compute_80", "--numba-debug"])
+
+
+@nvvm_available
+@pytest.mark.agent_authored(model="claude-opus-5[1m]")
+def test_nvvm_program_options_as_bytes_all_single_dashed():
+    """Every option cuda.core emits to libNVVM must be single-dashed, because
+    libNVVM rejects the double-dashed spelling of all of them (see #2570).
+    This covers every NVVM-supported field of ProgramOptions."""
+    options = ProgramOptions(
+        arch="sm_80",
+        debug=True,
+        numba_debug=True,
+        device_code_optimize=True,
+        ftz=True,
+        prec_sqrt=True,
+        prec_div=True,
+        fma=True,
+    )
+    nvvm_bytes = options.as_bytes("nvvm")
+    assert nvvm_bytes, "expected at least one emitted option"
+    offenders = [o for o in nvvm_bytes if o.startswith(b"--")]
+    assert not offenders, f"double-dashed options are rejected by libNVVM: {offenders}"
+
+
 @nvvm_available
 @pytest.mark.skipif(
     not _check_nvvm_supports_numba_debug(),
-    reason="installed libNVVM does not recognize --numba-debug (needs CTK 13.2+)",
+    reason="installed libNVVM does not recognize -numba-debug",
 )
 def test_nvvm_program_numba_debug(init_cuda, nvvm_ir):
     options = ProgramOptions(arch="sm_80", debug=True, numba_debug=True)
@@ -821,6 +924,34 @@ def test_ptx_program_extra_sources_unsupported(ptx_code_object):
         Program(ptx_code_object.code.decode(), "ptx", options)
 
 
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_ptx_program_numba_debug_warns_and_is_ignored(init_cuda, ptx_code_object):
+    """PTX inputs go to the linker, which cannot honor numba_debug (#2640).
+
+    It used to be forwarded into ``LinkerOptions`` and dropped without a word,
+    so the compile appeared to succeed with the option applied. It is still
+    ignored -- no linker can do anything with it -- but no longer silently.
+
+    ``UserWarning``, not ``DeprecationWarning``: ``ProgramOptions.numba_debug``
+    is not deprecated, it is supported on NVVM/NVRTC and merely inapplicable to
+    this backend.
+    """
+    with pytest.warns(UserWarning, match="numba_debug is ignored for code_type='ptx'"):
+        program = Program(ptx_code_object.code.decode(), "ptx", ProgramOptions(numba_debug=True))
+    assert program.compile("cubin") is not None
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("value", [None, False])
+def test_ptx_program_numba_debug_unset_or_false_does_not_warn(init_cuda, ptx_code_object, value):
+    """The gate is truthiness: only an enabled ``numba_debug`` asks for
+    something the PTX path cannot deliver, so ``False`` is not worth a warning."""
+    with warnings.catch_warnings():
+        warnings.simplefilter("error", UserWarning)
+        program = Program(ptx_code_object.code.decode(), "ptx", ProgramOptions(numba_debug=value))
+    assert program.compile("cubin") is not None
+
+
 def test_ptx_program_handle_is_linker_handle(init_cuda, ptx_code_object):
     """Program.handle for the PTX backend delegates to the linker handle."""
     program = Program(ptx_code_object.code.decode(), "ptx")
@@ -910,6 +1041,188 @@ def fake_find(name):
     assert captured == ["device"]
 
 
+@pytest.mark.agent_authored(model="cursor-grok-4.6")
+def test_nvrtc_debug_materializes_source_to_temp_file(init_cuda, tmp_path):
+    """debug/lineinfo writes NVRTC source to a real path; off and explicit name= do not."""
+    import os
+
+    code = 'extern "C" __global__ void matmul() {}'
+
+    # case 1: (debug=False, lineinfo=False)
+    off = Program(code, "c++", ProgramOptions(arch="sm_80"))
+    assert off.compile("ptx").name == "default_program"
+    off.close()
+
+    # case 2: (debug=True or lineinfo=True) and explicit_name is provided
+    explicit_name = str(tmp_path / "user_kernel.cu")
+    named = Program(code, "c++", ProgramOptions(name=explicit_name, debug=True, arch="sm_80"))
+    assert named.compile("ptx").name == explicit_name
+    assert not os.path.isfile(explicit_name)
+    named.close()
+
+    # case 3: (debug=True or lineinfo=True) and explicit_name is not provided
+    default_named = Program(code, "c++", ProgramOptions(debug=True, arch="sm_80"))
+    implicit_name = default_named.compile("ptx").name
+    try:
+        assert os.path.isfile(implicit_name)
+        assert re.fullmatch(r"test_program_matmul_[a-z0-9_]{8}\.cu", os.path.basename(implicit_name))
+        with open(implicit_name, encoding="utf-8") as fh:
+            assert fh.read() == code
+    finally:
+        default_named.close()
+    assert not os.path.isfile(implicit_name)
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.6")
+@pytest.mark.thread_unsafe(reason="monkeypatches tempfile.mkstemp on the Program module")
+def test_nvrtc_debug_falls_back_when_tmp_not_writable(init_cuda, monkeypatch):
+    """debug=True still compiles if the temp dir cannot be written (issue #2422)."""
+    from cuda.core import _program
+
+    def _denied(*_args, **_kwargs):
+        raise OSError(30, "Read-only file system")
+
+    monkeypatch.setattr(_program.tempfile, "mkstemp", _denied)
+
+    code = 'extern "C" __global__ void matmul() {}'
+    prog = Program(code, "c++", ProgramOptions(debug=True, arch="sm_80"))
+    try:
+        assert prog.compile("ptx").name == "default_program"
+    finally:
+        prog.close()
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.6")
+def test_nvrtc_debug_concurrent_compile_uses_unique_temp_files(init_cuda):
+    """Same kernel compiled concurrently gets distinct mkstemp paths (issue #2422)."""
+    import os
+    import threading
+    from concurrent.futures import ThreadPoolExecutor
+
+    code = 'extern "C" __global__ void matmul() {}'
+    n = 2
+    barrier = threading.Barrier(n)
+
+    def _compile_one():
+        Device().set_current()
+        barrier.wait()
+        prog = Program(code, "c++", ProgramOptions(debug=True, arch="sm_80"))
+        name = prog.compile("ptx").name
+        return prog, name
+
+    with ThreadPoolExecutor(max_workers=n) as pool:
+        futures = [pool.submit(_compile_one) for _ in range(n)]
+        results = [fut.result() for fut in futures]
+
+    progs, names = zip(*results)
+    try:
+        assert len(set(names)) == n
+        for name in names:
+            assert os.path.isfile(name)
+            assert re.fullmatch(r"test_program_matmul_[a-z0-9_]{8}\.cu", os.path.basename(name))
+            with open(name, encoding="utf-8") as fh:
+                assert fh.read() == code
+    finally:
+        for prog in progs:
+            prog.close()
+    for name in names:
+        assert not os.path.isfile(name)
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_nvrtc_debug_preserves_quoted_include_resolution(init_cuda, tmp_path, monkeypatch):
+    """A quoted #include keeps resolving once debug redirects the NVRTC name (issue #2422).
+
+    NVRTC looks for #include "..." in the directory of the name it was handed, so
+    pointing that name at a temp .cu moves the search away from where the header
+    lives and turning debug on alone breaks a compile that worked without it.
+    """
+    import os
+
+    (tmp_path / "local.h").write_text("#define BUMP 7\n", encoding="utf-8")
+    monkeypatch.chdir(tmp_path)
+    code = '#include "local.h"\nextern "C" __global__ void matmul(int* out) { *out = BUMP; }\n'
+
+    for debug in (False, True):
+        prog = Program(code, "c++", ProgramOptions(arch="sm_80", debug=debug))
+        try:
+            name = prog.compile("ptx").name
+        finally:
+            prog.close()
+        if debug:
+            # Only a regression test while the name really does move out of the
+            # directory holding local.h; otherwise it would pass for free.
+            assert os.path.dirname(os.path.realpath(name)) != os.path.realpath(tmp_path)
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("debug", [False, True])
+def test_nvrtc_debug_keeps_file_the_caller_named(init_cuda, tmp_path, debug):
+    """Program only unlinks a temp file it wrote itself (issue #2422).
+
+    The name handed to NVRTC doubled as the cleanup target, so a name pointing at
+    a file that already existed made teardown delete the caller's own source.
+    """
+    import gc
+
+    source = tmp_path / "matmul.cu"
+    contents = "// the caller's own file\n"
+    source.write_text(contents, encoding="utf-8")
+    code = 'extern "C" __global__ void matmul() {}'
+    options = ProgramOptions(arch="sm_80", name=str(source), debug=debug)
+
+    prog = Program(code, "c++", options)
+    prog.compile("ptx")
+    prog.close()
+    assert source.is_file(), "close() deleted a file the caller owns"
+
+    # __dealloc__ runs the same cleanup, so collection must spare it too.
+    prog = Program(code, "c++", options)
+    prog.compile("ptx")
+    del prog
+    gc.collect()
+    assert source.is_file(), "collection deleted a file the caller owns"
+    assert source.read_text(encoding="utf-8") == contents
+
+
+@pytest.mark.agent_authored(model="cursor-grok-4.6")
+def test_cuda_gdb_shows_nvrtc_debug_source_lines(init_cuda):
+    import pathlib
+
+    cuda_gdb = shutil.which("cuda-gdb")
+    if cuda_gdb is None:
+        pytest.skip("cuda-gdb is not on PATH")
+
+    child = pathlib.Path(__file__).resolve().parent / "helpers" / "cuda_gdb_src.py"
+    proc = subprocess.run(  # noqa: S603 - trusted argv: cuda-gdb + this interpreter + in-tree helper
+        [
+            cuda_gdb,
+            "--batch",
+            "-ex",
+            "set cuda break_on_launch application",
+            "-ex",
+            "run",
+            "-ex",
+            "list",
+            "--args",
+            sys.executable,
+            "-u",
+            str(child),
+        ],
+        check=False,
+        capture_output=True,
+        text=True,
+        timeout=120,
+    )
+    output = (proc.stdout or "") + (proc.stderr or "")
+    lowered = output.lower()
+    if "operation not permitted" in lowered or "ptrace" in lowered or "debugging is not possible" in lowered:
+        pytest.xfail("cuda-gdb is not usable for debugging on this machine: " + output)
+    assert re.search(r"cuda_gdb_src_kernel_\w+\.cu", output), output
+    assert "ISSUE_2422_SOURCE_LINE" in output, output
+    assert "No such file or directory" not in output, output
+
+
 def test_nvrtc_compile_with_logs_capture(init_cuda):
     """Program.compile with logs= exercises the NVRTC program-log reading path."""
     import io
@@ -922,3 +1235,162 @@ def test_nvrtc_compile_with_logs_capture(init_cuda):
     assert isinstance(result, ObjectCode)
     assert logs.getvalue(), "Expected non-empty compilation log from #warning directive"
     program.close()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_program_options_bad_define_macro_nested_list_invalid_element():
+    """Nested define_macro list with a non-processable element raises at the element."""
+    # [("MACRO", "1")] makes is_nested_sequence True; 42 fails the inner processor.
+    opts = ProgramOptions(name="test", arch="sm_80", define_macro=[("MACRO", "1"), 42])
+    with pytest.raises(RuntimeError, match=r"Expected define_macro.*got 42"):
+        opts.as_bytes("nvrtc")
+
+
+@pytest.mark.parametrize(
+    "kwargs",
+    [
+        {"relocatable_device_code": True},
+        {"extensible_whole_program": True},
+        {"lineinfo": True},
+        {"ptxas_options": "-v"},
+        {"max_register_count": 32},
+        {"use_fast_math": True},
+        {"extra_device_vectorization": True},
+        {"gen_opt_lto": True},
+        {"define_macro": "M"},
+        {"undefine_macro": "M"},
+        {"include_path": "include-dir"},
+        pytest.param({"use_bundled_headers": True}, marks=bundled_headers_available),
+        {"pre_include": "header.h"},
+        {"no_source_include": True},
+        {"std": "c++17"},
+        {"builtin_move_forward": False},
+        {"builtin_initializer_list": False},
+        {"disable_warnings": True},
+        {"restrict": True},
+        {"device_as_default_execution_space": True},
+        {"device_int128": True},
+        {"optimization_info": "inline"},
+        {"no_display_error_number": True},
+        {"diag_error": 1},
+        {"diag_suppress": 1},
+        {"diag_warn": 1},
+        {"brief_diagnostics": True},
+        {"time": "timing.csv"},
+        {"split_compile": 2},
+        {"fdevice_syntax_only": True},
+        {"minimal": True},
+    ],
+    ids=lambda kw: next(iter(kw)),
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_nvvm_options_reject_each_unsupported_flag(kwargs):
+    """Every NVVM-unsupported option is rejected, named, and reported alone."""
+    # This table mirrors _prepare_nvvm_options_impl's rejection list one-for-one.
+    options = ProgramOptions(arch="sm_80", **kwargs)
+    name = next(iter(kwargs))
+    with pytest.raises(CUDAError, match=rf"^The following options are not supported by NVVM backend: {name}$"):
+        options.as_bytes("nvvm")
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_nvrtc_as_bytes_emits_sequence_and_uncommon_flags():
+    """as_bytes emits the NVRTC spellings that compile-option tests do not hit."""
+    options = ProgramOptions(
+        arch="sm_80",
+        ptxas_options="-v",
+        pre_include=["a.h", "b.h"],
+        device_float128=True,
+        diag_warn=[1000, 1001],
+        time="timing.csv",
+        split_compile=2,
+        pch_dir="pch-cache",
+    )
+    flags = [opt.decode() for opt in options.as_bytes("nvrtc")]
+    assert "--ptxas-options=-v" in flags
+    assert "--pre-include=a.h" in flags
+    assert "--pre-include=b.h" in flags
+    assert "--device-float128" in flags
+    assert "--diag-warn=1000" in flags
+    assert "--diag-warn=1001" in flags
+    assert "--time=timing.csv" in flags
+    assert "--split-compile=2" in flags
+    assert "--pch-dir=pch-cache" in flags
+
+    single_pre = ProgramOptions(arch="sm_80", pre_include="only.h")
+    assert "--pre-include=only.h" in [opt.decode() for opt in single_pre.as_bytes("nvrtc")]
+
+
+@pytest.mark.thread_unsafe(reason="patches the process-global os.fdopen and tempfile.mkstemp")
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_nvrtc_debug_falls_back_when_temp_file_write_fails(init_cuda, monkeypatch):
+    """A write failure removes the temporary source and falls back to the default name."""
+    import contextlib
+    import os
+
+    from cuda.core import _program
+
+    real_fdopen = os.fdopen
+    real_mkstemp = _program.tempfile.mkstemp
+    temp_paths = []
+
+    class _FailingWriter:
+        def write(self, _code):
+            raise OSError("No space left on device")
+
+    @contextlib.contextmanager
+    def _write_fails(fd, *args, **kwargs):
+        with real_fdopen(fd, *args, **kwargs):
+            yield _FailingWriter()
+
+    def _record_mkstemp(*args, **kwargs):
+        fd, path = real_mkstemp(*args, **kwargs)
+        temp_paths.append(path)
+        return fd, path
+
+    monkeypatch.setattr(_program.os, "fdopen", _write_fails)
+    monkeypatch.setattr(_program.tempfile, "mkstemp", _record_mkstemp)
+
+    code = 'extern "C" __global__ void matmul() {}'
+    prog = Program(code, "c++", ProgramOptions(debug=True, arch="sm_80"))
+    try:
+        assert len(temp_paths) == 1
+        assert not os.path.exists(temp_paths[0])
+        assert prog.compile("ptx").name == "default_program"
+    finally:
+        prog.close()
+
+
+@nvvm_available
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_nvvm_compile_with_libdevice(nvvm_ir):
+    """use_libdevice resolves a referenced libdevice function into the generated PTX."""
+    store = "  store i32 %call, i32* %data, align 4"
+    declaration = "declare i32 @llvm.nvvm.read.ptx.sreg.ctaid.x()"
+    assert store in nvvm_ir and declaration in nvvm_ir
+    libdevice_ir = nvvm_ir.replace(
+        store,
+        """  %arg = sitofp i32 %call to double
+  %result = call double @__nv_sin(double %arg)
+  %converted = fptosi double %result to i32
+  store i32 %converted, i32* %data, align 4""",
+    ).replace(
+        declaration,
+        """declare double @__nv_sin(double)
+
+declare i32 @llvm.nvvm.read.ptx.sreg.ctaid.x()""",
+    )
+    from cuda.pathfinder import BitcodeLibNotFoundError
+
+    program = Program(libdevice_ir, "nvvm", ProgramOptions(use_libdevice=True, arch="sm_80"))
+    try:
+        try:
+            obj = program.compile("ptx")
+        except BitcodeLibNotFoundError:
+            pytest.skip("libdevice bitcode not found")
+        assert isinstance(obj, ObjectCode)
+        assert obj.code
+        # Without libdevice, NVVM leaves an external __nv_sin declaration in PTX.
+        assert not any(b".extern" in line and b"__nv_sin" in line for line in obj.code.splitlines())
+    finally:
+        program.close()
diff --git a/cuda_core/tests/test_program_cache.py b/cuda_core/tests/test_program_cache.py
index a8d3fc85f7e..bd327eb0d05 100644
--- a/cuda_core/tests/test_program_cache.py
+++ b/cuda_core/tests/test_program_cache.py
@@ -319,6 +319,20 @@ def test_make_program_cache_key_rejects_extra_sources_outside_nvvm(code_type, co
         )
 
 
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("value", [True, False])
+def test_make_program_cache_key_ignores_numba_debug_for_ptx(value):
+    """``numba_debug`` cannot change PTX-path output -- no linker backend reads
+    it -- so it must not perturb the cache key (#2640).
+
+    If it did, two compiles producing byte-identical cubins would miss each
+    other in the cache.
+    """
+    baseline = _make_key(code=".version 7.0", code_type="ptx", target_type="cubin", options=_opts())
+    with_flag = _make_key(code=".version 7.0", code_type="ptx", target_type="cubin", options=_opts(numba_debug=value))
+    assert with_flag == baseline
+
+
 @pytest.mark.parametrize(
     "kwargs, exc_type, match",
     [
@@ -1512,41 +1526,18 @@ def test_filestream_cache_rejects_non_positive_size_cap(tmp_path, bad):
         FileStreamProgramCache(tmp_path / "fc", max_size_bytes=bad)
 
 
-def test_default_cache_dir_lives_under_user_cache_root(monkeypatch, tmp_path):
-    """The cache root is platform-specific:
-
-    * Linux: ``$XDG_CACHE_HOME`` or ``~/.cache``.
-    * Windows: ``%LOCALAPPDATA%`` or ``~/AppData/Local``.
-
-    Both branches must end in ``cuda-python/program-cache``; that suffix
-    is what guarantees a stable on-disk layout across releases.
-    """
-    from pathlib import Path
-
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_file_stream_default_cache_dir_appends_program_cache_leaf(monkeypatch, tmp_path):
+    """The file-stream cache's default dir is the shared user-cache root plus a
+    ``program-cache`` leaf, so it can live alongside sibling caches (e.g. NVRTC's
+    bundled-headers cache) under the same ``cuda-python`` vendor directory."""
     from cuda.core.utils import _program_cache
-    from cuda.core.utils._program_cache._file_stream import _default_cache_dir
 
-    # Path must end with cuda-python/program-cache regardless of platform.
-    assert _default_cache_dir().parts[-2:] == ("cuda-python", "program-cache")
-
-    # Linux branch: XDG_CACHE_HOME wins when set.
-    monkeypatch.setattr(_program_cache._file_stream, "_IS_WINDOWS", False)
-    monkeypatch.setenv("XDG_CACHE_HOME", str(tmp_path / "xdg"))
-    assert _default_cache_dir() == tmp_path / "xdg" / "cuda-python" / "program-cache"
+    monkeypatch.setattr(_program_cache._file_stream, "_user_cache_dir", lambda: tmp_path / "root")
 
-    # Linux branch: falls back to ``~/.cache`` when XDG_CACHE_HOME is unset.
-    monkeypatch.delenv("XDG_CACHE_HOME", raising=False)
-    monkeypatch.setattr(Path, "home", classmethod(lambda _cls: tmp_path / "home"))
-    assert _default_cache_dir() == tmp_path / "home" / ".cache" / "cuda-python" / "program-cache"
-
-    # Windows branch: LOCALAPPDATA wins when set.
-    monkeypatch.setattr(_program_cache._file_stream, "_IS_WINDOWS", True)
-    monkeypatch.setenv("LOCALAPPDATA", str(tmp_path / "appdata"))
-    assert _default_cache_dir() == tmp_path / "appdata" / "cuda-python" / "program-cache"
+    from cuda.core.utils._program_cache._file_stream import _default_cache_dir
 
-    # Windows branch: falls back to ``~/AppData/Local`` when LOCALAPPDATA is unset.
-    monkeypatch.delenv("LOCALAPPDATA", raising=False)
-    assert _default_cache_dir() == tmp_path / "home" / "AppData" / "Local" / "cuda-python" / "program-cache"
+    assert _default_cache_dir() == tmp_path / "root" / "program-cache"
 
 
 def test_filestream_cache_uses_default_dir_when_path_omitted(tmp_path, monkeypatch):
diff --git a/cuda_core/tests/test_rlcompleter_patch.py b/cuda_core/tests/test_rlcompleter_patch.py
index 68bd7b6e4f7..50283e62a31 100644
--- a/cuda_core/tests/test_rlcompleter_patch.py
+++ b/cuda_core/tests/test_rlcompleter_patch.py
@@ -107,3 +107,61 @@ def test_opt_out_env_var_disables_patch_even_when_interactive():
     result = _run_probe(pythoninspect=True, opt_out=True)
     assert result.returncode == 0, f"stderr: {result.stderr}\nstdout: {result.stdout}"
     assert "crash: RuntimeError" in result.stdout, result.stdout
+
+
+# Imports cuda.core and reports whether the rlcompleter patch was installed.
+# No CUDA device is needed: the opt-out is evaluated at import time. The
+# stdlib rlcompleter module has no `property` attribute of its own, so its
+# presence is exactly the signal that the patch ran.
+_OPT_OUT_PROBE_SCRIPT = textwrap.dedent("""
+    import rlcompleter
+
+    import cuda.core  # noqa: F401
+
+    print(f"patched: {hasattr(rlcompleter, 'property')}")
+""")
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize(
+    ("value", "expect_patched"),
+    [
+        # Empty / whitespace-only means "not set": `export VAR=` is the usual
+        # way to neutralize a variable in a shell profile or container spec.
+        ("", True),
+        ("   ", True),
+        # Integer values keep their long-standing meaning.
+        ("0", True),
+        ("00", True),
+        ("1", False),
+        ("2", False),
+        # Non-integer values are honored as an opt-out.
+        ("true", False),
+        ("yes", False),
+    ],
+)
+def test_opt_out_env_var_values(value, expect_patched):
+    """`CUDA_CORE_DONT_FIX_TAB_COMPLETION` must never break `import cuda.core`.
+
+    The opt-out used to be read with a bare `int(...)` at import time, so any
+    value that is not a base-10 integer -- including the empty string -- raised
+    `ValueError: invalid literal for int() with base 10: ''` out of
+    `cuda/core/__init__.py` and made the package unimportable.
+    """
+    env = os.environ.copy()
+    env.pop("PYTHONPATH", None)
+    env["CUDA_CORE_DONT_FIX_TAB_COMPLETION"] = value
+    # Run from a neutral directory so a source tree next to the test run
+    # cannot shadow the installed package (see _run_probe).
+    with tempfile.TemporaryDirectory() as tmpdir:
+        result = subprocess.run(  # noqa: S603
+            [sys.executable, "-c", _OPT_OUT_PROBE_SCRIPT],
+            capture_output=True,
+            text=True,
+            env=env,
+            check=False,
+            stdin=subprocess.DEVNULL,
+            cwd=tmpdir,
+        )
+    assert result.returncode == 0, f"stderr: {result.stderr}\nstdout: {result.stdout}"
+    assert result.stdout.strip() == f"patched: {expect_patched}", result.stdout
diff --git a/cuda_core/tests/test_stream.py b/cuda_core/tests/test_stream.py
index 49e372c9d53..02e817cf85b 100644
--- a/cuda_core/tests/test_stream.py
+++ b/cuda_core/tests/test_stream.py
@@ -28,6 +28,14 @@ def test_stream_init_with_options(init_cuda):
     assert stream.priority == 0
 
 
+@pytest.mark.agent_authored(model="glm-5.2")
+def test_stream_init_with_dict_options(init_cuda):
+    """Device.create_stream accepts a plain dict for options (backward compat)."""
+    stream = Device().create_stream(options={"nonblocking": True, "priority": 0})
+    assert stream.is_nonblocking is True
+    assert stream.priority == 0
+
+
 def test_stream_handle(init_cuda):
     stream = Device().create_stream(options=StreamOptions())
     assert isinstance(stream.handle, driver.CUstream)
@@ -66,6 +74,31 @@ def test_stream_wait_event(init_cuda):
     s2.sync()
 
 
+@pytest.mark.agent_authored(model="claude-fable-5-1")
+def test_stream_wait_stream_on_other_device(device_x2):
+    """Stream.wait(other_stream) must work when the streams live on different
+    devices and neither device is necessarily current: the temporary ordering
+    event has to be created in the *recorded* stream's context, since
+    cuEventRecord rejects an event from another context (#2311)."""
+    from helpers.contexts import current_context_handle
+
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    s0 = dev0.create_stream()
+    dev1.set_current()
+    s1 = dev1.create_stream()
+    ambient = current_context_handle()
+    try:
+        s1.wait(s0)  # dev1 current: s0's device is not current
+        s0.wait(s1)  # dev1 current: self's device is not current
+        s0.sync()
+        s1.sync()
+        assert current_context_handle() == ambient
+    finally:
+        s0.close()
+        s1.close()
+
+
 def test_stream_wait_invalid_event(init_cuda):
     stream = Device().create_stream(options=StreamOptions())
     with pytest.raises(ValueError):
@@ -111,13 +144,78 @@ def test_per_thread_default_stream():
     assert isinstance(PER_THREAD_DEFAULT_STREAM, Stream)
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+@pytest.mark.parametrize(
+    ("handle", "singleton"),
+    [
+        (driver.CU_STREAM_LEGACY, LEGACY_DEFAULT_STREAM),
+        (driver.CU_STREAM_PER_THREAD, PER_THREAD_DEFAULT_STREAM),
+    ],
+)
+def test_borrowed_default_stream_token_can_close(handle, singleton, init_cuda):
+    Device().set_current()
+    stream = Stream.from_handle(int(handle))
+
+    assert stream is not singleton
+    assert not stream.is_closed
+
+    stream.close()
+
+    assert stream.is_closed
+    assert not singleton.is_closed
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_raw_null_stream_is_live_until_closed(init_cuda):
+    """A live wrapper around NULL CUstream is distinct from a closed wrapper."""
+    Device().set_current()
+    stream = Stream.from_handle(0)
+
+    assert not stream.is_closed
+    assert Stream_accept(stream) is stream
+    assert stream.__cuda_stream__() == (0, 0)
+
+    stream.close()
+    assert stream.is_closed
+    assert int(stream.handle) == 0
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_stream_rejected_before_operations(init_cuda):
+    stream = Device().create_stream()
+    wrapped = StreamWrapper(stream)
+    stream.close()
+
+    assert stream.is_closed
+    for operation in (
+        lambda: Stream_accept(stream),
+        lambda: Stream_accept(wrapped, allow_stream_protocol=True),
+        stream.__cuda_stream__,
+        stream.sync,
+        stream.record,
+        stream.create_graph_builder,
+    ):
+        with pytest.raises(RuntimeError, match="Stream has been closed"):
+            operation()
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_stream_accept_rejects_closed_graph_builder(init_cuda):
+    builder = Device().create_graph_builder()
+    builder.close()
+
+    assert builder.is_closed
+    with pytest.raises(RuntimeError, match="GraphBuilder has been closed"):
+        Stream_accept(builder)
+
+
 def test_stream_subclassing(init_cuda):
     class MyStream(Stream):
         pass
 
     dev = Device()
     dev.set_current()
-    stream = MyStream._init(options=StreamOptions(), device_id=dev.device_id)
+    stream = MyStream._init(options=StreamOptions(), device_id=dev.device_id, ctx=dev.context)
     assert isinstance(stream, MyStream)
 
 
@@ -303,3 +401,167 @@ def test_default_stream_consistency(init_cuda):
     # Should be same object (or at least equal)
     assert default1 == default2
     assert hash(default1) == hash(default2)
+
+
+class _BadStreamProtocol:
+    """Object whose __cuda_stream__ (a method) returns a malformed value."""
+
+    def __init__(self, value):
+        self._value = value
+
+    def __cuda_stream__(self):
+        return self._value
+
+
+class _AttrStreamProtocol:
+    """Object implementing __cuda_stream__ as an attribute (deprecated form)
+    rather than a method; the tuple length is wrong so resolution stops before
+    any GPU work."""
+
+    __cuda_stream__ = (0, 1, 2)
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_stream_init_rejects_obj_and_options():
+    """Stream._init rejects supplying both a foreign object and options."""
+    from cuda.core._stream import Stream
+
+    with pytest.raises(ValueError, match="obj and options cannot be both specified"):
+        Stream._init(obj=_BadStreamProtocol((0, 0)), options=StreamOptions())
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+@pytest.mark.parametrize(
+    "value,match",
+    [
+        ((0, 1, 2), "must return a sequence with 2 elements"),  # wrong length
+        (5, "must return a sequence with 2 elements"),  # not a sequence
+        ((1, 123), r"first element of the sequence.*must be 0"),  # bad version
+    ],
+)
+def test_stream_init_rejects_bad_cuda_stream_protocol(value, match):
+    """A foreign object whose __cuda_stream__ returns a malformed value is
+    rejected before any handle is created."""
+    from cuda.core._stream import Stream
+
+    with pytest.raises(RuntimeError, match=match):
+        Stream._init(obj=_BadStreamProtocol(value))
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_stream_init_warns_on_attribute_cuda_stream_protocol():
+    """Implementing __cuda_stream__ as an attribute (not a method) is deprecated:
+    resolution emits a DeprecationWarning and then still rejects the malformed
+    (wrong-length) value with a RuntimeError."""
+    from cuda.core._stream import Stream
+
+    with (
+        pytest.warns(DeprecationWarning, match="must be implemented as a method"),
+        pytest.raises(RuntimeError, match="must return a sequence with 2 elements"),
+    ):
+        Stream._init(obj=_AttrStreamProtocol())
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_stream_init_from_existing_stream_object(init_cuda):
+    """Passing an existing Stream as the foreign object yields a borrowed stream over the same handle."""
+    from cuda.core._stream import Stream
+
+    src = Device().create_stream(options=StreamOptions())
+    borrowed = Stream._init(obj=src)
+    assert int(borrowed.handle) == int(src.handle)
+    borrowed.close()
+    src.close()
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+def test_stream_from_handle_lazy_flag_and_priority_queries(init_cuda):
+    """A from_handle stream reports is_nonblocking and priority read back from the
+    driver (matching the source stream), not the constructor defaults."""
+    from cuda.core._stream import Stream
+
+    # priority=-1 (not the default 0) so the value proves the driver was actually queried.
+    real = Device().create_stream(options=StreamOptions(nonblocking=True, priority=-1))
+    wrapped = Stream.from_handle(int(real.handle))
+    assert wrapped.is_nonblocking is True
+    assert wrapped.priority == -1
+    wrapped.close()
+    real.close()
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+@pytest.mark.thread_unsafe(
+    reason="mutates the process-global CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM env var that default_stream() reads live"
+)
+def test_default_stream_per_thread_when_env_set(monkeypatch):
+    """default_stream() returns the per-thread default stream when
+    CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM is set to a nonzero value, and the
+    legacy default stream otherwise."""
+    from cuda.core._stream import default_stream
+
+    monkeypatch.setenv("CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM", "1")
+    assert default_stream() is PER_THREAD_DEFAULT_STREAM
+    monkeypatch.delenv("CUDA_PYTHON_CUDA_PER_THREAD_DEFAULT_STREAM", raising=False)
+    assert default_stream() is LEGACY_DEFAULT_STREAM
+
+
+def _skip_unless_multi_gpu():
+    if len(Device.get_all_devices()) < 2:
+        pytest.skip("requires 2+ GPUs")
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize("stream", [LEGACY_DEFAULT_STREAM, PER_THREAD_DEFAULT_STREAM])
+def test_default_stream_follows_current_context(stream):
+    """A default-stream token denotes whatever context is current, so its
+    queries follow a context switch instead of reporting the first context
+    they ever saw (issue #2485)."""
+    _skip_unless_multi_gpu()
+
+    for device_id in (0, 1, 0):
+        dev = Device(device_id)
+        dev.set_current()
+        assert stream.device.device_id == device_id
+        assert stream.context == dev.context
+        assert stream.record().context == dev.context
+        # Exercise Stream.resources and check it tracks the same context
+        # resolution as .context (issue #2485).
+        assert stream.resources.sm.sm_count == stream.context.resources.sm.sm_count
+        assert stream.resources.sm.sm_count == dev.resources.sm.sm_count
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_default_stream_first_touch_does_not_pin_context():
+    """Any query resolves the context, including repr(), so logging a default
+    stream must not bind the singleton to whichever context happened to be
+    current at the time (issue #2485)."""
+    _skip_unless_multi_gpu()
+
+    Device(1).set_current()
+    repr(LEGACY_DEFAULT_STREAM)
+
+    dev0 = Device(0)
+    dev0.set_current()
+    assert LEGACY_DEFAULT_STREAM.device.device_id == 0
+    assert LEGACY_DEFAULT_STREAM.context == dev0.context
+
+
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_created_stream_keeps_its_own_context():
+    """A created stream has a context fixed at creation and keeps reporting it
+    across a switch; only default-stream tokens follow the current context
+    (issue #2485)."""
+    _skip_unless_multi_gpu()
+
+    dev0 = Device(0)
+    dev0.set_current()
+    stream = dev0.create_stream()
+    assert stream.context == dev0.context
+
+    try:
+        Device(1).set_current()
+        assert stream.device.device_id == 0
+        assert stream.context == dev0.context
+    finally:
+        dev0.set_current()
+        stream.close()
diff --git a/cuda_core/tests/test_tensor_map.py b/cuda_core/tests/test_tensor_map.py
index b2d6cbd6c61..06433792a61 100644
--- a/cuda_core/tests/test_tensor_map.py
+++ b/cuda_core/tests/test_tensor_map.py
@@ -3,8 +3,8 @@
 
 import numpy as np
 import pytest
+from helpers.memory import create_managed_memory_resource_or_skip, skip_if_managed_memory_unsupported
 
-from conftest import create_managed_memory_resource_or_skip, skip_if_managed_memory_unsupported
 from cuda.core import (
     Device,
     ManagedMemoryResourceOptions,
@@ -19,7 +19,9 @@
     TensorMapL2Promotion,
     TensorMapOOBFill,
     TensorMapSwizzle,
+    _coerce_tensor_map_descriptor_options,
     _require_view_device,
+    _resolve_data_type,
 )
 from cuda.core.utils import StridedMemoryView
 
@@ -648,3 +650,67 @@ def test_from_im2col_wide_rank_validation(self, dev, skip_if_no_im2col_wide):
                 pixels_per_column=4,
                 data_type=TensorMapDataType.FLOAT32,
             )
+
+
+class _DtypeView:
+    """Minimal stand-in for a StridedMemoryView exposing only ``.dtype``.
+
+    ``_resolve_data_type`` reads nothing else off the view, so this keeps the
+    host-only tests free of any GPU allocation.
+    """
+
+    def __init__(self, dtype):
+        self.dtype = dtype
+
+
+@pytest.mark.agent_authored(model="claude-opus-4.8")
+class TestTensorMapHelpers:
+    """Host-only coverage for the arg-marshalling helpers' input-validation branches.
+
+    The happy-path normalize/coerce/resolve/stride cases are covered by the TMA
+    factory-method tests above once they run on TMA-capable hardware (e.g. the H200
+    coverage runner). Only the rejection branches those tests never hit — real
+    devices never feed bad inputs — are pinned here.
+    """
+
+    # Rejected by the public TensorMapDescriptorOptions(...) constructor, whose
+    # __post_init__ runs the normalize/require-enum helpers.
+    @pytest.mark.parametrize(
+        ("kwargs", "match"),
+        [
+            (dict(box_dim=5), "box_dim must be a tuple of ints"),
+            (dict(box_dim=(1, "x", 3)), r"box_dim\[1\] must be an int"),
+            (dict(box_dim=(32,), swizzle=2), "swizzle must be a TensorMapSwizzle"),
+            (dict(box_dim=(32,), interleave=0), "interleave must be a TensorMapInterleave"),
+        ],
+        ids=["box_dim_non_iterable", "box_dim_non_int_element", "swizzle_wrong_type", "interleave_wrong_type"],
+    )
+    def test_options_rejects_invalid(self, kwargs, match):
+        with pytest.raises(TypeError, match=match):
+            TensorMapDescriptorOptions(**kwargs)
+
+    @pytest.mark.parametrize(
+        ("view_dtype", "data_type", "match"),
+        [
+            (None, np.complex128, "Unsupported dtype"),  # explicit unsupported dtype
+            (None, None, "Cannot infer TMA data type"),  # nothing to infer from
+            (np.dtype(np.complex64), None, "Unsupported dtype"),  # view's dtype unsupported
+        ],
+        ids=["explicit_unsupported", "cannot_infer", "view_dtype_unsupported"],
+    )
+    def test_resolve_data_type_rejects(self, view_dtype, data_type, match):
+        with pytest.raises(ValueError, match=match):
+            _resolve_data_type(_DtypeView(view_dtype), data_type)
+
+    def test_coerce_requires_box_dim_without_options(self):
+        with pytest.raises(TypeError, match="box_dim is required unless options is provided"):
+            _coerce_tensor_map_descriptor_options(
+                None,
+                None,
+                element_strides=None,
+                data_type=None,
+                interleave=TensorMapInterleave.NONE,
+                swizzle=TensorMapSwizzle.NONE,
+                l2_promotion=TensorMapL2Promotion.NONE,
+                oob_fill=TensorMapOOBFill.NONE,
+            )
diff --git a/cuda_core/tests/test_texture_surface.py b/cuda_core/tests/test_texture_surface.py
index bee60104be7..42ae716e8f3 100644
--- a/cuda_core/tests/test_texture_surface.py
+++ b/cuda_core/tests/test_texture_surface.py
@@ -5,10 +5,12 @@
 
 import numpy as np
 import pytest
+from helpers.contexts import current_context_handle, no_current_context
 
 import cuda.core
 from cuda.core import (
     Device,
+    LegacyPinnedMemoryResource,
 )
 from cuda.core.texture import (
     MipmappedArrayOptions,
@@ -45,6 +47,107 @@ def test_resource_descriptor_init_disabled():
         ResourceDescriptor()
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_texture_resources_target_receiver_context(device_x2):
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    ctx0 = dev0.context
+    dev1.set_current()
+    ctx1_handle = current_context_handle()
+
+    with dev0.create_opaque_array(
+        OpaqueArrayOptions(
+            shape=(8, 8),
+            format=ArrayFormatType.UINT8,
+            num_channels=4,
+            is_surface_load_store=True,
+        )
+    ) as array:
+        assert array.device == dev0
+        assert current_context_handle() == ctx1_handle
+        with dev0.create_mipmapped_array(
+            MipmappedArrayOptions(
+                shape=(8, 8),
+                format=ArrayFormatType.UINT8,
+                num_channels=4,
+                num_levels=2,
+            )
+        ) as mipmap:
+            assert mipmap.device == dev0
+            assert current_context_handle() == ctx1_handle
+            with mipmap.get_level(0) as level:
+                assert level.device == dev0
+                assert current_context_handle() == ctx1_handle
+                resource = ResourceDescriptor.from_opaque_array(array)
+                with (
+                    dev0.create_texture_object(resource=resource, options=TextureObjectOptions()) as texture,
+                    dev0.create_surface_object(resource=resource) as surface,
+                ):
+                    assert texture.device == dev0
+                    assert surface.device == dev0
+                    assert current_context_handle() == ctx1_handle
+    assert current_context_handle() == ctx1_handle
+    assert int(ctx0.handle) != ctx1_handle
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_texture_resources_restore_no_current_context(deinit_cuda):
+    device = Device(0)
+    device.set_current()
+
+    with no_current_context():
+        with (
+            device.create_opaque_array(
+                OpaqueArrayOptions(
+                    shape=(8, 8),
+                    format=ArrayFormatType.UINT8,
+                    num_channels=4,
+                )
+            ) as array,
+            device.create_texture_object(resource=ResourceDescriptor.from_opaque_array(array)) as texture,
+        ):
+            assert array.device == device
+            assert texture.device == device
+            assert current_context_handle() == 0
+        assert current_context_handle() == 0
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_texture_creation_rejects_mismatched_receiver(device_x2):
+    dev0, dev1 = device_x2
+    dev0.set_current()
+    with dev0.create_opaque_array(
+        OpaqueArrayOptions(
+            shape=(8, 8),
+            format=ArrayFormatType.UINT8,
+            num_channels=4,
+            is_surface_load_store=True,
+        )
+    ) as array:
+        resource = ResourceDescriptor.from_opaque_array(array)
+        dev1.set_current()
+        ctx1_handle = current_context_handle()
+        with pytest.raises(ValueError, match="resource belongs to device 0"):
+            dev1.create_texture_object(resource=resource)
+        with pytest.raises(ValueError, match="resource belongs to device 0"):
+            dev1.create_surface_object(resource=resource)
+        assert current_context_handle() == ctx1_handle
+
+
+@pytest.mark.agent_authored(model="claude-sonnet-5")
+def test_texture_linear_accepts_pinned_buffer(init_cuda):
+    """Pinned memory is device-accessible and not bound to any device, so a
+    pinned buffer is a valid linear texture backing whose device check is
+    skipped (device_id == -1) rather than failed (#2311)."""
+    mr = LegacyPinnedMemoryResource()
+    with mr.allocate(256) as buf:
+        assert buf.device_id == -1
+
+        resource = ResourceDescriptor.from_linear(buf, format=ArrayFormatType.UINT8, num_channels=1)
+        with init_cuda.create_texture_object(resource=resource) as texture:
+            assert texture.device == init_cuda
+
+
 def test_array_2d_create_and_properties(init_cuda):
     arr = Device().create_opaque_array(
         OpaqueArrayOptions(shape=(32, 16), format=ArrayFormatType.FLOAT32, num_channels=1)
@@ -715,6 +818,77 @@ def test_texture_surface_close_is_idempotent(init_cuda):
     tex_arr.close()
 
 
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_closed_arrays_rejected_before_active_operations(init_cuda):
+    device = Device()
+    stream = device.create_stream()
+    arr = device.create_opaque_array(OpaqueArrayOptions(shape=(8,), format=ArrayFormatType.UINT8, num_channels=1))
+    array_resource = ResourceDescriptor.from_opaque_array(arr)
+    arr.close()
+
+    assert arr.is_closed
+    assert bool(arr) is True  # Preserve backward-compatible truthiness after close.
+    with pytest.raises(RuntimeError, match="OpaqueArray has been closed"):
+        arr.copy_from(bytearray(8), stream=stream)
+    with pytest.raises(RuntimeError, match="OpaqueArray has been closed"):
+        ResourceDescriptor.from_opaque_array(arr)
+    with pytest.raises(RuntimeError, match="OpaqueArray has been closed"):
+        device.create_texture_object(resource=array_resource, options=TextureObjectOptions())
+
+    mip = device.create_mipmapped_array(
+        MipmappedArrayOptions(
+            shape=(8, 8),
+            format=ArrayFormatType.UINT8,
+            num_channels=1,
+            num_levels=2,
+        )
+    )
+    mip_resource = ResourceDescriptor.from_mipmapped_array(mip)
+    mip.close()
+
+    assert mip.is_closed
+    assert bool(mip) is True  # Preserve backward-compatible truthiness after close.
+    with pytest.raises(RuntimeError, match="MipmappedArray has been closed"):
+        mip.get_level(0)
+    with pytest.raises(RuntimeError, match="MipmappedArray has been closed"):
+        ResourceDescriptor.from_mipmapped_array(mip)
+    with pytest.raises(RuntimeError, match="MipmappedArray has been closed"):
+        device.create_texture_object(resource=mip_resource, options=TextureObjectOptions())
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_texture_and_surface_state_tracks_close(init_cuda):
+    device = Device()
+    texture_array = device.create_opaque_array(
+        OpaqueArrayOptions(shape=(8,), format=ArrayFormatType.UINT8, num_channels=1)
+    )
+    texture = device.create_texture_object(
+        resource=ResourceDescriptor.from_opaque_array(texture_array),
+        options=TextureObjectOptions(),
+    )
+    assert not texture.is_closed
+    texture.close()
+    assert texture.is_closed
+    assert bool(texture) is True  # Preserve backward-compatible truthiness after close.
+
+    surface_array = device.create_opaque_array(
+        OpaqueArrayOptions(
+            shape=(8, 8),
+            format=ArrayFormatType.UINT8,
+            num_channels=4,
+            is_surface_load_store=True,
+        )
+    )
+    surface = device.create_surface_object(resource=ResourceDescriptor.from_opaque_array(surface_array))
+    assert not surface.is_closed
+    surface.close()
+    assert surface.is_closed
+    assert bool(surface) is True  # Preserve backward-compatible truthiness after close.
+
+    texture_array.close()
+    surface_array.close()
+
+
 # --- Negative-path validation tests ------------------------------------------
 
 
diff --git a/cuda_core/tests/test_utils.py b/cuda_core/tests/test_utils.py
index e637aac0a0f..0aaec2e04b9 100644
--- a/cuda_core/tests/test_utils.py
+++ b/cuda_core/tests/test_utils.py
@@ -27,7 +27,7 @@
     ml_dtypes = None
 import numpy as np
 import pytest
-from helpers.marks import requires_module
+from cuda_python_test_helpers.marks import requires_module
 
 from cuda.core import Device
 from cuda.core._dlpack import DLDeviceType
@@ -660,7 +660,7 @@ def test_from_array_interface(x, init_cuda, expected_dtype):
     assert smv.dtype == np.dtype(expected_dtype)
     assert smv.shape == x.shape
     assert smv.ptr == x.ctypes.data
-    assert smv.device_id == init_cuda.device_id
+    assert smv.device_id == -1
     assert smv.is_device_accessible is False
     assert smv.exporting_obj is x
     assert smv.readonly is not x.flags.writeable
@@ -1023,6 +1023,29 @@ def test_strided_memory_view_proxy_cai_only_has_dlpack_false():
     assert proxy.obj is obj
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_strided_memory_view_proxy_cai_view(init_cuda):
+    """A CAI-only proxy materializes its view through the CAI branch."""
+    from cuda.core._memoryview import _StridedMemoryViewProxy
+
+    obj = _make_cuda_array_interface_obj(shape=(2,), strides=None)
+    view = _StridedMemoryViewProxy(obj).view(-1)
+    assert view.exporting_obj is obj
+    assert view.shape == (2,)
+    assert view.is_device_accessible is True
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_strided_memory_view_view_rejects_dtype_itemsize_mismatch():
+    """Changing dtype cannot change the existing layout's element size."""
+    view = StridedMemoryView.from_any_interface(
+        np.arange(4, dtype=np.int16),
+        stream_ptr=-1,
+    )
+    with pytest.raises(ValueError, match="dtype's itemsize"):
+        view.view(dtype=np.int8)
+
+
 def test_view_as_cai_device_pointer_and_stream_ordering(init_cuda):
     """``view_as_cai`` on a real device pointer resolves the device ordinal via
     ``cuPointerGetAttribute`` and takes the cross-stream branch when the CAI
diff --git a/cuda_core/tests/test_utils_dlpack.py b/cuda_core/tests/test_utils_dlpack.py
index 9c2ff64a52f..70eaedc6118 100644
--- a/cuda_core/tests/test_utils_dlpack.py
+++ b/cuda_core/tests/test_utils_dlpack.py
@@ -23,6 +23,10 @@
 _PyCapsule_IsValid.argtypes = (ctypes.py_object, ctypes.c_char_p)
 _PyCapsule_IsValid.restype = ctypes.c_int
 
+_Py_DecRef = ctypes.pythonapi.Py_DecRef
+_Py_DecRef.argtypes = (ctypes.c_void_p,)
+_Py_DecRef.restype = None
+
 
 _NUMPY_NATIVE_DLPACK_DTYPES = (
     np.uint8,
@@ -76,6 +80,31 @@ def test_dlpack_export_roundtrip_special_shapes(shape):
     _assert_dlpack_export_roundtrip(np.zeros(shape, dtype=np.complex128))
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_export_array_interface_reports_cpu(init_cuda):
+    """An array-interface view without a DLPack tensor exports as CPU memory."""
+    src = np.arange(6, dtype=np.int32)
+    view = StridedMemoryView.from_array_interface(src)
+    assert view.is_device_accessible is False
+    assert view.device_id == -1
+    assert view.__dlpack_device__() == (int(DLDeviceType.kDLCPU), 0)
+    assert np.array_equal(np.from_dlpack(view), src)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_view_of_buffer_reuses_exporting_buffer(init_cuda):
+    """Re-viewing a Buffer-imported tensor reuses the original Buffer owner."""
+    buffer = init_cuda.memory_resource.allocate(16, stream=init_cuda.default_stream)
+    try:
+        view = StridedMemoryView.from_dlpack(buffer, stream_ptr=-1)
+        adjusted = view.view(dtype=np.uint8)
+        assert adjusted.exporting_obj is buffer
+        assert adjusted.ptr == int(buffer.handle)
+        del adjusted, view
+    finally:
+        buffer.close()
+
+
 def test_dlpack_export_unversioned_capsule_and_deleter():
     """``__dlpack__()`` with no ``max_version`` yields an *unversioned* unused
     DLPack capsule; dropping it unconsumed runs ``_smv_pycapsule_deleter`` on
@@ -121,6 +150,21 @@ def __dlpack__(self, **kwargs):
         StridedMemoryView.from_dlpack(_FakeUnsupportedDevice(), stream_ptr=0)
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_from_dlpack_cuda_stream_none_ambiguous():
+    """A CUDA DLPack source requires an explicit consumer stream."""
+
+    class _FakeCudaDevice:
+        def __dlpack_device__(self):
+            return (int(DLDeviceType.kDLCUDA), 0)
+
+        def __dlpack__(self, **kwargs):
+            raise AssertionError("__dlpack__ must not be reached")
+
+    with pytest.raises(BufferError, match="stream=None is ambiguous"):
+        StridedMemoryView.from_dlpack(_FakeCudaDevice(), stream_ptr=None)
+
+
 class _DLPackNoMaxVersion:
     """Wraps a StridedMemoryView but rejects the ``max_version`` kwarg, forcing the
     TypeError fallback in ``view_as_dlpack`` and an *unversioned* capsule import.
@@ -166,6 +210,11 @@ def test_from_dlpack_typeerror_fallback_unversioned_import():
 # consumer would, exercising the StridedMemoryView exchange-API implementation.
 # Pointers use PYFUNCTYPE so a failing call raises its real Python exception
 # (TypeError/RuntimeError/NotImplementedError).
+#
+# dlpack.h documents every `*_no_sync` entry point as returning "-1 on failure
+# with a Python exception set", so every failure below is asserted with
+# `pytest.raises`. A test that settles for `assert rc == -1` would be asserting a
+# contract violation, not the contract.
 # ---------------------------------------------------------------------------
 
 _PyCapsule_GetPointer = ctypes.pythonapi.PyCapsule_GetPointer
@@ -219,6 +268,72 @@ class _DLManagedTensorVersioned(ctypes.Structure):
     ]
 
 
+# DLPACK_FLAG_BITMASK_READ_ONLY in dlpack.h.
+_FLAG_READ_ONLY = 1 << 0
+
+
+class _VersionedCapsuleExport:
+    def __init__(self, base, capsule):
+        self.base = base
+        self.capsule = capsule
+
+    def __dlpack_device__(self):
+        return self.base.__dlpack_device__()
+
+    def __dlpack__(self, **kwargs):
+        return self.capsule
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_versioned_readonly_export_and_import(init_cuda):
+    """The versioned readonly flag survives a StridedMemoryView round-trip."""
+    src = np.arange(4, dtype=np.int32)
+    src.setflags(write=False)
+    base = StridedMemoryView.from_array_interface(src)
+    capsule = base.__dlpack__(max_version=(1, 0))
+    dlm = ctypes.cast(
+        _PyCapsule_GetPointer(capsule, b"dltensor_versioned"),
+        ctypes.POINTER(_DLManagedTensorVersioned),
+    )
+    assert dlm.contents.flags & _FLAG_READ_ONLY
+
+    imported = StridedMemoryView.from_dlpack(
+        _VersionedCapsuleExport(base, capsule),
+        stream_ptr=-1,
+    )
+    assert imported.readonly is True
+
+
+@pytest.mark.parametrize(
+    ("code", "bits", "lanes", "exception", "match"),
+    [
+        pytest.param(0, 32, 2, NotImplementedError, "vector dtypes", id="lanes"),
+        pytest.param(1, 24, 1, TypeError, "uint24", id="uint-bits"),
+        pytest.param(0, 24, 1, TypeError, "int24", id="int-bits"),
+        pytest.param(2, 8, 1, TypeError, "float8", id="float-bits"),
+        pytest.param(5, 32, 1, TypeError, "complex32", id="complex-bits"),
+        pytest.param(6, 1, 1, TypeError, "1-bit bool", id="bool-bits"),
+        pytest.param(255, 8, 1, TypeError, "Unsupported dtype", id="code"),
+    ],
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_from_dlpack_malformed_dtype_rejected_on_access(code, bits, lanes, exception, match):
+    """Accessing ``.dtype`` rejects malformed producer dtype metadata."""
+    base = StridedMemoryView.from_any_interface(np.arange(4, dtype=np.int32), stream_ptr=-1)
+    capsule = base.__dlpack__(max_version=(1, 0))
+    dlm = ctypes.cast(
+        _PyCapsule_GetPointer(capsule, b"dltensor_versioned"),
+        ctypes.POINTER(_DLManagedTensorVersioned),
+    )
+    dlm.contents.dl_tensor.dtype = _DLDataType(code, bits, lanes)
+    imported = StridedMemoryView.from_dlpack(
+        _VersionedCapsuleExport(base, capsule),
+        stream_ptr=-1,
+    )
+    with pytest.raises(exception, match=match):
+        _ = imported.dtype
+
+
 @pytest.mark.agent_authored(model="cursor-grok-4.5")
 @pytest.mark.parametrize(
     "max_version, capsule_name, managed_cls",
@@ -251,6 +366,46 @@ def __dlpack__(self, stream=None, max_version=None, **kwargs):
     producer_deleter(dlm)
 
 
+@pytest.mark.agent_authored(model="claude-opus-5")
+@pytest.mark.parametrize(
+    "max_version, capsule_name, managed_cls",
+    [
+        pytest.param(None, b"dltensor", _DLManagedTensor, id="unversioned"),
+        pytest.param((1, 0), b"dltensor_versioned", _DLManagedTensorVersioned, id="versioned"),
+    ],
+)
+def test_from_dlpack_honours_byte_offset(max_version, capsule_name, managed_cls):
+    """DLPack puts a tensor's first element at ``data + byte_offset``, so a producer
+    may report the allocation base in ``data`` and express a slice as an offset.
+    ``view.ptr`` must account for it, as the capsule-consuming path already does."""
+    src = np.arange(9, dtype=np.int32)
+    # View only the first 8 elements, so shifting by one element below stays inside
+    # the allocation and a regression fails an assertion instead of reading OOB.
+    base = StridedMemoryView.from_any_interface(src[:8], stream_ptr=-1)
+    capsule = base.__dlpack__(max_version=max_version)
+    dlm = ctypes.cast(_PyCapsule_GetPointer(capsule, capsule_name), ctypes.POINTER(managed_cls))
+    assert dlm.contents.dl_tensor.data == src.ctypes.data
+    assert dlm.contents.dl_tensor.byte_offset == 0
+
+    # Re-describe the same 8 elements as src[1:9]. byte_offset is the only field
+    # written: shape and strides share one producer-owned block, so leave them alone.
+    dlm.contents.dl_tensor.byte_offset = src.itemsize
+
+    class _Export:
+        def __dlpack_device__(self):
+            return base.__dlpack_device__()
+
+        def __dlpack__(self, stream=None, max_version=None, **kwargs):
+            if capsule_name == b"dltensor" and max_version is not None:
+                raise TypeError("force unversioned")
+            return capsule
+
+    view = StridedMemoryView.from_dlpack(_Export(), stream_ptr=-1)
+    assert view.ptr == src.ctypes.data + src.itemsize
+    assert view.shape == (8,)
+    assert np.array_equal(np.from_dlpack(view), src[1:])
+
+
 _FN_FROM_PY = ctypes.PYFUNCTYPE(ctypes.c_int, ctypes.c_void_p, ctypes.POINTER(ctypes.c_void_p))
 _FN_TO_PY = ctypes.PYFUNCTYPE(ctypes.c_int, ctypes.c_void_p, ctypes.POINTER(ctypes.c_void_p))
 _FN_DLTENSOR_FROM_PY = ctypes.PYFUNCTYPE(ctypes.c_int, ctypes.c_void_p, ctypes.c_void_p)
@@ -294,6 +449,14 @@ def test_dlpack_c_exchange_api_current_work_stream():
     assert not out.value  # set back to NULL
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_c_exchange_api_current_work_stream_null_output():
+    """``current_work_stream`` rejects a NULL output pointer."""
+    api = _get_exchange_api()
+    with pytest.raises(RuntimeError, match="out_current_stream cannot be NULL"):
+        api.current_work_stream(int(DLDeviceType.kDLCPU), 0, None)
+
+
 def test_dlpack_c_exchange_api_dltensor_from_py_object():
     """``dltensor_from_py_object_no_sync`` fills a borrowed DLTensor from a view."""
     api = _get_exchange_api()
@@ -317,6 +480,27 @@ def test_dlpack_c_exchange_api_dltensor_from_py_object_type_error():
         api.dltensor_from_py_object_no_sync(id(not_a_view), ctypes.byref(out))
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_c_exchange_api_dltensor_from_py_object_null_output():
+    """``dltensor_from_py_object_no_sync`` rejects a NULL output pointer."""
+    api = _get_exchange_api()
+    view = StridedMemoryView.from_any_interface(np.arange(3), stream_ptr=-1)
+    with pytest.raises(RuntimeError, match="out cannot be NULL"):
+        api.dltensor_from_py_object_no_sync(id(view), None)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_c_exchange_api_dltensor_from_py_object_scalar():
+    """A borrowed scalar DLTensor has NULL shape and strides pointers."""
+    api = _get_exchange_api()
+    view = StridedMemoryView.from_any_interface(np.array(7, dtype=np.int16), stream_ptr=-1)
+    out = _DLTensor()
+    assert api.dltensor_from_py_object_no_sync(id(view), ctypes.byref(out)) == 0
+    assert out.ndim == 0
+    assert not out.shape
+    assert not out.strides
+
+
 def test_dlpack_c_exchange_api_managed_tensor_roundtrip():
     """``managed_tensor_from_py_object_no_sync`` produces a managed tensor that
     ``managed_tensor_to_py_object_no_sync`` turns back into a StridedMemoryView.
@@ -345,6 +529,30 @@ def test_dlpack_c_exchange_api_managed_tensor_roundtrip():
     assert imported.ptr == src.ctypes.data
 
 
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_c_exchange_api_managed_tensor_from_py_object_errors():
+    """The managed-tensor producer validates both output and object inputs."""
+    api = _get_exchange_api()
+    view = StridedMemoryView.from_any_interface(np.arange(3), stream_ptr=-1)
+    with pytest.raises(RuntimeError, match="out cannot be NULL"):
+        api.managed_tensor_from_py_object_no_sync(id(view), None)
+
+    not_a_view = object()
+    out = ctypes.c_void_p()
+    with pytest.raises(TypeError, match="must be a StridedMemoryView"):
+        api.managed_tensor_from_py_object_no_sync(id(not_a_view), ctypes.byref(out))
+    assert not out.value
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_c_exchange_api_to_py_object_null_output():
+    """``managed_tensor_to_py_object_no_sync`` rejects a NULL output pointer."""
+    api = _get_exchange_api()
+    tensor = _DLManagedTensorVersioned()
+    with pytest.raises(RuntimeError, match="out_py_object cannot be NULL"):
+        api.managed_tensor_to_py_object_no_sync(ctypes.byref(tensor), None)
+
+
 def test_dlpack_c_exchange_api_to_py_object_null_tensor():
     """``managed_tensor_to_py_object_no_sync`` rejects a NULL tensor (RuntimeError)."""
     api = _get_exchange_api()
@@ -354,6 +562,36 @@ def test_dlpack_c_exchange_api_to_py_object_null_tensor():
     assert not out_obj.value  # set to NULL before the error
 
 
+@pytest.mark.parametrize(
+    "device_type",
+    [
+        DLDeviceType.kDLCUDA,
+        DLDeviceType.kDLCUDAHost,
+        DLDeviceType.kDLCUDAManaged,
+    ],
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_dlpack_c_exchange_api_to_py_object_device_accessible(device_type):
+    """Supported CUDA-family devices produce device-accessible views."""
+    api = _get_exchange_api()
+    tensor = _DLManagedTensorVersioned()
+    tensor.version = _DLPackVersion(1, 0)
+    tensor.dl_tensor.device = _DLDevice(int(device_type), 0)
+    tensor.dl_tensor.dtype = _DLDataType(0, 32, 1)
+    out_obj = ctypes.c_void_p()
+    assert api.managed_tensor_to_py_object_no_sync(ctypes.byref(tensor), ctypes.byref(out_obj)) == 0
+    assert out_obj.value
+    try:
+        imported = ctypes.cast(out_obj, ctypes.py_object).value
+        assert imported.is_device_accessible is True
+        assert imported.device_id == 0
+        del imported
+    finally:
+        # The C API returned a new reference. Release it while the synthetic
+        # tensor backing the view is still alive -- __dealloc__ dereferences it.
+        _Py_DecRef(out_obj)
+
+
 def test_dlpack_c_exchange_api_managed_tensor_allocator_not_supported():
     """Covers the ``managed_tensor_allocator`` entry point, which is unsupported
     and only ever raises NotImplementedError (StridedMemoryView never allocates)."""
diff --git a/cuda_pathfinder/LICENSE b/cuda_pathfinder/LICENSE
index a4baaa2d3fa..f3fe76ecadf 100644
--- a/cuda_pathfinder/LICENSE
+++ b/cuda_pathfinder/LICENSE
@@ -1,4 +1,4 @@
-Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 
                                  Apache License
                            Version 2.0, January 2004
@@ -176,3 +176,28 @@ Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
       of your accepting any such warranty or additional liability.
 
    END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
diff --git a/cuda_pathfinder/cuda/pathfinder/__init__.py b/cuda_pathfinder/cuda/pathfinder/__init__.py
index dc818dfd08f..a64b5ef64c7 100644
--- a/cuda_pathfinder/cuda/pathfinder/__init__.py
+++ b/cuda_pathfinder/cuda/pathfinder/__init__.py
@@ -20,9 +20,7 @@
 )
 from cuda.pathfinder._dynamic_libs.load_dl_common import LoadedDL as LoadedDL
 from cuda.pathfinder._dynamic_libs.load_nvidia_dynamic_lib import load_nvidia_dynamic_lib as load_nvidia_dynamic_lib
-from cuda.pathfinder._dynamic_libs.supported_nvidia_libs import (
-    SUPPORTED_LIBNAMES as SUPPORTED_NVIDIA_LIBNAMES,
-)
+from cuda.pathfinder._dynamic_libs.supported_nvidia_libs import SUPPORTED_LIBNAMES as _SUPPORTED_NVIDIA_LIBNAMES
 from cuda.pathfinder._headers.find_nvidia_headers import LocatedHeaderDir as LocatedHeaderDir
 from cuda.pathfinder._headers.find_nvidia_headers import find_nvidia_header_directory as find_nvidia_header_directory
 from cuda.pathfinder._headers.find_nvidia_headers import (
@@ -60,6 +58,7 @@
     locate_static_lib as locate_static_lib,
 )
 from cuda.pathfinder._utils.env_vars import get_cuda_path_or_home as get_cuda_path_or_home
+from cuda.pathfinder._utils.windows_arch import UnsupportedArchError as UnsupportedArchError
 
 from cuda.pathfinder._version import __version__  # isort: skip
 
@@ -76,6 +75,11 @@
 #: Example utilities: ``"nvdisasm"``, ``"cuobjdump"``, ``"nvcc"``.
 SUPPORTED_BINARY_UTILITIES = _SUPPORTED_BINARIES
 
+#: Tuple of CUDA Toolkit dynamic library names supported by
+#: :func:`load_nvidia_dynamic_lib` for the current operating system and
+#: interpreter architecture.
+SUPPORTED_NVIDIA_LIBNAMES = _SUPPORTED_NVIDIA_LIBNAMES
+
 #: Tuple of supported bitcode library names that can be resolved
 #: via ``locate_bitcode_lib()`` and ``find_bitcode_lib()``.
 #: Example value: ``"device"``.
diff --git a/cuda_pathfinder/cuda/pathfinder/_binaries/find_nvidia_binary_utility.py b/cuda_pathfinder/cuda/pathfinder/_binaries/find_nvidia_binary_utility.py
index 834db8fe8fa..42dcfda1cfb 100644
--- a/cuda_pathfinder/cuda/pathfinder/_binaries/find_nvidia_binary_utility.py
+++ b/cuda_pathfinder/cuda/pathfinder/_binaries/find_nvidia_binary_utility.py
@@ -3,8 +3,9 @@
 
 import functools
 import os
+from collections.abc import Iterable
 
-from cuda.pathfinder._binaries import supported_nvidia_binaries
+from cuda.pathfinder._binaries import supported_nvidia_binaries, windows_nsight
 from cuda.pathfinder._utils.ctk_root_canary import CTK_ROOT_CANARY_ANCHOR_LIBNAMES
 from cuda.pathfinder._utils.env_vars import get_cuda_path_or_home
 from cuda.pathfinder._utils.find_sub_dirs import find_sub_dirs_all_sitepackages
@@ -46,6 +47,27 @@ def _ctk_bin_subdirs(root: str) -> list[str]:
     return [os.path.join(root, "bin")]
 
 
+def _resolve_candidate_paths(candidates: Iterable[str]) -> str | None:
+    """Return the first executable candidate, preserving candidate order."""
+    seen: set[str] = set()
+    for candidate in candidates:
+        if candidate in seen:
+            continue
+        seen.add(candidate)
+        if _is_executable_candidate(candidate):
+            return os.path.abspath(candidate)
+    return None
+
+
+def _find_windows_compute_sanitizer(ctk_root: str) -> str | None:
+    return _resolve_candidate_paths(
+        (
+            os.path.join(ctk_root, "bin", "compute-sanitizer.bat"),
+            os.path.join(ctk_root, "compute-sanitizer", "compute-sanitizer.exe"),
+        )
+    )
+
+
 def _resolve_ctk_root_via_canary() -> str | None:
     from cuda.pathfinder._dynamic_libs.load_nvidia_dynamic_lib import resolve_ctk_root_via_canary
 
@@ -69,6 +91,20 @@ def _resolve_in_trusted_dirs(normalized_name: str, dirs: list[str]) -> str | Non
     return None
 
 
+def _resolve_names_in_trusted_dirs(candidate_names: tuple[str, ...], dirs: list[str]) -> str | None:
+    """Resolve ordered candidate names within each trusted directory."""
+    seen: set[str] = set()
+    for directory in dirs:
+        if directory in seen:
+            continue
+        assert directory
+        seen.add(directory)
+        found = _resolve_candidate_paths(os.path.join(directory, name) for name in candidate_names)
+        if found is not None:
+            return found
+    return None
+
+
 @functools.cache
 def find_nvidia_binary_utility(utility_name: str) -> str | None:
     """Locate a CUDA binary utility executable.
@@ -87,6 +123,19 @@ def find_nvidia_binary_utility(utility_name: str) -> str | None:
     Raises:
         UnsupportedBinaryError: If ``utility_name`` is not in the supported set
             (see ``SUPPORTED_BINARY_UTILITIES``).
+        RuntimeError: If a native Windows architecture needed for an
+            architecture-specific utility layout cannot be determined, or an
+            installed Nsight product has incomplete or invalid registry data.
+
+    Windows on ARM (WoA) Note:
+        Binary utilities execute in separate processes and do not need to match
+        the Python process architecture. When choosing among architecture-specific
+        Windows layouts, this API deliberately targets the native machine
+        architecture rather than the Python interpreter architecture. For
+        example, standalone ``nsys`` and ``ncu`` discovery under x64 Python on an
+        Arm64 machine selects the Arm64 target. This differs from
+        ``load_nvidia_dynamic_lib`` and ``find_static_lib``, which target the
+        Python interpreter architecture.
 
     Search order:
         1. **NVIDIA Python wheels**
@@ -100,17 +149,27 @@ def find_nvidia_binary_utility(utility_name: str) -> str | None:
              environment variable, which use platform-specific bin directory
              layouts (``Library/bin`` on Windows, ``bin`` on Linux).
 
-        3. **CUDA Toolkit environment variables**
+        3. **Library-specific standalone installations**
 
-           - Use ``CUDA_HOME`` or ``CUDA_PATH`` (in that order), searching
-             ``bin/x64``, ``bin/x86_64``, and ``bin`` subdirectories on Windows,
-             or just ``bin`` on Linux.
+           - Search the installation paths for the CUDA Toolkit, Nsight Systems,
+             and Nsight Compute.
+
+           3.1. **Nsight installations**: On Windows, locate Nsight Systems and
+                Nsight Compute from their installer registry entries. Select
+                architecture-specific binaries using the native machine
+                architecture, independent of Python. Lookup of the standalone
+                ``nsys`` and ``ncu`` CLIs is terminal; a miss does not fall
+                through to CUDA Toolkit locations.
+
+           3.2. **CUDA Toolkit installation**: Use ``CUDA_PATH`` or ``CUDA_HOME``
+                (in that order), searching ``bin/x64``, ``bin/x86_64``, and
+                ``bin`` subdirectories on Windows, or just ``bin`` on Linux.
 
         4. **CTK-root canary fallback**
 
-           - Only when steps 1-3 miss: resolve the ``cudart`` library through the
-             OS dynamic loader, derive the CUDA Toolkit root from it, and search
-             that root's bin layout.
+           - For utilities that reach this step after the earlier searches miss,
+             resolve the ``cudart`` library through the OS dynamic loader, derive
+             the CUDA Toolkit root from it, and search that root's bin layout.
 
     Note:
         Results are cached using ``@functools.cache`` for performance. The cache
@@ -146,17 +205,35 @@ def find_nvidia_binary_utility(utility_name: str) -> str | None:
         else:
             dirs.append(os.path.join(conda_prefix, "bin"))
 
-    # 3. Search in CUDA Toolkit (CUDA_HOME/CUDA_PATH)
-    if (cuda_home := get_cuda_path_or_home()) is not None:
-        dirs.extend(_ctk_bin_subdirs(cuda_home))
-
     normalized_name = _normalize_utility_name(utility_name)
-    found = _resolve_in_trusted_dirs(normalized_name, dirs)
+    if IS_WINDOWS and utility_name in ("compute-sanitizer", "ncu"):
+        candidate_names = (f"{utility_name}.bat", normalized_name)
+        found = _resolve_names_in_trusted_dirs(candidate_names, dirs)
+    else:
+        found = _resolve_in_trusted_dirs(normalized_name, dirs)
     if found is not None:
         return found
 
+    # 3. Search library-specific standalone installations.
+    # 3.1. Standalone Nsight CLI lookup is terminal; CTK does not contain nsys/ncu.
+    if IS_WINDOWS and utility_name == "nsys":
+        return _resolve_candidate_paths(windows_nsight.nsys_candidate_paths())
+    if IS_WINDOWS and utility_name == "ncu":
+        return _resolve_candidate_paths(windows_nsight.ncu_candidate_paths())
+
+    # 3.2. Search in CUDA Toolkit (CUDA_PATH/CUDA_HOME).
+    if (cuda_path := get_cuda_path_or_home()) is not None:
+        if IS_WINDOWS and utility_name == "compute-sanitizer":
+            found = _find_windows_compute_sanitizer(cuda_path)
+        else:
+            found = _resolve_in_trusted_dirs(normalized_name, _ctk_bin_subdirs(cuda_path))
+        if found is not None:
+            return found
+
     # 4. CTK-root canary fallback.
     ctk_root = _resolve_ctk_root_via_canary()
     if ctk_root is not None:
+        if IS_WINDOWS and utility_name == "compute-sanitizer":
+            return _find_windows_compute_sanitizer(ctk_root)
         return _resolve_in_trusted_dirs(normalized_name, _ctk_bin_subdirs(ctk_root))
     return None
diff --git a/cuda_pathfinder/cuda/pathfinder/_binaries/supported_nvidia_binaries.py b/cuda_pathfinder/cuda/pathfinder/_binaries/supported_nvidia_binaries.py
index ac70378f112..9839c03de3e 100644
--- a/cuda_pathfinder/cuda/pathfinder/_binaries/supported_nvidia_binaries.py
+++ b/cuda_pathfinder/cuda/pathfinder/_binaries/supported_nvidia_binaries.py
@@ -2,7 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 import os
 
-# Site-packages bin directories where binaries might be found
+# Site-packages bin directories where binaries might be found, in search order.
 # Based on NVIDIA wheel layouts (same for Linux and Windows)
 _CUDA_NVCC_BIN = os.path.join("nvidia", "cuda_nvcc", "bin")
 _CUDA13_BIN = os.path.join("nvidia", "cu13", "bin")
@@ -13,8 +13,9 @@
 SITE_PACKAGES_BINDIRS = {
     # Core compilation tools
     "nvcc": (_CUDA13_BIN, _CUDA_NVCC_BIN),
+    "ptxas": (_CUDA13_BIN, _CUDA_NVCC_BIN),
     "nvdisasm": (_CUDA13_BIN, _CUDA_NVCC_BIN),
-    "cuobjdump": (_CUDA_NVCC_BIN,),
+    "cuobjdump": (_CUDA13_BIN, _CUDA_NVCC_BIN),
     "nvprune": (_CUDA_NVCC_BIN,),
     "fatbinary": (_CUDA13_BIN, _CUDA_NVCC_BIN),
     "bin2c": (_CUDA13_BIN, _CUDA_NVCC_BIN),
diff --git a/cuda_pathfinder/cuda/pathfinder/_binaries/windows_nsight.py b/cuda_pathfinder/cuda/pathfinder/_binaries/windows_nsight.py
new file mode 100644
index 00000000000..c5944c39e64
--- /dev/null
+++ b/cuda_pathfinder/cuda/pathfinder/_binaries/windows_nsight.py
@@ -0,0 +1,74 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import importlib
+import os
+from collections.abc import Iterator
+from typing import Any
+
+from cuda.pathfinder._utils.windows_arch import windows_machine_arch
+
+_REGISTRY_ROOT = r"SOFTWARE\NVIDIA Corporation\Installed Products\Nsight"
+
+_NSYS_TARGET_DIR_BY_ARCH = {
+    "x64": "target-windows-x64",
+    "arm64": "target-windows-armv8",
+}
+
+_NCU_TARGET_DIR_BY_ARCH = {
+    "x64": os.path.join("target", "windows-desktop-win7-x64"),
+    "arm64": os.path.join("target", "windows-desktop-win10-t23x-a64"),
+}
+
+
+def _installed_product_root(product: str) -> str | None:
+    """Return the active Nsight product installation recorded by its MSI."""
+    # ``winreg`` attributes are absent from the type stubs on non-Windows hosts.
+    winreg: Any = importlib.import_module("winreg")
+
+    access = winreg.KEY_READ | winreg.KEY_WOW64_64KEY
+    product_key_path = rf"{_REGISTRY_ROOT}\{product}"
+    try:
+        product_context = winreg.OpenKey(winreg.HKEY_LOCAL_MACHINE, product_key_path, 0, access)
+    except FileNotFoundError:
+        return None
+
+    try:
+        with product_context as product_key:
+            current_version, _ = winreg.QueryValueEx(product_key, "CurrentVersion")
+            if not isinstance(current_version, str) or not current_version.strip():
+                raise RuntimeError(
+                    f"Invalid CurrentVersion value {current_version!r} in "
+                    f"Nsight {product!r} registry registration at {product_key_path!r}"
+                )
+            with winreg.OpenKey(product_key, current_version, 0, access) as version_key:
+                install_root, _ = winreg.QueryValueEx(version_key, None)
+    except FileNotFoundError as exc:
+        raise RuntimeError(f"Incomplete Nsight {product!r} registry registration at {product_key_path!r}") from exc
+
+    if not isinstance(install_root, str) or not install_root.strip():
+        raise RuntimeError(
+            f"Invalid installation directory {install_root!r} in Nsight {product!r} "
+            f"registry registration at {product_key_path!r} version {current_version!r}"
+        )
+    return install_root
+
+
+def nsys_candidate_paths() -> Iterator[str]:
+    install_root = _installed_product_root("Systems")
+    if install_root is None:
+        return
+
+    target_dir = _NSYS_TARGET_DIR_BY_ARCH[windows_machine_arch()]
+    yield os.path.join(install_root, target_dir, "nsys.exe")
+
+
+def ncu_candidate_paths() -> Iterator[str]:
+    install_root = _installed_product_root("Compute")
+    if install_root is None:
+        return
+
+    yield os.path.join(install_root, "ncu.bat")
+
+    target_dir = _NCU_TARGET_DIR_BY_ARCH[windows_machine_arch()]
+    yield os.path.join(install_root, target_dir, "ncu.exe")
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/descriptor_catalog.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/descriptor_catalog.py
index 378744ea420..3b51f486278 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/descriptor_catalog.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/descriptor_catalog.py
@@ -6,27 +6,80 @@
 from __future__ import annotations
 
 from dataclasses import dataclass
+from pathlib import PurePosixPath
 from typing import Literal
 
 from cuda.pathfinder._utils.ctk_root_canary import CTK_ROOT_CANARY_ANCHOR_LIBNAMES
 
 PackagedWith = Literal["ctk", "other", "driver"]
+WindowsArch = Literal["x64", "arm64"]
+
+
+@dataclass(frozen=True, slots=True)
+class WindowsSearchDirs:
+    """Windows search locations, highest priority first, grouped by architecture."""
+
+    x64: tuple[str, ...] = ()
+    arm64: tuple[str, ...] = ()
+
+    @classmethod
+    def x64_only(cls, *paths: str) -> WindowsSearchDirs:
+        return cls(x64=paths)
+
+    @classmethod
+    def arm64_only(cls, *paths: str) -> WindowsSearchDirs:
+        return cls(arm64=paths)
+
+    def for_arch(self, target_arch: str) -> tuple[str, ...]:
+        if target_arch == "x64":
+            return self.x64
+        if target_arch == "arm64":
+            return self.arm64
+        raise ValueError(f"Unsupported Windows target architecture: {target_arch!r}")
+
+
+# Windows CTK before 13.4 was x64-only and used the common bin directory.
+# Native ARM64 support starts with the architecture-qualified 13.4 layout.
+DEFAULT_WINDOWS_CTK_ANCHOR_DIRS = WindowsSearchDirs(
+    x64=("bin/x64", "bin"),
+    arm64=("bin/arm64",),
+)
+
+
+def _ctk_windows_wheel_dirs(cuda13_bin_dir: str, cuda12_dir: str) -> WindowsSearchDirs:
+    """Search CUDA 13 first, with the x64-only CUDA 12 wheel as an x64 fallback."""
+    cuda13_bin_path = PurePosixPath(cuda13_bin_dir)
+    return WindowsSearchDirs(
+        x64=((cuda13_bin_path / "x86_64").as_posix(), cuda12_dir),
+        arm64=((cuda13_bin_path / "arm64").as_posix(),),
+    )
 
 
 @dataclass(frozen=True, slots=True)
 class DescriptorSpec:
+    """Dynamic-library metadata; ordered search candidates are tried first-to-last."""
+
     name: str
     packaged_with: PackagedWith
+    # Library filenames are authored in search/load preference order, most preferred first.
     linux_sonames: tuple[str, ...] = ()
     windows_dlls: tuple[str, ...] = ()
+    supported_windows_arch: tuple[WindowsArch, ...] = ()
     site_packages_linux: tuple[str, ...] = ()
-    site_packages_windows: tuple[str, ...] = ()
+    site_packages_windows: WindowsSearchDirs = WindowsSearchDirs()
     dependencies: tuple[str, ...] = ()
+    optional_dependencies: tuple[str, ...] = ()
     anchor_rel_dirs_linux: tuple[str, ...] = ("lib64", "lib")
-    anchor_rel_dirs_windows: tuple[str, ...] = ("bin/x64", "bin")
+    anchor_rel_dirs_windows: WindowsSearchDirs = DEFAULT_WINDOWS_CTK_ANCHOR_DIRS
+    install_root_env_vars_linux: tuple[str, ...] = ()
+    install_root_env_rel_dirs_linux: tuple[str, ...] = ()
+    install_root_env_vars_windows: tuple[str, ...] = ()
+    install_root_env_rel_dirs_windows: WindowsSearchDirs = WindowsSearchDirs()
+    program_files_root_globs_windows: WindowsSearchDirs = WindowsSearchDirs()
     ctk_root_canary_anchor_libnames: tuple[str, ...] = ()
     requires_add_dll_directory: bool = False
     requires_rtld_deepbind: bool = False
+    requires_windows_binary_arch_check: bool = False
 
 
 DESCRIPTOR_CATALOG: tuple[DescriptorSpec, ...] = (
@@ -36,106 +89,128 @@ class DescriptorSpec:
     DescriptorSpec(
         name="cudart",
         packaged_with="ctk",
-        linux_sonames=("libcudart.so.12", "libcudart.so.13"),
-        windows_dlls=("cudart64_12.dll", "cudart64_13.dll"),
+        linux_sonames=("libcudart.so.13", "libcudart.so.12"),
+        windows_dlls=("cudart64_13.dll", "cudart64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cuda_runtime/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cuda_runtime/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cuda_runtime/bin"),
     ),
     DescriptorSpec(
         name="nvfatbin",
         packaged_with="ctk",
-        linux_sonames=("libnvfatbin.so.12", "libnvfatbin.so.13"),
-        windows_dlls=("nvfatbin_120_0.dll", "nvfatbin_130_0.dll"),
+        linux_sonames=("libnvfatbin.so.13", "libnvfatbin.so.12"),
+        windows_dlls=("nvfatbin_130_0.dll", "nvfatbin_120_0.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/nvfatbin/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/nvfatbin/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/nvfatbin/bin"),
     ),
     DescriptorSpec(
         name="nvJitLink",
         packaged_with="ctk",
-        linux_sonames=("libnvJitLink.so.12", "libnvJitLink.so.13"),
-        windows_dlls=("nvJitLink_120_0.dll", "nvJitLink_130_0.dll"),
+        linux_sonames=("libnvJitLink.so.13", "libnvJitLink.so.12"),
+        windows_dlls=("nvJitLink_130_0.dll", "nvJitLink_120_0.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/nvjitlink/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/nvjitlink/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/nvjitlink/bin"),
     ),
     DescriptorSpec(
         name="nvrtc",
         packaged_with="ctk",
-        linux_sonames=("libnvrtc.so.12", "libnvrtc.so.13"),
-        windows_dlls=("nvrtc64_120_0.dll", "nvrtc64_130_0.dll"),
+        linux_sonames=("libnvrtc.so.13", "libnvrtc.so.12"),
+        windows_dlls=("nvrtc64_130_0.dll", "nvrtc64_120_0.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cuda_nvrtc/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cuda_nvrtc/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cuda_nvrtc/bin"),
         requires_add_dll_directory=True,
     ),
     DescriptorSpec(
         name="nvvm",
         packaged_with="ctk",
-        linux_sonames=("libnvvm.so.4",),
-        windows_dlls=("nvvm64.dll", "nvvm64_40_0.dll", "nvvm70.dll"),
+        linux_sonames=("libnvvm.so.4", "libnvvm.so"),
+        windows_dlls=("nvvm70.dll", "nvvm64_40_0.dll", "nvvm64.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cuda_nvcc/nvvm/lib64"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cuda_nvcc/nvvm/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cuda_nvcc/nvvm/bin"),
         anchor_rel_dirs_linux=("nvvm/lib64",),
-        anchor_rel_dirs_windows=("nvvm/bin/*", "nvvm/bin"),
+        # CTK 13.4 installs the ARM64 DLL directly in nvvm/bin, while x64
+        # uses nvvm/bin/x64. Older x64 toolkits also used nvvm/bin, so the
+        # binary in the unqualified directory must be checked at runtime.
+        anchor_rel_dirs_windows=WindowsSearchDirs(
+            x64=("nvvm/bin/x64", "nvvm/bin"),
+            arm64=("nvvm/bin",),
+        ),
         ctk_root_canary_anchor_libnames=CTK_ROOT_CANARY_ANCHOR_LIBNAMES,
+        # requires_windows_binary_arch_check disambiguates pre-13.4 x64 DLLs
+        # from 13.4+ Arm64 DLLs in nvvm/bin; see
+        # _utils/windows_arch.py for the validation.
+        requires_windows_binary_arch_check=True,
     ),
     DescriptorSpec(
         name="cublas",
         packaged_with="ctk",
-        linux_sonames=("libcublas.so.12", "libcublas.so.13"),
-        windows_dlls=("cublas64_12.dll", "cublas64_13.dll"),
+        linux_sonames=("libcublas.so.13", "libcublas.so.12"),
+        windows_dlls=("cublas64_13.dll", "cublas64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cublas/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cublas/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cublas/bin"),
         dependencies=("cublasLt",),
     ),
     DescriptorSpec(
         name="cublasLt",
         packaged_with="ctk",
-        linux_sonames=("libcublasLt.so.12", "libcublasLt.so.13"),
-        windows_dlls=("cublasLt64_12.dll", "cublasLt64_13.dll"),
+        linux_sonames=("libcublasLt.so.13", "libcublasLt.so.12"),
+        windows_dlls=("cublasLt64_13.dll", "cublasLt64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cublas/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cublas/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cublas/bin"),
     ),
     DescriptorSpec(
         name="cufft",
         packaged_with="ctk",
-        linux_sonames=("libcufft.so.11", "libcufft.so.12"),
-        windows_dlls=("cufft64_11.dll", "cufft64_12.dll"),
+        linux_sonames=("libcufft.so.12", "libcufft.so.11"),
+        windows_dlls=("cufft64_12.dll", "cufft64_11.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cufft/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cufft/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cufft/bin"),
         requires_add_dll_directory=True,
     ),
     DescriptorSpec(
         name="cufftw",
         packaged_with="ctk",
-        linux_sonames=("libcufftw.so.11", "libcufftw.so.12"),
-        windows_dlls=("cufftw64_11.dll", "cufftw64_12.dll"),
+        linux_sonames=("libcufftw.so.12", "libcufftw.so.11"),
+        windows_dlls=("cufftw64_12.dll", "cufftw64_11.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cufft/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cufft/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cufft/bin"),
         dependencies=("cufft",),
     ),
     DescriptorSpec(
         name="curand",
         packaged_with="ctk",
-        linux_sonames=("libcurand.so.10", "libcurand.so.11"),
-        windows_dlls=("curand64_10.dll", "curand64_11.dll"),
+        linux_sonames=("libcurand.so.11", "libcurand.so.10"),
+        windows_dlls=("curand64_11.dll", "curand64_10.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/curand/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/curand/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/curand/bin"),
     ),
     DescriptorSpec(
         name="cusolver",
         packaged_with="ctk",
-        linux_sonames=("libcusolver.so.11", "libcusolver.so.12"),
-        windows_dlls=("cusolver64_11.dll", "cusolver64_12.dll"),
+        linux_sonames=("libcusolver.so.12", "libcusolver.so.11"),
+        windows_dlls=("cusolver64_12.dll", "cusolver64_11.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cusolver/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cusolver/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cusolver/bin"),
         dependencies=("nvJitLink", "cusparse", "cublasLt", "cublas"),
     ),
     DescriptorSpec(
         name="cusolverMg",
         packaged_with="ctk",
-        linux_sonames=("libcusolverMg.so.11", "libcusolverMg.so.12"),
-        windows_dlls=("cusolverMg64_11.dll", "cusolverMg64_12.dll"),
+        linux_sonames=("libcusolverMg.so.12", "libcusolverMg.so.11"),
+        windows_dlls=("cusolverMg64_12.dll", "cusolverMg64_11.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cusolver/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cusolver/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cusolver/bin"),
         dependencies=("nvJitLink", "cublasLt", "cublas"),
     ),
     DescriptorSpec(
@@ -143,124 +218,138 @@ class DescriptorSpec:
         packaged_with="ctk",
         linux_sonames=("libcusparse.so.12",),
         windows_dlls=("cusparse64_12.dll",),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cusparse/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cusparse/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cusparse/bin"),
         dependencies=("nvJitLink",),
     ),
     DescriptorSpec(
         name="nppc",
         packaged_with="ctk",
-        linux_sonames=("libnppc.so.12", "libnppc.so.13"),
-        windows_dlls=("nppc64_12.dll", "nppc64_13.dll"),
+        linux_sonames=("libnppc.so.13", "libnppc.so.12"),
+        windows_dlls=("nppc64_13.dll", "nppc64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
     ),
     DescriptorSpec(
         name="nppial",
         packaged_with="ctk",
-        linux_sonames=("libnppial.so.12", "libnppial.so.13"),
-        windows_dlls=("nppial64_12.dll", "nppial64_13.dll"),
+        linux_sonames=("libnppial.so.13", "libnppial.so.12"),
+        windows_dlls=("nppial64_13.dll", "nppial64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppicc",
         packaged_with="ctk",
-        linux_sonames=("libnppicc.so.12", "libnppicc.so.13"),
-        windows_dlls=("nppicc64_12.dll", "nppicc64_13.dll"),
+        linux_sonames=("libnppicc.so.13", "libnppicc.so.12"),
+        windows_dlls=("nppicc64_13.dll", "nppicc64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppidei",
         packaged_with="ctk",
-        linux_sonames=("libnppidei.so.12", "libnppidei.so.13"),
-        windows_dlls=("nppidei64_12.dll", "nppidei64_13.dll"),
+        linux_sonames=("libnppidei.so.13", "libnppidei.so.12"),
+        windows_dlls=("nppidei64_13.dll", "nppidei64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppif",
         packaged_with="ctk",
-        linux_sonames=("libnppif.so.12", "libnppif.so.13"),
-        windows_dlls=("nppif64_12.dll", "nppif64_13.dll"),
+        linux_sonames=("libnppif.so.13", "libnppif.so.12"),
+        windows_dlls=("nppif64_13.dll", "nppif64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppig",
         packaged_with="ctk",
-        linux_sonames=("libnppig.so.12", "libnppig.so.13"),
-        windows_dlls=("nppig64_12.dll", "nppig64_13.dll"),
+        linux_sonames=("libnppig.so.13", "libnppig.so.12"),
+        windows_dlls=("nppig64_13.dll", "nppig64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppim",
         packaged_with="ctk",
-        linux_sonames=("libnppim.so.12", "libnppim.so.13"),
-        windows_dlls=("nppim64_12.dll", "nppim64_13.dll"),
+        linux_sonames=("libnppim.so.13", "libnppim.so.12"),
+        windows_dlls=("nppim64_13.dll", "nppim64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppist",
         packaged_with="ctk",
-        linux_sonames=("libnppist.so.12", "libnppist.so.13"),
-        windows_dlls=("nppist64_12.dll", "nppist64_13.dll"),
+        linux_sonames=("libnppist.so.13", "libnppist.so.12"),
+        windows_dlls=("nppist64_13.dll", "nppist64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppisu",
         packaged_with="ctk",
-        linux_sonames=("libnppisu.so.12", "libnppisu.so.13"),
-        windows_dlls=("nppisu64_12.dll", "nppisu64_13.dll"),
+        linux_sonames=("libnppisu.so.13", "libnppisu.so.12"),
+        windows_dlls=("nppisu64_13.dll", "nppisu64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nppitc",
         packaged_with="ctk",
-        linux_sonames=("libnppitc.so.12", "libnppitc.so.13"),
-        windows_dlls=("nppitc64_12.dll", "nppitc64_13.dll"),
+        linux_sonames=("libnppitc.so.13", "libnppitc.so.12"),
+        windows_dlls=("nppitc64_13.dll", "nppitc64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="npps",
         packaged_with="ctk",
-        linux_sonames=("libnpps.so.12", "libnpps.so.13"),
-        windows_dlls=("npps64_12.dll", "npps64_13.dll"),
+        linux_sonames=("libnpps.so.13", "libnpps.so.12"),
+        windows_dlls=("npps64_13.dll", "npps64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/npp/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/npp/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/npp/bin"),
         dependencies=("nppc",),
     ),
     DescriptorSpec(
         name="nvblas",
         packaged_with="ctk",
-        linux_sonames=("libnvblas.so.12", "libnvblas.so.13"),
-        windows_dlls=("nvblas64_12.dll", "nvblas64_13.dll"),
+        linux_sonames=("libnvblas.so.13", "libnvblas.so.12"),
+        windows_dlls=("nvblas64_13.dll", "nvblas64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cublas/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cublas/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cublas/bin"),
         dependencies=("cublas", "cublasLt"),
     ),
     DescriptorSpec(
         name="nvjpeg",
         packaged_with="ctk",
-        linux_sonames=("libnvjpeg.so.12", "libnvjpeg.so.13"),
-        windows_dlls=("nvjpeg64_12.dll", "nvjpeg64_13.dll"),
+        linux_sonames=("libnvjpeg.so.13", "libnvjpeg.so.12"),
+        windows_dlls=("nvjpeg64_13.dll", "nvjpeg64_12.dll"),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/nvjpeg/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/nvjpeg/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/nvjpeg/bin"),
     ),
     DescriptorSpec(
         name="cufile",
@@ -271,7 +360,7 @@ class DescriptorSpec:
     DescriptorSpec(
         name="cupti",
         packaged_with="ctk",
-        linux_sonames=("libcupti.so.12", "libcupti.so.13"),
+        linux_sonames=("libcupti.so.13", "libcupti.so.12"),
         windows_dlls=(
             "cupti64_2026.3.0.dll",
             "cupti64_2026.2.1.dll",
@@ -290,10 +379,16 @@ class DescriptorSpec:
             "cupti64_2023.1.1.dll",
             "cupti64_2022.4.1.dll",
         ),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cuda_cupti/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x86_64", "nvidia/cuda_cupti/bin"),
+        site_packages_windows=_ctk_windows_wheel_dirs("nvidia/cu13/bin", "nvidia/cuda_cupti/bin"),
         anchor_rel_dirs_linux=("extras/CUPTI/lib64", "lib"),
-        anchor_rel_dirs_windows=("extras/CUPTI/lib64", "bin"),
+        # CTK 13.4 uses architecture-qualified CUPTI directories. Older
+        # Windows CUPTI toolkits were x64-only and used extras/CUPTI/lib64.
+        anchor_rel_dirs_windows=WindowsSearchDirs(
+            x64=("extras/CUPTI/lib/x64", "extras/CUPTI/lib64", "bin"),
+            arm64=("extras/CUPTI/lib/arm64",),
+        ),
         ctk_root_canary_anchor_libnames=CTK_ROOT_CANARY_ANCHOR_LIBNAMES,
     ),
     DescriptorSpec(
@@ -301,12 +396,11 @@ class DescriptorSpec:
         packaged_with="ctk",
         linux_sonames=("libcudla.so.1",),
         windows_dlls=("cudla.dll",),
+        supported_windows_arch=("arm64",),
         site_packages_linux=("nvidia/cu13/lib",),
         # No Windows pip wheel ships cudla.dll today; it is loaded from the local
         # CUDA Toolkit only, so site_packages_windows is intentionally left empty.
-        # The Windows CUDA Toolkit ships cudla.dll under per-architecture bin
-        # subdirs (e.g. bin/arm64 on N1X); search those ahead of the defaults.
-        anchor_rel_dirs_windows=("bin/arm64", "bin/x64", "bin"),
+        anchor_rel_dirs_windows=WindowsSearchDirs.arm64_only("bin/arm64"),
     ),
     # -----------------------------------------------------------------------
     # Third-party / separately packaged libraries
@@ -326,6 +420,29 @@ class DescriptorSpec:
         dependencies=("nvshmem_host",),
         requires_rtld_deepbind=True,
     ),
+    DescriptorSpec(
+        name="cudnn",
+        packaged_with="other",
+        linux_sonames=("libcudnn.so.9",),
+        windows_dlls=("cudnn64_9.dll",),
+        supported_windows_arch=("x64", "arm64"),
+        site_packages_linux=("nvidia/cudnn/lib",),
+        site_packages_windows=WindowsSearchDirs.x64_only("nvidia/cudnn/bin"),
+        dependencies=("cublasLt",),
+        optional_dependencies=("nvrtc",),
+        install_root_env_vars_linux=("CUDNN_PATH",),
+        install_root_env_rel_dirs_linux=("lib", "lib64"),
+        # The ARM64 layout is verified only for the standalone archive rooted
+        # at CUDNN_PATH, not for conda, CUDA_PATH, or Program Files installs.
+        anchor_rel_dirs_windows=WindowsSearchDirs.x64_only("bin/x64", "bin"),
+        install_root_env_vars_windows=("CUDNN_PATH",),
+        install_root_env_rel_dirs_windows=WindowsSearchDirs(
+            x64=("bin/x64", "bin"),
+            arm64=("bin/arm64",),
+        ),
+        program_files_root_globs_windows=WindowsSearchDirs.x64_only("NVIDIA/CUDNN/v9.*"),
+        requires_add_dll_directory=True,
+    ),
     DescriptorSpec(
         name="cusolverMp",
         packaged_with="other",
@@ -338,8 +455,12 @@ class DescriptorSpec:
         packaged_with="other",
         linux_sonames=("libmathdx.so.0",),
         windows_dlls=("mathdx64_0.dll",),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cu12/lib"),
-        site_packages_windows=("nvidia/cu13/bin", "nvidia/cu12/bin"),
+        site_packages_windows=WindowsSearchDirs(
+            x64=("nvidia/cu13/bin", "nvidia/cu12/bin"),
+            arm64=("nvidia/cu13/bin", "nvidia/cu12/bin"),
+        ),
         dependencies=("nvrtc",),
     ),
     DescriptorSpec(
@@ -347,8 +468,12 @@ class DescriptorSpec:
         packaged_with="other",
         linux_sonames=("libcudss.so.0",),
         windows_dlls=("cudss64_0.dll",),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cu12/lib"),
-        site_packages_windows=("nvidia/cu13/bin", "nvidia/cu12/bin"),
+        site_packages_windows=WindowsSearchDirs(
+            x64=("nvidia/cu13/bin", "nvidia/cu12/bin"),
+            arm64=("nvidia/cu13/bin", "nvidia/cu12/bin"),
+        ),
         dependencies=("cublas", "cublasLt"),
     ),
     DescriptorSpec(
@@ -356,16 +481,21 @@ class DescriptorSpec:
         packaged_with="other",
         linux_sonames=("libcusparseLt.so.0",),
         windows_dlls=("cusparseLt.dll",),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("nvidia/cu13/lib", "nvidia/cusparselt/lib"),
-        site_packages_windows=("nvidia/cu13/bin/x64", "nvidia/cusparselt/bin"),
+        site_packages_windows=WindowsSearchDirs(
+            x64=("nvidia/cu13/bin/x64", "nvidia/cusparselt/bin"),
+            arm64=("nvidia/cu13/bin/arm64",),
+        ),
     ),
     DescriptorSpec(
         name="cutensor",
         packaged_with="other",
         linux_sonames=("libcutensor.so.2",),
         windows_dlls=("cutensor.dll",),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("cutensor/lib",),
-        site_packages_windows=("cutensor/bin",),
+        site_packages_windows=WindowsSearchDirs(x64=("cutensor/bin",), arm64=("cutensor/bin",)),
         dependencies=("cublasLt",),
     ),
     DescriptorSpec(
@@ -373,8 +503,9 @@ class DescriptorSpec:
         packaged_with="other",
         linux_sonames=("libcutensorMg.so.2",),
         windows_dlls=("cutensorMg.dll",),
+        supported_windows_arch=("x64", "arm64"),
         site_packages_linux=("cutensor/lib",),
-        site_packages_windows=("cutensor/bin",),
+        site_packages_windows=WindowsSearchDirs(x64=("cutensor/bin",), arm64=("cutensor/bin",)),
         dependencies=("cutensor", "cublasLt"),
     ),
     DescriptorSpec(
@@ -431,6 +562,8 @@ class DescriptorSpec:
         packaged_with="other",
         linux_sonames=("libnccl.so.2",),
         site_packages_linux=("nvidia/nccl/lib",),
+        install_root_env_vars_linux=("NCCL_HOME",),
+        install_root_env_rel_dirs_linux=("lib", "lib64", "build/lib"),
     ),
     DescriptorSpec(
         name="nvpl_fftw",
@@ -452,6 +585,7 @@ class DescriptorSpec:
         packaged_with="driver",
         linux_sonames=("libcuda.so.1",),
         windows_dlls=("nvcuda.dll",),
+        supported_windows_arch=("x64", "arm64"),
     ),
     DescriptorSpec(
         name="nvcudla",
@@ -463,5 +597,6 @@ class DescriptorSpec:
         packaged_with="driver",
         linux_sonames=("libnvidia-ml.so.1",),
         windows_dlls=("nvml.dll",),
+        supported_windows_arch=("x64", "arm64"),
     ),
 )
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_common.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_common.py
index 8d7987d00e2..1dc47e4b52b 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_common.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_common.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 from __future__ import annotations
@@ -32,5 +32,20 @@ class LoadedDL:
 
 
 def load_dependencies(desc: LibDescriptor, load_func: Callable[[str], LoadedDL]) -> None:
+    """Load required dependencies, then best-effort runtime dependencies.
+
+    A plain ``DynamicLibNotFoundError`` from an optional dependency is
+    suppressed. More specific contract errors and failures while loading a
+    dependency that was found remain errors.
+    """
     for dep in desc.dependencies:
         load_func(dep)
+    for dep in desc.optional_dependencies:
+        try:
+            load_func(dep)
+        except DynamicLibNotFoundError as exc:
+            # Both public contract errors inherit DynamicLibNotFoundError, but
+            # neither an unknown descriptor nor platform incompatibility means
+            # that an optional runtime component is simply absent.
+            if type(exc) is not DynamicLibNotFoundError:
+                raise
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_linux.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_linux.py
index 10a92c20830..d9b6f2d8d9f 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_linux.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_linux.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 from __future__ import annotations
@@ -7,6 +7,7 @@
 import ctypes
 import ctypes.util
 import os
+import sys
 from typing import TYPE_CHECKING, cast
 
 from cuda.pathfinder._dynamic_libs.load_dl_common import LoadedDL
@@ -14,7 +15,10 @@
 if TYPE_CHECKING:
     from cuda.pathfinder._dynamic_libs.lib_descriptor import LibDescriptor
 
-CDLL_MODE = os.RTLD_NOW | os.RTLD_GLOBAL
+if sys.platform == "linux":
+    CDLL_MODE = os.RTLD_NOW | os.RTLD_GLOBAL
+else:
+    CDLL_MODE = 0
 
 
 def _load_libdl() -> ctypes.CDLL:
@@ -125,34 +129,35 @@ def abs_path_for_dynamic_library(libname: str, handle: ctypes.CDLL) -> str:
     return os.path.join(l_origin, os.path.basename(l_name))
 
 
-def _candidate_sonames(desc: LibDescriptor) -> list[str]:
-    # Reverse tabulated names to achieve new -> old search order.
-    candidates = list(reversed(desc.linux_sonames))
-    candidates.append(f"lib{desc.name}.so")
-    return candidates
+if sys.platform == "linux":
 
+    def check_if_already_loaded_from_elsewhere(desc: LibDescriptor) -> LoadedDL | None:
+        for soname in desc.linux_sonames:
+            try:
+                handle = ctypes.CDLL(soname, mode=os.RTLD_NOLOAD)
+            except OSError:
+                continue
+            else:
+                return LoadedDL(
+                    abs_path_for_dynamic_library(desc.name, handle),
+                    True,
+                    handle._handle,
+                    "was-already-loaded-from-elsewhere",
+                )
+        return None
 
-def check_if_already_loaded_from_elsewhere(desc: LibDescriptor, _have_abs_path: bool) -> LoadedDL | None:
-    for soname in _candidate_sonames(desc):
-        try:
-            handle = ctypes.CDLL(soname, mode=os.RTLD_NOLOAD)
-        except OSError:
-            continue
-        else:
-            return LoadedDL(
-                abs_path_for_dynamic_library(desc.name, handle),
-                True,
-                handle._handle,
-                "was-already-loaded-from-elsewhere",
-            )
-    return None
+    def _load_lib(desc: LibDescriptor, filename: str) -> ctypes.CDLL:
+        cdll_mode = CDLL_MODE
+        if desc.requires_rtld_deepbind:
+            cdll_mode |= os.RTLD_DEEPBIND
+        return ctypes.CDLL(filename, cdll_mode)
+else:
 
+    def check_if_already_loaded_from_elsewhere(_desc: LibDescriptor) -> LoadedDL | None:
+        raise RuntimeError(f"check_if_already_loaded_from_elsewhere() is not supported on platform {sys.platform!r}")
 
-def _load_lib(desc: LibDescriptor, filename: str) -> ctypes.CDLL:
-    cdll_mode = CDLL_MODE
-    if desc.requires_rtld_deepbind:
-        cdll_mode |= os.RTLD_DEEPBIND
-    return ctypes.CDLL(filename, cdll_mode)
+    def _load_lib(_desc: LibDescriptor, _filename: str) -> ctypes.CDLL:
+        raise RuntimeError(f"_load_lib() is not supported on platform {sys.platform!r}")
 
 
 def load_with_system_search(desc: LibDescriptor) -> LoadedDL | None:
@@ -165,7 +170,7 @@ def load_with_system_search(desc: LibDescriptor) -> LoadedDL | None:
         A LoadedDL object if successful, None if the library cannot be loaded
 
     """
-    for soname in _candidate_sonames(desc):
+    for soname in desc.linux_sonames:
         try:
             handle = _load_lib(desc, soname)
         except OSError:
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_windows.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_windows.py
index b2f61dfc9af..a659409fc83 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_windows.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_dl_windows.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 from __future__ import annotations
@@ -7,6 +7,7 @@
 import ctypes.wintypes
 import os
 import struct
+import sys
 import warnings
 from typing import TYPE_CHECKING
 
@@ -22,7 +23,10 @@
 POINTER_ADDRESS_SPACE = 2 ** (struct.calcsize("P") * 8)
 
 # Set up kernel32 functions with proper types
-kernel32 = ctypes.windll.kernel32  # type: ignore[attr-defined]
+windll = getattr(ctypes, "windll", None)
+if windll is None:
+    raise RuntimeError("ctypes.windll is required on Windows")
+kernel32 = windll.kernel32
 
 # GetModuleHandleW
 kernel32.GetModuleHandleW.argtypes = [ctypes.wintypes.LPCWSTR]
@@ -45,6 +49,11 @@
 kernel32.GetModuleFileNameW.restype = ctypes.wintypes.DWORD
 
 
+# GetLastError
+kernel32.GetLastError.argtypes = []
+kernel32.GetLastError.restype = ctypes.wintypes.DWORD
+
+
 def ctypes_handle_to_unsigned_int(handle: ctypes.wintypes.HMODULE) -> int:
     """Convert ctypes HMODULE to unsigned int."""
     handle_uint = int(handle)
@@ -73,7 +82,8 @@ def add_dll_directory(dll_abs_path: str) -> None:
     # the directory must stay on the search path for the process lifetime, and
     # the handle has no finalizer, so dropping it does not remove the directory.
     try:
-        os.add_dll_directory(dirpath)  # type: ignore[attr-defined]
+        if sys.platform == "win32":
+            os.add_dll_directory(dirpath)
     except OSError as e:
         # Warn instead of failing silently; the PATH update below is a weaker
         # fallback that newer loaders may ignore.
@@ -96,7 +106,7 @@ def abs_path_for_dynamic_library(libname: str, handle: ctypes.wintypes.HMODULE)
     length = kernel32.GetModuleFileNameW(handle, buffer, len(buffer))
 
     if length == 0:
-        error_code = ctypes.GetLastError()  # type: ignore[attr-defined]
+        error_code = kernel32.GetLastError()
         raise RuntimeError(f"GetModuleFileNameW failed for {libname!r} (error code: {error_code})")
 
     # If buffer was too small, try with larger buffer
@@ -104,21 +114,20 @@ def abs_path_for_dynamic_library(libname: str, handle: ctypes.wintypes.HMODULE)
         buffer = ctypes.create_unicode_buffer(32768)  # Extended path length
         length = kernel32.GetModuleFileNameW(handle, buffer, len(buffer))
         if length == 0:
-            error_code = ctypes.GetLastError()  # type: ignore[attr-defined]
+            error_code = kernel32.GetLastError()
             raise RuntimeError(f"GetModuleFileNameW failed for {libname!r} (error code: {error_code})")
 
     return buffer.value
 
 
-def check_if_already_loaded_from_elsewhere(desc: LibDescriptor, have_abs_path: bool) -> LoadedDL | None:
+def check_if_already_loaded_from_elsewhere(desc: LibDescriptor) -> LoadedDL | None:
     for dll_name in desc.windows_dlls:
         handle = kernel32.GetModuleHandleW(dll_name)
         if handle:
             abs_path = abs_path_for_dynamic_library(desc.name, handle)
-            if have_abs_path and desc.requires_add_dll_directory:
-                # This is a side-effect if the pathfinder loads the library via
-                # load_with_abs_path(). To make the side-effect more deterministic,
-                # activate it even if the library was already loaded from elsewhere.
+            if desc.requires_add_dll_directory:
+                # Match load_with_abs_path(): lazy component DLLs need the directory
+                # of the module that is actually loaded, regardless of how it arrived.
                 add_dll_directory(abs_path)
             return LoadedDL(abs_path, True, ctypes_handle_to_unsigned_int(handle), "was-already-loaded-from-elsewhere")
     return None
@@ -139,8 +148,7 @@ def load_with_system_search(desc: LibDescriptor) -> LoadedDL | None:
     Returns:
         A LoadedDL object if successful, None if the library cannot be loaded
     """
-    # Reverse tabulated names to achieve new -> old search order.
-    for dll_name in reversed(desc.windows_dlls):
+    for dll_name in desc.windows_dlls:
         handle = kernel32.LoadLibraryExW(dll_name, None, 0)
         if handle:
             abs_path = abs_path_for_dynamic_library(desc.name, handle)
@@ -170,7 +178,7 @@ def load_with_abs_path(desc: LibDescriptor, found_path: str, found_via: str | No
     handle = kernel32.LoadLibraryExW(found_path, None, flags)
 
     if not handle:
-        error_code = ctypes.GetLastError()  # type: ignore[attr-defined]
+        error_code = kernel32.GetLastError()
         raise RuntimeError(f"Failed to load DLL at {found_path}: Windows error {error_code}")
 
     return LoadedDL(found_path, False, ctypes_handle_to_unsigned_int(handle), found_via)
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py
index 95a71825793..2b0761be1a6 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/load_nvidia_dynamic_lib.py
@@ -34,6 +34,7 @@
     build_dynamic_lib_subprocess_command,
     parse_dynamic_lib_subprocess_payload,
 )
+from cuda.pathfinder._dynamic_libs.supported_nvidia_libs import ALL_AVAILABLE_LIBNAMES
 from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
 
 if TYPE_CHECKING:
@@ -42,9 +43,6 @@
 # All libnames recognized by load_nvidia_dynamic_lib, across all categories
 # (CTK, third-party, driver).
 _ALL_KNOWN_LIBNAMES: frozenset[str] = frozenset(LIB_DESCRIPTORS)
-_ALL_SUPPORTED_LIBNAMES: frozenset[str] = frozenset(
-    name for name, desc in LIB_DESCRIPTORS.items() if (desc.windows_dlls if IS_WINDOWS else desc.linux_sonames)
-)
 _PLATFORM_NAME = "Windows" if IS_WINDOWS else "Linux"
 _CANARY_PROBE_TIMEOUT_SECONDS = 10.0
 
@@ -62,7 +60,7 @@ def _load_driver_lib_no_cache(desc: LibDescriptor) -> LoadedDL:
     native loader mechanisms, so the full CTK search cascade (site-packages,
     conda, CUDA_PATH, canary) is unnecessary.
     """
-    loaded = LOADER.check_if_already_loaded_from_elsewhere(desc, False)
+    loaded = LOADER.check_if_already_loaded_from_elsewhere(desc)
     if loaded is not None:
         return loaded
     loaded = LOADER.load_with_system_search(desc)
@@ -176,9 +174,7 @@ def _load_lib_no_cache(libname: str) -> LoadedDL:
     find = run_find_steps(ctx, EARLY_FIND_STEPS)
 
     # Phase 2: Cross-cutting — already-loaded check and dependency loading.
-    # The already-loaded check on Windows uses the "have we found a path?"
-    # flag to decide whether to apply AddDllDirectory side-effects.
-    loaded = LOADER.check_if_already_loaded_from_elsewhere(desc, find is not None)
+    loaded = LOADER.check_if_already_loaded_from_elsewhere(desc)
     load_dependencies(desc, load_nvidia_dynamic_lib)
     if loaded is not None:
         return loaded
@@ -233,6 +229,15 @@ def load_nvidia_dynamic_lib(libname: str) -> LoadedDL:
         DynamicLibNotFoundError: If the library cannot be found or loaded.
         RuntimeError: If Python is not 64-bit.
 
+    Windows on ARM (WoA) Note:
+        On Windows, this API aims to load a dynamic library whose architecture
+        matches the Python interpreter architecture. For example, x64 Python
+        running on an Arm64 machine targets an x64 DLL, while native Arm64 Python
+        targets an Arm64 DLL. A library loaded into the Python process must be
+        compatible with that process. This differs from
+        ``find_nvidia_binary_utility``, which targets the native machine
+        architecture when selecting architecture-specific executables.
+
     Search order:
         0. **Already loaded in the current process**
 
@@ -268,12 +273,21 @@ def load_nvidia_dynamic_lib(libname: str) -> LoadedDL:
 
         4. **Environment variables**
 
-           - If set, use ``CUDA_PATH`` or ``CUDA_HOME`` (in that order).
-             On Windows, this is the typical way system-installed CTK DLLs are
-             located. Note that the NVIDIA CTK installer automatically
+           - First search library-specific roots declared by the descriptor,
+             such as ``CUDNN_PATH`` and ``NCCL_HOME``, using their
+             platform-specific product layouts. Then use ``CUDA_PATH`` or
+             ``CUDA_HOME`` (in that order).
+             On Windows, ``CUDA_PATH`` is the typical way system-installed CTK
+             DLLs are located. Note that the NVIDIA CTK installer automatically
              adds ``CUDA_PATH`` to the system-wide environment.
 
-        5. **CTK root canary probe (discoverable libs only)**
+        5. **Windows Program Files (configured libraries only)**
+
+           - Search descriptor-configured standalone installation roots, such
+             as versioned x64 cuDNN directories under ``ProgramFiles``, using
+             the general per-library anchor layout.
+
+        6. **CTK root canary probe (discoverable libs only)**
 
            - For selected libraries whose shared object doesn't reside on the
              standard linker path (currently ``nvvm``), attempt to derive CTK
@@ -291,8 +305,8 @@ def load_nvidia_dynamic_lib(libname: str) -> LoadedDL:
         0. Already loaded in the current process
         1. OS default mechanisms (``dlopen`` / ``LoadLibraryExW``)
 
-        The CTK-specific steps (site-packages, conda, ``CUDA_PATH``, canary
-        probe) are skipped entirely.
+        The non-driver steps (site-packages, conda, environment roots,
+        ``ProgramFiles``, and canary probe) are skipped entirely.
 
     Notes:
         The search is performed **per library**. There is currently no mechanism to
@@ -308,9 +322,9 @@ def load_nvidia_dynamic_lib(libname: str) -> LoadedDL:
         )
     if libname not in _ALL_KNOWN_LIBNAMES:
         raise DynamicLibUnknownError(f"Unknown library name: {libname!r}. Known names: {sorted(_ALL_KNOWN_LIBNAMES)}")
-    if libname not in _ALL_SUPPORTED_LIBNAMES:
+    if libname not in ALL_AVAILABLE_LIBNAMES:
         raise DynamicLibNotAvailableError(
             f"Library name {libname!r} is known but not available on {_PLATFORM_NAME}. "
-            f"Supported names on {_PLATFORM_NAME}: {sorted(_ALL_SUPPORTED_LIBNAMES)}"
+            f"Supported names on {_PLATFORM_NAME}: {sorted(ALL_AVAILABLE_LIBNAMES)}"
         )
     return _load_lib_no_cache(libname)
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/platform_loader.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/platform_loader.py
index 9b108a57acc..1d65f696f04 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/platform_loader.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/platform_loader.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 """Platform loader seam for OS-specific dynamic linking.
@@ -16,22 +16,22 @@
 
 from __future__ import annotations
 
+import sys
 from typing import Protocol
 
 from cuda.pathfinder._dynamic_libs.lib_descriptor import LibDescriptor
 from cuda.pathfinder._dynamic_libs.load_dl_common import LoadedDL
-from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
 
 
 class PlatformLoader(Protocol):
-    def check_if_already_loaded_from_elsewhere(self, desc: LibDescriptor, have_abs_path: bool) -> LoadedDL | None: ...
+    def check_if_already_loaded_from_elsewhere(self, desc: LibDescriptor) -> LoadedDL | None: ...
 
     def load_with_system_search(self, desc: LibDescriptor) -> LoadedDL | None: ...
 
     def load_with_abs_path(self, desc: LibDescriptor, found_path: str, found_via: str | None = None) -> LoadedDL: ...
 
 
-if IS_WINDOWS:
+if sys.platform == "win32":
     from cuda.pathfinder._dynamic_libs import load_dl_windows as _impl
 else:
     from cuda.pathfinder._dynamic_libs import load_dl_linux as _impl
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_platform.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_platform.py
index 37fd6eb1700..71a92b00924 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_platform.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_platform.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 """Platform abstraction for filesystem search steps.
@@ -10,77 +10,90 @@
 
 from __future__ import annotations
 
-import glob
 import os
 from collections.abc import Sequence
 from dataclasses import dataclass
+from pathlib import PurePath
 from typing import Protocol, cast
 
 from cuda.pathfinder._dynamic_libs.lib_descriptor import LibDescriptor
 from cuda.pathfinder._dynamic_libs.supported_nvidia_libs import is_suppressed_dll_file
 from cuda.pathfinder._utils.find_sub_dirs import find_sub_dirs_all_sitepackages
 from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
+from cuda.pathfinder._utils.windows_arch import windows_pe_matches_arch, windows_python_arch
 
 
 def _no_such_file_in_sub_dirs(
-    sub_dirs: Sequence[str], file_wild: str, error_messages: list[str], attachments: list[str]
+    sub_dirs: Sequence[str], file_description: str, error_messages: list[str], attachments: list[str]
 ) -> None:
-    error_messages.append(f"No such file: {file_wild}")
+    error_messages.append(f"No such file: {file_description}")
     for sub_dir in find_sub_dirs_all_sitepackages(sub_dirs):
         attachments.append(f'  listdir("{sub_dir}"):')
         for node in sorted(os.listdir(sub_dir)):
             attachments.append(f"    {node}")
 
 
+def _find_descriptor_so_under_dir(dirpath: str, desc: LibDescriptor) -> str | None:
+    for soname in desc.linux_sonames:
+        path = os.path.join(dirpath, soname)
+        if os.path.isfile(path):
+            return path
+    return None
+
+
 def _find_so_in_rel_dirs(
     rel_dirs: tuple[str, ...],
-    so_basename: str,
+    desc: LibDescriptor,
+    file_description: str,
     error_messages: list[str],
     attachments: list[str],
 ) -> str | None:
     sub_dirs_searched: list[tuple[str, ...]] = []
-    file_wild = so_basename + "*"
     for rel_dir in rel_dirs:
-        sub_dir = tuple(rel_dir.split(os.path.sep))
+        sub_dir = PurePath(rel_dir).parts
         for abs_dir in find_sub_dirs_all_sitepackages(sub_dir):
-            # Exact unversioned match first; fall back to versioned names because some
-            # distros only ship lib<name>.so.<major> (e.g. conda libcupti). Only one match
-            # is expected in practice. Sort in reverse so the newest-sorting name wins if
-            # multiple coexist, matching the newest-first bias elsewhere in pathfinder
-            # (see LinuxSearchPlatform.find_in_lib_dir and load_dl_linux._candidate_sonames).
-            # Issue #1732 tracks the deferred question of raising on true ambiguity.
-            so_name = os.path.join(abs_dir, so_basename)
-            if os.path.isfile(so_name):
-                return so_name
-            for so_name in sorted(glob.glob(os.path.join(abs_dir, file_wild)), reverse=True):
-                if os.path.isfile(so_name):
-                    return so_name
+            so_path = _find_descriptor_so_under_dir(abs_dir, desc)
+            if so_path is not None:
+                return so_path
         sub_dirs_searched.append(sub_dir)
     for sub_dir in sub_dirs_searched:
-        _no_such_file_in_sub_dirs(sub_dir, file_wild, error_messages, attachments)
+        _no_such_file_in_sub_dirs(sub_dir, file_description, error_messages, attachments)
     return None
 
 
-def _find_dll_under_dir(dirpath: str, file_wild: str) -> str | None:
-    for path in sorted(glob.glob(os.path.join(dirpath, file_wild))):
+def _find_descriptor_dll_under_dir(
+    dirpath: str,
+    desc: LibDescriptor,
+    target_arch: str | None = None,
+) -> str | None:
+    def candidate_is_usable(path: str) -> bool:
         if not os.path.isfile(path):
-            continue
-        if not is_suppressed_dll_file(os.path.basename(path)):
+            return False
+        if is_suppressed_dll_file(os.path.basename(path)):
+            return False
+        return target_arch is None or windows_pe_matches_arch(path, target_arch)
+
+    for dll_basename in desc.windows_dlls:
+        path = os.path.join(dirpath, dll_basename)
+        if candidate_is_usable(path):
             return path
     return None
 
 
 def _find_dll_in_rel_dirs(
     rel_dirs: tuple[str, ...],
+    desc: LibDescriptor,
+    target_arch: str,
     lib_searched_for: str,
     error_messages: list[str],
     attachments: list[str],
 ) -> str | None:
     sub_dirs_searched: list[tuple[str, ...]] = []
+    checked_arch = target_arch if desc.requires_windows_binary_arch_check else None
     for rel_dir in rel_dirs:
-        sub_dir = tuple(rel_dir.split(os.path.sep))
+        sub_dir = PurePath(rel_dir).parts
         for abs_dir in find_sub_dirs_all_sitepackages(sub_dir):
-            dll_name = _find_dll_under_dir(abs_dir, lib_searched_for)
+            dll_name = _find_descriptor_dll_under_dir(abs_dir, desc, checked_arch)
             if dll_name is not None:
                 return dll_name
         sub_dirs_searched.append(sub_dir)
@@ -90,7 +103,7 @@ def _find_dll_in_rel_dirs(
 
 
 class SearchPlatform(Protocol):
-    def lib_searched_for(self, libname: str) -> str: ...
+    def lib_searched_for(self, desc: LibDescriptor) -> str: ...
 
     def site_packages_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]: ...
 
@@ -98,10 +111,16 @@ def conda_anchor_point(self, conda_prefix: str) -> str: ...
 
     def anchor_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]: ...
 
+    def install_root_env_vars(self, desc: LibDescriptor) -> tuple[str, ...]: ...
+
+    def install_root_env_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]: ...
+
+    def program_files_root_globs(self, desc: LibDescriptor) -> tuple[str, ...]: ...
+
     def find_in_site_packages(
         self,
         rel_dirs: tuple[str, ...],
-        lib_searched_for: str,
+        desc: LibDescriptor,
         error_messages: list[str],
         attachments: list[str],
     ) -> str | None: ...
@@ -109,8 +128,7 @@ def find_in_site_packages(
     def find_in_lib_dir(
         self,
         lib_dir: str,
-        libname: str,
-        lib_searched_for: str,
+        desc: LibDescriptor,
         error_messages: list[str],
         attachments: list[str],
     ) -> str | None: ...
@@ -118,8 +136,8 @@ def find_in_lib_dir(
 
 @dataclass(frozen=True, slots=True)
 class LinuxSearchPlatform:
-    def lib_searched_for(self, libname: str) -> str:
-        return f"lib{libname}.so"
+    def lib_searched_for(self, desc: LibDescriptor) -> str:
+        return " or ".join(desc.linux_sonames)
 
     def site_packages_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]:
         return cast(tuple[str, ...], desc.site_packages_linux)
@@ -130,38 +148,35 @@ def conda_anchor_point(self, conda_prefix: str) -> str:
     def anchor_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]:
         return cast(tuple[str, ...], desc.anchor_rel_dirs_linux)
 
+    def install_root_env_vars(self, desc: LibDescriptor) -> tuple[str, ...]:
+        return cast(tuple[str, ...], desc.install_root_env_vars_linux)
+
+    def install_root_env_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]:
+        return cast(tuple[str, ...], desc.install_root_env_rel_dirs_linux)
+
+    def program_files_root_globs(self, _desc: LibDescriptor) -> tuple[str, ...]:
+        return ()
+
     def find_in_site_packages(
         self,
         rel_dirs: tuple[str, ...],
-        lib_searched_for: str,
+        desc: LibDescriptor,
         error_messages: list[str],
         attachments: list[str],
     ) -> str | None:
-        return _find_so_in_rel_dirs(rel_dirs, lib_searched_for, error_messages, attachments)
+        return _find_so_in_rel_dirs(rel_dirs, desc, self.lib_searched_for(desc), error_messages, attachments)
 
     def find_in_lib_dir(
         self,
         lib_dir: str,
-        _libname: str,
-        lib_searched_for: str,
+        desc: LibDescriptor,
         error_messages: list[str],
         attachments: list[str],
     ) -> str | None:
-        # Most libraries have both unversioned and versioned files/symlinks (exact match first)
-        so_name = os.path.join(lib_dir, lib_searched_for)
-        if os.path.isfile(so_name):
-            return so_name
-        # Some libraries only exist as versioned files (e.g., libcupti.so.13 in conda),
-        # so the glob fallback is needed
-        file_wild = lib_searched_for + "*"
-        # Only one match is expected, but to ensure deterministic behavior in unexpected
-        # situations, and to be internally consistent, we sort in reverse order with the
-        # intent to return the newest version first. Issue #1732 tracks the deferred
-        # question of raising on true ambiguity.
-        for so_name in sorted(glob.glob(os.path.join(lib_dir, file_wild)), reverse=True):
-            if os.path.isfile(so_name):
-                return so_name
-        error_messages.append(f"No such file: {file_wild}")
+        so_path = _find_descriptor_so_under_dir(lib_dir, desc)
+        if so_path is not None:
+            return so_path
+        error_messages.append(f"No such file: {self.lib_searched_for(desc)}")
         attachments.append(f'  listdir("{lib_dir}"):')
         if not os.path.isdir(lib_dir):
             attachments.append("    DIRECTORY DOES NOT EXIST")
@@ -173,40 +188,69 @@ def find_in_lib_dir(
 
 @dataclass(frozen=True, slots=True)
 class WindowsSearchPlatform:
-    def lib_searched_for(self, libname: str) -> str:
-        return f"{libname}*.dll"
+    target_arch: str
+
+    def lib_searched_for(self, desc: LibDescriptor) -> str:
+        return f"known {desc.name} DLL"
 
     def site_packages_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]:
-        return cast(tuple[str, ...], desc.site_packages_windows)
+        return cast(tuple[str, ...], desc.site_packages_windows.for_arch(self.target_arch))
 
     def conda_anchor_point(self, conda_prefix: str) -> str:
         return os.path.join(conda_prefix, "Library")
 
     def anchor_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]:
-        return cast(tuple[str, ...], desc.anchor_rel_dirs_windows)
+        return cast(tuple[str, ...], desc.anchor_rel_dirs_windows.for_arch(self.target_arch))
+
+    def install_root_env_vars(self, desc: LibDescriptor) -> tuple[str, ...]:
+        if self.target_arch not in desc.supported_windows_arch:
+            return ()
+        return cast(tuple[str, ...], desc.install_root_env_vars_windows)
+
+    def install_root_env_rel_dirs(self, desc: LibDescriptor) -> tuple[str, ...]:
+        if self.target_arch not in desc.supported_windows_arch:
+            return ()
+        return cast(tuple[str, ...], desc.install_root_env_rel_dirs_windows.for_arch(self.target_arch))
+
+    def program_files_root_globs(self, desc: LibDescriptor) -> tuple[str, ...]:
+        program_files = os.environ.get("PROGRAMW6432") or os.environ.get("PROGRAMFILES")
+        if not program_files:
+            return ()
+        rel_globs = desc.program_files_root_globs_windows.for_arch(self.target_arch)
+        return tuple(os.path.join(program_files, rel_glob) for rel_glob in rel_globs)
 
     def find_in_site_packages(
         self,
         rel_dirs: tuple[str, ...],
-        lib_searched_for: str,
+        desc: LibDescriptor,
         error_messages: list[str],
         attachments: list[str],
     ) -> str | None:
-        return _find_dll_in_rel_dirs(rel_dirs, lib_searched_for, error_messages, attachments)
+        return _find_dll_in_rel_dirs(
+            rel_dirs,
+            desc,
+            self.target_arch,
+            self.lib_searched_for(desc),
+            error_messages,
+            attachments,
+        )
 
     def find_in_lib_dir(
         self,
         lib_dir: str,
-        libname: str,
-        _lib_searched_for: str,
+        desc: LibDescriptor,
         error_messages: list[str],
         attachments: list[str],
     ) -> str | None:
-        file_wild = libname + "*.dll"
-        dll_name = _find_dll_under_dir(lib_dir, file_wild)
+        target_arch = self.target_arch if desc.requires_windows_binary_arch_check else None
+        dll_name = _find_descriptor_dll_under_dir(lib_dir, desc, target_arch)
         if dll_name is not None:
             return dll_name
-        error_messages.append(f"No such file: {file_wild}")
+        lib_searched_for = self.lib_searched_for(desc)
+        if target_arch is None:
+            error_messages.append(f"No such file: {lib_searched_for}")
+        else:
+            error_messages.append(f"No {target_arch}-compatible PE file: {lib_searched_for}")
         attachments.append(f'  listdir("{lib_dir}"):')
         if not os.path.isdir(lib_dir):
             attachments.append("    DIRECTORY DOES NOT EXIST")
@@ -216,4 +260,10 @@ def find_in_lib_dir(
         return None
 
 
-PLATFORM: SearchPlatform = WindowsSearchPlatform() if IS_WINDOWS else LinuxSearchPlatform()
+def _platform_for_current_system() -> SearchPlatform:
+    if IS_WINDOWS:
+        return WindowsSearchPlatform(target_arch=windows_python_arch())
+    return LinuxSearchPlatform()
+
+
+PLATFORM = _platform_for_current_system()
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_steps.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_steps.py
index 55d8a8aa674..80779f72ae2 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_steps.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/search_steps.py
@@ -21,7 +21,7 @@
 
 import glob
 import os
-from collections.abc import Callable
+from collections.abc import Callable, Iterator
 from dataclasses import dataclass, field
 from typing import NoReturn, cast
 
@@ -29,6 +29,7 @@
 from cuda.pathfinder._dynamic_libs.load_dl_common import DynamicLibNotFoundError
 from cuda.pathfinder._dynamic_libs.search_platform import PLATFORM, SearchPlatform
 from cuda.pathfinder._utils.env_vars import get_cuda_path_or_home
+from cuda.pathfinder._utils.path_sort import numeric_aware_path_sort_key
 
 # ---------------------------------------------------------------------------
 # Data types
@@ -58,7 +59,7 @@ def libname(self) -> str:
 
     @property
     def lib_searched_for(self) -> str:
-        return cast(str, self.platform.lib_searched_for(self.libname))
+        return cast(str, self.platform.lib_searched_for(self.desc))
 
     def raise_not_found(self) -> NoReturn:
         err = ", ".join(self.error_messages)
@@ -70,14 +71,26 @@ def raise_not_found(self) -> NoReturn:
 FindStep = Callable[[SearchContext], FindResult | None]
 
 
-def _find_lib_dir_using_anchor(desc: LibDescriptor, platform: SearchPlatform, anchor_point: str) -> str | None:
-    """Find the library directory under *anchor_point* using the descriptor's relative paths."""
-    rel_dirs = platform.anchor_rel_dirs(desc)
+def _iter_lib_dirs(root: str, rel_dirs: tuple[str, ...]) -> Iterator[str]:
+    """Yield existing library directories under *root* in descriptor order."""
     for rel_path in rel_dirs:
-        for dirname in sorted(glob.glob(os.path.join(anchor_point, rel_path))):
+        for dirname in sorted(glob.glob(os.path.join(root, rel_path))):
             if os.path.isdir(dirname):
-                return os.path.normpath(dirname)
-    return None
+                yield os.path.normpath(dirname)
+
+
+def _iter_lib_dirs_using_anchor(
+    desc: LibDescriptor,
+    platform: SearchPlatform,
+    anchor_point: str,
+) -> Iterator[str]:
+    """Yield existing library directories under *anchor_point* in descriptor order."""
+    yield from _iter_lib_dirs(anchor_point, platform.anchor_rel_dirs(desc))
+
+
+def _find_lib_dir_using_anchor(desc: LibDescriptor, platform: SearchPlatform, anchor_point: str) -> str | None:
+    """Find the first library directory under *anchor_point*."""
+    return next(_iter_lib_dirs_using_anchor(desc, platform, anchor_point), None)
 
 
 def _find_using_lib_dir(ctx: SearchContext, lib_dir: str | None) -> str | None:
@@ -88,14 +101,32 @@ def _find_using_lib_dir(ctx: SearchContext, lib_dir: str | None) -> str | None:
         str | None,
         ctx.platform.find_in_lib_dir(
             lib_dir,
-            ctx.libname,
-            ctx.lib_searched_for,
+            ctx.desc,
             ctx.error_messages,
             ctx.attachments,
         ),
     )
 
 
+def _find_under_root(
+    ctx: SearchContext,
+    root: str,
+    rel_dirs: tuple[str, ...],
+    found_via: str,
+) -> FindResult | None:
+    """Resolve *rel_dirs* under *root*, then find the requested library."""
+    for lib_dir in _iter_lib_dirs(root, rel_dirs):
+        abs_path = _find_using_lib_dir(ctx, lib_dir)
+        if abs_path is not None:
+            return FindResult(abs_path, found_via)
+    return None
+
+
+def _find_under_anchor_root(ctx: SearchContext, root: str, found_via: str) -> FindResult | None:
+    """Resolve the descriptor's general anchors under *root*."""
+    return _find_under_root(ctx, root, ctx.platform.anchor_rel_dirs(ctx.desc), found_via)
+
+
 def _derive_ctk_root_linux(resolved_lib_path: str) -> str | None:
     """Derive CTK root from Linux canary path.
 
@@ -121,13 +152,14 @@ def _derive_ctk_root_windows(resolved_lib_path: str) -> str | None:
 
     Supports:
     - ``$CTK_ROOT/bin/x64/foo.dll`` (CTK 13 style)
+    - ``$CTK_ROOT/bin/arm64/foo.dll`` (Windows on Arm CTK 13 style)
     - ``$CTK_ROOT/bin/foo.dll`` (CTK 12 style)
     """
     import ntpath
 
     lib_dir = ntpath.dirname(resolved_lib_path)
     basename = ntpath.basename(lib_dir).lower()
-    if basename == "x64":
+    if basename in ("x64", "arm64"):
         parent = ntpath.dirname(lib_dir)
         if ntpath.basename(parent).lower() == "bin":
             return ntpath.dirname(parent)
@@ -146,11 +178,7 @@ def derive_ctk_root(resolved_lib_path: str) -> str | None:
 
 def find_via_ctk_root(ctx: SearchContext, ctk_root: str) -> FindResult | None:
     """Find a library under a previously derived CTK root."""
-    lib_dir = _find_lib_dir_using_anchor(ctx.desc, ctx.platform, ctk_root)
-    abs_path = _find_using_lib_dir(ctx, lib_dir)
-    if abs_path is None:
-        return None
-    return FindResult(abs_path, "system-ctk-root")
+    return _find_under_anchor_root(ctx, ctk_root, "system-ctk-root")
 
 
 # ---------------------------------------------------------------------------
@@ -163,7 +191,12 @@ def find_in_site_packages(ctx: SearchContext) -> FindResult | None:
     rel_dirs = ctx.platform.site_packages_rel_dirs(ctx.desc)
     if not rel_dirs:
         return None
-    abs_path = ctx.platform.find_in_site_packages(rel_dirs, ctx.lib_searched_for, ctx.error_messages, ctx.attachments)
+    abs_path = ctx.platform.find_in_site_packages(
+        rel_dirs,
+        ctx.desc,
+        ctx.error_messages,
+        ctx.attachments,
+    )
     if abs_path is not None:
         return FindResult(abs_path, "site-packages")
     return None
@@ -175,10 +208,19 @@ def find_in_conda(ctx: SearchContext) -> FindResult | None:
     if not conda_prefix:
         return None
     anchor = ctx.platform.conda_anchor_point(conda_prefix)
-    lib_dir = _find_lib_dir_using_anchor(ctx.desc, ctx.platform, anchor)
-    abs_path = _find_using_lib_dir(ctx, lib_dir)
-    if abs_path is not None:
-        return FindResult(abs_path, "conda")
+    return _find_under_anchor_root(ctx, anchor, "conda")
+
+
+def find_in_install_root_env_vars(ctx: SearchContext) -> FindResult | None:
+    """Search installation roots named by descriptor-specific environment variables."""
+    rel_dirs = ctx.platform.install_root_env_rel_dirs(ctx.desc)
+    for env_var in ctx.platform.install_root_env_vars(ctx.desc):
+        root = os.environ.get(env_var)
+        if not root:
+            continue
+        result = _find_under_root(ctx, root, rel_dirs, env_var)
+        if result is not None:
+            return result
     return None
 
 
@@ -196,10 +238,18 @@ def find_in_cuda_path(ctx: SearchContext) -> FindResult | None:
     cuda_home = get_cuda_path_or_home()
     if cuda_home is None:
         return None
-    lib_dir = _find_lib_dir_using_anchor(ctx.desc, ctx.platform, cuda_home)
-    abs_path = _find_using_lib_dir(ctx, lib_dir)
-    if abs_path is not None:
-        return FindResult(abs_path, "CUDA_PATH")
+    return _find_under_anchor_root(ctx, cuda_home, "CUDA_PATH")
+
+
+def find_in_program_files_roots(ctx: SearchContext) -> FindResult | None:
+    """Search descriptor-configured installation roots under Program Files."""
+    for root_glob in ctx.platform.program_files_root_globs(ctx.desc):
+        for root in sorted(glob.glob(root_glob), key=numeric_aware_path_sort_key, reverse=True):
+            if not os.path.isdir(root):
+                continue
+            result = _find_under_anchor_root(ctx, os.path.normpath(root), "ProgramFiles")
+            if result is not None:
+                return result
     return None
 
 
@@ -211,7 +261,11 @@ def find_in_cuda_path(ctx: SearchContext) -> FindResult | None:
 EARLY_FIND_STEPS: tuple[FindStep, ...] = (find_in_site_packages, find_in_conda)
 
 #: Find steps that run after system search fails.
-LATE_FIND_STEPS: tuple[FindStep, ...] = (find_in_cuda_path,)
+LATE_FIND_STEPS: tuple[FindStep, ...] = (
+    find_in_install_root_env_vars,
+    find_in_cuda_path,
+    find_in_program_files_roots,
+)
 
 
 # ---------------------------------------------------------------------------
diff --git a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/supported_nvidia_libs.py b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/supported_nvidia_libs.py
index db06411c6d0..02951cba52e 100644
--- a/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/supported_nvidia_libs.py
+++ b/cuda_pathfinder/cuda/pathfinder/_dynamic_libs/supported_nvidia_libs.py
@@ -6,18 +6,30 @@
 The canonical data entry point is :mod:`descriptor_catalog`. This module keeps
 historical constant names for backward compatibility by deriving them from the
 catalog.
+
+The unsuffixed ``SUPPORTED_LIBNAMES_WINDOWS`` and
+``SITE_PACKAGES_LIBDIRS_WINDOWS*`` constants retain their historical x64
+meaning for compatibility, but are not recommended for new code. Use the
+explicit ``*_X64`` or ``*_ARM64`` projection instead. Never combine the two
+architecture projections.
 """
 
 from __future__ import annotations
 
 from cuda.pathfinder._dynamic_libs.descriptor_catalog import DESCRIPTOR_CATALOG
-from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
+from cuda.pathfinder._utils.platform_aware import IS_WINDOWS, IS_WINDOWS_ARM64, IS_WINDOWS_X64
 
 _CTK_DESCRIPTORS = tuple(desc for desc in DESCRIPTOR_CATALOG if desc.packaged_with == "ctk")
 _OTHER_DESCRIPTORS = tuple(desc for desc in DESCRIPTOR_CATALOG if desc.packaged_with == "other")
 _DRIVER_DESCRIPTORS = tuple(desc for desc in DESCRIPTOR_CATALOG if desc.packaged_with == "driver")
 _NON_CTK_DESCRIPTORS = _OTHER_DESCRIPTORS + _DRIVER_DESCRIPTORS
 
+
+def _legacy_least_preferred_first(names: tuple[str, ...]) -> tuple[str, ...]:
+    """Preserve the historical ordering of legacy filename projections."""
+    return tuple(reversed(names))
+
+
 SUPPORTED_LIBNAMES_COMMON = tuple(desc.name for desc in _CTK_DESCRIPTORS if desc.linux_sonames and desc.windows_dlls)
 SUPPORTED_LIBNAMES_LINUX_ONLY = tuple(
     desc.name for desc in _CTK_DESCRIPTORS if desc.linux_sonames and not desc.windows_dlls
@@ -26,22 +38,54 @@
     desc.name for desc in _CTK_DESCRIPTORS if desc.windows_dlls and not desc.linux_sonames
 )
 
+if not IS_WINDOWS:
+    ALL_AVAILABLE_LIBNAMES = frozenset(desc.name for desc in DESCRIPTOR_CATALOG if desc.linux_sonames)
+else:
+    assert IS_WINDOWS_X64 != IS_WINDOWS_ARM64
+    _current_windows_arch = "x64" if IS_WINDOWS_X64 else "arm64"
+    ALL_AVAILABLE_LIBNAMES = frozenset(
+        desc.name for desc in DESCRIPTOR_CATALOG if _current_windows_arch in desc.supported_windows_arch
+    )
+
 SUPPORTED_LIBNAMES_LINUX = SUPPORTED_LIBNAMES_COMMON + SUPPORTED_LIBNAMES_LINUX_ONLY
-SUPPORTED_LIBNAMES_WINDOWS = SUPPORTED_LIBNAMES_COMMON + SUPPORTED_LIBNAMES_WINDOWS_ONLY
+SUPPORTED_LIBNAMES_WINDOWS_X64 = tuple(desc.name for desc in _CTK_DESCRIPTORS if "x64" in desc.supported_windows_arch)
+SUPPORTED_LIBNAMES_WINDOWS_ARM64 = tuple(
+    desc.name for desc in _CTK_DESCRIPTORS if "arm64" in desc.supported_windows_arch
+)
+# Backward-compatible alias preserves the historical x64 meaning.
+SUPPORTED_LIBNAMES_WINDOWS = SUPPORTED_LIBNAMES_WINDOWS_X64
 SUPPORTED_LIBNAMES_ALL = SUPPORTED_LIBNAMES_COMMON + SUPPORTED_LIBNAMES_LINUX_ONLY + SUPPORTED_LIBNAMES_WINDOWS_ONLY
-SUPPORTED_LIBNAMES = SUPPORTED_LIBNAMES_WINDOWS if IS_WINDOWS else SUPPORTED_LIBNAMES_LINUX
+if not IS_WINDOWS:
+    SUPPORTED_LIBNAMES = SUPPORTED_LIBNAMES_LINUX
+elif IS_WINDOWS_X64:
+    SUPPORTED_LIBNAMES = SUPPORTED_LIBNAMES_WINDOWS_X64
+else:
+    assert IS_WINDOWS_ARM64
+    SUPPORTED_LIBNAMES = SUPPORTED_LIBNAMES_WINDOWS_ARM64
 
 DIRECT_DEPENDENCIES_CTK = {desc.name: desc.dependencies for desc in _CTK_DESCRIPTORS if desc.dependencies}
 DIRECT_DEPENDENCIES = {desc.name: desc.dependencies for desc in DESCRIPTOR_CATALOG if desc.dependencies}
 
-SUPPORTED_LINUX_SONAMES_CTK = {desc.name: desc.linux_sonames for desc in _CTK_DESCRIPTORS if desc.linux_sonames}
-SUPPORTED_LINUX_SONAMES_OTHER = {desc.name: desc.linux_sonames for desc in _OTHER_DESCRIPTORS if desc.linux_sonames}
-SUPPORTED_LINUX_SONAMES_DRIVER = {desc.name: desc.linux_sonames for desc in _DRIVER_DESCRIPTORS if desc.linux_sonames}
+SUPPORTED_LINUX_SONAMES_CTK = {
+    desc.name: _legacy_least_preferred_first(desc.linux_sonames) for desc in _CTK_DESCRIPTORS if desc.linux_sonames
+}
+SUPPORTED_LINUX_SONAMES_OTHER = {
+    desc.name: _legacy_least_preferred_first(desc.linux_sonames) for desc in _OTHER_DESCRIPTORS if desc.linux_sonames
+}
+SUPPORTED_LINUX_SONAMES_DRIVER = {
+    desc.name: _legacy_least_preferred_first(desc.linux_sonames) for desc in _DRIVER_DESCRIPTORS if desc.linux_sonames
+}
 SUPPORTED_LINUX_SONAMES = SUPPORTED_LINUX_SONAMES_CTK | SUPPORTED_LINUX_SONAMES_OTHER | SUPPORTED_LINUX_SONAMES_DRIVER
 
-SUPPORTED_WINDOWS_DLLS_CTK = {desc.name: desc.windows_dlls for desc in _CTK_DESCRIPTORS if desc.windows_dlls}
-SUPPORTED_WINDOWS_DLLS_OTHER = {desc.name: desc.windows_dlls for desc in _OTHER_DESCRIPTORS if desc.windows_dlls}
-SUPPORTED_WINDOWS_DLLS_DRIVER = {desc.name: desc.windows_dlls for desc in _DRIVER_DESCRIPTORS if desc.windows_dlls}
+SUPPORTED_WINDOWS_DLLS_CTK = {
+    desc.name: _legacy_least_preferred_first(desc.windows_dlls) for desc in _CTK_DESCRIPTORS if desc.windows_dlls
+}
+SUPPORTED_WINDOWS_DLLS_OTHER = {
+    desc.name: _legacy_least_preferred_first(desc.windows_dlls) for desc in _OTHER_DESCRIPTORS if desc.windows_dlls
+}
+SUPPORTED_WINDOWS_DLLS_DRIVER = {
+    desc.name: _legacy_least_preferred_first(desc.windows_dlls) for desc in _DRIVER_DESCRIPTORS if desc.windows_dlls
+}
 SUPPORTED_WINDOWS_DLLS = SUPPORTED_WINDOWS_DLLS_CTK | SUPPORTED_WINDOWS_DLLS_OTHER | SUPPORTED_WINDOWS_DLLS_DRIVER
 
 LIBNAMES_REQUIRING_OS_ADD_DLL_DIRECTORY = tuple(
@@ -51,7 +95,6 @@
     desc.name for desc in DESCRIPTOR_CATALOG if desc.requires_rtld_deepbind and desc.linux_sonames
 )
 
-# Based on output of toolshed/make_site_packages_libdirs_linux.py
 SITE_PACKAGES_LIBDIRS_LINUX_CTK = {
     desc.name: desc.site_packages_linux for desc in _CTK_DESCRIPTORS if desc.site_packages_linux
 }
@@ -60,13 +103,29 @@
 }
 SITE_PACKAGES_LIBDIRS_LINUX = SITE_PACKAGES_LIBDIRS_LINUX_CTK | SITE_PACKAGES_LIBDIRS_LINUX_OTHER
 
-SITE_PACKAGES_LIBDIRS_WINDOWS_CTK = {
-    desc.name: desc.site_packages_windows for desc in _CTK_DESCRIPTORS if desc.site_packages_windows
+# Architecture-specific Windows projections. Keep these separate: combining
+# them would make the table unsafe to consume for either process ABI.
+SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_X64 = {
+    desc.name: desc.site_packages_windows.x64 for desc in _CTK_DESCRIPTORS if desc.site_packages_windows.x64
 }
-SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER = {
-    desc.name: desc.site_packages_windows for desc in _NON_CTK_DESCRIPTORS if desc.site_packages_windows
+SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_ARM64 = {
+    desc.name: desc.site_packages_windows.arm64 for desc in _CTK_DESCRIPTORS if desc.site_packages_windows.arm64
 }
-SITE_PACKAGES_LIBDIRS_WINDOWS = SITE_PACKAGES_LIBDIRS_WINDOWS_CTK | SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER
+SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER_X64 = {
+    desc.name: desc.site_packages_windows.x64 for desc in _NON_CTK_DESCRIPTORS if desc.site_packages_windows.x64
+}
+SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER_ARM64 = {
+    desc.name: desc.site_packages_windows.arm64 for desc in _NON_CTK_DESCRIPTORS if desc.site_packages_windows.arm64
+}
+SITE_PACKAGES_LIBDIRS_WINDOWS_X64 = SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_X64 | SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER_X64
+SITE_PACKAGES_LIBDIRS_WINDOWS_ARM64 = (
+    SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_ARM64 | SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER_ARM64
+)
+
+# Backward-compatible aliases preserve the historical x64 meaning.
+SITE_PACKAGES_LIBDIRS_WINDOWS_CTK = SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_X64
+SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER = SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER_X64
+SITE_PACKAGES_LIBDIRS_WINDOWS = SITE_PACKAGES_LIBDIRS_WINDOWS_X64
 
 
 def is_suppressed_dll_file(path_basename: str) -> bool:
diff --git a/cuda_pathfinder/cuda/pathfinder/_headers/find_nvidia_headers.py b/cuda_pathfinder/cuda/pathfinder/_headers/find_nvidia_headers.py
index f5f56817141..86a86b2999c 100644
--- a/cuda_pathfinder/cuda/pathfinder/_headers/find_nvidia_headers.py
+++ b/cuda_pathfinder/cuda/pathfinder/_headers/find_nvidia_headers.py
@@ -18,10 +18,12 @@
     HEADER_DESCRIPTORS,
     platform_include_subdirs,
     resolve_conda_anchor,
+    system_install_dir_patterns,
 )
 from cuda.pathfinder._utils.ctk_root_canary import CTK_ROOT_CANARY_ANCHOR_LIBNAMES
 from cuda.pathfinder._utils.env_vars import get_cuda_path_or_home
 from cuda.pathfinder._utils.find_sub_dirs import find_sub_dirs_all_sitepackages
+from cuda.pathfinder._utils.path_sort import numeric_aware_path_sort_key
 
 if TYPE_CHECKING:
     from cuda.pathfinder._headers.header_descriptor import HeaderDescriptor
@@ -101,6 +103,18 @@ def find_in_conda(desc: HeaderDescriptor) -> LocatedHeaderDir | None:
     return None
 
 
+def find_in_product_roots(desc: HeaderDescriptor) -> LocatedHeaderDir | None:
+    """Search roots supplied through product-specific environment variables."""
+    for env_var in desc.product_root_env_vars:
+        root = os.environ.get(env_var)
+        if not root:
+            continue
+        result = _locate_in_anchor_layout(desc, root)
+        if result is not None:
+            return LocatedHeaderDir(abs_path=result, found_via=env_var)
+    return None
+
+
 def find_in_cuda_path(desc: HeaderDescriptor) -> LocatedHeaderDir | None:
     """Search ``$CUDA_PATH`` / ``$CUDA_HOME``."""
     cuda_home = get_cuda_path_or_home()
@@ -136,8 +150,8 @@ def find_via_ctk_root_canary(desc: HeaderDescriptor) -> LocatedHeaderDir | None:
 
 def find_in_system_install_dirs(desc: HeaderDescriptor) -> LocatedHeaderDir | None:
     """Search system install directories (glob patterns)."""
-    for pattern in desc.system_install_dirs:
-        for hdr_dir in sorted(glob.glob(pattern), reverse=True):
+    for pattern in system_install_dir_patterns(desc):
+        for hdr_dir in sorted(glob.glob(pattern), key=numeric_aware_path_sort_key, reverse=True):
             if _joined_isfile(hdr_dir, desc.header_basename):
                 return LocatedHeaderDir(abs_path=hdr_dir, found_via="supported_install_dir")
     return None
@@ -151,6 +165,7 @@ def find_in_system_install_dirs(desc: HeaderDescriptor) -> LocatedHeaderDir | No
 FIND_STEPS: tuple[HeaderFindStep, ...] = (
     find_in_site_packages,
     find_in_conda,
+    find_in_product_roots,
     find_in_cuda_path,
     find_via_ctk_root_canary,
     find_in_system_install_dirs,
@@ -190,10 +205,11 @@ def locate_nvidia_header_directory(libname: str) -> LocatedHeaderDir | None:
     Search order:
         1. **NVIDIA Python wheels** — site-packages directories from the descriptor.
         2. **Conda environments** — platform-specific conda include layouts.
-        3. **CUDA Toolkit environment variables** — ``CUDA_PATH`` / ``CUDA_HOME``.
-        4. **CTK root canary probe** — subprocess canary (descriptors with
+        3. **Product environment variables** — for example, ``CUDNN_PATH``.
+        4. **CUDA Toolkit environment variables** — ``CUDA_PATH`` / ``CUDA_HOME``.
+        5. **CTK root canary probe** — subprocess canary (descriptors with
            ``use_ctk_root_canary=True`` only).
-        5. **System install directories** — glob patterns from the descriptor.
+        6. **System install directories** — glob patterns from the descriptor.
     """
     desc = HEADER_DESCRIPTORS.get(libname)
     if desc is None:
@@ -218,10 +234,11 @@ def find_nvidia_header_directory(libname: str) -> str | None:
     Search order:
         1. **NVIDIA Python wheels** — site-packages directories from the descriptor.
         2. **Conda environments** — platform-specific conda include layouts.
-        3. **CUDA Toolkit environment variables** — ``CUDA_PATH`` / ``CUDA_HOME``.
-        4. **CTK root canary probe** — subprocess canary (descriptors with
+        3. **Product environment variables** — for example, ``CUDNN_PATH``.
+        4. **CUDA Toolkit environment variables** — ``CUDA_PATH`` / ``CUDA_HOME``.
+        5. **CTK root canary probe** — subprocess canary (descriptors with
            ``use_ctk_root_canary=True`` only).
-        5. **System install directories** — glob patterns from the descriptor.
+        6. **System install directories** — glob patterns from the descriptor.
     """
     found = locate_nvidia_header_directory(libname)
     return found.abs_path if found else None
diff --git a/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor.py b/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor.py
index 609dcab7184..3b108f618a5 100644
--- a/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor.py
+++ b/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor.py
@@ -12,6 +12,7 @@
 
 import glob
 import os
+import sysconfig
 from typing import TypeAlias, cast
 
 from cuda.pathfinder._headers.header_descriptor_catalog import (
@@ -37,6 +38,20 @@ def platform_include_subdirs(desc: HeaderDescriptor) -> tuple[str, ...]:
     return cast(tuple[str, ...], desc.include_subdirs)
 
 
+def system_install_dir_patterns(desc: HeaderDescriptor) -> tuple[str, ...]:
+    """Return platform-aware, expanded system include-directory patterns."""
+    patterns: list[str] = []
+    if IS_WINDOWS:
+        patterns.extend(os.path.expandvars(pattern) for pattern in desc.system_install_dirs_windows)
+        return tuple(patterns)
+    if desc.use_linux_multiarch_include_dir:
+        multiarch = sysconfig.get_config_var("MULTIARCH")
+        if isinstance(multiarch, str) and multiarch:
+            patterns.append(os.path.join("/usr/include", multiarch))
+    patterns.extend(os.path.expandvars(pattern) for pattern in desc.system_install_dirs)
+    return tuple(patterns)
+
+
 def resolve_conda_anchor(desc: HeaderDescriptor, conda_prefix: str) -> str | None:
     """Resolve the conda anchor point for header search on the current platform.
 
diff --git a/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor_catalog.py b/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor_catalog.py
index b364e224e7e..66570bd264d 100644
--- a/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor_catalog.py
+++ b/cuda_pathfinder/cuda/pathfinder/_headers/header_descriptor_catalog.py
@@ -13,6 +13,8 @@
 
 @dataclass(frozen=True, slots=True)
 class HeaderDescriptorSpec:
+    """Header metadata with ordered alternatives searched first-to-last."""
+
     name: str
     packaged_with: HeaderPackagedWith
     header_basename: str
@@ -21,12 +23,18 @@ class HeaderDescriptorSpec:
     available_on_windows: bool = True
     # Relative path(s) from anchor point to the include directory.
     anchor_include_rel_dirs: tuple[str, ...] = ("include",)
+    # Product-specific environment variables whose values are anchor points.
+    product_root_env_vars: tuple[str, ...] = ()
     # Subdirectories within the include dir to check before the include dir itself.
     include_subdirs: tuple[str, ...] = ()
     # Windows-only additional subdirectories within the include dir.
     include_subdirs_windows: tuple[str, ...] = ()
-    # System install directories (glob patterns).
+    # Linux system install directories (glob patterns; environment variables are expanded).
     system_install_dirs: tuple[str, ...] = ()
+    # Windows system install directories (glob patterns; environment variables are expanded).
+    system_install_dirs_windows: tuple[str, ...] = ()
+    # Whether to search /usr/include/<sysconfig MULTIARCH> before system_install_dirs.
+    use_linux_multiarch_include_dir: bool = False
     # Whether to use targets/<arch>/include layout for conda on Linux.
     conda_targets_layout: bool = True
     # Whether to attempt CTK-root canary probing (spawns a subprocess).
@@ -150,6 +158,21 @@ class HeaderDescriptorSpec:
     # -----------------------------------------------------------------------
     # Third-party / separately packaged headers
     # -----------------------------------------------------------------------
+    HeaderDescriptorSpec(
+        name="cudnn",
+        packaged_with="other",
+        header_basename="cudnn.h",
+        site_packages_dirs=("nvidia/cudnn/include",),
+        product_root_env_vars=("CUDNN_PATH",),
+        system_install_dirs=(
+            "/usr/include",
+            "/usr/local/include",
+        ),
+        system_install_dirs_windows=("${ProgramFiles}/NVIDIA/CUDNN/v9.*/include",),
+        use_linux_multiarch_include_dir=True,
+        conda_targets_layout=False,
+        use_ctk_root_canary=False,
+    ),
     HeaderDescriptorSpec(
         name="cusolverMp",
         packaged_with="other",
@@ -244,6 +267,18 @@ class HeaderDescriptorSpec:
         conda_targets_layout=False,
         use_ctk_root_canary=False,
     ),
+    HeaderDescriptorSpec(
+        name="nccl",
+        packaged_with="other",
+        header_basename="nccl.h",
+        site_packages_dirs=("nvidia/nccl/include",),
+        available_on_windows=False,
+        anchor_include_rel_dirs=("include", "build/include"),
+        product_root_env_vars=("NCCL_HOME",),
+        system_install_dirs=("/usr/include", "/usr/local/include"),
+        conda_targets_layout=False,
+        use_ctk_root_canary=False,
+    ),
     HeaderDescriptorSpec(
         name="nvshmem",
         packaged_with="other",
diff --git a/cuda_pathfinder/cuda/pathfinder/_headers/supported_nvidia_headers.py b/cuda_pathfinder/cuda/pathfinder/_headers/supported_nvidia_headers.py
index c7b40834e67..34736baad8d 100644
--- a/cuda_pathfinder/cuda/pathfinder/_headers/supported_nvidia_headers.py
+++ b/cuda_pathfinder/cuda/pathfinder/_headers/supported_nvidia_headers.py
@@ -12,6 +12,7 @@
 
 from typing import Final
 
+from cuda.pathfinder._headers.header_descriptor import system_install_dir_patterns
 from cuda.pathfinder._headers.header_descriptor_catalog import HEADER_DESCRIPTOR_CATALOG
 from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
 
@@ -77,5 +78,5 @@
 }
 
 SUPPORTED_INSTALL_DIRS_NON_CTK: Final[dict[str, tuple[str, ...]]] = {
-    desc.name: desc.system_install_dirs for desc in _NON_CTK_DESCRIPTORS if desc.system_install_dirs
+    desc.name: patterns for desc in _NON_CTK_DESCRIPTORS if (patterns := system_install_dir_patterns(desc))
 }
diff --git a/cuda_pathfinder/cuda/pathfinder/_static_libs/find_bitcode_lib.py b/cuda_pathfinder/cuda/pathfinder/_static_libs/find_bitcode_lib.py
index ac038aadfe7..fd9f3cdfe55 100644
--- a/cuda_pathfinder/cuda/pathfinder/_static_libs/find_bitcode_lib.py
+++ b/cuda_pathfinder/cuda/pathfinder/_static_libs/find_bitcode_lib.py
@@ -4,6 +4,7 @@
 import functools
 import os
 from dataclasses import dataclass
+from pathlib import Path
 from typing import NoReturn, TypedDict
 
 from cuda.pathfinder._utils.env_vars import get_cuda_path_or_home
@@ -26,6 +27,8 @@ class LocatedBitcodeLib:
 
 
 class _BitcodeLibInfo(TypedDict):
+    """Bitcode-library metadata with ordered alternatives searched first-to-last."""
+
     filename: str
     rel_path: str
     site_packages_dirs: tuple[str, ...]
@@ -35,7 +38,7 @@ class _BitcodeLibInfo(TypedDict):
 _SUPPORTED_BITCODE_LIBS_INFO: dict[str, _BitcodeLibInfo] = {
     "device": {
         "filename": "libdevice.10.bc",
-        "rel_path": os.path.join("nvvm", "libdevice"),
+        "rel_path": "nvvm/libdevice",
         "site_packages_dirs": (
             "nvidia/cu13/nvvm/libdevice",
             "nvidia/cuda_nvcc/nvvm/libdevice",
@@ -64,14 +67,14 @@ class _BitcodeLibInfo(TypedDict):
 )
 
 
-def _no_such_file_in_dir(dir_path: str, filename: str, error_messages: list[str], attachments: list[str]) -> None:
-    error_messages.append(f"No such file: {os.path.join(dir_path, filename)}")
-    if os.path.isdir(dir_path):
-        attachments.append(f'  listdir("{dir_path}"):')
-        for node in sorted(os.listdir(dir_path)):
+def _no_such_file_in_dir(directory: Path, filename: str, error_messages: list[str], attachments: list[str]) -> None:
+    error_messages.append(f"No such file: {directory / filename}")
+    if directory.is_dir():
+        attachments.append(f'  listdir("{directory}"):')
+        for node in sorted(node_path.name for node_path in directory.iterdir()):
             attachments.append(f"    {node}")
     else:
-        attachments.append(f'  Directory does not exist: "{dir_path}"')
+        attachments.append(f'  Directory does not exist: "{directory}"')
 
 
 class _FindBitcodeLib:
@@ -86,38 +89,39 @@ def __init__(self, name: str) -> None:
         self.error_messages: list[str] = []
         self.attachments: list[str] = []
 
-    def try_site_packages(self) -> str | None:
+    def try_site_packages(self) -> Path | None:
         for rel_dir in self.site_packages_dirs:
             sub_dir = tuple(rel_dir.split("/"))
             for abs_dir in find_sub_dirs_all_sitepackages(sub_dir):
-                file_path = os.path.join(abs_dir, self.filename)
-                if os.path.isfile(file_path):
+                file_path = Path(abs_dir, self.filename)
+                if file_path.is_file():
                     return file_path
         return None
 
-    def try_with_conda_prefix(self) -> str | None:
+    def try_with_conda_prefix(self) -> Path | None:
         conda_prefix = os.environ.get("CONDA_PREFIX")
         if not conda_prefix:
             return None
 
-        anchor = os.path.join(conda_prefix, "Library") if IS_WINDOWS else conda_prefix
-        file_path = os.path.join(anchor, self.rel_path, self.filename)
-        if os.path.isfile(file_path):
+        anchor = Path(conda_prefix, "Library") if IS_WINDOWS else Path(conda_prefix)
+        file_path = anchor / self.rel_path / self.filename
+        if file_path.is_file():
             return file_path
         return None
 
-    def try_with_cuda_home(self) -> str | None:
+    def try_with_cuda_home(self) -> Path | None:
         cuda_home = get_cuda_path_or_home()
         if cuda_home is None:
             self.error_messages.append("CUDA_HOME/CUDA_PATH not set")
             return None
 
-        file_path = os.path.join(cuda_home, self.rel_path, self.filename)
-        if os.path.isfile(file_path):
+        anchor = Path(cuda_home)
+        file_path = anchor / self.rel_path / self.filename
+        if file_path.is_file():
             return file_path
 
         _no_such_file_in_dir(
-            os.path.join(cuda_home, self.rel_path),
+            anchor / self.rel_path,
             self.filename,
             self.error_messages,
             self.attachments,
@@ -143,7 +147,7 @@ def locate_bitcode_lib(name: str) -> LocatedBitcodeLib:
     if abs_path is not None:
         return LocatedBitcodeLib(
             name=name,
-            abs_path=abs_path,
+            abs_path=str(abs_path),
             filename=finder.filename,
             found_via="site-packages",
         )
@@ -152,7 +156,7 @@ def locate_bitcode_lib(name: str) -> LocatedBitcodeLib:
     if abs_path is not None:
         return LocatedBitcodeLib(
             name=name,
-            abs_path=abs_path,
+            abs_path=str(abs_path),
             filename=finder.filename,
             found_via="conda",
         )
@@ -161,7 +165,7 @@ def locate_bitcode_lib(name: str) -> LocatedBitcodeLib:
     if abs_path is not None:
         return LocatedBitcodeLib(
             name=name,
-            abs_path=abs_path,
+            abs_path=str(abs_path),
             filename=finder.filename,
             found_via="CUDA_PATH",
         )
diff --git a/cuda_pathfinder/cuda/pathfinder/_static_libs/find_static_lib.py b/cuda_pathfinder/cuda/pathfinder/_static_libs/find_static_lib.py
index 804b1c04be7..f0f1c85f538 100644
--- a/cuda_pathfinder/cuda/pathfinder/_static_libs/find_static_lib.py
+++ b/cuda_pathfinder/cuda/pathfinder/_static_libs/find_static_lib.py
@@ -4,11 +4,13 @@
 import functools
 import os
 from dataclasses import dataclass
+from pathlib import Path
 from typing import NoReturn, TypedDict
 
 from cuda.pathfinder._utils.env_vars import get_cuda_path_or_home
 from cuda.pathfinder._utils.find_sub_dirs import find_sub_dirs_all_sitepackages
 from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
+from cuda.pathfinder._utils.windows_arch import windows_python_arch
 
 
 class StaticLibNotFoundError(RuntimeError):
@@ -26,36 +28,49 @@ class LocatedStaticLib:
 
 
 class _StaticLibInfo(TypedDict):
+    """Static-library metadata with ordered alternatives searched first-to-last."""
+
     filename: str
     ctk_rel_paths: tuple[str, ...]
     conda_rel_paths: tuple[str, ...]
     site_packages_dirs: tuple[str, ...]
 
 
+def _cudadevrt_info() -> _StaticLibInfo:
+    if not IS_WINDOWS:
+        return {
+            "filename": "libcudadevrt.a",
+            "ctk_rel_paths": ("lib64", "lib"),
+            "conda_rel_paths": ("lib",),
+            "site_packages_dirs": ("nvidia/cu13/lib", "nvidia/cuda_runtime/lib"),
+        }
+
+    arch_dir = windows_python_arch()
+    component_wheel_dirs = ("nvidia/cuda_runtime/lib/x64",) if arch_dir == "x64" else ()
+    conda_fallback_dirs = ("lib",) if arch_dir == "x64" else ()
+    return {
+        "filename": "cudadevrt.lib",
+        "ctk_rel_paths": (str(Path("lib", arch_dir)),),
+        "conda_rel_paths": (str(Path("lib", arch_dir)), *conda_fallback_dirs),
+        "site_packages_dirs": (f"nvidia/cu13/lib/{arch_dir}", *component_wheel_dirs),
+    }
+
+
 _SUPPORTED_STATIC_LIBS_INFO: dict[str, _StaticLibInfo] = {
-    "cudadevrt": {
-        "filename": "cudadevrt.lib" if IS_WINDOWS else "libcudadevrt.a",
-        "ctk_rel_paths": (os.path.join("lib", "x64"),) if IS_WINDOWS else ("lib64", "lib"),
-        "conda_rel_paths": ((os.path.join("lib", "x64"), "lib") if IS_WINDOWS else ("lib",)),
-        "site_packages_dirs": (
-            ("nvidia/cu13/lib/x64", "nvidia/cuda_runtime/lib/x64")
-            if IS_WINDOWS
-            else ("nvidia/cu13/lib", "nvidia/cuda_runtime/lib")
-        ),
-    },
+    "cudadevrt": _cudadevrt_info(),
 }
 
 SUPPORTED_STATIC_LIBS: tuple[str, ...] = tuple(sorted(_SUPPORTED_STATIC_LIBS_INFO.keys()))
 
 
-def _no_such_file_in_dir(dir_path: str, filename: str, error_messages: list[str], attachments: list[str]) -> None:
-    error_messages.append(f"No such file: {os.path.join(dir_path, filename)}")
-    if os.path.isdir(dir_path):
-        attachments.append(f'  listdir("{dir_path}"):')
-        for node in sorted(os.listdir(dir_path)):
+def _no_such_file_in_dir(directory: Path, filename: str, error_messages: list[str], attachments: list[str]) -> None:
+    error_messages.append(f"No such file: {directory / filename}")
+    if directory.is_dir():
+        attachments.append(f'  listdir("{directory}"):')
+        for node in sorted(node_path.name for node_path in directory.iterdir()):
             attachments.append(f"    {node}")
     else:
-        attachments.append(f'  Directory does not exist: "{dir_path}"')
+        attachments.append(f'  Directory does not exist: "{directory}"')
 
 
 class _FindStaticLib:
@@ -71,40 +86,41 @@ def __init__(self, name: str) -> None:
         self.error_messages: list[str] = []
         self.attachments: list[str] = []
 
-    def try_site_packages(self) -> str | None:
+    def try_site_packages(self) -> Path | None:
         for rel_dir in self.site_packages_dirs:
             sub_dir = tuple(rel_dir.split("/"))
             for abs_dir in find_sub_dirs_all_sitepackages(sub_dir):
-                file_path = os.path.join(abs_dir, self.filename)
-                if os.path.isfile(file_path):
+                file_path = Path(abs_dir, self.filename)
+                if file_path.is_file():
                     return file_path
         return None
 
-    def try_with_conda_prefix(self) -> str | None:
+    def try_with_conda_prefix(self) -> Path | None:
         conda_prefix = os.environ.get("CONDA_PREFIX")
         if not conda_prefix:
             return None
 
-        anchor = os.path.join(conda_prefix, "Library") if IS_WINDOWS else conda_prefix
+        anchor = Path(conda_prefix, "Library") if IS_WINDOWS else Path(conda_prefix)
         for rel_path in self.conda_rel_paths:
-            file_path = os.path.join(anchor, rel_path, self.filename)
-            if os.path.isfile(file_path):
+            file_path = anchor / rel_path / self.filename
+            if file_path.is_file():
                 return file_path
         return None
 
-    def try_with_cuda_home(self) -> str | None:
+    def try_with_cuda_home(self) -> Path | None:
         cuda_home = get_cuda_path_or_home()
         if cuda_home is None:
             self.error_messages.append("CUDA_HOME/CUDA_PATH not set")
             return None
 
+        anchor = Path(cuda_home)
         for rel_path in self.ctk_rel_paths:
-            file_path = os.path.join(cuda_home, rel_path, self.filename)
-            if os.path.isfile(file_path):
+            file_path = anchor / rel_path / self.filename
+            if file_path.is_file():
                 return file_path
 
         _no_such_file_in_dir(
-            os.path.join(cuda_home, self.ctk_rel_paths[0]),
+            anchor / self.ctk_rel_paths[0],
             self.filename,
             self.error_messages,
             self.attachments,
@@ -130,7 +146,7 @@ def locate_static_lib(name: str) -> LocatedStaticLib:
     if abs_path is not None:
         return LocatedStaticLib(
             name=name,
-            abs_path=abs_path,
+            abs_path=str(abs_path),
             filename=finder.filename,
             found_via="site-packages",
         )
@@ -139,7 +155,7 @@ def locate_static_lib(name: str) -> LocatedStaticLib:
     if abs_path is not None:
         return LocatedStaticLib(
             name=name,
-            abs_path=abs_path,
+            abs_path=str(abs_path),
             filename=finder.filename,
             found_via="conda",
         )
@@ -148,7 +164,7 @@ def locate_static_lib(name: str) -> LocatedStaticLib:
     if abs_path is not None:
         return LocatedStaticLib(
             name=name,
-            abs_path=abs_path,
+            abs_path=str(abs_path),
             filename=finder.filename,
             found_via="CUDA_PATH",
         )
@@ -163,5 +179,13 @@ def find_static_lib(name: str) -> str:
     Raises:
         ValueError: If ``name`` is not a supported static library.
         StaticLibNotFoundError: If the static library cannot be found.
+
+    Windows on ARM (WoA) Note:
+        On Windows, this API aims to return the path to a static library whose
+        architecture matches the Python interpreter architecture. For example,
+        x64 Python running on an Arm64 machine targets the x64 library, while
+        native Arm64 Python targets the Arm64 library. This differs from
+        ``find_nvidia_binary_utility``, which targets the native machine
+        architecture when selecting architecture-specific executables.
     """
     return locate_static_lib(name).abs_path
diff --git a/cuda_pathfinder/cuda/pathfinder/_utils/driver_info.py b/cuda_pathfinder/cuda/pathfinder/_utils/driver_info.py
index a5d4d167d33..d07c4b861d3 100644
--- a/cuda_pathfinder/cuda/pathfinder/_utils/driver_info.py
+++ b/cuda_pathfinder/cuda/pathfinder/_utils/driver_info.py
@@ -5,13 +5,13 @@
 
 import ctypes
 import functools
+import sys
 from collections.abc import Callable
 from dataclasses import dataclass
 
 from cuda.pathfinder._dynamic_libs.load_nvidia_dynamic_lib import (
     load_nvidia_dynamic_lib as _load_nvidia_dynamic_lib,
 )
-from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
 
 
 class QueryDriverCudaVersionError(RuntimeError):
@@ -60,16 +60,16 @@ def query_driver_cuda_version() -> DriverCudaVersion:
         raise QueryDriverCudaVersionError("Failed to query the CUDA driver version.") from exc
 
 
+if sys.platform == "win32":
+    _DRIVER_LIB_LOADER: Callable[[str], ctypes.CDLL] = ctypes.WinDLL
+else:
+    _DRIVER_LIB_LOADER = ctypes.CDLL
+
+
 def _query_driver_cuda_version_int() -> int:
     """Return the encoded CUDA driver version from ``cuDriverGetVersion()``."""
     loaded_cuda = _load_nvidia_dynamic_lib("cuda")
-    if IS_WINDOWS:
-        # `ctypes.WinDLL` exists on Windows at runtime. The ignore is only for
-        # Linux mypy runs, where the platform stubs do not define that attribute.
-        loader_cls: Callable[[str], ctypes.CDLL] = ctypes.WinDLL  # type: ignore[attr-defined]
-    else:
-        loader_cls = ctypes.CDLL
-    driver_lib = loader_cls(loaded_cuda.abs_path)
+    driver_lib = _DRIVER_LIB_LOADER(loaded_cuda.abs_path)
     cu_driver_get_version = driver_lib.cuDriverGetVersion
     cu_driver_get_version.argtypes = [ctypes.POINTER(ctypes.c_int)]
     cu_driver_get_version.restype = ctypes.c_int
diff --git a/cuda_pathfinder/cuda/pathfinder/_utils/path_sort.py b/cuda_pathfinder/cuda/pathfinder/_utils/path_sort.py
new file mode 100644
index 00000000000..183c9123aaa
--- /dev/null
+++ b/cuda_pathfinder/cuda/pathfinder/_utils/path_sort.py
@@ -0,0 +1,23 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+"""Deterministic path ordering helpers."""
+
+from __future__ import annotations
+
+import os
+import re
+
+_DIGIT_RUN = re.compile(r"(\d+)")
+
+
+def numeric_aware_path_sort_key(path: str) -> tuple[tuple[int, int, str], ...]:
+    """Return a key that compares embedded digit runs by numeric value."""
+    key: list[tuple[int, int, str]] = []
+    for part in _DIGIT_RUN.split(os.path.normcase(path)):
+        if part.isdigit():
+            normalized = part.lstrip("0") or "0"
+            key.append((1, len(normalized), normalized))
+        else:
+            key.append((0, 0, part))
+    return tuple(key)
diff --git a/cuda_pathfinder/cuda/pathfinder/_utils/platform_aware.py b/cuda_pathfinder/cuda/pathfinder/_utils/platform_aware.py
index 72ecbc53593..af0610a6cdb 100644
--- a/cuda_pathfinder/cuda/pathfinder/_utils/platform_aware.py
+++ b/cuda_pathfinder/cuda/pathfinder/_utils/platform_aware.py
@@ -4,6 +4,18 @@
 import sys
 
 IS_WINDOWS = sys.platform == "win32"
+_WINDOWS_PYTHON_ARCH: str | None
+
+if IS_WINDOWS:
+    from cuda.pathfinder._utils.windows_arch import windows_python_arch
+
+    _WINDOWS_PYTHON_ARCH = windows_python_arch()
+else:
+    _WINDOWS_PYTHON_ARCH = None
+
+# These describe the Python process ABI, not the Windows host architecture.
+IS_WINDOWS_X64 = _WINDOWS_PYTHON_ARCH == "x64"
+IS_WINDOWS_ARM64 = _WINDOWS_PYTHON_ARCH == "arm64"
 
 
 def quote_for_shell(s: str) -> str:
diff --git a/cuda_pathfinder/cuda/pathfinder/_utils/windows_arch.py b/cuda_pathfinder/cuda/pathfinder/_utils/windows_arch.py
new file mode 100644
index 00000000000..fc802db370f
--- /dev/null
+++ b/cuda_pathfinder/cuda/pathfinder/_utils/windows_arch.py
@@ -0,0 +1,138 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+import platform
+import sysconfig
+
+WINDOWS_PE_MACHINE_BY_ARCH = {
+    "x64": 0x8664,
+    "arm64": 0xAA64,
+}
+
+_WINDOWS_ARCH_BY_PE_MACHINE = {machine: arch for arch, machine in WINDOWS_PE_MACHINE_BY_ARCH.items()}
+
+
+class UnsupportedArchError(RuntimeError):
+    """Raised when Python reports an unsupported Windows architecture."""
+
+    def __init__(self, platform_tag: str) -> None:
+        self.platform_tag = platform_tag
+        super().__init__(
+            f"Unsupported Windows Python platform tag: {platform_tag!r}; expected 'win-amd64' or 'win-arm64'"
+        )
+
+
+def windows_python_arch() -> str:
+    """Return the current Windows Python interpreter architecture."""
+    raw_platform_tag = sysconfig.get_platform()
+    platform_tag = raw_platform_tag.lower().replace("_", "-")
+
+    if platform_tag == "win-arm64":
+        return "arm64"
+
+    if platform_tag == "win-amd64":
+        return "x64"
+
+    raise UnsupportedArchError(raw_platform_tag)
+
+
+def _windows_machine_arch_from_platform() -> str:
+    """Return the Windows architecture reported by Python's platform module."""
+    raw_machine = platform.machine()
+    machine = raw_machine.lower().replace("_", "-")
+
+    if machine in ("amd64", "x86-64"):
+        return "x64"
+
+    if machine in ("arm64", "aarch64"):
+        return "arm64"
+
+    raise RuntimeError(f"Unsupported Windows machine architecture: {raw_machine!r}")
+
+
+def _windows_native_machine() -> int | None:
+    """Return the native Windows PE machine type, or None on older Windows."""
+    import ctypes
+    from ctypes import wintypes
+
+    try:
+        # These ctypes attributes are absent from the type stubs on non-Windows hosts.
+        kernel32 = ctypes.WinDLL("kernel32", use_last_error=True)  # type: ignore[attr-defined, unused-ignore]
+    except OSError as exc:
+        raise RuntimeError("Failed to load kernel32 while detecting the native Windows architecture") from exc
+
+    get_current_process = kernel32.GetCurrentProcess
+    try:
+        is_wow64_process2 = kernel32.IsWow64Process2
+    except AttributeError:
+        return None
+
+    get_current_process.argtypes = ()
+    get_current_process.restype = wintypes.HANDLE
+    is_wow64_process2.argtypes = (
+        wintypes.HANDLE,
+        ctypes.POINTER(wintypes.USHORT),
+        ctypes.POINTER(wintypes.USHORT),
+    )
+    is_wow64_process2.restype = wintypes.BOOL
+
+    process_machine = wintypes.USHORT()
+    native_machine = wintypes.USHORT()
+    if not is_wow64_process2(
+        get_current_process(),
+        ctypes.byref(process_machine),
+        ctypes.byref(native_machine),
+    ):
+        error_code = ctypes.get_last_error()  # type: ignore[attr-defined, unused-ignore]
+        error = ctypes.WinError(error_code)  # type: ignore[attr-defined, unused-ignore]
+        raise RuntimeError(
+            f"IsWow64Process2 failed while detecting the native Windows architecture "
+            f"(Windows error {error_code}): {error}"
+        ) from error
+    return native_machine.value
+
+
+def windows_machine_arch() -> str:
+    """Return the native Windows machine architecture, ignoring process emulation."""
+    native_machine = _windows_native_machine()
+    if native_machine is None:
+        # IsWow64Process2 predates x64-on-Arm emulation, so this fallback is only
+        # needed on older Windows versions where platform.machine() is sufficient.
+        return _windows_machine_arch_from_platform()
+
+    try:
+        return _WINDOWS_ARCH_BY_PE_MACHINE[native_machine]
+    except KeyError:
+        raise RuntimeError(f"Unsupported native Windows PE machine type: 0x{native_machine:04x}") from None
+
+
+def windows_pe_matches_arch(path: str, target_arch: str) -> bool:
+    """Return whether a Windows Portable Executable (PE) targets the requested architecture.
+
+    PE is the file format used for Windows executables and DLLs. This reads the
+    PE/COFF header's machine field to distinguish x64 images from Arm64 images.
+    """
+    expected_machine = WINDOWS_PE_MACHINE_BY_ARCH.get(target_arch)
+    if expected_machine is None:
+        raise ValueError(f"Unsupported Windows target architecture: {target_arch!r}")
+
+    try:
+        with open(path, "rb") as stream:
+            if stream.read(2) != b"MZ":
+                return False
+            stream.seek(0x3C)
+            pe_offset_bytes = stream.read(4)
+            if len(pe_offset_bytes) != 4:
+                return False
+            stream.seek(int.from_bytes(pe_offset_bytes, "little"))
+            if stream.read(4) != b"PE\0\0":
+                return False
+            machine_bytes = stream.read(2)
+            if len(machine_bytes) != 2:
+                return False
+    except OSError:
+        return False
+
+    return int.from_bytes(machine_bytes, "little") == expected_machine
diff --git a/cuda_pathfinder/docs/nv-versions.json b/cuda_pathfinder/docs/nv-versions.json
index 36d6666e926..175716889da 100644
--- a/cuda_pathfinder/docs/nv-versions.json
+++ b/cuda_pathfinder/docs/nv-versions.json
@@ -3,6 +3,22 @@
         "version": "latest",
         "url": "https://nvidia.github.io/cuda-python/cuda-pathfinder/latest/"
     },
+    {
+        "version": "1.8.1",
+        "url": "https://nvidia.github.io/cuda-python/cuda-pathfinder/1.8.1/"
+    },
+    {
+        "version": "1.8.0",
+        "url": "https://nvidia.github.io/cuda-python/cuda-pathfinder/1.8.0/"
+    },
+    {
+        "version": "1.7.0",
+        "url": "https://nvidia.github.io/cuda-python/cuda-pathfinder/1.7.0/"
+    },
+    {
+        "version": "1.6.1",
+        "url": "https://nvidia.github.io/cuda-python/cuda-pathfinder/1.6.1/"
+    },
     {
         "version": "1.6.0",
         "url": "https://nvidia.github.io/cuda-python/cuda-pathfinder/1.6.0/"
diff --git a/cuda_pathfinder/docs/source/api.rst b/cuda_pathfinder/docs/source/api.rst
index e49478c09ec..f65014923f9 100644
--- a/cuda_pathfinder/docs/source/api.rst
+++ b/cuda_pathfinder/docs/source/api.rst
@@ -24,6 +24,7 @@ CUDA bitcode and static libraries.
    DynamicLibNotFoundError
    DynamicLibUnknownError
    DynamicLibNotAvailableError
+   UnsupportedArchError
 
    SUPPORTED_HEADERS_CTK
    find_nvidia_header_directory
diff --git a/cuda_pathfinder/docs/source/install.rst b/cuda_pathfinder/docs/source/install.rst
index abc8fbb9d50..078abf47ee3 100644
--- a/cuda_pathfinder/docs/source/install.rst
+++ b/cuda_pathfinder/docs/source/install.rst
@@ -9,7 +9,7 @@ Runtime Requirements
 
 ``cuda.pathfinder`` is a pure-Python package with no runtime dependencies:
 
-* Linux (x86-64, arm64) and Windows (x86-64)
+* Linux (x86-64, arm64) and Windows (x86-64, arm64)
 * Python 3.10 - 3.14
 
 Installing from PyPI
@@ -59,7 +59,7 @@ Installing from Source
 
 .. code-block:: console
 
-   $ git clone https://github.com/NVIDIA/cuda-python
+   $ git clone https://github.com/NVIDIA/cuda-python.git
    $ cd cuda-python/cuda_pathfinder
    $ pip install .
 
@@ -68,3 +68,13 @@ For an editable install (e.g. when developing ``cuda.pathfinder`` itself):
 .. code-block:: console
 
    $ pip install -v -e .
+
+.. note::
+
+   The version is derived from git tags via ``setuptools-scm``, so the clone
+   must include tags reaching back to at least the latest ``cuda-pathfinder-v*``
+   tag. Do not use ``--depth`` or ``--no-tags``: a shallow clone builds without
+   error but produces a bogus version such as ``0.1.dev1+g0d22cb444``. See
+   `Cloning the repository
+   <https://github.com/NVIDIA/cuda-python/blob/main/CONTRIBUTING.md>`_
+   for details and recovery steps.
diff --git a/cuda_pathfinder/docs/source/release/1.6.1-notes.rst b/cuda_pathfinder/docs/source/release/1.6.1-notes.rst
new file mode 100644
index 00000000000..59638c40afe
--- /dev/null
+++ b/cuda_pathfinder/docs/source/release/1.6.1-notes.rst
@@ -0,0 +1,81 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. py:currentmodule:: cuda.pathfinder
+
+``cuda-pathfinder`` 1.6.1 Release notes
+=======================================
+
+Highlights
+----------
+
+* Make Windows dynamic-library discovery architecture-aware. Pathfinder now
+  detects whether the current Python interpreter is x64 or Arm64, searches
+  only the matching CUDA Toolkit and wheel directories, and reports only the
+  CTK libraries available for that architecture through
+  ``SUPPORTED_NVIDIA_LIBNAMES``. A known library unavailable for the current
+  architecture raises ``DynamicLibNotAvailableError``.
+  (`PR #2393 <https://github.com/NVIDIA/cuda-python/pull/2393>`_)
+
+* Add Windows Arm64 discovery for CUDA 13.4 layouts while retaining legacy
+  CUDA 12 wheel directories as x64-only fallbacks. This includes corrected
+  architecture-specific locations for cuDLA, NVVM, CUPTI, and cuSPARSELt.
+  NVVM binaries found in an unqualified legacy directory are checked for a
+  matching PE machine architecture before loading.
+  (`PR #2393 <https://github.com/NVIDIA/cuda-python/pull/2393>`_)
+
+* Add ``UnsupportedArchError`` for unsupported Windows Python platform tags.
+  (`PR #2393 <https://github.com/NVIDIA/cuda-python/pull/2393>`_)
+
+* Make Windows static-library discovery architecture-aware. Searches now use
+  the current Python interpreter architecture to select the matching
+  ``lib/x64`` or ``lib/arm64`` CUDA Toolkit and wheel directories. CUDA 12
+  component-wheel and legacy Conda fallbacks remain x64-only.
+  (`PR #2491 <https://github.com/NVIDIA/cuda-python/pull/2491>`_)
+
+* Fix Windows binary-utility discovery for CUDA 13.4 Arm64 layouts. Prefer the
+  Compute Sanitizer launcher, locate standalone Nsight Systems and Nsight
+  Compute through their installer registry entries, and select
+  architecture-specific executable targets using the native Windows machine
+  architecture.
+  (`PR #2586 <https://github.com/NVIDIA/cuda-python/pull/2586>`_)
+
+Bugfixes
+--------
+
+* Ensure :func:`find_nvidia_binary_utility` returns an absolute path when a
+  configured search root is relative. On Windows, dynamic-library loading now
+  warns when registering a dependent-DLL directory fails before falling back
+  to updating ``PATH``.
+  (`PR #2399 <https://github.com/NVIDIA/cuda-python/pull/2399>`_)
+
+Documentation
+-------------
+
+* Document that source builds require Git history and
+  ``cuda-pathfinder-v*`` tags so ``setuptools-scm`` can derive the package
+  version.
+  (`PR #2424 <https://github.com/NVIDIA/cuda-python/pull/2424>`_)
+
+Internal maintenance
+--------------------
+
+* Group Windows search locations by architecture in the dynamic-library
+  descriptor catalog. Add explicit ``_X64`` and ``_ARM64`` variants of the
+  internal ``SUPPORTED_LIBNAMES_WINDOWS*`` and
+  ``SITE_PACKAGES_LIBDIRS_WINDOWS*`` tables. Unsuffixed names remain x64
+  aliases for backward compatibility.
+  (`PR #2393 <https://github.com/NVIDIA/cuda-python/pull/2393>`_)
+
+* Remove the obsolete descriptor-catalog writer and its catalog-update tools.
+  The site-packages collection scripts remain available for gathering library
+  paths.
+  (`PR #2393 <https://github.com/NVIDIA/cuda-python/pull/2393>`_)
+
+* Use ``pathlib.Path`` internally for static- and bitcode-library discovery
+  while preserving the public string return types.
+  (`PR #2493 <https://github.com/NVIDIA/cuda-python/pull/2493>`_)
+
+* Isolate Windows Nsight registry discovery in a dedicated internal module and
+  add focused tests; runtime behavior is unchanged.
+  (`PR #2614 <https://github.com/NVIDIA/cuda-python/pull/2614>`_)
diff --git a/cuda_pathfinder/docs/source/release/1.7.0-notes.rst b/cuda_pathfinder/docs/source/release/1.7.0-notes.rst
new file mode 100644
index 00000000000..b31f0a7aa0c
--- /dev/null
+++ b/cuda_pathfinder/docs/source/release/1.7.0-notes.rst
@@ -0,0 +1,68 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. py:currentmodule:: cuda.pathfinder
+
+``cuda-pathfinder`` 1.7.0 Release notes
+=======================================
+
+Highlights
+----------
+
+* Add cuDNN 9 dynamic-library loading on Linux and Windows through
+  :func:`load_nvidia_dynamic_lib`. Discovery supports NVIDIA Python wheels and
+  Conda environments, adds ``CUDNN_PATH``, and recognizes versioned x64
+  installations under Program Files alongside existing native and CUDA-root
+  searches. Loading cuDNN preloads the required cuBLASLt dependency and NVRTC
+  when available.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
+
+* Add native Windows Arm64 cuDNN loading through the verified standalone
+  archive layout at ``CUDNN_PATH/bin/arm64``. Windows Arm64 wheel, Conda,
+  ``CUDA_PATH``, and Program Files dynamic-library layouts remain outside the
+  supported scope; those routes remain x64-only.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
+
+* Add cuDNN header discovery on Linux and Windows through NVIDIA Python
+  wheels, Conda environments, ``CUDNN_PATH``, common Linux system and
+  multiarch include directories, and versioned Windows Program Files
+  installations.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
+
+* Add NCCL header discovery on Linux through NVIDIA Python wheels, Conda
+  environments, ``NCCL_HOME``, common system include directories, and NCCL
+  source-build layouts. ``NCCL_HOME`` also participates in the existing NCCL
+  dynamic-library search through ``lib``, ``lib64``, and ``build/lib``.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
+
+Bugfixes
+--------
+
+* Make Windows filesystem DLL matching exact by default, preventing similarly
+  named libraries and component DLLs from being selected for the wrong
+  descriptor. CUPTI retains forward-compatible discovery through the explicit
+  ``cupti64_*.dll`` fallback. Known names take precedence over fallback
+  matches, and each group is searched newest-first.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
+
+* When an already-loaded Windows library requires dependent-DLL directory
+  registration, register the directory of the actual loaded module regardless
+  of whether an earlier filesystem search found another candidate. Also make
+  already-loaded lookup prefer the newest known DLL name, matching native
+  system loading.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
+
+* Continue through every configured dynamic-library directory when an earlier
+  directory exists but does not contain the requested library. Use
+  numeric-aware ordering for versioned installation roots and Windows fallback
+  DLL matches so, for example, ``v9.10`` is preferred over ``v9.9``.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
+
+Internal maintenance
+--------------------
+
+* Extend the dynamic-library and header descriptor metadata and platform
+  search abstractions for product-specific installation roots, optional
+  dependencies, architecture-specific Windows layouts, and opt-in fallback
+  globs. Public function signatures remain unchanged.
+  (`PR #2680 <https://github.com/NVIDIA/cuda-python/pull/2680>`_)
diff --git a/cuda_pathfinder/docs/source/release/1.8.0-notes.rst b/cuda_pathfinder/docs/source/release/1.8.0-notes.rst
new file mode 100644
index 00000000000..96f502e67ee
--- /dev/null
+++ b/cuda_pathfinder/docs/source/release/1.8.0-notes.rst
@@ -0,0 +1,55 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. py:currentmodule:: cuda.pathfinder
+
+``cuda-pathfinder`` 1.8.0 Release notes
+=======================================
+
+Compatibility note
+------------------
+
+The discovery behavior change in this release is subtle and is expected to
+affect only a small fraction of installations: those that rely exclusively on
+a dynamic-library filename not declared in Pathfinder's descriptor catalog.
+All currently verified NVIDIA wheel and local CUDA Toolkit layouts continue to
+work. Nevertheless, because a previously accepted wildcard-only layout can now
+fail discovery, this release increments the minor version out of an abundance
+of caution.
+
+Highlights
+----------
+
+* Add support for the CUDA 13.4 cuRAND dynamic-library filenames
+  ``libcurand.so.11`` on Linux and ``curand64_11.dll`` on Windows, so
+  :func:`load_nvidia_dynamic_lib` can recognize the installed library while
+  retaining support for the ABI 10 filenames.
+  (`PR #2692 <https://github.com/NVIDIA/cuda-python/pull/2692>`_)
+
+Bugfixes
+--------
+
+* Restrict Windows CUPTI filesystem discovery to descriptor-declared DLL
+  names. Removing its wildcard fallback keeps candidate selection consistent
+  with already-loaded detection and native loading, and prevents undeclared
+  DLL names from being selected.
+  (`PR #2689 <https://github.com/NVIDIA/cuda-python/pull/2689>`_)
+
+* Make Linux filesystem discovery, already-loaded detection, and native loading
+  use one descriptor-declared library filename list in runtime preference
+  order. Remove the implicit ``lib<name>.so`` and broad ``.so*`` filesystem
+  fallbacks, so explicit directory layouts must expose a declared filename.
+  Explicitly declare the unversioned ``libnvvm.so`` wheel filename to preserve
+  CUDA 12.9 wheel discovery, and correct the ``cufftMp`` catalog order so ABI
+  12 is preferred over ABI 11.
+  (`PR #2689 <https://github.com/NVIDIA/cuda-python/pull/2689>`_)
+
+Internal maintenance
+--------------------
+
+* Author dynamic-library filename candidates directly in runtime preference
+  order and consume them without catalog-to-runtime reversals. Document the
+  same first-to-last candidate convention for dynamic libraries, headers,
+  binary utilities, static libraries, and bitcode libraries. Runtime selection
+  is unchanged.
+  (`PR #2708 <https://github.com/NVIDIA/cuda-python/pull/2708>`_)
diff --git a/cuda_pathfinder/docs/source/release/1.8.1-notes.rst b/cuda_pathfinder/docs/source/release/1.8.1-notes.rst
new file mode 100644
index 00000000000..b43fcdb0cf5
--- /dev/null
+++ b/cuda_pathfinder/docs/source/release/1.8.1-notes.rst
@@ -0,0 +1,33 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+.. py:currentmodule:: cuda.pathfinder
+
+``cuda-pathfinder`` 1.8.1 Release notes
+=======================================
+
+Highlights
+----------
+
+* Add ``ptxas`` to ``SUPPORTED_BINARY_UTILITIES``. The
+  :func:`find_nvidia_binary_utility` function can now locate it on Linux and
+  Windows through the existing NVIDIA wheel, Conda, and CUDA Toolkit search
+  pipeline. NVIDIA wheel discovery prefers the CUDA 13 ``nvidia/cu13/bin``
+  layout while retaining the legacy ``nvidia/cuda_nvcc/bin`` fallback.
+  (`PR #2741 <https://github.com/NVIDIA/cuda-python/pull/2741>`_)
+
+Bugfixes
+--------
+
+* Find ``cuobjdump`` in the CUDA 13 ``nvidia/cu13/bin`` NVIDIA wheel layout
+  while retaining discovery from the legacy ``nvidia/cuda_nvcc/bin`` layout.
+  (`PR #2739 <https://github.com/NVIDIA/cuda-python/pull/2739>`_)
+
+Internal maintenance
+--------------------
+
+* Add ``pytest-run-parallel>=0.4.1`` to the normal test dependencies so the
+  existing ``thread_unsafe`` marker and ``thread_unsafe_fixtures``
+  configuration option are registered in standard test environments. This is
+  test-only and does not add a runtime dependency.
+  (`PR #2741 <https://github.com/NVIDIA/cuda-python/pull/2741>`_)
diff --git a/cuda_pathfinder/pixi.lock b/cuda_pathfinder/pixi.lock
index 0891bddfece..d621d6a9d22 100644
--- a/cuda_pathfinder/pixi.lock
+++ b/cuda_pathfinder/pixi.lock
@@ -98,6 +98,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-mock-3.15.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -136,6 +137,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-mock-3.15.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -156,6 +158,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-mock-3.15.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -214,6 +217,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-mock-3.15.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -252,6 +256,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -272,6 +277,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -330,6 +336,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -368,6 +375,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -388,6 +396,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-mock-3.15.1-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-randomly-3.15.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-repeat-0.9.4-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python_abi-3.14-8_cp314.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/tomli-2.3.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/typing_extensions-4.15.0-pyhcf101f3_0.conda
@@ -420,7 +429,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/backports.zstd-1.3.0-py312h90b7ffd_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.2.0-py312hdb49522_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_9.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.4-py312h68e6be4_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.9-py312h68e6be4_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/debugpy-1.8.20-py312h8285ef7_0.conda
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       - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-h33c6efd_0.conda
@@ -586,7 +595,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/bzip2-1.0.8-h4777abc_9.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.4-py312he940de5_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.9-py312hbda70bc_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/debugpy-1.8.20-py312hf55c4e8_0.conda
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@@ -863,7 +872,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/win-64/brotli-python-1.2.0-py312hc6d9e41_1.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h0ad9c76_9.conda
-      - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.4-py312hd245ac3_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.9-py312hd245ac3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/win-64/debugpy-1.8.20-py312ha1a9051_0.conda
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       - conda: https://conda.anaconda.org/conda-forge/win-64/krb5-1.22.2-h0ea6238_0.conda
@@ -1003,9 +1012,9 @@ packages:
     - bzip2 >=1.0.8,<2.0a0
   size: 260182
   timestamp: 1771350215188
-- conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.4-py312h68e6be4_0.conda
-  sha256: 01b815091e0c534a5f32a830b514e31c150dc2f539b7ba1d5c70b6d095a5ebcf
-  md5: 14f638dad5953c83443a2c4f011f1c9e
+- conda: https://conda.anaconda.org/conda-forge/linux-64/cython-3.2.9-py312h68e6be4_0.conda
+  sha256: 13e37a868e52933951b3f80fd5fe953742804499f2ee2b9a123e74070c265c0d
+  md5: 7311d3a6721eec7d76f4a84045f1ddfd
   depends:
   - __glibc >=2.17,<3.0.a0
   - libgcc >=14
@@ -1016,8 +1025,9 @@ packages:
   license_family: APACHE
   purls:
   - pkg:pypi/cython?source=hash-mapping
-  size: 3738170
-  timestamp: 1767577770165
+  run_exports: {}
+  size: 3731635
+  timestamp: 1785016112258
 - conda: https://conda.anaconda.org/conda-forge/linux-64/debugpy-1.8.20-py312h8285ef7_0.conda
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   md5: ee1b48795ceb07311dd3e665dd4f5f33
@@ -2115,21 +2125,21 @@ packages:
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   timestamp: 1771350241232
-- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.4-py312he940de5_0.conda
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-  md5: 2f50ec4afc8e9f402b9041e9cee62744
+- conda: https://conda.anaconda.org/conda-forge/linux-aarch64/cython-3.2.9-py312hbda70bc_0.conda
+  sha256: 9c3df78ef64fc05aaf01b4d16ccefe25656b7aac677a3a9d5e89e0c462c65a2c
+  md5: 30984003a6a35ea7b9eedc979cf52c7e
   depends:
   - libgcc >=14
   - libstdcxx >=14
   - python >=3.12,<3.13.0a0
-  - python >=3.12,<3.13.0a0 *_cpython
   - python_abi 3.12.* *_cp312
   license: Apache-2.0
   license_family: APACHE
   purls:
   - pkg:pypi/cython?source=hash-mapping
-  size: 3629503
-  timestamp: 1767577211661
+  run_exports: {}
+  size: 3649707
+  timestamp: 1785016066705
 - conda: https://conda.anaconda.org/conda-forge/linux-aarch64/debugpy-1.8.20-py312hf55c4e8_0.conda
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   md5: d7ee86593223e812e41612678c26a10d
@@ -4308,6 +4318,17 @@ packages:
   license_family: MOZILLA
   size: 10537
   timestamp: 1744061283541
+- conda: https://conda.anaconda.org/conda-forge/noarch/pytest-run-parallel-0.10.0-pyhd8ed1ab_0.conda
+  sha256: e69fc1d40c3ad22ad4b664143916ccb2f5d57cdb70879c371b8905e4f51c82bb
+  md5: 79c30c544dd76bd4f81d7e975efaca4b
+  depends:
+  - pytest >=6.2.0
+  - python >=3.10
+  license: MIT
+  license_family: MIT
+  run_exports: {}
+  size: 24875
+  timestamp: 1785909313088
 - conda: https://conda.anaconda.org/conda-forge/noarch/python-dateutil-2.9.0.post0-pyhe01879c_2.conda
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   md5: 5b8d21249ff20967101ffa321cab24e8
@@ -4959,9 +4980,9 @@ packages:
     - bzip2 >=1.0.8,<2.0a0
   size: 56115
   timestamp: 1771350256444
-- conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.4-py312hd245ac3_0.conda
-  sha256: 68e921fad16accb32e86c7c73abaea7d49c9346e078924d0a593f821672a5a0c
-  md5: 575ebca0d973015c21087b800bc48515
+- conda: https://conda.anaconda.org/conda-forge/win-64/cython-3.2.9-py312hd245ac3_0.conda
+  sha256: 277887d63842d6b9d8a49f6bde1c57149fd65342c85e1f3e2aa44402125d3115
+  md5: 762f58961f768b8790a215a8521d33cd
   depends:
   - python >=3.12,<3.13.0a0
   - python_abi 3.12.* *_cp312
@@ -4972,8 +4993,9 @@ packages:
   license_family: APACHE
   purls:
   - pkg:pypi/cython?source=hash-mapping
-  size: 3285032
-  timestamp: 1767577225362
+  run_exports: {}
+  size: 3316549
+  timestamp: 1785016176418
 - conda: https://conda.anaconda.org/conda-forge/win-64/debugpy-1.8.20-py312ha1a9051_0.conda
   sha256: 5a886b1af3c66bf58213c7f3d802ea60fe8218313d9072bc1c9e8f7840548ba0
   md5: 032746a0b0663920f0afb18cec61062b
diff --git a/cuda_pathfinder/pixi.toml b/cuda_pathfinder/pixi.toml
index 7ebcc9644d7..6236aead9b9 100644
--- a/cuda_pathfinder/pixi.toml
+++ b/cuda_pathfinder/pixi.toml
@@ -15,11 +15,12 @@ pytest = ">=6.2.4"
 pytest-mock = "*"
 pytest-repeat = "*"
 pytest-randomly = "*"
+pytest-run-parallel = ">=0.4.1"
 
 # Keep this dependency set aligned with cuda_python/docs/environment-docs.yml.
 [feature.docs.dependencies]
 python = "3.12.*"
-cython = "*"
+cython = ">=3.2.5,<3.3"
 enum_tools = "*"
 make = "*"
 myst-nb = "*"
diff --git a/cuda_pathfinder/pyproject.toml b/cuda_pathfinder/pyproject.toml
index 227b8fa4eb7..9b480976614 100644
--- a/cuda_pathfinder/pyproject.toml
+++ b/cuda_pathfinder/pyproject.toml
@@ -16,6 +16,10 @@ test = [
     "pytest-mock==3.15.1",
     "pytest-repeat==0.9.4",
     "pytest-randomly==4.1.0",
+    "pytest-run-parallel>=0.4.1",
+]
+test-ft = [
+    "pytest-run-parallel==0.10.0",
 ]
 # Internal organization of test dependencies.
 cu12 = [
@@ -24,6 +28,7 @@ cu12 = [
     "cuquantum-cu12; sys_platform != 'win32'",
     "cutensor-cu12",
     "nvidia-cublasmp-cu12; sys_platform != 'win32'",
+    "nvidia-cudnn-cu12>=9,<10",
     "nvidia-cudss-cu12",
     "nvidia-cufftmp-cu12; sys_platform != 'win32'",
     "nvidia-cusolvermp-cu12; sys_platform != 'win32'",
@@ -39,6 +44,7 @@ cu13 = [
     "cutensor-cu13",
     "nvidia-cublasmp-cu13; sys_platform != 'win32'",
     "nvidia-cudla; platform_system == 'Linux' and platform_machine == 'aarch64'",
+    "nvidia-cudnn-cu13>=9,<10",
     "nvidia-cudss-cu13",
     "nvidia-cufftmp-cu13; sys_platform != 'win32'",
     "nvidia-cusolvermp-cu13; sys_platform != 'win32'",
@@ -103,7 +109,7 @@ tag_regex = "^cuda-pathfinder-(?P<version>v\\d+\\.\\d+\\.\\d+(?:[ab]\\d+)?)"
 git_describe_command = [ "git", "describe", "--dirty", "--tags", "--long", "--match", "cuda-pathfinder-v*[0-9]*" ]
 
 [tool.pytest.ini_options]
-addopts = "--showlocals"
+addopts = "--showlocals --durations=20"
 thread_unsafe_fixtures = ['mocker']
 # Keep this authorship marker registry in sync across all pytest config roots.
 # Search for "agent_authored(model)" before editing.
diff --git a/cuda_pathfinder/tests/test_ctk_root_discovery.py b/cuda_pathfinder/tests/test_ctk_root_discovery.py
index 9ad148dccd2..cac4343e3cb 100644
--- a/cuda_pathfinder/tests/test_ctk_root_discovery.py
+++ b/cuda_pathfinder/tests/test_ctk_root_discovery.py
@@ -6,6 +6,7 @@
 import subprocess
 import sys
 import textwrap
+from pathlib import Path
 
 import pytest
 
@@ -19,6 +20,7 @@
     _try_ctk_root_canary,
     resolve_ctk_root_via_canary,
 )
+from cuda.pathfinder._dynamic_libs.search_platform import WindowsSearchPlatform
 from cuda.pathfinder._dynamic_libs.search_steps import (
     SearchContext,
     _derive_ctk_root_linux,
@@ -32,6 +34,7 @@
     MODE_CANARY,
 )
 from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
+from cuda.pathfinder._utils.windows_arch import windows_python_arch
 
 _MODULE = "cuda.pathfinder._dynamic_libs.load_nvidia_dynamic_lib"
 _STEPS_MODULE = "cuda.pathfinder._dynamic_libs.search_steps"
@@ -60,24 +63,35 @@ def _create_nvvm_in_ctk(ctk_root):
         nvvm_dir = ctk_root / "nvvm" / "bin"
         nvvm_dir.mkdir(parents=True)
         nvvm_lib = nvvm_dir / "nvvm64.dll"
+        machine = {"x64": 0x8664, "arm64": 0xAA64}[windows_python_arch()]
+        image = bytearray(0x86)
+        image[:2] = b"MZ"
+        image[0x3C:0x40] = (0x80).to_bytes(4, "little")
+        image[0x80:0x84] = b"PE\0\0"
+        image[0x84:0x86] = machine.to_bytes(2, "little")
+        nvvm_lib.write_bytes(image)
     else:
         nvvm_dir = ctk_root / "nvvm" / "lib64"
         nvvm_dir.mkdir(parents=True)
-        nvvm_lib = nvvm_dir / "libnvvm.so"
-    nvvm_lib.write_bytes(b"fake")
+        nvvm_lib = nvvm_dir / "libnvvm.so.4"
+        nvvm_lib.write_bytes(b"fake")
     return nvvm_lib
 
 
 def _create_cudart_in_ctk(ctk_root):
     """Create a fake cudart lib in the platform-appropriate CTK subdirectory."""
     if IS_WINDOWS:
-        lib_dir = ctk_root / "bin"
+        # Native ARM64 uses bin/arm64 only.
+        if windows_python_arch() == "arm64":
+            lib_dir = ctk_root / "bin" / "arm64"
+        else:
+            lib_dir = ctk_root / "bin"
         lib_dir.mkdir(parents=True)
         lib_file = lib_dir / "cudart64_12.dll"
     else:
         lib_dir = ctk_root / "lib64"
         lib_dir.mkdir(parents=True)
-        lib_file = lib_dir / "libcudart.so"
+        lib_file = lib_dir / "libcudart.so.13"
     lib_file.write_bytes(b"fake")
     return lib_file
 
@@ -126,6 +140,12 @@ def test_derive_ctk_root_windows_ctk13():
     assert _derive_ctk_root_windows(path) == r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.0"
 
 
+@pytest.mark.agent_authored(model="gpt-5")
+def test_derive_ctk_root_windows_ctk13_arm64():
+    path = r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4\bin\arm64\cudart64_13.dll"
+    assert _derive_ctk_root_windows(path) == r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v13.4"
+
+
 def test_derive_ctk_root_windows_ctk12():
     path = r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8\bin\cudart64_12.dll"
     assert _derive_ctk_root_windows(path) == r"C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12.8"
@@ -190,6 +210,24 @@ def test_try_via_ctk_root_regular_lib(tmp_path):
     assert result.found_via == "system-ctk-root"
 
 
+@pytest.mark.agent_authored(model="gpt-5")
+def test_try_via_ctk_root_windows_arm64_prefers_arch_dir(tmp_path):
+    ctk_root = tmp_path / "cuda-13"
+    x64_dir = ctk_root / "bin" / "x64"
+    arm64_dir = ctk_root / "bin" / "arm64"
+    x64_dir.mkdir(parents=True)
+    arm64_dir.mkdir(parents=True)
+    (x64_dir / "cudart64_13.dll").write_bytes(b"fake")
+    arm64_lib = arm64_dir / "cudart64_13.dll"
+    arm64_lib.write_bytes(b"fake")
+
+    ctx = SearchContext(LIB_DESCRIPTORS["cudart"], platform=WindowsSearchPlatform(target_arch="arm64"))
+    result = find_via_ctk_root(ctx, str(ctk_root))
+    assert result is not None
+    assert result.abs_path == str(arm64_lib)
+    assert result.found_via == "system-ctk-root"
+
+
 # ---------------------------------------------------------------------------
 # _resolve_system_loaded_abs_path_in_subprocess
 # ---------------------------------------------------------------------------
@@ -394,7 +432,7 @@ def test_resolve_ctk_root_via_canary_none_when_probe_fails(mocker):
 def test_resolve_ctk_root_via_canary_none_when_unrecognized(mocker):
     mocker.patch(
         f"{_MODULE}._resolve_system_loaded_abs_path_in_subprocess",
-        return_value=os.path.join(os.sep, "weird", "path", "libcudart.so.13"),
+        return_value=str(Path(os.sep, "weird", "path", "libcudart.so.13")),
     )
     assert resolve_ctk_root_via_canary("cudart") is None
 
diff --git a/cuda_pathfinder/tests/test_descriptor_catalog.py b/cuda_pathfinder/tests/test_descriptor_catalog.py
index b2c8eece4bb..835e7572ef0 100644
--- a/cuda_pathfinder/tests/test_descriptor_catalog.py
+++ b/cuda_pathfinder/tests/test_descriptor_catalog.py
@@ -13,10 +13,11 @@
 
 import pytest
 
-from cuda.pathfinder._dynamic_libs.descriptor_catalog import DESCRIPTOR_CATALOG, DescriptorSpec
+from cuda.pathfinder._dynamic_libs.descriptor_catalog import DESCRIPTOR_CATALOG, DescriptorSpec, WindowsSearchDirs
 
 _VALID_NAME_RE = re.compile(r"^[A-Za-z_][A-Za-z0-9_]*$")
 _VALID_PACKAGED_WITH_VALUES = {"ctk", "other", "driver"}
+_VALID_WINDOWS_ARCHES = ("x64", "arm64")
 _CATALOG_BY_NAME = {spec.name: spec for spec in DESCRIPTOR_CATALOG}
 
 
@@ -51,6 +52,15 @@ def test_no_self_dependency(spec: DescriptorSpec):
     assert spec.name not in spec.dependencies, f"{spec.name} lists itself as a dependency"
 
 
+@pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_optional_dependencies_reference_existing_entries(spec: DescriptorSpec):
+    for dep in spec.optional_dependencies:
+        assert dep in _CATALOG_BY_NAME, f"{spec.name} optionally depends on unknown library {dep!r}"
+        assert dep != spec.name, f"{spec.name} lists itself as an optional dependency"
+        assert dep not in spec.dependencies, f"{spec.name} lists {dep!r} as both required and optional"
+
+
 @pytest.mark.parametrize(
     "spec",
     [s for s in DESCRIPTOR_CATALOG if s.packaged_with == "driver"],
@@ -59,7 +69,7 @@ def test_no_self_dependency(spec: DescriptorSpec):
 def test_driver_libs_have_no_site_packages(spec: DescriptorSpec):
     """Driver libs are system-search-only; site-packages paths would be unused."""
     assert not spec.site_packages_linux, f"driver lib {spec.name} has site_packages_linux"
-    assert not spec.site_packages_windows, f"driver lib {spec.name} has site_packages_windows"
+    assert spec.site_packages_windows == WindowsSearchDirs(), f"driver lib {spec.name} has site_packages_windows"
 
 
 @pytest.mark.parametrize(
@@ -79,12 +89,106 @@ def test_linux_sonames_look_like_sonames(spec: DescriptorSpec):
         assert ".so" in soname, f"Unexpected Linux soname format: {soname}"
 
 
+@pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_library_filenames_are_unique_per_platform(spec: DescriptorSpec):
+    assert len(spec.linux_sonames) == len(set(spec.linux_sonames))
+    assert len(spec.windows_dlls) == len({dll.casefold() for dll in spec.windows_dlls})
+
+
 @pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
 def test_windows_dlls_look_like_dlls(spec: DescriptorSpec):
     for dll in spec.windows_dlls:
         assert dll.endswith(".dll"), f"Unexpected Windows DLL format: {dll}"
 
 
+@pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_supported_windows_arch_is_explicit_and_canonical(spec: DescriptorSpec):
+    expected = tuple(arch for arch in _VALID_WINDOWS_ARCHES if arch in spec.supported_windows_arch)
+    assert spec.supported_windows_arch == expected
+    assert bool(spec.supported_windows_arch) == bool(spec.windows_dlls)
+
+
+@pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_windows_search_dirs_do_not_include_unsupported_arches(spec: DescriptorSpec):
+    if not spec.windows_dlls:
+        return
+    for arch in _VALID_WINDOWS_ARCHES:
+        if arch not in spec.supported_windows_arch:
+            assert not spec.site_packages_windows.for_arch(arch)
+            assert not spec.anchor_rel_dirs_windows.for_arch(arch)
+            assert not spec.install_root_env_rel_dirs_windows.for_arch(arch)
+            assert not spec.program_files_root_globs_windows.for_arch(arch)
+
+
+@pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_windows_install_root_env_metadata_is_complete(spec: DescriptorSpec):
+    has_env_vars = bool(spec.install_root_env_vars_windows)
+    has_rel_dirs = any(spec.install_root_env_rel_dirs_windows.for_arch(arch) for arch in _VALID_WINDOWS_ARCHES)
+
+    assert has_env_vars == has_rel_dirs, f"{spec.name} must define both installation-root env vars and relative dirs"
+    if has_env_vars:
+        for arch in spec.supported_windows_arch:
+            assert spec.install_root_env_rel_dirs_windows.for_arch(arch), (
+                f"{spec.name} exposes installation-root env vars without {arch} relative dirs"
+            )
+
+
+@pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_linux_install_root_env_metadata_is_complete(spec: DescriptorSpec):
+    has_env_vars = bool(spec.install_root_env_vars_linux)
+    has_rel_dirs = bool(spec.install_root_env_rel_dirs_linux)
+
+    assert has_env_vars == has_rel_dirs, f"{spec.name} must define both Linux installation-root env vars and dirs"
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_cusparselt_windows_metadata_matches_wheel_layouts():
+    spec = _CATALOG_BY_NAME["cusparseLt"]
+    assert spec.supported_windows_arch == ("x64", "arm64")
+    assert spec.site_packages_windows == WindowsSearchDirs(
+        x64=("nvidia/cu13/bin/x64", "nvidia/cusparselt/bin"),
+        arm64=("nvidia/cu13/bin/arm64",),
+    )
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_cudnn_metadata_matches_supported_layouts():
+    spec = _CATALOG_BY_NAME["cudnn"]
+    assert spec.packaged_with == "other"
+    assert spec.linux_sonames == ("libcudnn.so.9",)
+    assert spec.windows_dlls == ("cudnn64_9.dll",)
+    assert spec.supported_windows_arch == ("x64", "arm64")
+    assert spec.site_packages_linux == ("nvidia/cudnn/lib",)
+    assert spec.site_packages_windows == WindowsSearchDirs.x64_only("nvidia/cudnn/bin")
+    assert spec.anchor_rel_dirs_windows == WindowsSearchDirs.x64_only("bin/x64", "bin")
+    assert spec.dependencies == ("cublasLt",)
+    assert spec.optional_dependencies == ("nvrtc",)
+    assert spec.install_root_env_vars_linux == ("CUDNN_PATH",)
+    assert spec.install_root_env_rel_dirs_linux == ("lib", "lib64")
+    assert spec.install_root_env_vars_windows == ("CUDNN_PATH",)
+    assert spec.install_root_env_rel_dirs_windows == WindowsSearchDirs(
+        x64=("bin/x64", "bin"),
+        arm64=("bin/arm64",),
+    )
+    assert spec.program_files_root_globs_windows == WindowsSearchDirs.x64_only("NVIDIA/CUDNN/v9.*")
+    assert spec.requires_add_dll_directory
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_nccl_metadata_matches_supported_linux_install_layouts():
+    spec = _CATALOG_BY_NAME["nccl"]
+    assert spec.packaged_with == "other"
+    assert spec.linux_sonames == ("libnccl.so.2",)
+    assert spec.site_packages_linux == ("nvidia/nccl/lib",)
+    assert spec.install_root_env_vars_linux == ("NCCL_HOME",)
+    assert spec.install_root_env_rel_dirs_linux == ("lib", "lib64", "build/lib")
+
+
 @pytest.mark.parametrize("spec", DESCRIPTOR_CATALOG, ids=lambda s: s.name)
 def test_ctk_root_canary_anchors_reference_known_ctk_libs(spec: DescriptorSpec):
     for anchor in spec.ctk_root_canary_anchor_libnames:
@@ -96,3 +200,10 @@ def test_ctk_root_canary_anchors_reference_known_ctk_libs(spec: DescriptorSpec):
 def test_only_ctk_libs_define_ctk_root_canary_anchors(spec: DescriptorSpec):
     if spec.ctk_root_canary_anchor_libnames:
         assert spec.packaged_with == "ctk", f"{spec.name} defines canary anchors but is not a CTK lib"
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_only_nvvm_requires_windows_binary_arch_check():
+    checked_libs = {spec.name for spec in DESCRIPTOR_CATALOG if spec.requires_windows_binary_arch_check}
+
+    assert checked_libs == {"nvvm"}
diff --git a/cuda_pathfinder/tests/test_driver_lib_loading.py b/cuda_pathfinder/tests/test_driver_lib_loading.py
index b97453c9b5a..defca06abed 100644
--- a/cuda_pathfinder/tests/test_driver_lib_loading.py
+++ b/cuda_pathfinder/tests/test_driver_lib_loading.py
@@ -9,14 +9,15 @@
 """
 
 import os
+from pathlib import Path
 
 import pytest
 from child_load_nvidia_dynamic_lib_helper import (
     build_child_process_failed_for_libname_message,
     run_load_nvidia_dynamic_lib_in_subprocess,
 )
-
 from conftest import skip_if_missing_libnvcudla_so
+
 from cuda.pathfinder._dynamic_libs.lib_descriptor import LIB_DESCRIPTORS
 from cuda.pathfinder._dynamic_libs.load_dl_common import DynamicLibNotFoundError, LoadedDL
 from cuda.pathfinder._dynamic_libs.load_nvidia_dynamic_lib import (
@@ -157,7 +158,7 @@ def raise_child_process_failed():
         abs_path = payload.abs_path
         assert abs_path is not None
         info_summary_append(f"abs_path={quote_for_shell(abs_path)}")
-        assert os.path.isfile(abs_path)
+        assert Path(abs_path).is_file()
 
 
 def test_real_query_driver_cuda_version(info_summary_append):
diff --git a/cuda_pathfinder/tests/test_find_bitcode_lib.py b/cuda_pathfinder/tests/test_find_bitcode_lib.py
index 659b068f0ff..6b5f2de49eb 100644
--- a/cuda_pathfinder/tests/test_find_bitcode_lib.py
+++ b/cuda_pathfinder/tests/test_find_bitcode_lib.py
@@ -66,7 +66,7 @@ def _located_bitcode_lib_asserts(located_bitcode_lib):
     assert isinstance(located_bitcode_lib.filename, str)
     assert isinstance(located_bitcode_lib.found_via, str)
     assert located_bitcode_lib.found_via in ("site-packages", "conda", "CUDA_PATH")
-    assert os.path.isfile(located_bitcode_lib.abs_path)
+    assert Path(located_bitcode_lib.abs_path).is_file()
 
 
 @pytest.mark.usefixtures("clear_find_bitcode_lib_cache")
@@ -83,10 +83,10 @@ def test_locate_bitcode_lib(info_summary_append, libname):
 
     info_summary_append(f"{lib_path=!r}")
     _located_bitcode_lib_asserts(located_lib)
-    assert os.path.isfile(lib_path)
+    assert Path(lib_path).is_file()
     assert lib_path == located_lib.abs_path
     expected_filename = located_lib.filename
-    assert os.path.basename(lib_path) == expected_filename
+    assert Path(lib_path).name == expected_filename
 
 
 @pytest.mark.usefixtures("clear_find_bitcode_lib_cache")
@@ -156,7 +156,7 @@ def test_find_bitcode_lib_not_found_error_includes_cuda_home_directory_listing(m
         find_bitcode_lib("device")
 
     message = str(exc_info.value)
-    expected_missing_file = os.path.join(str(lib_dir), _bitcode_lib_filename("device"))
+    expected_missing_file = lib_dir / _bitcode_lib_filename("device")
     assert f"No such file: {expected_missing_file}" in message
     assert f'listdir("{lib_dir}"):' in message
     assert "README.txt" in message
diff --git a/cuda_pathfinder/tests/test_find_nvidia_binaries.py b/cuda_pathfinder/tests/test_find_nvidia_binaries.py
index 2784633ff38..1fc9cb29906 100644
--- a/cuda_pathfinder/tests/test_find_nvidia_binaries.py
+++ b/cuda_pathfinder/tests/test_find_nvidia_binaries.py
@@ -9,11 +9,16 @@
 from cuda.pathfinder._binaries import find_nvidia_binary_utility as binary_finder_module
 from cuda.pathfinder._binaries.find_nvidia_binary_utility import UnsupportedBinaryError
 from cuda.pathfinder._binaries.supported_nvidia_binaries import (
+    _CUDA13_BIN,
     SITE_PACKAGES_BINDIRS,
     SUPPORTED_BINARIES,
     SUPPORTED_BINARIES_ALL,
 )
 
+CUDA13_WHEEL_BINARIES = frozenset(
+    ("nvcc", "ptxas", "nvdisasm", "cuobjdump", "fatbinary", "bin2c", "nvlink", "compute-sanitizer")
+)
+
 
 def test_unknown_utility_name():
     with pytest.raises(UnsupportedBinaryError, match=r"'unknown-utility' is not supported"):
@@ -33,6 +38,20 @@ def test_supported_binaries_consistency():
     assert set(SITE_PACKAGES_BINDIRS).issubset(SUPPORTED_BINARIES_ALL)
 
 
+@pytest.mark.agent_authored(model="claude-opus-5")
+def test_cuda13_wheel_layout_is_declared_and_preferred():
+    """Every supported utility shipped in nvidia/cu13/bin must declare that layout first.
+
+    Omitting it makes the site-packages search step skip an installed CUDA 13
+    wheel entirely, which is only visible on hosts without a local CTK to fall
+    back on.
+    """
+    declared = {name for name, bindirs in SITE_PACKAGES_BINDIRS.items() if _CUDA13_BIN in bindirs}
+    assert declared == set(CUDA13_WHEEL_BINARIES)
+    for name in CUDA13_WHEEL_BINARIES:
+        assert SITE_PACKAGES_BINDIRS[name][0] == _CUDA13_BIN
+
+
 @pytest.fixture
 def clear_find_binary_cache():
     find_nvidia_binary_utility.cache_clear()
@@ -128,6 +147,256 @@ def test_find_binary_windows_extension_and_search_dirs(monkeypatch, mocker):
     assert checked == [os.path.join(d, "nvcc.exe") for d in expected_dirs]
 
 
+@pytest.mark.parametrize(
+    ("launcher_exists", "expected_rel", "checked_rels"),
+    (
+        (True, os.path.join("bin", "compute-sanitizer.bat"), (os.path.join("bin", "compute-sanitizer.bat"),)),
+        (
+            False,
+            os.path.join("compute-sanitizer", "compute-sanitizer.exe"),
+            (
+                os.path.join("bin", "compute-sanitizer.bat"),
+                os.path.join("compute-sanitizer", "compute-sanitizer.exe"),
+            ),
+        ),
+    ),
+)
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_compute_sanitizer_prefers_ctk_launcher_with_executable_fallback(
+    monkeypatch, mocker, launcher_exists, expected_rel, checked_rels
+):
+    cuda_home = os.path.join(os.sep, "cuda")
+    launcher = os.path.join(cuda_home, "bin", "compute-sanitizer.bat")
+    executable = os.path.join(cuda_home, "compute-sanitizer", "compute-sanitizer.exe")
+
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(binary_finder_module.supported_nvidia_binaries, "SITE_PACKAGES_BINDIRS", {})
+    monkeypatch.delenv("CONDA_PREFIX", raising=False)
+    mocker.patch.object(binary_finder_module, "get_cuda_path_or_home", return_value=cuda_home)
+    canary_mock = mocker.patch.object(binary_finder_module, "_resolve_ctk_root_via_canary")
+    existing = [executable]
+    if launcher_exists:
+        existing.append(launcher)
+    checked = _patch_exec_probe(mocker, existing=existing)
+
+    assert find_nvidia_binary_utility("compute-sanitizer") == os.path.abspath(os.path.join(cuda_home, expected_rel))
+    assert checked == [os.path.join(cuda_home, rel) for rel in checked_rels]
+    canary_mock.assert_not_called()
+
+
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_compute_sanitizer_uses_canary_ctk_root(monkeypatch, mocker):
+    ctk_root = os.path.join(os.sep, "cuda")
+    launcher = os.path.join(ctk_root, "bin", "compute-sanitizer.bat")
+
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(binary_finder_module.supported_nvidia_binaries, "SITE_PACKAGES_BINDIRS", {})
+    monkeypatch.delenv("CONDA_PREFIX", raising=False)
+    mocker.patch.object(binary_finder_module, "get_cuda_path_or_home", return_value=None)
+    canary = mocker.patch.object(binary_finder_module, "_resolve_ctk_root_via_canary", return_value=ctk_root)
+    checked = _patch_exec_probe(mocker, existing=[launcher])
+
+    assert find_nvidia_binary_utility("compute-sanitizer") == os.path.abspath(launcher)
+    assert checked == [launcher]
+    canary.assert_called_once_with()
+
+
+@pytest.mark.parametrize(
+    ("utility_name", "candidate_names"),
+    (
+        ("nsys", ("nsys.exe",)),
+        ("ncu", ("ncu.bat", "ncu.exe")),
+    ),
+)
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_binary_windows_nsight_conda_precedes_registry(monkeypatch, mocker, utility_name, candidate_names):
+    site_dir = os.path.join(os.sep, "site-packages", utility_name, "bin")
+    conda_prefix = os.path.join(os.sep, "conda")
+    conda_bin = os.path.join(conda_prefix, "Library", "bin")
+    expected = os.path.join(conda_bin, candidate_names[0])
+
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(binary_finder_module, "find_sub_dirs_all_sitepackages", return_value=[site_dir])
+    monkeypatch.setenv("CONDA_PREFIX", conda_prefix)
+    candidate_paths = mocker.patch.object(binary_finder_module.windows_nsight, f"{utility_name}_candidate_paths")
+    get_cuda_path = mocker.patch.object(binary_finder_module, "get_cuda_path_or_home")
+    canary = mocker.patch.object(binary_finder_module, "_resolve_ctk_root_via_canary")
+    checked = _patch_exec_probe(mocker, existing=[expected])
+
+    assert find_nvidia_binary_utility(utility_name) == os.path.abspath(expected)
+    assert checked == [
+        *(os.path.join(site_dir, name) for name in candidate_names),
+        os.path.join(conda_bin, candidate_names[0]),
+    ]
+    candidate_paths.assert_not_called()
+    get_cuda_path.assert_not_called()
+    canary.assert_not_called()
+
+
+@pytest.mark.parametrize(
+    ("utility_name", "product", "machine_arch", "target_rel", "candidate_names"),
+    (
+        ("nsys", "Systems", "x64", os.path.join("target-windows-x64", "nsys.exe"), ("nsys.exe",)),
+        ("nsys", "Systems", "arm64", os.path.join("target-windows-armv8", "nsys.exe"), ("nsys.exe",)),
+        (
+            "ncu",
+            "Compute",
+            "x64",
+            os.path.join("target", "windows-desktop-win7-x64", "ncu.exe"),
+            ("ncu.bat", "ncu.exe"),
+        ),
+        (
+            "ncu",
+            "Compute",
+            "arm64",
+            os.path.join("target", "windows-desktop-win10-t23x-a64", "ncu.exe"),
+            ("ncu.bat", "ncu.exe"),
+        ),
+    ),
+)
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_binary_windows_nsight_composes_registry_and_native_target(
+    monkeypatch, mocker, utility_name, product, machine_arch, target_rel, candidate_names
+):
+    site_dir = os.path.join(os.sep, "site-packages", utility_name, "bin")
+    conda_prefix = os.path.join(os.sep, "conda")
+    conda_bin = os.path.join(conda_prefix, "Library", "bin")
+    install_root = os.path.join(os.sep, "Program Files", utility_name)
+    expected = os.path.join(install_root, target_rel)
+
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(binary_finder_module, "find_sub_dirs_all_sitepackages", return_value=[site_dir])
+    monkeypatch.setenv("CONDA_PREFIX", conda_prefix)
+    registry_root = mocker.patch.object(
+        binary_finder_module.windows_nsight, "_installed_product_root", return_value=install_root
+    )
+    machine_arch_mock = mocker.patch.object(
+        binary_finder_module.windows_nsight, "windows_machine_arch", return_value=machine_arch
+    )
+    get_cuda_path = mocker.patch.object(binary_finder_module, "get_cuda_path_or_home")
+    canary = mocker.patch.object(binary_finder_module, "_resolve_ctk_root_via_canary")
+    checked = _patch_exec_probe(mocker, existing=[expected])
+
+    assert find_nvidia_binary_utility(utility_name) == os.path.abspath(expected)
+    assert checked == [
+        *(os.path.join(directory, name) for directory in (site_dir, conda_bin) for name in candidate_names),
+        *((os.path.join(install_root, "ncu.bat"),) if utility_name == "ncu" else ()),
+        expected,
+    ]
+    registry_root.assert_called_once_with(product)
+    machine_arch_mock.assert_called_once_with()
+    get_cuda_path.assert_not_called()
+    canary.assert_not_called()
+
+
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_binary_windows_ncu_launcher_hit_does_not_resolve_machine_arch(monkeypatch, mocker):
+    install_root = os.path.join(os.sep, "Program Files", "Nsight Compute")
+    launcher = os.path.join(install_root, "ncu.bat")
+
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(binary_finder_module.supported_nvidia_binaries, "SITE_PACKAGES_BINDIRS", {})
+    monkeypatch.delenv("CONDA_PREFIX", raising=False)
+    registry_root = mocker.patch.object(
+        binary_finder_module.windows_nsight, "_installed_product_root", return_value=install_root
+    )
+    machine_arch = mocker.patch.object(binary_finder_module.windows_nsight, "windows_machine_arch")
+    get_cuda_path = mocker.patch.object(binary_finder_module, "get_cuda_path_or_home")
+    canary = mocker.patch.object(binary_finder_module, "_resolve_ctk_root_via_canary")
+    checked = _patch_exec_probe(mocker, existing=[launcher])
+
+    assert find_nvidia_binary_utility("ncu") == os.path.abspath(launcher)
+    assert checked == [launcher]
+    registry_root.assert_called_once_with("Compute")
+    machine_arch.assert_not_called()
+    get_cuda_path.assert_not_called()
+    canary.assert_not_called()
+
+
+@pytest.mark.parametrize(("utility_name", "product"), (("nsys", "Systems"), ("ncu", "Compute")))
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_binary_windows_nsight_registry_miss_is_terminal(monkeypatch, mocker, utility_name, product):
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(binary_finder_module.supported_nvidia_binaries, "SITE_PACKAGES_BINDIRS", {})
+    monkeypatch.delenv("CONDA_PREFIX", raising=False)
+    registry_root = mocker.patch.object(
+        binary_finder_module.windows_nsight, "_installed_product_root", return_value=None
+    )
+    machine_arch = mocker.patch.object(binary_finder_module.windows_nsight, "windows_machine_arch")
+    get_cuda_path = mocker.patch.object(binary_finder_module, "get_cuda_path_or_home")
+    canary = mocker.patch.object(binary_finder_module, "_resolve_ctk_root_via_canary")
+
+    assert find_nvidia_binary_utility(utility_name) is None
+    registry_root.assert_called_once_with(product)
+    machine_arch.assert_not_called()
+    get_cuda_path.assert_not_called()
+    canary.assert_not_called()
+
+
+@pytest.mark.parametrize("utility_name", ("nsight-sys", "nsight-compute"))
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_windows_nsight_legacy_names_remain_literal_in_early_search(monkeypatch, mocker, utility_name):
+    site_key = os.path.join("nvidia", utility_name, "bin")
+    site_dir = os.path.join(os.sep, "site-packages", utility_name, "bin")
+    conda_prefix = os.path.join(os.sep, "conda")
+    conda_bin = os.path.join(conda_prefix, "Library", "bin")
+    expected = os.path.join(conda_bin, f"{utility_name}.exe")
+
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(
+        binary_finder_module.supported_nvidia_binaries,
+        "SITE_PACKAGES_BINDIRS",
+        {utility_name: (site_key,)},
+    )
+    find_sub_dirs = mocker.patch.object(binary_finder_module, "find_sub_dirs_all_sitepackages", return_value=[site_dir])
+    monkeypatch.setenv("CONDA_PREFIX", conda_prefix)
+    get_cuda_path = mocker.patch.object(binary_finder_module, "get_cuda_path_or_home")
+    nsys_candidates = mocker.patch.object(binary_finder_module.windows_nsight, "nsys_candidate_paths")
+    ncu_candidates = mocker.patch.object(binary_finder_module.windows_nsight, "ncu_candidate_paths")
+    checked = _patch_exec_probe(mocker, existing=[expected])
+
+    assert find_nvidia_binary_utility(utility_name) == os.path.abspath(expected)
+    assert checked == [os.path.join(site_dir, f"{utility_name}.exe"), expected]
+    find_sub_dirs.assert_called_once_with(site_key.split(os.sep))
+    get_cuda_path.assert_not_called()
+    nsys_candidates.assert_not_called()
+    ncu_candidates.assert_not_called()
+
+
+@pytest.mark.parametrize("utility_name", ("nsight-sys", "nsight-compute"))
+@pytest.mark.usefixtures("clear_find_binary_cache")
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_find_windows_nsight_legacy_names_remain_literal_in_ctk(monkeypatch, mocker, utility_name):
+    cuda_home = os.path.join(os.sep, "cuda")
+    expected = os.path.join(cuda_home, "bin", f"{utility_name}.exe")
+
+    mocker.patch.object(binary_finder_module, "IS_WINDOWS", new=True)
+    mocker.patch.object(binary_finder_module.supported_nvidia_binaries, "SITE_PACKAGES_BINDIRS", {})
+    monkeypatch.delenv("CONDA_PREFIX", raising=False)
+    mocker.patch.object(binary_finder_module, "get_cuda_path_or_home", return_value=cuda_home)
+    nsys_candidates = mocker.patch.object(binary_finder_module.windows_nsight, "nsys_candidate_paths")
+    ncu_candidates = mocker.patch.object(binary_finder_module.windows_nsight, "ncu_candidate_paths")
+    canary = mocker.patch.object(binary_finder_module, "_resolve_ctk_root_via_canary")
+    checked = _patch_exec_probe(mocker, existing=[expected])
+
+    assert find_nvidia_binary_utility(utility_name) == os.path.abspath(expected)
+    assert checked == [
+        os.path.join(cuda_home, "bin", "x64", f"{utility_name}.exe"),
+        os.path.join(cuda_home, "bin", "x86_64", f"{utility_name}.exe"),
+        expected,
+    ]
+    nsys_candidates.assert_not_called()
+    ncu_candidates.assert_not_called()
+    canary.assert_not_called()
+
+
 @pytest.mark.usefixtures("clear_find_binary_cache")
 def test_find_binary_first_matching_dir_wins(monkeypatch, mocker):
     conda_prefix = os.path.join(os.sep, "conda")
diff --git a/cuda_pathfinder/tests/test_find_nvidia_headers.py b/cuda_pathfinder/tests/test_find_nvidia_headers.py
index 90fe3cf9815..9f10dc2bacf 100644
--- a/cuda_pathfinder/tests/test_find_nvidia_headers.py
+++ b/cuda_pathfinder/tests/test_find_nvidia_headers.py
@@ -20,13 +20,17 @@
 from pathlib import Path
 
 import pytest
+from conftest import skip_if_missing_libnvcudla_so
+from packaging.requirements import Requirement
+from packaging.version import Version
 
 import cuda.pathfinder._headers.find_nvidia_headers as find_nvidia_headers_module
-from conftest import skip_if_missing_libnvcudla_so
+import cuda.pathfinder._headers.header_descriptor as header_descriptor_module
 from cuda.pathfinder import LocatedHeaderDir, find_nvidia_header_directory, locate_nvidia_header_directory
 from cuda.pathfinder._dynamic_libs.load_nvidia_dynamic_lib import (
     _resolve_system_loaded_abs_path_in_subprocess,
 )
+from cuda.pathfinder._headers.header_descriptor import HEADER_DESCRIPTORS
 from cuda.pathfinder._headers.supported_nvidia_headers import (
     SUPPORTED_HEADERS_CTK,
     SUPPORTED_HEADERS_CTK_ALL,
@@ -43,6 +47,7 @@
 
 NON_CTK_IMPORTLIB_METADATA_DISTRIBUTIONS_NAMES = {
     "cudensitymat": r"^cudensitymat-.*$",
+    "cudnn": r"^nvidia-cudnn-cu(?:12|13)$",
     "cupauliprop": r"^cupauliprop-.*$",
     "cusolverMp": r"^nvidia-cusolvermp-.*$",
     "cusparseLt": r"^nvidia-cusparselt-.*$",
@@ -53,6 +58,7 @@
     "custatevec": r"^custatevec-.*$",
     "cutlass": r"^nvidia-cutlass$",
     "mathdx": r"^nvidia-libmathdx-.*$",
+    "nccl": r"^nvidia-nccl-.*$",
     "nvshmem": r"^nvidia-nvshmem-.*$",
 }
 
@@ -67,6 +73,8 @@ def _located_hdr_dir_asserts(located_hdr_dir):
     assert located_hdr_dir.found_via in (
         "site-packages",
         "conda",
+        "CUDNN_PATH",
+        "NCCL_HOME",
         "CUDA_PATH",
         "system-ctk-root",
         "supported_install_dir",
@@ -78,6 +86,35 @@ def test_non_ctk_importlib_metadata_distributions_names():
     assert sorted(NON_CTK_IMPORTLIB_METADATA_DISTRIBUTIONS_NAMES) == sorted(SUPPORTED_HEADERS_NON_CTK_ALL)
 
 
+@pytest.mark.agent_authored(model="gpt-5")
+def test_cudnn_and_nccl_header_metadata_matches_wheel_layouts():
+    cudnn = HEADER_DESCRIPTORS["cudnn"]
+    assert cudnn.header_basename == "cudnn.h"
+    assert cudnn.site_packages_dirs == ("nvidia/cudnn/include",)
+    assert cudnn.product_root_env_vars == ("CUDNN_PATH",)
+    assert cudnn.system_install_dirs == (
+        "/usr/include",
+        "/usr/local/include",
+    )
+    assert cudnn.system_install_dirs_windows == ("${ProgramFiles}/NVIDIA/CUDNN/v9.*/include",)
+    assert cudnn.use_linux_multiarch_include_dir
+    assert cudnn.available_on_linux
+    assert cudnn.available_on_windows
+    assert not cudnn.conda_targets_layout
+    assert not cudnn.use_ctk_root_canary
+
+    nccl = HEADER_DESCRIPTORS["nccl"]
+    assert nccl.header_basename == "nccl.h"
+    assert nccl.site_packages_dirs == ("nvidia/nccl/include",)
+    assert nccl.available_on_linux
+    assert not nccl.available_on_windows
+    assert nccl.anchor_include_rel_dirs == ("include", "build/include")
+    assert nccl.product_root_env_vars == ("NCCL_HOME",)
+    assert nccl.system_install_dirs == ("/usr/include", "/usr/local/include")
+    assert not nccl.conda_targets_layout
+    assert not nccl.use_ctk_root_canary
+
+
 @functools.cache
 def have_distribution_for(libname: str) -> bool:
     pattern = re.compile(NON_CTK_IMPORTLIB_METADATA_DISTRIBUTIONS_NAMES[libname])
@@ -86,6 +123,39 @@ def have_distribution_for(libname: str) -> bool:
     )
 
 
+@pytest.mark.parametrize(
+    ("distribution_name", "expected"),
+    [
+        ("nvidia-cudnn-cu12", True),
+        ("nvidia-cudnn-cu13", True),
+        ("nvidia-cudnn-frontend", False),
+        ("nvidia-cudnn-jit-cu12", False),
+        ("nvidia-cudnn-jit-cu13", False),
+    ],
+)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_cudnn_distribution_pattern_only_matches_backend_wheels(distribution_name, expected):
+    pattern = re.compile(NON_CTK_IMPORTLIB_METADATA_DISTRIBUTIONS_NAMES["cudnn"])
+
+    assert bool(pattern.match(distribution_name)) is expected
+
+
+@pytest.mark.parametrize(
+    "requirement",
+    ["nvidia-cudnn-cu12>=9,<10", "nvidia-cudnn-cu13>=9,<10"],
+)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_cudnn_test_dependencies_are_bounded_to_major_nine(requirement):
+    pyproject_text = (Path(__file__).parents[1] / "pyproject.toml").read_text(encoding="utf-8")
+    parsed = Requirement(requirement)
+
+    assert f'"{requirement}",' in pyproject_text
+    assert Version("8.9") not in parsed.specifier
+    assert Version("9.0") in parsed.specifier
+    assert Version("9.24.0.43") in parsed.specifier
+    assert Version("10.0") not in parsed.specifier
+
+
 @pytest.fixture
 def clear_locate_nvidia_header_cache():
     locate_nvidia_header_directory.cache_clear()
@@ -118,6 +188,104 @@ def _fake_cudart_canary_abs_path(ctk_root: Path) -> str:
     return str(ctk_root / "lib64" / "libcudart.so.13")
 
 
+@pytest.mark.parametrize(
+    ("libname", "env_var", "include_rel_dir"),
+    [
+        ("cudnn", "CUDNN_PATH", "include"),
+        ("nccl", "NCCL_HOME", "build/include"),
+    ],
+)
+@pytest.mark.usefixtures("clear_locate_nvidia_header_cache")
+@pytest.mark.agent_authored(model="gpt-5")
+def test_locate_non_ctk_headers_uses_product_root(tmp_path, monkeypatch, mocker, libname, env_var, include_rel_dir):
+    product_root = tmp_path / libname
+    header_dir = product_root / include_rel_dir
+    header_dir.mkdir(parents=True)
+    (header_dir / HEADER_DESCRIPTORS[libname].header_basename).touch()
+
+    monkeypatch.delenv("CONDA_PREFIX", raising=False)
+    monkeypatch.delenv("CUDNN_PATH", raising=False)
+    monkeypatch.delenv("NCCL_HOME", raising=False)
+    monkeypatch.setenv(env_var, str(product_root))
+    monkeypatch.setenv("CUDA_HOME", str(tmp_path / "unused-cuda-home"))
+    monkeypatch.delenv("CUDA_PATH", raising=False)
+    mocker.patch.object(find_nvidia_headers_module, "find_sub_dirs_all_sitepackages", return_value=[])
+
+    located_hdr_dir = locate_nvidia_header_directory(libname)
+
+    assert located_hdr_dir is not None
+    assert located_hdr_dir.abs_path == str(header_dir)
+    assert located_hdr_dir.found_via == env_var
+
+
+@pytest.mark.parametrize(
+    ("libname", "system_pattern"),
+    [
+        ("cudnn", "/usr/include"),
+        ("cudnn", "/usr/local/include"),
+        ("nccl", "/usr/include"),
+        ("nccl", "/usr/local/include"),
+    ],
+)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_find_in_system_install_dirs_uses_native_linux_layouts(tmp_path, mocker, libname, system_pattern):
+    header_dir = tmp_path / libname
+    header_dir.mkdir()
+    (header_dir / HEADER_DESCRIPTORS[libname].header_basename).touch()
+    mocker.patch.object(header_descriptor_module, "IS_WINDOWS", False)
+    glob_mock = mocker.patch.object(
+        find_nvidia_headers_module.glob,
+        "glob",
+        side_effect=lambda pattern: [str(header_dir)] if pattern == system_pattern else [],
+    )
+
+    located_hdr_dir = find_nvidia_headers_module.find_in_system_install_dirs(HEADER_DESCRIPTORS[libname])
+
+    assert located_hdr_dir is not None
+    assert located_hdr_dir.abs_path == str(header_dir)
+    assert located_hdr_dir.found_via == "supported_install_dir"
+    assert any(call.args == (system_pattern,) for call in glob_mock.call_args_list)
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_find_in_system_install_dirs_uses_running_linux_multiarch(tmp_path, mocker):
+    header_dir = tmp_path / "multiarch"
+    header_dir.mkdir()
+    (header_dir / "cudnn.h").touch()
+    mocker.patch.object(header_descriptor_module, "IS_WINDOWS", False)
+    mocker.patch.object(header_descriptor_module.sysconfig, "get_config_var", return_value="x86_64-linux-gnu")
+    expected_pattern = os.path.join("/usr/include", "x86_64-linux-gnu")
+    glob_mock = mocker.patch.object(
+        find_nvidia_headers_module.glob,
+        "glob",
+        side_effect=lambda pattern: [str(header_dir)] if pattern == expected_pattern else [],
+    )
+
+    located_hdr_dir = find_nvidia_headers_module.find_in_system_install_dirs(HEADER_DESCRIPTORS["cudnn"])
+
+    assert located_hdr_dir is not None
+    assert located_hdr_dir.abs_path == str(header_dir)
+    assert located_hdr_dir.found_via == "supported_install_dir"
+    assert glob_mock.call_args_list[0].args == (expected_pattern,)
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_find_in_system_install_dirs_expands_program_files_and_prefers_newest_cudnn(tmp_path, monkeypatch, mocker):
+    program_files = tmp_path / "Program Files"
+    older_header_dir = program_files / "NVIDIA" / "CUDNN" / "v9.9" / "include"
+    newer_header_dir = program_files / "NVIDIA" / "CUDNN" / "v9.10" / "include"
+    for header_dir in (older_header_dir, newer_header_dir):
+        header_dir.mkdir(parents=True)
+        (header_dir / "cudnn.h").touch()
+    mocker.patch.object(header_descriptor_module, "IS_WINDOWS", True)
+    monkeypatch.setenv("ProgramFiles", str(program_files))
+    located_hdr_dir = find_nvidia_headers_module.find_in_system_install_dirs(HEADER_DESCRIPTORS["cudnn"])
+
+    assert located_hdr_dir is not None
+    assert located_hdr_dir.abs_path == str(newer_header_dir)
+    assert located_hdr_dir.found_via == "supported_install_dir"
+
+
 # TODO: remove the Python 3.15 guard once 3.15 is officially supported
 _CUTLASS_SKIP = pytest.mark.skipif(
     sys.version_info >= (3, 15),
@@ -138,21 +306,25 @@ def test_locate_non_ctk_headers(info_summary_append, libname):
     info_summary_append(f"{hdr_dir=!r}")
     if hdr_dir:
         _located_hdr_dir_asserts(located_hdr_dir)
-        assert os.path.isdir(hdr_dir)
-        assert os.path.isfile(os.path.join(hdr_dir, SUPPORTED_HEADERS_NON_CTK[libname]))
+        hdr_dir_path = Path(hdr_dir)
+        assert hdr_dir_path.is_dir()
+        assert (hdr_dir_path / SUPPORTED_HEADERS_NON_CTK[libname]).is_file()
     if have_distribution_for(libname):
         assert hdr_dir is not None
-        hdr_dir_parts = hdr_dir.split(os.path.sep)
-        assert "site-packages" in hdr_dir_parts
+        assert "site-packages" in Path(hdr_dir).parts
     elif STRICTNESS == "all_must_work":
         assert hdr_dir is not None
-        if conda_prefix := os.environ.get("CONDA_PREFIX"):
+        if located_hdr_dir.found_via in HEADER_DESCRIPTORS[libname].product_root_env_vars:
+            assert hdr_dir.startswith(os.environ[located_hdr_dir.found_via])
+        elif conda_prefix := os.environ.get("CONDA_PREFIX"):
             assert hdr_dir.startswith(conda_prefix)
         else:
             inst_dirs = SUPPORTED_INSTALL_DIRS_NON_CTK.get(libname)
             if inst_dirs is not None:
                 for inst_dir in inst_dirs:
-                    globbed = glob.glob(inst_dir)
+                    # Absolute glob pattern: Path.glob needs a separate base dir,
+                    # and the wildcard is not pinned to the last component.
+                    globbed = glob.glob(os.path.expandvars(inst_dir))
                     if hdr_dir in globbed:
                         break
                 else:
@@ -172,9 +344,10 @@ def test_locate_ctk_headers(info_summary_append, libname):
     info_summary_append(f"{hdr_dir=!r}")
     if hdr_dir:
         _located_hdr_dir_asserts(located_hdr_dir)
-        assert os.path.isdir(hdr_dir)
+        hdr_dir_path = Path(hdr_dir)
+        assert hdr_dir_path.is_dir()
         h_filename = SUPPORTED_HEADERS_CTK[libname]
-        assert os.path.isfile(os.path.join(hdr_dir, h_filename))
+        assert (hdr_dir_path / h_filename).is_file()
     if STRICTNESS == "all_must_work":
         if libname == "cudla":
             skip_if_missing_libnvcudla_so(libname, timeout=30)
diff --git a/cuda_pathfinder/tests/test_find_static_lib.py b/cuda_pathfinder/tests/test_find_static_lib.py
index e5560dcabbf..cf0e62dc8a2 100644
--- a/cuda_pathfinder/tests/test_find_static_lib.py
+++ b/cuda_pathfinder/tests/test_find_static_lib.py
@@ -52,7 +52,7 @@ def _located_static_lib_asserts(located_static_lib):
     assert isinstance(located_static_lib.filename, str)
     assert isinstance(located_static_lib.found_via, str)
     assert located_static_lib.found_via in ("site-packages", "conda", "CUDA_PATH")
-    assert os.path.isfile(located_static_lib.abs_path)
+    assert Path(located_static_lib.abs_path).is_file()
 
 
 @pytest.mark.usefixtures("clear_find_static_lib_cache")
@@ -69,10 +69,10 @@ def test_locate_static_lib(info_summary_append, libname):
 
     info_summary_append(f"abs_path={quote_for_shell(lib_path)}")
     _located_static_lib_asserts(located_lib)
-    assert os.path.isfile(lib_path)
+    assert Path(lib_path).is_file()
     assert lib_path == located_lib.abs_path
     expected_filename = located_lib.filename
-    assert os.path.basename(lib_path) == expected_filename
+    assert Path(lib_path).name == expected_filename
 
 
 @pytest.mark.usefixtures("clear_find_static_lib_cache")
@@ -81,7 +81,7 @@ def test_locate_static_lib_search_order(monkeypatch, tmp_path):
     conda_rel_path = CUDADEVRT_INFO["conda_rel_paths"][0]
 
     site_pkg_rel = CUDADEVRT_INFO["site_packages_dirs"][0]
-    site_packages_lib_dir = tmp_path / "site-packages" / Path(site_pkg_rel.replace("/", os.sep))
+    site_packages_lib_dir = tmp_path / "site-packages" / Path(site_pkg_rel)
     site_packages_path = _make_static_lib_file(site_packages_lib_dir, filename)
 
     conda_prefix = tmp_path / "conda-prefix"
@@ -143,6 +143,41 @@ def test_locate_static_lib_conda_rel_path_fallback(monkeypatch, tmp_path):
     assert located_lib.found_via == "conda"
 
 
+@pytest.mark.parametrize(
+    ("target_arch", "expected_ctk_dirs", "expected_conda_dirs", "expected_site_packages_dirs"),
+    (
+        (
+            "x64",
+            (os.path.join("lib", "x64"),),
+            (os.path.join("lib", "x64"), "lib"),
+            ("nvidia/cu13/lib/x64", "nvidia/cuda_runtime/lib/x64"),
+        ),
+        (
+            "arm64",
+            (os.path.join("lib", "arm64"),),
+            (os.path.join("lib", "arm64"),),
+            ("nvidia/cu13/lib/arm64",),
+        ),
+    ),
+)
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_cudadevrt_windows_paths_follow_python_arch(
+    monkeypatch,
+    target_arch,
+    expected_ctk_dirs,
+    expected_conda_dirs,
+    expected_site_packages_dirs,
+):
+    monkeypatch.setattr(find_static_lib_module, "IS_WINDOWS", True)
+    monkeypatch.setattr(find_static_lib_module, "windows_python_arch", lambda: target_arch)
+
+    info = find_static_lib_module._cudadevrt_info()
+
+    assert info["ctk_rel_paths"] == expected_ctk_dirs
+    assert info["conda_rel_paths"] == expected_conda_dirs
+    assert info["site_packages_dirs"] == expected_site_packages_dirs
+
+
 @pytest.mark.usefixtures("clear_find_static_lib_cache")
 def test_find_static_lib_not_found_error_includes_cuda_home_directory_listing(monkeypatch, tmp_path):
     filename = CUDADEVRT_INFO["filename"]
@@ -167,7 +202,7 @@ def test_find_static_lib_not_found_error_includes_cuda_home_directory_listing(mo
         find_static_lib("cudadevrt")
 
     message = str(exc_info.value)
-    expected_missing_file = os.path.join(str(lib_dir), filename)
+    expected_missing_file = lib_dir / filename
     assert f"No such file: {expected_missing_file}" in message
     assert f'listdir("{lib_dir}"):' in message
     assert "README.txt" in message
diff --git a/cuda_pathfinder/tests/test_lib_descriptor.py b/cuda_pathfinder/tests/test_lib_descriptor.py
index cda96131e13..d56ee464378 100644
--- a/cuda_pathfinder/tests/test_lib_descriptor.py
+++ b/cuda_pathfinder/tests/test_lib_descriptor.py
@@ -1,8 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-"""Tests verifying that the LibDescriptor registry faithfully represents
-the existing data tables in supported_nvidia_libs.py."""
+"""Tests for the canonical library descriptors and their legacy projections."""
 
 import pytest
 
@@ -13,10 +12,21 @@
     LIBNAMES_REQUIRING_RTLD_DEEPBIND,
     SITE_PACKAGES_LIBDIRS_LINUX,
     SITE_PACKAGES_LIBDIRS_WINDOWS,
+    SITE_PACKAGES_LIBDIRS_WINDOWS_ARM64,
+    SITE_PACKAGES_LIBDIRS_WINDOWS_CTK,
+    SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_X64,
+    SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER,
+    SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER_X64,
+    SITE_PACKAGES_LIBDIRS_WINDOWS_X64,
     SUPPORTED_LIBNAMES,
+    SUPPORTED_LIBNAMES_LINUX,
+    SUPPORTED_LIBNAMES_WINDOWS,
+    SUPPORTED_LIBNAMES_WINDOWS_ARM64,
+    SUPPORTED_LIBNAMES_WINDOWS_X64,
     SUPPORTED_LINUX_SONAMES,
     SUPPORTED_WINDOWS_DLLS,
 )
+from cuda.pathfinder._utils.platform_aware import IS_WINDOWS, IS_WINDOWS_ARM64, IS_WINDOWS_X64
 
 # ---------------------------------------------------------------------------
 # Registry completeness
@@ -43,12 +53,12 @@ def test_registry_has_no_extra_entries():
 
 @pytest.mark.parametrize("name", sorted(LIB_DESCRIPTORS))
 def test_linux_sonames_match(name):
-    assert LIB_DESCRIPTORS[name].linux_sonames == SUPPORTED_LINUX_SONAMES.get(name, ())
+    assert tuple(reversed(LIB_DESCRIPTORS[name].linux_sonames)) == SUPPORTED_LINUX_SONAMES.get(name, ())
 
 
 @pytest.mark.parametrize("name", sorted(LIB_DESCRIPTORS))
 def test_windows_dlls_match(name):
-    assert LIB_DESCRIPTORS[name].windows_dlls == SUPPORTED_WINDOWS_DLLS.get(name, ())
+    assert tuple(reversed(LIB_DESCRIPTORS[name].windows_dlls)) == SUPPORTED_WINDOWS_DLLS.get(name, ())
 
 
 @pytest.mark.parametrize("name", sorted(LIB_DESCRIPTORS))
@@ -56,9 +66,49 @@ def test_site_packages_linux_match(name):
     assert LIB_DESCRIPTORS[name].site_packages_linux == SITE_PACKAGES_LIBDIRS_LINUX.get(name, ())
 
 
+@pytest.mark.parametrize(
+    ("target_arch", "site_packages_libdirs"),
+    [
+        ("x64", SITE_PACKAGES_LIBDIRS_WINDOWS_X64),
+        ("arm64", SITE_PACKAGES_LIBDIRS_WINDOWS_ARM64),
+    ],
+)
 @pytest.mark.parametrize("name", sorted(LIB_DESCRIPTORS))
-def test_site_packages_windows_match(name):
-    assert LIB_DESCRIPTORS[name].site_packages_windows == SITE_PACKAGES_LIBDIRS_WINDOWS.get(name, ())
+@pytest.mark.agent_authored(model="gpt-5")
+def test_site_packages_windows_match(name, target_arch, site_packages_libdirs):
+    assert LIB_DESCRIPTORS[name].site_packages_windows.for_arch(target_arch) == site_packages_libdirs.get(name, ())
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_legacy_site_packages_windows_tables_are_x64_aliases():
+    assert SITE_PACKAGES_LIBDIRS_WINDOWS_CTK is SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_X64
+    assert SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER is SITE_PACKAGES_LIBDIRS_WINDOWS_OTHER_X64
+    assert SITE_PACKAGES_LIBDIRS_WINDOWS is SITE_PACKAGES_LIBDIRS_WINDOWS_X64
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_legacy_supported_libnames_windows_is_x64_alias():
+    assert SUPPORTED_LIBNAMES_WINDOWS is SUPPORTED_LIBNAMES_WINDOWS_X64
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_supported_libnames_selects_current_platform_and_arch():
+    if not IS_WINDOWS:
+        expected = SUPPORTED_LIBNAMES_LINUX
+    elif IS_WINDOWS_X64:
+        expected = SUPPORTED_LIBNAMES_WINDOWS_X64
+    else:
+        assert IS_WINDOWS_ARM64
+        expected = SUPPORTED_LIBNAMES_WINDOWS_ARM64
+    assert SUPPORTED_LIBNAMES is expected
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_arch_specific_ctk_libname_projections():
+    assert "cudla" not in SUPPORTED_LIBNAMES_WINDOWS_X64
+    assert "cudla" in SUPPORTED_LIBNAMES_WINDOWS_ARM64
+    assert "nvjpeg" in SUPPORTED_LIBNAMES_WINDOWS_X64
+    assert "nvjpeg" in SUPPORTED_LIBNAMES_WINDOWS_ARM64
 
 
 @pytest.mark.parametrize("name", sorted(LIB_DESCRIPTORS))
@@ -102,3 +152,38 @@ def test_descriptor_is_frozen():
     desc = LIB_DESCRIPTORS["cudart"]
     with pytest.raises(AttributeError):
         desc.name = "bogus"  # type: ignore[misc]
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_linux_sonames_are_authored_in_runtime_preference_order():
+    desc = LIB_DESCRIPTORS["cudart"]
+
+    assert desc.linux_sonames == ("libcudart.so.13", "libcudart.so.12")
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_linux_sonames_preserve_explicit_unversioned_name():
+    desc = LIB_DESCRIPTORS["nvcudla"]
+
+    assert desc.linux_sonames == ("libnvcudla.so",)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_linux_sonames_prefer_versioned_name_over_declared_unversioned_name():
+    desc = LIB_DESCRIPTORS["nvvm"]
+
+    assert desc.linux_sonames == ("libnvvm.so.4", "libnvvm.so")
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_windows_dlls_are_authored_in_runtime_preference_order():
+    desc = LIB_DESCRIPTORS["nvvm"]
+
+    assert desc.windows_dlls == ("nvvm70.dll", "nvvm64_40_0.dll", "nvvm64.dll")
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_cufft_mp_sonames_preserve_abi_preference():
+    desc = LIB_DESCRIPTORS["cufftMp"]
+
+    assert desc.linux_sonames == ("libcufftMp.so.12", "libcufftMp.so.11")
diff --git a/cuda_pathfinder/tests/test_load_dl_common.py b/cuda_pathfinder/tests/test_load_dl_common.py
new file mode 100644
index 00000000000..61a204c41ee
--- /dev/null
+++ b/cuda_pathfinder/tests/test_load_dl_common.py
@@ -0,0 +1,88 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import pytest
+
+from cuda.pathfinder._dynamic_libs.descriptor_catalog import DescriptorSpec
+from cuda.pathfinder._dynamic_libs.load_dl_common import (
+    DynamicLibNotAvailableError,
+    DynamicLibNotFoundError,
+    DynamicLibUnknownError,
+    LoadedDL,
+    load_dependencies,
+)
+
+
+def _loaded(name: str) -> LoadedDL:
+    return LoadedDL(f"/{name}", False, 1, "test")
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_load_dependencies_loads_required_then_optional_dependencies():
+    desc = DescriptorSpec(
+        name="subject",
+        packaged_with="other",
+        dependencies=("required",),
+        optional_dependencies=("optional",),
+    )
+    calls = []
+
+    def load_func(name):
+        calls.append(name)
+        return _loaded(name)
+
+    load_dependencies(desc, load_func)
+
+    assert calls == ["required", "optional"]
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_load_dependencies_continues_after_optional_dependency_is_absent():
+    desc = DescriptorSpec(
+        name="subject",
+        packaged_with="other",
+        optional_dependencies=("absent", "available"),
+    )
+    calls = []
+
+    def load_func(name):
+        calls.append(name)
+        if name == "absent":
+            raise DynamicLibNotFoundError(name)
+        return _loaded(name)
+
+    load_dependencies(desc, load_func)
+
+    assert calls == ["absent", "available"]
+
+
+@pytest.mark.parametrize("error_type", (DynamicLibUnknownError, DynamicLibNotAvailableError, RuntimeError))
+@pytest.mark.agent_authored(model="gpt-5")
+def test_load_dependencies_propagates_malformed_or_unloadable_optional_dependency(error_type):
+    desc = DescriptorSpec(name="subject", packaged_with="other", optional_dependencies=("broken",))
+
+    def load_func(name):
+        raise error_type(name)
+
+    with pytest.raises(error_type):
+        load_dependencies(desc, load_func)
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_load_dependencies_keeps_required_dependencies_fail_fast():
+    desc = DescriptorSpec(
+        name="subject",
+        packaged_with="other",
+        dependencies=("required",),
+        optional_dependencies=("optional",),
+    )
+    calls = []
+
+    def load_func(name):
+        calls.append(name)
+        raise DynamicLibNotFoundError(name)
+
+    with pytest.raises(DynamicLibNotFoundError):
+        load_dependencies(desc, load_func)
+
+    assert calls == ["required"]
diff --git a/cuda_pathfinder/tests/test_load_dl_linux.py b/cuda_pathfinder/tests/test_load_dl_linux.py
new file mode 100644
index 00000000000..df7b1718a1b
--- /dev/null
+++ b/cuda_pathfinder/tests/test_load_dl_linux.py
@@ -0,0 +1,56 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import os
+import sys
+
+import pytest
+
+if sys.platform != "linux":
+    pytest.skip("Linux dynamic-loader tests", allow_module_level=True)
+
+from cuda.pathfinder._dynamic_libs import load_dl_linux
+from cuda.pathfinder._dynamic_libs.descriptor_catalog import DescriptorSpec
+
+
+def _descriptor() -> DescriptorSpec:
+    return DescriptorSpec(
+        name="probe",
+        packaged_with="other",
+        linux_sonames=("libprobe.so.13", "libprobe.so.12"),
+    )
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_already_loaded_library_checks_declared_sonames_in_preference_order(mocker):
+    queried_sonames: list[tuple[str, int]] = []
+
+    def cdll(soname, mode):
+        queried_sonames.append((soname, mode))
+        raise OSError
+
+    mocker.patch.object(load_dl_linux.ctypes, "CDLL", side_effect=cdll)
+
+    loaded = load_dl_linux.check_if_already_loaded_from_elsewhere(_descriptor())
+
+    assert loaded is None
+    assert queried_sonames == [
+        ("libprobe.so.13", os.RTLD_NOLOAD),
+        ("libprobe.so.12", os.RTLD_NOLOAD),
+    ]
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_system_search_checks_declared_sonames_in_preference_order(mocker):
+    queried_sonames: list[str] = []
+
+    def load_lib(_desc, soname):
+        queried_sonames.append(soname)
+        raise OSError
+
+    mocker.patch.object(load_dl_linux, "_load_lib", side_effect=load_lib)
+
+    loaded = load_dl_linux.load_with_system_search(_descriptor())
+
+    assert loaded is None
+    assert queried_sonames == ["libprobe.so.13", "libprobe.so.12"]
diff --git a/cuda_pathfinder/tests/test_load_dl_windows.py b/cuda_pathfinder/tests/test_load_dl_windows.py
new file mode 100644
index 00000000000..28a2e51b368
--- /dev/null
+++ b/cuda_pathfinder/tests/test_load_dl_windows.py
@@ -0,0 +1,82 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import sys
+
+import pytest
+
+if sys.platform != "win32":
+    pytest.skip("Windows dynamic-loader tests", allow_module_level=True)
+
+from cuda.pathfinder._dynamic_libs import load_dl_windows
+from cuda.pathfinder._dynamic_libs.lib_descriptor import LIB_DESCRIPTORS
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_already_loaded_library_checks_known_dlls_in_preference_order(mocker):
+    desc = LIB_DESCRIPTORS["cublasLt"]
+    preferred_dll = desc.windows_dlls[0]
+    fallback_dll = desc.windows_dlls[-1]
+    queried_dlls: list[str] = []
+    handle = 0xBEEF
+
+    def get_module_handle(dll_name):
+        queried_dlls.append(dll_name)
+        return handle if dll_name == fallback_dll else 0
+
+    mocker.patch.object(load_dl_windows.kernel32, "GetModuleHandleW", side_effect=get_module_handle)
+    mocker.patch.object(
+        load_dl_windows,
+        "abs_path_for_dynamic_library",
+        return_value=rf"C:\CUDA\bin\{fallback_dll}",
+    )
+
+    loaded = load_dl_windows.check_if_already_loaded_from_elsewhere(desc)
+
+    assert loaded is not None
+    assert queried_dlls == list(desc.windows_dlls)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_system_search_checks_known_dlls_in_preference_order(mocker):
+    desc = LIB_DESCRIPTORS["cublasLt"]
+    queried_dlls: list[str] = []
+
+    def load_library(dll_name, _file, _flags):
+        queried_dlls.append(dll_name)
+        return 0
+
+    mocker.patch.object(load_dl_windows.kernel32, "LoadLibraryExW", side_effect=load_library)
+
+    loaded = load_dl_windows.load_with_system_search(desc)
+
+    assert loaded is None
+    assert queried_dlls == list(desc.windows_dlls)
+
+
+@pytest.mark.parametrize(
+    ("libname", "register_directory"),
+    (("cudnn", True), ("cublasLt", False)),
+)
+@pytest.mark.agent_authored(model="gpt-5.6-sol")
+def test_already_loaded_library_registers_resolved_directory_by_descriptor_policy(
+    mocker, tmp_path, libname, register_directory
+):
+    desc = LIB_DESCRIPTORS[libname]
+    resolved_path = str(tmp_path / desc.windows_dlls[0])
+    handle = 0xBEEF
+    mocker.patch.object(load_dl_windows.kernel32, "GetModuleHandleW", return_value=handle)
+    mocker.patch.object(load_dl_windows, "abs_path_for_dynamic_library", return_value=resolved_path)
+    add_dll_directory = mocker.patch.object(load_dl_windows, "add_dll_directory")
+
+    loaded = load_dl_windows.check_if_already_loaded_from_elsewhere(desc)
+
+    assert loaded is not None
+    assert loaded.abs_path == resolved_path
+    assert loaded.was_already_loaded_from_elsewhere
+    assert loaded._handle_uint == handle
+    assert loaded.found_via == "was-already-loaded-from-elsewhere"
+    if register_directory:
+        add_dll_directory.assert_called_once_with(resolved_path)
+    else:
+        add_dll_directory.assert_not_called()
diff --git a/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib.py b/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib.py
index 3e240dcf468..f08d100a1ae 100644
--- a/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib.py
+++ b/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib.py
@@ -3,15 +3,16 @@
 
 import os
 import platform
+from pathlib import Path
 
 import pytest
 from child_load_nvidia_dynamic_lib_helper import (
     build_child_process_failed_for_libname_message,
     run_load_nvidia_dynamic_lib_in_subprocess,
 )
+from conftest import skip_if_missing_libnvcudla_so
 from local_helpers import have_distribution
 
-from conftest import skip_if_missing_libnvcudla_so
 from cuda.pathfinder import DynamicLibNotAvailableError, DynamicLibUnknownError, load_nvidia_dynamic_lib
 from cuda.pathfinder._dynamic_libs import load_nvidia_dynamic_lib as load_nvidia_dynamic_lib_module
 from cuda.pathfinder._dynamic_libs import supported_nvidia_libs
@@ -25,32 +26,49 @@
 assert STRICTNESS in ("see_what_works", "all_must_work")
 
 
+@pytest.mark.agent_authored(model="gpt-5")
+def test_loader_uses_all_available_libnames():
+    assert supported_nvidia_libs.ALL_AVAILABLE_LIBNAMES == load_nvidia_dynamic_lib_module.ALL_AVAILABLE_LIBNAMES
+
+
 def test_supported_libnames_linux_sonames_consistency():
     assert tuple(sorted(supported_nvidia_libs.SUPPORTED_LIBNAMES_LINUX)) == tuple(
         sorted(supported_nvidia_libs.SUPPORTED_LINUX_SONAMES_CTK.keys())
     )
 
 
-def test_supported_libnames_windows_dlls_consistency():
-    assert tuple(sorted(supported_nvidia_libs.SUPPORTED_LIBNAMES_WINDOWS)) == tuple(
-        sorted(supported_nvidia_libs.SUPPORTED_WINDOWS_DLLS_CTK.keys())
-    )
-
-
 def test_supported_libnames_linux_site_packages_libdirs_ctk_consistency():
     assert tuple(sorted(supported_nvidia_libs.SUPPORTED_LIBNAMES_LINUX)) == tuple(
         sorted(supported_nvidia_libs.SITE_PACKAGES_LIBDIRS_LINUX_CTK.keys())
     )
 
 
-def test_supported_libnames_windows_site_packages_libdirs_ctk_consistency():
+@pytest.mark.parametrize(
+    ("site_packages_libdirs", "supported_libnames"),
+    [
+        pytest.param(
+            supported_nvidia_libs.SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_X64,
+            supported_nvidia_libs.SUPPORTED_LIBNAMES_WINDOWS_X64,
+            id="x64",
+        ),
+        pytest.param(
+            supported_nvidia_libs.SITE_PACKAGES_LIBDIRS_WINDOWS_CTK_ARM64,
+            supported_nvidia_libs.SUPPORTED_LIBNAMES_WINDOWS_ARM64,
+            id="arm64",
+        ),
+    ],
+)
+@pytest.mark.human_reviewed
+def test_supported_libnames_windows_site_packages_libdirs_ctk_consistency(
+    site_packages_libdirs,
+    supported_libnames,
+):
     # Not every Windows CTK library ships in a pip wheel (e.g. cudla is loaded
     # from the local CUDA Toolkit only), so a library may legitimately omit
     # site_packages_windows. Only assert that every site-packages entry maps to
     # a supported Windows libname, not the other way around.
-    site_packages_libnames = set(supported_nvidia_libs.SITE_PACKAGES_LIBDIRS_WINDOWS_CTK.keys())
-    supported_libnames = set(supported_nvidia_libs.SUPPORTED_LIBNAMES_WINDOWS)
-    assert site_packages_libnames <= supported_libnames
+    site_packages_libnames = set(site_packages_libdirs)
+    assert site_packages_libnames <= set(supported_libnames)
 
 
 @pytest.mark.parametrize("dict_name", ["SUPPORTED_LINUX_SONAMES", "SUPPORTED_WINDOWS_DLLS"])
@@ -68,7 +86,7 @@ def test_libname_dict_values_are_unique(dict_name):
 def test_supported_libnames_windows_libnames_requiring_os_add_dll_directory_consistency():
     assert not (
         set(supported_nvidia_libs.LIBNAMES_REQUIRING_OS_ADD_DLL_DIRECTORY)
-        - set(supported_nvidia_libs.SUPPORTED_LIBNAMES_WINDOWS)
+        - set(supported_nvidia_libs.SUPPORTED_WINDOWS_DLLS)
     )
 
 
@@ -88,7 +106,7 @@ def test_unknown_libname_raises_dynamic_lib_unknown_error():
 def test_known_but_platform_unavailable_libname_raises_dynamic_lib_not_available_error(monkeypatch):
     load_nvidia_dynamic_lib.cache_clear()
     monkeypatch.setattr(load_nvidia_dynamic_lib_module, "_ALL_KNOWN_LIBNAMES", frozenset(("known_but_unavailable",)))
-    monkeypatch.setattr(load_nvidia_dynamic_lib_module, "_ALL_SUPPORTED_LIBNAMES", frozenset())
+    monkeypatch.setattr(load_nvidia_dynamic_lib_module, "ALL_AVAILABLE_LIBNAMES", frozenset())
     monkeypatch.setattr(load_nvidia_dynamic_lib_module, "_PLATFORM_NAME", "TestOS")
     with pytest.raises(
         DynamicLibNotAvailableError,
@@ -142,4 +160,4 @@ def raise_child_process_failed():
         abs_path = payload.abs_path
         assert abs_path is not None
         info_summary_append(f"abs_path={quote_for_shell(abs_path)}")
-        assert os.path.isfile(abs_path)  # double-check the abs_path
+        assert Path(abs_path).is_file()  # double-check the abs_path
diff --git a/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib_using_mocker.py b/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib_using_mocker.py
index f46ad43356b..09c8bd3ea61 100644
--- a/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib_using_mocker.py
+++ b/cuda_pathfinder/tests/test_load_nvidia_dynamic_lib_using_mocker.py
@@ -10,7 +10,8 @@
     _load_lib_no_cache,
     _resolve_system_loaded_abs_path_in_subprocess,
 )
-from cuda.pathfinder._dynamic_libs.search_steps import EARLY_FIND_STEPS
+from cuda.pathfinder._dynamic_libs.search_platform import WindowsSearchPlatform
+from cuda.pathfinder._dynamic_libs.search_steps import EARLY_FIND_STEPS, SearchContext
 from cuda.pathfinder._utils.platform_aware import IS_WINDOWS
 
 _MODULE = "cuda.pathfinder._dynamic_libs.load_nvidia_dynamic_lib"
@@ -45,6 +46,45 @@ def _create_cupti_in_ctk(ctk_root):
     return cupti_lib
 
 
+# ---------------------------------------------------------------------------
+# cuDNN Windows ARM64 archive
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_cudnn_arm64_archive_layout_reaches_loader(tmp_path, mocker, monkeypatch):
+    bin_dir = tmp_path / "bin" / "arm64"
+    bin_dir.mkdir(parents=True)
+    dll = bin_dir / "cudnn64_9.dll"
+    dll.touch()
+    monkeypatch.delenv("CONDA_PREFIX", raising=False)
+    monkeypatch.setenv("CUDNN_PATH", str(tmp_path))
+
+    desc = load_mod.LIB_DESCRIPTORS["cudnn"]
+    ctx = SearchContext(desc, platform=WindowsSearchPlatform(target_arch="arm64"))
+    mocker.patch(f"{_MODULE}.SearchContext", return_value=ctx)
+    mocker.patch.object(load_mod.LOADER, "check_if_already_loaded_from_elsewhere", return_value=None)
+
+    def _load_dependency(name):
+        if name == "nvrtc":
+            raise DynamicLibNotFoundError(name)
+        return _make_loaded_dl(name, "dependency")
+
+    load_dependency = mocker.patch(f"{_MODULE}.load_nvidia_dynamic_lib", side_effect=_load_dependency)
+    mocker.patch.object(load_mod.LOADER, "load_with_system_search", return_value=None)
+    load_with_abs_path = mocker.patch.object(
+        load_mod.LOADER,
+        "load_with_abs_path",
+        side_effect=lambda _desc, path, via: _make_loaded_dl(path, via),
+    )
+
+    result = _load_lib_no_cache("cudnn")
+
+    assert result == _make_loaded_dl(str(dll), "CUDNN_PATH")
+    assert [call.args for call in load_dependency.call_args_list] == [("cublasLt",), ("nvrtc",)]
+    load_with_abs_path.assert_called_once_with(desc, str(dll), "CUDNN_PATH")
+
+
 # ---------------------------------------------------------------------------
 # Conda tests
 # Note: Site-packages and CTK are covered by real CI tests.
diff --git a/cuda_pathfinder/tests/test_search_steps.py b/cuda_pathfinder/tests/test_search_steps.py
index 1b881707dfb..5fa194d544a 100644
--- a/cuda_pathfinder/tests/test_search_steps.py
+++ b/cuda_pathfinder/tests/test_search_steps.py
@@ -5,13 +5,22 @@
 
 from __future__ import annotations
 
+import ctypes
 import os
+from ctypes import wintypes
 
 import pytest
 
+from cuda.pathfinder import UnsupportedArchError
+from cuda.pathfinder._dynamic_libs import search_platform as search_platform_mod
+from cuda.pathfinder._dynamic_libs.descriptor_catalog import WindowsSearchDirs
 from cuda.pathfinder._dynamic_libs.lib_descriptor import LIB_DESCRIPTORS, LibDescriptor
 from cuda.pathfinder._dynamic_libs.load_dl_common import DynamicLibNotFoundError
-from cuda.pathfinder._dynamic_libs.search_platform import LinuxSearchPlatform, WindowsSearchPlatform
+from cuda.pathfinder._dynamic_libs.search_platform import (
+    LinuxSearchPlatform,
+    WindowsSearchPlatform,
+    _find_descriptor_dll_under_dir,
+)
 from cuda.pathfinder._dynamic_libs.search_steps import (
     EARLY_FIND_STEPS,
     LATE_FIND_STEPS,
@@ -20,9 +29,12 @@
     _find_lib_dir_using_anchor,
     find_in_conda,
     find_in_cuda_path,
+    find_in_install_root_env_vars,
+    find_in_program_files_roots,
     find_in_site_packages,
     run_find_steps,
 )
+from cuda.pathfinder._utils import windows_arch as windows_arch_mod
 
 _STEPS_MOD = "cuda.pathfinder._dynamic_libs.search_steps"
 _PLAT_MOD = "cuda.pathfinder._dynamic_libs.search_platform"
@@ -40,7 +52,10 @@ def _make_desc(name: str = "cudart", **overrides) -> LibDescriptor:
         "linux_sonames": ("libcudart.so",),
         "windows_dlls": ("cudart64_12.dll",),
         "site_packages_linux": (os.path.join("nvidia", "cuda_runtime", "lib"),),
-        "site_packages_windows": (os.path.join("nvidia", "cuda_runtime", "bin"),),
+        "site_packages_windows": WindowsSearchDirs(
+            x64=(os.path.join("nvidia", "cuda_runtime", "bin"),),
+            arm64=(os.path.join("nvidia", "cuda_runtime", "bin"),),
+        ),
     }
     defaults.update(overrides)
     return LibDescriptor(**defaults)
@@ -52,6 +67,23 @@ def _ctx(desc: LibDescriptor | None = None, *, platform=None) -> SearchContext:
     return SearchContext(desc or _make_desc(), platform=platform)
 
 
+def _patch_site_packages_search(mocker, root):
+    def _find_sub_dirs(sub_dirs):
+        path = root.joinpath(*sub_dirs)
+        return [str(path)] if path.is_dir() else []
+
+    return mocker.patch(f"{_PLAT_MOD}.find_sub_dirs_all_sitepackages", side_effect=_find_sub_dirs)
+
+
+def _write_pe(path, machine):
+    image = bytearray(0x86)
+    image[:2] = b"MZ"
+    image[0x3C:0x40] = (0x80).to_bytes(4, "little")
+    image[0x80:0x84] = b"PE\0\0"
+    image[0x84:0x86] = machine.to_bytes(2, "little")
+    path.write_bytes(image)
+
+
 # ---------------------------------------------------------------------------
 # SearchContext
 # ---------------------------------------------------------------------------
@@ -63,16 +95,16 @@ def test_libname_delegates_to_descriptor(self):
         assert ctx.libname == "nvrtc"
 
     def test_lib_searched_for_linux(self):
-        ctx = SearchContext(_make_desc(name="cublas"), platform=LinuxSearchPlatform())
-        assert ctx.lib_searched_for == "libcublas.so"
+        ctx = SearchContext(LIB_DESCRIPTORS["cublas"], platform=LinuxSearchPlatform())
+        assert ctx.lib_searched_for == "libcublas.so.13 or libcublas.so.12"
 
     def test_lib_searched_for_windows(self):
-        ctx = SearchContext(_make_desc(name="cublas"), platform=WindowsSearchPlatform())
-        assert ctx.lib_searched_for == "cublas*.dll"
+        ctx = SearchContext(_make_desc(name="cublas"), platform=WindowsSearchPlatform(target_arch="x64"))
+        assert ctx.lib_searched_for == "known cublas DLL"
 
     def test_raise_not_found_includes_messages(self):
         ctx = _ctx()
-        ctx.error_messages.append("No such file: libcudart.so*")
+        ctx.error_messages.append("No such file: libcudart.so")
         ctx.attachments.append('  listdir("/some/dir"):')
         with pytest.raises(DynamicLibNotFoundError, match="No such file"):
             ctx.raise_not_found()
@@ -83,6 +115,150 @@ def test_raise_not_found_empty_messages(self):
             ctx.raise_not_found()
 
 
+# ---------------------------------------------------------------------------
+# Windows Python architecture detection
+# ---------------------------------------------------------------------------
+
+
+class TestWindowsPythonArch:
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_linux_platform_does_not_detect_windows_arch(self, mocker):
+        mocker.patch.object(search_platform_mod, "IS_WINDOWS", False)
+        get_windows_arch = mocker.patch.object(search_platform_mod, "windows_python_arch")
+
+        platform = search_platform_mod._platform_for_current_system()
+
+        assert isinstance(platform, LinuxSearchPlatform)
+        get_windows_arch.assert_not_called()
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_detects_sysconfig_x64(self, mocker):
+        mocker.patch.object(windows_arch_mod.sysconfig, "get_platform", return_value="win-amd64")
+
+        assert windows_arch_mod.windows_python_arch() == "x64"
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_detects_sysconfig_arm64(self, mocker):
+        mocker.patch.object(windows_arch_mod.sysconfig, "get_platform", return_value="win-arm64")
+
+        assert windows_arch_mod.windows_python_arch() == "arm64"
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_rejects_unknown_sysconfig_tag(self, mocker):
+        mocker.patch.object(windows_arch_mod.sysconfig, "get_platform", return_value="custom-win")
+
+        with pytest.raises(
+            UnsupportedArchError,
+            match=r"Unsupported Windows Python platform tag: 'custom-win'.*win-amd64.*win-arm64",
+        ) as exc_info:
+            windows_arch_mod.windows_python_arch()
+        assert exc_info.value.platform_tag == "custom-win"
+
+
+class TestWindowsMachineArch:
+    @pytest.mark.parametrize(
+        ("native_machine", "expected"),
+        ((0x8664, "x64"), (0xAA64, "arm64")),
+    )
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_uses_native_pe_machine(self, mocker, native_machine, expected):
+        mocker.patch.object(windows_arch_mod, "_windows_native_machine", return_value=native_machine)
+        platform_machine = mocker.patch.object(windows_arch_mod.platform, "machine", return_value="AMD64")
+
+        assert windows_arch_mod.windows_machine_arch() == expected
+        platform_machine.assert_not_called()
+
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_rejects_unknown_native_pe_machine(self, mocker):
+        mocker.patch.object(windows_arch_mod, "_windows_native_machine", return_value=0x014C)
+
+        with pytest.raises(RuntimeError, match=r"Unsupported native Windows PE machine type: 0x014c"):
+            windows_arch_mod.windows_machine_arch()
+
+    @pytest.mark.parametrize(
+        ("reported_machine", "expected"),
+        (("AMD64", "x64"), ("x86_64", "x64"), ("ARM64", "arm64"), ("aarch64", "arm64")),
+    )
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_old_windows_fallback_normalizes_platform_machine(self, mocker, reported_machine, expected):
+        mocker.patch.object(windows_arch_mod, "_windows_native_machine", return_value=None)
+        mocker.patch.object(windows_arch_mod.platform, "machine", return_value=reported_machine)
+
+        assert windows_arch_mod.windows_machine_arch() == expected
+
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_native_machine_returns_none_when_is_wow64_process2_is_unavailable(self, mocker):
+        kernel32 = mocker.Mock(spec=["GetCurrentProcess"])
+        mocker.patch.object(ctypes, "WinDLL", create=True, return_value=kernel32)
+
+        assert windows_arch_mod._windows_native_machine() is None
+
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_native_machine_configures_api_and_returns_native_machine(self, mocker):
+        kernel32 = mocker.Mock()
+        kernel32.GetCurrentProcess.return_value = wintypes.HANDLE(1)
+
+        def report_native_machine(_process, _process_machine, native_machine):
+            native_machine._obj.value = 0xAA64
+            return True
+
+        kernel32.IsWow64Process2.side_effect = report_native_machine
+        mocker.patch.object(ctypes, "WinDLL", create=True, return_value=kernel32)
+
+        assert windows_arch_mod._windows_native_machine() == 0xAA64
+        assert kernel32.GetCurrentProcess.argtypes == ()
+        assert kernel32.GetCurrentProcess.restype is wintypes.HANDLE
+        assert kernel32.IsWow64Process2.argtypes == (
+            wintypes.HANDLE,
+            ctypes.POINTER(wintypes.USHORT),
+            ctypes.POINTER(wintypes.USHORT),
+        )
+        assert kernel32.IsWow64Process2.restype is wintypes.BOOL
+
+    @pytest.mark.agent_authored(model="gpt-5.6")
+    def test_native_machine_raises_contextual_error_when_api_call_fails(self, mocker):
+        kernel32 = mocker.Mock()
+        kernel32.GetCurrentProcess.return_value = wintypes.HANDLE(1)
+        kernel32.IsWow64Process2.return_value = False
+        mocker.patch.object(ctypes, "WinDLL", create=True, return_value=kernel32)
+        mocker.patch.object(ctypes, "get_last_error", create=True, return_value=87)
+        windows_error = OSError(87, "The parameter is incorrect")
+        mocker.patch.object(ctypes, "WinError", create=True, return_value=windows_error)
+
+        with pytest.raises(
+            RuntimeError,
+            match=r"IsWow64Process2 failed while detecting the native Windows architecture \(Windows error 87\)",
+        ) as exc_info:
+            windows_arch_mod._windows_native_machine()
+
+        assert exc_info.value.__cause__ is windows_error
+
+
+@pytest.mark.parametrize(
+    ("machine", "target_arch", "expected"),
+    (
+        (0x8664, "x64", True),
+        (0x8664, "arm64", False),
+        (0xAA64, "x64", False),
+        (0xAA64, "arm64", True),
+    ),
+)
+@pytest.mark.agent_authored(model="gpt-5")
+def test_windows_pe_matches_arch(tmp_path, machine, target_arch, expected):
+    dll = tmp_path / "test.dll"
+    _write_pe(dll, machine)
+
+    assert windows_arch_mod.windows_pe_matches_arch(str(dll), target_arch) is expected
+
+
+@pytest.mark.agent_authored(model="gpt-5")
+def test_windows_pe_matches_arch_rejects_malformed_file(tmp_path):
+    dll = tmp_path / "test.dll"
+    dll.write_bytes(b"not a PE file")
+
+    assert windows_arch_mod.windows_pe_matches_arch(str(dll), "x64") is False
+
+
 # ---------------------------------------------------------------------------
 # find_in_site_packages
 # ---------------------------------------------------------------------------
@@ -90,7 +266,7 @@ def test_raise_not_found_empty_messages(self):
 
 class TestFindInSitePackages:
     def test_returns_none_when_no_rel_dirs(self):
-        desc = _make_desc(site_packages_linux=(), site_packages_windows=())
+        desc = _make_desc(site_packages_linux=(), site_packages_windows=WindowsSearchDirs())
         result = find_in_site_packages(_ctx(desc))
         assert result is None
 
@@ -113,6 +289,24 @@ def test_found_linux(self, mocker, tmp_path):
         assert result.abs_path == str(so_file)
         assert result.found_via == "site-packages"
 
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_nvvm_linux_wheel_accepts_declared_unversioned_filename(self, mocker, tmp_path):
+        lib_dir = tmp_path / "nvidia" / "cuda_nvcc" / "nvvm" / "lib64"
+        lib_dir.mkdir(parents=True)
+        so_file = lib_dir / "libnvvm.so"
+        so_file.touch()
+
+        mocker.patch(
+            f"{_PLAT_MOD}.find_sub_dirs_all_sitepackages",
+            return_value=[str(lib_dir)],
+        )
+
+        result = find_in_site_packages(_ctx(LIB_DESCRIPTORS["nvvm"], platform=LinuxSearchPlatform()))
+
+        assert result is not None
+        assert result.abs_path == str(so_file)
+        assert result.found_via == "site-packages"
+
     def test_found_windows(self, mocker, tmp_path):
         bin_dir = tmp_path / "nvidia" / "cuda_runtime" / "bin"
         bin_dir.mkdir(parents=True)
@@ -127,13 +321,156 @@ def test_found_windows(self, mocker, tmp_path):
 
         desc = _make_desc(
             name="cudart",
-            site_packages_windows=(os.path.join("nvidia", "cuda_runtime", "bin"),),
+            site_packages_windows=WindowsSearchDirs(
+                x64=(os.path.join("nvidia", "cuda_runtime", "bin"),),
+                arm64=(os.path.join("nvidia", "cuda_runtime", "bin"),),
+            ),
         )
-        result = find_in_site_packages(_ctx(desc, platform=WindowsSearchPlatform()))
+        result = find_in_site_packages(_ctx(desc, platform=WindowsSearchPlatform(target_arch="x64")))
         assert result is not None
         assert result.abs_path == str(dll)
         assert result.found_via == "site-packages"
 
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_windows_exact_names_reject_cudnn_sidecar(self, mocker, tmp_path):
+        bin_dir = tmp_path / "nvidia" / "cudnn" / "bin"
+        bin_dir.mkdir(parents=True)
+        (bin_dir / "cudnn_adv64_9.dll").touch()
+
+        mocker.patch(
+            f"{_PLAT_MOD}.find_sub_dirs_all_sitepackages",
+            return_value=[str(bin_dir)],
+        )
+
+        result = find_in_site_packages(
+            _ctx(LIB_DESCRIPTORS["cudnn"], platform=WindowsSearchPlatform(target_arch="x64"))
+        )
+
+        assert result is None
+
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_windows_matching_rejects_unlisted_cupti_name(self, mocker, tmp_path):
+        bin_dir = tmp_path / "nvidia" / "cuda_cupti" / "bin"
+        bin_dir.mkdir(parents=True)
+        (bin_dir / "cupti64_14.dll").touch()
+
+        mocker.patch(
+            f"{_PLAT_MOD}.find_sub_dirs_all_sitepackages",
+            return_value=[str(bin_dir)],
+        )
+
+        result = find_in_site_packages(
+            _ctx(LIB_DESCRIPTORS["cupti"], platform=WindowsSearchPlatform(target_arch="x64"))
+        )
+
+        assert result is None
+
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_windows_known_cupti_names_follow_declared_preference_order(self, tmp_path):
+        preferred_dll = tmp_path / "cupti64_2026.3.0.dll"
+        fallback_dll = tmp_path / "cupti64_2026.2.1.dll"
+        preferred_dll.touch()
+        fallback_dll.touch()
+
+        result = _find_descriptor_dll_under_dir(str(tmp_path), LIB_DESCRIPTORS["cupti"])
+
+        assert result == str(preferred_dll)
+
+    @pytest.mark.parametrize(
+        ("libname", "sibling_dll"),
+        (
+            ("cublas", "cublasLt64_13.dll"),
+            ("cufft", "cufftw64_12.dll"),
+            ("cusolver", "cusolverMg64_12.dll"),
+            ("cusparse", "cusparseLt.dll"),
+            ("cutensor", "cutensorMg.dll"),
+        ),
+    )
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_windows_matching_rejects_sibling_library(self, tmp_path, libname, sibling_dll):
+        (tmp_path / sibling_dll).touch()
+
+        result = _find_descriptor_dll_under_dir(str(tmp_path), LIB_DESCRIPTORS[libname])
+
+        assert result is None
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_found_windows_arm64_prefers_cuda13_arch_dir_to_cuda12(self, mocker, tmp_path):
+        x86_64_dir = tmp_path / "nvidia" / "cu13" / "bin" / "x86_64"
+        arm64_dir = tmp_path / "nvidia" / "cu13" / "bin" / "arm64"
+        cuda12_dir = tmp_path / "nvidia" / "cuda_runtime" / "bin"
+        x86_64_dir.mkdir(parents=True)
+        arm64_dir.mkdir(parents=True)
+        cuda12_dir.mkdir(parents=True)
+        (x86_64_dir / "cudart64_12.dll").touch()
+        (cuda12_dir / "cudart64_12.dll").touch()
+        arm64_dll = arm64_dir / "cudart64_12.dll"
+        arm64_dll.touch()
+
+        _patch_site_packages_search(mocker, tmp_path)
+        mocker.patch(f"{_PLAT_MOD}.is_suppressed_dll_file", return_value=False)
+
+        desc = LIB_DESCRIPTORS["cudart"]
+        result = find_in_site_packages(_ctx(desc, platform=WindowsSearchPlatform(target_arch="arm64")))
+        assert result is not None
+        assert result.abs_path == str(arm64_dll)
+        assert result.found_via == "site-packages"
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_found_windows_x64_prefers_cuda13_arch_dir_to_cuda12(self, mocker, tmp_path):
+        x86_64_dir = tmp_path / "nvidia" / "cu13" / "bin" / "x86_64"
+        arm64_dir = tmp_path / "nvidia" / "cu13" / "bin" / "arm64"
+        cuda12_dir = tmp_path / "nvidia" / "cuda_runtime" / "bin"
+        x86_64_dir.mkdir(parents=True)
+        arm64_dir.mkdir(parents=True)
+        cuda12_dir.mkdir(parents=True)
+        x86_64_dll = x86_64_dir / "cudart64_12.dll"
+        x86_64_dll.touch()
+        (arm64_dir / "cudart64_12.dll").touch()
+        (cuda12_dir / "cudart64_12.dll").touch()
+
+        _patch_site_packages_search(mocker, tmp_path)
+        mocker.patch(f"{_PLAT_MOD}.is_suppressed_dll_file", return_value=False)
+
+        desc = LIB_DESCRIPTORS["cudart"]
+        result = find_in_site_packages(_ctx(desc, platform=WindowsSearchPlatform(target_arch="x64")))
+        assert result is not None
+        assert result.abs_path == str(x86_64_dll)
+        assert result.found_via == "site-packages"
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_found_windows_x64_uses_cuda12_when_cuda13_is_absent(self, mocker, tmp_path):
+        cuda12_dir = tmp_path / "nvidia" / "cuda_runtime" / "bin"
+        cuda12_dir.mkdir(parents=True)
+        cuda12_dll = cuda12_dir / "cudart64_12.dll"
+        cuda12_dll.touch()
+
+        _patch_site_packages_search(mocker, tmp_path)
+        mocker.patch(f"{_PLAT_MOD}.is_suppressed_dll_file", return_value=False)
+
+        desc = LIB_DESCRIPTORS["cudart"]
+        result = find_in_site_packages(_ctx(desc, platform=WindowsSearchPlatform(target_arch="x64")))
+        assert result is not None
+        assert result.abs_path == str(cuda12_dll)
+        assert result.found_via == "site-packages"
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_found_windows_arm64_skips_cuda12_when_cuda13_is_absent(self, mocker, tmp_path):
+        cuda12_dir = tmp_path / "nvidia" / "cuda_runtime" / "bin"
+        cuda12_dir.mkdir(parents=True)
+        (cuda12_dir / "cudart64_12.dll").touch()
+
+        _patch_site_packages_search(mocker, tmp_path)
+        mocker.patch(f"{_PLAT_MOD}.is_suppressed_dll_file", return_value=False)
+
+        desc = LIB_DESCRIPTORS["cudart"]
+        platform = WindowsSearchPlatform(target_arch="arm64")
+        assert platform.site_packages_rel_dirs(desc) == ("nvidia/cu13/bin/arm64",)
+
+        result = find_in_site_packages(_ctx(desc, platform=platform))
+
+        assert result is None
+
     def test_not_found_appends_error(self, mocker, tmp_path):
         empty_dir = tmp_path / "nvidia" / "cuda_runtime" / "lib"
         empty_dir.mkdir(parents=True)
@@ -148,15 +485,8 @@ def test_not_found_appends_error(self, mocker, tmp_path):
         assert result is None
         assert any("No such file" in m for m in ctx.error_messages)
 
-    # The next three tests cover the Linux glob fallback in
-    # cuda.pathfinder._dynamic_libs.search_platform._find_so_in_rel_dirs.
-    # The fallback triggers when the unversioned libfoo.so is absent but
-    # versioned libfoo.so.<major> files exist (e.g. some conda layouts).
-    # Issue #1732 tracks the decision to return the newest-sorting match
-    # deterministically; these tests lock in that policy at the
-    # site-packages call site.
-
-    def test_glob_fallback_returns_single_versioned_match(self, mocker, tmp_path):
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_linux_declared_versioned_soname_does_not_need_unversioned_link(self, mocker, tmp_path):
         lib_dir = tmp_path / "nvidia" / "cuda_runtime" / "lib"
         lib_dir.mkdir(parents=True)
         versioned = lib_dir / "libcudart.so.13"
@@ -167,43 +497,53 @@ def test_glob_fallback_returns_single_versioned_match(self, mocker, tmp_path):
             return_value=[str(lib_dir)],
         )
 
-        result = find_in_site_packages(_ctx(platform=LinuxSearchPlatform()))
+        desc = _make_desc(linux_sonames=("libcudart.so.13", "libcudart.so.12"))
+        result = find_in_site_packages(_ctx(desc, platform=LinuxSearchPlatform()))
         assert result is not None
         assert result.abs_path == str(versioned)
         assert result.found_via == "site-packages"
 
-    def test_glob_fallback_returns_newest_of_multiple_matches(self, mocker, tmp_path):
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_linux_declared_sonames_follow_preference_order(self, mocker, tmp_path):
         lib_dir = tmp_path / "nvidia" / "cuda_runtime" / "lib"
         lib_dir.mkdir(parents=True)
-        older = lib_dir / "libcudart.so.12"
-        newer = lib_dir / "libcudart.so.13"
-        older.touch()
-        newer.touch()
+        preferred = lib_dir / "libcudart.so.13"
+        fallback = lib_dir / "libcudart.so.12"
+        preferred.touch()
+        fallback.touch()
 
         mocker.patch(
             f"{_PLAT_MOD}.find_sub_dirs_all_sitepackages",
             return_value=[str(lib_dir)],
         )
 
-        result = find_in_site_packages(_ctx(platform=LinuxSearchPlatform()))
+        desc = _make_desc(linux_sonames=("libcudart.so.13", "libcudart.so.12"))
+        result = find_in_site_packages(_ctx(desc, platform=LinuxSearchPlatform()))
         assert result is not None
-        assert result.abs_path == str(newer)
+        assert result.abs_path == str(preferred)
         assert result.found_via == "site-packages"
 
-    def test_glob_fallback_zero_matches_returns_none(self, mocker, tmp_path):
+    @pytest.mark.parametrize(
+        "undeclared_filename",
+        ("libcudart.so", "libcudart.so.14", "libcudart.so.13.5.0", "libcudart.so.13.backup"),
+    )
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_linux_rejects_undeclared_filename(self, mocker, tmp_path, undeclared_filename):
         lib_dir = tmp_path / "nvidia" / "cuda_runtime" / "lib"
         lib_dir.mkdir(parents=True)
-        (lib_dir / "unrelated.txt").touch()
+        (lib_dir / undeclared_filename).touch()
 
         mocker.patch(
             f"{_PLAT_MOD}.find_sub_dirs_all_sitepackages",
             return_value=[str(lib_dir)],
         )
 
-        ctx = _ctx(platform=LinuxSearchPlatform())
+        desc = _make_desc(linux_sonames=("libcudart.so.13", "libcudart.so.12"))
+        ctx = _ctx(desc, platform=LinuxSearchPlatform())
         result = find_in_site_packages(ctx)
         assert result is None
-        assert any("No such file" in m and "libcudart.so" in m for m in ctx.error_messages)
+        assert ctx.error_messages
+        assert all("*" not in message for message in ctx.error_messages)
 
 
 # ---------------------------------------------------------------------------
@@ -241,58 +581,61 @@ def test_found_windows(self, mocker, tmp_path):
 
         mocker.patch.dict(os.environ, {"CONDA_PREFIX": str(tmp_path)})
 
-        result = find_in_conda(_ctx(platform=WindowsSearchPlatform()))
+        result = find_in_conda(_ctx(platform=WindowsSearchPlatform(target_arch="x64")))
         assert result is not None
         assert result.abs_path == str(dll)
         assert result.found_via == "conda"
 
-    # The next three tests cover the Linux glob fallback in
-    # cuda.pathfinder._dynamic_libs.search_platform.LinuxSearchPlatform.find_in_lib_dir,
-    # which is exercised by find_in_conda (and find_in_cuda_path) when the
-    # resolved lib dir contains only versioned libfoo.so.<major> files.
-    # Issue #1732 tracks the decision to return the newest-sorting match
-    # deterministically; these tests lock in that policy at the conda /
-    # CUDA_PATH call site.
-
-    def test_glob_fallback_returns_single_versioned_match(self, mocker, tmp_path):
-        lib_dir = tmp_path / "lib"
-        lib_dir.mkdir()
-        versioned = lib_dir / "libcudart.so.13"
-        versioned.touch()
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_found_windows_arm64_prefers_arch_dir(self, mocker, tmp_path):
+        x64_dir = tmp_path / "Library" / "bin" / "x64"
+        arm64_dir = tmp_path / "Library" / "bin" / "arm64"
+        x64_dir.mkdir(parents=True)
+        arm64_dir.mkdir(parents=True)
+        (x64_dir / "cudart64_12.dll").touch()
+        arm64_dll = arm64_dir / "cudart64_12.dll"
+        arm64_dll.touch()
 
         mocker.patch.dict(os.environ, {"CONDA_PREFIX": str(tmp_path)})
 
-        result = find_in_conda(_ctx(platform=LinuxSearchPlatform()))
+        result = find_in_conda(_ctx(platform=WindowsSearchPlatform(target_arch="arm64")))
         assert result is not None
-        assert result.abs_path == str(versioned)
+        assert result.abs_path == str(arm64_dll)
         assert result.found_via == "conda"
 
-    def test_glob_fallback_returns_newest_of_multiple_matches(self, mocker, tmp_path):
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_linux_declared_versioned_soname_found_in_lib_dir(self, mocker, tmp_path):
         lib_dir = tmp_path / "lib"
         lib_dir.mkdir()
-        older = lib_dir / "libcudart.so.12"
-        newer = lib_dir / "libcudart.so.13"
-        older.touch()
-        newer.touch()
+        versioned = lib_dir / "libcudart.so.13"
+        versioned.touch()
 
         mocker.patch.dict(os.environ, {"CONDA_PREFIX": str(tmp_path)})
 
-        result = find_in_conda(_ctx(platform=LinuxSearchPlatform()))
+        desc = _make_desc(linux_sonames=("libcudart.so.13", "libcudart.so.12"))
+        result = find_in_conda(_ctx(desc, platform=LinuxSearchPlatform()))
         assert result is not None
-        assert result.abs_path == str(newer)
+        assert result.abs_path == str(versioned)
         assert result.found_via == "conda"
 
-    def test_glob_fallback_zero_matches_returns_none(self, mocker, tmp_path):
+    @pytest.mark.parametrize(
+        "undeclared_filename",
+        ("libcudart.so", "libcudart.so.14", "libcudart.so.13.5.0", "libcudart.so.13.backup"),
+    )
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_linux_rejects_undeclared_filename_in_lib_dir(self, mocker, tmp_path, undeclared_filename):
         lib_dir = tmp_path / "lib"
         lib_dir.mkdir()
-        (lib_dir / "unrelated.txt").touch()
+        (lib_dir / undeclared_filename).touch()
 
         mocker.patch.dict(os.environ, {"CONDA_PREFIX": str(tmp_path)})
 
-        ctx = _ctx(platform=LinuxSearchPlatform())
+        desc = _make_desc(linux_sonames=("libcudart.so.13", "libcudart.so.12"))
+        ctx = _ctx(desc, platform=LinuxSearchPlatform())
         result = find_in_conda(ctx)
         assert result is None
-        assert any("No such file" in m and "libcudart.so" in m for m in ctx.error_messages)
+        assert ctx.error_messages
+        assert all("*" not in message for message in ctx.error_messages)
 
 
 # ---------------------------------------------------------------------------
@@ -326,11 +669,215 @@ def test_found_windows(self, mocker, tmp_path):
 
         mocker.patch(f"{_STEPS_MOD}.get_cuda_path_or_home", return_value=str(tmp_path))
 
-        result = find_in_cuda_path(_ctx(platform=WindowsSearchPlatform()))
+        result = find_in_cuda_path(_ctx(platform=WindowsSearchPlatform(target_arch="x64")))
         assert result is not None
         assert result.abs_path == str(dll)
         assert result.found_via == "CUDA_PATH"
 
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_found_windows_arm64_prefers_arch_dir(self, mocker, tmp_path):
+        x64_dir = tmp_path / "bin" / "x64"
+        arm64_dir = tmp_path / "bin" / "arm64"
+        x64_dir.mkdir(parents=True)
+        arm64_dir.mkdir(parents=True)
+        (x64_dir / "cudart64_12.dll").touch()
+        arm64_dll = arm64_dir / "cudart64_12.dll"
+        arm64_dll.touch()
+
+        mocker.patch(f"{_STEPS_MOD}.get_cuda_path_or_home", return_value=str(tmp_path))
+
+        result = find_in_cuda_path(_ctx(platform=WindowsSearchPlatform(target_arch="arm64")))
+        assert result is not None
+        assert result.abs_path == str(arm64_dll)
+        assert result.found_via == "CUDA_PATH"
+
+    @pytest.mark.parametrize(
+        ("target_arch", "machine", "expected_found"),
+        (
+            ("x64", 0x8664, True),
+            ("x64", 0xAA64, False),
+            ("arm64", 0x8664, False),
+            ("arm64", 0xAA64, True),
+        ),
+    )
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_nvvm_windows_checks_binary_arch(self, mocker, tmp_path, target_arch, machine, expected_found):
+        nvvm_dir = tmp_path / "nvvm" / "bin"
+        nvvm_dir.mkdir(parents=True)
+        dll = nvvm_dir / "nvvm64_40_0.dll"
+        _write_pe(dll, machine)
+
+        mocker.patch(f"{_STEPS_MOD}.get_cuda_path_or_home", return_value=str(tmp_path))
+
+        ctx = _ctx(LIB_DESCRIPTORS["nvvm"], platform=WindowsSearchPlatform(target_arch=target_arch))
+        result = find_in_cuda_path(ctx)
+
+        assert (result is not None) is expected_found
+        if expected_found:
+            assert result is not None
+            assert result.abs_path == str(dll)
+            assert result.found_via == "CUDA_PATH"
+        else:
+            assert any(f"No {target_arch}-compatible PE file" in message for message in ctx.error_messages)
+
+
+# ---------------------------------------------------------------------------
+# Descriptor-specific Linux install roots
+# ---------------------------------------------------------------------------
+
+
+class TestLinuxInstallRoots:
+    @pytest.mark.parametrize(
+        ("libname", "env_var", "rel_dir", "soname"),
+        (
+            ("cudnn", "CUDNN_PATH", "lib", "libcudnn.so.9"),
+            ("cudnn", "CUDNN_PATH", "lib64", "libcudnn.so.9"),
+            ("nccl", "NCCL_HOME", "lib", "libnccl.so.2"),
+            ("nccl", "NCCL_HOME", "lib64", "libnccl.so.2"),
+            ("nccl", "NCCL_HOME", "build/lib", "libnccl.so.2"),
+        ),
+    )
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_product_root_finds_supported_layouts(self, mocker, tmp_path, libname, env_var, rel_dir, soname):
+        root = tmp_path / libname
+        lib_dir = root / rel_dir
+        lib_dir.mkdir(parents=True)
+        library = lib_dir / soname
+        library.touch()
+        env = {"CUDNN_PATH": "", "NCCL_HOME": ""}
+        env[env_var] = str(root)
+        mocker.patch.dict(os.environ, env)
+
+        result = find_in_install_root_env_vars(_ctx(LIB_DESCRIPTORS[libname], platform=LinuxSearchPlatform()))
+
+        assert result == FindResult(str(library), env_var)
+
+    @pytest.mark.agent_authored(model="gpt-5.6-sol")
+    def test_nccl_home_prefers_canonical_installed_layout(self, mocker, tmp_path):
+        libraries = []
+        for rel_dir in ("lib", "lib64", "build/lib"):
+            lib_dir = tmp_path / rel_dir
+            lib_dir.mkdir(parents=True)
+            library = lib_dir / "libnccl.so.2"
+            library.touch()
+            libraries.append(library)
+        mocker.patch.dict(os.environ, {"CUDNN_PATH": "", "NCCL_HOME": str(tmp_path)})
+
+        result = find_in_install_root_env_vars(_ctx(LIB_DESCRIPTORS["nccl"], platform=LinuxSearchPlatform()))
+
+        assert result == FindResult(str(libraries[0]), "NCCL_HOME")
+
+
+# ---------------------------------------------------------------------------
+# Descriptor-specific Windows install roots
+# ---------------------------------------------------------------------------
+
+
+class TestWindowsInstallRoots:
+    @pytest.mark.parametrize(
+        ("target_arch", "archive_bin_rel_dir"),
+        [
+            ("x64", "bin/x64"),
+            ("x64", "bin"),
+            ("arm64", "bin/arm64"),
+        ],
+    )
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_cudnn_path_finds_supported_archive_layouts(self, mocker, tmp_path, target_arch, archive_bin_rel_dir):
+        bin_dir = tmp_path / archive_bin_rel_dir
+        bin_dir.mkdir(parents=True)
+        dll = bin_dir / "cudnn64_9.dll"
+        dll.touch()
+        mocker.patch.dict(os.environ, {"CUDNN_PATH": str(tmp_path)})
+
+        result = find_in_install_root_env_vars(
+            _ctx(LIB_DESCRIPTORS["cudnn"], platform=WindowsSearchPlatform(target_arch=target_arch))
+        )
+
+        assert result == FindResult(str(dll), "CUDNN_PATH")
+
+    @pytest.mark.parametrize(
+        ("target_arch", "other_arch_bin_rel_dir"),
+        [
+            ("x64", "bin/arm64"),
+            ("arm64", "bin/x64"),
+            ("arm64", "bin"),
+        ],
+    )
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_cudnn_path_does_not_cross_architectures(self, mocker, tmp_path, target_arch, other_arch_bin_rel_dir):
+        bin_dir = tmp_path / other_arch_bin_rel_dir
+        bin_dir.mkdir(parents=True)
+        (bin_dir / "cudnn64_9.dll").touch()
+        mocker.patch.dict(os.environ, {"CUDNN_PATH": str(tmp_path)})
+
+        result = find_in_install_root_env_vars(
+            _ctx(LIB_DESCRIPTORS["cudnn"], platform=WindowsSearchPlatform(target_arch=target_arch))
+        )
+
+        assert result is None
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_program_files_finds_versioned_cudnn_install(self, mocker, tmp_path):
+        bin_dir = tmp_path / "NVIDIA" / "CUDNN" / "v9.24" / "bin"
+        x64_bin_dir = bin_dir / "x64"
+        x64_bin_dir.mkdir(parents=True)
+        (x64_bin_dir / "cudnn_adv64_9.dll").touch()
+        dll = bin_dir / "cudnn64_9.dll"
+        dll.touch()
+        mocker.patch.dict(os.environ, {"PROGRAMFILES": str(tmp_path), "PROGRAMW6432": ""})
+
+        result = find_in_program_files_roots(
+            _ctx(LIB_DESCRIPTORS["cudnn"], platform=WindowsSearchPlatform(target_arch="x64"))
+        )
+
+        assert result == FindResult(str(dll), "ProgramFiles")
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_program_files_prefers_newest_numeric_cudnn_version_across_layouts(self, mocker, tmp_path):
+        older_dir = tmp_path / "NVIDIA" / "CUDNN" / "v9.9" / "bin" / "x64"
+        newer_dir = tmp_path / "NVIDIA" / "CUDNN" / "v9.10" / "bin"
+        older_dir.mkdir(parents=True)
+        newer_dir.mkdir(parents=True)
+        (older_dir / "cudnn64_9.dll").touch()
+        newer_dll = newer_dir / "cudnn64_9.dll"
+        newer_dll.touch()
+        mocker.patch.dict(os.environ, {"PROGRAMFILES": str(tmp_path), "PROGRAMW6432": ""})
+
+        result = find_in_program_files_roots(
+            _ctx(LIB_DESCRIPTORS["cudnn"], platform=WindowsSearchPlatform(target_arch="x64"))
+        )
+
+        assert result == FindResult(str(newer_dll), "ProgramFiles")
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_cudnn_arm64_archive_layout_is_not_assumed_for_other_roots(self, mocker, tmp_path):
+        conda_root = tmp_path / "conda"
+        cuda_root = tmp_path / "cuda"
+        program_files_root = tmp_path / "Program Files"
+        for bin_dir in (
+            conda_root / "Library" / "bin" / "arm64",
+            cuda_root / "bin" / "arm64",
+            program_files_root / "NVIDIA" / "CUDNN" / "v9.25" / "bin" / "arm64",
+        ):
+            bin_dir.mkdir(parents=True)
+            (bin_dir / "cudnn64_9.dll").touch()
+        mocker.patch.dict(
+            os.environ,
+            {
+                "CONDA_PREFIX": str(conda_root),
+                "PROGRAMFILES": str(program_files_root),
+                "PROGRAMW6432": "",
+            },
+        )
+        mocker.patch(f"{_STEPS_MOD}.get_cuda_path_or_home", return_value=str(cuda_root))
+        ctx = _ctx(LIB_DESCRIPTORS["cudnn"], platform=WindowsSearchPlatform(target_arch="arm64"))
+
+        assert find_in_conda(ctx) is None
+        assert find_in_cuda_path(ctx) is None
+        assert find_in_program_files_roots(ctx) is None
+        assert ctx.platform.site_packages_rel_dirs(ctx.desc) == ()
+
 
 # ---------------------------------------------------------------------------
 # run_find_steps
@@ -374,7 +921,17 @@ def test_early_find_steps_contains_expected(self):
         assert find_in_conda in EARLY_FIND_STEPS
 
     def test_late_find_steps_contains_expected(self):
+        assert find_in_install_root_env_vars in LATE_FIND_STEPS
         assert find_in_cuda_path in LATE_FIND_STEPS
+        assert find_in_program_files_roots in LATE_FIND_STEPS
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_late_find_steps_use_specific_roots_before_generic_roots(self):
+        assert (
+            find_in_install_root_env_vars,
+            find_in_cuda_path,
+            find_in_program_files_roots,
+        ) == LATE_FIND_STEPS
 
     def test_early_and_late_are_disjoint(self):
         assert not set(EARLY_FIND_STEPS) & set(LATE_FIND_STEPS)
@@ -388,19 +945,63 @@ def test_early_and_late_are_disjoint(self):
 class TestAnchorRelDirs:
     """Verify that descriptor anchor paths drive directory resolution."""
 
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_windows_search_dirs_arch_only_constructors(self):
+        assert WindowsSearchDirs.x64_only("first", "second") == WindowsSearchDirs(x64=("first", "second"))
+        assert WindowsSearchDirs.arm64_only("first", "second") == WindowsSearchDirs(arm64=("first", "second"))
+
     def test_nvvm_has_custom_linux_paths(self):
         desc = LIB_DESCRIPTORS["nvvm"]
         assert desc.anchor_rel_dirs_linux == ("nvvm/lib64",)
 
     def test_nvvm_has_custom_windows_paths(self):
         desc = LIB_DESCRIPTORS["nvvm"]
-        assert desc.anchor_rel_dirs_windows == ("nvvm/bin/*", "nvvm/bin")
+        assert desc.anchor_rel_dirs_windows.for_arch("x64") == ("nvvm/bin/x64", "nvvm/bin")
+        assert desc.anchor_rel_dirs_windows.for_arch("arm64") == ("nvvm/bin",)
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_cupti_has_custom_windows_paths(self):
+        desc = LIB_DESCRIPTORS["cupti"]
+        assert desc.anchor_rel_dirs_windows.for_arch("x64") == (
+            "extras/CUPTI/lib/x64",
+            "extras/CUPTI/lib64",
+            "bin",
+        )
+        assert desc.anchor_rel_dirs_windows.for_arch("arm64") == ("extras/CUPTI/lib/arm64",)
 
     @pytest.mark.parametrize("libname", ["cudart", "cublas", "nvrtc"])
     def test_regular_ctk_libs_use_defaults(self, libname):
         desc = LIB_DESCRIPTORS[libname]
         assert desc.anchor_rel_dirs_linux == ("lib64", "lib")
-        assert desc.anchor_rel_dirs_windows == ("bin/x64", "bin")
+        assert desc.anchor_rel_dirs_windows.for_arch("x64") == ("bin/x64", "bin")
+        assert desc.anchor_rel_dirs_windows.for_arch("arm64") == ("bin/arm64",)
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_cudla_uses_arm64_only_windows_anchor(self):
+        desc = LIB_DESCRIPTORS["cudla"]
+
+        assert desc.anchor_rel_dirs_windows.for_arch("x64") == ()
+        assert desc.anchor_rel_dirs_windows.for_arch("arm64") == ("bin/arm64",)
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_windows_anchor_dirs_select_arm64(self):
+        desc = _make_desc(
+            anchor_rel_dirs_windows=WindowsSearchDirs(
+                x64=("bin/x64", "bin"),
+                arm64=("bin/arm64", "bin"),
+            )
+        )
+        assert WindowsSearchPlatform(target_arch="arm64").anchor_rel_dirs(desc) == ("bin/arm64", "bin")
+
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_windows_anchor_dirs_select_x64(self):
+        desc = _make_desc(
+            anchor_rel_dirs_windows=WindowsSearchDirs(
+                x64=("bin/x64", "bin"),
+                arm64=("bin/arm64", "bin"),
+            )
+        )
+        assert WindowsSearchPlatform(target_arch="x64").anchor_rel_dirs(desc) == ("bin/x64", "bin")
 
     def test_find_lib_dir_uses_descriptor_linux(self, tmp_path):
         (tmp_path / "nvvm" / "lib64").mkdir(parents=True)
@@ -413,11 +1014,33 @@ def test_find_lib_dir_uses_descriptor_linux(self, tmp_path):
     def test_find_lib_dir_uses_descriptor_windows(self, tmp_path):
         (tmp_path / "nvvm" / "bin").mkdir(parents=True)
 
-        desc = _make_desc(name="nvvm", anchor_rel_dirs_windows=("nvvm/bin/*", "nvvm/bin"))
-        result = _find_lib_dir_using_anchor(desc, WindowsSearchPlatform(), str(tmp_path))
+        desc = _make_desc(
+            name="nvvm",
+            anchor_rel_dirs_windows=WindowsSearchDirs(
+                x64=("nvvm/bin/x64", "nvvm/bin"),
+                arm64=("nvvm/bin/arm64", "nvvm/bin"),
+            ),
+        )
+        result = _find_lib_dir_using_anchor(desc, WindowsSearchPlatform(target_arch="x64"), str(tmp_path))
         assert result is not None
         assert result.endswith(os.path.join("nvvm", "bin"))
 
+    @pytest.mark.agent_authored(model="gpt-5")
+    def test_find_lib_dir_windows_arm64_uses_arm64_anchor(self, tmp_path):
+        (tmp_path / "bin" / "x64").mkdir(parents=True)
+        (tmp_path / "bin" / "arm64").mkdir(parents=True)
+
+        desc = _make_desc(
+            name="cudart",
+            anchor_rel_dirs_windows=WindowsSearchDirs(
+                x64=("bin/x64", "bin"),
+                arm64=("bin/arm64",),
+            ),
+        )
+        result = _find_lib_dir_using_anchor(desc, WindowsSearchPlatform(target_arch="arm64"), str(tmp_path))
+        assert result is not None
+        assert result.endswith(os.path.join("bin", "arm64"))
+
     def test_find_lib_dir_returns_none_when_no_match(self, tmp_path):
         desc = _make_desc(anchor_rel_dirs_linux=("nonexistent",))
         assert _find_lib_dir_using_anchor(desc, LinuxSearchPlatform(), str(tmp_path)) is None
diff --git a/cuda_pathfinder/tests/test_utils_driver_info.py b/cuda_pathfinder/tests/test_utils_driver_info.py
index 21948dadafe..0b3cd61d299 100644
--- a/cuda_pathfinder/tests/test_utils_driver_info.py
+++ b/cuda_pathfinder/tests/test_utils_driver_info.py
@@ -46,7 +46,6 @@ def test_query_driver_cuda_version_uses_windll_on_windows(monkeypatch):
     fake_driver_lib = _FakeDriverLib(status=0, version=12080)
     loaded_paths: list[str] = []
 
-    monkeypatch.setattr(driver_info, "IS_WINDOWS", True)
     monkeypatch.setattr(
         driver_info,
         "_load_nvidia_dynamic_lib",
@@ -57,7 +56,7 @@ def fake_windll(abs_path: str):
         loaded_paths.append(abs_path)
         return fake_driver_lib
 
-    monkeypatch.setattr(driver_info.ctypes, "WinDLL", fake_windll, raising=False)
+    monkeypatch.setattr(driver_info, "_DRIVER_LIB_LOADER", fake_windll)
 
     assert driver_info._query_driver_cuda_version_int() == 12080
     assert loaded_paths == [r"C:\Windows\System32\nvcuda.dll"]
@@ -93,9 +92,8 @@ def fail_query_driver_cuda_version_int() -> int:
 def test_query_driver_cuda_version_int_raises_when_cuda_call_fails(monkeypatch):
     fake_driver_lib = _FakeDriverLib(status=1, version=0)
 
-    monkeypatch.setattr(driver_info, "IS_WINDOWS", False)
     monkeypatch.setattr(driver_info, "_load_nvidia_dynamic_lib", lambda _libname: _loaded_cuda("/usr/lib/libcuda.so.1"))
-    monkeypatch.setattr(driver_info.ctypes, "CDLL", lambda _abs_path: fake_driver_lib)
+    monkeypatch.setattr(driver_info, "_DRIVER_LIB_LOADER", lambda _abs_path: fake_driver_lib)
 
     with pytest.raises(RuntimeError, match=r"cuDriverGetVersion\(\) \(status=1\)"):
         driver_info._query_driver_cuda_version_int()
diff --git a/cuda_pathfinder/tests/test_utils_find_sub_dirs.py b/cuda_pathfinder/tests/test_utils_find_sub_dirs.py
index a647e66099b..56dab23dc42 100644
--- a/cuda_pathfinder/tests/test_utils_find_sub_dirs.py
+++ b/cuda_pathfinder/tests/test_utils_find_sub_dirs.py
@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-import os
+from pathlib import Path
 
 import pytest
 
@@ -77,7 +77,7 @@ def test_empty_parent_paths():
 def test_empty_sub_dirs(test_tree):
     parent_paths = test_tree["parent_paths"]
     result = find_sub_dirs(parent_paths, ())
-    expected = [p for p in parent_paths if os.path.isdir(p)]
+    expected = [p for p in parent_paths if Path(p).is_dir()]
     assert sorted(result) == sorted(expected)
 
 
diff --git a/cuda_pathfinder/tests/test_windows_nsight.py b/cuda_pathfinder/tests/test_windows_nsight.py
new file mode 100644
index 00000000000..78da205988b
--- /dev/null
+++ b/cuda_pathfinder/tests/test_windows_nsight.py
@@ -0,0 +1,196 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+import os
+
+import pytest
+
+from cuda.pathfinder._binaries import windows_nsight
+
+
+def _patch_winreg(mocker):
+    winreg = mocker.MagicMock()
+    winreg.HKEY_LOCAL_MACHINE = object()
+    winreg.KEY_READ = 0x20019
+    winreg.KEY_WOW64_64KEY = 0x0100
+    mocker.patch.object(windows_nsight.importlib, "import_module", return_value=winreg)
+    return winreg
+
+
+@pytest.mark.parametrize(
+    ("machine_arch", "target_dir"),
+    (
+        ("x64", "target-windows-x64"),
+        ("arm64", "target-windows-armv8"),
+    ),
+)
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_nsys_candidate_paths_use_machine_arch(mocker, machine_arch, target_dir):
+    install_root = os.path.join(os.sep, "Program Files", "Nsight Systems")
+    expected = os.path.join(install_root, target_dir, "nsys.exe")
+    mocker.patch.object(windows_nsight, "_installed_product_root", return_value=install_root)
+    mocker.patch.object(windows_nsight, "windows_machine_arch", return_value=machine_arch)
+
+    assert tuple(windows_nsight.nsys_candidate_paths()) == (expected,)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_nsys_candidate_paths_do_not_include_other_arch(mocker):
+    install_root = os.path.join(os.sep, "Program Files", "Nsight Systems")
+    arm64 = os.path.join(install_root, "target-windows-armv8", "nsys.exe")
+    mocker.patch.object(windows_nsight, "_installed_product_root", return_value=install_root)
+    mocker.patch.object(windows_nsight, "windows_machine_arch", return_value="arm64")
+
+    assert tuple(windows_nsight.nsys_candidate_paths()) == (arm64,)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_ncu_candidate_paths_yield_launcher_before_resolving_machine_arch(mocker):
+    install_root = os.path.join(os.sep, "Program Files", "Nsight Compute")
+    launcher = os.path.join(install_root, "ncu.bat")
+    mocker.patch.object(windows_nsight, "_installed_product_root", return_value=install_root)
+    machine_arch = mocker.patch.object(windows_nsight, "windows_machine_arch")
+
+    candidates = windows_nsight.ncu_candidate_paths()
+
+    assert next(candidates) == launcher
+    machine_arch.assert_not_called()
+
+
+@pytest.mark.parametrize(
+    ("machine_arch", "target_dir"),
+    (
+        ("x64", os.path.join("target", "windows-desktop-win7-x64")),
+        ("arm64", os.path.join("target", "windows-desktop-win10-t23x-a64")),
+    ),
+)
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_ncu_candidate_paths_fall_back_to_machine_binary(mocker, machine_arch, target_dir):
+    install_root = os.path.join(os.sep, "Program Files", "Nsight Compute")
+    launcher = os.path.join(install_root, "ncu.bat")
+    expected = os.path.join(install_root, target_dir, "ncu.exe")
+    mocker.patch.object(windows_nsight, "_installed_product_root", return_value=install_root)
+    mocker.patch.object(windows_nsight, "windows_machine_arch", return_value=machine_arch)
+
+    assert tuple(windows_nsight.ncu_candidate_paths()) == (launcher, expected)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_reads_64_bit_registry(mocker):
+    install_root = os.path.join(os.sep, "Program Files", "Nsight Systems")
+    product_key = mocker.MagicMock()
+    version_key = mocker.MagicMock()
+    product_context = mocker.MagicMock()
+    product_context.__enter__.return_value = product_key
+    version_context = mocker.MagicMock()
+    version_context.__enter__.return_value = version_key
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.side_effect = (product_context, version_context)
+    winreg.QueryValueEx.side_effect = (("2026.1.3", 1), (install_root, 1))
+
+    assert windows_nsight._installed_product_root("Systems") == install_root
+    access = winreg.KEY_READ | winreg.KEY_WOW64_64KEY
+    winreg.OpenKey.assert_has_calls(
+        (
+            mocker.call(
+                winreg.HKEY_LOCAL_MACHINE,
+                rf"{windows_nsight._REGISTRY_ROOT}\Systems",
+                0,
+                access,
+            ),
+            mocker.call(product_key, "2026.1.3", 0, access),
+        )
+    )
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_returns_none_when_product_key_is_absent(mocker):
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.side_effect = FileNotFoundError("Nsight Systems is not installed")
+
+    assert windows_nsight._installed_product_root("Systems") is None
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_rejects_missing_current_version(mocker):
+    product_context = mocker.MagicMock()
+    product_context.__enter__.return_value = mocker.MagicMock()
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.return_value = product_context
+    winreg.QueryValueEx.side_effect = FileNotFoundError("CurrentVersion is missing")
+
+    with pytest.raises(RuntimeError, match=r"Incomplete Nsight 'Systems' registry registration") as exc_info:
+        windows_nsight._installed_product_root("Systems")
+
+    assert isinstance(exc_info.value.__cause__, FileNotFoundError)
+
+
+@pytest.mark.parametrize("current_version", (None, "", "   ", 2026))
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_rejects_invalid_current_version(mocker, current_version):
+    product_context = mocker.MagicMock()
+    product_context.__enter__.return_value = mocker.MagicMock()
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.return_value = product_context
+    winreg.QueryValueEx.return_value = (current_version, 1)
+
+    with pytest.raises(RuntimeError, match=r"Invalid CurrentVersion value .*Nsight 'Systems' registry registration"):
+        windows_nsight._installed_product_root("Systems")
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_rejects_missing_version_key(mocker):
+    product_key = mocker.MagicMock()
+    product_context = mocker.MagicMock()
+    product_context.__enter__.return_value = product_key
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.side_effect = (product_context, FileNotFoundError("Version key is missing"))
+    winreg.QueryValueEx.return_value = ("2026.1.3", 1)
+
+    with pytest.raises(RuntimeError, match=r"Incomplete Nsight 'Systems' registry registration") as exc_info:
+        windows_nsight._installed_product_root("Systems")
+
+    assert isinstance(exc_info.value.__cause__, FileNotFoundError)
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_rejects_missing_installation_directory(mocker):
+    product_context = mocker.MagicMock()
+    product_context.__enter__.return_value = mocker.MagicMock()
+    version_context = mocker.MagicMock()
+    version_context.__enter__.return_value = mocker.MagicMock()
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.side_effect = (product_context, version_context)
+    winreg.QueryValueEx.side_effect = (("2026.1.3", 1), FileNotFoundError("Installation directory is missing"))
+
+    with pytest.raises(RuntimeError, match=r"Incomplete Nsight 'Systems' registry registration") as exc_info:
+        windows_nsight._installed_product_root("Systems")
+
+    assert isinstance(exc_info.value.__cause__, FileNotFoundError)
+
+
+@pytest.mark.parametrize("install_root", (None, "", "   ", 2026))
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_rejects_invalid_installation_directory(mocker, install_root):
+    product_context = mocker.MagicMock()
+    product_context.__enter__.return_value = mocker.MagicMock()
+    version_context = mocker.MagicMock()
+    version_context.__enter__.return_value = mocker.MagicMock()
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.side_effect = (product_context, version_context)
+    winreg.QueryValueEx.side_effect = (("2026.1.3", 1), (install_root, 1))
+
+    with pytest.raises(
+        RuntimeError,
+        match=r"Invalid installation directory .*Nsight 'Systems' registry registration.*version '2026.1.3'",
+    ):
+        windows_nsight._installed_product_root("Systems")
+
+
+@pytest.mark.agent_authored(model="gpt-5.6")
+def test_installed_product_root_propagates_access_errors(mocker):
+    winreg = _patch_winreg(mocker)
+    winreg.OpenKey.side_effect = PermissionError("Registry access denied")
+
+    with pytest.raises(PermissionError, match="Registry access denied"):
+        windows_nsight._installed_product_root("Systems")
diff --git a/cuda_python/DESCRIPTION.rst b/cuda_python/DESCRIPTION.rst
index 3f0a92b5af6..79fa69584ff 100644
--- a/cuda_python/DESCRIPTION.rst
+++ b/cuda_python/DESCRIPTION.rst
@@ -15,7 +15,7 @@ CUDA Python is the home for accessing NVIDIA's CUDA platform from Python. It con
 * `numba.cuda <https://nvidia.github.io/numba-cuda/>`_: A Python DSL that exposes CUDA **SIMT** programming model and compiles a restricted subset of Python code into CUDA kernels and device functions
 * `cuda.tile <https://docs.nvidia.com/cuda/cutile-python/>`_: A new Python DSL that exposes CUDA **Tile** programming model and allows users to write NumPy-like code in CUDA kernels
 * `nvmath-python <https://docs.nvidia.com/cuda/nvmath-python/latest>`_: Pythonic access to NVIDIA CPU & GPU Math Libraries, with `host <https://docs.nvidia.com/cuda/nvmath-python/latest/overview.html#host-apis>`_, `device <https://docs.nvidia.com/cuda/nvmath-python/latest/overview.html#device-apis>`_, and `distributed <https://docs.nvidia.com/cuda/nvmath-python/latest/distributed-apis/index.html>`_ APIs. It also provides low-level Python bindings to host C APIs (`nvmath.bindings <https://docs.nvidia.com/cuda/nvmath-python/latest/bindings/index.html>`_).
-* `nvshmem4py <https://docs.nvidia.com/nvshmem/api/api/language_bindings/python/index.html>`_: Pythonic interface to the NVSHMEM library, enabling Python applications to leverage NVSHMEM's high-performance PGAS (Partitioned Global Address Space) programming model for GPU-accelerated computing
+* `nvshmem4py <https://docs.nvidia.com/nvshmem/api/latest/api/language_bindings/python/index.html>`_: Pythonic interface to the NVSHMEM library, enabling Python applications to leverage NVSHMEM's high-performance PGAS (Partitioned Global Address Space) programming model for GPU-accelerated computing
 * `Nsight Python <https://docs.nvidia.com/nsight-python/index.html>`_: Python kernel profiling interface that automates performance analysis across multiple kernel configurations using NVIDIA Nsight Tools
 * `CUPTI Python <https://docs.nvidia.com/cupti-python/>`_: Python APIs for creation of profiling tools that target CUDA Python applications via the CUDA Profiling Tools Interface (CUPTI)
 * `Accelerated Computing Hub <https://github.com/NVIDIA/accelerated-computing-hub>`_: Open-source learning materials related to GPU computing. You will find user guides, tutorials, and other works freely available for all learners interested in GPU computing.
diff --git a/cuda_python/LICENSE b/cuda_python/LICENSE
index d6f74778be8..f3fe76ecadf 100644
--- a/cuda_python/LICENSE
+++ b/cuda_python/LICENSE
@@ -176,3 +176,28 @@ Copyright (c) 2024-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
       of your accepting any such warranty or additional liability.
 
    END OF TERMS AND CONDITIONS
+
+   APPENDIX: How to apply the Apache License to your work.
+
+      To apply the Apache License to your work, attach the following
+      boilerplate notice, with the fields enclosed by brackets "[]"
+      replaced with your own identifying information. (Don't include
+      the brackets!)  The text should be enclosed in the appropriate
+      comment syntax for the file format. We also recommend that a
+      file or class name and description of purpose be included on the
+      same "printed page" as the copyright notice for easier
+      identification within third-party archives.
+
+   Copyright [yyyy] [name of copyright owner]
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.
diff --git a/cuda_python/docs/environment-docs.yml b/cuda_python/docs/environment-docs.yml
index d6c5dde6c9b..3152f0a3a93 100644
--- a/cuda_python/docs/environment-docs.yml
+++ b/cuda_python/docs/environment-docs.yml
@@ -7,7 +7,7 @@ channels:
 dependencies:
   # ATTENTION: This dependency list is duplicated in
   #            toolshed/setup-docs-env.sh. Please KEEP THEM IN SYNC!
-  - cython
+  - cython >=3.2.5,<3.3
   - myst-parser
   - numpy
   - numpydoc
diff --git a/cuda_python/docs/exts/release_toc.py b/cuda_python/docs/exts/release_toc.py
index 78345da8974..ac833b1990f 100644
--- a/cuda_python/docs/exts/release_toc.py
+++ b/cuda_python/docs/exts/release_toc.py
@@ -7,8 +7,7 @@
 from sphinx.directives.other import TocTree
 
 
-def _version_sort_key(docname):
-    version_text = Path(docname).name.removesuffix("-notes")
+def _version_sort_key(version_text):
     normalized = version_text.replace(".x", ".999999")
     try:
         return (1, Version(normalized))
@@ -16,6 +15,14 @@ def _version_sort_key(docname):
         return (0, version_text)
 
 
+def _is_prerelease(version_text):
+    try:
+        version = Version(version_text)
+        return version.is_prerelease
+    except InvalidVersion:
+        return False
+
+
 class TocTreeSorted(TocTree):
     """A toctree directive that sorts entries by version."""
 
@@ -30,7 +37,9 @@ def parse_content(self, toctree):
             return
 
         entries = [(Path(x[1]).name.removesuffix("-notes"), x[1]) for x in entries]
-        entries.sort(key=lambda x: _version_sort_key(x[1]), reverse=True)
+        # Don't include any prereleases in the toctree
+        entries = [entry for entry in entries if not _is_prerelease(entry[0])]
+        entries.sort(key=lambda x: _version_sort_key(x[0]), reverse=True)
         toctree["entries"] = entries
 
 
diff --git a/cuda_python/docs/nv-versions.json b/cuda_python/docs/nv-versions.json
index 0d0772ccf40..1d442c13209 100644
--- a/cuda_python/docs/nv-versions.json
+++ b/cuda_python/docs/nv-versions.json
@@ -3,6 +3,10 @@
         "version": "latest",
         "url": "https://nvidia.github.io/cuda-python/latest/"
     },
+    {
+        "version": "13.4.1",
+        "url": "https://nvidia.github.io/cuda-python/13.4.1/"
+    },
     {
         "version": "13.3.1",
         "url": "https://nvidia.github.io/cuda-python/13.3.1/"
diff --git a/cuda_python/docs/source/index.rst b/cuda_python/docs/source/index.rst
index 472a9bee90f..199758f0cf8 100644
--- a/cuda_python/docs/source/index.rst
+++ b/cuda_python/docs/source/index.rst
@@ -29,7 +29,7 @@ multiple components:
 .. _device: https://docs.nvidia.com/cuda/nvmath-python/latest/overview.html#device-apis
 .. _distributed: https://docs.nvidia.com/cuda/nvmath-python/latest/distributed-apis/index.html
 .. _nvmath.bindings: https://docs.nvidia.com/cuda/nvmath-python/latest/bindings/index.html
-.. _nvshmem4py: https://docs.nvidia.com/nvshmem/api/api/language_bindings/python/index.html
+.. _nvshmem4py: https://docs.nvidia.com/nvshmem/api/latest/api/language_bindings/python/index.html
 .. _Nsight Python: https://docs.nvidia.com/nsight-python/index.html
 .. _CUPTI Python: https://docs.nvidia.com/cupti-python/
 .. _Accelerated Computing Hub: https://github.com/NVIDIA/accelerated-computing-hub
@@ -55,7 +55,7 @@ be available, please refer to the `cuda.bindings`_ documentation for installatio
    numba.cuda <https://nvidia.github.io/numba-cuda/>
    cuda.tile <https://docs.nvidia.com/cuda/cutile-python/>
    nvmath-python <https://docs.nvidia.com/cuda/nvmath-python/>
-   nvshmem4py <https://docs.nvidia.com/nvshmem/api/api/language_bindings/python/index.html>
+   nvshmem4py <https://docs.nvidia.com/nvshmem/api/latest/api/language_bindings/python/index.html>
    Nsight Python <https://docs.nvidia.com/nsight-python/index.html>
    CUPTI Python <https://docs.nvidia.com/cupti-python/>
    Accelerated Computing Hub <https://github.com/NVIDIA/accelerated-computing-hub>
diff --git a/cuda_python/docs/source/release/13.4.1-notes.rst b/cuda_python/docs/source/release/13.4.1-notes.rst
new file mode 100644
index 00000000000..485d17366f1
--- /dev/null
+++ b/cuda_python/docs/source/release/13.4.1-notes.rst
@@ -0,0 +1,17 @@
+.. SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+.. SPDX-License-Identifier: Apache-2.0
+
+CUDA Python 13.4.1 Release notes
+=================================
+
+Deprecation Notices
+-------------------
+
+* Support for using ``cuda-python`` with Python 3.10 is deprecated and will be
+  removed in a future version.  Python 3.10 reaches end of life in October 2026
+  per the `CPython support cycle <https://devguide.python.org/versions/>`_.
+
+Known issues
+------------
+
+* Updating from older versions (v12.6.2.post1 and below) via ``pip install -U cuda-python`` might not work. Please do a clean re-installation by uninstalling ``pip uninstall -y cuda-python`` followed by installing ``pip install cuda-python``.
diff --git a/cuda_python/setup.py b/cuda_python/setup.py
index dad8a596c95..fb04dade50a 100644
--- a/cuda_python/setup.py
+++ b/cuda_python/setup.py
@@ -32,7 +32,7 @@
     version=version,
     install_requires=[
         f"cuda-bindings{matcher}{version}",
-        "cuda-core~=1.0.0",
+        "cuda-core~=1.2.0",
         "cuda-pathfinder~=1.1",
     ],
     extras_require={
diff --git a/cuda_python_test_helpers/cuda_python_test_helpers/__init__.py b/cuda_python_test_helpers/cuda_python_test_helpers/__init__.py
index 342c2477ffc..7e1e33a428b 100644
--- a/cuda_python_test_helpers/cuda_python_test_helpers/__init__.py
+++ b/cuda_python_test_helpers/cuda_python_test_helpers/__init__.py
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 import ctypes
@@ -8,6 +8,7 @@
 from contextlib import suppress
 
 __all__ = [
+    "IS_LINUX",
     "IS_WINDOWS",
     "IS_WSL",
     "libc",
@@ -26,6 +27,7 @@ def _detect_wsl() -> bool:
 
 IS_WSL: bool = _detect_wsl()
 IS_WINDOWS: bool = platform.system() == "Windows" or sys.platform.startswith("win")
+IS_LINUX: bool = not IS_WINDOWS and not IS_WSL and platform.system() == "Linux"
 
 if IS_WINDOWS:
     libc = ctypes.CDLL("msvcrt.dll")
@@ -63,3 +65,13 @@ def under_compute_sanitizer() -> bool:
     # Another common indicator: sanitizer injectors are configured via env vars.
     inj = os.environ.get("CUDA_INJECTION64_PATH", "")
     return "compute-sanitizer" in inj or "cuda-memcheck" in inj
+
+
+def driver_version_less_than(target):
+    from cuda.bindings import driver
+
+    (err,) = driver.cuInit(0)
+    assert err == driver.CUresult.CUDA_SUCCESS
+    err, version = driver.cuDriverGetVersion()
+    assert err == driver.CUresult.CUDA_SUCCESS
+    return version < target
diff --git a/conftest.py b/cuda_python_test_helpers/cuda_python_test_helpers/_pytest_plugin.py
similarity index 65%
rename from conftest.py
rename to cuda_python_test_helpers/cuda_python_test_helpers/_pytest_plugin.py
index ea53d79546e..1c0e37988b6 100644
--- a/conftest.py
+++ b/cuda_python_test_helpers/cuda_python_test_helpers/_pytest_plugin.py
@@ -1,30 +1,32 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
+"""Pytest plugin registered via the ``pytest11`` entry point.
 
-import os
+Automatically tags collected items with package markers and gates cython
+tests on CUDA header availability.  Loaded by pytest whenever
+``cuda-python-test-helpers`` is installed, and also explicitly via
+``pytest_plugins`` in each subpackage conftest so the fallback sys.path
+install path is covered too.
+"""
 
 import pytest
 
-from cuda.pathfinder import get_cuda_path_or_home
-
-
-# Please keep in sync with the copy in cuda_core/tests/conftest.py.
-def _cuda_headers_available() -> bool:
-    """Return True if CUDA headers are available, False otherwise.
-
-    Returns False if no CUDA path is set or if the CUDA path has no
-    include/ subdirectory (e.g. a sanitizer-only mini-CTK install).
-    """
-    cuda_path = get_cuda_path_or_home()
-    if cuda_path is None:
-        return False
-    return os.path.isdir(os.path.join(cuda_path, "include"))
+from cuda_python_test_helpers import IS_WINDOWS
+from cuda_python_test_helpers.marks import _cuda_headers_available
 
 
 def pytest_collection_modifyitems(config, items):  # noqa: ARG001
     have_headers = _cuda_headers_available()
     for item in items:
+        if IS_WINDOWS and "subtests" in getattr(item, "fixturenames", ()):
+            item.add_marker(
+                pytest.mark.thread_unsafe(
+                    reason="as of 2026-09, subtests are not thread-safe on windows: "
+                    "https://github.com/Quansight-Labs/pytest-run-parallel/issues/195"
+                )
+            )
+
         nodeid = item.nodeid.replace("\\", "/")
 
         # Package markers by path
diff --git a/cuda_python_test_helpers/cuda_python_test_helpers/arch_check.py b/cuda_python_test_helpers/cuda_python_test_helpers/arch_check.py
new file mode 100644
index 00000000000..2eb0a61ffca
--- /dev/null
+++ b/cuda_python_test_helpers/cuda_python_test_helpers/arch_check.py
@@ -0,0 +1,94 @@
+# SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-License-Identifier: Apache-2.0
+
+from __future__ import annotations
+
+from contextlib import contextmanager
+from functools import cache
+
+import pytest
+
+
+@cache
+def hardware_supports_nvml():
+    """Try the simplest NVML API to verify basic functionality.
+
+    Returns False on platforms where NVML is unsupported (e.g. Jetson Orin).
+    """
+    from cuda.bindings import nvml
+    from cuda.bindings._internal.utils import FunctionNotFoundError as NvmlSymbolNotFoundError  # noqa: F401
+
+    nvml.init_v2()
+    try:
+        nvml.system_get_driver_branch()
+    except (nvml.NotSupportedError, nvml.UnknownError):
+        return False
+    else:
+        return True
+    finally:
+        nvml.shutdown()
+
+
+def _should_skip_nvml_tests() -> bool:
+    """Return True if NVML tests should be skipped on this system.
+
+    Checks cuda.core's compatibility gate first (if cuda.core is installed),
+    then falls back to a hardware-level NVML probe.
+    """
+    try:
+        from cuda.core import system
+
+        if not system.CUDA_BINDINGS_NVML_IS_COMPATIBLE:
+            return True
+    except ImportError:
+        pass  # cuda.core not installed; skip the compat gate
+    return not hardware_supports_nvml()
+
+
+skip_if_nvml_unsupported = pytest.mark.skipif(
+    _should_skip_nvml_tests(),
+    reason="NVML support requires cuda.bindings version 12.9.6+ for CUDA 12.x or 13.2.0+ for CUDA 13.x, and hardware that supports NVML",
+)
+
+
+@contextmanager
+def unsupported_before(device, expected_device_arch):
+    """Context manager that skips or xfails when an NVML API is not supported on this device.
+
+    ``device`` may be a raw NVML device handle (int) or any object that exposes
+    the handle via a ``._handle`` attribute (e.g. ``cuda.core.system.Device``).
+    """
+    from cuda.bindings import nvml
+    from cuda.bindings._internal.utils import FunctionNotFoundError as NvmlSymbolNotFoundError
+
+    handle = getattr(device, "_handle", device)
+    device_arch = nvml.device_get_architecture(handle)
+
+    if isinstance(expected_device_arch, nvml.DeviceArch):
+        expected_device_arch_int = int(expected_device_arch)
+    elif expected_device_arch == "FERMI":
+        expected_device_arch_int = 1
+    else:
+        expected_device_arch_int = 0
+
+    if expected_device_arch is None or expected_device_arch == "HAS_INFOROM" or device_arch == nvml.DeviceArch.UNKNOWN:
+        # We don't know if it will fail, so we tolerate either outcome.
+        #
+        # TODO: There are APIs that are documented as supported only if the
+        # device has an InfoROM, but I couldn't find a way to detect that.  For
+        # now, they are just handled as "possibly failing".
+        try:
+            yield
+        except (nvml.NotSupportedError, nvml.FunctionNotFoundError, NvmlSymbolNotFoundError):
+            try:
+                name = nvml.DeviceArch(device_arch).name
+            except ValueError:
+                name = f"UNKNOWN({device_arch})"
+            pytest.skip(f"Unsupported call for device architecture {name} on device '{nvml.device_get_name(handle)}'")
+    elif int(device_arch) < expected_device_arch_int:
+        # We know it will fail; assert that it does.
+        with pytest.raises(nvml.NotSupportedError):
+            yield
+        pytest.skip(f"Unsupported before {expected_device_arch.name}, got {nvml.device_get_name(handle)}")
+    else:
+        yield
diff --git a/cuda_python_test_helpers/cuda_python_test_helpers/graphics.py b/cuda_python_test_helpers/cuda_python_test_helpers/graphics.py
new file mode 100644
index 00000000000..0f25554a111
--- /dev/null
+++ b/cuda_python_test_helpers/cuda_python_test_helpers/graphics.py
@@ -0,0 +1,65 @@
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+"""GL availability classification for graphics interop tests.
+
+Both ``cuda_core`` and ``cuda_bindings`` graphics tests need to skip
+when the GL backend cannot be made current, and that decision must not
+hide real bugs in the tests' own GL allocation code. This module owns the
+shared predicate so the two test suites stay in sync.
+
+The helper intentionally does **not** import ``pyglet``: importing
+``pyglet.gl`` / ``pyglet.window`` triggers pyglet's shadow-window
+creation, which fails on headless machines before the test has had a
+chance to set ``pyglet.options["headless"]``. Classification is by
+exception module/name and tightly matched built-in loader errors instead.
+"""
+
+_GL_CONTEXT_UNAVAILABLE_EXC_NAMES = frozenset(
+    {
+        "NoSuchDisplayException",
+        "NoSuchConfigException",
+        "NoSuchScreenModeException",
+        "WindowException",
+        "ContextException",
+        # Pyglet's headless display raises MissingFunctionException when libEGL
+        # exists but eglQueryDevicesEXT / eglGetPlatformDisplayEXT entry points do not.
+        "MissingFunctionException",
+    }
+)
+
+# pyglet raises these from pyglet/lib.py when libGL/libEGL cannot be loaded.
+_PYGLET_GL_LIBRARY_IMPORT_ERRORS = frozenset(
+    {
+        'Library "GL" not found.',
+        'Library "EGL" not found.',
+    }
+)
+
+
+def is_gl_context_unavailable(exc: BaseException) -> bool:
+    """Return True if *exc* means "no GL context could be created".
+
+    Returns False for any other exception, so a real bug in the caller's
+    own GL allocation code (e.g. a ``GLException`` from an invalid-enum GL
+    call, a ``TypeError`` from wrong argument types) propagates and
+    fails the test rather than being hidden as a skip.
+    """
+    exc_type = type(exc)
+    if exc_type.__module__.startswith("pyglet") and exc_type.__name__ in _GL_CONTEXT_UNAVAILABLE_EXC_NAMES:
+        return True
+
+    # Windows CI runners may lack opengl32.dll; pyglet's WGL backend raises
+    # FileNotFoundError from ctypes.windll.opengl32. On newer Python
+    # (3.12+) ctypes.LibraryLoader catches that and re-raises
+    # AttributeError(dll_name). Match narrowly on the dll name so a
+    # different FileNotFoundError or AttributeError from our own code
+    # does not match.
+    if isinstance(exc, (FileNotFoundError, AttributeError)) and "opengl32" in str(exc):
+        return True
+
+    # Linux without libGL/libEGL: pyglet raises ImportError with the
+    # exact messages above from pyglet/lib.py. A different ImportError
+    # from our own code does not match.
+    return isinstance(exc, ImportError) and str(exc) in _PYGLET_GL_LIBRARY_IMPORT_ERRORS
diff --git a/cuda_core/tests/helpers/marks.py b/cuda_python_test_helpers/cuda_python_test_helpers/marks.py
similarity index 66%
rename from cuda_core/tests/helpers/marks.py
rename to cuda_python_test_helpers/cuda_python_test_helpers/marks.py
index 53fcc544eb7..03d6ff2b622 100644
--- a/cuda_core/tests/helpers/marks.py
+++ b/cuda_python_test_helpers/cuda_python_test_helpers/marks.py
@@ -1,12 +1,15 @@
 # SPDX-FileCopyrightText: Copyright (c) 2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
-"""Reusable pytest marks for cuda_core tests."""
+"""Reusable pytest marks and skip helpers for CUDA Python test suites."""
 
 import inspect
+import os
 
 import pytest
 
+from cuda.pathfinder import get_cuda_path_or_home
+
 
 def requires_module(module, *args, **kwargs):
     """Skip the test if a module is missing or older than required.
@@ -43,3 +46,23 @@ def test_bar(): ...
         return pytest.mark.skipif(True, reason=str(exc))
     else:
         return pytest.mark.skipif(False, reason="")
+
+
+def _cuda_headers_available() -> bool:
+    """Return True if CUDA headers are available, False if no CUDA path is set.
+
+    Raises AssertionError if a CUDA path is set but has no include/ subdirectory.
+    """
+    cuda_path = get_cuda_path_or_home()
+    if cuda_path is None:
+        return False
+    assert os.path.isdir(os.path.join(cuda_path, "include")), (
+        f"CUDA path {cuda_path} does not contain an 'include' subdirectory"
+    )
+    return True
+
+
+skipif_need_cuda_headers = pytest.mark.skipif(
+    not _cuda_headers_available(),
+    reason="need CUDA header",
+)
diff --git a/cuda_bindings/cuda/bindings/_test_helpers/mempool.py b/cuda_python_test_helpers/cuda_python_test_helpers/mempool.py
similarity index 84%
rename from cuda_bindings/cuda/bindings/_test_helpers/mempool.py
rename to cuda_python_test_helpers/cuda_python_test_helpers/mempool.py
index e2a61e48c53..c1fad576da9 100644
--- a/cuda_bindings/cuda/bindings/_test_helpers/mempool.py
+++ b/cuda_python_test_helpers/cuda_python_test_helpers/mempool.py
@@ -5,16 +5,11 @@
 
 import pytest
 
-from cuda.bindings import driver, runtime
 
-
-# Keep in sync with the fallback in cuda_core/tests/conftest.py. The cuda_core
-# copy is intentionally simpler because it only handles cuda_core CUDAError
-# exceptions when this helper is absent from older published bindings.
 def is_windows_mcdm_device(device=0):
     if sys.platform != "win32":
         return False
-    import cuda.bindings.nvml as nvml
+    from cuda.bindings import driver, nvml
 
     device_id = int(getattr(device, "device_id", device))
     (err,) = driver.cuInit(0)
@@ -34,6 +29,8 @@ def is_windows_mcdm_device(device=0):
 
 
 def xfail_if_mempool_oom(err_or_exc, api_name=None, device=0):
+    from cuda.bindings import driver, runtime
+
     if api_name is not None and not isinstance(api_name, str):
         device = api_name
         api_name = None
diff --git a/cuda_bindings/cuda/bindings/_test_helpers/pep723.py b/cuda_python_test_helpers/cuda_python_test_helpers/pep723.py
similarity index 100%
rename from cuda_bindings/cuda/bindings/_test_helpers/pep723.py
rename to cuda_python_test_helpers/cuda_python_test_helpers/pep723.py
diff --git a/cuda_python_test_helpers/pyproject.toml b/cuda_python_test_helpers/pyproject.toml
index 85652b61c50..f20720f6158 100644
--- a/cuda_python_test_helpers/pyproject.toml
+++ b/cuda_python_test_helpers/pyproject.toml
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 [build-system]
@@ -12,7 +12,7 @@ description = "Shared test helpers for CUDA Python projects"
 readme = {file = "README.md", content-type = "text/markdown"}
 authors = [{ name = "NVIDIA Corporation" }]
 license = "Apache-2.0"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 classifiers = [
   "Programming Language :: Python :: 3 :: Only",
   "Operating System :: POSIX :: Linux",
diff --git a/pytest.ini b/pytest.ini
index 148b722aca2..505b4269490 100644
--- a/pytest.ini
+++ b/pytest.ini
@@ -2,7 +2,7 @@
 # SPDX-License-Identifier: Apache-2.0
 
 [pytest]
-addopts = --showlocals
+addopts = --showlocals --durations=20
 norecursedirs =
     cuda_bindings/examples
     cuda_core/examples
diff --git a/toolshed/_catalog_writer.py b/toolshed/_catalog_writer.py
deleted file mode 100644
index b41fb5838dd..00000000000
--- a/toolshed/_catalog_writer.py
+++ /dev/null
@@ -1,182 +0,0 @@
-#!/usr/bin/env python3
-
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-# SPDX-License-Identifier: Apache-2.0
-
-"""Shared helper for reading, updating, and rewriting descriptor_catalog.py.
-
-Each toolshed script that extracts data from CTK distributions or wheel
-layouts uses this module to merge its findings into the authored catalog
-without touching fields it doesn't own.
-"""
-
-from __future__ import annotations
-
-import dataclasses
-import json
-import sys
-from pathlib import Path
-
-# Ensure the cuda_pathfinder package is importable.
-_REPO_ROOT = Path(__file__).resolve().parents[1]
-_PATHFINDER_ROOT = _REPO_ROOT / "cuda_pathfinder"
-if str(_PATHFINDER_ROOT) not in sys.path:
-    sys.path.insert(0, str(_PATHFINDER_ROOT))
-
-from cuda.pathfinder._dynamic_libs.descriptor_catalog import (  # noqa: E402
-    DESCRIPTOR_CATALOG,
-    DescriptorSpec,
-)
-
-CATALOG_PATH = _PATHFINDER_ROOT / "cuda" / "pathfinder" / "_dynamic_libs" / "descriptor_catalog.py"
-
-_DEFAULTS = DescriptorSpec(name="", packaged_with="ctk")
-
-_SECTION_COMMENTS = {
-    "ctk": (
-        "    # -----------------------------------------------------------------------\n"
-        "    # CTK (CUDA Toolkit) libraries\n"
-        "    # -----------------------------------------------------------------------"
-    ),
-    "other": (
-        "    # -----------------------------------------------------------------------\n"
-        "    # Third-party / separately packaged libraries\n"
-        "    # -----------------------------------------------------------------------"
-    ),
-    "driver": (
-        "    # -----------------------------------------------------------------------\n"
-        "    # Driver libraries (system-search only, no CTK cascade)\n"
-        "    # -----------------------------------------------------------------------"
-    ),
-}
-
-
-def _quote(s: str) -> str:
-    return json.dumps(s)
-
-
-def _render_tuple(values: tuple[str, ...]) -> str:
-    if not values:
-        return "()"
-    if len(values) == 1:
-        return f"({_quote(values[0])},)"
-    return "(" + ", ".join(_quote(v) for v in values) + ")"
-
-
-def _render_spec(spec: DescriptorSpec) -> str:
-    """Render a single DescriptorSpec constructor call, omitting default-valued fields."""
-    lines = [
-        "    DescriptorSpec(",
-        f"        name={_quote(spec.name)},",
-        f'        packaged_with="{spec.packaged_with}",',
-    ]
-
-    tuple_fields = [
-        "linux_sonames",
-        "windows_dlls",
-        "site_packages_linux",
-        "site_packages_windows",
-        "dependencies",
-        "anchor_rel_dirs_linux",
-        "anchor_rel_dirs_windows",
-        "ctk_root_canary_anchor_libnames",
-    ]
-    bool_fields = [
-        "requires_add_dll_directory",
-        "requires_rtld_deepbind",
-    ]
-
-    for field in tuple_fields:
-        value = getattr(spec, field)
-        default = getattr(_DEFAULTS, field)
-        if value != default:
-            lines.append(f"        {field}={_render_tuple(value)},")
-
-    for field in bool_fields:
-        value = getattr(spec, field)
-        default = getattr(_DEFAULTS, field)
-        if value != default:
-            lines.append(f"        {field}={value},")
-
-    lines.append("    ),")
-    return "\n".join(lines)
-
-
-def render_catalog(specs: tuple[DescriptorSpec, ...]) -> str:
-    """Render the full descriptor_catalog.py file content."""
-    header = '''\
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-# SPDX-License-Identifier: Apache-2.0
-
-"""Canonical authored descriptor catalog for dynamic libraries."""
-
-from __future__ import annotations
-
-from dataclasses import dataclass
-from typing import Literal
-
-PackagedWith = Literal["ctk", "other", "driver"]
-
-
-@dataclass(frozen=True, slots=True)
-class DescriptorSpec:
-    name: str
-    packaged_with: PackagedWith
-    linux_sonames: tuple[str, ...] = ()
-    windows_dlls: tuple[str, ...] = ()
-    site_packages_linux: tuple[str, ...] = ()
-    site_packages_windows: tuple[str, ...] = ()
-    dependencies: tuple[str, ...] = ()
-    anchor_rel_dirs_linux: tuple[str, ...] = ("lib64", "lib")
-    anchor_rel_dirs_windows: tuple[str, ...] = ("bin/x64", "bin")
-    ctk_root_canary_anchor_libnames: tuple[str, ...] = ()
-    requires_add_dll_directory: bool = False
-    requires_rtld_deepbind: bool = False
-
-
-DESCRIPTOR_CATALOG: tuple[DescriptorSpec, ...] = (
-'''
-
-    body_parts: list[str] = []
-    prev_packaged_with = None
-    for spec in specs:
-        if spec.packaged_with != prev_packaged_with:
-            comment = _SECTION_COMMENTS.get(spec.packaged_with)
-            if comment is not None:
-                body_parts.append(comment)
-            prev_packaged_with = spec.packaged_with
-        body_parts.append(_render_spec(spec))
-
-    footer = ")\n"
-    return header + "\n".join(body_parts) + "\n" + footer
-
-
-def load_catalog() -> tuple[DescriptorSpec, ...]:
-    """Return the current DESCRIPTOR_CATALOG from disk."""
-    return DESCRIPTOR_CATALOG
-
-
-def load_catalog_as_dict() -> dict[str, DescriptorSpec]:
-    """Return the current catalog keyed by name."""
-    return {spec.name: spec for spec in DESCRIPTOR_CATALOG}
-
-
-def update_specs(
-    catalog: tuple[DescriptorSpec, ...],
-    updates: dict[str, dict[str, object]],
-) -> tuple[DescriptorSpec, ...]:
-    """Apply field updates to matching specs by name, preserving order."""
-    result = []
-    for spec in catalog:
-        if spec.name in updates:
-            result.append(dataclasses.replace(spec, **updates[spec.name]))
-        else:
-            result.append(spec)
-    return tuple(result)
-
-
-def write_catalog(specs: tuple[DescriptorSpec, ...], path: Path | None = None) -> None:
-    """Render and write the catalog to disk."""
-    if path is None:
-        path = CATALOG_PATH
-    path.write_text(render_catalog(specs), encoding="utf-8")
diff --git a/toolshed/build_pathfinder_dlls.py b/toolshed/build_pathfinder_dlls.py
deleted file mode 100755
index 63abba52386..00000000000
--- a/toolshed/build_pathfinder_dlls.py
+++ /dev/null
@@ -1,118 +0,0 @@
-#!/usr/bin/env python3
-
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
-
-"""Scan 7z listing files for .dll names, update descriptor_catalog.py.
-
-Usage:
-    # First generate listings from CTK .exe installers:
-    #   for exe in *.exe; do 7z l "$exe" > "${exe%.exe}.txt"; done
-    python toolshed/build_pathfinder_dlls.py listing1.txt [listing2.txt ...]
-"""
-
-from __future__ import annotations
-
-import collections
-import sys
-from pathlib import Path
-
-sys.path.insert(0, str(Path(__file__).resolve().parent))
-from _catalog_writer import load_catalog, update_specs, write_catalog
-
-
-def _is_suppressed_dll(libname: str, dll: str) -> bool:
-    if libname == "cudart":
-        if dll.startswith("cudart32_"):
-            return True
-        if dll == "cudart64_65.dll":
-            # PhysX/files/Common/cudart64_65.dll from CTK 6.5, but shipped with CTK 12.0-12.9
-            return True
-        if dll == "cudart64_101.dll":
-            # GFExperience.NvStreamSrv/amd64/server/cudart64_101.dll from CTK 10.1, but shipped with CTK 12.0-12.6
-            return True
-    elif libname == "nvrtc":
-        if dll.endswith(".alt.dll"):
-            return True
-        if dll.startswith("nvrtc-builtins"):
-            return True
-    elif libname == "nvvm" and dll == "nvvm32.dll":
-        return True
-    return False
-
-
-def _parse_listings(paths: list[str]) -> set[str]:
-    dlls: set[str] = set()
-    for filename in paths:
-        lines_iter = iter(Path(filename).read_text().splitlines())
-        for line in lines_iter:
-            if line.startswith("-------------------"):
-                break
-        else:
-            raise RuntimeError(f"------------------- NOT FOUND in {filename}")
-        for line in lines_iter:
-            if line.startswith("-------------------"):
-                break
-            assert line[52] == " ", line
-            assert line[53] != " ", line
-            path = line[53:]
-            if path.endswith(".dll"):
-                dll = path.rsplit("/", 1)[1]
-                dlls.add(dll)
-        else:
-            raise RuntimeError(f"------------------- NOT FOUND in {filename}")
-    return dlls
-
-
-def run(listing_files: list[str]) -> None:
-    dlls_from_files = _parse_listings(listing_files)
-    catalog = load_catalog()
-
-    # Longest-prefix-first to avoid ambiguous matches (e.g. "cufftw" before "cufft").
-    ctk_names = sorted(
-        (spec.name for spec in catalog if spec.packaged_with == "ctk"),
-        key=lambda n: (-len(n), n),
-    )
-
-    dlls_in_scope: set[str] = set()
-    dlls_by_name: dict[str, list[str]] = collections.defaultdict(list)
-    suppressed: set[str] = set()
-
-    for name in ctk_names:
-        for dll in sorted(dlls_from_files):
-            if dll not in dlls_in_scope and dll.startswith(name):
-                if _is_suppressed_dll(name, dll):
-                    suppressed.add(dll)
-                else:
-                    dlls_by_name[name].append(dll)
-                dlls_in_scope.add(dll)
-
-    updates: dict[str, dict[str, object]] = {}
-    for name, dlls in dlls_by_name.items():
-        updates[name] = {"windows_dlls": tuple(dlls)}
-
-    if updates:
-        write_catalog(update_specs(catalog, updates))
-        for name in sorted(updates):
-            print(f"  updated {name}: windows_dlls={updates[name]['windows_dlls']}")
-    else:
-        print("No matching DLLs found.")
-
-    if suppressed:
-        print(f"\nSuppressed DLLs ({len(suppressed)}):")
-        for dll in sorted(suppressed):
-            print(f"  {dll}")
-
-    out_of_scope = dlls_from_files - dlls_in_scope
-    if out_of_scope:
-        print(f"\nDLLs out of scope ({len(out_of_scope)}):")
-        for dll in sorted(out_of_scope):
-            print(f"  {dll}")
-
-
-if __name__ == "__main__":
-    if len(sys.argv) < 2:
-        print("Usage: build_pathfinder_dlls.py <7z-listing.txt> ...", file=sys.stderr)
-        sys.exit(1)
-    run(listing_files=sys.argv[1:])
diff --git a/toolshed/build_pathfinder_sonames.py b/toolshed/build_pathfinder_sonames.py
deleted file mode 100755
index b3fa6c2efc9..00000000000
--- a/toolshed/build_pathfinder_sonames.py
+++ /dev/null
@@ -1,93 +0,0 @@
-#!/usr/bin/env python3
-
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
-
-"""Scan directories for .so files, extract SONAMEs, update descriptor_catalog.py.
-
-Usage:
-    python toolshed/build_pathfinder_sonames.py /path/to/cuda [/more/paths ...]
-"""
-
-from __future__ import annotations
-
-import os
-import subprocess
-import sys
-from pathlib import Path
-
-sys.path.insert(0, str(Path(__file__).resolve().parent))
-from _catalog_writer import load_catalog, update_specs, write_catalog
-
-
-def _extract_soname(path: str) -> str | None:
-    try:
-        out = subprocess.run(  # noqa: S603
-            ["readelf", "-d", path],  # noqa: S607
-            capture_output=True,
-            text=True,
-            timeout=10,
-        )
-    except (FileNotFoundError, subprocess.TimeoutExpired):
-        return None
-    for line in out.stdout.splitlines():
-        if "SONAME" in line:
-            # Format: 0x000000000000000e (SONAME)  Library soname: [libfoo.so.1]
-            start = line.find("[")
-            end = line.find("]")
-            if start != -1 and end != -1:
-                return line[start + 1 : end]
-    return None
-
-
-def _find_sonames(roots: list[str]) -> set[str]:
-    sonames: set[str] = set()
-    for root in roots:
-        for dirpath, _dirnames, filenames in os.walk(root):
-            for fname in filenames:
-                if ".so" not in fname:
-                    continue
-                full = os.path.join(dirpath, fname)
-                if os.path.islink(full):
-                    continue
-                soname = _extract_soname(full)
-                if soname is not None:
-                    sonames.add(soname)
-    return sonames
-
-
-def run(roots: list[str]) -> None:
-    sonames_found = _find_sonames(roots)
-    catalog = load_catalog()
-
-    updates: dict[str, dict[str, object]] = {}
-    matched: set[str] = set()
-    for spec in catalog:
-        if spec.packaged_with != "ctk":
-            continue
-        prefix = "lib" + spec.name + ".so"
-        found = tuple(sorted(s for s in sonames_found if s.startswith(prefix)))
-        if found:
-            updates[spec.name] = {"linux_sonames": found}
-            matched.update(found)
-
-    if updates:
-        write_catalog(update_specs(catalog, updates))
-        for name, upd in sorted(updates.items()):
-            print(f"  updated {name}: linux_sonames={upd['linux_sonames']}")
-    else:
-        print("No matching sonames found.")
-
-    unmatched = sonames_found - matched
-    if unmatched:
-        print(f"\nSONAMEs not matched to any CTK descriptor ({len(unmatched)}):")
-        for s in sorted(unmatched):
-            print(f"  {s}")
-
-
-if __name__ == "__main__":
-    if len(sys.argv) < 2:
-        print("Usage: build_pathfinder_sonames.py <dir> [<dir> ...]", file=sys.stderr)
-        sys.exit(1)
-    run(roots=sys.argv[1:])
diff --git a/toolshed/build_static_bitcode_input.py b/toolshed/build_static_bitcode_input.py
index e2400100dde..816603aed50 100755
--- a/toolshed/build_static_bitcode_input.py
+++ b/toolshed/build_static_bitcode_input.py
@@ -1,6 +1,6 @@
 #!/usr/bin/env python3
 
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES.
+# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 """
@@ -14,9 +14,9 @@
 """
 
 import binascii
-import os
 import sys
 import textwrap
+from pathlib import Path
 
 import llvmlite.binding  # HINT: pip install llvmlite
 
@@ -24,11 +24,9 @@
 
 
 def get_minimal_nvvmir_txt_template():
-    cuda_bindings_tests_dir = os.path.normpath("cuda_bindings/tests")
-    assert os.path.isdir(cuda_bindings_tests_dir), (
-        "Please run this helper script from the cuda-python top-level directory."
-    )
-    sys.path.insert(0, os.path.abspath(cuda_bindings_tests_dir))
+    cuda_bindings_tests_dir = Path("cuda_bindings/tests")
+    assert cuda_bindings_tests_dir.is_dir(), "Please run this helper script from the cuda-python top-level directory."
+    sys.path.insert(0, str(cuda_bindings_tests_dir.resolve()))
     import test_nvvm
 
     return test_nvvm.MINIMAL_NVVMIR_TXT_TEMPLATE
diff --git a/toolshed/check_cython_abi.py b/toolshed/check_cython_abi.py
index 155d9c625f3..b72edf40c5c 100644
--- a/toolshed/check_cython_abi.py
+++ b/toolshed/check_cython_abi.py
@@ -92,6 +92,21 @@ def is_cython_module(module: object) -> bool:
     return hasattr(module, "__pyx_capi__")
 
 
+def iter_public_extension_modules(build_dir: Path):
+    """Yield the extension modules under `build_dir` that are part of the public ABI.
+
+    Private modules (e.g. cuda/bindings/_internal/utils.so) are skipped. Only the
+    path *inside* the package is inspected: directories above it routinely start
+    with an underscore (manylinux installs Python under /opt/_internal, GitHub
+    Actions containers check out under /__w), and those must not make every
+    module look private.
+    """
+    for so_path in Path(build_dir).glob(f"**/*{EXT_SUFFIX}"):
+        if any(part.startswith("_") for part in so_path.relative_to(build_dir).parts):
+            continue
+        yield so_path
+
+
 ######################################################################################
 # STRUCTS
 
@@ -473,7 +488,7 @@ def check(package: str, abi_dir: Path) -> bool:
             print(f"No module found for {abi_path.relative_to(abi_dir)}")
             has_errors = True
 
-    for so_path in Path(build_dir).glob(f"**/*{EXT_SUFFIX}"):
+    for so_path in iter_public_extension_modules(build_dir):
         module = import_from_path(package, build_dir, so_path)
         if hasattr(module, "__pyx_capi__"):
             abi_path = so_path_to_abi_path(so_path, build_dir, abi_dir)
@@ -498,10 +513,7 @@ def generate(package: str, abi_dir: Path) -> bool:
         return True
 
     build_dir = get_package_path(package)
-    for so_path in Path(build_dir).glob(f"**/*{EXT_SUFFIX}"):
-        if any(x.startswith("_") for x in so_path.parts):
-            # Skip private modules (e.g. _driver.so) since they are not part of the public ABI
-            continue
+    for so_path in iter_public_extension_modules(build_dir):
         try:
             module = import_from_path(package, build_dir, so_path)
         except ImportError:
diff --git a/toolshed/check_generated_file_seals.py b/toolshed/check_generated_file_seals.py
index 1a9c45de61b..4863fe32d61 100644
--- a/toolshed/check_generated_file_seals.py
+++ b/toolshed/check_generated_file_seals.py
@@ -2,7 +2,6 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import hashlib
-import os
 import re
 import subprocess
 import sys
@@ -17,7 +16,10 @@
 assert GENERATED_FILE_MARKER_FRAGMENT in GENERATED_FILE_SEAL_TOKEN
 _TOKEN_BYTES = GENERATED_FILE_SEAL_TOKEN.encode("ascii")
 _MARKER_REGEX = re.compile(
-    rb"^(?P<prefix>#|\.\.) "
+    # Keep the alternation in sync with the values of _COMMENT_CHARS below:
+    # a prefix that is not matched here can never reach the
+    # expected_comment_prefix() comparison in validate_generated_file_seal().
+    rb"^(?P<prefix>#|\.\.|//) "
     + re.escape(_TOKEN_BYTES)
     + rb" format=(?P<format>[0-9]+); content-sha256=(?P<digest>[0-9a-f]{64})\n$"
 )
@@ -142,7 +144,7 @@ def main(args):
 
     returncode = 0
     for filepath in args:
-        if not os.path.isfile(filepath):
+        if not Path(filepath).is_file():
             continue
         if not validate_generated_file_seal(filepath, previously_sealed_paths):
             returncode = 1
diff --git a/toolshed/check_spdx.py b/toolshed/check_spdx.py
index a2d0c041546..33276250e00 100644
--- a/toolshed/check_spdx.py
+++ b/toolshed/check_spdx.py
@@ -2,11 +2,10 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import datetime
-import os
 import re
 import subprocess
 import sys
-from pathlib import PureWindowsPath
+from pathlib import Path, PureWindowsPath
 
 import pathspec
 
@@ -22,6 +21,7 @@
 # Every top-level directory needs to have an entry here, so new paths
 # can't slip in without a reviewed license decision.
 TOP_LEVEL_DIRS_LICENSE_IDENTIFIERS = {
+    ".agents": "Apache-2.0",
     ".github": "Apache-2.0",
     "benchmarks": "Apache-2.0",
     "ci": "Apache-2.0",
@@ -36,10 +36,23 @@
 }
 
 SPDX_IGNORE_FILENAME = ".spdx-ignore"
+REPOSITORY_LICENSE_CONTENTS = Path("LICENSE").read_bytes()
+
+
+def license_files_match_repository(filepaths):
+    licenses_match = True
+    for filepath in filepaths:
+        license_path = Path(filepath)
+        if license_path.name != "LICENSE":
+            continue
+        if license_path.read_bytes() != REPOSITORY_LICENSE_CONTENTS:
+            print(f"PACKAGE LICENSE {filepath!r} does not match repository LICENSE")
+            licenses_match = False
+    return licenses_match
 
 
 def load_spdx_ignore():
-    if os.path.exists(SPDX_IGNORE_FILENAME):
+    if Path(SPDX_IGNORE_FILENAME).exists():
         with open(SPDX_IGNORE_FILENAME, encoding="utf-8") as f:
             lines = f.readlines()
     else:
@@ -50,7 +63,7 @@ def load_spdx_ignore():
 
 COPYRIGHT_REGEX = (
     rb"Copyright \(c\) (?P<years>[0-9]{4}(-[0-9]{4})?) "
-    rb"(?P<affiliation>NVIDIA CORPORATION( & AFFILIATES\. All rights reserved\.)?)"
+    rb"(?P<affiliation>NVIDIA CORPORATION & AFFILIATES\. All rights reserved\.)"
 )
 COPYRIGHT_SUB = r"Copyright (c) {} \g<affiliation>"
 CURRENT_YEAR = str(datetime.datetime.now(tz=datetime.timezone.utc).year)
@@ -203,9 +216,12 @@ def main(args):
     else:
         fix = False
 
+    returncode = 0
+    if not license_files_match_repository(args):
+        returncode = 1
+
     ignore_spec = load_spdx_ignore()
 
-    returncode = 0
     for filepath in args:
         if ignore_spec.match_file(filepath):
             continue
diff --git a/toolshed/collect_site_packages_dll_files.ps1 b/toolshed/collect_site_packages_dll_files.ps1
index f0a6f799242..4efebbf3aab 100644
--- a/toolshed/collect_site_packages_dll_files.ps1
+++ b/toolshed/collect_site_packages_dll_files.ps1
@@ -1,12 +1,11 @@
 # collect_site_packages_dll_files.ps1
 
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # Usage:
 #     cd cuda-python
 #     powershell -File toolshed\collect_site_packages_dll_files.ps1
-#     python .\toolshed\make_site_packages_libdirs.py windows site_packages_dll.txt
 
 $ErrorActionPreference = 'Stop'
 
diff --git a/toolshed/collect_site_packages_so_files.sh b/toolshed/collect_site_packages_so_files.sh
index 974f6eeae86..a88652bdfe0 100755
--- a/toolshed/collect_site_packages_so_files.sh
+++ b/toolshed/collect_site_packages_so_files.sh
@@ -1,12 +1,11 @@
 #!/bin/bash
 
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # Usage:
 #     cd cuda-python
 #     ./toolshed/collect_site_packages_so_files.sh
-#     ./toolshed/make_site_packages_libdirs.py linux site_packages_so.txt
 
 set -euo pipefail
 fresh_venv() {
diff --git a/toolshed/conda_create_for_pathfinder_testing.ps1 b/toolshed/conda_create_for_pathfinder_testing.ps1
index fbdbb5a0362..94a917d6ff0 100644
--- a/toolshed/conda_create_for_pathfinder_testing.ps1
+++ b/toolshed/conda_create_for_pathfinder_testing.ps1
@@ -1,4 +1,4 @@
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 param(
@@ -19,6 +19,7 @@ conda activate "pathfinder_testing_cu$CudaMajorMinorPatch"
 # Keep this list aligned with the Windows-installable subset of
 # cuda_pathfinder/pyproject.toml.
 $cpkgs = @(
+    "cudnn",
     "cusparselt-dev",
     "cutensor",
     "cutlass",
diff --git a/toolshed/conda_create_for_pathfinder_testing.sh b/toolshed/conda_create_for_pathfinder_testing.sh
index 4e38c5dbe88..3512f80ec43 100755
--- a/toolshed/conda_create_for_pathfinder_testing.sh
+++ b/toolshed/conda_create_for_pathfinder_testing.sh
@@ -26,6 +26,7 @@ set -u
 # cuda_pathfinder/pyproject.toml.
 cpkgs=(
     "cuquantum"
+    "cudnn"
     "cusparselt-dev"
     "cutensor"
     "cutlass"
@@ -34,6 +35,7 @@ cpkgs=(
     "libcufftmp-dev"
     "libcusolvermp-dev"
     "libmathdx-dev"
+    "nccl"
     "libnvshmem3"
     "libnvshmem-dev"
 )
diff --git a/toolshed/dump_cutile_b64.py b/toolshed/dump_cutile_b64.py
index 422bf95232b..8e58e452e02 100644
--- a/toolshed/dump_cutile_b64.py
+++ b/toolshed/dump_cutile_b64.py
@@ -9,9 +9,9 @@
 """
 
 import base64
-import glob
 import os
 import sys
+from pathlib import Path
 
 import cupy
 
@@ -54,13 +54,13 @@ def main():
         raise
 
     # Find the .cutile file in current directory
-    cutile_files = glob.glob("./*.cutile")
+    cutile_files = list(Path().glob("*.cutile"))
     if not cutile_files:
         print("No .cutile file found in current directory", file=sys.stderr)
         sys.exit(1)
 
     # Use the most recently modified one if multiple exist
-    cutile_path = max(cutile_files, key=os.path.getmtime)
+    cutile_path = max(cutile_files, key=lambda path: path.stat().st_mtime)
 
     # Read the binary content
     with open(cutile_path, "rb") as f:
diff --git a/toolshed/find_skipped_tests.py b/toolshed/find_skipped_tests.py
index af44d7c0ad5..c2cb1c9777d 100755
--- a/toolshed/find_skipped_tests.py
+++ b/toolshed/find_skipped_tests.py
@@ -36,7 +36,10 @@
 
 ANSI_ESCAPE = re.compile(r"\x1B\[[0-9;]*[A-Za-z]")
 PYTEST_NODE_ID = re.compile(r"tests/\S+\.py::\S+")
-PYTEST_TEST_OUTCOME = re.compile(r"(tests/\S+\.py::\S+)\s+(PASSED|FAILED|ERROR|SKIPPED|XFAIL|XPASS)\b")
+PYTEST_TEST_OUTCOME = re.compile(
+    r"(tests/\S+\.py::\S+)\s+"
+    r"(PASSED|FAILED|ERROR|SKIPPED|XFAIL|XPASS|SUBPASSED|SUBFAILED|SUBERROR|SUBSKIPPED|SUBXFAIL|SUBXPASS)\b"
+)
 
 # GHA log format markers used to identify which test suite is active.
 # `gh api` logs: ##[group]<step-name> opens a section, ##[endgroup] closes it.
@@ -194,6 +197,8 @@ def extract_test_status_sets(text: str) -> tuple[set[str], set[str], dict[str, s
     """Parse pytest output and return (skipped, non_skipped, test_id->suite)."""
     skipped: set[str] = set()
     non_skipped: set[str] = set()
+    passed: set[str] = set()
+    subtest_seen: set[str] = set()
     test_suites: dict[str, str] = {}
     current_suite = ""
 
@@ -216,10 +221,20 @@ def extract_test_status_sets(text: str) -> tuple[set[str], set[str], dict[str, s
 
         # Parse per-test outcomes first so PASS/FAIL lines disqualify tests.
         for test_id, outcome in PYTEST_TEST_OUTCOME.findall(line):
-            if outcome == "SKIPPED":
+            if outcome.startswith("SUB"):
+                subtest_seen.add(test_id)
+                if outcome == "SUBSKIPPED":
+                    skipped.add(test_id)
+                    if current_suite:
+                        test_suites.setdefault(test_id, current_suite)
+                else:
+                    non_skipped.add(test_id)
+            elif outcome == "SKIPPED":
                 skipped.add(test_id)
                 if current_suite:
                     test_suites.setdefault(test_id, current_suite)
+            elif outcome == "PASSED":
+                passed.add(test_id)
             else:
                 non_skipped.add(test_id)
 
@@ -233,6 +248,11 @@ def extract_test_status_sets(text: str) -> tuple[set[str], set[str], dict[str, s
             if current_suite:
                 test_suites.setdefault(test_id, current_suite)
 
+    # Pytest reports a passing parent after its subtests even when every
+    # subtest skipped. Only treat that parent pass as execution evidence when
+    # the test did not emit subtest outcomes of its own.
+    non_skipped.update(passed - subtest_seen)
+
     return skipped, non_skipped, test_suites
 
 
diff --git a/toolshed/make_site_packages_libdirs.py b/toolshed/make_site_packages_libdirs.py
deleted file mode 100755
index e1cbcb28825..00000000000
--- a/toolshed/make_site_packages_libdirs.py
+++ /dev/null
@@ -1,123 +0,0 @@
-#!/usr/bin/env python3
-
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-# SPDX-License-Identifier: Apache-2.0
-
-"""Parse collected site-packages library paths, update descriptor_catalog.py.
-
-Usage:
-    python toolshed/make_site_packages_libdirs.py linux collected_linux.txt
-    python toolshed/make_site_packages_libdirs.py windows collected_windows.txt
-"""
-
-from __future__ import annotations
-
-import argparse
-import os
-import re
-import sys
-from pathlib import Path
-from typing import Dict, Set
-
-sys.path.insert(0, str(Path(__file__).resolve().parent))
-from _catalog_writer import load_catalog, update_specs, write_catalog
-
-_SITE_PACKAGES_RE = re.compile(r"(?i)^.*?/site-packages/")
-
-
-def _strip_site_packages_prefix(p: str) -> str:
-    """Remove any leading '.../site-packages/' (handles '\\' or '/', case-insensitive)."""
-    p = p.replace("\\", "/")
-    return _SITE_PACKAGES_RE.sub("", p)
-
-
-def _parse_lines_linux(lines: list[str]) -> Dict[str, Set[str]]:
-    d: Dict[str, Set[str]] = {}
-    for raw in lines:
-        line = raw.strip()
-        if not line or line.startswith("#"):
-            continue
-        line = _strip_site_packages_prefix(line)
-        dirpath, fname = os.path.split(line)
-        # Require something like libNAME.so, libNAME.so.12, libNAME.so.12.1, etc.
-        i = fname.find(".so")
-        if not fname.startswith("lib") or i == -1:
-            continue
-        name = fname[3:i]  # e.g. "libnvrtc" -> "nvrtc"
-        d.setdefault(name, set()).add(dirpath)
-    return d
-
-
-def _extract_libname_from_dll(fname: str) -> str | None:
-    """Return base libname per the heuristic, or None if not a .dll."""
-    base = os.path.basename(fname)
-    if not base.lower().endswith(".dll"):
-        return None
-    stem = base[:-4]  # drop ".dll"
-    out = []
-    for ch in stem:
-        if ch == "_" or ch.isdigit():
-            break
-        out.append(ch)
-    name = "".join(out)
-    return name or None
-
-
-def _parse_lines_windows(lines: list[str]) -> Dict[str, Set[str]]:
-    """Collect {libname: set(dirnames)} with deduped directories."""
-    m: Dict[str, Set[str]] = {}
-    for raw in lines:
-        line = raw.strip()
-        if not line or line.startswith("#"):
-            continue
-        line = _strip_site_packages_prefix(line)
-        dirpath, fname = os.path.split(line)
-        libname = _extract_libname_from_dll(fname)
-        if not libname:
-            continue
-        m.setdefault(libname, set()).add(dirpath)
-    return m
-
-
-def main() -> None:
-    ap = argparse.ArgumentParser(
-        description="Update site_packages_* in descriptor_catalog.py from collected library paths"
-    )
-    ap.add_argument("platform", choices=["linux", "windows"])
-    ap.add_argument("path", help="Text file with one library path per line")
-    args = ap.parse_args()
-
-    with open(args.path, encoding="utf-8") as f:
-        lines = f.read().splitlines()
-
-    if args.platform == "linux":
-        parsed = _parse_lines_linux(lines)
-        field = "site_packages_linux"
-    else:
-        parsed = _parse_lines_windows(lines)
-        field = "site_packages_windows"
-
-    catalog = load_catalog()
-    catalog_names = {spec.name for spec in catalog}
-
-    updates: dict[str, dict[str, object]] = {}
-    for name, dirs in parsed.items():
-        if name in catalog_names:
-            updates[name] = {field: tuple(sorted(dirs))}
-
-    if updates:
-        write_catalog(update_specs(catalog, updates))
-        for name in sorted(updates):
-            print(f"  updated {name}: {field}={updates[name][field]}")
-    else:
-        print("No matching libraries found.")
-
-    unmatched = set(parsed.keys()) - catalog_names
-    if unmatched:
-        print(f"\nLibraries not in catalog ({len(unmatched)}):")
-        for name in sorted(unmatched):
-            print(f"  {name}")
-
-
-if __name__ == "__main__":
-    main()
diff --git a/toolshed/setup-docs-env.sh b/toolshed/setup-docs-env.sh
index 16378725e93..9acbaa8e391 100755
--- a/toolshed/setup-docs-env.sh
+++ b/toolshed/setup-docs-env.sh
@@ -1,6 +1,6 @@
 #!/usr/bin/env bash
 
-# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 # SPDX-License-Identifier: Apache-2.0
 
 # Setup a local conda environment for building the sphinx docs to mirror the CI environment
@@ -39,7 +39,7 @@ echo "Creating environment '${ENV_NAME}'…"
 #            cuda_python/docs/environment-docs.yml. Please KEEP THEM IN SYNC!
 conda create -y -n "${ENV_NAME}" \
     "python=${PYVER}" \
-    cython \
+    "cython>=3.2.5,<3.3" \
     myst-parser \
     numpy \
     numpydoc \
diff --git a/toolshed/update_catalog.py b/toolshed/update_catalog.py
deleted file mode 100644
index 800451ca45d..00000000000
--- a/toolshed/update_catalog.py
+++ /dev/null
@@ -1,47 +0,0 @@
-#!/usr/bin/env python3
-
-# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
-#
-# SPDX-License-Identifier: Apache-2.0
-
-"""Update descriptor_catalog.py from CTK installations.
-
-On Linux, scans directories for .so files and extracts SONAMEs via readelf.
-On Windows, parses 7z listing files generated from CTK .exe installers.
-
-Usage:
-    # Linux — pass one or more CTK lib directories:
-    python toolshed/update_catalog.py /path/to/ctk12/lib64 /path/to/ctk13/lib64
-
-    # Windows — pass 7z listing .txt files:
-    #   for exe in *.exe; do 7z l "$exe" > "${exe%.exe}.txt"; done
-    python toolshed/update_catalog.py listing12.txt listing13.txt
-"""
-
-from __future__ import annotations
-
-import sys
-from pathlib import Path
-
-sys.path.insert(0, str(Path(__file__).resolve().parent))
-
-
-def main() -> None:
-    if len(sys.argv) < 2:
-        print(__doc__, file=sys.stderr)
-        sys.exit(1)
-
-    args = sys.argv[1:]
-
-    if sys.platform == "win32":
-        from build_pathfinder_dlls import run as run_dlls
-
-        run_dlls(listing_files=args)
-    else:
-        from build_pathfinder_sonames import run as run_sonames
-
-        run_sonames(roots=args)
-
-
-if __name__ == "__main__":
-    main()