feat(vector): fuse the BBQ rerank distance kernels

nodedb-vector/Cargo.toml

@@ -44,3 +44,13 @@ rand = { workspace = true }
 tempfile = { workspace = true }
 libc = { workspace = true }
 nodedb-wal = { workspace = true }
+
+# `fluxbench` pulls `tokio`, which does not build for wasm32. Keeping it out of
+# the wasm dev-dependency set is what lets the crate's own wasm tests build and
+# run under a wasm runner, instead of only being compile-checked.
+[target.'cfg(not(target_arch = "wasm32"))'.dev-dependencies]
+fluxbench = { workspace = true }
+
+[[bench]]
+name = "bbq_kernel"
+harness = false

nodedb-vector/benches/bbq_kernel.rs

@@ -0,0 +1,147 @@
+// SPDX-License-Identifier: Apache-2.0
+
+//! BBQ kernel benches: the fused path against a reconstruct-and-measure
+//! baseline.
+//!
+//! The baseline models the shape of the pre-fusion rerank pass — decode the
+//! prepared payload into a `Vec<f32>` per candidate, then reconstruct each
+//! dimension — so the allocation and pass counts are comparable. It is an
+//! approximation of that path, not a copy of it: it uses a fixed `1/√dim` scale
+//! in place of the candidate's stored corrective factor, and reads the sign bits
+//! at a fixed header offset. It measures pass and allocation shape, not the
+//! codec's arithmetic.
+//!
+//! Fixtures are built once per thread, outside the timed region, so only the
+//! kernel loop is measured.
+//!
+//! Run with: cargo bench -p nodedb-vector --bench bbq_kernel
+
+use fluxbench::bench;
+use fluxbench::prelude::*;
+use std::hint::black_box;
+
+use nodedb_vector::rerank::codec::{PreparedQuery, RerankCodec};
+use nodedb_vector::rerank::codecs::BbqRerank;
+
+/// Installs fluxbench's tracking allocator so the harness reports heap bytes and
+/// allocation counts per benchmark: the fused path shows zero allocations per
+/// candidate, the baseline shows one `Vec<f32>`.
+#[global_allocator]
+static ALLOC: fluxbench::TrackingAllocator = fluxbench::TrackingAllocator;
+
+const OVERSAMPLE: u8 = 4;
+const CANDIDATES: usize = 256;
+
+fn det_vec(i: usize, dim: usize) -> Vec<f32> {
+    (0..dim)
+        .map(|j| (((i * 31 + j) % 100) as f32 / 100.0) - 0.5)
+        .collect()
+}
+
+/// Trained codec, prepared query, and 256 encoded candidates for `dim`.
+fn setup(dim: usize) -> (BbqRerank, PreparedQuery, Vec<Vec<u8>>) {
+    let vecs: Vec<Vec<f32>> = (0..CANDIDATES).map(|i| det_vec(i, dim)).collect();
+    let refs: Vec<&[f32]> = vecs.iter().map(|v| v.as_slice()).collect();
+    let mut codec = BbqRerank::new(dim, OVERSAMPLE);
+    codec.train(&refs).expect("train");
+    let prepared = codec.prepare_query(&vecs[0]).expect("prepare_query");
+    let encoded: Vec<Vec<u8>> = vecs
+        .iter()
+        .map(|v| codec.encode(v).expect("encode"))
+        .collect();
+    (codec, prepared, encoded)
+}
+
+thread_local! {
+    static STATE_128: (BbqRerank, PreparedQuery, Vec<Vec<u8>>) = setup(128);
+    static STATE_768: (BbqRerank, PreparedQuery, Vec<Vec<u8>>) = setup(768);
+}
+
+/// The baseline: decode the prepared payload to `Vec<f32>` per candidate, then
+/// reconstruct each dimension. `encoded` carries a 32-byte quant header before
+/// the sign bits, and the reconstruction uses a fixed `1/√dim` scale rather than
+/// the candidate's stored `residual_norm` — see the module docs.
+fn unfused_l2(payload: &[u8], encoded: &[u8], dim: usize) -> f32 {
+    let centered: Vec<f32> = payload[4..]
+        .as_chunks::<4>()
+        .0
+        .iter()
+        .map(|b| f32::from_le_bytes(*b))
+        .collect();
+    let scale = 1.0f32 / (dim as f32).sqrt();
+    let mut acc = 0.0f32;
+    for i in 0..dim {
+        let bit = (encoded[32 + i / 8] >> (7 - (i % 8))) & 1;
+        let recon = if bit != 0 { scale } else { -scale };
+        let d = centered[i] - recon;
+        acc += d * d;
+    }
+    acc.sqrt()
+}
+
+#[bench(id = "bbq_fused_128", group = "bbq_kernel")]
+fn bbq_fused_128(b: &mut Bencher) {
+    STATE_128.with(|(codec, prepared, encoded)| {
+        b.iter(|| {
+            let mut acc = 0.0f32;
+            for e in encoded {
+                acc += codec.distance_prepared(prepared, e).expect("distance");
+            }
+            black_box(acc)
+        });
+    });
+}
+
+#[bench(id = "bbq_unfused_128", group = "bbq_kernel")]
+fn bbq_unfused_128(b: &mut Bencher) {
+    STATE_128.with(|(_codec, prepared, encoded)| {
+        let payload = match prepared {
+            PreparedQuery::Bytes(b) => b.as_slice(),
+            _ => panic!("bbq prepared form is Bytes"),
+        };
+        b.iter(|| {
+            let mut acc = 0.0f32;
+            for e in encoded {
+                acc += unfused_l2(payload, e, 128);
+            }
+            black_box(acc)
+        });
+    });
+}
+
+#[bench(id = "bbq_fused_768", group = "bbq_kernel")]
+fn bbq_fused_768(b: &mut Bencher) {
+    STATE_768.with(|(codec, prepared, encoded)| {
+        b.iter(|| {
+            let mut acc = 0.0f32;
+            for e in encoded {
+                acc += codec.distance_prepared(prepared, e).expect("distance");
+            }
+            black_box(acc)
+        });
+    });
+}
+
+#[bench(id = "bbq_unfused_768", group = "bbq_kernel")]
+fn bbq_unfused_768(b: &mut Bencher) {
+    STATE_768.with(|(_codec, prepared, encoded)| {
+        let payload = match prepared {
+            PreparedQuery::Bytes(b) => b.as_slice(),
+            _ => panic!("bbq prepared form is Bytes"),
+        };
+        b.iter(|| {
+            let mut acc = 0.0f32;
+            for e in encoded {
+                acc += unfused_l2(payload, e, 768);
+            }
+            black_box(acc)
+        });
+    });
+}
+
+fn main() {
+    if let Err(e) = fluxbench::run() {
+        eprintln!("Error: {e}");
+        std::process::exit(1);
+    }
+}

nodedb-vector/src/distance/simd/avx2.rs

@@ -4,6 +4,8 @@
 
 #![cfg(target_arch = "x86_64")]
 
+use super::bbq::{assert_payload_shapes, l2_scalar_from_bytes, recon_scale};
+
 pub fn l2_squared(a: &[f32], b: &[f32]) -> f32 {
     assert_eq!(a.len(), b.len(), "avx2 l2: length mismatch");
     // SAFETY: caller verified avx2+fma via is_x86_feature_detected.
@@ -114,3 +116,60 @@ unsafe fn hsum256(v: std::arch::x86_64::__m256) -> f32 {
     let sums2 = _mm_add_ss(sums, shuf2);
     _mm_cvtss_f32(sums2)
 }
+
+/// Safe entry for `SimdRuntime`; the feature guard lives in `SimdRuntime::detect`.
+pub fn l2_bbq(centered: &[u8], packed: &[u8], residual_norm: f32, dim: usize) -> f32 {
+    assert_payload_shapes(centered, packed, dim);
+    // SAFETY: selected only when `detect()` observed this tier's features, and
+    // both slices were just checked against `dim`.
+    unsafe { l2_bbq_impl(centered, packed, residual_norm, dim) }
+}
+
+#[target_feature(enable = "avx2,fma")]
+unsafe fn l2_bbq_impl(centered: &[u8], packed: &[u8], residual_norm: f32, dim: usize) -> f32 {
+    use std::arch::x86_64::*;
+
+    let scale = recon_scale(residual_norm, dim);
+    let scale_v = _mm256_set1_ps(scale);
+    let mut acc = _mm256_setzero_ps();
+
+    let mut i = 0;
+    while i + 8 <= dim {
+        // SAFETY: `i + 8 <= dim`, and `l2_bbq` asserted
+        // `centered.len() >= dim * 4`, so the 32-byte unaligned load stays in
+        // bounds; `i / 8` is in range because eight dims consume one byte.
+        let q = unsafe { _mm256_loadu_ps(centered.as_ptr().add(i * 4).cast::<f32>()) };
+        let byte = unsafe { *packed.get_unchecked(i / 8) } as usize;
+        let signs = unsafe { _mm256_load_ps(SIGN_LANES[byte].0.as_ptr()) };
+        let recon = _mm256_mul_ps(signs, scale_v);
+        let d = _mm256_sub_ps(q, recon);
+        acc = _mm256_fmadd_ps(d, d, acc);
+        i += 8;
+    }
+
+    let sum = unsafe { hsum256(acc) } + l2_scalar_from_bytes(centered, packed, scale, i, dim);
+    sum.sqrt()
+}
+
+/// `±1.0` lane patterns for every packed byte, MSB-first, 32-byte aligned for
+/// an aligned load. Precomputed `reverse_bits` mapping (dim `k` → lane `k`).
+#[derive(Clone, Copy)]
+#[repr(align(32))]
+struct Aligned8([f32; 8]);
+
+static SIGN_LANES: [Aligned8; 256] = build_sign_lanes();
+
+const fn build_sign_lanes() -> [Aligned8; 256] {
+    let mut table = [Aligned8([0.0; 8]); 256];
+    let mut byte = 0usize;
+    while byte < 256 {
+        let mut lane = 0usize;
+        while lane < 8 {
+            let bit = (byte >> (7 - lane)) & 1;
+            table[byte].0[lane] = if bit == 1 { 1.0 } else { -1.0 };
+            lane += 1;
+        }
+        byte += 1;
+    }
+    table
+}

nodedb-vector/src/distance/simd/avx512.rs

@@ -4,6 +4,8 @@
 
 #![cfg(target_arch = "x86_64")]
 
+use super::bbq::{assert_payload_shapes, l2_scalar_from_bytes, recon_scale};
+
 pub fn l2_squared(a: &[f32], b: &[f32]) -> f32 {
     assert_eq!(a.len(), b.len(), "avx512 l2: length mismatch");
     unsafe { l2_impl(a, b) }
@@ -99,3 +101,39 @@ unsafe fn ip_impl(a: &[f32], b: &[f32]) -> f32 {
         -dot
     }
 }
+
+/// Safe entry for `SimdRuntime`; the feature guard lives in `SimdRuntime::detect`.
+pub fn l2_bbq(centered: &[u8], packed: &[u8], residual_norm: f32, dim: usize) -> f32 {
+    assert_payload_shapes(centered, packed, dim);
+    // SAFETY: selected only when `detect()` observed this tier's features, and
+    // both slices were just checked against `dim`.
+    unsafe { l2_bbq_impl(centered, packed, residual_norm, dim) }
+}
+
+#[target_feature(enable = "avx512f")]
+unsafe fn l2_bbq_impl(centered: &[u8], packed: &[u8], residual_norm: f32, dim: usize) -> f32 {
+    use std::arch::x86_64::*;
+
+    let scale = recon_scale(residual_norm, dim);
+    let pos = _mm512_set1_ps(scale);
+    let neg = _mm512_set1_ps(-scale);
+    let mut acc = _mm512_setzero_ps();
+
+    let mut i = 0;
+    while i + 16 <= dim {
+        // SAFETY: `i + 16 <= dim`, and `l2_bbq` asserted
+        // `centered.len() >= dim * 4`; two packed bytes are in range because
+        // 16 dims consume exactly two bytes.
+        let q = unsafe { _mm512_loadu_ps(centered.as_ptr().add(i * 4).cast::<f32>()) };
+        let b0 = unsafe { *packed.get_unchecked(i / 8) };
+        let b1 = unsafe { *packed.get_unchecked(i / 8 + 1) };
+        let mask: __mmask16 = (b0.reverse_bits() as u16) | ((b1.reverse_bits() as u16) << 8);
+        let recon = _mm512_mask_blend_ps(mask, neg, pos);
+        let d = _mm512_sub_ps(q, recon);
+        acc = _mm512_fmadd_ps(d, d, acc);
+        i += 16;
+    }
+
+    let sum = _mm512_reduce_add_ps(acc) + l2_scalar_from_bytes(centered, packed, scale, i, dim);
+    sum.sqrt()
+}