mir-algorithm currently supports only row major slices. Adding optional support for column major slices, as in Eigen's template parameter approach, would provide a number of benefits, albeit at the cost of additional testing and work to set it up.
Column major slices can provide better data locality and memory access than row major slices, depending on the use case. For instance, an algorithm that loops through columns is faster with a column major order than a row major order, all else equal. Correspondingly, optionally column major slices would also be useful when working with dataframes, particularly with use cases related to tall data that are common in the R tidyverse or pandas.
Adding support for column major slices would also be useful for interacting with Fortran, R, Pandas, or other languages/frameworks that use column major arrays.
It would require a breaking change to change the definition of mir_slice from
struct mir_slice(Iterator_, size_t N_ = 1, SliceKind kind_ = Contiguous, Labels_...)
to something like
enum StorageOrder { Row, Column}
alias RowMajor = StorageOrder.Row;
alias ColumnMajor = StorageOrder.Column;
struct mir_slice(Iterator_, size_t N_ = 1, SliceKind kind_ = Contiguous, StorageOrder = RowMajor, Labels_...)because D requires variadic templates to be at the end of the list. However, it shouldn't break code that relies on the Slice!(Iterator, N, kind) pattern so long as the underlying functions are set up properly.
As far as I can tell, the key thing would be adjusting functions like indexStride, but additional testing would be required to confirm everything works as expected for column major slices.
mir-algorithm currently supports only row major slices. Adding optional support for column major slices, as in Eigen's template parameter approach, would provide a number of benefits, albeit at the cost of additional testing and work to set it up.
Column major slices can provide better data locality and memory access than row major slices, depending on the use case. For instance, an algorithm that loops through columns is faster with a column major order than a row major order, all else equal. Correspondingly, optionally column major slices would also be useful when working with dataframes, particularly with use cases related to tall data that are common in the R tidyverse or pandas.
Adding support for column major slices would also be useful for interacting with Fortran, R, Pandas, or other languages/frameworks that use column major arrays.
It would require a breaking change to change the definition of
mir_slicefromto something like
because D requires variadic templates to be at the end of the list. However, it shouldn't break code that relies on the
Slice!(Iterator, N, kind)pattern so long as the underlying functions are set up properly.As far as I can tell, the key thing would be adjusting functions like
indexStride, but additional testing would be required to confirm everything works as expected for column major slices.