GitHub-Proxy/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2025-08-11 19:29:02 +08:00
Code Issues Packages Projects Releases Wiki Activity

Add explanations of the logic behind the matrix-vector products

Browse Source
This commit is contained in:
Gael Guennebaud 2013-08-21 14:29:53 +02:00
parent d9381598bc
commit 4ecfdc4716
1 changed files with 28 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

28
Eigen/src/Core/products/GeneralMatrixVector.h
View File

@ -26,6 +26,34 @@ namespace internal {
* |real |cplx |real | alpha is converted to a cplx when calling the run function, no vectorization
* |cplx |real |cplx | invalid, the caller has to do tmp: = A * B; C += alpha*tmp
* |cplx |real |real | optimal case, vectorization possible via real-cplx mul
*
* Accesses to the matrix coefficients follow the following logic:
*
* - if all columns have the same alignment then
* - if the columns have the same alignment as the result vector, then easy! (-> AllAligned case)
* - otherwise perform unaligned loads only (-> NoneAligned case)
* - otherwise
* - if even columns have the same alignment then
* // odd columns are guaranteed to have the same alignment too
* - if even or odd columns have the same alignment as the result, then
* // for a register size of 2 scalars, this is guarantee to be the case (e.g., SSE with double)
* - perform half aligned and half unaligned loads (-> EvenAligned case)
* - otherwise perform unaligned loads only (-> NoneAligned case)
* - otherwise, if the register size is 4 scalars (e.g., SSE with float) then
* - one over 4 consecutive columns is guaranteed to be aligned with the result vector,
* perform simple aligned loads for this column and aligned loads plus re-alignment for the other. (-> FirstAligned case)
* // this re-alignment is done by the palign function implemented for SSE in Eigen/src/Core/arch/SSE/PacketMath.h
* - otherwise,
* // if we get here, this means the register size is greater than 4 (e.g., AVX with floats),
* // we currently fall back to the NoneAligned case
*
* The same reasoning apply for the transposed case.
*
* The last case (PacketSize>4) could probably be improved by generalizing the FirstAligned case, but since we do not support AVX yet...
* One might also wonder why in the EvenAligned case we perform unaligned loads instead of using the aligned-loads plus re-alignment
* strategy as in the FirstAligned case. The reason is that we observed that unaligned loads on a 8 byte boundary are not too slow
* compared to unaligned loads on a 4 byte boundary.
*
*/
template<typename Index, typename LhsScalar, bool ConjugateLhs, typename RhsScalar, bool ConjugateRhs, int Version>
struct general_matrix_vector_product<Index,LhsScalar,ColMajor,ConjugateLhs,RhsScalar,ConjugateRhs,Version>