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Abhishek Gola bdf348c13a Merge pull request #28934 from abhishek-gola:mlas_gemm
Added MLAS third party module and integrated into GeMM path #28934

### Pull Request Readiness Checklist

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- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [x] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
2026-05-22 20:22:15 +03:00

88 lines
2.1 KiB
C++

/*++
Copyright (c) Microsoft Corporation. All rights reserved.
Licensed under the MIT License.
Module Name:
SgemmKernelPower.cpp
Abstract:
This module implements the kernels for the single precision matrix/matrix
multiply operation (SGEMM).
--*/
#include "SgemmKernelpower.h"
size_t
MLASCALL
MlasSgemmKernel(
const float* A,
const float* B,
float* C,
size_t CountK,
size_t CountM,
size_t CountN,
size_t lda,
size_t ldc,
float alpha,
bool ZeroMode
)
/*++
Routine Description:
This routine is an inner kernel to compute matrix multiplication for a
set of rows.
Arguments:
A - Supplies the address of matrix A.
B - Supplies the address of matrix B. The matrix data has been packed using
MlasSgemmCopyPackB or MlasSgemmTransposePackB.
C - Supplies the address of matrix C.
CountK - Supplies the number of columns from matrix A and the number of rows
from matrix B to iterate over.
CountM - Supplies the maximum number of rows that can be processed for
matrix A and matrix C. The actual number of rows handled for this
invocation depends on the kernel implementation.
CountN - Supplies the number of columns from matrix B and matrix C to
iterate over.
lda - Supplies the first dimension of matrix A.
ldc - Supplies the first dimension of matrix C.
alpha - Supplies the scalar multiplier (see SGEMM definition).
ZeroMode - Supplies true if the output matrix must be zero initialized,
else false if the output matrix is accumulated into.
Return Value:
Returns the number of rows handled.
--*/
{
size_t RowsHandled;
MLAS_FLOAT32X4 AlphaBroadcast = MlasBroadcastFloat32x4(alpha);
if (CountM >= 4) {
RowsHandled = MlasSgemmProcessCount<4>(A, B, C, CountK, CountN, lda, ldc, AlphaBroadcast, ZeroMode);
} else if (CountM >= 2) {
RowsHandled = MlasSgemmProcessCount<2>(A, B, C, CountK, CountN, lda, ldc, AlphaBroadcast, ZeroMode);
} else {
RowsHandled = MlasSgemmProcessCount<1>(A, B, C, CountK, CountN, lda, ldc, AlphaBroadcast, ZeroMode);
}
return RowsHandled;
}