source/backend/cpu/x86_x64/avx/FunctionSummary.hpp

// // FunctionSummary.hpp // MNN // // Created by MNN on 2019/08/25. // Copyright © 2018, Alibaba Group Holding Limited // #include "core/SimdHeader.h" #include <MNN/MNNDefine.h> #include <stdint.h> #ifndef _MM_TRANSPOSE4_PS #define _MM_TRANSPOSE4_PS(row0, row1, row2, row3) \ do { \ __m128 tmp3, tmp2, tmp1, tmp0; \ tmp0 = _mm_unpacklo_ps((row0), (row1)); \ tmp2 = _mm_unpacklo_ps((row2), (row3)); \ tmp1 = _mm_unpackhi_ps((row0), (row1)); \ tmp3 = _mm_unpackhi_ps((row2), (row3)); \ (row0) = _mm_movelh_ps(tmp0, tmp2); \ (row1) = _mm_movehl_ps(tmp2, tmp0); \ (row2) = _mm_movelh_ps(tmp1, tmp3); \ (row3) = _mm_movehl_ps(tmp3, tmp1); \ } while (0) #endif #include "backend/cpu/compute/Int8FunctionsOpt.h" #include "backend/cpu/compute/CommonOptFunction.h" // ========= CommonOptFunction.cpp =========== extern "C" { void _AVX_MNNPackedMatMul(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b); void _AVX_MNNPackedMatMulRemain(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b); #ifdef MNN_CPU_WEIGHT_DEQUANT_GEMM void _AVX_MNNPackedMatMul_int4(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b); void _AVX_MNNPackedMatMulRemain_int4(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b); void _AVX_MNNPackedMatMul_int8(float* C, const float* A, const float* B, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b); void _AVX_MNNPackedMatMulRemain_int8(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, const float* k, const float* b); #endif #ifdef MNN_LOW_MEMORY void _AVX_MNNAbsMaxFP32(const float* source, float* absmax, size_t src_depth_quad, size_t realSize, int pack); void _AVX_MNNDynamicQuant(const float* src, int8_t* dst, const float* scale, size_t src_depth_quad, size_t realSize, int pack, const float* bias); void _AVX_MNNAsyQuantFunc(int8_t* dst, const float* src, float* qscale, float* qbias, const size_t* info); void _AVX_MNNAsyQuantInfo(float* scale, float* bias, float* qscale, float* qbias, float* dstMin, float* dstMax, const float* src, const size_t* info); #endif void _AVX_MNNPackC4ForMatMul_A(float* destOrigin, float const** sourceGroup, const int32_t* info, const int32_t* el); void _AVX_MNNExpC8(float* dest, const float* source, float* offset, const float* parameters, size_t countC8); void _AVX_MNNSoftmax(float* dest, const float* source, size_t size); void _AVX_MNNFloat2Int8(const float* src, int8_t* dst, size_t sizeQuad, const float* scalep, ssize_t minV, ssize_t maxV, const float* zeroPoint, ssize_t quanParamVec); void _AVX_MNNInt8ScaleToFloat(float* dst, const int8_t* src, const float* scale, size_t sizeQuad, const float* zeroPoint, ssize_t quanParamVec); void _AVX_MNNLineDepthWiseInt8AddBiasScaleUnit(int8_t* dstO, const int8_t* srcO, const int8_t* weightO, const QuanPostTreatParameters* parameters, size_t width, size_t src_w_step, size_t fw, size_t fh, size_t dilateX_step, size_t dilateY_step, int8_t* idxOrder); void _AVX_MNNComputeMatMulForE_1(const float* A, const float* B, float* C, const float* biasPtr, const MatMulParam* param, size_t tId); void _AVX_MNNPackC4ForMatMul_A_BF16(float* destOrigin, float const** sourceGroup, const int32_t* info, const int32_t* el); void _AVX_MNNCountMinMaxValue(const float* source, float* minVal, float* maxVal, size_t size); void _AVX_MNNGetMatMulPackMode_BF16(int* eP, int *lP, int* hP); void _AVX_MNNPackForMatMul_B_BF16(float* dest, const float* source, size_t h, size_t l, bool transpose); void _AVX_MNNPackedSparseMatMul(float* C, const float* A, const float* B, unsigned int* NNZMap, int* dataOffsetMap, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias); void _AVX_MNNComputeMatMulForH_1(const float* A, const float* B, float* C, const float* biasPtr, const MatMulParam* param, size_t tId); void _AVX_ReorderInit(void* functions); void _AVX_MNNInt8FunctionInit(void* functions); void _AVX_MNNPackCUnit(float* dst, const float* src, size_t area, size_t depth, int* areaOffset); void _AVX_MNNUnpackCUnit(float* dst, const float* src, size_t area, size_t depth, int* areaOffset); void _AVX_MNNPackCUnitTranspose(float* dst, const float* src, size_t area, size_t depth, int* areaOffset); void _AVX_MNNUnpackCUnitTranspose(float* dst, const float* src, size_t area, size_t depth, int* areaOffset); void _AVX_MNNPackForMatMul_B(float* dest, const float* source, size_t h, size_t l, bool transpose); void _AVX_ExtraInit(void* functions); void _AVX_WinogradInit(void* functions); void _AVX_MNNGelu(float *dst, const float *src, size_t size, float* parameters); void _AVX_MNNNorm(float *dst, const float *src, const float *gamma, const float *beta, float epsilon, size_t size, bool RMSNorm); void _AVX_MNNNormInt8(int8_t* dst, const int8_t* src, const float* gamma, const float* beta, float epsilon, size_t size, QuanPrePostParameters* params, bool RMSNorm); void _AVX_MNNGetSparseMatMulPackMode(int* eP, int *lP, int* hP); void _AVX_MNNPackedSparseMatMulEpx1EFMA(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, unsigned int* NNZMap, int* dataOffsetMap); void _AVX_MNNPackedSparseMatMulEpx4EFMA(float* C, const float* A, const float* B, size_t eSize, const size_t* parameter, const float* postParameters, const float* bias, unsigned int* NNZMap, int* dataOffsetMap); }

source/backend/cpu/x86_x64/avx/FunctionSummary.hpp (69 lines of code) (raw):