MNN/source/backend/cpu/arm/CommonOptFunctionNeon.cpp

990 lines
38 KiB
C++

#include "core/Macro.h"
#include "../compute/CommonOptFunction.h"
#ifdef MNN_USE_NEON
#include <arm_neon.h>
#include "./FunctionSummary.hpp"
#include "core/MemoryFormater.h"
extern "C" {
void MNNTranspose32Bit4x4(int32_t* dstO, const int32_t* srcO, int32_t* dim);
void MNNTranspose16Bit8x8(int16_t* dstO, const int16_t* srcO, int32_t* dim);
}
void MNNTranspose32Bit(int32_t* dstO, const int32_t* srcO, int32_t* dim) {
int w = dim[0];
int h = dim[1];
auto wC4 = w / 4;
auto hC4 = h / 4;
int srcStride = dim[2];
int dstStride = dim[3];
if (wC4 > 0 && hC4 > 0) {
MNNTranspose32Bit4x4(dstO, srcO, dim);
}
// Down
for (int i=hC4 * 4; i<h; ++i) {
auto si = srcO + i;
auto di = dstO + i * dstStride;
for (int j=0; j<w; ++j) {
auto sj = si + j * srcStride;
auto dj = di + j;
*dj = *sj;
}
}
// Right
for (int i=0; i<hC4 * 4; ++i) {
auto si = srcO + i;
auto di = dstO + i * dstStride;
for (int j=wC4 * 4; j<w; ++j) {
auto sj = si + j * srcStride;
auto dj = di + j;
*dj = *sj;
}
}
}
void MNNTranspose16Bit(int16_t* dstO, const int16_t* srcO, int32_t* dim) {
int w = dim[0];
int h = dim[1];
auto wC8 = w / 8;
auto hC8 = h / 8;
int srcStride = dim[2];
int dstStride = dim[3];
if (wC8 > 0 && hC8 > 0) {
MNNTranspose16Bit8x8(dstO, srcO, dim);
}
// Down
for (int i = hC8 * 8; i < h; ++i) {
auto si = srcO + i;
auto di = dstO + i * dstStride;
for (int j = 0; j < w; ++j) {
auto sj = si + j * srcStride;
auto dj = di + j;
*dj = *sj;
}
}
// Right
for (int i = 0; i < hC8 * 8; ++i) {
auto si = srcO + i;
auto di = dstO + i * dstStride;
for (int j = wC8 * 8; j < w; ++j) {
auto sj = si + j * srcStride;
auto dj = di + j;
*dj = *sj;
}
}
}
#ifndef MNN_USE_NEON
void MNNPackedSparseMatMulEpx1(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) {
auto eP = parameter[0] / sizeof(float);
MNN_ASSERT((eP & 0x03) == 0); // In sparse calculate, eP should be evenly divided by 4
auto h = parameter[2];
auto l = parameter[1];
auto cStride = parameter[3] / sizeof(float);
auto hRemain = parameter[4];
auto bExtraStride = parameter[5] / sizeof(float);
auto bStride = bExtraStride + l * 4;
auto aStride = eP * l; // sizeof(float);
auto hC4 = UP_DIV(h, 4);
float minValue = -std::numeric_limits<float>().max();
float maxValue = std::numeric_limits<float>().max();
if (nullptr != postParameters) {
minValue = postParameters[2];
maxValue = postParameters[3];
}
const float32x4_t vmin = vld1q_dup_f32(&minValue);
const float32x4_t vmax = vld1q_dup_f32(&maxValue);
// MNN_PRINT("NEON MNNPackedSparseMatMul eP:%lu, eSize:%lu, l:%lu, h:%lu, cStride:%lu, aStride:%lu\n", eP, eSize, l, h, cStride, aStride);
const float* a = A;
size_t ie = 0;
for (ie = 0; ie + eP <= eSize; ie += eP) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
for (auto ih = 0; ih < h; ih++) {
auto ihPack = ih >> 2;
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihPack * cStride + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x4_t vacc0123 = vld1q_dup_f32(&initValue);
float32x4_t vacc4567 = vacc0123;
float32x4_t vacc89AB = vacc0123;
float32x4_t vaccCDEF = vacc0123;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
const float32x4_t va4567 = vld1q_f32(a + 4);
const float32x4_t va89AB = vld1q_f32(a + 8);
const float32x4_t vaCDEF = vld1q_f32(a + 12);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_dup_f32(w);
// MNN_PRINT("16-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-15]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {16});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc0123 = vfmaq_f32(vacc0123, va0123, w4);
vacc4567 = vfmaq_f32(vacc4567, va4567, w4);
vacc89AB = vfmaq_f32(vacc89AB, va89AB, w4);
vaccCDEF = vfmaq_f32(vaccCDEF, vaCDEF, w4);
}
vacc0123 = vminq_f32(vacc0123, vmax);
vacc4567 = vminq_f32(vacc4567, vmax);
vacc89AB = vminq_f32(vacc89AB, vmax);
vaccCDEF = vminq_f32(vaccCDEF, vmax);
vacc0123 = vmaxq_f32(vacc0123, vmin);
vacc4567 = vmaxq_f32(vacc4567, vmin);
vacc89AB = vmaxq_f32(vacc89AB, vmin);
vaccCDEF = vmaxq_f32(vaccCDEF, vmin);
// how to store faster: st4 / transpose /
vst1q_lane_f32(c, vacc0123, 0);
vst1q_lane_f32(c + 4, vacc0123, 1);
vst1q_lane_f32(c + 4 * 2, vacc0123, 2);
vst1q_lane_f32(c + 4 * 3, vacc0123, 3);
vst1q_lane_f32(c+ 4 * 4, vacc4567, 0);
vst1q_lane_f32(c + 4 * 5, vacc4567, 1);
vst1q_lane_f32(c + 4 * 6, vacc4567, 2);
vst1q_lane_f32(c + 4 * 7, vacc4567, 3);
vst1q_lane_f32(c + 4 * 8, vacc89AB, 0);
vst1q_lane_f32(c + 4 * 9, vacc89AB, 1);
vst1q_lane_f32(c + 4 * 10, vacc89AB, 2);
vst1q_lane_f32(c + 4 * 11, vacc89AB, 3);
vst1q_lane_f32(c + 4 * 12, vaccCDEF, 0);
vst1q_lane_f32(c + 4 * 13, vaccCDEF, 1);
vst1q_lane_f32(c + 4 * 14, vaccCDEF, 2);
vst1q_lane_f32(c + 4 * 15, vaccCDEF, 3);
}
a += aStride;
}
// const float* blockA = A + ie * l;
if (eSize & 0x08) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
for (auto ih = 0; ih < h; ih++) {
auto ihPack = ih >> 2;
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihPack * cStride + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x4_t vacc0123 = vld1q_dup_f32(&initValue);
float32x4_t vacc4567 = vacc0123;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
const float32x4_t va4567 = vld1q_f32(a + 4);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_dup_f32(w);
// MNN_PRINT("8-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-7]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {8});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc0123 = vfmaq_f32(vacc0123, va0123, w4);
vacc4567 = vfmaq_f32(vacc4567, va4567, w4);
}
vacc0123 = vminq_f32(vacc0123, vmax);
vacc4567 = vminq_f32(vacc4567, vmax);
vacc0123 = vmaxq_f32(vacc0123, vmin);
vacc4567 = vmaxq_f32(vacc4567, vmin);
// how to store faster: st4 / transpose /
vst1q_lane_f32(c, vacc0123, 0);
vst1q_lane_f32(c + 4, vacc0123, 1);
vst1q_lane_f32(c + 4 * 2, vacc0123, 2);
vst1q_lane_f32(c + 4 * 3, vacc0123, 3);
vst1q_lane_f32(c + 4 * 4, vacc4567, 0);
vst1q_lane_f32(c + 4 * 5, vacc4567, 1);
vst1q_lane_f32(c + 4 * 6, vacc4567, 2);
vst1q_lane_f32(c + 4 * 7, vacc4567, 3);
}
ie += 8;
a += 8;
}
if (eSize & 0x04) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// const float* a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
for (auto ih = 0; ih < h; ih++) {
auto ihPack = ih >> 2;
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihPack * cStride + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x4_t vacc0123 = vld1q_dup_f32(&initValue);
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_dup_f32(w);
// MNN_PRINT("4-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-3]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {4});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc0123 = vfmaq_f32(vacc0123, va0123, w4);
}
vacc0123 = vminq_f32(vacc0123, vmax);
vacc0123 = vmaxq_f32(vacc0123, vmin);
// how to store faster: st4 / transpose /
vst1q_lane_f32(c, vacc0123, 0);
vst1q_lane_f32(c + 4, vacc0123, 1);
vst1q_lane_f32(c + 4 * 2, vacc0123, 2);
vst1q_lane_f32(c + 4 * 3, vacc0123, 3);
}
ie += 4;
a += 4;
}
if (eSize & 0x02) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// const float* a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
for (auto ih = 0; ih < h; ih++) {
auto ihPack = ih >> 2;
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihPack * cStride + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x2_t vacc01 = vld1_dup_f32(&initValue);
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x2_t va01 = vld1_f32(a);
// __builtin_prefetch(a + aStride);
float32x2_t w2 = vld1_dup_f32(w);
// MNN_PRINT("2-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-1]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {2});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc01 = vfma_f32(vacc01, va01, w2);
}
vacc01 = vmin_f32(vacc01, vget_low_f32(vmax));
vacc01 = vmax_f32(vacc01, vget_low_f32(vmin));
// how to store faster: st4 / transpose /
vst1_lane_f32(c, vacc01, 0);
vst1_lane_f32(c + 4, vacc01, 1);
}
ie += 2;
a += 2;
}
if (eSize & 0x01) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// const float* a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
for (auto ih = 0; ih < h; ih++) {
auto ihPack = ih >> 2;
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihPack * cStride + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float acc0 = initValue;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float a0 = a[0];
const float oneW = *w++;
// MNN_PRINT("1-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0]:", ie, a - A, w - B - 1, c - C, oneW);
// formatMatrix(a, {1});
// MNN_PRINT("\n");
a = a + diff;
acc0 += a0 * oneW;
}
acc0 = std::max(std::min(maxValue, acc0), minValue);
// how to store faster: st4 / transpose /
c[0] = acc0;
}
ie += 1;
// a += 1;
}
return;
}
void MNNPackedSparseMatMulEpx4(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) {
auto eP = parameter[0] / sizeof(float);
MNN_ASSERT((eP & 0x03) == 0); // In sparse calculate, eP should be evenly divided by 4
auto h = parameter[2];
auto l = parameter[1];
auto cStride = parameter[3] / sizeof(float);
auto hRemain = parameter[4];
auto bExtraStride = parameter[5] / sizeof(float);
// auto bStride = bExtraStride + l * 4;
auto aStride = eP * l; // sizeof(float);
auto hC4 = UP_DIV(h, 4);
float minValue = -std::numeric_limits<float>().max();
float maxValue = std::numeric_limits<float>().max();
if (nullptr != postParameters) {
minValue = postParameters[2];
maxValue = postParameters[3];
}
const float32x4_t vmin = vld1q_dup_f32(&minValue);
const float32x4_t vmax = vld1q_dup_f32(&maxValue);
const int sparseBlockOC = 4;
// MNN_PRINT("NEON MNNPackedSparseMatMul eP:%lu, eSize:%lu, l:%lu, h:%lu, cStride:%lu, aStride:%lu\n", eP, eSize, l, h, cStride, aStride);
const float* a = A;
size_t ie = 0;
for (ie = 0; ie + eP <= eSize; ie += eP) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
size_t ih = 0;
for (; ih < (h & (~0x03)); ih += sparseBlockOC) {
auto ihPack = ih >> 2;
auto c = blockC + ihPack * cStride;
// tobe merged in to weight data
float32x4_t vacc0c4 = nullptr != bias ? vld1q_f32(bias + ih) : vdupq_n_f32(0);
float32x4_t vacc1c4 = vacc0c4;
float32x4_t vacc2c4 = vacc0c4;
float32x4_t vacc3c4 = vacc0c4;
float32x4_t vacc4c4 = vacc0c4;
float32x4_t vacc5c4 = vacc0c4;
float32x4_t vacc6c4 = vacc0c4;
float32x4_t vacc7c4 = vacc0c4;
float32x4_t vacc8c4 = vacc0c4;
float32x4_t vacc9c4 = vacc0c4;
float32x4_t vacc10c4 = vacc0c4;
float32x4_t vacc11c4 = vacc0c4;
float32x4_t vacc12c4 = vacc0c4;
float32x4_t vacc13c4 = vacc0c4;
float32x4_t vacc14c4 = vacc0c4;
float32x4_t vacc15c4 = vacc0c4;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
const float32x4_t va4567 = vld1q_f32(a + 4);
const float32x4_t va89AB = vld1q_f32(a + 8);
const float32x4_t vaCDEF = vld1q_f32(a + 12);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_f32(w);
// MNN_PRINT("16-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-15]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {16});
// MNN_PRINT("\n");
w += 4;
a = a + diff;
vacc0c4 = vfmaq_laneq_f32(vacc0c4, w4, va0123, 0);
vacc4c4 = vfmaq_laneq_f32(vacc4c4, w4, va4567, 0);
vacc8c4 = vfmaq_laneq_f32(vacc8c4, w4, va89AB, 0);
vacc12c4 = vfmaq_laneq_f32(vacc12c4, w4, vaCDEF, 0);
vacc1c4 = vfmaq_laneq_f32(vacc1c4, w4, va0123, 1);
vacc5c4 = vfmaq_laneq_f32(vacc5c4, w4, va4567, 1);
vacc9c4 = vfmaq_laneq_f32(vacc9c4, w4, va89AB, 1);
vacc13c4 = vfmaq_laneq_f32(vacc13c4, w4, vaCDEF, 1);
vacc2c4 = vfmaq_laneq_f32(vacc2c4, w4, va0123, 2);
vacc6c4 = vfmaq_laneq_f32(vacc6c4, w4, va4567, 2);
vacc10c4 = vfmaq_laneq_f32(vacc10c4, w4, va89AB, 2);
vacc14c4 = vfmaq_laneq_f32(vacc14c4, w4, vaCDEF, 2);
vacc3c4 = vfmaq_laneq_f32(vacc3c4, w4, va0123, 3);
vacc7c4 = vfmaq_laneq_f32(vacc7c4, w4, va4567, 3);
vacc11c4 = vfmaq_laneq_f32(vacc11c4, w4, va89AB, 3);
vacc15c4 = vfmaq_laneq_f32(vacc15c4, w4, vaCDEF, 3);
}
vacc0c4 = vminq_f32(vacc0c4, vmax);
vacc1c4 = vminq_f32(vacc1c4, vmax);
vacc2c4 = vminq_f32(vacc2c4, vmax);
vacc3c4 = vminq_f32(vacc3c4, vmax);
vacc4c4 = vminq_f32(vacc4c4, vmax);
vacc5c4 = vminq_f32(vacc5c4, vmax);
vacc6c4 = vminq_f32(vacc6c4, vmax);
vacc7c4 = vminq_f32(vacc7c4, vmax);
vacc8c4 = vminq_f32(vacc8c4, vmax);
vacc9c4 = vminq_f32(vacc9c4, vmax);
vacc10c4 = vminq_f32(vacc10c4, vmax);
vacc11c4 = vminq_f32(vacc11c4, vmax);
vacc12c4 = vminq_f32(vacc12c4, vmax);
vacc13c4 = vminq_f32(vacc13c4, vmax);
vacc14c4 = vminq_f32(vacc14c4, vmax);
vacc15c4 = vminq_f32(vacc15c4, vmax);
vacc0c4 = vmaxq_f32(vacc0c4, vmin);
vacc1c4 = vmaxq_f32(vacc1c4, vmin);
vacc2c4 = vmaxq_f32(vacc2c4, vmin);
vacc3c4 = vmaxq_f32(vacc3c4, vmin);
vacc4c4 = vmaxq_f32(vacc4c4, vmin);
vacc5c4 = vmaxq_f32(vacc5c4, vmin);
vacc6c4 = vmaxq_f32(vacc6c4, vmin);
vacc7c4 = vmaxq_f32(vacc7c4, vmin);
vacc8c4 = vmaxq_f32(vacc8c4, vmin);
vacc9c4 = vmaxq_f32(vacc9c4, vmin);
vacc10c4 = vmaxq_f32(vacc10c4, vmin);
vacc11c4 = vmaxq_f32(vacc11c4, vmin);
vacc12c4 = vmaxq_f32(vacc12c4, vmin);
vacc13c4 = vmaxq_f32(vacc13c4, vmin);
vacc14c4 = vmaxq_f32(vacc14c4, vmin);
vacc15c4 = vmaxq_f32(vacc15c4, vmin);
// vacc is continuous along c
vst1q_f32(c, vacc0c4);
vst1q_f32(c + 4 , vacc1c4);
vst1q_f32(c + 4 * 2 , vacc2c4);
vst1q_f32(c + 4 * 3 , vacc3c4);
vst1q_f32(c + 4 * 4 , vacc4c4);
vst1q_f32(c + 4 * 5 , vacc5c4);
vst1q_f32(c + 4 * 6 , vacc6c4);
vst1q_f32(c + 4 * 7 , vacc7c4);
vst1q_f32(c + 4 * 8 , vacc8c4);
vst1q_f32(c + 4 * 9 , vacc9c4);
vst1q_f32(c + 4 * 10 , vacc10c4);
vst1q_f32(c + 4 * 11 , vacc11c4);
vst1q_f32(c + 4 * 12 , vacc12c4);
vst1q_f32(c + 4 * 13 , vacc13c4);
vst1q_f32(c + 4 * 14 , vacc14c4);
vst1q_f32(c + 4 * 15 , vacc15c4);
}
blockC += (h >> 2) * cStride;
for (; ih < h; ih++) {
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x4_t vacc0123 = vld1q_dup_f32(&initValue);
float32x4_t vacc4567 = vacc0123;
float32x4_t vacc89AB = vacc0123;
float32x4_t vaccCDEF = vacc0123;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
const float32x4_t va4567 = vld1q_f32(a + 4);
const float32x4_t va89AB = vld1q_f32(a + 8);
const float32x4_t vaCDEF = vld1q_f32(a + 12);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_dup_f32(w);
// MNN_PRINT("16-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-15]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {16});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc0123 = vfmaq_f32(vacc0123, va0123, w4);
vacc4567 = vfmaq_f32(vacc4567, va4567, w4);
vacc89AB = vfmaq_f32(vacc89AB, va89AB, w4);
vaccCDEF = vfmaq_f32(vaccCDEF, vaCDEF, w4);
}
vacc0123 = vminq_f32(vacc0123, vmax);
vacc4567 = vminq_f32(vacc4567, vmax);
vacc89AB = vminq_f32(vacc89AB, vmax);
vaccCDEF = vminq_f32(vaccCDEF, vmax);
vacc0123 = vmaxq_f32(vacc0123, vmin);
vacc4567 = vmaxq_f32(vacc4567, vmin);
vacc89AB = vmaxq_f32(vacc89AB, vmin);
vaccCDEF = vmaxq_f32(vaccCDEF, vmin);
// how to store faster: st4 / transpose /
vst1q_lane_f32(c, vacc0123, 0);
vst1q_lane_f32(c + 4, vacc0123, 1);
vst1q_lane_f32(c + 4 * 2, vacc0123, 2);
vst1q_lane_f32(c + 4 * 3, vacc0123, 3);
vst1q_lane_f32(c+ 4 * 4, vacc4567, 0);
vst1q_lane_f32(c + 4 * 5, vacc4567, 1);
vst1q_lane_f32(c + 4 * 6, vacc4567, 2);
vst1q_lane_f32(c + 4 * 7, vacc4567, 3);
vst1q_lane_f32(c + 4 * 8, vacc89AB, 0);
vst1q_lane_f32(c + 4 * 9, vacc89AB, 1);
vst1q_lane_f32(c + 4 * 10, vacc89AB, 2);
vst1q_lane_f32(c + 4 * 11, vacc89AB, 3);
vst1q_lane_f32(c + 4 * 12, vaccCDEF, 0);
vst1q_lane_f32(c + 4 * 13, vaccCDEF, 1);
vst1q_lane_f32(c + 4 * 14, vaccCDEF, 2);
vst1q_lane_f32(c + 4 * 15, vaccCDEF, 3);
}
a += aStride;
}
// const float* blockA = A + ie * l;
if (eSize & 0x08) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
size_t ih = 0;
for (; ih < (h & (~0x03)); ih += sparseBlockOC) {
auto ihPack = ih >> 2;
auto c = blockC + ihPack * cStride;
float32x4_t vacc0c4 = nullptr != bias ? vld1q_f32(bias + ih) : vdupq_n_f32(0.f);
float32x4_t vacc1c4 = vacc0c4;
float32x4_t vacc2c4 = vacc0c4;
float32x4_t vacc3c4 = vacc0c4;
float32x4_t vacc4c4 = vacc0c4;
float32x4_t vacc5c4 = vacc0c4;
float32x4_t vacc6c4 = vacc0c4;
float32x4_t vacc7c4 = vacc0c4;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
const float32x4_t va4567 = vld1q_f32(a + 4);
const float32x4_t va89AB = vld1q_f32(a + 8);
const float32x4_t vaCDEF = vld1q_f32(a + 12);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_f32(w);
// MNN_PRINT("16-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-15]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {16});
// MNN_PRINT("\n");
w += 4;
a = a + diff;
vacc0c4 = vfmaq_laneq_f32(vacc0c4, w4, va0123, 0);
vacc4c4 = vfmaq_laneq_f32(vacc4c4, w4, va4567, 0);
vacc1c4 = vfmaq_laneq_f32(vacc1c4, w4, va0123, 1);
vacc5c4 = vfmaq_laneq_f32(vacc5c4, w4, va4567, 1);
vacc2c4 = vfmaq_laneq_f32(vacc2c4, w4, va0123, 2);
vacc6c4 = vfmaq_laneq_f32(vacc6c4, w4, va4567, 2);
vacc3c4 = vfmaq_laneq_f32(vacc3c4, w4, va0123, 3);
vacc7c4 = vfmaq_laneq_f32(vacc7c4, w4, va4567, 3);
}
vacc0c4 = vminq_f32(vacc0c4, vmax);
vacc1c4 = vminq_f32(vacc1c4, vmax);
vacc2c4 = vminq_f32(vacc2c4, vmax);
vacc3c4 = vminq_f32(vacc3c4, vmax);
vacc4c4 = vminq_f32(vacc4c4, vmax);
vacc5c4 = vminq_f32(vacc5c4, vmax);
vacc6c4 = vminq_f32(vacc6c4, vmax);
vacc7c4 = vminq_f32(vacc7c4, vmax);
vacc0c4 = vmaxq_f32(vacc0c4, vmin);
vacc1c4 = vmaxq_f32(vacc1c4, vmin);
vacc2c4 = vmaxq_f32(vacc2c4, vmin);
vacc3c4 = vmaxq_f32(vacc3c4, vmin);
vacc4c4 = vmaxq_f32(vacc4c4, vmin);
vacc5c4 = vmaxq_f32(vacc5c4, vmin);
vacc6c4 = vmaxq_f32(vacc6c4, vmin);
vacc7c4 = vmaxq_f32(vacc7c4, vmin);
// vacc is continuous along c
vst1q_f32(c, vacc0c4);
vst1q_f32(c + 4 , vacc1c4);
vst1q_f32(c + 4 * 2 , vacc2c4);
vst1q_f32(c + 4 * 3 , vacc3c4);
vst1q_f32(c + 4 * 4 , vacc4c4);
vst1q_f32(c + 4 * 5 , vacc5c4);
vst1q_f32(c + 4 * 6 , vacc6c4);
vst1q_f32(c + 4 * 7 , vacc7c4);
}
blockC += (h >> 2) * cStride;
for (; ih < h; ih++) {
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x4_t vacc0123 = vld1q_dup_f32(&initValue);
float32x4_t vacc4567 = vacc0123;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
const float32x4_t va4567 = vld1q_f32(a + 4);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_dup_f32(w);
// MNN_PRINT("8-4-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-7]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {8});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc0123 = vfmaq_f32(vacc0123, va0123, w4);
vacc4567 = vfmaq_f32(vacc4567, va4567, w4);
}
vacc0123 = vminq_f32(vacc0123, vmax);
vacc4567 = vminq_f32(vacc4567, vmax);
vacc0123 = vmaxq_f32(vacc0123, vmin);
vacc4567 = vmaxq_f32(vacc4567, vmin);
// how to store faster: st4 / transpose /
vst1q_lane_f32(c, vacc0123, 0);
vst1q_lane_f32(c + 4, vacc0123, 1);
vst1q_lane_f32(c + 4 * 2, vacc0123, 2);
vst1q_lane_f32(c + 4 * 3, vacc0123, 3);
vst1q_lane_f32(c + 4 * 4, vacc4567, 0);
vst1q_lane_f32(c + 4 * 5, vacc4567, 1);
vst1q_lane_f32(c + 4 * 6, vacc4567, 2);
vst1q_lane_f32(c + 4 * 7, vacc4567, 3);
}
ie += 8;
a += 8;
}
if (eSize & 0x04) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// const float* a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
size_t ih = 0;
for (; ih < (h & (~0x03)); ih += sparseBlockOC) {
auto ihPack = ih >> 2;
auto c = blockC + ihPack * cStride;
float32x4_t vacc0c4 = nullptr != bias ? vld1q_f32(bias + ih) : vdupq_n_f32(0);
float32x4_t vacc1c4 = vacc0c4;
float32x4_t vacc2c4 = vacc0c4;
float32x4_t vacc3c4 = vacc0c4;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_f32(w);
// MNN_PRINT("4-4-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-15]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {16});
// MNN_PRINT("\n");
w += 4;
a = a + diff;
vacc0c4 = vfmaq_laneq_f32(vacc0c4, w4, va0123, 0);
vacc1c4 = vfmaq_laneq_f32(vacc1c4, w4, va0123, 1);
vacc2c4 = vfmaq_laneq_f32(vacc2c4, w4, va0123, 2);
vacc3c4 = vfmaq_laneq_f32(vacc3c4, w4, va0123, 3);
}
vacc0c4 = vminq_f32(vacc0c4, vmax);
vacc1c4 = vminq_f32(vacc1c4, vmax);
vacc2c4 = vminq_f32(vacc2c4, vmax);
vacc3c4 = vminq_f32(vacc3c4, vmax);
vacc0c4 = vmaxq_f32(vacc0c4, vmin);
vacc1c4 = vmaxq_f32(vacc1c4, vmin);
vacc2c4 = vmaxq_f32(vacc2c4, vmin);
vacc3c4 = vmaxq_f32(vacc3c4, vmin);
// vacc is continuous along c
vst1q_f32(c, vacc0c4);
vst1q_f32(c + 4 , vacc1c4);
vst1q_f32(c + 4 * 2 , vacc2c4);
vst1q_f32(c + 4 * 3 , vacc3c4);
}
blockC += (h >> 2) * cStride;
for (; ih < h; ih++) {
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x4_t vacc0123 = vld1q_dup_f32(&initValue);
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x4_t va0123 = vld1q_f32(a);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_dup_f32(w);
// MNN_PRINT("4-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-3]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {4});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc0123 = vfmaq_f32(vacc0123, va0123, w4);
}
vacc0123 = vminq_f32(vacc0123, vmax);
vacc0123 = vmaxq_f32(vacc0123, vmin);
// how to store faster: st4 / transpose /
vst1q_lane_f32(c, vacc0123, 0);
vst1q_lane_f32(c + 4, vacc0123, 1);
vst1q_lane_f32(c + 4 * 2, vacc0123, 2);
vst1q_lane_f32(c + 4 * 3, vacc0123, 3);
}
ie += 4;
a += 4;
}
if (eSize & 0x02) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// const float* a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
size_t ih = 0;
for (; ih < (h & (~0x03)); ih += sparseBlockOC) {
auto ihPack = ih >> 2;
auto c = blockC + ihPack * cStride;
float32x4_t vacc0c4 = nullptr != bias ? vld1q_f32(bias + ih) : vdupq_n_f32(0.f);
float32x4_t vacc1c4 = vacc0c4;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x2_t va01 = vld1_f32(a);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_f32(w);
// MNN_PRINT("2-4-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-15]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {16});
// MNN_PRINT("\n");
w += 4;
a = a + diff;
vacc0c4 = vfmaq_lane_f32(vacc0c4, w4, va01, 0);
vacc1c4 = vfmaq_lane_f32(vacc1c4, w4, va01, 1);
}
vacc0c4 = vminq_f32(vacc0c4, vmax);
vacc1c4 = vminq_f32(vacc1c4, vmax);
vacc0c4 = vmaxq_f32(vacc0c4, vmin);
vacc1c4 = vmaxq_f32(vacc1c4, vmin);
// vacc is continuous along c
vst1q_f32(c, vacc0c4);
vst1q_f32(c + 4, vacc1c4);
}
blockC += (h >> 2) * cStride;
for (; ih < h; ih++) {
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float32x2_t vacc01 = vld1_dup_f32(&initValue);
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x2_t va01 = vld1_f32(a);
// __builtin_prefetch(a + aStride);
float32x2_t w2 = vld1_dup_f32(w);
// MNN_PRINT("2-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-1]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {2});
// MNN_PRINT("\n");
w++;
a = a + diff;
vacc01 = vfma_f32(vacc01, va01, w2);
}
vacc01 = vmin_f32(vacc01, vget_low_f32(vmax));
vacc01 = vmax_f32(vacc01, vget_low_f32(vmin));
// how to store faster: st4 / transpose /
vst1_lane_f32(c, vacc01, 0);
vst1_lane_f32(c + 4, vacc01, 1);
}
ie += 2;
a += 2;
}
if (eSize & 0x01) {
const int* dataOffset = dataOffsetMap;
const int diff = *dataOffset++;
// const float* a = blockA + diff;
a += diff;
const float* w = B;
float* blockC = C + (ie << 2);
const unsigned int* nnz = NNZMap;
size_t ih = 0;
for (; ih < (h & (~0x03)); ih += sparseBlockOC) {
auto ihPack = ih >> 2;
auto c = blockC + ihPack * cStride;
float32x4_t vacc0c4 = nullptr != bias ? vld1q_f32(bias + ih) : vdupq_n_f32(0);
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float32x2_t va01 = vld1_f32(a);
// __builtin_prefetch(a + aStride);
float32x4_t w4 = vld1q_f32(w);
// MNN_PRINT("1-4-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0-15]:", ie, a - A, w - B, c - C, *w);
// formatMatrix(a, {16});
// MNN_PRINT("\n");
w += 4;
a = a + diff;
vacc0c4 = vfmaq_lane_f32(vacc0c4, w4, va01, 0);
}
vacc0c4 = vminq_f32(vacc0c4, vmax);
vacc0c4 = vmaxq_f32(vacc0c4, vmin);
// vacc is continuous along c
vst1q_f32(c, vacc0c4);
}
blockC += (h >> 2) * cStride;
for (; ih < h; ih++) {
auto ihSubIndex = ih & 0x03;
auto c = blockC + ihSubIndex;
const float initValue = nullptr != bias ? bias[ih] : 0;
float acc0 = initValue;
const unsigned int lElement = *nnz++;
for (auto il = 0; il < lElement; il++) {
const int diff = *dataOffset++;
const float a0 = a[0];
const float oneW = *w++;
// MNN_PRINT("1-loop: ie:%zu, a offset:%ld, w offset:%ld, c offset:%ld, w value:%f, a value[0]:", ie, a - A, w - B - 1, c - C, oneW);
// formatMatrix(a, {1});
// MNN_PRINT("\n");
a = a + diff;
acc0 += a0 * oneW;
}
acc0 = std::max(std::min(maxValue, acc0), minValue);
// how to store faster: st4 / transpose /
c[0] = acc0;
}
ie += 1;
// a += 1;
}
return;
}
#endif
void MNNGetSparseMatMulPackMode(int* eP, int *lP, int* hP) {
#ifdef __aarch64__
*eP = 16;
#else
*eP = 8; // total vector number is 16, we choose to use 8 for output.
#endif
*lP = 1;
*hP = 4;
// hp is corresponding to sparse block along right matrix colum dimension. in ramdom sparse, it is 1.
return;
}
void MNNGetMatMulPackMode(int* eP, int *lP, int* hP) {
*eP = 12;
*lP = 1;
#ifdef __aarch64__
*hP = 8;
#else
*hP = 4;
#endif
}
#ifdef __aarch64__
// input shape is (l, h) when transpose=false, else input shape is (h, l)
// output shape is (UP_DIV(h, 8), l, 8)
void MNNPackForMatMul_B(float* dest, const float* source, size_t h, size_t kernelsize, size_t ic, bool transpose) {
auto hP = (int)h / 8;
auto hR = (int)hP * 8;
auto l = kernelsize * ic;
if (hR != h) {
::memset(dest, 0, UP_DIV(h, 8)*8*l*sizeof(float));
}
if (!transpose) {
for (int y=0; y<hP; ++y) {
auto destY = dest + y * 8 * l;
auto sourceY = source + y * 8;
for (int x=0; x<l; ++x) {
::memcpy(destY + 8 * x, sourceY + x * h, 8 * sizeof(float));
}
}
auto hRemain = h - hR;
if (hRemain > 0) {
auto destY = dest + hP * 8 * l;
auto sourceY = source + hP * 8;
for (int x=0; x<l; ++x) {
::memcpy(destY + 8 * x, sourceY + x * h, hRemain * sizeof(float));
}
}
return;
}
int lC8 = (int)l / 8;
auto lR = lC8 * 8;
if (hP > 0 && lC8 > 0) {
MNNPackC8(dest, source, l, h);
}
for (int y=hR; y<h; ++y) {
auto yR = y % 8;
auto yC = hP;
for (int x=0; x<l; ++x) {
dest[x * 8 + yR + yC * 8 * l] = source[x + y * l];
}
}
for (int y=0; y<hR; ++y) {
auto yR = y % 8;
auto yC = y / 8;
for (int x=lR; x<l; ++x) {
dest[x * 8 + yR + yC * 8 * l] = source[x + y * l];
}
}
}
#else
void MNNPackForMatMul_B(float* dest, const float* source, size_t h, size_t kernelsize, size_t ic, bool transpose) {
auto l = kernelsize * ic;
if (!transpose) {
auto hP = h / 4;
auto hR = hP * 4;
if (hR != h) {
::memset(dest, 0, UP_DIV(h, 4)*4*l*sizeof(float));
}
for (int y=0; y<hP; ++y) {
auto destY = dest + y * 4 * l;
auto sourceY = source + y * 4;
for (int x=0; x<l; ++x) {
::memcpy(destY + 4 * x, sourceY + x * h, 4 * sizeof(float));
}
}
auto hRemain = h - hR;
if (hRemain > 0) {
auto destY = dest + hP * 4 * l;
auto sourceY = source + hP * 4;
for (int x=0; x<l; ++x) {
::memcpy(destY + 4 * x, sourceY + x * h, hRemain * sizeof(float));
}
}
return;
}
int offset[] = {
(int)l, (int)l
};
MNNPackC4(dest, source, l, h, offset);
}
#endif
#endif