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/*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#include "fbgemm/FbgemmI8Spmdm.h"
#include <algorithm>
#include <array>
#include <cassert>
#include <cmath>
#include <cstring>
#include "OptimizedKernelsAvx2.h"
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
double spmdm_initial_time = 0.0;
double spmdm_transpose_uint8_time = 0.0;
double spmdm_transpose_32xN_time = 0.0;
double spmdm_compute_time = 0.0;
double spmdm_transpose_Nx32_time = 0.0;
double spmdm_run_time = 0.0;
double sconv_run_time = 0.0;
#endif
using namespace std;
namespace fbgemm {
CompressedSparseColumn::CompressedSparseColumn(int num_of_rows, int num_of_cols)
: num_rows_(num_of_rows),
colptr_(num_of_cols + 1),
hyper_sparse_(false),
old_nnz_(-1) {}
double CompressedSparseColumn::Density() const {
return static_cast<double>(NumOfNonZeros()) / (NumOfRows() * NumOfCols());
}
bool CompressedSparseColumn::IsHyperSparse() const {
if (NumOfNonZeros() != old_nnz_) {
old_nnz_ = NumOfNonZeros();
// The number of non-zero per row is very small.
hyper_sparse_ = static_cast<double>(old_nnz_) / NumOfRows() < 0.3;
}
return hyper_sparse_;
}
// TODO: fallback when AVX2 is not available
void CompressedSparseColumn::SpMDM(
const block_type_t& block,
const uint8_t* A,
int lda,
bool accumulation,
int32_t* C,
int ldc) const {
int K = NumOfRows();
int N = block.col_size;
if (K == 0 || N == 0) {
return;
}
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
std::chrono::time_point<std::chrono::high_resolution_clock> t_very_start,
t_start, t_end;
double dt;
t_start = std::chrono::high_resolution_clock::now();
t_very_start = std::chrono::high_resolution_clock::now();
#endif
alignas(64) uint8_t A_buffer[K * 32];
alignas(64) int32_t C_buffer[N * 32];
// If we compute C = C + A * B, where B is a sparse matrix in CSC format, for
// each non-zero in B, we'd need to access the corresponding column in A.
// This results in strided access, which we want to avoid.
// Instead, we pre-transpose A and C, and compute C = (C^T + B^T * A^T)^T
if (IsHyperSparse()) {
// The cost of transpose is O(K*N) and we do O(NNZ*N) multiplications.
// If NNZ/K is small, it's not worth doing transpose so we just use this
// scalar loop.
int32_t C_temp[block.row_size];
if (accumulation) {
for (int j = 0; j < block.col_size; ++j) {
int k = colptr_[block.col_start + j];
int k_end = colptr_[block.col_start + j + 1];
if (k_end == k) {
} else if (k_end == k + 1) {
int row = rowidx_[k];
int w = values_[k];
for (int i = 0; i < block.row_size; ++i) {
C[i * ldc + j] += A[(block.row_start + i) * lda + row] * w;
}
} else {
for (int i = 0; i < block.row_size; ++i) {
C_temp[i] = C[i * ldc + j];
}
for (; k < k_end; ++k) {
int row = rowidx_[k];
int w = values_[k];
for (int i = 0; i < block.row_size; ++i) {
C_temp[i] += A[(block.row_start + i) * lda + row] * w;
}
}
for (int i = 0; i < block.row_size; ++i) {
C[i * ldc + j] = C_temp[i];
}
}
} // for each column of B
} else {
for (int j = 0; j < block.col_size; ++j) {
int k = colptr_[block.col_start + j];
int k_end = colptr_[block.col_start + j + 1];
if (k_end == k) {
for (int i = 0; i < block.row_size; ++i) {
C[i * ldc + j] = 0;
}
} else if (k_end == k + 1) {
int row = rowidx_[k];
int w = values_[k];
for (int i = 0; i < block.row_size; ++i) {
C[i * ldc + j] = A[(block.row_start + i) * lda + row] * w;
}
} else {
for (int i = 0; i < block.row_size; ++i) {
C_temp[i] = 0;
}
for (; k < k_end; ++k) {
int row = rowidx_[k];
int w = values_[k];
for (int i = 0; i < block.row_size; ++i) {
C_temp[i] += A[(block.row_start + i) * lda + row] * w;
}
}
for (int i = 0; i < block.row_size; ++i) {
C[i * ldc + j] = C_temp[i];
}
}
} // for each column of B
}
return;
}
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
t_end = std::chrono::high_resolution_clock::now();
dt = std::chrono::duration_cast<std::chrono::nanoseconds>(t_end - t_start)
.count();
spmdm_initial_time += (dt);
t_start = std::chrono::high_resolution_clock::now();
#endif
// Take 32 rows at a time
int i_end = block.row_start + block.row_size;
for (int i1 = block.row_start; i1 < i_end; i1 += 32) {
// Transpose 32 x K submatrix of A
if (i_end - i1 < 32) {
alignas(64) uint8_t A_temp_buffer[K * 32];
for (int i2 = 0; i2 < (i_end - i1) / 8 * 8; i2 += 8) {
transpose_8rows(K, A + (i1 + i2) * lda, lda, A_buffer + i2, 32);
}
for (int i2 = (i_end - i1) / 8 * 8; i2 < i_end - i1; ++i2) {
memcpy(
A_temp_buffer + i2 * K, A + (i1 + i2) * lda, K * sizeof(uint8_t));
}
memset(
A_temp_buffer + (i_end - i1) * K,
0,
(32 - (i_end - i1)) * K * sizeof(uint8_t));
for (int i2 = (i_end - i1) / 8 * 8; i2 < 32; i2 += 8) {
transpose_8rows(K, A_temp_buffer + i2 * K, K, A_buffer + i2, 32);
}
} else {
for (int i2 = 0; i2 < 32; i2 += 8) {
transpose_8rows(K, A + (i1 + i2) * lda, lda, A_buffer + i2, 32);
}
}
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
t_end = std::chrono::high_resolution_clock::now();
dt = std::chrono::duration_cast<std::chrono::nanoseconds>(t_end - t_start)
.count();
spmdm_transpose_uint8_time += (dt);
t_start = std::chrono::high_resolution_clock::now();
#endif
if (accumulation) {
// Transpose 32 x N submatrix of C to fill N x 32 C_buffer
transpose_simd(
std::min(32, i_end - i1),
N,
reinterpret_cast<const float*>(C + (i1 - block.row_start) * ldc),
ldc,
reinterpret_cast<float*>(C_buffer),
32);
} else {
memset(C_buffer, 0, N * 32 * sizeof(int32_t));
}
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
t_end = std::chrono::high_resolution_clock::now();
dt = std::chrono::duration_cast<std::chrono::nanoseconds>(t_end - t_start)
.count();
spmdm_transpose_32xN_time += (dt);
t_start = std::chrono::high_resolution_clock::now();
#endif
spmdmKernelAvx2(
block.col_size,
A_buffer,
colptr_.data() + block.col_start,
values_.data(),
rowidx_.data(),
C_buffer);
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
t_end = std::chrono::high_resolution_clock::now();
dt = std::chrono::duration_cast<std::chrono::nanoseconds>(t_end - t_start)
.count();
spmdm_compute_time += (dt);
t_start = std::chrono::high_resolution_clock::now();
#endif
// Transpose N x 32 C_buffer to fill 32 x N submatrix of C
transpose_simd(
N,
std::min(32, i_end - i1),
reinterpret_cast<const float*>(C_buffer),
32,
reinterpret_cast<float*>(C + (i1 - block.row_start) * ldc),
ldc);
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
t_end = std::chrono::high_resolution_clock::now();
dt = std::chrono::duration_cast<std::chrono::nanoseconds>(t_end - t_start)
.count();
spmdm_transpose_Nx32_time += (dt);
t_start = std::chrono::high_resolution_clock::now();
#endif
}
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
t_end = std::chrono::high_resolution_clock::now();
dt =
std::chrono::duration_cast<std::chrono::nanoseconds>(t_end - t_very_start)
.count();
spmdm_run_time += (dt);
t_start = std::chrono::high_resolution_clock::now();
#endif
}
void CompressedSparseColumn::SparseConv(
const conv_param_t<>& conv_p,
const block_type_t& block,
const uint8_t* A,
int32_t A_zero_point,
bool accumulation,
int32_t* C,
int ldc) const {
int K = NumOfRows();
int N = block.col_size;
if (K == 0 || N == 0) {
return;
}
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
std::chrono::time_point<std::chrono::high_resolution_clock> t_start, t_end;
double dt;
t_start = std::chrono::high_resolution_clock::now();
#endif
// TODO: if not hyper sparse, transpose a block of A matrix as in SpMDM.
if (!accumulation) {
for (int i = block.row_start; i < block.row_start + block.row_size; ++i) {
for (int j = block.col_start; j < block.col_start + block.col_size; ++j) {
C[(i - block.row_start) * ldc + j - block.col_start] = 0;
}
}
}
for (int j = block.col_start; j < block.col_start + block.col_size; ++j) {
for (int k = colptr_[j]; k < colptr_[j + 1]; ++k) {
int v = values_[k];
for (int i = block.row_start; i < block.row_start + block.row_size; ++i) {
int ow = i % conv_p.OUT_DIM[1];
int oh = i / conv_p.OUT_DIM[1] % conv_p.OUT_DIM[0];
int n = i / conv_p.OUT_DIM[1] / conv_p.OUT_DIM[0];
assert(n < conv_p.MB);
int iw = -conv_p.pad[1] + ow * conv_p.stride[1] + kw_[k];
int ih = -conv_p.pad[0] + oh * conv_p.stride[0] + kh_[k];
if (ih >= 0 && ih < conv_p.IN_DIM[0] && iw >= 0 &&
iw < conv_p.IN_DIM[1]) {
C[(i - block.row_start) * ldc + j - block.col_start] +=
A[((n * conv_p.IN_DIM[0] + ih) * conv_p.IN_DIM[1] + iw) *
conv_p.IC +
ic_[k]] *
v;
} else {
C[(i - block.row_start) * ldc + j - block.col_start] +=
A_zero_point * v;
}
}
}
} // for each column of B
#ifdef FBGEMM_MEASURE_TIME_BREAKDOWN
t_end = std::chrono::high_resolution_clock::now();
dt = std::chrono::duration_cast<std::chrono::nanoseconds>(t_end - t_start)
.count();
sconv_run_time += (dt);
#endif
}
} // namespace fbgemm
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