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Copy pathFbgemmSparseDenseVectorInt8Avx512.cc
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FbgemmSparseDenseVectorInt8Avx512.cc
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/*
* Copyright (c) Meta Platforms, Inc. and 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.
*/
#define FBGEMM_EXPORTS
#include "fbgemm/FbgemmSparse.h"
#include "fbgemm/Utils.h"
#include "fbgemm/spmmUtilsAvx2.h"
#if defined(__x86_64__) || defined(__i386__) || \
(defined(_MSC_VER) && (defined(_M_X64) || defined(_M_IX86)))
#include <immintrin.h>
#endif
#include <cassert>
namespace fbgemm {
namespace internal {
static inline int32_t horizontal_add(__m256i a) {
__m256i t1 = _mm256_hadd_epi32(a, a);
__m256i t2 = _mm256_hadd_epi32(t1, t1);
__m128i t3 = _mm256_extracti128_si256(t2, 1);
__m128i t4 = _mm_add_epi32(_mm256_castsi256_si128(t2), t3);
return _mm_cvtsi128_si32(t4);
}
template <
bool FUSE_RELU,
bool ACT_ZP_0, // is activation zero point 0?
bool HAS_BIAS,
QuantizationGranularity Q_GRAN>
static inline void requantizeForMV(
uint8_t* dst,
int32_t* src,
int len,
trRequantizationParams_t& rParams) {
constexpr int VLEN_INT32 = 16;
__m512i C_zero_point_epi8_v = _mm512_set1_epi8(rParams.C_zero_point);
__m512i C_zero_point_epi32_v = _mm512_set1_epi32(rParams.C_zero_point);
// clang-format off
__m512i permute_mask_v = _mm512_set_epi32(
0x0F, 0x0B, 0x07, 0x03,
0x0E, 0x0A, 0x06, 0x02,
0x0D, 0x09, 0x05, 0x01,
0x0C, 0x08, 0x04, 0x00);
// clang-format on
int i = 0;
for (; i < len / VLEN_INT32 * VLEN_INT32; i += VLEN_INT32) {
__m512i x_v = _mm512_loadu_si512(src + i);
if (!ACT_ZP_0) {
__m512i weight_row_offset_v =
_mm512_loadu_si512(rParams.weight_row_offsets + i);
__m512i act_zero_point_v = _mm512_set1_epi32(rParams.act_zero_point);
x_v = _mm512_sub_epi32(
x_v, _mm512_mullo_epi32(act_zero_point_v, weight_row_offset_v));
}
__m512 act_times_w_scale_v;
if (Q_GRAN == QuantizationGranularity::OUT_CHANNEL) {
act_times_w_scale_v = _mm512_loadu_ps(rParams.act_times_w_scale + i);
} else {
act_times_w_scale_v = _mm512_set1_ps(rParams.act_times_w_scale[0]);
}
__m512 c_scale_v = _mm512_set1_ps(rParams.C_scale);
__m512 act_times_w_div_c_v = _mm512_div_ps(act_times_w_scale_v, c_scale_v);
__m512 xf_v;
if (HAS_BIAS) {
__m512 bias_v = _mm512_loadu_ps(rParams.bias + i);
bias_v = _mm512_div_ps(bias_v, act_times_w_scale_v);
xf_v = _mm512_add_ps(_mm512_cvtepi32_ps(x_v), bias_v);
} else {
xf_v = _mm512_cvtepi32_ps(x_v);
}
__m512 x_scaled_v = _mm512_mul_ps(xf_v, act_times_w_div_c_v);
__m512i x_rounded_v = _mm512_cvtps_epi32(x_scaled_v);
__m512i x_added_v = _mm512_add_epi32(x_rounded_v, C_zero_point_epi32_v);
__m512i x_clamped_v = _mm512_packs_epi32(x_added_v, _mm512_setzero_si512());
x_clamped_v = _mm512_packus_epi16(x_clamped_v, _mm512_setzero_si512());
if (FUSE_RELU) {
x_clamped_v = _mm512_max_epu8(C_zero_point_epi8_v, x_clamped_v);
}
x_clamped_v = _mm512_permutexvar_epi32(permute_mask_v, x_clamped_v);
_mm_store_si128(
reinterpret_cast<__m128i*>(dst + i),
_mm512_castsi512_si128(x_clamped_v));
}
int rem_int32 = len - i;
if (rem_int32 > 0) {
__mmask64 mask_int8_v = (((long long)1) << rem_int32) - 1;
__mmask16 mask_int32_v = (((long long)1) << rem_int32) - 1;
__m512i x_v = _mm512_maskz_loadu_epi32(mask_int32_v, src + i);
if (!ACT_ZP_0) {
__m512i weight_row_offset_v = _mm512_maskz_loadu_epi32(
mask_int32_v, rParams.weight_row_offsets + i);
__m512i act_zero_point_v = _mm512_set1_epi32(rParams.act_zero_point);
x_v = _mm512_sub_epi32(
x_v, _mm512_mullo_epi32(act_zero_point_v, weight_row_offset_v));
}
__m512 act_times_w_scale_v;
if (Q_GRAN == QuantizationGranularity::OUT_CHANNEL) {
act_times_w_scale_v =
_mm512_maskz_loadu_ps(mask_int32_v, rParams.act_times_w_scale + i);
} else {
act_times_w_scale_v = _mm512_set1_ps(rParams.act_times_w_scale[0]);
}
__m512 c_scale_v = _mm512_set1_ps(rParams.C_scale);
__m512 act_times_w_div_c_v = _mm512_div_ps(act_times_w_scale_v, c_scale_v);
__m512 xf_v;
if (HAS_BIAS) {
__m512 bias_v = _mm512_maskz_loadu_ps(mask_int32_v, rParams.bias + i);
bias_v = _mm512_div_ps(bias_v, act_times_w_scale_v);
xf_v = _mm512_add_ps(_mm512_cvtepi32_ps(x_v), bias_v);
} else {
xf_v = _mm512_cvtepi32_ps(x_v);
}
__m512 x_scaled_v = _mm512_mul_ps(xf_v, act_times_w_div_c_v);
__m512i x_rounded_v = _mm512_cvtps_epi32(x_scaled_v);
__m512i x_added_v = _mm512_add_epi32(x_rounded_v, C_zero_point_epi32_v);
__m512i x_clamped_v = _mm512_packs_epi32(x_added_v, _mm512_setzero_si512());
x_clamped_v = _mm512_packus_epi16(x_clamped_v, _mm512_setzero_si512());
if (FUSE_RELU) {
x_clamped_v = _mm512_max_epu8(C_zero_point_epi8_v, x_clamped_v);
}
x_clamped_v = _mm512_permutexvar_epi32(permute_mask_v, x_clamped_v);
_mm512_mask_storeu_epi8(dst + i, mask_int8_v, x_clamped_v);
}
}
// matrix-vector product
// i.e., produces same results as SparseDenseInt8MMAvx512 with N == 1
template <bool FUSE_RELU, QuantizationGranularity Q_GRAN>
void SparseDenseInt8MVAvx512(
const std::unique_ptr<BCSRMatrix<>>& bcsr,
const uint8_t* B,
int ldb,
int32_t* C_i32,
uint8_t* C_u8,
trRequantizationParams_t& rParams,
bool accum,
int thread_id,
int num_threads) {
(void)num_threads; // Suppress unused variable warning
// Calcualtes accum ? C += A * B : C = A * B
constexpr int VLEN_INT32 = 16;
constexpr int block_size = BCSRMatrix<>::CB;
constexpr int colTileSize = BCSRMatrix<>::COLTILE;
// all work is done by thread 0 for now
assert(num_threads > 0 && "Numbers of threads should be > 0");
if (thread_id > 0) {
return;
}
assert(ldb == 1 && "ldb should be 1");
__m512i one_16bit_v = _mm512_set1_epi16(1);
// Number of columns in the sparse matrix A
int K = bcsr->C;
int M = bcsr->R;
assert(K % 4 == 0 && "K should be multiple of 4");
assert((K > 0) && "K needs to be positive");
int kTiles = (K + colTileSize - 1) / colTileSize;
const int* row_ptr = bcsr->rowBPtr.data();
const int* col_idx = bcsr->colBIdx.data();
const int8_t* values = bcsr->values.data();
for (int kt = 0; kt < kTiles; ++kt) {
const int* cur_row_ptr = row_ptr + kt * M;
const uint8_t* cur_B = B + kt * colTileSize * ldb;
// TODO: unroll this loop?
for (int i = 0; i < M; ++i) {
__m512i res = _mm512_set1_epi32(0);
int r = cur_row_ptr[i];
int r_end_aligned = cur_row_ptr[i] +
(cur_row_ptr[i + 1] - cur_row_ptr[i]) / VLEN_INT32 * VLEN_INT32;
for (; r < r_end_aligned; r += VLEN_INT32) {
__m512i a_v = _mm512_loadu_si512(values + r * block_size);
__m512i b_idx = _mm512_loadu_si512(col_idx + r);
__m512i b_v = _mm512_i32gather_epi32(
b_idx, reinterpret_cast<const int32_t*>(cur_B), block_size);
__m512i c_i16_v = _mm512_maddubs_epi16(b_v, a_v);
__m512i c_i32_v = _mm512_madd_epi16(one_16bit_v, c_i16_v);
res = _mm512_add_epi32(res, c_i32_v);
}
int rem = cur_row_ptr[i + 1] - r;
if (rem > 0) {
__mmask16 mask_int32_v = (((long long)1) << (rem)) - 1;
__m512i a_v =
_mm512_maskz_loadu_epi32(mask_int32_v, values + r * block_size);
__m512i b_idx = _mm512_maskz_loadu_epi32(mask_int32_v, col_idx + r);
__m512i b_v = _mm512_i32gather_epi32(
b_idx, reinterpret_cast<const int32_t*>(cur_B), block_size);
__m512i c_i16_v = _mm512_maddubs_epi16(b_v, a_v);
__m512i c_i32_v = _mm512_madd_epi16(one_16bit_v, c_i16_v);
res = _mm512_add_epi32(res, c_i32_v);
}
// Horizontal reduce
// _mm512_reduce_add_epi32 is only available for gcc version > 7
#if __GNUC__ >= 7
int32_t res_i32 = _mm512_reduce_add_epi32(res);
#else
__m256i low = _mm512_castsi512_si256(res);
__m256i high = _mm512_extracti64x4_epi64(res, 1);
int32_t res_i32 = horizontal_add(_mm256_add_epi32(low, high));
#endif
// store the results
if (accum || kt > 0) {
C_i32[i] += res_i32;
} else {
C_i32[i] = res_i32;
}
}
}
if (rParams.bias == nullptr) {
if (rParams.act_zero_point) {
requantizeForMV<FUSE_RELU, false, false, Q_GRAN>(C_u8, C_i32, M, rParams);
} else {
requantizeForMV<FUSE_RELU, true, false, Q_GRAN>(C_u8, C_i32, M, rParams);
}
} else {
if (rParams.act_zero_point) {
requantizeForMV<FUSE_RELU, false, true, Q_GRAN>(C_u8, C_i32, M, rParams);
} else {
requantizeForMV<FUSE_RELU, true, true, Q_GRAN>(C_u8, C_i32, M, rParams);
}
}
}
#define CREATE_INSTANCE(FUSE_RELU, QGRAN) \
template void SparseDenseInt8MVAvx512<FUSE_RELU, QGRAN>( \
const std::unique_ptr<BCSRMatrix<>>& bcsr, \
const uint8_t* B, \
int ldb, \
int32_t* C_i32, \
uint8_t* C_u8, \
trRequantizationParams_t& rParams, \
bool accum, \
int thread_id, \
int num_threads);
CREATE_INSTANCE(true, QuantizationGranularity::TENSOR)
CREATE_INSTANCE(true, QuantizationGranularity::OUT_CHANNEL)
CREATE_INSTANCE(false, QuantizationGranularity::TENSOR)
CREATE_INSTANCE(false, QuantizationGranularity::OUT_CHANNEL)
#undef CREATE_INSTANCE
} // namespace internal
} // namespace fbgemm