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Vectorize requantize_ for Arm64 with NEON intrinsics #5130

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Vectorize requantize_ for Arm64 with NEON intrinsics #5130

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2 changes: 1 addition & 1 deletion src/FbgemmI8Depthwise2DAvx2-inl.h
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,7 @@

#pragma once

#include "./FbgemmI8DepthwiseAvx2-inl.h" // @manual
#include "./FbgemmI8DepthwiseUtils.h" // @manual
#include "./GenerateI8Depthwise.h" // @manual
#include "./MaskAvx2.h" // @manual
#include "fbgemm/Utils.h"
Expand Down
2 changes: 1 addition & 1 deletion src/FbgemmI8Depthwise3DAvx2.cc
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Expand Up @@ -12,7 +12,7 @@
#include <stdexcept> // for logic_error
#include <string>

#include "./FbgemmI8DepthwiseAvx2-inl.h" // @manual
#include "./FbgemmI8DepthwiseUtils.h" // @manual
#include "./GenerateI8Depthwise.h" // @manual
#include "./MaskAvx2.h" // @manual
#include "fbgemm/Utils.h"
Expand Down
80 changes: 28 additions & 52 deletions src/FbgemmI8DepthwiseAvx2-inl.h
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Expand Up @@ -8,25 +8,21 @@

#pragma once

#include <algorithm> // for min and max
#if defined(__x86_64__) || defined(__i386__) || \
(defined(_MSC_VER) && (defined(_M_X64) || defined(_M_IX86)))

#include <cassert>
#include <cmath> // for lrintf and sqrt
#include <cstdint>
#include <type_traits> // for is_same

#if defined(__x86_64__) || defined(__i386__) || \
(defined(_MSC_VER) && (defined(_M_X64) || defined(_M_IX86)))
#include <immintrin.h>
#include <math.h>
#endif

#include "fbgemm/FbgemmBuild.h"
#include "fbgemm/UtilsAvx2.h"

namespace fbgemm {

// Almost same as ReQuantizeOutput in OutputProcessing-inh.h but different
// row_offsets for each row because of depth-wise convolution
template <
bool FUSE_RELU,
bool HAS_BIAS,
Expand All @@ -47,6 +43,8 @@ static ALWAYS_INLINE void requantize_(
const std::int32_t* col_offsets,
const BIAS_TYPE* bias [[maybe_unused]],
const float* act_times_w_scale = nullptr) {
int j = 0;
#ifdef __AVX2__
__m256 multiplier_v = _mm256_setzero_ps();
// Broadcasted reciprocal of act_times_w_scale
__m256 act_times_w_rcp_v [[maybe_unused]] = _mm256_setzero_ps();
Expand All @@ -73,7 +71,6 @@ static ALWAYS_INLINE void requantize_(
_mm256_set_epi32(0x07, 0x03, 0x06, 0x02, 0x05, 0x01, 0x04, 0x00);

constexpr int VLEN = 8;
int j = 0;
for (; j < n / (VLEN * 4) * (VLEN * 4); j += (VLEN * 4)) {
__m256i x_v =
_mm256_loadu_si256(reinterpret_cast<const __m256i*>(C_int32 + j));
Expand Down Expand Up @@ -502,51 +499,30 @@ static ALWAYS_INLINE void requantize_(
reinterpret_cast<__m128i*>(C_uint8 + j),
_mm256_castsi256_si128(x_clamped_v));
} // j loop vectorized
#endif

for (; j < n; ++j) {
std::int32_t raw = C_int32[j];
int quant_param_idx = 0;
if constexpr (
Q_GRAN == QuantizationGranularity::OUT_CHANNEL ||
(Q_GRAN == QuantizationGranularity::GROUP && K_PER_G == 1)) {
quant_param_idx = j;
} else if constexpr (Q_GRAN == QuantizationGranularity::GROUP) {
quant_param_idx = j / 2;
}
if constexpr (!B_SYMMETRIC) {
raw -= B_zero_point[quant_param_idx] * row_offsets[j / K_PER_G];
}
if constexpr (!A_SYMMETRIC) {
raw -= A_zero_point * col_offsets[j];
}
float raw_f = NAN;
if constexpr (HAS_BIAS) { // static if
if constexpr (std::is_same_v<BIAS_TYPE, float>) {
raw_f = raw;
raw_f += bias[j] / act_times_w_scale[quant_param_idx];
} else {
raw += bias[j];
raw_f = raw;
}
} else {
raw_f = raw;
}

float ab = raw_f * C_multiplier[quant_param_idx];
long rounded = lrintf(ab) + C_zero_point;

C_uint8[j] = std::max(
FUSE_RELU ? static_cast<long>(C_zero_point) : 0l,
std::min(255l, rounded));
}
}

static inline std::pair<int, int> closest_factors_(int n) {
int a = static_cast<int>(std::sqrt(n));
while (n % a != 0) {
a--;
}
return {a, n / a}; // a <= n / a
requantize_i8dw_ref_<
FUSE_RELU,
HAS_BIAS,
Q_GRAN,
A_SYMMETRIC,
B_SYMMETRIC,
K_PER_G,
BIAS_TYPE>(
A_zero_point,
B_zero_point,
C_multiplier,
C_zero_point,
C_int32,
C_uint8,
n,
j,
row_offsets,
col_offsets,
bias,
act_times_w_scale);
}

} // namespace fbgemm

#endif
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