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[Executorch] Add multithreading for op_quantize #15609

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[Executorch] Add multithreading for op_quantize #15609

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27fc8b1
[Executorch] Add multithreading for op_quantize
kimishpatel Nov 5, 2025
d40a03e
Update on "[Executorch] Add multithreading for op_quantize"
kimishpatel Nov 6, 2025
0a65b43
Update on "[Executorch] Add multithreading for op_quantize"
kimishpatel Nov 6, 2025
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122 changes: 88 additions & 34 deletions kernels/quantized/cpu/op_quantize.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
*/

#include <executorch/runtime/kernel/kernel_includes.h>
#include <executorch/runtime/kernel/thread_parallel_interface.h>
#include <algorithm>
#include <cinttypes>
#include <cmath>
Expand Down Expand Up @@ -461,51 +462,104 @@ Tensor& quantize_per_channel_out(
#if defined(__aarch64__) || defined(__ARM_NEON__)
if (input.scalar_type() == ScalarType::Float) {
const int64_t num_blocks = input.numel() / axis_block_size;
const int64_t total_elements = input.numel();
constexpr int64_t MIN_ELEMENTS_FOR_PARALLEL = 512;
const bool use_parallel = (total_elements >= MIN_ELEMENTS_FOR_PARALLEL);

if (dtype == ScalarType::Byte) {
auto* out_data_ptr = out.mutable_data_ptr<uint8_t>();
const auto* input_data_ptr = input.const_data_ptr<float>();

// Process each contiguous block (which shares the same scale/zero_point)
for (int64_t block = 0; block < num_blocks; ++block) {
int64_t channel_idx = block % axis_size;
float inv_scale = 1.0f / static_cast<float>(scale_data[channel_idx]);
int32_t zp = static_cast<int32_t>(zero_point_data[channel_idx]);

const float* in_ptr = input_data_ptr + block * axis_block_size;
uint8_t* out_ptr = out_data_ptr + block * axis_block_size;

quantize_arm<uint8_t>(
in_ptr,
out_ptr,
axis_block_size,
inv_scale,
zp,
static_cast<int32_t>(quant_min),
static_cast<int32_t>(quant_max));
if (use_parallel) {
::executorch::extension::parallel_for(
0, num_blocks, 1, [&](const int64_t begin, const int64_t end) {
for (int64_t block = begin; block < end; ++block) {
int64_t channel_idx = block % axis_size;
float inv_scale =
1.0f / static_cast<float>(scale_data[channel_idx]);
int32_t zp = static_cast<int32_t>(zero_point_data[channel_idx]);

const float* in_ptr = input_data_ptr + block * axis_block_size;
uint8_t* out_ptr = out_data_ptr + block * axis_block_size;

quantize_arm<uint8_t>(
in_ptr,
out_ptr,
axis_block_size,
inv_scale,
zp,
static_cast<int32_t>(quant_min),
static_cast<int32_t>(quant_max));
}
});
} else {
// Process each contiguous block (which shares the same
// scale/zero_point)
for (int64_t block = 0; block < num_blocks; ++block) {
int64_t channel_idx = block % axis_size;
float inv_scale = 1.0f / static_cast<float>(scale_data[channel_idx]);
int32_t zp = static_cast<int32_t>(zero_point_data[channel_idx]);

const float* in_ptr = input_data_ptr + block * axis_block_size;
uint8_t* out_ptr = out_data_ptr + block * axis_block_size;

quantize_arm<uint8_t>(
in_ptr,
out_ptr,
axis_block_size,
inv_scale,
zp,
static_cast<int32_t>(quant_min),
static_cast<int32_t>(quant_max));
}
}
return out;
} else if (dtype == ScalarType::Char) {
auto* out_data_ptr = out.mutable_data_ptr<int8_t>();
const auto* input_data_ptr = input.const_data_ptr<float>();

// Process each contiguous block (which shares the same scale/zero_point)
for (int64_t block = 0; block < num_blocks; ++block) {
int64_t channel_idx = block % axis_size;
float inv_scale = 1.0f / static_cast<float>(scale_data[channel_idx]);
int32_t zp = static_cast<int32_t>(zero_point_data[channel_idx]);

const float* in_ptr = input_data_ptr + block * axis_block_size;
int8_t* out_ptr = out_data_ptr + block * axis_block_size;

quantize_arm<int8_t>(
in_ptr,
out_ptr,
axis_block_size,
inv_scale,
zp,
static_cast<int32_t>(quant_min),
static_cast<int32_t>(quant_max));
if (use_parallel) {
::executorch::extension::parallel_for(
0, num_blocks, 1, [&](const int64_t begin, const int64_t end) {
for (int64_t block = begin; block < end; ++block) {
int64_t channel_idx = block % axis_size;
float inv_scale =
1.0f / static_cast<float>(scale_data[channel_idx]);
int32_t zp = static_cast<int32_t>(zero_point_data[channel_idx]);

const float* in_ptr = input_data_ptr + block * axis_block_size;
int8_t* out_ptr = out_data_ptr + block * axis_block_size;

quantize_arm<int8_t>(
in_ptr,
out_ptr,
axis_block_size,
inv_scale,
zp,
static_cast<int32_t>(quant_min),
static_cast<int32_t>(quant_max));
}
});
} else {
// Process each contiguous block (which shares the same
// scale/zero_point)
for (int64_t block = 0; block < num_blocks; ++block) {
int64_t channel_idx = block % axis_size;
float inv_scale = 1.0f / static_cast<float>(scale_data[channel_idx]);
int32_t zp = static_cast<int32_t>(zero_point_data[channel_idx]);

const float* in_ptr = input_data_ptr + block * axis_block_size;
int8_t* out_ptr = out_data_ptr + block * axis_block_size;

quantize_arm<int8_t>(
in_ptr,
out_ptr,
axis_block_size,
inv_scale,
zp,
static_cast<int32_t>(quant_min),
static_cast<int32_t>(quant_max));
}
}
return out;
}
Expand Down
3 changes: 3 additions & 0 deletions kernels/quantized/cpu/targets.bzl
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Original file line number Diff line number Diff line change
Expand Up @@ -52,6 +52,9 @@ _QUANT_OPS = (
),
op_target(
name = "op_quantize",
deps = [
"//executorch/extension/threadpool:threadpool",
],
),
)

Expand Down
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