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// Copyright 2015 The Gemmlowp Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
// multi_thread_common.h: Multithreading code shared by different meta gemm
// versions.
#ifndef GEMMLOWP_META_MULTI_THREAD_COMMON_H_
#define GEMMLOWP_META_MULTI_THREAD_COMMON_H_
#include "../internal/multi_thread_gemm.h"
namespace gemmlowp {
namespace meta {
namespace internal {
const std::int32_t kMinTaskSize = 16000;
const std::int32_t kMinTaskDimension = 4;
struct TaskRect {
std::int32_t m_offset;
std::int32_t m;
std::int32_t n_offset;
std::int32_t n;
TaskRect(std::int32_t m_offset, std::int32_t m, std::int32_t n_offset,
std::int32_t n)
: m_offset(m_offset), m(m), n_offset(n_offset), n(n) {}
};
template <typename IN_TYPE, typename OUT_TYPE, typename F>
struct MetaTask : gemmlowp::Task {
std::uint8_t* scratch;
const IN_TYPE* lhs;
const IN_TYPE* rhs;
TaskRect task_rect;
std::int32_t k;
OUT_TYPE* result;
std::int32_t result_stride;
const F& operation;
MetaTask(std::uint8_t* scratch, const IN_TYPE* lhs, const IN_TYPE* rhs,
const TaskRect& task_rect, std::int32_t k, OUT_TYPE* result,
std::int32_t result_stride, const F& operation)
: scratch(scratch),
lhs(lhs),
rhs(rhs),
task_rect(task_rect),
k(k),
result(result),
result_stride(result_stride),
operation(operation) {}
void Run() override {
const IN_TYPE* task_lhs = lhs + task_rect.m_offset * k;
const IN_TYPE* task_rhs = rhs + task_rect.n_offset * k;
OUT_TYPE* task_result =
result + task_rect.m_offset * result_stride + task_rect.n_offset;
operation.ExecuteMatrixMatrix(scratch, task_lhs, task_rhs, task_rect.m,
task_rect.n, k, task_result, result_stride);
}
};
std::int32_t ResolveMaxThreads(std::int32_t max_threads) {
if (max_threads == 0) {
static const int hardware_threads_count =
static_cast<int>(sysconf(_SC_NPROCESSORS_CONF));
return hardware_threads_count;
}
return max_threads;
}
void PrepareTasks(std::int32_t max_tasks, std::int32_t m, std::int32_t n,
std::int32_t k, std::vector<internal::TaskRect>* tasks) {
const std::int32_t max_tasks_by_size = (m * n * k) / kMinTaskSize;
const std::int32_t max_tasks_m = m / kMinTaskDimension;
const std::int32_t max_tasks_n = n / kMinTaskDimension;
const std::int32_t max_tasks_dimension = std::max(max_tasks_m, max_tasks_n);
std::int32_t real_tasks = std::max(
1, std::min(max_tasks, std::min(max_tasks_by_size, max_tasks_dimension)));
if (real_tasks == 1) {
tasks->push_back(TaskRect(0, m, 0, n));
return;
}
if (max_tasks_m > max_tasks_n) {
const std::int32_t m_chunk = m / real_tasks;
for (int i = 0; i < real_tasks - 1; ++i) {
tasks->push_back(TaskRect(i * m_chunk, m_chunk, 0, n));
}
const std::int32_t last_m_offset = (real_tasks - 1) * m_chunk;
tasks->push_back(TaskRect(last_m_offset, m - last_m_offset, 0, n));
} else {
const std::int32_t n_chunk = n / real_tasks;
for (int i = 0; i < real_tasks - 1; ++i) {
tasks->push_back(TaskRect(0, m, i * n_chunk, n_chunk));
}
const std::int32_t last_n_offset = (real_tasks - 1) * n_chunk;
tasks->push_back(TaskRect(0, m, last_n_offset, n - last_n_offset));
}
}
template <typename IN_TYPE, typename OUT_TYPE, typename F>
void MultiThreadedMatrixMatrix(gemmlowp::WorkersPool* pool,
std::int32_t max_threads, std::uint8_t* scratch,
const IN_TYPE* lhs, const IN_TYPE* rhs,
std::int32_t m, std::int32_t n, std::int32_t k,
OUT_TYPE* result, std::int32_t result_stride,
const F& operation) {
max_threads = internal::ResolveMaxThreads(max_threads);
std::vector<internal::TaskRect> task_rects;
internal::PrepareTasks(max_threads, m, n, k, &task_rects);
if (task_rects.size() == 1) {
operation.ExecuteMatrixMatrix(scratch, lhs, rhs, m, n, k, result,
result_stride);
return;
}
std::uint8_t* task_scratch = scratch;
std::int32_t scratch_per_thread = operation.ScratchPerThread(m, n, k);
std::vector<Task*> tasks;
std::for_each(
task_rects.begin(), task_rects.end(),
[&tasks, &task_scratch, lhs, rhs, k, result, result_stride, operation,
scratch_per_thread](internal::TaskRect& rect) {
tasks.push_back(new internal::MetaTask<IN_TYPE, OUT_TYPE, F>(
task_scratch, lhs, rhs, rect, k, result, result_stride, operation));
task_scratch += scratch_per_thread;
});
pool->Execute(tasks);
}
} // namespace internal
} // namespace meta
} // namespace gemmlowp
#endif // GEMMLOWP_META_MULTI_THREAD_COMMON_H_
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