pytorch/caffe2/utils/threadpool/ThreadPool.cc
Yangqing Jia 8286ce1e3a Re-license to Apache
Summary: Closes https://github.com/caffe2/caffe2/pull/1260

Differential Revision: D5906739

Pulled By: Yangqing

fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
2017-09-28 16:22:00 -07:00

189 lines
5.6 KiB
C++

/**
* Copyright (c) 2016-present, Facebook, Inc.
*
* 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.
*/
#include "caffe2/utils/threadpool/ThreadPool.h"
#include "WorkersPool.h"
#include "caffe2/core/logging.h"
#if CAFFE2_ANDROID
#include <cpu-features.h>
#endif
CAFFE2_DEFINE_bool(caffe2_threadpool_force_inline, false,
"Force to always run jobs on the calling thread");
// Whether or not threadpool caps apply to Android
CAFFE2_DEFINE_int(caffe2_threadpool_android_cap, true, "");
// Whether or not threadpool caps apply to iOS
CAFFE2_DEFINE_int(caffe2_threadpool_ios_cap, false, "");
#if CAFFE2_THREADPOOL_MOBILE
namespace caffe2 {
// Default smallest amount of work that will be partitioned between
// multiple threads; the runtime value is configurable
#if CAFFE2_ANDROID
constexpr size_t kDefaultMinWorkSize = 8;
#else
constexpr size_t kDefaultMinWorkSize = 80;
#endif
std::unique_ptr<ThreadPool> ThreadPool::defaultThreadPool() {
int numThreads = std::thread::hardware_concurrency();
#ifdef CAFFE2_ANDROID
// std::thread::hardware_concurrency returns online cores
// (sysconf(_SC_NPROCESSORS_ONLN)), but we want the total number of CPUs. In
// most cases they will match, but since the threadpool is instantiated once,
// we want the number of threads for each device to be predictable.
int numCpus = android_getCpuCount();
LOG(INFO) << "Android cpu count: " << numCpus
<< ", hardware_concurrency: " << numThreads;
numThreads = numCpus;
#endif
bool applyCap = false;
#if CAFFE2_ANDROID
applyCap = caffe2::FLAGS_caffe2_threadpool_android_cap;
#elif CAFFE2_IOS
applyCap = caffe2::FLAGS_caffe2_threadpool_ios_cap;
#else
#error Undefined architecture
#endif
if (applyCap) {
switch (numThreads) {
#if CAFFE2_ANDROID && defined(__arm__)
case 4:
switch (android_getCpuIdArm() & UINT32_C(0xFF00FFF0)) {
case UINT32_C(0x51002110): /* Snapdragon 820 Kryo Silver */
case UINT32_C(0x51002010): /* Snapdragon 821 Kryo Silver */
case UINT32_C(0x51002050): /* Snapdragon 820/821 Kryo Gold */
/* Kryo: 2+2 big.LITTLE */
numThreads = 2;
break;
default:
/* Anything else: assume homogeneous architecture */
numThreads = 4;
break;
}
break;
#endif
case 5:
/* 4+1 big.LITTLE */
numThreads = 4;
break;
case 6:
/* 2+4 big.LITTLE */
numThreads = 2;
break;
case 8:
/* 4+4 big.LITTLE */
numThreads = 4;
break;
case 10:
/* 4+4+2 Min.Med.Max, running on Med cores */
numThreads = 4;
break;
default:
if (numThreads > 4) {
numThreads = numThreads / 2;
}
break;
}
}
LOG(INFO) << "Constructing thread pool with " << numThreads << " threads";
return caffe2::make_unique<ThreadPool>(numThreads);
}
ThreadPool::ThreadPool(int numThreads)
: minWorkSize_(kDefaultMinWorkSize), numThreads_(numThreads),
workersPool_(std::make_shared<WorkersPool>()) {}
ThreadPool::~ThreadPool() {}
int ThreadPool::getNumThreads() const {
std::lock_guard<std::mutex> guard(executionMutex_);
return numThreads_;
}
// Sets the minimum work size (range) for which to invoke the
// threadpool; work sizes smaller than this will just be run on the
// main (calling) thread
void ThreadPool::setMinWorkSize(size_t size) {
std::lock_guard<std::mutex> guard(executionMutex_);
minWorkSize_ = size;
}
void ThreadPool::run(const std::function<void(int, size_t)>& fn, size_t range) {
std::lock_guard<std::mutex> guard(executionMutex_);
// If there are no worker threads, or if the range is too small (too
// little work), just run locally
const bool runLocally = range < minWorkSize_ ||
FLAGS_caffe2_threadpool_force_inline ||
(numThreads_ == 0);
if (runLocally) {
// Work is small enough to just run locally; multithread overhead
// is too high
for (size_t i = 0; i < range; ++i) {
fn(0, i);
}
return;
}
struct FnTask : public Task {
FnTask(){};
virtual ~FnTask(){};
const std::function<void(int, size_t)> *fn_;
int idx_;
size_t start_;
size_t end_;
virtual void Run() override {
for (auto i = start_; i < end_; ++i) {
(*fn_)(idx_, i);
}
}
};
CAFFE_ENFORCE_GE(numThreads_, 1);
const size_t unitsPerTask = (range + numThreads_ - 1) / numThreads_;
tasks_.resize(numThreads_);
for (size_t i = 0; i < numThreads_; ++i) {
if (!tasks_[i]) {
tasks_[i].reset(new FnTask());
}
auto *task = (FnTask *)tasks_[i].get();
task->fn_ = &fn;
task->idx_ = i;
task->start_ = std::min<size_t>(range, i * unitsPerTask);
task->end_ = std::min<size_t>(range, (i + 1) * unitsPerTask);
if (task->start_ >= task->end_) {
tasks_.resize(i);
break;
}
CAFFE_ENFORCE_LE(task->start_, range);
CAFFE_ENFORCE_LE(task->end_, range);
}
CAFFE_ENFORCE_LE(tasks_.size(), numThreads_);
CAFFE_ENFORCE_GE(tasks_.size(), 1);
workersPool_->Execute(tasks_);
}
} // namespace caffe2
#endif // CAFFE2_THREADPOOL_MOBILE