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Fixes #ISSUE_NUMBER Pull Request resolved: https://github.com/pytorch/pytorch/pull/139605 Approved by: https://github.com/ezyang
229 lines
6.7 KiB
C++
229 lines
6.7 KiB
C++
#include "caffe2/utils/threadpool/ThreadPool.h"
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#include "WorkersPool.h"
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#if !defined(__s390x__) && !defined(__powerpc__)
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#include <cpuinfo.h>
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#else
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#include <thread>
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#endif
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C10_DEFINE_bool(
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caffe2_threadpool_force_inline,
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false,
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"Force to always run jobs on the calling thread")
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// Whether or not threadpool caps apply to Android
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C10_DEFINE_int(caffe2_threadpool_android_cap, true, "")
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// Whether or not threadpool caps apply to iOS and MacOS
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C10_DEFINE_int(caffe2_threadpool_ios_cap, true, "")
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C10_DEFINE_int(caffe2_threadpool_macos_cap, true, "")
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C10_DEFINE_int(pthreadpool_size, 0, "Override the default thread pool size.")
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namespace caffe2 {
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namespace {
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class ThreadPoolImpl : public ThreadPool {
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public:
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explicit ThreadPoolImpl(int numThreads);
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~ThreadPoolImpl() override;
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// Returns the number of threads currently in use
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int getNumThreads() const override;
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void setNumThreads(size_t numThreads) override;
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void run(const std::function<void(int, size_t)>& fn, size_t range) override;
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void withPool(const std::function<void(WorkersPool*)>& f) override;
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private:
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std::atomic_size_t numThreads_;
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std::shared_ptr<WorkersPool> workersPool_;
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std::vector<std::shared_ptr<Task>> tasks_;
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};
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}
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size_t getDefaultNumThreads() {
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#if !defined(__s390x__) && !defined(__powerpc__)
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auto numThreads = 1U;
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if (cpuinfo_initialize()) {
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numThreads = std::max(cpuinfo_get_processors_count(), 1U);
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} else {
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LOG(WARNING) << "cpuinfo initialization failed";
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numThreads = std::max(std::thread::hardware_concurrency(), 1U);
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}
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bool applyCap = false;
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#if defined(C10_ANDROID)
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applyCap = FLAGS_caffe2_threadpool_android_cap;
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#elif defined(C10_IOS)
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applyCap = FLAGS_caffe2_threadpool_ios_cap;
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#elif defined(TARGET_OS_MAC)
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applyCap = FLAGS_caffe2_threadpool_macos_cap;
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#endif
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if (applyCap) {
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switch (numThreads) {
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#if defined(C10_ANDROID) && (CPUINFO_ARCH_ARM || CPUINFO_ARCH_ARM64)
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case 4:
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switch (cpuinfo_get_core(0)->midr & UINT32_C(0xFF00FFF0)) {
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case UINT32_C(0x51002110): /* Snapdragon 820 Kryo Silver */
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case UINT32_C(0x51002010): /* Snapdragon 821 Kryo Silver */
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case UINT32_C(0x51002050): /* Snapdragon 820/821 Kryo Gold */
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/* Kryo: 2+2 big.LITTLE */
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numThreads = 2;
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break;
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default:
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/* Anything else: assume homogeneous architecture */
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numThreads = 4;
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break;
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}
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break;
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#endif
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case 5:
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/* 4+1 big.LITTLE */
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numThreads = 4;
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break;
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case 6:
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/* 2+4 big.LITTLE */
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numThreads = 2;
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break;
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// NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers,bugprone-branch-clone)
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case 8:
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/* 4+4 big.LITTLE */
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numThreads = 4;
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break;
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case 10:
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/* 4+4+2 Min.Med.Max, running on Med cores */
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numThreads = 4;
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break;
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default:
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if (numThreads > 4) {
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numThreads = numThreads / 2;
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}
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break;
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}
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}
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#else
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auto numThreads = std::max(std::thread::hardware_concurrency(), 1U);
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#endif
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if (FLAGS_pthreadpool_size) {
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// Always give precedence to explicit setting.
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numThreads = FLAGS_pthreadpool_size;
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}
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/*
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* For llvm-tsan, holding limit for the number of locks for a single thread
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* is 63 (because of comparison < 64 instead of <=). pthreadpool's worst
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* case is the number of threads in a pool. So we want to limit the threadpool
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* size to 64 when running with tsan. However, sometimes it is tricky to
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* detect if we are running under tsan, for now capping the default
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* threadcount to the tsan limit unconditionally.
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*/
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auto tsanThreadLimit = 63U;
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numThreads = std::min(numThreads, tsanThreadLimit);
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return numThreads;
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}
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// Default smallest amount of work that will be partitioned between
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// multiple threads; the runtime value is configurable
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constexpr size_t kDefaultMinWorkSize = 1;
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size_t ThreadPool::defaultNumThreads_ = 0;
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ThreadPool* ThreadPool::createThreadPool(int numThreads) {
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return new ThreadPoolImpl(numThreads);
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}
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std::unique_ptr<ThreadPool> ThreadPool::defaultThreadPool() {
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defaultNumThreads_ = getDefaultNumThreads();
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LOG(INFO) << "Constructing thread pool with " << defaultNumThreads_
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<< " threads";
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return std::make_unique<ThreadPoolImpl>(defaultNumThreads_);
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}
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ThreadPoolImpl::ThreadPoolImpl(int numThreads)
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: numThreads_(numThreads),
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workersPool_(std::make_shared<WorkersPool>()) {
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minWorkSize_ = kDefaultMinWorkSize;
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}
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// NOLINTNEXTLINE(modernize-use-equals-default)
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ThreadPoolImpl::~ThreadPoolImpl() {}
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int ThreadPoolImpl::getNumThreads() const {
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return numThreads_;
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}
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// Sets the number of threads
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// # of threads should not be bigger than the number of big cores
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void ThreadPoolImpl::setNumThreads(size_t numThreads) {
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if (defaultNumThreads_ == 0) {
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defaultNumThreads_ = getDefaultNumThreads();
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}
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numThreads_ = std::min(numThreads, defaultNumThreads_);
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}
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void ThreadPoolImpl::run(const std::function<void(int, size_t)>& fn, size_t range) {
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const auto numThreads = numThreads_.load(std::memory_order_relaxed);
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std::lock_guard<std::mutex> guard(executionMutex_);
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// If there are no worker threads, or if the range is too small (too
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// little work), just run locally
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const bool runLocally = range < minWorkSize_ ||
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FLAGS_caffe2_threadpool_force_inline || (numThreads == 0);
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if (runLocally) {
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// Work is small enough to just run locally; multithread overhead
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// is too high
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for (size_t i = 0; i < range; ++i) {
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fn(0, i);
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}
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return;
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}
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struct FnTask : public Task {
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const std::function<void(int, size_t)>* fn_{};
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int idx_{};
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size_t start_{};
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size_t end_{};
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void Run() override {
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for (auto i = start_; i < end_; ++i) {
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(*fn_)(idx_, i);
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}
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}
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};
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CAFFE_ENFORCE_GE(numThreads_, 1);
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const size_t unitsPerTask = (range + numThreads - 1) / numThreads;
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tasks_.resize(numThreads);
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for (size_t i = 0; i < numThreads; ++i) {
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if (!tasks_[i]) {
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// NOLINTNEXTLINE(modernize-make-shared)
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tasks_[i].reset(new FnTask());
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}
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auto* task = (FnTask*)tasks_[i].get();
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task->fn_ = &fn;
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task->idx_ = i;
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task->start_ = std::min<size_t>(range, i * unitsPerTask);
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task->end_ = std::min<size_t>(range, (i + 1) * unitsPerTask);
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if (task->start_ >= task->end_) {
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tasks_.resize(i);
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break;
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}
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CAFFE_ENFORCE_LE(task->start_, range);
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CAFFE_ENFORCE_LE(task->end_, range);
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}
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CAFFE_ENFORCE_LE(tasks_.size(), numThreads);
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CAFFE_ENFORCE_GE(tasks_.size(), 1);
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workersPool_->Execute(tasks_);
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}
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void ThreadPoolImpl::withPool(const std::function<void(WorkersPool*)>& f) {
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std::lock_guard<std::mutex> guard(executionMutex_);
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f(workersPool_.get());
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}
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} // namespace caffe2
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