xref: /aosp_15_r20/external/pytorch/caffe2/utils/threadpool/ThreadPool.cc (revision da0073e96a02ea20f0ac840b70461e3646d07c45)

#include "caffe2/utils/threadpool/ThreadPool.h"
#include "WorkersPool.h"

#if !defined(__s390x__) && !defined(__powerpc__)
#include <cpuinfo.h>
#else
#include <thread>
#endif

C10_DEFINE_bool(
    caffe2_threadpool_force_inline,
    false,
    "Force to always run jobs on the calling thread");

// Whether or not threadpool caps apply to Android
C10_DEFINE_int(caffe2_threadpool_android_cap, true, "");

// Whether or not threadpool caps apply to iOS and MacOS
C10_DEFINE_int(caffe2_threadpool_ios_cap, true, "");
C10_DEFINE_int(caffe2_threadpool_macos_cap, true, "");

C10_DEFINE_int(pthreadpool_size, 0, "Override the default thread pool size.");

namespace caffe2 {

namespace {
  class ThreadPoolImpl : public ThreadPool {
  public:
    explicit ThreadPoolImpl(int numThreads);
    ~ThreadPoolImpl() override;

    // Returns the number of threads currently in use
    int getNumThreads() const override;
    void setNumThreads(size_t numThreads) override;

    void run(const std::function<void(int, size_t)>& fn, size_t range) override;
    void withPool(const std::function<void(WorkersPool*)>& f) override;

  private:
    std::atomic_size_t numThreads_;
    std::shared_ptr<WorkersPool> workersPool_;
    std::vector<std::shared_ptr<Task>> tasks_;
  };
}

size_t getDefaultNumThreads() {
#if !defined(__s390x__) && !defined(__powerpc__)
  auto numThreads = 1U;
  if (cpuinfo_initialize()) {
    numThreads = std::max(cpuinfo_get_processors_count(), 1U);
  } else {
    LOG(WARNING) << "cpuinfo initialization failed";
    numThreads = std::max(std::thread::hardware_concurrency(), 1U);
  }

  bool applyCap = false;
#if defined(C10_ANDROID)
  applyCap = FLAGS_caffe2_threadpool_android_cap;
#elif defined(C10_IOS)
  applyCap = FLAGS_caffe2_threadpool_ios_cap;
#elif defined(TARGET_OS_MAC)
  applyCap = FLAGS_caffe2_threadpool_macos_cap;
#endif

  if (applyCap) {
    switch (numThreads) {
#if defined(C10_ANDROID) && (CPUINFO_ARCH_ARM || CPUINFO_ARCH_ARM64)
      case 4:
        switch (cpuinfo_get_core(0)->midr & 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;
      // NOLINTNEXTLINE(cppcoreguidelines-avoid-magic-numbers,bugprone-branch-clone)
      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;
    }
  }
#else
  auto numThreads = std::max(std::thread::hardware_concurrency(), 1U);
#endif

  if (FLAGS_pthreadpool_size) {
    // Always give precedence to explicit setting.
    numThreads = FLAGS_pthreadpool_size;
  }

  /*
   * For llvm-tsan, holding limit for the number of locks for a single thread
   * is 63 (because of comparison < 64 instead of <=). pthreadpool's worst
   * case is the number of threads in a pool. So we want to limit the threadpool
   * size to 64 when running with tsan. However, sometimes it is tricky to
   * detect if we are running under tsan, for now capping the default
   * threadcount to the tsan limit unconditionally.
   */
  auto tsanThreadLimit = 63U;
  numThreads = std::min(numThreads, tsanThreadLimit);

  return numThreads;
}

// Default smallest amount of work that will be partitioned between
// multiple threads; the runtime value is configurable
constexpr size_t kDefaultMinWorkSize = 1;

size_t ThreadPool::defaultNumThreads_ = 0;

ThreadPool* ThreadPool::createThreadPool(int numThreads) {
  return new ThreadPoolImpl(numThreads);
}

std::unique_ptr<ThreadPool> ThreadPool::defaultThreadPool() {
  defaultNumThreads_ = getDefaultNumThreads();
  LOG(INFO) << "Constructing thread pool with " << defaultNumThreads_
            << " threads";
  return std::make_unique<ThreadPoolImpl>(defaultNumThreads_);
}

ThreadPoolImpl::ThreadPoolImpl(int numThreads)
    : numThreads_(numThreads),
      workersPool_(std::make_shared<WorkersPool>()) {
  minWorkSize_ = kDefaultMinWorkSize;
}

// NOLINTNEXTLINE(modernize-use-equals-default)
ThreadPoolImpl::~ThreadPoolImpl() {}

int ThreadPoolImpl::getNumThreads() const {
  return numThreads_;
}

// Sets the number of threads
// # of threads should not be bigger than the number of big cores
void ThreadPoolImpl::setNumThreads(size_t numThreads) {
  if (defaultNumThreads_ == 0) {
    defaultNumThreads_ = getDefaultNumThreads();
  }
  numThreads_ = std::min(numThreads, defaultNumThreads_);
}

void ThreadPoolImpl::run(const std::function<void(int, size_t)>& fn, size_t range) {
  const auto numThreads = numThreads_.load(std::memory_order_relaxed);

  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 {
    // NOLINTNEXTLINE(modernize-use-equals-default,cppcoreguidelines-pro-type-member-init)
    FnTask(){};
    // NOLINTNEXTLINE(modernize-use-equals-default)
    ~FnTask() override{};
    const std::function<void(int, size_t)>* fn_;
    int idx_;
    size_t start_;
    size_t end_;
    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]) {
      // NOLINTNEXTLINE(modernize-make-shared)
      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_);
}

void ThreadPoolImpl::withPool(const std::function<void(WorkersPool*)>& f) {
  std::lock_guard<std::mutex> guard(executionMutex_);
  f(workersPool_.get());
}

} // namespace caffe2