profiler.h

/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

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. */

#pragma once
#include <forward_list>
#include <list>
#include <mutex>
#include <vector>
#include "paddle/platform/device_context.h"

namespace paddle {
namespace platform {

enum EventKind { kMark, kPushRange, kPopRange };

class Event {
 public:
  // The DeviceContext is used to get the cuda stream.
  // If CPU profiling mode, can pass nullptr.
  Event(EventKind kind, std::string name, uint32_t thread_id,
        DeviceContext* dev_ctx);

  std::string kind() const;
  std::string name() const { return name_; }
  bool has_cuda() const { return has_cuda_; }

#ifdef PADDLE_WITH_CUDA
  cudaEvent_t event() const { return event_; }
  int device() const { return device_; }
#endif

  double CpuElapsedUs(const Event& e) const;
  double CudaElapsedUs(const Event& e) const;

 private:
  EventKind kind_;
  std::string name_;
  uint32_t thread_id_;
  int64_t cpu_ns_;
  bool has_cuda_;
#ifdef PADDLE_WITH_CUDA
  cudaEvent_t event_ = nullptr;
  int device_ = -1;
#endif
};

struct EventList {
  constexpr static size_t kMB = 1024 * 1024;
  constexpr static size_t kEventBlockSize = 16 * kMB;
  constexpr static size_t kEventSize = sizeof(Event);
  constexpr static size_t kEventAlign = alignof(Event);
  constexpr static size_t kNumBlock =
      kEventBlockSize /
      ((kEventSize + kEventAlign - 1) / kEventAlign * kEventAlign);

  template <typename... Args>
  void Record(Args&&... args) {
    if (event_blocks.empty() || event_blocks.front().size() == kNumBlock) {
      event_blocks.emplace_front();
      event_blocks.front().reserve(kNumBlock);
    }
    event_blocks.front().emplace_back(std::forward<Args>(args)...);
  }

  std::vector<Event> Reduce() {
    std::vector<Event> result;
    for (auto& block : event_blocks) {
      result.insert(result.begin(), std::make_move_iterator(block.begin()),
                    std::make_move_iterator(block.end()));
    }
    event_blocks.clear();
    return result;
  }

  std::forward_list<std::vector<Event>> event_blocks;
};

enum ProfilerState {
  kDisabled,  // disabled state
  kCPU,       // CPU profiling state
  kCUDA,      // GPU profiling state
};

void Mark(const std::string& name, DeviceContext* dev_ctx);

void PushEvent(const std::string& name, DeviceContext* dev_ctx);

void PopEvent(const std::string& name, DeviceContext* dev_ctx);

struct RecordEvent {
  explicit RecordEvent(const std::string& name, DeviceContext* dev_ctx);

  ~RecordEvent();

  // The device context is used by Event to get the current cuda stream.
  DeviceContext* dev_ctx_;
  // Event name
  std::string name_;
};

// Enable the profiling function.
void EnableProfiler(ProfilerState state);

// Return the event list of all threads. Asummed the returned value calls
// event_lists, event_lists[i][j] represents the j-th Event of i-th thread.
std::vector<std::vector<Event>> DisableProfiler();

void ParseEvents(std::vector<std::vector<Event>>&);

}  // namespace platform
}  // namespace paddle