nccl_gpu_common.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 <algorithm>
#include <condition_variable>
#include <memory>
#include <mutex>
#include <string>
#include <unordered_map>
#include <vector>

#include "paddle/platform/device_context.h"
#include "paddle/platform/enforce.h"

namespace paddle {
namespace platform {

class WaitGroup {
 public:
  inline void Add(int n) {
    std::unique_lock<std::mutex> lk(mu_);
    PADDLE_ENFORCE(n >= 0, "add wait must >=0.");
    counter_ += n;
  }

  inline void Done(int n) {
    std::unique_lock<std::mutex> lk(mu_);
    PADDLE_ENFORCE(n <= counter_, " wait group done unmatch to add.");
    counter_ -= n;
    if (counter_ == 0) {
      cv_.notify_all();
    }
  }

  inline void Add() { Add(1); }

  inline void Done() { Done(1); }

  inline void Wait() {
    std::unique_lock<std::mutex> lk(mu_);
    cv_.wait(lk, [&] { return counter_ == 0; });
  }

  inline int GetCount() {
    std::unique_lock<std::mutex> lk(mu_);
    return counter_;
  }

 private:
  int counter_ = 0;
  std::mutex mu_;
  std::condition_variable cv_;
};

// class NCCLContext : public DeviceContext {
// public:
//   explicit NCCLContext(GPUPlace place);
//   virtual ~NCCLContext();

// private:
//   std::vector<int> gpu_ids_;
//   std::vector<cudaStream_t> streams_;
// };

// TODO(dzh) : make resources managed unified with framework
struct Communicator {
  std::vector<ncclComm_t> comms_;
  std::vector<cudaStream_t*> streams_;
  std::vector<cudaEvent_t> events_;
  std::vector<int> gpus_;
  WaitGroup wg_;
  int root_gpu = -1;
  // cudaEvent_t root_monitor;
  explicit Communicator(const std::vector<int>& gpus) : gpus_(gpus) {
    comms_.resize(gpus.size());
    streams_.resize(gpus.size());
    events_.resize(gpus.size());
  }
  // Communicator(int num_device): comms_.resize(num_device) {}

  inline int get_root_gpu() const { return root_gpu; }

  inline void set_root_gpu(int id) { root_gpu = id; }
};

class NCCLManager {
 public:
  static NCCLManager* Get() {
    static NCCLManager m;
    return &m;
  }

  NCCLManager();

  ~NCCLManager();

  // for each card only have one communicator
  Communicator* GetCommunicator(const std::vector<int>& gpus);

 private:
  // // the gpu id list available. Note that only support
  // // whole world communication.
  // std::vector<int> _gpu_worlds;

  // communicator list
  std::unordered_map<std::string /* key*/, std::unique_ptr<Communicator>>
      comm_table;
};

}  // namespace platform
}  // namespace paddle