/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. 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 "paddle/fluid/operators/nccl/nccl_gpu_common.h" #include "paddle/fluid/platform/gpu_info.h" namespace paddle { namespace platform { namespace { // TODO(panyx0718): Where to destroy them. std::unique_ptr> global_comms; std::unique_ptr> comm_id_map; bool inited = false; size_t last_num_gpus = -1; // TODO(panyx0718): Need to decide whether Paddle supports parallel // runs with different number GPUs. If true, current solution is not enough. std::mutex comm_mu; } int Communicator::GetCommId(int device_id) const { std::lock_guard guard(comm_mu); return comm_id_map->at(device_id); } void Communicator::InitAll(const std::vector& gpus) { std::lock_guard guard(comm_mu); if (inited && last_num_gpus == gpus.size()) { return; } last_num_gpus = gpus.size(); if (global_comms) { for (size_t i = 0; i < global_comms->size(); ++i) { // FIXME(dzh) : PADDLE_ENFORCE return void dynload::ncclCommDestroy((*global_comms)[i]); } } global_comms.reset(new std::vector()); comm_id_map.reset(new std::unordered_map()); global_comms->resize(gpus.size()); for (size_t i = 0; i < gpus.size(); ++i) { (*comm_id_map)[gpus[i]] = i; } PADDLE_ENFORCE( dynload::ncclCommInitAll(global_comms->data(), gpus.size(), gpus.data())); inited = true; } const std::vector& Communicator::comms() const { std::lock_guard guard(comm_mu); return *global_comms; } } // namespace platform } // namespace paddle