// Copyright (c) 2019 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/framework/fleet/nccl_wrapper.h" #include #include "paddle/fluid/framework/data_feed.h" #include "paddle/fluid/framework/scope.h" namespace paddle { namespace framework { std::shared_ptr NCCLWrapper::s_instance_ = NULL; bool NCCLWrapper::is_initialized_ = false; void NCCLWrapper::InitNCCL() { #if defined(PADDLE_WITH_NCCL) PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclCommInitRank( &(nccl_info_.comm_), nccl_info_.global_ranks_, nccl_info_.nccl_id_, nccl_info_.my_global_rank_)); #endif return; } void NCCLWrapper::SetNCCLId(const NCCLInfo& nccl_info) { #if defined(PADDLE_WITH_NCCL) nccl_info_.nccl_id_ = nccl_info.nccl_id_; #endif return; } NCCLInfo NCCLWrapper::GetNCCLId() { #if defined(PADDLE_WITH_NCCL) PADDLE_ENFORCE_CUDA_SUCCESS( platform::dynload::ncclGetUniqueId(&(nccl_info_.nccl_id_))); #endif return nccl_info_; } void NCCLWrapper::SetRankInfo(const int local_rank, const int global_rank, const int ranks) { #if defined(PADDLE_WITH_NCCL) nccl_info_.local_rank_ = local_rank; nccl_info_.my_global_rank_ = global_rank; nccl_info_.global_ranks_ = ranks; PADDLE_ENFORCE_CUDA_SUCCESS(cudaSetDevice(local_rank)); PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamCreate(&(nccl_info_.stream_))); #endif return; } void NCCLWrapper::SyncVar(const int root_rank, const Scope& scope, const std::vector& var_names) { #if defined(PADDLE_WITH_NCCL) for (auto& name : var_names) { auto var = scope.FindVar(name); LoDTensor* tensor = var->GetMutable(); int32_t total_size = tensor->numel(); PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclBcast( reinterpret_cast(tensor->data()), total_size, ncclFloat, root_rank, nccl_info_.comm_, nccl_info_.stream_)); cudaStreamSynchronize(nccl_info_.stream_); } #endif return; } } // end namespace framework } // end namespace paddle