/* Copyright (c) 2021 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/collective/partial_recv_op.h" #if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL) #include "paddle/fluid/distributed/collective/process_group.h" #include "paddle/fluid/platform/collective_helper.h" #include "paddle/fluid/platform/device/gpu/nccl_helper.h" #endif namespace paddle { namespace operators { template class PartialRecvOpCUDAKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext &ctx) const override { #if (defined(PADDLE_WITH_RCCL) || defined(PADDLE_WITH_NCCL)) && \ NCCL_VERSION_CODE >= 2703 auto out = ctx.Output("Out"); auto out_dims = out->dims(); auto numel = out->numel(); int rid = ctx.Attr("ring_id"); int peer = ctx.Attr("peer"); int data_type = ctx.Attr("dtype"); int num = ctx.Attr("num"); int id = ctx.Attr("id"); framework::proto::VarType::Type type = framework::proto::VarType::Type(data_type); PADDLE_ENFORCE_GE( rid, 0, platform::errors::InvalidArgument( "The ring_id (%d) for partial_recv op must be non-negative.", rid)); PADDLE_ENFORCE_GE( peer, 0, platform::errors::InvalidArgument( "The peer (%d) for partial_recv op must be non-negative.", peer)); PADDLE_ENFORCE_GE(num, 1, platform::errors::InvalidArgument( "The num (%d) for partial_recv op must >=1", num)); PADDLE_ENFORCE_EQ( (id >= 0 && id < num), true, platform::errors::InvalidArgument( "The id (%d) for partial_recv op must >=0 and mutable_data(out_dims, place); int recv_numel = numel / num; int offset = recv_numel * id; auto map = distributed::ProcessGroupMapFromGid::getInstance(); if (map->has(rid)) { // Use ProcessGroup distributed::ProcessGroup *pg = map->get(rid); auto task = pg->Recv(out, peer, offset, recv_numel, /*sync_op*/ true); task->Wait(); } else { gpuStream_t stream = nullptr; auto comm = platform::NCCLCommContext::Instance().Get(rid, place); if (ctx.Attr("use_calc_stream")) { // should ExecutionContext for calc stream. stream = ctx.cuda_device_context().stream(); } else { stream = comm->stream(); } PADDLE_ENFORCE_LT(peer, comm->nranks(), platform::errors::InvalidArgument( "The value of peer (%d) you set must " "be less than comm->nranks (%d).", peer, comm->nranks())); ncclDataType_t dtype = platform::ToNCCLDataType(type); PADDLE_ENFORCE_GPU_SUCCESS( platform::dynload::ncclRecv(out->data() + offset, recv_numel, dtype, peer, comm->comm(), stream)); VLOG(3) << "rank " << comm->rank() << " recv " << recv_numel << " from offset[" << offset << "] from " << peer; } #else PADDLE_THROW(platform::errors::Unavailable( "PaddlePaddle should be compiled with NCCL and " "NCCL version >= 2.7.3 is needed.")); #endif } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL(partial_recv, ops::PartialRecvOpCUDAKernel, ops::PartialRecvOpCUDAKernel, ops::PartialRecvOpCUDAKernel, ops::PartialRecvOpCUDAKernel, ops::PartialRecvOpCUDAKernel);