/* 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/operators/collective/c_gather_op.h" #if defined(PADDLE_WITH_NCCL) #include "paddle/fluid/platform/collective_helper.h" #include "paddle/fluid/platform/nccl_helper.h" #endif namespace paddle { namespace operators { template class CGatherOpCUDAKernel : public framework::OpKernel { public: void Compute(const framework::ExecutionContext& ctx) const override { #if defined(PADDLE_WITH_NCCL) auto x = ctx.Input("X"); auto out = ctx.Output("Out"); int send_numel = x->numel(); ncclDataType_t dtype = platform::ToNCCLDataType(x->type()); int nranks = ctx.Attr("nranks"); int root_id = ctx.Attr("root"); int ring_id = ctx.Attr("ring_id"); auto place = ctx.GetPlace(); auto comm = platform::NCCLCommContext::Instance().Get(ring_id, place); PADDLE_ENFORCE_EQ(nranks, comm->nranks(), platform::errors::InvalidArgument( "The number of ranks (%d) you set of must " "be equal to comm->nranks (%d).", nranks, comm->nranks())); PADDLE_ENFORCE_GE( root_id, 0, platform::errors::InvalidArgument( "The root_id (%d) for c_scatter_op must be non-negative.", root_id)); PADDLE_ENFORCE_GE( ring_id, 0, platform::errors::InvalidArgument( "The ring_id (%d) for c_scatter_op must be non-negative.", ring_id)); cudaStream_t stream = nullptr; if (ctx.Attr("use_calc_stream")) { auto dev_ctx = platform::DeviceContextPool::Instance().Get(place); stream = static_cast(dev_ctx)->stream(); } else { stream = comm->stream(); } framework::DDim x_dims = x->dims(); framework::DDim out_dims(x_dims); out_dims[0] *= nranks; auto send_buf = x->data(); auto offset = 0; PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupStart()); PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclSend( send_buf, send_numel, dtype, root_id, comm->comm(), stream)); if (root_id == comm->rank()) { auto recv_buf = out->mutable_data(out_dims, place); for (auto i = 0; i < nranks; ++i) { PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclRecv( recv_buf + offset, send_numel, dtype, i, comm->comm(), stream)); offset += send_numel; } } PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclGroupEnd()); #else PADDLE_ENFORCE_EQ( true, false, platform::errors::Unavailable("PaddlePaddle should compile with GPU.")); #endif } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; namespace plat = paddle::platform; REGISTER_OP_CUDA_KERNEL(c_gather, ops::CGatherOpCUDAKernel, ops::CGatherOpCUDAKernel, ops::CGatherOpCUDAKernel, ops::CGatherOpCUDAKernel, ops::CGatherOpCUDAKernel);