Dong Zhihong
8 years ago
parent
fdfc8f9baa
commit
333045d7b2
@ -1,61 +1,17 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/operators/nccl/nccl_gpu_common.h"
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#include "paddle/operators/nccl/nccl_gpu_common.h"
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#include "paddle/platform/gpu_info.h"
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#include "paddle/platform/gpu_info.h"
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namespace paddle {
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namespace paddle {
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namespace platform {
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namespace platform {} // namespace platform
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NCCLManager::NCCLManager() {}
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NCCLManager::~NCCLManager() {
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for (auto& p : comm_table) {
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auto& comm = p.second;
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auto& gpus_ = comm->gpus_;
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for (size_t i = 0; i < gpus_.size(); ++i) {
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int gid = gpus_[i];
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platform::SetDeviceId(gid);
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// mapping gid to idx
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int idx = gid % gpus_.size();
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// wait finish
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PADDLE_ENFORCE(
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cudaStreamWaitEvent(comm->streams_[idx], comm->events_[idx], 0));
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PADDLE_ENFORCE(cudaEventDestroy(comm->events_[idx]));
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PADDLE_ENFORCE(ncclCommDestroy(comm->comms_[idx]));
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}
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comm.reset(nullptr);
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}
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}
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Communicator* NCCLManager::GetCommunicator(const std::vector<int>& gpus) {
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std::string key;
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for (auto& id : gpus) {
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key += std::to_string(id);
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}
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std::sort(key.begin(), key.end());
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std::mutex mu;
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std::lock_guard<std::mutex> lk(mu);
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auto it = comm_table.find(key);
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if (it->second == nullptr) {
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auto* comm = new Communicator(gpus);
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PADDLE_ENFORCE(
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ncclCommInitAll(comm->comms_.data(), gpus.size(), gpus.data()));
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for (size_t i = 0; i < gpus.size(); ++i) {
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platform::SetDeviceId(gpus[i]);
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// block wait
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PADDLE_ENFORCE(cudaEventCreateWithFlags(
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&comm->events_[i], cudaEventBlockingSync | cudaEventDisableTiming));
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}
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comm_table[key].reset(comm);
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}
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return comm_table[key].get();
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}
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} // namespace operators
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} // namespace paddle
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} // namespace paddle
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@ -1,16 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#define EIGEN_USE_GPU
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#include "paddle/operators/nccl/nccl_ops.h"
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namespace ops = paddle::operators;
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REGISTER_OP_GPU_KERNEL(ncclAllReduce, ops::NCCLAllReduceKernel<float>);
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@ -1,103 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/framework/op_registry.h"
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#include "paddle/operators/nccl/nccl_gpu_common.h"
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#include <string.h>
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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template <typename Type>
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class NCCLTypeWrapper;
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template <>
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class NCCLTypeWrapper<float> {
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public:
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static const ncclDataType_t type = ncclFloat;
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};
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template <>
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class NCCLTypeWrapper<double> {
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public:
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static const ncclDataType_t type = ncclDouble;
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};
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class NCCLInitOp : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto gpus = ctx.Input<std::vector<int>>("gpus");
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auto* comm = ctx.Output<Communicator>("Communicator");
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comm->mutable_data<Communicator>(CPUPlace());
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comm = NCCLManager::GetCommunicator(gpus);
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}
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};
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template <typename T>
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class NCCLAllReduceKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto ins = ctx.MultiInput<Tensor>("X");
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auto outs = ctx.MultiOutput<Tensor>("Out");
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std::string reduction = ctx.Attr<std::string>("reduction");
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std::vector<int> gpus = ctx.Attr<std::vector<int>>("gpus");
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ncclRedOp_t op_type;
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if (reduction == "ncclSum") {
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op_type = ncclSum;
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} else if (reduction == "ncclProd") {
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op_type = ncclProd;
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} else if (reduction == "ncclMin") {
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op_type = ncclMin;
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} else if (reduction == "ncclMax") {
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op_type = ncclMax;
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}
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auto* comm = ctx.Input<Communicator>("Communicator");
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auto dev_ctx =
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static_cast<const platform::CUDADeviceContext>(ctx.device_context());
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// platform::NCCLManager* m = platform::NCCLManager::Get();
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// auto* comm = m->GetCommunicator(gpus);
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// comm->wg_.Add(1);
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auto stream = dev_ctx.stream();
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// device id
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int gid = static_cast<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
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int idx = gid % gpus.size();
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comm->streams_[idx] = stream;
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for (size_t i = 0; i < ins.size(); ++i) {
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PADDLE_ENFORCE(
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ncclAllReduce(ins[i]->data<T>(), outs[i]->mutable_data<T>(),
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outs[i]->numel() * sizeof(T), NCCLTypeWrapper<T>::type,
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op_type, comm->comms_[idx], comm->streams_[idx]));
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PADDLE_ENFORCE(cudaEventRecord(comm->events_[idx], comm->streams_[idx]));
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// // wait finish
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// PADDLE_ENFORCE(
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// cudaStreamWaitEvent(comm->streams_[idx], comm->events_[idx], 0));
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}
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// comm->wg_.Done();
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// comm->wg_.Wait();
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}
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};
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} // namespace operators
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} // namespace paddle
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@ -0,0 +1,66 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#define EIGEN_USE_GPU
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#include "paddle/operators/nccl_op.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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class NCCLAllReduceKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
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"This kernel only runs on GPU device.");
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auto ins = ctx.MultiInput<Tensor>("X");
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auto outs = ctx.MultiOutput<Tensor>("Out");
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std::string reduction = ctx.Attr<std::string>("reduction");
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ncclRedOp_t op_type;
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if (reduction == "ncclSum") {
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op_type = ncclSum;
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} else if (reduction == "ncclProd") {
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op_type = ncclProd;
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} else if (reduction == "ncclMin") {
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op_type = ncclMin;
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} else if (reduction == "ncclMax") {
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op_type = ncclMax;
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} else {
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PADDLE_ENFORCE(false, "reduction error.");
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}
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auto* comm = ctx.Input<Communicator>("Communicator");
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auto stream = reinterpret_cast<const platform::CUDADeviceContext&>(
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ctx.device_context())
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.stream();
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// device id
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int device_id =
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boost::get<platform::GPUPlace>(ctx.GetPlace()).GetDeviceId();
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int idx = comm->GetCommId(device_id);
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for (size_t i = 0; i < ins.size(); ++i) {
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PADDLE_ENFORCE(ncclAllReduce(
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ins[i]->data<T>(), outs[i]->mutable_data<T>(ctx.GetPlace()),
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outs[i]->numel() * sizeof(T), NCCLTypeWrapper<T>::type, op_type,
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comm->comms_[idx], stream));
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PADDLE_ENFORCE(cudaStreamSynchronize(stream));
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}
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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REGISTER_OP_GPU_KERNEL(ncclAllReduce, ops::NCCLAllReduceKernel<float>);
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@ -0,0 +1,50 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/framework/op_registry.h"
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#include "paddle/operators/nccl/nccl_gpu_common.h"
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#include <string.h>
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namespace paddle {
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namespace operators {
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using framework::Tensor;
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using platform::Communicator;
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template <typename Type>
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class NCCLTypeWrapper;
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template <>
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class NCCLTypeWrapper<float> {
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public:
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static const ncclDataType_t type = ncclFloat;
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};
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template <>
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class NCCLTypeWrapper<double> {
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public:
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static const ncclDataType_t type = ncclDouble;
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};
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template <typename T>
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class NCCLInitKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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auto* gpus = ctx.Input<std::vector<int>>("gpus");
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auto* comm = ctx.Output<Communicator>("Communicator");
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comm->InitAll(*gpus);
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}
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};
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} // namespace operators
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} // namespace paddle
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