Paddle/paddle/operators/nccl_op_test.cu

/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

   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. */

#define EIGEN_USE_GPU

#include <glog/logging.h>
#include <gtest/gtest.h>
#include <memory>
#include <mutex>
#include <thread>
#include <utility>
#include <vector>

#include "paddle/framework/block_desc.h"
#include "paddle/framework/op_desc.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/program_desc.h"
#include "paddle/framework/var_desc.h"
#include "paddle/operators/nccl/nccl_gpu_common.h"
#include "paddle/platform/device_context.h"
#include "paddle/platform/enforce.h"
#include "paddle/platform/gpu_info.h"
#include "paddle/platform/place.h"

USE_NO_KERNEL_OP(ncclInit);
USE_GPU_ONLY_OP(ncclAllReduce);
USE_GPU_ONLY_OP(ncclReduce);
USE_GPU_ONLY_OP(ncclBcastSend);
USE_GPU_ONLY_OP(ncclBcastRecv);

namespace f = paddle::framework;
namespace p = paddle::platform;

static std::vector<int> gpu_list;
static std::vector<std::unique_ptr<p::DeviceContext>> dev_ctxs;
std::mutex mu;

// test data amount
const f::DDim kDims = {100, 100};

// ncclInitOp with desc
TEST(NCCL, ncclInitOp) {
  std::unique_ptr<f::OpDescBind> op_desc(new f::OpDescBind);

  op_desc->SetType("ncclInit");
  op_desc->SetOutput("Communicator", {"x1"});
  op_desc->SetAttr("gpus", {gpu_list});
  f::Scope g_scope;
  p::DeviceContext *ctx = new p::CPUDeviceContext(p::CPUPlace());

  auto *var = g_scope.Var("x1");
  var->GetMutable<p::Communicator>();

  auto op = f::OpRegistry::CreateOp(*op_desc);
  VLOG(1) << "invoke NCCLInitOp.";
  op->Run(g_scope, *ctx);
  VLOG(1) << "NCCLInitOp finished.";
}

template <class T>
void DeviceProgram(int gpu_id, const f::OpDescBind &op_desc, f::Scope *scope) {
  std::unique_lock<std::mutex> lk(mu);
  f::ProgramDescBind program;
  f::BlockDescBind *block = program.Block(0);
  f::OpDescBind *op1 = block->AppendOp();
  *op1 = op_desc;

  p::GPUPlace place(gpu_id);
  auto ctx = dev_ctxs.at(gpu_id);

  auto *send_tensor = scope->Var("st")->GetMutable<f::LoDTensor>();
  auto *recv_tensor = scope->Var("rt")->GetMutable<f::LoDTensor>();
  send_tensor->Resize(kDims);
  send_tensor->mutable_data<T>(kDims, place);

  std::vector<T> send_vector(f::product(kDims), gpu_id);
  send_tensor->CopyFromVector<T>(send_vector, *ctx);
  lk.unlock();
  PADDLE_ENFORCE(send_tensor->numel() == f::product(kDims),
                 "Tensor numel not match!");
  ctx->Wait();

  VLOG(1) << "Send Tensor filled with elements " << send_tensor->numel();

  auto op = f::OpRegistry::CreateOp(*op1);
  VLOG(1) << "Device : " << gpu_id << " invoke " << op_desc.Type();
  op->Run(*scope, *ctx);
  VLOG(1) << "Device : " << gpu_id << " finished " << op_desc.Type();
}

// ncclAllReduceOp with desc
TEST(NCCL, ncclAllReduceOp) {
  std::unique_ptr<p::DeviceContext> ctx(new p::CPUDeviceContext(p::CPUPlace()));
  std::unique_ptr<f::Scope> g_scope(new Scope);

  std::unique_ptr<f::OpDescBind> op1(new f::OpDescBind);
  op1->SetType("ncclInit");
  op1->SetOutput("Communicator", {"comm"});
  op1->SetAttr("gpus", {gpu_list});

  auto *var = g_scope.Var("comm");
  var->GetMutable<p::Communicator>();

  auto op = f::OpRegistry::CreateOp(*op1);
  VLOG(1) << "invoke NCCLInitOp.";
  op->Run(g_scope, *ctx);
  VLOG(1) << "NCCLInitOp finished.";
  delete ctx;

  std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
  op2->SetType("ncclAllReduce");
  op2->SetInput("X", {"st"});
  op2->SetInput("Communicator", {"comm"});
  op2->SetOutput("Out", {"rt"});

  std::vector<std::thread> ths;
  for (size_t i = 0; i < gpu_list.size(); ++i) {
    std::thread th(DeviceProgram<float>, gpu_list[i], *op2,
                   &g_scope.NewScope());
    ths.emplace_back(std::move(th));
  }

  for (size_t i = 0; i < gpu_list.size(); ++i) {
    ths[i].join();
  }
  g_scope->reset(nullptr);
}

// ncclReduceOp with desc
TEST(NCCL, ncclReduceOp) {
  std::unique_ptr<p::DeviceContext> ctx(new p::CPUDeviceContext(p::CPUPlace()));
  std::unique_ptr<f::Scope> g_scope(new Scope);

  std::unique_ptr<f::OpDescBind> op1(new f::OpDescBind);
  op1->SetType("ncclInit");
  op1->SetOutput("Communicator", {"comm"});
  op1->SetAttr("gpus", {gpu_list});

  auto *var = g_scope.Var("comm");
  var->GetMutable<p::Communicator>();

  auto op = f::OpRegistry::CreateOp(*op1);
  VLOG(1) << "invoke NCCLInitOp.";
  op->Run(g_scope, *ctx);
  VLOG(1) << "NCCLInitOp finished.";
  delete ctx;

  std::unique_ptr<f::OpDescBind> op2(new f::OpDescBind);
  op2->SetType("ncclReduce");
  op2->SetInput("X", {"st"});
  op2->SetInput("Communicator", {"comm"});
  op2->SetOutput("Out", {"rt"});

  std::vector<std::thread> ths;
  for (size_t i = 0; i < gpu_list.size(); ++i) {
    std::thread th(DeviceProgram<float>, gpu_list[i], *op2,
                   &g_scope.NewScope());
    ths.emplace_back(std::move(th));
  }

  for (size_t i = 0; i < gpu_list.size(); ++i) {
    ths[i].join();
  }
  g_scope->reset(nullptr);
}

// ncclBcastOp with desc
TEST(NCCL, ncclBcastOp) {
  f::ProgramDescBind program;
  f::BlockDescBind *block = program.Block(0);
  f::OpDescBind *op1 = block->AppendOp();

  p::DeviceContext *ctx = new p::CPUDeviceContext(p::CPUPlace());

  op1->SetType("ncclInit");
  op1->SetOutput("Communicator", {"comm"});
  op1->SetAttr("gpus", {gpu_list});

  auto *var = g_scope.Var("comm");
  var->GetMutable<p::Communicator>();

  auto op = f::OpRegistry::CreateOp(*op1);
  VLOG(1) << "invoke NCCLInitOp.";
  op->Run(g_scope, *ctx);
  VLOG(1) << "NCCLInitOp finished.";

  f::OpDescBind *op2 = new f::OpDescBind;
  op2->SetType("ncclBcastSend");
  op2->SetInput("X", {"st"});
  op2->SetInput("Communicator", {"comm"});
  op2->SetOutput("Out", {"rt"});

  std::vector<std::thread> ths;
  for (size_t i = 0; i < gpu_list.size(); ++i) {
    std::thread th(DeviceProgram<float>, gpu_list[i], *op2);
    ths.emplace_back(std::move(th));
  }

  for (size_t i = 0; i < gpu_list.size(); ++i) {
    ths[i].join();
  }
}

int main(int argc, char **argv) {
  const int dev_count = p::GetCUDADeviceCount();
  if (dev_count <= 1) {
    LOG(WARNING)
        << "Cannot test multi-gpu nccl, because the CUDA device count is "
        << dev_count;
    return 0;
  }

  for (int i = 0; i < dev_count; ++i) {
    gpu_list.emplace_back(i);
  }
  testing::InitGoogleTest(&argc, argv);

  // device context should be release before scope.
  // otherwise driver will down.
  for (size_t i = 0; i < gpu_list.size(); ++i) {
    p::GPUPlace place(i);
    dev_ctxs.emplace_back(new p::CUDADeviceContext(place));
  }
  return RUN_ALL_TESTS();
}