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76 lines
2.2 KiB
76 lines
2.2 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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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 <cuda_runtime.h>
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#include <memory>
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/mixed_vector.h"
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#include "paddle/fluid/platform/gpu_info.h"
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template <typename T>
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using vec = paddle::framework::Vector<T>;
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static __global__ void multiply_10(int* ptr) {
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for (int i = 0; i < 10; ++i) {
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ptr[i] *= 10;
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}
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}
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cudaStream_t GetCUDAStream(paddle::platform::CUDAPlace place) {
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return reinterpret_cast<const paddle::platform::CUDADeviceContext*>(
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paddle::platform::DeviceContextPool::Instance().Get(place))
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->stream();
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}
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TEST(mixed_vector, GPU_VECTOR) {
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vec<int> tmp;
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for (int i = 0; i < 10; ++i) {
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tmp.push_back(i);
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}
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ASSERT_EQ(tmp.size(), 10UL);
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paddle::platform::CUDAPlace gpu(0);
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multiply_10<<<1, 1, 0, GetCUDAStream(gpu)>>>(tmp.MutableData(gpu));
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for (int i = 0; i < 10; ++i) {
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ASSERT_EQ(tmp[i], i * 10);
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}
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}
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TEST(mixed_vector, MultiGPU) {
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if (paddle::platform::GetCUDADeviceCount() < 2) {
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LOG(WARNING) << "Skip mixed_vector.MultiGPU since there are not multiple "
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"GPUs in your machine.";
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return;
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}
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vec<int> tmp;
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for (int i = 0; i < 10; ++i) {
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tmp.push_back(i);
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}
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ASSERT_EQ(tmp.size(), 10UL);
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paddle::platform::CUDAPlace gpu0(0);
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paddle::platform::SetDeviceId(0);
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multiply_10<<<1, 1, 0, GetCUDAStream(gpu0)>>>(tmp.MutableData(gpu0));
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paddle::platform::CUDAPlace gpu1(1);
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auto* gpu1_ptr = tmp.MutableData(gpu1);
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paddle::platform::SetDeviceId(1);
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multiply_10<<<1, 1, 0, GetCUDAStream(gpu1)>>>(gpu1_ptr);
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for (int i = 0; i < 10; ++i) {
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ASSERT_EQ(tmp[i], i * 100);
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}
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}
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