提交 ffa63974 编写于 作者: C chengduoZH

compare the performance of unpinned memory and pinned memory

上级 58a9f9f7
......@@ -4,13 +4,17 @@ cc_library(memory SRCS memory.cc DEPS place enforce)
cc_library(memcpy SRCS memcpy.cc DEPS place)
cc_library(paddle_memory
DEPS
memory
memcpy
meta_data
meta_cache
memory_block
buddy_allocator
system_allocator)
DEPS
memory
memcpy
meta_data
meta_cache
memory_block
buddy_allocator
system_allocator)
cc_test(memory_test SRCS memory_test.cc DEPS place paddle_memory)
if (WITH_GPU)
nv_test(pinned_memory_test SRCS pinned_memory_test.cu DEPS place paddle_memory)
endif()
/* Copyright (c) 2018 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/memory/detail/memory_block.h"
#include "paddle/fluid/memory/detail/meta_data.h"
#include "paddle/fluid/memory/memcpy.h"
#include "paddle/fluid/memory/memory.h"
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/gpu_info.h"
#include "paddle/fluid/platform/place.h"
#include <gtest/gtest.h>
#include <unordered_map>
template <typename T>
__global__ void Kernel(T* output, int dim) {
int tid = blockIdx.x * blockDim.x + threadIdx.x;
if (tid < dim) {
output[tid] = output[tid] * output[tid] / 100;
}
}
template <typename Place>
void test_pinned_memory() {
Place cpu_place;
paddle::platform::CUDAPlace cuda_place;
const int data_size = 4096;
const int iteration = 10;
// create event start and end
cudaEvent_t start_e, stop_e, copying_e;
float elapsedTime = 0;
cudaEventCreate(&start_e);
cudaEventCreate(&stop_e);
cudaEventCreate(&copying_e);
// create computation stream, data copying stream
cudaStream_t computation_stream, copying_stream;
cudaStreamCreate(&computation_stream);
cudaStreamCreate(&copying_stream);
// create record event, pinned memory, gpu memory
std::vector<cudaEvent_t> record_event(iteration);
std::vector<float*> input_pinned_mem(iteration);
std::vector<float*> gpu_mem(iteration);
std::vector<float*> output_pinned_mem(iteration);
// initial data
for (int j = 0; j < iteration; ++j) {
cudaEventCreateWithFlags(&record_event[j], cudaEventDisableTiming);
cudaEventCreate(&(record_event[j]));
input_pinned_mem[j] = static_cast<float*>(
paddle::memory::Alloc(cpu_place, data_size * sizeof(float)));
output_pinned_mem[j] = static_cast<float*>(
paddle::memory::Alloc(cpu_place, data_size * sizeof(float)));
gpu_mem[j] = static_cast<float*>(
paddle::memory::Alloc(cuda_place, data_size * sizeof(float)));
for (int k = 0; k < data_size; ++k) {
input_pinned_mem[j][k] = k;
}
}
cudaEventRecord(start_e, computation_stream);
// computation
for (int m = 0; m < 30; ++m) {
for (int i = 0; i < iteration; ++i) {
// cpu -> GPU on computation stream.
// note: this operation is async for pinned memory.
paddle::memory::Copy(cuda_place, gpu_mem[i], cpu_place,
input_pinned_mem[i], data_size * sizeof(float),
computation_stream);
// call kernel on computation stream.
Kernel<<<4, 1024, 0, computation_stream>>>(gpu_mem[i], data_size);
// record event_computation on computation stream
cudaEventRecord(record_event[i], computation_stream);
// wait event_computation on copy stream.
// note: this operation is async.
cudaStreamWaitEvent(copying_stream, record_event[i], 0);
// copy data GPU->CPU, on copy stream.
// note: this operation is async for pinned memory.
paddle::memory::Copy(cpu_place, output_pinned_mem[i], cuda_place,
gpu_mem[i], data_size * sizeof(float),
copying_stream);
}
}
cudaEventRecord(copying_e, copying_stream);
cudaStreamWaitEvent(computation_stream, copying_e, 0);
cudaEventRecord(stop_e, computation_stream);
cudaEventSynchronize(start_e);
cudaEventSynchronize(stop_e);
cudaEventElapsedTime(&elapsedTime, start_e, stop_e);
std::cout << cpu_place << " "
<< "time consume:" << elapsedTime / 30 << std::endl;
for (int l = 0; l < iteration; ++l) {
for (int k = 0; k < data_size; ++k) {
float temp = input_pinned_mem[l][k];
temp = temp * temp / 100;
EXPECT_FLOAT_EQ(temp, output_pinned_mem[l][k]);
}
}
// destroy resource
cudaEventDestroy(copying_e);
cudaEventDestroy(start_e);
cudaEventDestroy(stop_e);
for (int j = 0; j < 10; ++j) {
cudaEventDestroy((record_event[j]));
paddle::memory::Free(cpu_place, input_pinned_mem[j]);
paddle::memory::Free(cpu_place, output_pinned_mem[j]);
paddle::memory::Free(cuda_place, gpu_mem[j]);
}
}
TEST(CPUANDCUDAPinned, CPUAllocator) {
test_pinned_memory<paddle::platform::CPUPlace>();
}
TEST(CPUANDCUDAPinned, CUDAPinnedAllocator) {
test_pinned_memory<paddle::platform::CUDAPinnedPlace>();
}
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