未验证 提交 21053c16 编写于 作者: Q qingqing01 提交者: GitHub

Merge pull request #5954 from qingqing01/nvprof

Add CUDA profiler tools in new framework.
/* 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. */
#pragma once
#include <cuda_profiler_api.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
namespace paddle {
namespace platform {
void CudaProfilerInit(std::string output_file, std::string output_mode,
std::vector<std::string> config_flags) {
std::array<char, 128> buf;
std::string tmpl = "/tmp/cuda_profile_config.XXXXXX";
PADDLE_ENFORCE_LT(tmpl.size(), buf.size());
memcpy(buf.data(), tmpl.data(), tmpl.size());
auto result = mktemp(buf.data());
PADDLE_ENFORCE(strlen(result) != 0);
std::string config_file = result;
{
std::ofstream ofs(config_file, std::ios::out | std::ios::trunc);
PADDLE_ENFORCE(ofs.is_open(), "ofstream: ", ofs.rdstate());
for (const auto& line : config_flags) {
ofs << line << std::endl;
}
}
PADDLE_ENFORCE(output_mode == "kvp" || output_mode == "csv");
cudaOutputMode_t mode = output_mode == "csv" ? cudaCSV : cudaKeyValuePair;
PADDLE_ENFORCE(
cudaProfilerInitialize(config_file.c_str(), output_file.c_str(), mode));
}
void CudaProfilerStart() { PADDLE_ENFORCE(cudaProfilerStart()); }
void CudaProfilerStop() { PADDLE_ENFORCE(cudaProfilerStop()); }
} // namespace platform
} // namespace paddle
...@@ -37,6 +37,7 @@ limitations under the License. */ ...@@ -37,6 +37,7 @@ limitations under the License. */
#ifdef PADDLE_WITH_CUDA #ifdef PADDLE_WITH_CUDA
#include "paddle/operators/nccl/nccl_gpu_common.h" #include "paddle/operators/nccl/nccl_gpu_common.h"
#include "paddle/platform/cuda_profiler.h"
#include "paddle/platform/gpu_info.h" #include "paddle/platform/gpu_info.h"
#endif #endif
...@@ -460,6 +461,10 @@ All parameter, weight, gradient are variables in Paddle. ...@@ -460,6 +461,10 @@ All parameter, weight, gradient are variables in Paddle.
m.def("op_support_gpu", OpSupportGPU); m.def("op_support_gpu", OpSupportGPU);
#ifdef PADDLE_WITH_CUDA #ifdef PADDLE_WITH_CUDA
m.def("get_cuda_device_count", platform::GetCUDADeviceCount); m.def("get_cuda_device_count", platform::GetCUDADeviceCount);
m.def("nvprof_init", platform::CudaProfilerInit);
m.def("nvprof_start", platform::CudaProfilerStart);
m.def("nvprof_stop", platform::CudaProfilerStop);
#endif #endif
return m.ptr(); return m.ptr();
......
import paddle.v2.fluid.core as core
from contextlib import contextmanager
__all__ = ['CudaProfiler']
NVPROF_CONFIG = [
"gpustarttimestamp",
"gpuendtimestamp",
"gridsize3d",
"threadblocksize",
"streamid",
"enableonstart 0",
"conckerneltrace",
]
@contextmanager
def cuda_profiler(output_file, output_mode=None, config=None):
"""The CUDA profiler.
This fuctions is used to profile CUDA program by CUDA runtime application
programming interface. The profiling result will be written into
`output_file` with Key-Value pair format or Comma separated values format.
The user can set the output mode by `output_mode` argument and set the
counters/options for profiling by `config` argument. The default config
caontains 'gpustarttimestamp', 'gpustarttimestamp', 'gridsize3d',
'threadblocksize', 'streamid', 'enableonstart 0', 'conckerneltrace'.
Args:
output_file (string) : The output file name, the result will be
written into this file.
output_mode (string) : The output mode has Key-Value pair format and
Comma separated values format. It should be 'kv' or 'csv'.
config (string) : The profiler options and counters can refer to
"Compute Command Line Profiler User Guide".
"""
if output_mode is None:
output_mode = 'csv'
if output_mode not in ['kv', 'csv']:
raise ValueError("The output mode must be 'key-value' or 'csv'.")
config = NVPROF_CONFIG if config is None else config
core.nvprof_init(output_file, output_mode, config)
# Enables profiler collection by the active CUDA profiling tool.
core.nvprof_start()
yield
# Disables profiler collection.
core.nvprof_stop()
import unittest
import numpy as np
import paddle.v2.fluid as fluid
import paddle.v2.fluid.profiler as profiler
import paddle.v2.fluid.layers as layers
class TestProfiler(unittest.TestCase):
def test_nvprof(self):
if not fluid.core.is_compile_gpu():
return
epoc = 8
dshape = [4, 3, 28, 28]
data = layers.data(name='data', shape=[3, 28, 28], dtype='float32')
conv = layers.conv2d(data, 20, 3, stride=[1, 1], padding=[1, 1])
place = fluid.GPUPlace(0)
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())
with profiler.cuda_profiler("cuda_profiler.txt", 'csv') as nvprof:
for i in range(epoc):
input = np.random.random(dshape).astype("float32")
exe.run(fluid.default_main_program(), feed={'data': input})
if __name__ == '__main__':
unittest.main()
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