init.cc 7.5 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
D
dzhwinter 已提交
2

L
Luo Tao 已提交
3 4 5
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
D
dzhwinter 已提交
6

L
Luo Tao 已提交
7
    http://www.apache.org/licenses/LICENSE-2.0
D
dzhwinter 已提交
8

L
Luo Tao 已提交
9 10 11 12 13
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. */
Y
Yang Yu 已提交
14
#include <string.h>  // for strdup
D
dzhwinter 已提交
15
#include <algorithm>
C
chengduo 已提交
16 17
#include <fstream>
#include <iostream>
Q
qingqing01 已提交
18 19
#include <memory>
#include <set>
D
dzhwinter 已提交
20
#include <stdexcept>
D
dzhwinter 已提交
21 22
#include <string>

Y
Yi Wang 已提交
23
#include "paddle/fluid/framework/operator.h"
T
tensor-tang 已提交
24
#include "paddle/fluid/platform/cpu_helper.h"
T
tensor-tang 已提交
25
#include "paddle/fluid/platform/cpu_info.h"
26
#include "paddle/fluid/string/split.h"
S
sneaxiy 已提交
27
#ifdef PADDLE_WITH_CUDA
Y
Yu Yang 已提交
28
#include "paddle/fluid/platform/cuda_device_guard.h"
29
#include "paddle/fluid/platform/dynload/cupti.h"
S
sneaxiy 已提交
30
#endif
Y
Yi Wang 已提交
31
#include "paddle/fluid/platform/device_context.h"
32
#include "paddle/fluid/platform/init.h"
Y
Yi Wang 已提交
33
#include "paddle/fluid/platform/place.h"
34
#include "paddle/fluid/string/piece.h"
35

36
DECLARE_int32(paddle_num_threads);
37 38 39
DEFINE_int32(multiple_of_cupti_buffer_size, 1,
             "Multiple of the CUPTI device buffer size. If the timestamps have "
             "been dropped when you are profiling, try increasing this value.");
T
tensor-tang 已提交
40

D
dzhwinter 已提交
41 42 43
namespace paddle {
namespace framework {

44 45 46 47
#ifdef _WIN32
#define strdup _strdup
#endif

D
dzhwinter 已提交
48
std::once_flag gflags_init_flag;
49
std::once_flag glog_init_flag;
X
Xin Pan 已提交
50
std::once_flag p2p_init_flag;
51
std::once_flag glog_warning_once_flag;
D
dzhwinter 已提交
52

53
void InitGflags(std::vector<std::string> argv) {
D
dzhwinter 已提交
54
  std::call_once(gflags_init_flag, [&]() {
C
chengduo 已提交
55
    FLAGS_logtostderr = true;
W
wanghaoshuang 已提交
56
    argv.insert(argv.begin(), "dummy");
D
dzhwinter 已提交
57 58 59 60 61 62 63 64 65
    int argc = argv.size();
    char **arr = new char *[argv.size()];
    std::string line;
    for (size_t i = 0; i < argv.size(); i++) {
      arr[i] = &argv[i][0];
      line += argv[i];
      line += ' ';
    }
    google::ParseCommandLineFlags(&argc, &arr, true);
M
minqiyang 已提交
66
    VLOG(1) << "Init commandline: " << line;
D
dzhwinter 已提交
67 68 69
  });
}

70 71 72 73 74 75 76 77 78 79 80 81 82 83 84
void InitP2P(std::vector<int> devices) {
#ifdef PADDLE_WITH_CUDA
  std::call_once(p2p_init_flag, [&]() {
    int count = devices.size();
    for (int i = 0; i < count; ++i) {
      for (int j = 0; j < count; ++j) {
        if (devices[i] == devices[j]) continue;
        int can_acess = -1;
        PADDLE_ENFORCE(
            cudaDeviceCanAccessPeer(&can_acess, devices[i], devices[j]),
            "Failed to test P2P access.");
        if (can_acess != 1) {
          LOG(WARNING) << "Cannot enable P2P access from " << devices[i]
                       << " to " << devices[j];
        } else {
Y
Yu Yang 已提交
85
          platform::CUDADeviceGuard guard(devices[i]);
86 87 88 89 90 91 92 93
          cudaDeviceEnablePeerAccess(devices[j], 0);
        }
      }
    }
  });
#endif
}

94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115
void InitCupti() {
#ifdef PADDLE_WITH_CUPTI
  if (FLAGS_multiple_of_cupti_buffer_size == 1) return;
  size_t attrValue = 0, attrValueSize = sizeof(size_t);
#define MULTIPLY_ATTR_VALUE(attr)                                 \
  {                                                               \
    PADDLE_ENFORCE(!platform::dynload::cuptiActivityGetAttribute( \
        attr, &attrValueSize, &attrValue));                       \
    attrValue *= FLAGS_multiple_of_cupti_buffer_size;             \
    LOG(WARNING) << "Set " #attr " " << attrValue << " byte";     \
    PADDLE_ENFORCE(!platform::dynload::cuptiActivitySetAttribute( \
        attr, &attrValueSize, &attrValue));                       \
  }
  MULTIPLY_ATTR_VALUE(CUPTI_ACTIVITY_ATTR_DEVICE_BUFFER_SIZE);
  MULTIPLY_ATTR_VALUE(CUPTI_ACTIVITY_ATTR_DEVICE_BUFFER_SIZE_CDP);
#if CUDA_VERSION >= 9000
  MULTIPLY_ATTR_VALUE(CUPTI_ACTIVITY_ATTR_PROFILING_SEMAPHORE_POOL_SIZE);
#endif
#undef MULTIPLY_ATTR_VALUE
#endif
}

X
Xin Pan 已提交
116
void InitDevices(bool init_p2p) {
117 118 119
  // CUPTI attribute should be set before any CUDA context is created (see CUPTI
  // documentation about CUpti_ActivityAttribute).
  InitCupti();
120
  /*Init all available devices by default */
121
  std::vector<int> devices;
122
#ifdef PADDLE_WITH_CUDA
D
dzhwinter 已提交
123
  try {
124 125
    // use user specified GPUs in single-node multi-process mode.
    devices = platform::GetSelectedDevices();
D
dzhwinter 已提交
126 127
  } catch (const std::exception &exp) {
    LOG(WARNING) << "Compiled with WITH_GPU, but no GPU found in runtime.";
128
  }
D
dzhwinter 已提交
129
#endif
130
  InitDevices(init_p2p, devices);
D
dzhwinter 已提交
131 132
}

133 134 135 136
void InitDevices(bool init_p2p, const std::vector<int> devices) {
  std::vector<platform::Place> places;

  for (size_t i = 0; i < devices.size(); ++i) {
137 138 139
    // In multi process multi gpu mode, we may have gpuid = 7
    // but count = 1.
    if (devices[i] < 0) {
140 141 142
      LOG(WARNING) << "Invalid devices id.";
      continue;
    }
143

144 145 146 147 148 149 150
    places.emplace_back(platform::CUDAPlace(devices[i]));
  }
  if (init_p2p) {
    InitP2P(devices);
  }
  places.emplace_back(platform::CPUPlace());
  platform::DeviceContextPool::Init(places);
Q
qingqing01 已提交
151

152
#ifndef PADDLE_WITH_MKLDNN
T
tensor-tang 已提交
153
  platform::SetNumThreads(FLAGS_paddle_num_threads);
154
#endif
T
tensor-tang 已提交
155

T
tensor-tang 已提交
156
#if !defined(_WIN32) && !defined(__APPLE__) && !defined(__OSX__)
T
tensor-tang 已提交
157
  if (platform::MayIUse(platform::avx)) {
T
tensor-tang 已提交
158 159 160 161
#ifndef __AVX__
    LOG(WARNING) << "AVX is available, Please re-compile on local machine";
#endif
  }
162 163 164 165 166 167 168 169 170 171

// Throw some informations when CPU instructions mismatch.
#define AVX_GUIDE(compiletime, runtime)                                     \
  LOG(FATAL)                                                                \
      << "This version is compiled on higher instruction(" #compiletime     \
         ") system, you may encounter illegal instruction error running on" \
         " your local CPU machine. Please reinstall the " #runtime          \
         " version or compile from source code."

#ifdef __AVX512F__
T
tensor-tang 已提交
172 173
  if (!platform::MayIUse(platform::avx512f)) {
    if (platform::MayIUse(platform::avx2)) {
174
      AVX_GUIDE(AVX512, AVX2);
T
tensor-tang 已提交
175
    } else if (platform::MayIUse(platform::avx)) {
176 177 178 179 180
      AVX_GUIDE(AVX512, AVX);
    } else {
      AVX_GUIDE(AVX512, NonAVX);
    }
  }
T
tensor-tang 已提交
181
#endif
182 183

#ifdef __AVX2__
T
tensor-tang 已提交
184 185
  if (!platform::MayIUse(platform::avx2)) {
    if (platform::MayIUse(platform::avx)) {
186 187 188 189
      AVX_GUIDE(AVX2, AVX);
    } else {
      AVX_GUIDE(AVX2, NonAVX);
    }
T
tensor-tang 已提交
190 191
  }
#endif
192 193

#ifdef __AVX__
T
tensor-tang 已提交
194
  if (!platform::MayIUse(platform::avx)) {
195
    AVX_GUIDE(AVX, NonAVX);
T
tensor-tang 已提交
196
  }
197 198
#endif
#undef AVX_GUIDE
T
tensor-tang 已提交
199 200

#endif
201 202
}

C
chengduo 已提交
203
#ifndef _WIN32
204
void SignalHandle(const char *data, int size) {
C
chengduo 已提交
205 206
  auto file_path = string::Sprintf("/tmp/paddle.%d.dump_info", ::getpid());
  try {
207 208
    // The signal is coming line by line but we print general guide just once
    std::call_once(glog_warning_once_flag, [&]() {
209 210 211 212 213
      LOG(WARNING) << "Warning: PaddlePaddle catches a failure signal, it may "
                      "not work properly\n";
      LOG(WARNING) << "You could check whether you killed PaddlePaddle "
                      "thread/process accidentally or report the case to "
                      "PaddlePaddle\n";
214 215 216
      LOG(WARNING) << "The detail failure signal is:\n\n";
    });

217
    LOG(WARNING) << std::string(data, size);
C
chengduo 已提交
218 219 220 221 222 223 224 225 226
    std::ofstream dump_info;
    dump_info.open(file_path, std::ios::app);
    dump_info << std::string(data, size);
    dump_info.close();
  } catch (...) {
  }
}
#endif

Y
Yang Yu 已提交
227
void InitGLOG(const std::string &prog_name) {
228 229 230 231
  std::call_once(glog_init_flag, [&]() {
    // glog will not hold the ARGV[0] inside.
    // Use strdup to alloc a new string.
    google::InitGoogleLogging(strdup(prog_name.c_str()));
C
chengduo 已提交
232
#ifndef _WIN32
233 234
    google::InstallFailureSignalHandler();
    google::InstallFailureWriter(&SignalHandle);
C
chengduo 已提交
235
#endif
236
  });
Y
Yang Yu 已提交
237 238
}

D
dzhwinter 已提交
239 240
}  // namespace framework
}  // namespace paddle