init.cc 7.9 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;
L
Leo Chen 已提交
56 57 58 59 60
    // NOTE(zhiqiu): dummy is needed, since the function
    // ParseNewCommandLineFlags in gflags.cc starts processing
    // commandline strings from idx 1.
    // The reason is, it assumes that the first one (idx 0) is
    // the filename of executable file.
W
wanghaoshuang 已提交
61
    argv.insert(argv.begin(), "dummy");
D
dzhwinter 已提交
62 63 64 65 66 67 68 69
    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 += ' ';
    }
L
Leo Chen 已提交
70 71
    VLOG(1) << "Before Parse: argc is " << argc
            << ", Init commandline: " << line;
D
dzhwinter 已提交
72
    google::ParseCommandLineFlags(&argc, &arr, true);
L
Leo Chen 已提交
73
    VLOG(1) << "After Parse: argc is " << argc;
D
dzhwinter 已提交
74 75 76
  });
}

77 78 79 80 81 82 83 84 85 86 87 88 89 90 91
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
92
          platform::CUDADeviceGuard guard(devices[i]);
93 94 95 96 97 98 99 100
          cudaDeviceEnablePeerAccess(devices[j], 0);
        }
      }
    }
  });
#endif
}

101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122
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
123
void InitDevices(bool init_p2p) {
124 125 126
  // CUPTI attribute should be set before any CUDA context is created (see CUPTI
  // documentation about CUpti_ActivityAttribute).
  InitCupti();
127
  /*Init all available devices by default */
128
  std::vector<int> devices;
129
#ifdef PADDLE_WITH_CUDA
D
dzhwinter 已提交
130
  try {
131 132
    // use user specified GPUs in single-node multi-process mode.
    devices = platform::GetSelectedDevices();
D
dzhwinter 已提交
133 134
  } catch (const std::exception &exp) {
    LOG(WARNING) << "Compiled with WITH_GPU, but no GPU found in runtime.";
135
  }
D
dzhwinter 已提交
136
#endif
137
  InitDevices(init_p2p, devices);
D
dzhwinter 已提交
138 139
}

140 141 142 143
void InitDevices(bool init_p2p, const std::vector<int> devices) {
  std::vector<platform::Place> places;

  for (size_t i = 0; i < devices.size(); ++i) {
144 145 146
    // In multi process multi gpu mode, we may have gpuid = 7
    // but count = 1.
    if (devices[i] < 0) {
147 148 149
      LOG(WARNING) << "Invalid devices id.";
      continue;
    }
150

151 152 153 154 155 156 157
    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
158

159
#ifndef PADDLE_WITH_MKLDNN
T
tensor-tang 已提交
160
  platform::SetNumThreads(FLAGS_paddle_num_threads);
161
#endif
T
tensor-tang 已提交
162

T
tensor-tang 已提交
163
#if !defined(_WIN32) && !defined(__APPLE__) && !defined(__OSX__)
T
tensor-tang 已提交
164
  if (platform::MayIUse(platform::avx)) {
T
tensor-tang 已提交
165 166 167 168
#ifndef __AVX__
    LOG(WARNING) << "AVX is available, Please re-compile on local machine";
#endif
  }
169 170 171 172 173 174 175 176 177 178

// 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
179 180
  if (!platform::MayIUse(platform::avx512f)) {
    if (platform::MayIUse(platform::avx2)) {
181
      AVX_GUIDE(AVX512, AVX2);
T
tensor-tang 已提交
182
    } else if (platform::MayIUse(platform::avx)) {
183 184 185 186 187
      AVX_GUIDE(AVX512, AVX);
    } else {
      AVX_GUIDE(AVX512, NonAVX);
    }
  }
T
tensor-tang 已提交
188
#endif
189 190

#ifdef __AVX2__
T
tensor-tang 已提交
191 192
  if (!platform::MayIUse(platform::avx2)) {
    if (platform::MayIUse(platform::avx)) {
193 194 195 196
      AVX_GUIDE(AVX2, AVX);
    } else {
      AVX_GUIDE(AVX2, NonAVX);
    }
T
tensor-tang 已提交
197 198
  }
#endif
199 200

#ifdef __AVX__
T
tensor-tang 已提交
201
  if (!platform::MayIUse(platform::avx)) {
202
    AVX_GUIDE(AVX, NonAVX);
T
tensor-tang 已提交
203
  }
204 205
#endif
#undef AVX_GUIDE
T
tensor-tang 已提交
206 207

#endif
208 209
}

C
chengduo 已提交
210
#ifndef _WIN32
211
void SignalHandle(const char *data, int size) {
C
chengduo 已提交
212 213
  auto file_path = string::Sprintf("/tmp/paddle.%d.dump_info", ::getpid());
  try {
214 215
    // The signal is coming line by line but we print general guide just once
    std::call_once(glog_warning_once_flag, [&]() {
216 217 218 219 220
      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";
221 222 223
      LOG(WARNING) << "The detail failure signal is:\n\n";
    });

224
    LOG(WARNING) << std::string(data, size);
C
chengduo 已提交
225 226 227 228 229 230 231 232 233
    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
234
void InitGLOG(const std::string &prog_name) {
235 236 237 238
  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
239
#ifndef _WIN32
240 241
    google::InstallFailureSignalHandler();
    google::InstallFailureWriter(&SignalHandle);
C
chengduo 已提交
242
#endif
243
  });
Y
Yang Yu 已提交
244 245
}

D
dzhwinter 已提交
246 247
}  // namespace framework
}  // namespace paddle