init.cc 10.7 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 37 38 39 40
#ifdef PADDLE_WITH_XPU
#include "paddle/fluid/platform/xpu_header.h"
#include "paddle/fluid/platform/xpu_info.h"
#endif

41
DECLARE_int32(paddle_num_threads);
42 43 44
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
45

46 47 48 49 50 51 52 53 54 55
namespace paddle {
namespace platform {

void ParseCommandLineFlags(int argc, char **argv, bool remove) {
  google::ParseCommandLineFlags(&argc, &argv, remove);
}

}  // namespace platform
}  // namespace paddle

D
dzhwinter 已提交
56 57 58
namespace paddle {
namespace framework {

59 60 61 62
#ifdef _WIN32
#define strdup _strdup
#endif

D
dzhwinter 已提交
63
std::once_flag gflags_init_flag;
64
std::once_flag glog_init_flag;
X
Xin Pan 已提交
65
std::once_flag p2p_init_flag;
D
dzhwinter 已提交
66

67
bool InitGflags(std::vector<std::string> args) {
68
  bool successed = false;
D
dzhwinter 已提交
69
  std::call_once(gflags_init_flag, [&]() {
C
chengduo 已提交
70
    FLAGS_logtostderr = true;
L
Leo Chen 已提交
71 72 73 74 75
    // 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.
76 77
    args.insert(args.begin(), "dummy");
    std::vector<char *> argv;
D
dzhwinter 已提交
78
    std::string line;
79 80 81 82
    int argc = args.size();
    for (auto &arg : args) {
      argv.push_back(const_cast<char *>(arg.data()));
      line += arg;
D
dzhwinter 已提交
83 84
      line += ' ';
    }
L
Leo Chen 已提交
85 86
    VLOG(1) << "Before Parse: argc is " << argc
            << ", Init commandline: " << line;
87 88

    char **arr = argv.data();
D
dzhwinter 已提交
89
    google::ParseCommandLineFlags(&argc, &arr, true);
90
    successed = true;
91 92

    VLOG(1) << "After Parse: argc is " << argc;
D
dzhwinter 已提交
93
  });
94
  return successed;
D
dzhwinter 已提交
95 96
}

97 98 99 100 101 102 103 104
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;
G
GaoWei8 已提交
105 106
        PADDLE_ENFORCE_CUDA_SUCCESS(
            cudaDeviceCanAccessPeer(&can_acess, devices[i], devices[j]));
107 108 109 110
        if (can_acess != 1) {
          LOG(WARNING) << "Cannot enable P2P access from " << devices[i]
                       << " to " << devices[j];
        } else {
Y
Yu Yang 已提交
111
          platform::CUDADeviceGuard guard(devices[i]);
112 113 114 115 116 117 118 119
          cudaDeviceEnablePeerAccess(devices[j], 0);
        }
      }
    }
  });
#endif
}

120 121 122 123
void InitCupti() {
#ifdef PADDLE_WITH_CUPTI
  if (FLAGS_multiple_of_cupti_buffer_size == 1) return;
  size_t attrValue = 0, attrValueSize = sizeof(size_t);
G
GaoWei8 已提交
124 125 126 127 128 129 130 131 132 133 134 135
#define MULTIPLY_ATTR_VALUE(attr)                                            \
  {                                                                          \
    PADDLE_ENFORCE_EQ(                                                       \
        !platform::dynload::cuptiActivityGetAttribute(attr, &attrValueSize,  \
                                                      &attrValue),           \
        true, platform::errors::Unavailable("Get cupti attribute failed.")); \
    attrValue *= FLAGS_multiple_of_cupti_buffer_size;                        \
    LOG(WARNING) << "Set " #attr " " << attrValue << " byte";                \
    PADDLE_ENFORCE_EQ(                                                       \
        !platform::dynload::cuptiActivitySetAttribute(attr, &attrValueSize,  \
                                                      &attrValue),           \
        true, platform::errors::Unavailable("Set cupti attribute failed.")); \
136 137 138 139 140 141 142 143 144 145
  }
  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
146
void InitDevices(bool init_p2p) {
147 148 149
  // CUPTI attribute should be set before any CUDA context is created (see CUPTI
  // documentation about CUpti_ActivityAttribute).
  InitCupti();
150
  /*Init all available devices by default */
151
  std::vector<int> devices;
152
#ifdef PADDLE_WITH_CUDA
D
dzhwinter 已提交
153
  try {
154 155
    // use user specified GPUs in single-node multi-process mode.
    devices = platform::GetSelectedDevices();
D
dzhwinter 已提交
156 157
  } catch (const std::exception &exp) {
    LOG(WARNING) << "Compiled with WITH_GPU, but no GPU found in runtime.";
158
  }
159 160 161 162 163 164 165 166
#endif
#ifdef PADDLE_WITH_XPU
  try {
    // use user specified XPUs in single-node multi-process mode.
    devices = platform::GetXPUSelectedDevices();
  } catch (const std::exception &exp) {
    LOG(WARNING) << "Compiled with WITH_XPU, but no XPU found in runtime.";
  }
D
dzhwinter 已提交
167
#endif
168
  InitDevices(init_p2p, devices);
D
dzhwinter 已提交
169 170
}

171 172 173 174
void InitDevices(bool init_p2p, const std::vector<int> devices) {
  std::vector<platform::Place> places;

  for (size_t i = 0; i < devices.size(); ++i) {
175 176 177
    // In multi process multi gpu mode, we may have gpuid = 7
    // but count = 1.
    if (devices[i] < 0) {
178 179 180
      LOG(WARNING) << "Invalid devices id.";
      continue;
    }
181 182

#ifdef PADDLE_WITH_CUDA
183
    places.emplace_back(platform::CUDAPlace(devices[i]));
184 185 186 187
#endif
#ifdef PADDLE_WITH_XPU
    places.emplace_back(platform::XPUPlace(devices[i]));
#endif
188 189 190 191 192
  }
  if (init_p2p) {
    InitP2P(devices);
  }
  places.emplace_back(platform::CPUPlace());
193 194 195
#ifdef PADDLE_WITH_CUDA
  places.emplace_back(platform::CUDAPinnedPlace());
#endif
196
  platform::DeviceContextPool::Init(places);
Q
qingqing01 已提交
197

198
#ifndef PADDLE_WITH_MKLDNN
T
tensor-tang 已提交
199
  platform::SetNumThreads(FLAGS_paddle_num_threads);
200
#endif
T
tensor-tang 已提交
201

T
tensor-tang 已提交
202
#if !defined(_WIN32) && !defined(__APPLE__) && !defined(__OSX__)
T
tensor-tang 已提交
203
  if (platform::MayIUse(platform::avx)) {
T
tensor-tang 已提交
204 205 206 207
#ifndef __AVX__
    LOG(WARNING) << "AVX is available, Please re-compile on local machine";
#endif
  }
208 209

// Throw some informations when CPU instructions mismatch.
210 211 212 213 214 215
#define AVX_GUIDE(compiletime, runtime)                                  \
  PADDLE_THROW(platform::errors::Unavailable(                            \
      "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."))
216 217

#ifdef __AVX512F__
T
tensor-tang 已提交
218 219
  if (!platform::MayIUse(platform::avx512f)) {
    if (platform::MayIUse(platform::avx2)) {
220
      AVX_GUIDE(AVX512, AVX2);
T
tensor-tang 已提交
221
    } else if (platform::MayIUse(platform::avx)) {
222 223 224 225 226
      AVX_GUIDE(AVX512, AVX);
    } else {
      AVX_GUIDE(AVX512, NonAVX);
    }
  }
T
tensor-tang 已提交
227
#endif
228 229

#ifdef __AVX2__
T
tensor-tang 已提交
230 231
  if (!platform::MayIUse(platform::avx2)) {
    if (platform::MayIUse(platform::avx)) {
232 233 234 235
      AVX_GUIDE(AVX2, AVX);
    } else {
      AVX_GUIDE(AVX2, NonAVX);
    }
T
tensor-tang 已提交
236 237
  }
#endif
238 239

#ifdef __AVX__
T
tensor-tang 已提交
240
  if (!platform::MayIUse(platform::avx)) {
241
    AVX_GUIDE(AVX, NonAVX);
T
tensor-tang 已提交
242
  }
243 244
#endif
#undef AVX_GUIDE
T
tensor-tang 已提交
245 246

#endif
247 248
}

C
chengduo 已提交
249
#ifndef _WIN32
250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280
// Description Quoted from
// https://pubs.opengroup.org/onlinepubs/9699919799/basedefs/signal.h.html
const struct {
  const char *name;
  const char *error_string;
} SignalErrorStrings[] = {
    {"SIGSEGV", "Segmentation fault"},
    {"SIGILL", "Illegal instruction"},
    {"SIGFPE", "Erroneous arithmetic operation"},
    {"SIGABRT", "Process abort signal"},
    {"SIGBUS", "Access to an undefined portion of a memory object"},
    {"SIGTERM", "Termination signal"},
};

bool StartsWith(const char *str, const char *prefix) {
  size_t len_prefix = strlen(prefix);
  size_t len_str = strlen(str);
  return len_str < len_prefix ? false : memcmp(prefix, str, len_prefix) == 0;
}

const char *ParseSignalErrorString(const std::string &str) {
  for (size_t i = 0;
       i < (sizeof(SignalErrorStrings) / sizeof(*(SignalErrorStrings))); ++i) {
    if (std::string::npos != str.find(SignalErrorStrings[i].name)) {
      return SignalErrorStrings[i].error_string;
    }
  }
  return "Unknown signal";
}

// Handle SIGSEGV, SIGILL, SIGFPE, SIGABRT, SIGBUS, and SIGTERM.
281
void SignalHandle(const char *data, int size) {
C
chengduo 已提交
282
  try {
283 284
    // NOTE1: The glog FailureSignalHandler dumped messages
    //   are deal with line by line
285
    auto signal_msg_dunmer_ptr = SignalMessageDumper::Instance().Get();
286 287 288
    // NOTE2: we only deal with the time info ane signal info,
    //   the stack trace will generated by paddle self
    if (StartsWith(data, "*** Aborted at")) {
289 290
      *signal_msg_dunmer_ptr << "  [TimeInfo: " << std::string(data, size - 1)
                             << "]\n";
291 292 293 294 295
    } else if (StartsWith(data, "***")) {
      std::string signal_info(data, size - 1);
      std::string useless_substr("; stack trace:");
      size_t start_pos = signal_info.rfind(useless_substr);
      signal_info.replace(start_pos, useless_substr.length(), "");
296
      *signal_msg_dunmer_ptr << "  [SignalInfo: " << signal_info << "]\n";
297 298 299 300 301 302 303
      // NOTE3: Here does not throw an exception,
      // otherwise it will casue "terminate called recursively"
      auto exp = platform::EnforceNotMet(
          platform::errors::Fatal(
              "A serious error (%s) is detected by the operating system.",
              ParseSignalErrorString(signal_info)),
          __FILE__, __LINE__);
304
      std::cout << exp.what() << (*signal_msg_dunmer_ptr).str() << std::endl;
305
    }
C
chengduo 已提交
306
  } catch (...) {
307 308 309
    // Since the program has already triggered a system error,
    // no further processing is required here, glog FailureSignalHandler
    // will Kill program by the default signal handler
C
chengduo 已提交
310 311 312 313
  }
}
#endif

Y
Yang Yu 已提交
314
void InitGLOG(const std::string &prog_name) {
315 316 317 318
  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
319
#ifndef _WIN32
320 321
    google::InstallFailureSignalHandler();
    google::InstallFailureWriter(&SignalHandle);
C
chengduo 已提交
322
#endif
323
  });
Y
Yang Yu 已提交
324 325
}

D
dzhwinter 已提交
326 327
}  // namespace framework
}  // namespace paddle