device_context.cc 9.1 KB
Newer Older
1
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Q
qijun 已提交
2 3 4 5 6 7 8 9 10
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. */
Y
Yi Wang 已提交
11
#include "paddle/fluid/platform/device_context.h"
12

13
#include <set>
14
#include <string>
Y
Yu Yang 已提交
15
#include <unordered_set>
16 17
#include <vector>

F
fengjiayi 已提交
18 19 20 21
#ifdef PADDLE_WITH_CUDA
#include <boost\thread\thread.hpp>
#endif

Y
Yi Wang 已提交
22
#include "paddle/fluid/memory/memory.h"
23

Q
qijun 已提交
24 25 26
namespace paddle {
namespace platform {

D
dzhwinter 已提交
27 28
DeviceContextPool* DeviceContextPool::pool = nullptr;

Y
Yu Yang 已提交
29
platform::DeviceContext* DeviceContextPool::Get(const platform::Place& place) {
D
dzhwinter 已提交
30 31 32 33 34 35
  auto it = device_contexts_.find(place);
  if (it == device_contexts_.end()) {
    PADDLE_THROW(
        "'Place' is not supported, Please re-compile with WITH_GPU "
        "option");
  }
Y
Yu Yang 已提交
36
  return it->second.get();
D
dzhwinter 已提交
37 38 39 40 41
}

DeviceContextPool::DeviceContextPool(
    const std::vector<platform::Place>& places) {
  PADDLE_ENFORCE_GT(places.size(), 0);
Y
Yu Yang 已提交
42
  using PtrType = std::unique_ptr<DeviceContext>;
43
  std::set<Place> set;
Y
Yu Yang 已提交
44 45 46 47 48 49
  for (auto& p : places) {
    set.insert(p);
  }

  for (auto& p : set) {
    if (platform::is_cpu_place(p)) {
50
#ifdef PADDLE_WITH_MKLDNN
Y
Yu Yang 已提交
51 52
      device_contexts_.emplace(
          p, PtrType(new MKLDNNDeviceContext(boost::get<CPUPlace>(p))));
53
#else
Y
Yu Yang 已提交
54 55
      device_contexts_.emplace(
          p, PtrType(new CPUDeviceContext(boost::get<CPUPlace>(p))));
56
#endif
Y
Yu Yang 已提交
57
    } else if (platform::is_gpu_place(p)) {
D
dzhwinter 已提交
58
#ifdef PADDLE_WITH_CUDA
Y
Yu Yang 已提交
59 60
      device_contexts_.emplace(
          p, PtrType(new CUDADeviceContext(boost::get<CUDAPlace>(p))));
D
dzhwinter 已提交
61 62
#else
      PADDLE_THROW(
D
dzhwinter 已提交
63
          "'CUDAPlace' is not supported, Please re-compile with WITH_GPU "
D
dzhwinter 已提交
64
          "option");
C
chengduoZH 已提交
65 66 67 68 69 70 71 72 73 74
#endif
    } else if (platform::is_cuda_pinned_place(p)) {
#ifdef PADDLE_WITH_CUDA
      device_contexts_.emplace(
          p,
          PtrType(new CUDAPinnedDeviceContext(boost::get<CUDAPinnedPlace>(p))));
#else
      PADDLE_THROW(
          "'CUDAPlace' is not supported, Please re-compile with WITH_GPU "
          "option");
D
dzhwinter 已提交
75 76 77 78 79
#endif
    }
  }
}

80 81 82 83
CPUDeviceContext::CPUDeviceContext() {
  eigen_device_.reset(new Eigen::DefaultDevice());
}

D
dzhwinter 已提交
84
CPUDeviceContext::CPUDeviceContext(CPUPlace place) : place_(place) {
85 86 87 88 89 90 91
  eigen_device_.reset(new Eigen::DefaultDevice());
}

Eigen::DefaultDevice* CPUDeviceContext::eigen_device() const {
  return eigen_device_.get();
}

D
dzhwinter 已提交
92
Place CPUDeviceContext::GetPlace() const { return place_; }
93

94
#ifdef PADDLE_WITH_CUDA
95

Q
init  
qijun 已提交
96 97 98 99 100 101 102
class EigenCudaStreamDevice : public Eigen::StreamInterface {
 public:
  EigenCudaStreamDevice() : scratch_(nullptr), semaphore_(nullptr) {
    Eigen::initializeDeviceProp();
  }
  ~EigenCudaStreamDevice() override {}

D
dzhwinter 已提交
103
  void Reinitialize(const cudaStream_t* cuda_stream, CUDAPlace place) {
Q
init  
qijun 已提交
104 105 106 107 108 109 110 111 112 113 114 115
    stream_ = cuda_stream;
    place_ = place;
    device_prop_ = &Eigen::m_deviceProperties[place.device];
  }

  const cudaStream_t& stream() const override { return *stream_; }

  const cudaDeviceProp& deviceProperties() const override {
    return *device_prop_;
  }

  void* allocate(size_t num_bytes) const override {
Q
qijun 已提交
116
    return paddle::memory::Alloc(place_, num_bytes);
Q
init  
qijun 已提交
117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141
  }

  void deallocate(void* buffer) const override {
    paddle::memory::Free(place_, buffer);
  }

  void* scratchpad() const override {
    if (scratch_ == NULL) {
      scratch_ = allocate(Eigen::kCudaScratchSize + sizeof(unsigned int));
    }
    return scratch_;
  }

  unsigned int* semaphore() const override {
    if (semaphore_ == NULL) {
      char* scratch =
          static_cast<char*>(scratchpad()) + Eigen::kCudaScratchSize;
      semaphore_ = reinterpret_cast<unsigned int*>(scratch);
      PADDLE_ENFORCE(
          cudaMemsetAsync(semaphore_, 0, sizeof(unsigned int), *stream_));
    }
    return semaphore_;
  }

 private:
D
dzhwinter 已提交
142
  CUDAPlace place_;
Q
init  
qijun 已提交
143 144
  const cudaStream_t* stream_;         // not owned;
  const cudaDeviceProp* device_prop_;  // not owned;
Q
qijun 已提交
145
  mutable void* scratch_;
Q
init  
qijun 已提交
146 147 148
  mutable unsigned int* semaphore_;
};

149 150 151
class CudnnHolder {
 public:
  CudnnHolder(const cudaStream_t* stream, const CUDAPlace& place)
F
fengjiayi 已提交
152
      : workspace_(nullptr), workspace_len_(0), stream_(stream), place_(place) {
153
    PADDLE_ENFORCE(dynload::cudnnCreate(&cudnn_handle_));
F
fengjiayi 已提交
154
    PADDLE_ENFORCE(dynload::cudnnSetStream(cudnn_handle_, *stream_));
155 156
  }

F
fengjiayi 已提交
157 158 159 160 161 162 163
  cudnnHandle_t cudnn_handle() const { return cudnn_handle_; }

  void RunFunc(const std::function<void(void*)>& cudnn_func,
               size_t required_workspace_len) {
    boost::upgrade_lock<boost::shared_mutex> shared_lock(mtx_);
    if (required_workspace_len > workspace_len_) {
      ReallocateWorkspace(required_workspace_len, &shared_lock);
164
    }
F
fengjiayi 已提交
165
    cudnn_func(workspace_);
166 167 168 169 170
  }

  ~CudnnHolder() { PADDLE_ENFORCE(dynload::cudnnDestroy(cudnn_handle_)); }

 private:
F
fengjiayi 已提交
171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187
  void ReallocateWorkspace(size_t required_workspace_len,
                           boost::upgrade_lock<boost::shared_mutex>* lock) {
    boost::upgrade_to_unique_lock<boost::shared_mutex> unique_lock(*lock);
    if (required_workspace_len <= workspace_len_) {
      return;
    }
    void* new_workspace = paddle::memory::Alloc(place_, required_len);
    if (workspace_ != nullptr) {
      // Maybe someone is using the current workspace
      PADDLE_ENFORCE(cudaStreamSynchronize(*stream_));
      PADDLE_ENFORCE(cudaGetLastError());
      paddle::memory::Free(place_, workspace_);
    }
    workspace_ = new_workspace;
    workspace_len_ = required_len;
  }

188 189 190 191 192 193
  cudnnHandle_t cudnn_handle_;
  void* workspace_;
  size_t workspace_len_;

  const cudaStream_t* stream_;  // not owned;
  const CUDAPlace place_;
F
fengjiayi 已提交
194 195

  boost::shared_mutex mtx_;
196 197 198 199
};

CUDADeviceContext::CUDADeviceContext(CUDAPlace place)
    : place_(place), cudnn_holder_(nullptr) {
200
  SetDeviceId(place_.device);
K
Kexin Zhao 已提交
201
  compute_capability = GetCUDAComputeCapability(place_.device);
202 203
  multi_process = GetCUDAMultiProcessors(place_.device);
  max_threads_per_mp = GetCUDAMaxThreadsPerMultiProcessor(place_.device);
Q
init  
qijun 已提交
204 205 206
  PADDLE_ENFORCE(cudaStreamCreate(&stream_));
  eigen_stream_.reset(new EigenCudaStreamDevice());
  eigen_stream_->Reinitialize(&stream_, place);
207
  eigen_device_.reset(new Eigen::GpuDevice(eigen_stream_.get()));
208 209
  PADDLE_ENFORCE(dynload::cublasCreate(&cublas_handle_));
  PADDLE_ENFORCE(dynload::cublasSetStream(cublas_handle_, stream_));
D
dzhwinter 已提交
210
  if (dynload::HasCUDNN()) {
211
    cudnn_holder_.reset(new CudnnHolder(&stream_, place));
D
dzhwinter 已提交
212
  }
213 214 215 216
}

CUDADeviceContext::~CUDADeviceContext() {
  SetDeviceId(place_.device);
L
liaogang 已提交
217
  Wait();
218
  PADDLE_ENFORCE(dynload::cublasDestroy(cublas_handle_));
219 220
  eigen_stream_.reset();
  eigen_device_.reset();
Q
init  
qijun 已提交
221
  PADDLE_ENFORCE(cudaStreamDestroy(stream_));
222 223
}

L
liaogang 已提交
224
Place CUDADeviceContext::GetPlace() const { return place_; }
225

L
liaogang 已提交
226
void CUDADeviceContext::Wait() const {
Q
init  
qijun 已提交
227
  PADDLE_ENFORCE(cudaStreamSynchronize(stream_));
228 229 230
  PADDLE_ENFORCE(cudaGetLastError());
}

K
Kexin Zhao 已提交
231 232 233 234
int CUDADeviceContext::GetComputeCapability() const {
  return compute_capability;
}

235 236 237 238
int CUDADeviceContext::GetMaxPhysicalThreadCount() const {
  return multi_process * max_threads_per_mp;
}

239 240 241 242
Eigen::GpuDevice* CUDADeviceContext::eigen_device() const {
  return eigen_device_.get();
}

243
cublasHandle_t CUDADeviceContext::cublas_handle() const {
244 245 246
  return cublas_handle_;
}

247
cudnnHandle_t CUDADeviceContext::cudnn_handle() const {
F
fengjiayi 已提交
248
  return cudnn_holder_->cudnn_handle();
249 250
}

F
fengjiayi 已提交
251 252 253
void CUDADeviceContext::RunCudnnFuncWithWorkspace(
    const std::function<void(void*)>& cudnn_func, size_t workspace_len) const {
  cudnn_holder_->RunFunc(cudnn_func, workspace_len);
254
}
255

256
cudaStream_t CUDADeviceContext::stream() const { return stream_; }
Q
qijun 已提交
257

C
chengduoZH 已提交
258 259 260 261 262 263 264 265 266 267 268 269 270 271
CUDAPinnedDeviceContext::CUDAPinnedDeviceContext() {
  eigen_device_.reset(new Eigen::DefaultDevice());
}

CUDAPinnedDeviceContext::CUDAPinnedDeviceContext(CUDAPinnedPlace place)
    : place_(place) {
  eigen_device_.reset(new Eigen::DefaultDevice());
}

Eigen::DefaultDevice* CUDAPinnedDeviceContext::eigen_device() const {
  return eigen_device_.get();
}

Place CUDAPinnedDeviceContext::GetPlace() const { return place_; }
L
Luo Tao 已提交
272
#endif
Q
qijun 已提交
273

T
tensor-tang 已提交
274 275
#ifdef PADDLE_WITH_MKLDNN
MKLDNNDeviceContext::MKLDNNDeviceContext(CPUPlace place)
276 277
    : CPUDeviceContext(place), engine_(mkldnn::engine::cpu, 0), p_blobs_() {
  p_blobs_.reset(new std::unordered_map<std::string, std::shared_ptr<void>>());
T
tensor-tang 已提交
278 279
}

280 281 282 283
void MKLDNNDeviceContext::SetBlob(const std::string& name,
                                  std::shared_ptr<void> data) const {
  std::unordered_map<std::string, std::shared_ptr<void>>* p;
  p = p_blobs_.get();
T
tensor-tang 已提交
284

285
  auto it = p->find(name);
T
tensor-tang 已提交
286

287 288 289 290 291
  if (it == p->end()) {
    (*p)[name] = data;  // create new blob
  } else {
    it->second = data;  // set data to existing blob
  }
T
tensor-tang 已提交
292

293
  return;
T
tensor-tang 已提交
294 295
}

296 297 298 299
std::shared_ptr<void> MKLDNNDeviceContext::GetBlob(
    const std::string& name) const {
  std::unordered_map<std::string, std::shared_ptr<void>>* p;
  p = p_blobs_.get();
T
tensor-tang 已提交
300

301
  auto it = p->find(name);
T
tensor-tang 已提交
302

303 304
  if (it != p->end()) {
    return it->second;
T
tensor-tang 已提交
305
  }
306 307

  return nullptr;
T
tensor-tang 已提交
308 309 310 311
}

#endif

Q
qijun 已提交
312
}  // namespace platform
Q
qijun 已提交
313
}  // namespace paddle