cl_runtime.cc 10.8 KB
Newer Older
Y
Yan Chunwei 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.

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. */

15
#include "lite/backends/opencl/cl_runtime.h"
Y
Yan Chunwei 已提交
16
#include <string>
17
#include <unordered_map>
Y
Yan Chunwei 已提交
18 19 20 21 22 23 24 25 26 27 28 29 30 31
#include <utility>
#include <vector>
#include "lite/utils/cp_logging.h"

namespace paddle {
namespace lite {

CLRuntime* CLRuntime::Global() {
  static CLRuntime cl_runtime_;
  cl_runtime_.Init();
  return &cl_runtime_;
}

CLRuntime::~CLRuntime() {
32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47
  LOG(INFO) << "CLRuntime::~CLRuntime()";
  // Note: do ReleaseResources() in predictor
  command_queue_&& clReleaseCommandQueue(command_queue_->get());
  command_queue_.reset();
  context_&& clReleaseContext(context_->get());
  context_.reset();
  device_.reset();
  platform_.reset();
  initialized_ = false;
}

void CLRuntime::ReleaseResources() {
  //  if (is_resources_released_) {
  //    return;
  //  }

Y
Yan Chunwei 已提交
48
  if (command_queue_ != nullptr) {
49
    command_queue_->flush();
Y
Yan Chunwei 已提交
50 51
    command_queue_->finish();
  }
开心的小妮's avatar
开心的小妮 已提交
52 53
  LOG(INFO) << "kernels_.size():" << kernels_.size();
  LOG(INFO) << "programs_.size():" << programs_.size();
54 55 56 57 58 59 60
  for (size_t kidx = 0; kidx < kernels_.size(); ++kidx) {
    clReleaseKernel(kernels_[kidx]->get());
    kernels_[kidx].reset();
  }
  kernels_.clear();
  kernel_offset_.clear();
  for (auto& p : programs_) {
开心的小妮's avatar
开心的小妮 已提交
61
    // clReleaseProgram(p.second->get());
62
  }
开心的小妮's avatar
开心的小妮 已提交
63
  // programs_.clear();
64 65
  LOG(INFO) << "release resources finished.";
  is_resources_released_ = true;
Y
Yan Chunwei 已提交
66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102
}

bool CLRuntime::Init() {
  if (initialized_) {
    return true;
  }
  bool is_platform_init = InitializePlatform();
  bool is_device_init = InitializeDevice();
  is_init_success_ = is_platform_init && is_device_init;
  initialized_ = true;
  return initialized_;
}

cl::Platform& CLRuntime::platform() {
  CHECK(platform_ != nullptr) << "platform_ is not initialized!";
  return *platform_;
}

cl::Context& CLRuntime::context() {
  if (context_ == nullptr) {
    context_ = CreateContext();
  }
  return *context_;
}

cl::Device& CLRuntime::device() {
  CHECK(device_ != nullptr) << "device_ is not initialized!";
  return *device_;
}

cl::CommandQueue& CLRuntime::command_queue() {
  if (command_queue_ == nullptr) {
    command_queue_ = CreateCommandQueue(context());
  }
  return *command_queue_;
}

103
std::shared_ptr<cl::Program> CLRuntime::CreateProgram(
Y
Yan Chunwei 已提交
104
    const cl::Context& context, std::string file_name) {
105 106
  auto cl_file = opencl_kernels_files.find(file_name);
  std::string content(cl_file->second.begin(), cl_file->second.end());
Y
Yan Chunwei 已提交
107 108 109
  cl::Program::Sources sources;
  sources.push_back(content);
  auto prog =
110
      std::shared_ptr<cl::Program>(new cl::Program(context, sources, &status_));
Y
Yan Chunwei 已提交
111 112 113 114 115 116 117 118 119 120 121 122 123 124 125
  VLOG(4) << "OpenCL kernel file name: " << file_name;
  VLOG(4) << "Program source size: " << content.size();
  CL_CHECK_FATAL(status_);
  return std::move(prog);
}

std::unique_ptr<cl::UserEvent> CLRuntime::CreateEvent(
    const cl::Context& context) {
  auto event =
      std::unique_ptr<cl::UserEvent>(new cl::UserEvent(context, &status_));
  CL_CHECK_FATAL(status_);
  return std::move(event);
}

bool CLRuntime::BuildProgram(cl::Program* program, const std::string& options) {
126 127
  /* -I +CLRuntime::Global()->cl_path() + "/cl_kernel"*/
  std::string build_option = options + " -cl-fast-relaxed-math ";
128
  VLOG(4) << "OpenCL build_option: " << build_option;
Y
Yan Chunwei 已提交
129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157
  status_ = program->build({*device_}, build_option.c_str());
  CL_CHECK_ERROR(status_);

  if (status_ != CL_SUCCESS) {
    if (program->getBuildInfo<CL_PROGRAM_BUILD_STATUS>(device()) ==
        CL_BUILD_ERROR) {
      std::string log = program->getBuildInfo<CL_PROGRAM_BUILD_LOG>(device());
      LOG(FATAL) << "Program build error: " << log;
    }
    return false;
  }

  return true;
}

bool CLRuntime::InitializePlatform() {
  std::vector<cl::Platform> all_platforms;
  status_ = cl::Platform::get(&all_platforms);
  CL_CHECK_ERROR(status_);
  if (all_platforms.empty()) {
    LOG(FATAL) << "No OpenCL platform found!";
    return false;
  }
  platform_ = std::make_shared<cl::Platform>();
  *platform_ = all_platforms[0];
  return true;
}

bool CLRuntime::InitializeDevice() {
158 159 160 161 162 163
  // ===================== BASIC =====================
  // CL_DEVICE_TYPE_GPU
  // CL_DEVICE_NAME
  // CL_DEVICE_SUPPORT
  // CL_DEVICE_MAX_COMPUTE_UNITS
  // CL_DEVICE_MAX_CLOCK_FREQUENCY
Y
Yan Chunwei 已提交
164 165 166 167 168 169 170 171 172 173 174 175
  std::vector<cl::Device> all_devices;
  status_ = platform_->getDevices(CL_DEVICE_TYPE_GPU, &all_devices);
  CL_CHECK_ERROR(status_);
  if (all_devices.empty()) {
    LOG(FATAL) << "No OpenCL GPU device found!";
    return false;
  }
  device_ = std::make_shared<cl::Device>();
  *device_ = all_devices[0];

  auto device_name = device_->getInfo<CL_DEVICE_NAME>();
  LOG(INFO) << "Using device: " << device_name;
176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274

  cl_device_type device_type = device_->getInfo<CL_DEVICE_TYPE>();
  auto device_type_to_str = [](cl_device_type t) -> std::string {
    std::string t_str{""};
    switch (t) {
      case CL_DEVICE_TYPE_CPU:
        t_str = "CPU";
        break;
      case CL_DEVICE_TYPE_GPU:
        t_str = "GPU";
        break;
      case CL_DEVICE_TYPE_ACCELERATOR:
        t_str = "Accelerator";
        break;
      case CL_DEVICE_TYPE_DEFAULT:
        t_str = "Default";
        break;
      default:
        t_str = "Unknown";
    }
    return t_str;
  };
  LOG(INFO) << "device_type:" << device_type_to_str(device_type);
  device_info_["CL_DEVICE_TYPE"] = device_type;

  auto max_units = device_->getInfo<CL_DEVICE_MAX_COMPUTE_UNITS>();
  LOG(INFO) << "The chosen device has " << max_units << " compute units.";
  device_info_["CL_DEVICE_MAX_COMPUTE_UNITS"] = max_units;

  auto max_clock_freq = device_->getInfo<CL_DEVICE_MAX_CLOCK_FREQUENCY>();
  LOG(INFO) << "CL_DEVICE_MAX_CLOCK_FREQUENCY:" << max_clock_freq;
  device_info_["CL_DEVICE_MAX_CLOCK_FREQUENCY"] = max_clock_freq;

  // ===================== MEMORY =====================
  // CL_DEVICE_LOCAL_MEM_SIZE
  // CL_DEVICE_GLOBAL_MEM_CACHE_SIZE
  // CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE
  // CL_DEVICE_GLOBAL_MEM_SIZE
  auto local_mem_kb =
      static_cast<float>(device_->getInfo<CL_DEVICE_LOCAL_MEM_SIZE>()) / 1024;
  LOG(INFO) << "The local memory size of the chosen device is " << local_mem_kb
            << " KB.";
  device_info_["CL_DEVICE_LOCAL_MEM_SIZE_KB"] = local_mem_kb;

  auto global_mem_cache_size_kb =
      static_cast<float>(device_->getInfo<CL_DEVICE_GLOBAL_MEM_CACHE_SIZE>()) /
      1024;
  LOG(INFO) << "CL_DEVICE_GLOBAL_MEM_CACHE_SIZE(KB):"
            << global_mem_cache_size_kb << " KB.";
  device_info_["CL_DEVICE_GLOBAL_MEM_CACHE_SIZE_KB"] = global_mem_cache_size_kb;

  auto global_mem_cacheline_size_kb =
      static_cast<float>(
          device_->getInfo<CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE>()) /
      1024;
  LOG(INFO) << "CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE(KB):"
            << global_mem_cacheline_size_kb << " KB.";
  device_info_["CL_DEVICE_GLOBAL_MEM_CACHELINE_SIZE_KB"] =
      global_mem_cacheline_size_kb;

  auto global_mem_size_kb =
      static_cast<float>(device_->getInfo<CL_DEVICE_GLOBAL_MEM_SIZE>()) / 1024;
  LOG(INFO) << "CL_DEVICE_GLOBAL_MEM_SIZE(KB):" << global_mem_size_kb << " KB.";
  device_info_["CL_DEVICE_GLOBAL_MEM_SIZE_KB"] = global_mem_size_kb;

  // ===================== WORK_GROUP =====================
  // CL_DEVICE_MAX_WORK_GROUP_SIZE
  // CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS
  // CL_DEVICE_MAX_WORK_ITEM_SIZES
  auto max_work_group_size = device_->getInfo<CL_DEVICE_MAX_WORK_GROUP_SIZE>();
  LOG(INFO) << "CL_DEVICE_MAX_WORK_GROUP_SIZE:" << max_work_group_size;
  device_info_["CL_DEVICE_MAX_WORK_GROUP_SIZE"] = max_work_group_size;

  auto max_dims_num = device_->getInfo<CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS>();
  LOG(INFO) << "CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS:" << max_dims_num;
  device_info_["CL_DEVICE_MAX_WORK_ITEM_DIMENSIONS"] = max_dims_num;

  auto max_work_item_sizes = device_->getInfo<CL_DEVICE_MAX_WORK_ITEM_SIZES>();
  for (size_t i = 0; i < max_work_item_sizes.size(); ++i) {
    LOG(INFO) << "max_work_item_sizes[" << i << "]:" << max_work_item_sizes[i];
    std::string dim_key = "CL_DEVICE_MAX_WORK_ITEM_SIZES_" + std::to_string(i);
    device_info_[dim_key] = max_work_item_sizes[i];
  }

  // ===================== BUFFER =====================
  // CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE
  auto max_constant_buffer_size_kb =
      static_cast<float>(
          device_->getInfo<CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE>()) /
      1024;
  LOG(INFO) << "CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE:"
            << max_constant_buffer_size_kb;
  device_info_["CL_DEVICE_MAX_CONSTANT_BUFFER_SIZE"] =
      max_constant_buffer_size_kb;

  // ===================== IMAGE =====================
  // CL_DEVICE_IMAGE_SUPPORT
  // CL_DEVICE_IMAGE2D_MAX_HEIGHT
  // CL_DEVICE_IMAGE2D_MAX_WIDTH
Y
Yan Chunwei 已提交
275 276 277
  auto image_support = device_->getInfo<CL_DEVICE_IMAGE_SUPPORT>();
  if (image_support) {
    LOG(INFO) << "The chosen device supports image processing.";
278
    device_info_["CL_DEVICE_IMAGE_SUPPORT"] = 1;
Y
Yan Chunwei 已提交
279 280
  } else {
    LOG(INFO) << "The chosen device doesn't support image processing!";
281
    device_info_["CL_DEVICE_IMAGE_SUPPORT"] = 0;
Y
Yan Chunwei 已提交
282 283
    return false;
  }
284 285 286 287 288 289 290 291 292 293 294 295

  auto image2d_max_height = device_->getInfo<CL_DEVICE_IMAGE2D_MAX_HEIGHT>();
  LOG(INFO) << "CL_DEVICE_IMAGE2D_MAX_HEIGHT:" << image2d_max_height;
  device_info_["CL_DEVICE_IMAGE2D_MAX_HEIGHT"] = image2d_max_height;

  auto image2d_max_width = device_->getInfo<CL_DEVICE_IMAGE2D_MAX_WIDTH>();
  LOG(INFO) << "CL_DEVICE_IMAGE2D_MAX_WIDTH:" << image2d_max_width;
  device_info_["CL_DEVICE_IMAGE2D_MAX_WIDTH"] = image2d_max_width;

  // ===================== OTHERS / EXTENSION / VERSION =====================
  // CL_DEVICE_EXTENSIONS
  // CL_DEVICE_ADDRESS_BITS
Y
Yan Chunwei 已提交
296 297 298 299
  auto ext_data = device_->getInfo<CL_DEVICE_EXTENSIONS>();
  VLOG(4) << "The extensions supported by this device: " << ext_data;
  if (ext_data.find("cl_khr_fp16") != std::string::npos) {
    LOG(INFO) << "The chosen device supports the half data type.";
300
    device_info_["CL_DEVICE_EXTENSIONS_FP16"] = 1;
Y
Yan Chunwei 已提交
301 302
  } else {
    LOG(INFO) << "The chosen device doesn't support the half data type!";
303
    device_info_["CL_DEVICE_EXTENSIONS_FP16"] = 0;
Y
Yan Chunwei 已提交
304
  }
305 306 307 308 309 310 311 312

  auto address_bits = device_->getInfo<CL_DEVICE_ADDRESS_BITS>();
  LOG(INFO) << "CL_DEVICE_ADDRESS_BITS:" << address_bits;
  device_info_["CL_DEVICE_ADDRESS_BITS"] = address_bits;

  auto driver_version = device_->getInfo<CL_DRIVER_VERSION>();
  LOG(INFO) << "CL_DRIVER_VERSION:" << driver_version;

Y
Yan Chunwei 已提交
313 314 315
  return true;
}

316 317 318 319 320 321 322 323
std::map<std::string, size_t>& CLRuntime::GetDeviceInfo() {
  if (0 != device_info_.size()) {
    return device_info_;
  }
  InitializeDevice();
  return device_info_;
}

Y
Yan Chunwei 已提交
324 325
}  // namespace lite
}  // namespace paddle