示例#1
0
// Enqueues a kernel, waits for completion, and checks for errors
void RunKernel(Kernel &kernel, Queue &queue, const Device &device,
               std::vector<size_t> global, const std::vector<size_t> &local,
               EventPointer event, const std::vector<Event> &waitForEvents) {

  if (!local.empty()) {
    // Tests for validity of the local thread sizes
    if (local.size() > device.MaxWorkItemDimensions()) {
      throw RuntimeErrorCode(StatusCode::kInvalidLocalNumDimensions);
    }
    const auto max_work_item_sizes = device.MaxWorkItemSizes();
    for (auto i=size_t{0}; i<local.size(); ++i) {
      if (local[i] > max_work_item_sizes[i]) {
        throw RuntimeErrorCode(StatusCode::kInvalidLocalThreadsDim);
      }
    }
    auto local_size = size_t{1};
    for (auto &item: local) { local_size *= item; }
    if (local_size > device.MaxWorkGroupSize()) {
      throw RuntimeErrorCode(StatusCode::kInvalidLocalThreadsTotal);
    }

    // Make sure the global thread sizes are at least equal to the local sizes
    for (auto i=size_t{0}; i<global.size(); ++i) {
      if (global[i] < local[i]) { global[i] = local[i]; }
    }
  }

  // Tests for local memory usage
  const auto local_mem_usage = kernel.LocalMemUsage(device);
  if (!device.IsLocalMemoryValid(local_mem_usage)) {
    throw RuntimeErrorCode(StatusCode::kInvalidLocalMemUsage);
  }

  // Prints the name of the kernel to launch in case of debugging in verbose mode
  #ifdef VERBOSE
    queue.Finish();
    printf("[DEBUG] Running kernel '%s'\n", kernel.GetFunctionName().c_str());
    const auto start_time = std::chrono::steady_clock::now();
  #endif

  // Launches the kernel (and checks for launch errors)
  kernel.Launch(queue, global, local, event, waitForEvents);

  // Prints the elapsed execution time in case of debugging in verbose mode
  #ifdef VERBOSE
    queue.Finish();
    const auto elapsed_time = std::chrono::steady_clock::now() - start_time;
    const auto timing = std::chrono::duration<double,std::milli>(elapsed_time).count();
    printf("[DEBUG] Completed kernel in %.2lf ms\n", timing);
  #endif
}
示例#2
0
文件: database.hpp 项目: gpu/CLBlast
 // Retrieves a parameter from the database
 size_t operator[](const std::string &key) const {
   for (const auto &kernel_name : kernel_names_) {
     const auto &kernel_db = databases_.find(kernel_name)->second;
     if (kernel_db.exists(key)) { return kernel_db[key]; }
   }
   throw RuntimeErrorCode(StatusCode::kDatabaseError);
 }
示例#3
0
void Routine::InitProgram(std::initializer_list<const char *> source) {

  // Determines the identifier for this particular routine call
  auto routine_info = routine_name_;
  for (const auto &kernel_name : kernel_names_) {
    routine_info += "_" + kernel_name + db_(kernel_name).GetValuesString();
  }
  log_debug(routine_info);

  // Queries the cache to see whether or not the program (context-specific) is already there
  bool has_program;
  program_ = ProgramCache::Instance().Get(ProgramKeyRef{ context_(), device_(), precision_, routine_info },
                                          &has_program);
  if (has_program) { return; }

  // Sets the build options from an environmental variable (if set)
  auto options = std::vector<std::string>();
  const auto environment_variable = std::getenv("CLBLAST_BUILD_OPTIONS");
  if (environment_variable != nullptr) {
    options.push_back(std::string(environment_variable));
  }

  // Queries the cache to see whether or not the binary (device-specific) is already there. If it
  // is, a program is created and stored in the cache
  const auto device_name = GetDeviceName(device_);
  const auto platform_id = device_.PlatformID();
  bool has_binary;
  auto binary = BinaryCache::Instance().Get(BinaryKeyRef{platform_id,  precision_, routine_info, device_name },
                                            &has_binary);
  if (has_binary) {
    program_ = std::make_shared<Program>(device_, context_, binary);
    program_->Build(device_, options);
    ProgramCache::Instance().Store(ProgramKey{ context_(), device_(), precision_, routine_info },
                                    std::shared_ptr<Program>{program_});
    return;
  }

  // Otherwise, the kernel will be compiled and program will be built. Both the binary and the
  // program will be added to the cache.

  // Inspects whether or not FP64 is supported in case of double precision
  if ((precision_ == Precision::kDouble && !PrecisionSupported<double>(device_)) ||
      (precision_ == Precision::kComplexDouble && !PrecisionSupported<double2>(device_))) {
    throw RuntimeErrorCode(StatusCode::kNoDoublePrecision);
  }

  // As above, but for FP16 (half precision)
  if (precision_ == Precision::kHalf && !PrecisionSupported<half>(device_)) {
    throw RuntimeErrorCode(StatusCode::kNoHalfPrecision);
  }

  // Collects the parameters for this device in the form of defines
  auto source_string = std::string{""};
  for (const auto &kernel_name : kernel_names_) {
    source_string += db_(kernel_name).GetDefines();
  }

  // Adds routine-specific code to the constructed source string
  for (const char *s: source) {
    source_string += s;
  }

  // Completes the source and compiles the kernel
  program_ = CompileFromSource(source_string, precision_, routine_name_,
                               device_, context_, options, 0);


  // Store the compiled binary and program in the cache
  BinaryCache::Instance().Store(BinaryKey{platform_id, precision_, routine_info, device_name},
                                program_->GetIR());

  ProgramCache::Instance().Store(ProgramKey{context_(), device_(), precision_, routine_info},
                                 std::shared_ptr<Program>{program_});
}