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paddlepaddle--paddle/paddle/cinn/runtime/cuda/cuda_module.cc
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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2021 CINN 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.
#include "paddle/cinn/runtime/cuda/cuda_module.h"
#include <cuda.h>
#include <cuda_runtime.h>
#include <glog/logging.h>
#include <glog/raw_logging.h>
#include <mutex> // NOLINT
#include <string>
#include <vector>
#include "paddle/cinn/backends/cuda_util.h"
#include "paddle/cinn/runtime/cuda/cuda_util.h"
#include "paddle/cinn/runtime/flags.h"
#include "paddle/cinn/utils/profiler.h"
#include "paddle/common/enforce.h"
namespace cinn {
namespace runtime {
namespace cuda {
CUDAModule::CUDAModule(const std::string& data, Kind kind)
: data_(data), kind_(kind) {
PADDLE_ENFORCE_NE(data.empty(),
true,
::common::errors::PreconditionNotMet("data is is empty!"));
cudaGetDeviceCount(&num_devices_);
PADDLE_ENFORCE_GT(
num_devices_,
0,
::common::errors::ResourceExhausted("No available devices!"));
// TODO(Superjomn) Determine whether to initialize all the devices.
int current_device_id;
cudaGetDevice(&current_device_id);
cudaSetDevice(current_device_id);
cuDeviceGet(&device_, current_device_id);
cuCtxGetCurrent(&context_);
cuDevicePrimaryCtxRetain(&context_, device_);
VLOG(5) << "Construct CUDAModule " << this
<< " in device: " << current_device_id;
}
void CUDAModule::LaunchKernel(int device_id,
const std::string& func_name,
dim3 gridDim,
dim3 blockDim,
void** args,
size_t share_memory_size,
CUstream stream) {
VLOG(3) << "cuLaunchKernel with func_name : " << func_name
<< ", gridDim.x:" << gridDim.x << ", gridDim.y:" << gridDim.y
<< ", gridDim.z:" << gridDim.z << ", blockDim.x:" << blockDim.x
<< ", blockDim.y:" << blockDim.y << ", blockDim.z:" << blockDim.z
<< ", share_memory_size:" << share_memory_size;
auto function = GetFunction(device_id, func_name);
PADDLE_ENFORCE_NOT_NULL(
function,
::common::errors::NotFound(
"%s function not found on device %d.", func_name, device_id));
cinn::utils::RecordEvent record_run("cuLaunchKernel",
cinn::utils::EventType::kInstruction);
CUDA_DRIVER_CALL(cuLaunchKernel(function,
gridDim.x,
gridDim.y,
gridDim.z,
blockDim.x,
blockDim.y,
blockDim.z,
share_memory_size,
stream,
args,
nullptr));
}
CUfunction CUDAModule::GetFunction(const std::string& func_name) {
int device_id;
cudaGetDevice(&device_id);
return this->GetFunction(device_id, func_name);
}
CUfunction CUDAModule::GetFunction(int device_id,
const std::string& func_name) {
VLOG(5) << "GetFunction : " << func_name << " with device_id : " << device_id;
cinn::utils::RecordEvent record_run("cuLaunchKernel",
cinn::utils::EventType::kOrdinary);
if (!module_per_card_[device_id]) {
std::lock_guard<std::mutex> lock(mutex_);
// Compilation with parameters
const size_t jit_num_options = 5;
std::vector<CUjit_option> jit_options(jit_num_options);
std::vector<void*> jit_opt_vals(jit_num_options);
// set up size of compilation log buffer
jit_options[0] = CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES;
size_t log_buffer_size = 1024;
jit_opt_vals[0] = reinterpret_cast<void*>(log_buffer_size);
// set up pointer to the compilation log buffer
jit_options[1] = CU_JIT_ERROR_LOG_BUFFER;
std::vector<char> log_buffer(log_buffer_size, '\0');
jit_opt_vals[1] = log_buffer.data();
int value = 1;
// Specifies whether to create debug information in output (-g)
jit_options[2] = CU_JIT_GENERATE_DEBUG_INFO;
jit_opt_vals[2] = reinterpret_cast<void*>(value);
// Generate verbose log messages
jit_options[3] = CU_JIT_LOG_VERBOSE;
jit_opt_vals[3] = reinterpret_cast<void*>(value);
// Generate line number information (-lineinfo)
jit_options[4] = CU_JIT_GENERATE_LINE_INFO;
jit_opt_vals[4] = reinterpret_cast<void*>(value);
if (runtime::CanUseNvccCompiler()) {
CUDA_DRIVER_CALL(
cuModuleLoad(&module_per_card_[device_id], data_.c_str()));
} else {
CUDA_DRIVER_CALL(cuModuleLoadDataEx(&module_per_card_[device_id],
data_.c_str(),
jit_num_options,
jit_options.data(),
jit_opt_vals.data()));
}
}
CUfunction func;
CUDA_DRIVER_CALL(cuModuleGetFunction(
&func, module_per_card_[device_id], func_name.c_str()));
return func;
}
CUdeviceptr CUDAModule::GetGlobal(int device_id,
const std::string& name,
size_t nbytes) {
if (!module_per_card_[device_id]) {
std::lock_guard<std::mutex> lock(mutex_);
if (runtime::CanUseNvccCompiler()) {
CUDA_DRIVER_CALL(
cuModuleLoad(&module_per_card_[device_id], data_.c_str()));
} else {
CUDA_DRIVER_CALL(
cuModuleLoadData(&module_per_card_[device_id], data_.c_str()));
}
}
size_t _nbytes;
CUdeviceptr global;
CUDA_DRIVER_CALL(cuModuleGetGlobal(
&global, &_nbytes, module_per_card_[device_id], name.c_str()));
return global;
}
CUDAModule::~CUDAModule() {
for (int i = 0; i < module_per_card_.size(); i++) {
auto* module = module_per_card_[i];
if (module) {
CUDA_CALL(cudaSetDevice(i));
CUDA_DRIVER_CALL(cuModuleUnload(module));
}
}
}
} // namespace cuda
} // namespace runtime
} // namespace cinn