mindspore2022/mindspore/ccsrc/device/gpu/gpu_buffer_mgr.h

142 lines
4.1 KiB
C++

/**
* Copyright 2019 Huawei Technologies Co., Ltd
*
* 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.
*/
#ifndef MINDSPORE_CCSRC_DEVICE_GPU_GPU_BUFFER_MGR_H_
#define MINDSPORE_CCSRC_DEVICE_GPU_GPU_BUFFER_MGR_H_
#include <unistd.h>
#include <cstring>
#include <iostream>
#include <functional>
#include <map>
#include <string>
#include <memory>
#include "device/gpu/blocking_queue.h"
#define EXPORT __attribute__((visibility("default")))
namespace mindspore {
namespace device {
static const unsigned int MAX_WAIT_TIME_IN_SEC = 60;
class Semaphore {
public:
explicit Semaphore(int count = 0) : count_(count) {}
inline void Signal() {
std::unique_lock<std::mutex> lock(mutex_);
++count_;
cv_.notify_one();
}
inline bool Wait() {
std::unique_lock<std::mutex> lock(mutex_);
while (count_ == 0) {
if (cv_.wait_for(lock, std::chrono::seconds(MAX_WAIT_TIME_IN_SEC)) == std::cv_status::timeout) {
return false;
}
}
--count_;
return true;
}
private:
std::mutex mutex_;
std::condition_variable cv_;
int count_;
};
class HandleMgr {
public:
static const unsigned int MAX_HANDLE_NUM = 32;
static const unsigned int INVALID_HANDLE = 0xffffffffUL;
unsigned int AllocHandle();
void FreeHandle(unsigned int);
private:
bool handle_list_[MAX_HANDLE_NUM];
};
class GpuBufferMgr {
public:
EXPORT GpuBufferMgr() : cur_dev_id_(0), init_(false), closed_(false), open_by_dataset_(0) {}
EXPORT virtual ~GpuBufferMgr() = default;
EXPORT static GpuBufferMgr &GetInstance() noexcept;
EXPORT BlockQueueStatus_T Create(unsigned int device_id, const std::string &channel_name, void *addr,
const size_t &feature_len, const size_t &label_size, const size_t &capacity);
// call for Push thread
EXPORT unsigned int Open(unsigned int device_id, const std::string &channel_name, const size_t &feature_len,
const size_t &label_size, std::function<void(void *)> func);
// call for Front/Pop thread
EXPORT unsigned int Open(unsigned int device_id, const std::string &channel_name, const size_t &feature_len,
const size_t &label_size);
EXPORT BlockQueueStatus_T Push(unsigned int handle, void *feature_addr, size_t feature_size, void *label_addr,
size_t label_size, unsigned int timeout_in_sec);
EXPORT BlockQueueStatus_T Front(unsigned int handle, void **feature_addr, size_t *feature_size, void **label_addr,
size_t *label_size);
EXPORT BlockQueueStatus_T Pop(unsigned int handle);
EXPORT void set_device_id(int device_id);
EXPORT void Close(unsigned int handle) noexcept;
EXPORT bool IsInit() const;
EXPORT bool IsClosed() const;
EXPORT bool Destroy();
// call for Release GPU Resources
EXPORT bool CloseNotify();
// call for dataset send thread
EXPORT void CloseConfirm();
private:
void set_device() const;
int cur_dev_id_;
bool init_;
bool closed_;
std::mutex mutex_;
std::mutex close_mutex_;
std::condition_variable close_confirm_cond_;
// how many queues opened by dataset
int open_by_dataset_;
Semaphore sema;
HandleMgr handle_mgr_;
std::map<unsigned int, std::shared_ptr<BlockingQueue>> handle_queue_map_;
std::map<std::string, std::shared_ptr<BlockingQueue>> name_queue_map_;
inline bool isCreated(unsigned int device_id, const std::string &channel_name);
GpuBufferMgr(const GpuBufferMgr &) = delete;
GpuBufferMgr &operator=(const GpuBufferMgr &) = delete;
};
} // namespace device
} // namespace mindspore
#endif // MINDSPORE_CCSRC_DEVICE_GPU_GPU_BUFFER_MGR_H_