MNN/source/backend/opencl/core/runtime/OpenCLRuntime.hpp

216 lines
6.6 KiB
C++

//
// OpenCLRuntime.hpp
// MNN
//
// Created by MNN on 2019/01/31.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef OpenCLRuntime_hpp
#define OpenCLRuntime_hpp
#include <map>
#include <memory>
#include <mutex>
#include <set>
#include <string>
#include <vector>
#include <string>
#include <vector>
#include "core/Macro.h"
#include "Type_generated.h"
#include "backend/opencl/core/runtime/OpenCLWrapper.hpp"
#include "MNN/MNNForwardType.h"
namespace MNN {
#define CL_CONTEXT_PERF_HINT_QCOM 0x40C2
#define CL_PERF_HINT_HIGH_QCOM 0x40C3
#define CL_PERF_HINT_NORMAL_QCOM 0x40C4
#define CL_PERF_HINT_LOW_QCOM 0x40C5
#define CL_CONTEXT_PRIORITY_HINT_QCOM 0x40C9
#define CL_PRIORITY_HINT_HIGH_QCOM 0x40CA
#define CL_PRIORITY_HINT_NORMAL_QCOM 0x40CB
#define CL_PRIORITY_HINT_LOW_QCOM 0x40CC
#define CL_KERNEL_WAVE_SIZE_QCOM 0xAA02
enum GpuType { MALI = 0, ADRENO = 1, RADEON = 2, INTEL = 3, OTHER = 4 };
enum MaliAr { MIDGARD = 0, BIFROST = 1, VALHALL = 2 };
enum GpuMemObject { AUTO = 0, BUFFER = 1, IMAGE = 2};
enum CLTuneLevel { None = 0, Heavy = 1, Wide = 2, Normal = 3, Fast = 4};
enum SvmType { FINE_BUFFER = 0, COARSE_BUFFER = 1, SVM_NONE = 2};
class OpenCLRuntime {
public:
OpenCLRuntime(const BackendConfig::PrecisionMode precision, const int cl_mode, int platformSize, int platformId, int deviceId);
~OpenCLRuntime();
OpenCLRuntime(const OpenCLRuntime &) = delete;
OpenCLRuntime &operator=(const OpenCLRuntime &) = delete;
bool isSupportedFP16() const;
bool isWeightCpuTransHalf() const;
bool isDeviceSupportedFP16() const;
bool isDeviceSupportedLowPower() const;
bool isSupportedDotInt8() const;
bool isSupportedDotAccInt8() const;
bool isSupportedIntelSubgroup() const;
::cl::Context &context();
::cl::CommandQueue &commandQueue();
::cl::CommandQueue &recordableQueue();
uint64_t deviceGlobalMemeryCacheSize() const;
uint32_t deviceComputeUnits() const;
uint32_t MaxThreadsPerDevice() const;
uint32_t MaxWorkGroupSize() const;
uint32_t maxFreq() const;
uint64_t getMaxWorkGroupSize(const ::cl::Kernel &kernel);
uint64_t GetKernelWaveSize(const cl::Kernel &kernel);
std::vector<uint32_t> getMaxWorkItemSizes();
uint64_t getMaxLocalMem() const;
std::vector<cl_recording_qcom> *getRecordings(){
return &mRecordings;
}
uint32_t getUseRecordableQueueSize(){
return mUseRecordableQueueSize;
}
bool isUseRecordQueue(){
return mUseRecordQueue;
}
bool isDevideOpRecord(){
return mDevideOpRecord;
}
void setDevideOpRecord(){
mDevideOpRecord = true;
}
void setRecordNum(int num){
mRecordNums = num;
}
uint32_t getRecordNum(){
return mRecordNums;
}
GpuType getGpuType() {
return mGpuType;
}
MaliAr getMaliAr() {
return mMaliAr;
}
float getCLVersion() {
return mCLVersion;
}
#ifdef MNN_OPENCL_SVM_ENABLE
cl_device_svm_capabilities getSvmCapabilities() {
return mSvmCapabilities;
}
#endif
GpuMemObject getGpuMemType() {
return mMemType;
}
CLTuneLevel getCLTuneLevel() {
return mTuneLevel;
}
std::string getDeviceName() {
return mDeviceName;
}
void pushEvent(std::pair<std::string, cl::Event> data) {
return mEvents.push_back(data);
}
void printEventTime();
void clearEvent(){
mKernelTime = 0;
mEvents.clear();
}
uint64_t maxAllocSize() const;
void setCommandQueueProfileEnable();
void setCommandQueueProfileDisable();
void clearRecord();
void enqeueRecord();
void endRecord();
void releaseRecord();
unsigned int mQueueCount = 0;
unsigned int getQueueNum();
unsigned int mKernelTime = 0;
std::map<std::pair<std::string, std::vector<uint32_t>>, std::pair<std::vector<uint32_t>, uint32_t>>& tunedLwsMap();
::cl::Kernel buildKernel(const std::string &programName, const std::string &kernelName,
const std::set<std::string> &buildOptions);
::cl::Kernel buildKernelFromSource(const std::string&, const std::string &kernelName,
const std::set<std::string> &buildOptions);
std::vector<size_t> getMaxImage2DSize();
bool isCreateError() const {
return mIsCreateError;
}
float flops() const {
return mFlops;
}
double getCostTime(const cl::Event *event);
double getQueuedTime(const cl::Event *event);
double getSubmitTime(const cl::Event *event);
std::pair<const void*, size_t> makeCache(void* tuneInfo);
bool setCache(std::pair<const void*, size_t> cache);
private:
bool loadProgram(const std::string &programName, cl::Program *program);
bool buildProgram(const std::string &buildOptionsStr, cl::Program *program);
bool getDeviceSupportsExtension(const cl::Device &device, const char *extensionName);
void setGpuMode(const int cl_mode_num);
private:
std::shared_ptr<::cl::Context> mContext;
std::shared_ptr<::cl::Device> mFirstGPUDevicePtr;
std::shared_ptr<::cl::CommandQueue> mCommandQueuePtr;
std::map<std::tuple<std::string, std::string>, ::cl::Program> mBuildProgramMap;
std::shared_ptr<::cl::CommandQueue> mRecordableQueuePtr;
std::vector<cl_recording_qcom> mRecordings;
uint64_t mGPUGlobalMemeryCacheSize;
uint32_t mGPUComputeUnits;
uint32_t mMaxFreq;
uint32_t mMaxMemAllocSize;
uint64_t mMaxLocalMemSize;
uint32_t mMaxThreadsPerDevice;
uint32_t mMaxWorkGroupSize;
uint32_t mUseRecordableQueueSize;
uint32_t mRecordNums = 0;
bool mUseRecordQueue = false;
bool mDevideOpRecord = true;
bool mIsSupportedFP16 = false;
bool mIsDeviceSupportedFP16 = false;
bool mIsDeviceSupportedLowPower = false;
bool mSupportDotInt8 = false;
bool mSupportDotAccInt8 = false;
bool mSupportedIntelSubgroup = false;
GpuType mGpuType;
MaliAr mMaliAr;
float mCLVersion = 1.0f;
std::vector<std::pair<std::string, cl::Event>> mEvents;
#ifdef MNN_OPENCL_SVM_ENABLE
cl_device_svm_capabilities mSvmCapabilities;
#endif
GpuMemObject mMemType = AUTO;
CLTuneLevel mTuneLevel = Wide;
std::string mDeviceName;
bool isSetWorkGroupAttribute = false;
std::string mDefaultBuildParams;
float mFlops = 4.0f;
bool mIsCreateError{false};
double mStartNanos;
double mStopNanos;
std::map<std::pair<std::string, std::vector<uint32_t>>, std::pair<std::vector<uint32_t>, uint32_t>> mTunedLws;
std::vector<uint8_t> mBuffer;
const void* mCacheOutside = nullptr;
size_t mCacheOutsideSize = 0;
};
} // namespace MNN
#endif /* OpenCLRuntime_hpp */