136 lines
3.6 KiB
C++
136 lines
3.6 KiB
C++
/*******************************************************************************
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* Copyright (c) 2015-2018 Skymind, Inc.
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*
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* This program and the accompanying materials are made available under the
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* terms of the Apache License, Version 2.0 which is available at
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* https://www.apache.org/licenses/LICENSE-2.0.
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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* License for the specific language governing permissions and limitations
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* under the License.
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*
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* SPDX-License-Identifier: Apache-2.0
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******************************************************************************/
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//
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// Created by raver119 on 30.11.17.
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//
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#ifndef LIBND4J_CUDACONTEXT_H
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#define LIBND4J_CUDACONTEXT_H
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#ifdef __CUDABLAS__
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#include <cuda.h>
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#include <cuda_runtime_api.h>
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#include <cuda_runtime.h>
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#include <cuda_device_runtime_api.h>
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#include "config.h"
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#endif
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// used for MKLDNN etc
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#if !defined(__STANDALONE_BUILD__)
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#include "config.h"
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#endif
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#include <system/dll.h>
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#include <memory>
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#include <system/op_boilerplate.h>
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#include <memory/Workspace.h>
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#include <vector>
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#include <mutex>
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#include <execution/ContextBuffers.h>
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#include <execution/ErrorReference.h>
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namespace sd {
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class ND4J_EXPORT LaunchContext {
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private:
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static std::vector<std::shared_ptr<LaunchContext>> _contexts;
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static std::mutex _mutex;
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static MAP_IMPL<int, std::mutex*> _deviceMutexes;
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// used for MKLDNN
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void *_engine = nullptr;
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#ifdef __CUDABLAS__
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#ifndef __JAVACPP_HACK__
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void* _cublasHandle = nullptr;
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void* _cusolverHandle = nullptr;
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#endif // JCPP
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bool _isAllocated = false;
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#endif // CUDA
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sd::memory::Workspace* _workspace = nullptr;
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int _deviceID = 0;
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public:
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#ifdef __CUDABLAS__
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#ifndef __JAVACPP_HACK__
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LaunchContext(cudaStream_t* cudaStream, cudaStream_t& specialCudaStream, void* reductionPointer = nullptr, void* scalarPointer = nullptr, int* allocationPointer = nullptr);
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void* getReductionPointer () const;
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void* getScalarPointer() const;
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int* getAllocationPointer() const;
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void* getCublasHandle() const;
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void* getCusolverHandle() const;
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void* getCuDnnHandle() const;
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cudaStream_t* getCudaStream() const;
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cudaStream_t* getCudaSpecialStream() const;
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void setReductionPointer (void* reductionPointer);
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void setScalarPointer(void* scalarPointer);
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void setAllocationPointer(int* allocationPointer);
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void setCudaStream(cudaStream_t* cudaStream);
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void setCudaSpecialStream(cudaStream_t* cudaStream);
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void setCublasHandle(void *handle);
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#endif // JCPP
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#endif // CUDA
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LaunchContext(Nd4jPointer cudaStream, Nd4jPointer reductionPointer = nullptr, Nd4jPointer scalarPointer = nullptr, Nd4jPointer allocationPointer = nullptr);
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LaunchContext();
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~LaunchContext();
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sd::memory::Workspace* getWorkspace() const { return _workspace; }
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void setWorkspace(sd::memory::Workspace* theWorkspace) {
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_workspace = theWorkspace;
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}
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void* engine();
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int getDeviceID() const {return _deviceID;}
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void setDeviceID(int deviceID) { _deviceID = deviceID; }
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sd::ErrorReference* errorReference();
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#ifndef __JAVACPP_HACK__
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// this method returns mutex shared between all threads that use the same device
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static std::mutex* deviceMutex();
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#endif
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static bool isInitialized();
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static void releaseBuffers();
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static LaunchContext* defaultContext();
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static void swapContextBuffers(ContextBuffers &buffers);
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};
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}
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#endif //LIBND4J_CUDACONTEXT_H
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