raver119 7783012f39
cuDNN integration (#150)
* initial commit

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* one file

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* few more includes

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* m?

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* const

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* cudnn linkage in tests

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* culibos

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* static reminder

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* platform engine tag

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* HAVE_CUDNN moved to config.h.in

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* include

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* include

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* skip cudnn handle creation if there's not cudnn

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* meh

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* target device in context

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* platform engines

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* platform engines

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* allow multiple -h args

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* allow multiple -h args

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* move mkldnn out of CPU block

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* link to mkldnn on cuda

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* less prints

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* minor tweaks

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* next step

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* conv2d NCHW draft

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* conv2d biasAdd

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* test for MKL/CUDNN combined use

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* - provide additional code for conv2d ff based on cudnn api, not tested yet

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* - further work on conv2d helper based on using cudnn api

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* - fixing several cuda bugs which appeared after cudnn lib had been started to use

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* - implementation of conv2d backprop op based on cudnn api

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* - implementaion of conv3d and conv3d_bp ops based on cudnn api

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* - bugs fixing in conv3d/conv3d_bp ops (cudnn in use)

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* - implementation of depthwiseConv2d (ff/bp) op based on cudnn api

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* - implementation of batchnorm ff op based on cudnn api

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* - disable cudnn batchnorm temporary

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* - add minor change in cmake

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* engine for depthwise mkldnn

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* couple of includes

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* - provide permutation to cudnn batchnorm ff when format is NHWC

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* lgamma fix

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* - eliminate memory leak in two tests

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Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
2020-01-20 21:32:46 +03:00

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/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
//
// @author raver119@gmail.com
//
#include <cublas_v2.h>
#include <cusolverDn.h>
#include "../cublasHelper.h"
#include <exceptions/cuda_exception.h>
#include <helpers/logger.h>
#include <execution/AffinityManager.h>
#include "config.h"
#ifdef HAVE_CUDNN
#include <cudnn.h>
#endif
namespace nd4j {
std::mutex CublasHelper::_mutex;
static void* handle_() {
auto _handle = new cublasHandle_t();
auto status = cublasCreate_v2(_handle); // initialize CUBLAS context
if (status != CUBLAS_STATUS_SUCCESS)
throw cuda_exception::build("cuBLAS handle creation failed !", status);
return reinterpret_cast<void *>(_handle);
}
static void* solver_() {
auto cusolverH = new cusolverDnHandle_t();
auto status = cusolverDnCreate(cusolverH);
if (status != CUSOLVER_STATUS_SUCCESS)
throw cuda_exception::build("cuSolver handle creation failed !", status);
return cusolverH;
}
static void* cudnn_() {
#ifdef HAVE_CUDNN
auto cudnnH = new cudnnHandle_t();
auto status = cudnnCreate(cudnnH);
if (status != CUDNN_STATUS_SUCCESS)
throw cuda_exception::build("cuDNN handle creation failed !", status);
return cudnnH;
#endif
return nullptr;
}
static void destroyHandle_(void* handle) {
auto ch = reinterpret_cast<cublasHandle_t *>(handle);
auto status = cublasDestroy_v2(*ch);
if (status != CUBLAS_STATUS_SUCCESS)
throw cuda_exception::build("cuBLAS handle destruction failed !", status);
delete ch;
}
CublasHelper::CublasHelper() {
//nd4j_printf("Initializing cuBLAS\n","");
auto numDevices = AffinityManager::numberOfDevices();
auto currentDevice = AffinityManager::currentDeviceId();
_cache.resize(numDevices);
_solvers.resize(numDevices);
_cudnn.resize(numDevices);
for (int e = 0; e < numDevices; e++) {
AffinityManager::setCurrentNativeDevice(e);
_cache[e] = handle_();
_solvers[e] = solver_();
_cudnn[e] = cudnn_();
}
// don't forget to restore back original device
AffinityManager::setCurrentNativeDevice(currentDevice);
}
CublasHelper::~CublasHelper() {
nd4j_printf("Releasing cuBLAS\n","");
auto numDevices = AffinityManager::numberOfDevices();
for (int e = 0; e < numDevices; e++)
destroyHandle_(_cache[e]);
}
CublasHelper* CublasHelper::getInstance() {
_mutex.lock();
if (!_INSTANCE)
_INSTANCE = new nd4j::CublasHelper();
_mutex.unlock();
return _INSTANCE;
}
void* CublasHelper::cudnn() {
auto deviceId = AffinityManager::currentDeviceId();
if (deviceId < 0 || deviceId > _cudnn.size())
throw cuda_exception::build("requested deviceId doesn't look valid", deviceId);
return _cudnn[deviceId];
}
void* CublasHelper::handle() {
auto deviceId = AffinityManager::currentDeviceId();
return handle(deviceId);
}
void* CublasHelper::solver() {
auto deviceId = AffinityManager::currentDeviceId();
if (deviceId < 0 || deviceId > _solvers.size())
throw cuda_exception::build("requested deviceId doesn't look valid", deviceId);
return _solvers[deviceId];
}
void* CublasHelper::handle(int deviceId) {
if (deviceId < 0 || deviceId > _cache.size())
throw cuda_exception::build("requested deviceId doesn't look valid", deviceId);
return _cache[deviceId];
}
nd4j::CublasHelper* nd4j::CublasHelper::_INSTANCE = 0;
}