* initial commit Signed-off-by: raver119 <raver119@gmail.com> * one file Signed-off-by: raver119 <raver119@gmail.com> * few more includes Signed-off-by: raver119 <raver119@gmail.com> * m? Signed-off-by: raver119 <raver119@gmail.com> * const Signed-off-by: raver119 <raver119@gmail.com> * cudnn linkage in tests Signed-off-by: raver119 <raver119@gmail.com> * culibos Signed-off-by: raver119 <raver119@gmail.com> * static reminder Signed-off-by: raver119 <raver119@gmail.com> * platform engine tag Signed-off-by: raver119 <raver119@gmail.com> * HAVE_CUDNN moved to config.h.in Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * include Signed-off-by: raver119 <raver119@gmail.com> * skip cudnn handle creation if there's not cudnn Signed-off-by: raver119 <raver119@gmail.com> * meh Signed-off-by: raver119 <raver119@gmail.com> * target device in context Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * platform engines Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * allow multiple -h args Signed-off-by: raver119 <raver119@gmail.com> * move mkldnn out of CPU block Signed-off-by: raver119 <raver119@gmail.com> * link to mkldnn on cuda Signed-off-by: raver119 <raver119@gmail.com> * less prints Signed-off-by: raver119 <raver119@gmail.com> * minor tweaks Signed-off-by: raver119 <raver119@gmail.com> * next step Signed-off-by: raver119 <raver119@gmail.com> * conv2d NCHW draft Signed-off-by: raver119 <raver119@gmail.com> * conv2d biasAdd Signed-off-by: raver119 <raver119@gmail.com> * test for MKL/CUDNN combined use Signed-off-by: raver119 <raver119@gmail.com> * - provide additional code for conv2d ff based on cudnn api, not tested yet Signed-off-by: Yurii <iuriish@yahoo.com> * - further work on conv2d helper based on using cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - fixing several cuda bugs which appeared after cudnn lib had been started to use Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of conv2d backprop op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementaion of conv3d and conv3d_bp ops based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - bugs fixing in conv3d/conv3d_bp ops (cudnn in use) Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of depthwiseConv2d (ff/bp) op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - implementation of batchnorm ff op based on cudnn api Signed-off-by: Yurii <iuriish@yahoo.com> * - disable cudnn batchnorm temporary Signed-off-by: Yurii <iuriish@yahoo.com> * - add minor change in cmake Signed-off-by: Yurii <iuriish@yahoo.com> * engine for depthwise mkldnn Signed-off-by: raver119 <raver119@gmail.com> * couple of includes Signed-off-by: raver119 <raver119@gmail.com> * - provide permutation to cudnn batchnorm ff when format is NHWC Signed-off-by: Yurii <iuriish@yahoo.com> * lgamma fix Signed-off-by: raver119 <raver119@gmail.com> * - eliminate memory leak in two tests Signed-off-by: Yurii <iuriish@yahoo.com> Co-authored-by: Yurii Shyrma <iuriish@yahoo.com>
298 lines
11 KiB
Plaintext
298 lines
11 KiB
Plaintext
/*******************************************************************************
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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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// CUDA workspaces implementation
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//
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// @author raver119@gmail.com
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//
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#include <op_boilerplate.h>
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#include <atomic>
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#include <stdio.h>
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#include <stdlib.h>
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#include "../Workspace.h"
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#include <helpers/logger.h>
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#include <templatemath.h>
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#include <cstring>
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#include <cuda_exception.h>
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#include <cuda.h>
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#include <cuda_runtime.h>
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namespace nd4j {
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namespace memory {
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Workspace::Workspace(ExternalWorkspace *external) {
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if (external->sizeHost() > 0) {
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_ptrHost = (char *) external->pointerHost();
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_ptrDevice = (char *) external->pointerDevice();
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_initialSize = external->sizeDevice();
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_currentSize = external->sizeDevice();
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_initialSizeSecondary = external->sizeHost();
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_currentSizeSecondary = external->sizeHost();
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_offset = 0L;
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_offsetSecondary = 0L;
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this->_cycleAllocations = 0;
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this->_cycleAllocationsSecondary = 0;
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this->_spillsSize = 0;
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this->_spillsSizeSecondary = 0;
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_externalized = true;
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}
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}
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Workspace::Workspace(Nd4jLong primarySize, Nd4jLong secondarySize) {
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if (secondarySize > 0) {
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auto res = cudaHostAlloc(reinterpret_cast<void **>(&_ptrHost), secondarySize, cudaHostAllocDefault);
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if (res != 0)
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throw cuda_exception::build("Can't allocate [HOST] memory", res);
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cudaMemset(this->_ptrHost, 0, secondarySize);
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this->_allocatedHost = true;
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} else
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this->_allocatedHost = false;
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if (primarySize > 0) {
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auto res = cudaMalloc(reinterpret_cast<void **>(&_ptrDevice), primarySize);
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if (res != 0)
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throw cuda_exception::build("Can't allocate [DEVICE] memory", res);
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cudaMemset(this->_ptrDevice, 0, primarySize);
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this->_allocatedDevice = true;
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} else
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this->_allocatedDevice = false;
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this->_initialSize = primarySize;
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this->_initialSizeSecondary = secondarySize;
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this->_currentSize = primarySize;
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this->_currentSizeSecondary = secondarySize;
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this->_offset = 0;
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this->_offsetSecondary = 0;
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this->_cycleAllocations = 0;
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this->_spillsSize = 0;
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this->_spillsSizeSecondary = 0;
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}
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void Workspace::init(Nd4jLong primaryBytes, Nd4jLong secondaryBytes) {
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if (this->_currentSize < primaryBytes) {
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if (this->_allocatedDevice && !_externalized)
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cudaFree((void *)this->_ptrDevice);
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auto res = cudaMalloc(reinterpret_cast<void **>(&_ptrDevice), secondaryBytes);
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if (res != 0)
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throw cuda_exception::build("Can't allocate [DEVICE] memory", res);
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cudaMemset(this->_ptrDevice, 0, primaryBytes);
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this->_currentSize = primaryBytes;
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this->_allocatedDevice = true;
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}
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if (this->_currentSizeSecondary < secondaryBytes) {
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if (this->_allocatedHost && !_externalized)
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cudaFreeHost((void *)this->_ptrHost);
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auto res = cudaHostAlloc(reinterpret_cast<void **>(&_ptrHost), secondaryBytes, cudaHostAllocDefault);
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if (res != 0)
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throw cuda_exception::build("Can't allocate [HOST] memory", res);
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cudaMemset(this->_ptrHost, 0, secondaryBytes);
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this->_currentSizeSecondary = secondaryBytes;
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this->_allocatedHost = true;
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}
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}
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void Workspace::expandBy(Nd4jLong numBytes, Nd4jLong secondaryBytes) {
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this->init(_currentSize + numBytes, _currentSizeSecondary + secondaryBytes);
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}
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void Workspace::expandTo(Nd4jLong numBytes, Nd4jLong secondaryBytes) {
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this->init(numBytes, secondaryBytes);
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}
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void Workspace::freeSpills() {
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_spillsSize = 0;
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_spillsSizeSecondary = 0;
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for (auto v:_spills)
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cudaFree(v);
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for (auto v:_spillsSecondary)
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cudaFreeHost(v);
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_spills.clear();
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_spillsSecondary.clear();
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}
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Workspace::~Workspace() {
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if (this->_allocatedHost && !_externalized)
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cudaFreeHost((void *)this->_ptrHost);
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if (this->_allocatedDevice && !_externalized)
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cudaFree((void *)this->_ptrDevice);
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freeSpills();
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}
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Nd4jLong Workspace::getUsedSize() {
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return getCurrentOffset();
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}
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Nd4jLong Workspace::getCurrentSize() {
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return _currentSize;
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}
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Nd4jLong Workspace::getCurrentOffset() {
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return _offset.load();
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}
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void* Workspace::allocateBytes(Nd4jLong numBytes) {
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return allocateBytes(nd4j::memory::MemoryType::HOST, numBytes);
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}
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Nd4jLong Workspace::getAllocatedSize() {
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return getCurrentSize() + getSpilledSize();
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}
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void Workspace::scopeIn() {
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freeSpills();
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init(_cycleAllocations.load());
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_cycleAllocations = 0;
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}
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void Workspace::scopeOut() {
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_offset = 0;
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}
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Nd4jLong Workspace::getSpilledSize() {
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return _spillsSize.load();
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}
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void* Workspace::allocateBytes(nd4j::memory::MemoryType type, Nd4jLong numBytes) {
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switch (type) {
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case HOST: {
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if (numBytes < 1)
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throw allocation_exception::build("Number of [HOST] bytes for allocation should be positive", numBytes);
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//numBytes += 32;
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void* result = nullptr;
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this->_cycleAllocationsSecondary += numBytes;
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this->_mutexAllocation.lock();
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if (_offsetSecondary.load() + numBytes > _currentSizeSecondary) {
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nd4j_debug("Allocating %lld [HOST] bytes in spills\n", numBytes);
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this->_mutexAllocation.unlock();
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Nd4jPointer p;
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auto res = cudaHostAlloc(reinterpret_cast<void **>(&p), numBytes, cudaHostAllocDefault);
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if (res != 0)
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throw cuda_exception::build("Can't allocate [HOST] memory", res);
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_mutexSpills.lock();
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_spillsSecondary.push_back(p);
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_mutexSpills.unlock();
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_spillsSizeSecondary += numBytes;
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return p;
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}
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result = (void *)(_ptrHost + _offsetSecondary.load());
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_offsetSecondary += numBytes;
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//memset(result, 0, (int) numBytes);
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nd4j_debug("Allocating %lld bytes from [HOST] workspace; Current PTR: %p; Current offset: %lld\n", numBytes, result, _offset.load());
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this->_mutexAllocation.unlock();
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return result;
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}
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break;
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case DEVICE: {
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if (numBytes < 1)
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throw allocation_exception::build("Number of [DEVICE] bytes for allocation should be positive", numBytes);
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//numBytes += 32;
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void* result = nullptr;
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this->_cycleAllocations += numBytes;
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this->_mutexAllocation.lock();
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if (_offset.load() + numBytes > _currentSize) {
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nd4j_debug("Allocating %lld [DEVICE] bytes in spills\n", numBytes);
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this->_mutexAllocation.unlock();
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Nd4jPointer p;
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auto res = cudaMalloc(reinterpret_cast<void **>(&p), numBytes);
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if (res != 0)
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throw cuda_exception::build("Can't allocate [DEVICE] memory", res);
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_mutexSpills.lock();
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_spills.push_back(p);
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_mutexSpills.unlock();
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_spillsSize += numBytes;
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return p;
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}
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result = (void *)(_ptrDevice + _offset.load());
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_offset += numBytes;
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//memset(result, 0, (int) numBytes);
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nd4j_debug("Allocating %lld bytes from [DEVICE] workspace; Current PTR: %p; Current offset: %lld\n", numBytes, result, _offset.load());
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this->_mutexAllocation.unlock();
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return result;
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}
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break;
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default:
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throw std::runtime_error("Unknown MemoryType was passed in");
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}
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}
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Workspace* Workspace::clone() {
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// for clone we take whatever is higher: current allocated size, or allocated size of current loop
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return new Workspace(nd4j::math::nd4j_max<Nd4jLong >(this->getCurrentSize(), this->_cycleAllocations.load()));
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}
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Nd4jLong Workspace::getAllocatedSecondarySize() {
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return getCurrentSecondarySize() + getSpilledSecondarySize();
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}
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Nd4jLong Workspace::getCurrentSecondarySize() {
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return _currentSizeSecondary;
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}
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Nd4jLong Workspace::getCurrentSecondaryOffset() {
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return _offsetSecondary.load();
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}
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Nd4jLong Workspace::getSpilledSecondarySize() {
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return _spillsSizeSecondary;
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}
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Nd4jLong Workspace::getUsedSecondarySize() {
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return getCurrentSecondaryOffset();
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}
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}
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}
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