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fix cuda::BufferPool deinitialization

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The deinitialization of BufferPool internal objects is controled by global
object, but it depends on other global objects, which leads to errors
caused by undefined deinitialization order of global objects.

I merge global objects initialization into single class, which performs
initialization and deinitialization in correct order.
pull/3523/head
Vladislav Vinogradov 10 years ago
parent fd6ef87c32
commit 7ed38b97c3
3 changed files with 466 additions and 458 deletions
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  1. 1
      modules/core/include/opencv2/core/cuda.hpp
  2. 435
      modules/core/src/cuda_buffer_pool.cpp
  3. 488
      modules/core/src/cuda_stream.cpp

1
modules/core/include/opencv2/core/cuda.hpp
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@ -479,6 +479,7 @@ private:
friend struct StreamAccessor;
friend class BufferPool;
friend class DefaultDeviceInitializer;
};
class CV_EXPORTS Event

435
modules/core/src/cuda_buffer_pool.cpp
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@ -1,435 +0,0 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
using namespace cv;
using namespace cv::cuda;
#ifdef HAVE_CUDA
#include "opencv2/cudev/common.hpp"
/////////////////////////////////////////////////////////////
/// MemoryStack
namespace
{
class MemoryPool;
}
class cv::cuda::MemoryStack
{
public:
uchar* requestMemory(size_t size);
void returnMemory(uchar* ptr);
uchar* datastart;
uchar* dataend;
uchar* tip;
bool isFree;
MemoryPool* pool;
#if defined(DEBUG) || defined(_DEBUG)
std::vector<size_t> allocations;
#endif
};
uchar* cv::cuda::MemoryStack::requestMemory(size_t size)
{
const size_t freeMem = dataend - tip;
if (size > freeMem)
return 0;
uchar* ptr = tip;
tip += size;
#if defined(DEBUG) || defined(_DEBUG)
allocations.push_back(size);
#endif
return ptr;
}
void cv::cuda::MemoryStack::returnMemory(uchar* ptr)
{
CV_DbgAssert( ptr >= datastart && ptr < dataend );
#if defined(DEBUG) || defined(_DEBUG)
const size_t allocSize = tip - ptr;
CV_Assert( allocSize == allocations.back() );
allocations.pop_back();
#endif
tip = ptr;
}
/////////////////////////////////////////////////////////////
/// MemoryPool
namespace
{
class MemoryPool
{
public:
MemoryPool();
void initialize(size_t stackSize, int stackCount);
void release();
MemoryStack* getFreeMemStack();
void returnMemStack(MemoryStack* memStack);
private:
void initilizeImpl();
Mutex mtx_;
bool initialized_;
size_t stackSize_;
int stackCount_;
uchar* mem_;
std::vector<MemoryStack> stacks_;
};
MemoryPool::MemoryPool() : initialized_(false), mem_(0)
{
// default : 10 Mb, 5 stacks
stackSize_ = 10 * 1024 * 1024;
stackCount_ = 5;
}
void MemoryPool::initialize(size_t stackSize, int stackCount)
{
AutoLock lock(mtx_);
release();
stackSize_ = stackSize;
stackCount_ = stackCount;
initilizeImpl();
}
void MemoryPool::initilizeImpl()
{
const size_t totalSize = stackSize_ * stackCount_;
if (totalSize > 0)
{
cudaError_t err = cudaMalloc(&mem_, totalSize);
if (err != cudaSuccess)
return;
stacks_.resize(stackCount_);
uchar* ptr = mem_;
for (int i = 0; i < stackCount_; ++i)
{
stacks_[i].datastart = ptr;
stacks_[i].dataend = ptr + stackSize_;
stacks_[i].tip = ptr;
stacks_[i].isFree = true;
stacks_[i].pool = this;
ptr += stackSize_;
}
initialized_ = true;
}
}
void MemoryPool::release()
{
if (mem_)
{
#if defined(DEBUG) || defined(_DEBUG)
for (int i = 0; i < stackCount_; ++i)
{
CV_DbgAssert( stacks_[i].isFree );
CV_DbgAssert( stacks_[i].tip == stacks_[i].datastart );
}
#endif
cudaFree( mem_ );
mem_ = 0;
initialized_ = false;
}
}
MemoryStack* MemoryPool::getFreeMemStack()
{
AutoLock lock(mtx_);
if (!initialized_)
initilizeImpl();
if (!mem_)
return 0;
for (int i = 0; i < stackCount_; ++i)
{
if (stacks_[i].isFree)
{
stacks_[i].isFree = false;
return &stacks_[i];
}
}
return 0;
}
void MemoryPool::returnMemStack(MemoryStack* memStack)
{
AutoLock lock(mtx_);
CV_DbgAssert( !memStack->isFree );
#if defined(DEBUG) || defined(_DEBUG)
bool found = false;
for (int i = 0; i < stackCount_; ++i)
{
if (memStack == &stacks_[i])
{
found = true;
break;
}
}
CV_DbgAssert( found );
#endif
CV_DbgAssert( memStack->tip == memStack->datastart );
memStack->isFree = true;
}
}
/////////////////////////////////////////////////////////////
/// MemoryPoolManager
namespace
{
Mutex mtx_;
bool memory_pool_manager_initialized;
class MemoryPoolManager
{
public:
MemoryPoolManager();
~MemoryPoolManager();
void Init();
MemoryPool* getPool(int deviceId);
private:
std::vector<MemoryPool> pools_;
} manager;
//MemoryPoolManager ;
MemoryPoolManager::MemoryPoolManager()
{
}
void MemoryPoolManager::Init()
{
int deviceCount = getCudaEnabledDeviceCount();
if (deviceCount > 0)
pools_.resize(deviceCount);
}
MemoryPoolManager::~MemoryPoolManager()
{
for (size_t i = 0; i < pools_.size(); ++i)
{
cudaSetDevice(static_cast<int>(i));
pools_[i].release();
}
}
MemoryPool* MemoryPoolManager::getPool(int deviceId)
{
CV_DbgAssert( deviceId >= 0 && deviceId < static_cast<int>(pools_.size()) );
return &pools_[deviceId];
}
MemoryPool* memPool(int deviceId)
{
{
AutoLock lock(mtx_);
if (!memory_pool_manager_initialized)
{
memory_pool_manager_initialized = true;
manager.Init();
}
}
return manager.getPool(deviceId);
}
}
/////////////////////////////////////////////////////////////
/// StackAllocator
namespace
{
bool enableMemoryPool = true;
}
cv::cuda::StackAllocator::StackAllocator(cudaStream_t stream) : stream_(stream), memStack_(0)
{
if (enableMemoryPool)
{
const int deviceId = getDevice();
{
AutoLock lock(mtx_);
memStack_ = memPool(deviceId)->getFreeMemStack();
}
DeviceInfo devInfo(deviceId);
alignment_ = devInfo.textureAlignment();
}
}
cv::cuda::StackAllocator::~StackAllocator()
{
cudaStreamSynchronize(stream_);
if (memStack_ != 0)
memStack_->pool->returnMemStack(memStack_);
}
namespace
{
size_t alignUp(size_t what, size_t alignment)
{
size_t alignMask = alignment-1;
size_t inverseAlignMask = ~alignMask;
size_t res = (what + alignMask) & inverseAlignMask;
return res;
}
}
bool cv::cuda::StackAllocator::allocate(GpuMat* mat, int rows, int cols, size_t elemSize)
{
if (memStack_ == 0)
return false;
size_t pitch, memSize;
if (rows > 1 && cols > 1)
{
pitch = alignUp(cols * elemSize, alignment_);
memSize = pitch * rows;
}
else
{
// Single row or single column must be continuous
pitch = elemSize * cols;
memSize = alignUp(elemSize * cols * rows, 64);
}
uchar* ptr = memStack_->requestMemory(memSize);
if (ptr == 0)
return false;
mat->data = ptr;
mat->step = pitch;
mat->refcount = (int*) fastMalloc(sizeof(int));
return true;
}
void cv::cuda::StackAllocator::free(GpuMat* mat)
{
if (memStack_ == 0)
return;
memStack_->returnMemory(mat->datastart);
fastFree(mat->refcount);
}
void cv::cuda::setBufferPoolUsage(bool on)
{
enableMemoryPool = on;
}
void cv::cuda::setBufferPoolConfig(int deviceId, size_t stackSize, int stackCount)
{
const int currentDevice = getDevice();
if (deviceId >= 0)
{
setDevice(deviceId);
memPool(deviceId)->initialize(stackSize, stackCount);
}
else
{
const int deviceCount = getCudaEnabledDeviceCount();
for (deviceId = 0; deviceId < deviceCount; ++deviceId)
{
setDevice(deviceId);
memPool(deviceId)->initialize(stackSize, stackCount);
}
}
setDevice(currentDevice);
}
/////////////////////////////////////////////////////////////
/// BufferPool
GpuMat cv::cuda::BufferPool::getBuffer(int rows, int cols, int type)
{
GpuMat buf(allocator_);
buf.create(rows, cols, type);
return buf;
}
#endif

488
modules/core/src/cuda_stream.cpp
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@ -45,8 +45,217 @@
using namespace cv;
using namespace cv::cuda;
/////////////////////////////////////////////////////////////
/// MemoryStack
#ifdef HAVE_CUDA
namespace
{
class MemoryPool;
}
class cv::cuda::MemoryStack
{
public:
uchar* requestMemory(size_t size);
void returnMemory(uchar* ptr);
uchar* datastart;
uchar* dataend;
uchar* tip;
bool isFree;
MemoryPool* pool;
#if !defined(NDEBUG)
std::vector<size_t> allocations;
#endif
};
uchar* cv::cuda::MemoryStack::requestMemory(size_t size)
{
const size_t freeMem = dataend - tip;
if (size > freeMem)
return 0;
uchar* ptr = tip;
tip += size;
#if !defined(NDEBUG)
allocations.push_back(size);
#endif
return ptr;
}
void cv::cuda::MemoryStack::returnMemory(uchar* ptr)
{
CV_DbgAssert( ptr >= datastart && ptr < dataend );
#if !defined(NDEBUG)
const size_t allocSize = tip - ptr;
CV_Assert( allocSize == allocations.back() );
allocations.pop_back();
#endif
tip = ptr;
}
#endif
/////////////////////////////////////////////////////////////
/// MemoryPool
#ifdef HAVE_CUDA
namespace
{
class MemoryPool
{
public:
MemoryPool();
void initialize(size_t stackSize, int stackCount);
void release();
MemoryStack* getFreeMemStack();
void returnMemStack(MemoryStack* memStack);
private:
void initilizeImpl();
Mutex mtx_;
bool initialized_;
size_t stackSize_;
int stackCount_;
uchar* mem_;
std::vector<MemoryStack> stacks_;
};
MemoryPool::MemoryPool() : initialized_(false), mem_(0)
{
// default : 10 Mb, 5 stacks
stackSize_ = 10 * 1024 * 1024;
stackCount_ = 5;
}
void MemoryPool::initialize(size_t stackSize, int stackCount)
{
AutoLock lock(mtx_);
release();
stackSize_ = stackSize;
stackCount_ = stackCount;
initilizeImpl();
}
void MemoryPool::initilizeImpl()
{
const size_t totalSize = stackSize_ * stackCount_;
if (totalSize > 0)
{
cudaError_t err = cudaMalloc(&mem_, totalSize);
if (err != cudaSuccess)
return;
stacks_.resize(stackCount_);
uchar* ptr = mem_;
for (int i = 0; i < stackCount_; ++i)
{
stacks_[i].datastart = ptr;
stacks_[i].dataend = ptr + stackSize_;
stacks_[i].tip = ptr;
stacks_[i].isFree = true;
stacks_[i].pool = this;
ptr += stackSize_;
}
initialized_ = true;
}
}
void MemoryPool::release()
{
if (mem_)
{
#if !defined(NDEBUG)
for (int i = 0; i < stackCount_; ++i)
{
CV_DbgAssert( stacks_[i].isFree );
CV_DbgAssert( stacks_[i].tip == stacks_[i].datastart );
}
#endif
cudaFree(mem_);
mem_ = 0;
initialized_ = false;
}
}
MemoryStack* MemoryPool::getFreeMemStack()
{
AutoLock lock(mtx_);
if (!initialized_)
initilizeImpl();
if (!mem_)
return 0;
for (int i = 0; i < stackCount_; ++i)
{
if (stacks_[i].isFree)
{
stacks_[i].isFree = false;
return &stacks_[i];
}
}
return 0;
}
void MemoryPool::returnMemStack(MemoryStack* memStack)
{
AutoLock lock(mtx_);
CV_DbgAssert( !memStack->isFree );
#if !defined(NDEBUG)
bool found = false;
for (int i = 0; i < stackCount_; ++i)
{
if (memStack == &stacks_[i])
{
found = true;
break;
}
}
CV_DbgAssert( found );
#endif
CV_DbgAssert( memStack->tip == memStack->datastart );
memStack->isFree = true;
}
}
#endif
////////////////////////////////////////////////////////////////
// Stream
/// Stream::Impl
#ifndef HAVE_CUDA
@ -74,10 +283,6 @@ public:
~Impl();
};
cv::cuda::BufferPool::BufferPool(Stream& stream) : allocator_(stream.impl_->stackAllocator_.get())
{
}
cv::cuda::Stream::Impl::Impl() : stream(0)
{
cudaSafeCall( cudaStreamCreate(&stream) );
@ -98,13 +303,120 @@ cv::cuda::Stream::Impl::~Impl()
cudaStreamDestroy(stream);
}
cudaStream_t cv::cuda::StreamAccessor::getStream(const Stream& stream)
#endif
/////////////////////////////////////////////////////////////
/// DefaultDeviceInitializer
#ifdef HAVE_CUDA
namespace cv { namespace cuda
{
return stream.impl_->stream;
}
class DefaultDeviceInitializer
{
public:
DefaultDeviceInitializer();
~DefaultDeviceInitializer();
Stream& getNullStream(int deviceId);
MemoryPool* getMemoryPool(int deviceId);
private:
void initStreams();
void initPools();
Mutex streams_mtx_;
volatile bool streams_initialized_;
Mutex pools_mtx_;
volatile bool pools_initialized_;
std::vector<Ptr<Stream> > streams_;
std::vector<MemoryPool> pools_;
};
DefaultDeviceInitializer::DefaultDeviceInitializer()
{
}
DefaultDeviceInitializer::~DefaultDeviceInitializer()
{
streams_.clear();
for (size_t i = 0; i < pools_.size(); ++i)
{
cudaSetDevice(static_cast<int>(i));
pools_[i].release();
}
pools_.clear();
}
Stream& DefaultDeviceInitializer::getNullStream(int deviceId)
{
initStreams();
CV_DbgAssert( deviceId >= 0 && deviceId < static_cast<int>(streams_.size()) );
return *streams_[deviceId];
}
MemoryPool* DefaultDeviceInitializer::getMemoryPool(int deviceId)
{
initPools();
CV_DbgAssert( deviceId >= 0 && deviceId < static_cast<int>(pools_.size()) );
return &pools_[deviceId];
}
void DefaultDeviceInitializer::initStreams()
{
AutoLock lock(streams_mtx_);
if (!streams_initialized_)
{
int deviceCount = getCudaEnabledDeviceCount();
if (deviceCount > 0)
{
streams_.resize(deviceCount);
for (int i = 0; i < deviceCount; ++i)
{
cudaStream_t stream = NULL;
Ptr<Stream::Impl> impl = makePtr<Stream::Impl>(stream);
streams_[i] = Ptr<Stream>(new Stream(impl));
}
}
streams_initialized_ = true;
}
}
void DefaultDeviceInitializer::initPools()
{
AutoLock lock(pools_mtx_);
if (!pools_initialized_)
{
int deviceCount = getCudaEnabledDeviceCount();
if (deviceCount > 0)
pools_.resize(deviceCount);
pools_initialized_ = true;
}
}
DefaultDeviceInitializer initializer;
}}
#endif
/////////////////////////////////////////////////////////////
/// Stream
cv::cuda::Stream::Stream()
{
#ifndef HAVE_CUDA
@ -181,7 +493,7 @@ void cv::cuda::Stream::enqueueHostCallback(StreamCallback callback, void* userDa
#if CUDART_VERSION < 5000
(void) callback;
(void) userData;
CV_Error(cv::Error::StsNotImplemented, "This function requires CUDA 5.0");
CV_Error(cv::Error::StsNotImplemented, "This function requires CUDA >= 5.0");
#else
CallbackData* data = new CallbackData(callback, userData);
@ -190,22 +502,16 @@ void cv::cuda::Stream::enqueueHostCallback(StreamCallback callback, void* userDa
#endif
}
namespace
{
bool default_stream_is_initialized;
Mutex mtx;
Ptr<Stream> default_stream;
}
Stream& cv::cuda::Stream::Null()
{
AutoLock lock(mtx);
if (!default_stream_is_initialized)
{
default_stream = Ptr<Stream>(new Stream(Ptr<Impl>(new Impl(0))));
default_stream_is_initialized = true;
}
return *default_stream;
#ifndef HAVE_CUDA
throw_no_cuda();
static Stream stream;
return stream;
#else
const int deviceId = getDevice();
return initializer.getNullStream(deviceId);
#endif
}
cv::cuda::Stream::operator bool_type() const
@ -217,6 +523,142 @@ cv::cuda::Stream::operator bool_type() const
#endif
}
#ifdef HAVE_CUDA
cudaStream_t cv::cuda::StreamAccessor::getStream(const Stream& stream)
{
return stream.impl_->stream;
}
#endif
/////////////////////////////////////////////////////////////
/// StackAllocator
#ifdef HAVE_CUDA
namespace
{
bool enableMemoryPool = true;
}
cv::cuda::StackAllocator::StackAllocator(cudaStream_t stream) : stream_(stream), memStack_(0)
{
if (enableMemoryPool)
{
const int deviceId = getDevice();
memStack_ = initializer.getMemoryPool(deviceId)->getFreeMemStack();
DeviceInfo devInfo(deviceId);
alignment_ = devInfo.textureAlignment();
}
}
cv::cuda::StackAllocator::~StackAllocator()
{
cudaStreamSynchronize(stream_);
if (memStack_ != 0)
memStack_->pool->returnMemStack(memStack_);
}
namespace
{
size_t alignUp(size_t what, size_t alignment)
{
size_t alignMask = alignment-1;
size_t inverseAlignMask = ~alignMask;
size_t res = (what + alignMask) & inverseAlignMask;
return res;
}
}
bool cv::cuda::StackAllocator::allocate(GpuMat* mat, int rows, int cols, size_t elemSize)
{
if (memStack_ == 0)
return false;
size_t pitch, memSize;
if (rows > 1 && cols > 1)
{
pitch = alignUp(cols * elemSize, alignment_);
memSize = pitch * rows;
}
else
{
// Single row or single column must be continuous
pitch = elemSize * cols;
memSize = alignUp(elemSize * cols * rows, 64);
}
uchar* ptr = memStack_->requestMemory(memSize);
if (ptr == 0)
return false;
mat->data = ptr;
mat->step = pitch;
mat->refcount = (int*) fastMalloc(sizeof(int));
return true;
}
void cv::cuda::StackAllocator::free(GpuMat* mat)
{
if (memStack_ == 0)
return;
memStack_->returnMemory(mat->datastart);
fastFree(mat->refcount);
}
void cv::cuda::setBufferPoolUsage(bool on)
{
enableMemoryPool = on;
}
void cv::cuda::setBufferPoolConfig(int deviceId, size_t stackSize, int stackCount)
{
const int currentDevice = getDevice();
if (deviceId >= 0)
{
setDevice(deviceId);
initializer.getMemoryPool(deviceId)->initialize(stackSize, stackCount);
}
else
{
const int deviceCount = getCudaEnabledDeviceCount();
for (deviceId = 0; deviceId < deviceCount; ++deviceId)
{
setDevice(deviceId);
initializer.getMemoryPool(deviceId)->initialize(stackSize, stackCount);
}
}
setDevice(currentDevice);
}
#endif
/////////////////////////////////////////////////////////////
/// BufferPool
#ifdef HAVE_CUDA
cv::cuda::BufferPool::BufferPool(Stream& stream) : allocator_(stream.impl_->stackAllocator_.get())
{
}
GpuMat cv::cuda::BufferPool::getBuffer(int rows, int cols, int type)
{
GpuMat buf(allocator_);
buf.create(rows, cols, type);
return buf;
}
#endif
////////////////////////////////////////////////////////////////
// Event

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