niftk::CUDAManager Class Reference

Inheritance diagram for niftk::CUDAManager:

Collaboration diagram for niftk::CUDAManager:

Public Member Functions
ScopedCUDADevice	ActivateDevice (int dev)
cudaStream_t	GetStream (const std::string &name)
ReadAccessor	RequestReadAccess (const LightweightCUDAImage &lwci)
WriteAccessor	RequestOutputImage (unsigned int width, unsigned int height, int FIXME_pixeltype)
LightweightCUDAImage	Finalise (WriteAccessor &writeAccessor, cudaStream_t stream)
LightweightCUDAImage	FinaliseAndAutorelease (WriteAccessor &writeAccessor, ReadAccessor &readAccessor, cudaStream_t stream)
void	Autorelease (ReadAccessor &readAccessor, cudaStream_t stream)
void	Autorelease (WriteAccessor &writeAccessor, cudaStream_t stream)

Static Public Member Functions
static CUDAManager *	GetInstance ()

Protected Member Functions
	CUDAManager ()
virtual	~CUDAManager ()
void	AllRefsDropped (LightweightCUDAImage &lwci)

Friends
class	LightweightCUDAImage
struct	impldetail::ModuleCleanup

Detailed Description

Singleton that owns all CUDA resources. It manages images in a copy-on-write like fashion: you cannot write into an existing CUDA-image, you can only read from these and write data into a newly allocated one.

To get access to an image living on the card, do the usual DataNode::GetData(), and a cast to CUDAImage. Then call CUDAImage::GetLightweightCUDAImage() to retrieve a handle to the actual bits in CUDA-memory. Side note: even though LightweightCUDAImage has members you should consider it opaque.

This LightweightCUDAImage instance you can use with RequestReadAccess() to obtain a device pointer that you can read from in your kernel. RequestReadAccess() will increment a reference count for that image so that CUDAManager will not recycle it too early.

Then call RequestOutputImage() to get a device pointer to where you can write your kernel's output. From an API point of view, RequestOutputImage() will always give you a new memory block so that you never overwrite an existing image.

Call GetStream() with your favourite name, or create your own stream, for synchronising and coarse-grain parallelising CUDA tasks.

Run your kernel on your stream. But do not synchronise on its completion!

When all your work has been submitted to the driver, call FinaliseAndAutorelease() to turn the output device pointer into a proper LightweightCUDAImage that you can stick onto a DataNode. This function will also release your read-request on the input image at the right time so that it can be eventually returned to the memory pool. In addition, Finalise*() functions will queue a "ready" event that you can use on your stream to GPU-synchronise on completion of a previous processing step.

CUDAManager is thread-safe: all public methods can be called from any thread at any time.

Constructor & Destructor Documentation

niftk::CUDAManager::CUDAManager ( )

protected

niftk::CUDAManager::~CUDAManager ( )

protectedvirtual

Member Function Documentation

ScopedCUDADevice niftk::CUDAManager::ActivateDevice

(

int

dev

)

void niftk::CUDAManager::AllRefsDropped ( LightweightCUDAImage &  lwci )

protected

Used by LightweightCUDAImage to notify us that all references to it have been dropped, and that it can be placed back onto m_AvailableImagePool for later re-use.

void niftk::CUDAManager::Autorelease	(	ReadAccessor &	readAccessor,
		cudaStream_t	stream
	)

Releases the read-request of an image once processing on stream has finished. This method does not block, it will return immediately. Make sure you call this method after Finalise(), or use FinaliseAndAutorelease().

void niftk::CUDAManager::Autorelease	(	WriteAccessor &	writeAccessor,
		cudaStream_t	stream
	)

LightweightCUDAImage niftk::CUDAManager::Finalise	(	WriteAccessor &	writeAccessor,
		cudaStream_t	stream
	)

LightweightCUDAImage niftk::CUDAManager::FinaliseAndAutorelease	(	WriteAccessor &	writeAccessor,
		ReadAccessor &	readAccessor,
		cudaStream_t	stream
	)

Combines Finalise() and Autorelease() into a single call.

CUDAManager * niftk::CUDAManager::GetInstance ( )

static

Exceptions

std::runtime_error

if CUDA is not available on the system.

cudaStream_t niftk::CUDAManager::GetStream

(

const std::string &

name

)

WriteAccessor niftk::CUDAManager::RequestOutputImage	(	unsigned int	width,
		unsigned int	height,
		int	FIXME_pixeltype
	)

ReadAccessor niftk::CUDAManager::RequestReadAccess

(

const LightweightCUDAImage &

lwci

)

Exceptions

std::runtime_error

if lwci is not valid.

Friends And Related Function Documentation

friend struct impldetail::ModuleCleanup

friend

friend class LightweightCUDAImage

friend

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The documentation for this class was generated from the following files:

• niftkCUDAManager.h
• niftkCUDAManager.cxx