MyCaffe.common.GPUParams< T > Class Template Reference

The GPUParams contains the connection to the low-level Cuda, and the stream associated with this instance. More...

Inheritance diagram for MyCaffe.common.GPUParams< T >:

Public Member Functions
	GPUParams (CudaDnn< T > cuda, Log log, Solver< T > root_solver, int nDeviceID)
	The GPUParams constructor. More...
void	Dispose ()
	Release all GPU and Host resources used. More...
void	SynchronizeStream ()
	Synchronize with the Cuda stream. More...
void	Configure (Solver< T > solver)
	Configure the GPU Params by copying the Solver training Net parameters into the data and diff buffers. More...
void	apply_buffers (BlobCollection< T > rgBlobs, long hBuffer, long lTotalSize, Op op)
	Transfer between the data/diff buffers and a collection of Blobs (e.g. the learnable parameters). More...
Public Member Functions inherited from MyCaffe.common.Params< T >
	Params (Solver< T > root_solver)
	The Param constructor. More...

Protected Attributes
CudaDnn< T >	m_cuda
	The instance of CudaDnn that provides the connection to Cuda. More...
Log	m_log
	The Log used for output. More...
long	m_hStream
	The handle to the Cuda stream used for synchronization. More...
Protected Attributes inherited from MyCaffe.common.Params< T >
long	m_lCount
	size of the buffers (in items). More...
long	m_lExtra
	size of the padding added to the memory buffers. More...
long	m_hData
	Handle to GPU memory containing the Net parameters. More...
long	m_hDiff
	Handle to GPU memory containing the Net gradient. More...
int	m_nDeviceID
	The Device ID. More...

Additional Inherited Members
Properties inherited from MyCaffe.common.Params< T >
long	count [get]
	Returns the size of the buffers (in items). More...
long	data [get]
	Returns the handle to the GPU memory containing the Net parameters. More...
long	diff [get]
	Returns the handle to the GPU memory containing the Net gradients. More...

Detailed Description

The GPUParams contains the connection to the low-level Cuda, and the stream associated with this instance.

Template Parameters

T	Specifies the base type float or double. Using float is recommended to conserve GPU memory.

Definition at line 103 of file Parallel.cs.

Constructor & Destructor Documentation

GPUParams()

MyCaffe.common.GPUParams< T >.GPUParams	(	CudaDnn< T >	cuda,
		Log	log,
		Solver< T >	root_solver,
		int	nDeviceID
	)

The GPUParams constructor.

Parameters

cuda	Specifies the CudaDnn connection to Cuda.
log	Specifies the Log for output.
root_solver	Specifies the root Solver.
nDeviceID	Specifies the device ID to use for this instance.

Definition at line 144 of file Parallel.cs.

Member Function Documentation

apply_buffers()

void MyCaffe.common.GPUParams< T >.apply_buffers	(	BlobCollection< T >	rgBlobs,
		long	hBuffer,
		long	lTotalSize,
		Op	op
	)

Transfer between the data/diff buffers and a collection of Blobs (e.g. the learnable parameters).

Parameters

rgBlobs	Specifies the collection of Blobs to transfer data with.
hBuffer	Specifies a handle to the memory on the GPU to transfer with the Blob collection.
lTotalSize	Specifies the number of items to transfer.
op	Specifies the type of transfer to perform.

Definition at line 221 of file Parallel.cs.

Configure()

void MyCaffe.common.GPUParams< T >.Configure

(

Solver< T >

solver

)

Configure the GPU Params by copying the Solver training Net parameters into the data and diff buffers.

Parameters

solver

Definition at line 207 of file Parallel.cs.

Dispose()

void MyCaffe.common.GPUParams< T >.Dispose

(

)

Release all GPU and Host resources used.

Definition at line 174 of file Parallel.cs.

SynchronizeStream()

void MyCaffe.common.GPUParams< T >.SynchronizeStream

(

)

Synchronize with the Cuda stream.

Definition at line 198 of file Parallel.cs.

Member Data Documentation

m_cuda

CudaDnn<T> MyCaffe.common.GPUParams< T >.m_cuda

protected

The instance of CudaDnn that provides the connection to Cuda.

Definition at line 108 of file Parallel.cs.

m_hStream

long MyCaffe.common.GPUParams< T >.m_hStream

protected

The handle to the Cuda stream used for synchronization.

Definition at line 116 of file Parallel.cs.

m_log

Log MyCaffe.common.GPUParams< T >.m_log

protected

The Log used for output.

Definition at line 112 of file Parallel.cs.

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

• C:/Data/Data/SS_Projects/Intelligence/GitHub/MyCaffe/MyCaffe/common/Parallel.cs