The GpuSparseMatrixGeneric class uses cuSPARSE Generic API for sparse matrix operations. More...

#include <GpuSparseMatrixGeneric.hpp>

Public Types
using	field_type = T

Public Member Functions
	GpuSparseMatrixGeneric (const T nonZeroElements, const int rowIndices, const int *columnIndices, size_t numberOfNonzeroBlocks, size_t blockSize, size_t numberOfRows)

	GpuSparseMatrixGeneric (const GpuVector< int > &rowIndices, const GpuVector< int > &columnIndices, size_t blockSize)

	GpuSparseMatrixGeneric (const GpuSparseMatrixGeneric &)

void	preprocessSpMV ()
	Preprocess SpMV operation to optimize for sparsity pattern. More...

GpuSparseMatrixGeneric &	operator= (const GpuSparseMatrixGeneric &)=delete

virtual	~GpuSparseMatrixGeneric ()

size_t	N () const
	N returns the number of rows (which is equal to the number of columns) More...

size_t	nonzeroes () const
	nonzeroes behaves as the Dune::BCRSMatrix::nonzeros() function and returns the number of non zero blocks More...

GpuVector< T > &	getNonZeroValues ()
	getNonZeroValues returns the GPU vector containing the non-zero values (ordered by block) More...

const GpuVector< T > &	getNonZeroValues () const
	getNonZeroValues returns the GPU vector containing the non-zero values (ordered by block) More...

GpuVector< int > &	getRowIndices ()
	getRowIndices returns the row indices used to represent the BSR structure. More...

const GpuVector< int > &	getRowIndices () const
	getRowIndices returns the row indices used to represent the BSR structure. More...

GpuVector< int > &	getColumnIndices ()
	getColumnIndices returns the column indices used to represent the BSR structure. More...

const GpuVector< int > &	getColumnIndices () const
	getColumnIndices returns the column indices used to represent the BSR structure. More...

size_t	dim () const
	dim returns the dimension of the vector space on which this matrix acts More...

size_t	blockSize () const
	blockSize size of the blocks More...

virtual void	mv (const GpuVector< T > &x, GpuVector< T > &y) const
	mv performs matrix vector multiply y = Ax More...

virtual void	umv (const GpuVector< T > &x, GpuVector< T > &y) const
	umv computes y=Ax+y More...

virtual void	usmv (T alpha, const GpuVector< T > &x, GpuVector< T > &y) const
	umv computes y=alpha * Ax + y More...

template<class MatrixType >
void	updateNonzeroValues (const MatrixType &matrix, bool copyNonZeroElementsDirectly=false)
	updateNonzeroValues updates the non-zero values by using the non-zero values of the supplied matrix More...

void	updateNonzeroValues (const GpuSparseMatrixGeneric< T > &matrix)
	updateNonzeroValues updates the non-zero values by using the non-zero values of the supplied matrix More...

template<class FunctionType >
auto	dispatchOnBlocksize (FunctionType function) const
	Dispatches a function based on the block size of the matrix. More...

Static Public Member Functions
template<class MatrixType >
static GpuSparseMatrixGeneric< T >	fromMatrix (const MatrixType &matrix, bool copyNonZeroElementsDirectly=false)
	fromMatrix creates a new matrix with the same block size and values as the given matrix More...

Static Public Attributes
static constexpr int	max_block_size = 6
	Maximum block size supported by this implementation. More...

Detailed Description

template<typename T>
class Opm::gpuistl::GpuSparseMatrixGeneric< T >

The GpuSparseMatrixGeneric class uses cuSPARSE Generic API for sparse matrix operations.

Note: We support raw primitives for T (double and float). Block size is handled through the blockSize parameter.

Template Parameters

T	the type to store. Can be either float or double.

Note: we only support square matrices.

Member Typedef Documentation

◆ field_type

template<typename T >

using Opm::gpuistl::GpuSparseMatrixGeneric< T >::field_type = T

Constructor & Destructor Documentation

◆ GpuSparseMatrixGeneric() [1/3]

template<typename T >

Opm::gpuistl::GpuSparseMatrixGeneric< T >::GpuSparseMatrixGeneric	(	const T *	nonZeroElements,
		const int *	rowIndices,
		const int *	columnIndices,
		size_t	numberOfNonzeroBlocks,
		size_t	blockSize,
		size_t	numberOfRows
	)

Create the sparse matrix specified by the raw data.

Parameters

[in]	nonZeroElements	the non-zero values of the matrix
[in]	rowIndices	the row indices of the non-zero elements
[in]	columnIndices	the column indices of the non-zero elements
[in]	numberOfNonzeroBlocks	number of nonzero elements
[in]	blockSize	size of each block matrix (typically 3)
[in]	numberOfRows	the number of rows

◆ GpuSparseMatrixGeneric() [2/3]

template<typename T >

Opm::gpuistl::GpuSparseMatrixGeneric< T >::GpuSparseMatrixGeneric	(	const GpuVector< int > &	rowIndices,
		const GpuVector< int > &	columnIndices,
		size_t	blockSize
	)

Create a sparse matrix by copying the sparsity structure of another matrix, not filling in the values

Parameters

[in]	rowIndices	the row indices of the non-zero elements
[in]	columnIndices	the column indices of the non-zero elements
[in]	blockSize	size of each block matrix (typically 3)

◆ GpuSparseMatrixGeneric() [3/3]

template<typename T >

Opm::gpuistl::GpuSparseMatrixGeneric< T >::GpuSparseMatrixGeneric ( const GpuSparseMatrixGeneric< T > & )

◆ ~GpuSparseMatrixGeneric()

template<typename T >

virtual Opm::gpuistl::GpuSparseMatrixGeneric< T >::~GpuSparseMatrixGeneric ( )

virtual

Member Function Documentation

◆ blockSize()

template<typename T >

size_t Opm::gpuistl::GpuSparseMatrixGeneric< T >::blockSize ( ) const

inline

blockSize size of the blocks

References Opm::gpuistl::detail::to_size_t().

◆ dim()

template<typename T >

size_t Opm::gpuistl::GpuSparseMatrixGeneric< T >::dim ( ) const

inline

dim returns the dimension of the vector space on which this matrix acts

This is equivalent to matrix.N() * matrix.blockSize()

Returns: matrix.N() * matrix.blockSize()

References Opm::gpuistl::detail::to_size_t().

◆ dispatchOnBlocksize()

template<typename T >

template<class FunctionType >

auto Opm::gpuistl::GpuSparseMatrixGeneric< T >::dispatchOnBlocksize ( FunctionType function ) const

inline

Dispatches a function based on the block size of the matrix.

This method allows executing different code paths depending on the block size of the matrix, up to the maximum block size specified by max_block_size.

Use this function if you need the block size to be known at compile time.

Template Parameters

FunctionType Type of the function to be dispatched

Parameters

function The function to be executed based on the block size

Returns: The result of the function execution

You can use this function as

matrix.dispatchOnBlocksize([](auto val) {
   constexpr int blockSize = decltype(val)::value;
});

◆ fromMatrix()

template<typename T >

template<class MatrixType >

static GpuSparseMatrixGeneric< T > Opm::gpuistl::GpuSparseMatrixGeneric< T >::fromMatrix	(	const MatrixType &	matrix,
		bool	copyNonZeroElementsDirectly = `false`
	)

static

fromMatrix creates a new matrix with the same block size and values as the given matrix

Parameters

matrix	the matrix to copy from
copyNonZeroElementsDirectly	if true will do a memcpy from matrix[0][0][0][0], otherwise will build up the non-zero elements by looping over the matrix. Note that setting this to true will yield a performance increase, but might not always yield correct results depending on how the matrix has been initialized. If unsure, leave it as false.

Template Parameters

MatrixType is assumed to be a Dune::BCRSMatrix compatible matrix.

◆ getColumnIndices() [1/2]

template<typename T >

GpuVector< int > & Opm::gpuistl::GpuSparseMatrixGeneric< T >::getColumnIndices ( )

inline

getColumnIndices returns the column indices used to represent the BSR structure.

Returns: Read the CuSPARSE documentation on Block Compressed Sparse Row Format (BSR) for the exact ordering.

◆ getColumnIndices() [2/2]

template<typename T >

const GpuVector< int > & Opm::gpuistl::GpuSparseMatrixGeneric< T >::getColumnIndices ( ) const

inline

getColumnIndices returns the column indices used to represent the BSR structure.

Returns: Read the CuSPARSE documentation on Block Compressed Sparse Row Format (BSR) for the exact ordering.

◆ getNonZeroValues() [1/2]

template<typename T >

GpuVector< T > & Opm::gpuistl::GpuSparseMatrixGeneric< T >::getNonZeroValues ( )

inline

getNonZeroValues returns the GPU vector containing the non-zero values (ordered by block)

Note: Read the CuSPARSE documentation on Block Compressed Sparse Row Format (BSR) for the exact ordering.

◆ getNonZeroValues() [2/2]

template<typename T >

const GpuVector< T > & Opm::gpuistl::GpuSparseMatrixGeneric< T >::getNonZeroValues ( ) const

inline

getNonZeroValues returns the GPU vector containing the non-zero values (ordered by block)

Note: Read the CuSPARSE documentation on Block Compressed Sparse Row Format (BSR) for the exact ordering.

◆ getRowIndices() [1/2]

template<typename T >

GpuVector< int > & Opm::gpuistl::GpuSparseMatrixGeneric< T >::getRowIndices ( )

inline

getRowIndices returns the row indices used to represent the BSR structure.

Note: Read the CuSPARSE documentation on Block Compressed Sparse Row Format (BSR) for the exact ordering.

◆ getRowIndices() [2/2]

template<typename T >

const GpuVector< int > & Opm::gpuistl::GpuSparseMatrixGeneric< T >::getRowIndices ( ) const

inline

getRowIndices returns the row indices used to represent the BSR structure.

Note: Read the CuSPARSE documentation on Block Compressed Sparse Row Format (BSR) for the exact ordering.

◆ mv()

template<typename T >

virtual void Opm::gpuistl::GpuSparseMatrixGeneric< T >::mv	(	const GpuVector< T > &	x,
		GpuVector< T > &	y
	)		const

virtual

mv performs matrix vector multiply y = Ax

Parameters

[in]	x	the vector to multiply the matrix with
[out]	y	the output vector

◆ N()

template<typename T >

size_t Opm::gpuistl::GpuSparseMatrixGeneric< T >::N ( ) const

inline

N returns the number of rows (which is equal to the number of columns)

References Opm::gpuistl::detail::to_size_t().

◆ nonzeroes()

template<typename T >

size_t Opm::gpuistl::GpuSparseMatrixGeneric< T >::nonzeroes ( ) const

inline

nonzeroes behaves as the Dune::BCRSMatrix::nonzeros() function and returns the number of non zero blocks

Returns: number of non zero blocks.

References Opm::gpuistl::detail::to_size_t().

◆ operator=()

template<typename T >

GpuSparseMatrixGeneric & Opm::gpuistl::GpuSparseMatrixGeneric< T >::operator= ( const GpuSparseMatrixGeneric< T > & )

delete

◆ preprocessSpMV()

template<typename T >

void Opm::gpuistl::GpuSparseMatrixGeneric< T >::preprocessSpMV ( )

Preprocess SpMV operation to optimize for sparsity pattern.

This function preprocesses the sparsity pattern of the matrix to optimize for the SpMV operation.

◆ umv()

template<typename T >

virtual void Opm::gpuistl::GpuSparseMatrixGeneric< T >::umv	(	const GpuVector< T > &	x,
		GpuVector< T > &	y
	)		const

virtual

umv computes y=Ax+y

Parameters

[in]	x	the vector to multiply with A
[in,out]	y	the vector to add and store the output in

◆ updateNonzeroValues() [1/2]

template<typename T >

void Opm::gpuistl::GpuSparseMatrixGeneric< T >::updateNonzeroValues ( const GpuSparseMatrixGeneric< T > & matrix )

updateNonzeroValues updates the non-zero values by using the non-zero values of the supplied matrix

Parameters

matrix the matrix to extract the non-zero values from

Note: This assumes the given matrix has the same sparsity pattern.

◆ updateNonzeroValues() [2/2]

template<typename T >

template<class MatrixType >

void Opm::gpuistl::GpuSparseMatrixGeneric< T >::updateNonzeroValues	(	const MatrixType &	matrix,
		bool	copyNonZeroElementsDirectly = `false`
	)

updateNonzeroValues updates the non-zero values by using the non-zero values of the supplied matrix

Parameters

matrix	the matrix to extract the non-zero values from
copyNonZeroElementsDirectly	if true will do a memcpy from matrix[0][0][0][0], otherwise will build up the non-zero elements by looping over the matrix. Note that setting this to true will yield a performance increase, but might not always yield correct results depending on how the matrix matrix has been initialized. If unsure, leave it as false.

Note: This assumes the given matrix has the same sparsity pattern.

Template Parameters

MatrixType is assumed to be a Dune::BCRSMatrix compatible matrix.

◆ usmv()

template<typename T >

virtual void Opm::gpuistl::GpuSparseMatrixGeneric< T >::usmv	(	T	alpha,
		const GpuVector< T > &	x,
		GpuVector< T > &	y
	)		const

virtual

umv computes y=alpha * Ax + y

Parameters

[in]	alpha	The scaling factor for the matrix-vector product
[in]	x	the vector to multiply with A
[in,out]	y	the vector to add and store the output in

Member Data Documentation

◆ max_block_size

template<typename T >

constexpr int Opm::gpuistl::GpuSparseMatrixGeneric< T >::max_block_size = 6

staticconstexpr

Maximum block size supported by this implementation.

This constant defines an upper bound on the block size to ensure reasonable compilation times. While this class itself could support larger values, functions that call dispatchOnBlocksize() might have limitations. This value can be increased if needed, but will increase compilation time due to template instantiations.

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

Public Types

Public Member Functions

Static Public Member Functions

Static Public Attributes

Detailed Description

Member Typedef Documentation

◆ field_type

Constructor & Destructor Documentation

◆ GpuSparseMatrixGeneric() [1/3]

◆ GpuSparseMatrixGeneric() [2/3]

◆ GpuSparseMatrixGeneric() [3/3]

◆ ~GpuSparseMatrixGeneric()

Member Function Documentation

◆ blockSize()

◆ dim()

◆ dispatchOnBlocksize()

◆ fromMatrix()

◆ getColumnIndices() [1/2]

◆ getColumnIndices() [2/2]

◆ getNonZeroValues() [1/2]

◆ getNonZeroValues() [2/2]

◆ getRowIndices() [1/2]

◆ getRowIndices() [2/2]

◆ mv()

◆ N()

◆ nonzeroes()

◆ operator=()

◆ preprocessSpMV()

◆ umv()

◆ updateNonzeroValues() [1/2]

◆ updateNonzeroValues() [2/2]

◆ usmv()

Member Data Documentation

◆ max_block_size