Opm::Accelerator Namespace Reference

Classes
class	amgclSolverBackend
class	BdaResult
class	BdaSolver
class	BlockedMatrix
class	CprCreation
	This class implements a Constrained Pressure Residual (CPR) preconditioner. More...
class	cusparseSolverBackend
	This class implements a cusparse-based ilu0-bicgstab solver on GPU. More...
class	Matrix
class	openclBILU0
class	openclBISAI
class	openclCPR
	This class implements a Constrained Pressure Residual (CPR) preconditioner. More...
class	OpenclKernels
class	OpenclMatrix
class	openclPreconditioner
class	openclSolverBackend
	This class implements a opencl-based ilu0-bicgstab solver on GPU. More...
class	Preconditioner
class	rocalutionSolverBackend
class	RocmMatrix
	This struct resembles a csr matrix. More...
class	RocmVector
class	rocsparseBILU0
class	rocsparseCPR
	This class implements a Constrained Pressure Residual (CPR) preconditioner. More...
class	rocsparsePreconditioner
class	rocsparseSolverBackend
	This class implements a rocsparse-based ilu0-bicgstab solver on GPU. More...

Typedefs
using	spmv_blocked_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int, const cl::Buffer &, cl::Buffer &, const unsigned int, cl::LocalSpaceArg >
using	spmv_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int, const cl::Buffer &, cl::Buffer &, cl::LocalSpaceArg >
using	residual_blocked_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int, cl::Buffer &, const cl::Buffer &, cl::Buffer &, const unsigned int, cl::LocalSpaceArg >
using	residual_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int, cl::Buffer &, const cl::Buffer &, cl::Buffer &, cl::LocalSpaceArg >
using	ilu_apply1_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, const cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int, const unsigned int, cl::LocalSpaceArg >
using	ilu_apply2_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int, const unsigned int, cl::LocalSpaceArg >
using	stdwell_apply_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int, const unsigned int, cl::Buffer &, cl::LocalSpaceArg, cl::LocalSpaceArg, cl::LocalSpaceArg >
using	ilu_decomp_kernel_type = cl::KernelFunctor< const unsigned int, const unsigned int, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, const int, cl::LocalSpaceArg >
using	isaiL_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int >
using	isaiU_kernel_type = cl::KernelFunctor< cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, cl::Buffer &, const unsigned int >

Enumerations
enum class	SolverStatus { BDA_SOLVER_SUCCESS , BDA_SOLVER_ANALYSIS_FAILED , BDA_SOLVER_CREATE_PRECONDITIONER_FAILED , BDA_SOLVER_UNKNOWN_ERROR }
enum	PreconditionerType { BILU0 , CPR , BISAI }

Functions
void	sortRow (int *colIndices, int *data, int left, int right)
template<class Scalar >
void	blockMultSub (Scalar *a, Scalar *b, Scalar *c, unsigned int block_size)
template<class Scalar >
void	blockMult (Scalar *mat1, Scalar *mat2, Scalar *resMat, unsigned int block_size)
unsigned int	ceilDivision (const unsigned int A, const unsigned int B)
template<class Scalar >
Scalar	get_absmax (const Scalar *data, const int N)
template<class Scalar >
void	solve_transposed_3x3 (const Scalar *A, const Scalar *b, Scalar *x)
std::string	getErrorString (cl_int error)
std::vector< int >	buildCsrToCscOffsetMap (std::vector< int > colPointers, std::vector< int > rowIndices)
bool	canBeStarted (const int rowIndex, const int *rowPointers, const int *colIndices, const std::vector< bool > &doneRows)
void	findLevelScheduling (int *CSRColIndices, int *CSRRowPointers, int *CSCRowIndices, int *CSCColPointers, int Nb, int *numColors, int *toOrder, int *fromOrder, std::vector< int > &rowsPerColor)
void	csrPatternToCsc (int *CSRColIndices, int *CSRRowPointers, int *CSCRowIndices, int *CSCColPointers, int Nb)

Typedef Documentation

ilu_apply1_kernel_type

using Opm::Accelerator::ilu_apply1_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, const cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, const unsigned int, cl::LocalSpaceArg>

ilu_apply2_kernel_type

using Opm::Accelerator::ilu_apply2_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, const unsigned int, cl::LocalSpaceArg>

ilu_decomp_kernel_type

using Opm::Accelerator::ilu_decomp_kernel_type = typedef cl::KernelFunctor<const unsigned int, const unsigned int, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, const int, cl::LocalSpaceArg>

isaiL_kernel_type

using Opm::Accelerator::isaiL_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int>

isaiU_kernel_type

using Opm::Accelerator::isaiU_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int>

residual_blocked_kernel_type

using Opm::Accelerator::residual_blocked_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, cl::Buffer&, const cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg>

residual_kernel_type

using Opm::Accelerator::residual_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, cl::Buffer&, const cl::Buffer&, cl::Buffer&, cl::LocalSpaceArg>

spmv_blocked_kernel_type

using Opm::Accelerator::spmv_blocked_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, const cl::Buffer&, cl::Buffer&, const unsigned int, cl::LocalSpaceArg>

spmv_kernel_type

using Opm::Accelerator::spmv_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, const cl::Buffer&, cl::Buffer&, cl::LocalSpaceArg>

stdwell_apply_kernel_type

using Opm::Accelerator::stdwell_apply_kernel_type = typedef cl::KernelFunctor<cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, cl::Buffer&, const unsigned int, const unsigned int, cl::Buffer&, cl::LocalSpaceArg, cl::LocalSpaceArg, cl::LocalSpaceArg>

Enumeration Type Documentation

PreconditionerType

enum Opm::Accelerator::PreconditionerType

Enumerator
BILU0
CPR
BISAI

SolverStatus

enum class Opm::Accelerator::SolverStatus

strong

Enumerator
BDA_SOLVER_SUCCESS
BDA_SOLVER_ANALYSIS_FAILED
BDA_SOLVER_CREATE_PRECONDITIONER_FAILED
BDA_SOLVER_UNKNOWN_ERROR

Function Documentation

blockMult()

template<class Scalar >

void Opm::Accelerator::blockMult	(	Scalar *	mat1,
		Scalar *	mat2,
		Scalar *	resMat,
		unsigned int	block_size
	)

Perform a matrix-matrix multiplication on two blocks resMat = mat1 * mat2

Parameters

[in]	mat1	input block 1
[in]	mat2	input block 2
[out]	resMat	output block
[in]	block_size	size of block

blockMultSub()

template<class Scalar >

void Opm::Accelerator::blockMultSub	(	Scalar *	a,
		Scalar *	b,
		Scalar *	c,
		unsigned int	block_size
	)

Multiply and subtract blocks a = a - (b * c)

Parameters

[in,out]	a	block to be subtracted from
[in]	b	input block
[in]	c	input block
[in]	block_size	size of block

buildCsrToCscOffsetMap()

std::vector< int > Opm::Accelerator::buildCsrToCscOffsetMap	(	std::vector< int >	colPointers,
		std::vector< int >	rowIndices
	)

Similar function to csrPatternToCsc. It gives an offset map from CSR to CSC instead of the full CSR to CSC conversion. The map works as follows: if an element 'e' of the matrix is in the i-th position in the CSR representation, it will be in the csrToCscOffsetMap[i]-th position in the CSC representation.

canBeStarted()

bool Opm::Accelerator::canBeStarted	(	const int	rowIndex,
		const int *	rowPointers,
		const int *	colIndices,
		const std::vector< bool > &	doneRows
	)

Determine whether all rows that a certain row depends on are done already

Parameters

[in]	rowIndex	index of the row that needs to be checked for
[in]	rowPointers	row pointers of the matrix that the row is in
[in]	colIndices	column indices of the matrix that the row is in
[in]	doneRows	array that for each row lists whether it is done or not

Returns

true iff all dependencies are done and if the result itself was not done yet

ceilDivision()

unsigned int Opm::Accelerator::ceilDivision	(	const unsigned int	A,
		const unsigned int	B
	)

csrPatternToCsc()

void Opm::Accelerator::csrPatternToCsc	(	int *	CSRColIndices,
		int *	CSRRowPointers,
		int *	CSCRowIndices,
		int *	CSCColPointers,
		int	Nb
	)

Convert a sparsity pattern stored in the CSR format to the CSC format CSCRowIndices and CSCColPointers arrays must be allocated already Based on the csr_tocsc() function from the scipy package from python, https://github.com/scipy/scipy/blob/master/scipy/sparse/sparsetools/csr.h

Parameters

[in]	CSRColIndices	column indices of the CSR representation of the pattern
[in]	CSRRowPointers	row pointers of the CSR representation of the pattern
[in,out]	CSCRowIndices	row indices of the result CSC representation of the pattern
[in,out]	CSCColPointers	column pointers of the result CSC representation of the pattern
[in]	Nb	number of blockrows in the matrix

findLevelScheduling()

void Opm::Accelerator::findLevelScheduling	(	int *	CSRColIndices,
		int *	CSRRowPointers,
		int *	CSCRowIndices,
		int *	CSCColPointers,
		int	Nb,
		int *	numColors,
		int *	toOrder,
		int *	fromOrder,
		std::vector< int > &	rowsPerColor
	)

Find a level scheduling reordering for an input matrix The toOrder and fromOrder arrays must be allocated already

Parameters

[in]	CSRColIndices	column indices array, obtained from storing the input matrix in the CSR format
[in]	CSRRowPointers	row pointers array, obtained from storing the input matrix in the CSR format
[in]	CSCRowIndices	row indices array, obtained from storing the input matrix in the CSC format
[in]	CSCColPointers	column pointers array, obtained from storing the input matrix in the CSC format
[in]	Nb	number of blockrows in the matrix
[out]	numColors	a pointer to the number of colors needed for the level scheduling
[out]	toOrder	the reorder pattern that was found, which lists for each index in the original order, to which index in the new order it should be moved
[out]	fromOrder	the reorder pattern that was found, which lists for each index in the new order, from which index in the original order it was moved
[out]	rowsPerColor	for each color, an array of all rowIndices in that color, this function uses emplace_back() to fill

get_absmax()

template<class Scalar >

Scalar Opm::Accelerator::get_absmax	(	const Scalar *	data,
		const int	N
	)

getErrorString()

std::string Opm::Accelerator::getErrorString

(

cl_int

error

)

Translate OpenCL error codes to strings Integer - String combinations are defined in CL/cl.h

Parameters

[in]

error

error code

solve_transposed_3x3()

template<class Scalar >

void Opm::Accelerator::solve_transposed_3x3	(	const Scalar *	A,
		const Scalar *	b,
		Scalar *	x
	)

sortRow()

void Opm::Accelerator::sortRow	(	int *	colIndices,
		int *	data,
		int	left,
		int	right
	)

Sort a row of matrix elements from a CSR-format, where the nonzeroes are ints These ints aren't actually nonzeroes, but represent a mapping used later

Parameters

[in,out]	colIndices	represent keys in sorting
[in,out]	data	sorted according to the colIndices
[in]	left	lower index of data of row
[in]	right	upper index of data of row