lama::MetaMatrix Class Reference

#include <MetaMatrix.hpp>

Inheritance diagram for lama::MetaMatrix:

Public Types
typedef std::string::const_iterator	StringIterator
enum	SyncKind { ASYNCHRONOUS, SYNCHRONOUS }
	SyncKind describes if the communication and computation should be done synchronously or asynchronously. More...
enum	MatrixKind { DENSE, SPARSE }
	MatrixKind describes if a matrix is dense or sparse. More...
typedef const Matrix &	ExpressionMemberType
	ExpressionMemberType is the type that is used the template Expression to store a Vector.
Public Member Functions
	MetaMatrix (Matrix &other, const std::string &config)
	Construct a square matrix with the given size and the specified distribution.
virtual	~MetaMatrix ()
	virtual destructor of MetaMatrix
void	interpreteArgument (Matrix &other, const std::string &arg)
void	parseConfiguration (Matrix &other, const std::string &configuration)
virtual const char *	getTypeName () const
	Virtual method that delivers the class name to which a matrix belongs.
virtual void	clear ()
	Clear the full matrix, resets global and local sizes to 0.
virtual void	allocate (const IndexType numRows, const IndexType numColumns)
	Reallocate this matrix to a replicated zero-matrix of the given shape.
virtual void	allocate (DistributionPtr rowDistribution, DistributionPtr colDistribution)
	Reallocate this matrix to a distributed zero-matrix by the given distributions.
virtual void	setIdentity ()
	Operator that sets the matrix to the identity matrix.
virtual void	assign (const Matrix &other)
	This method assigns a matrix to this matrix with automatic conversion to the matrix type and the current row / column distribution of *this.
virtual void	assign (const _MatrixStorage &other)
	This method assigns replicated/global matrix storage data to this matrix.
virtual void	assign (const _MatrixStorage &storage, DistributionPtr rowDist, DistributionPtr colDist)
	Assign local storage for a distributed matrix.
virtual void	buildLocalStorage (_MatrixStorage &storage) const
	Get the local part (no splitted columns) of a matrix as if colDist is replicated.
virtual void	redistribute (DistributionPtr rowDistribution, DistributionPtr colDistribution)
	This method allows any arbitrary redistribution of the matrix.
virtual void	getRow (Vector &row, const IndexType globalRowIndex) const
	This method returns one row of the matrix.
virtual void	getDiagonal (Vector &diagonal) const
	This method returns the diagonal.
virtual void	setDiagonal (const Vector &diagonal)
	This method replaces the diagonal.
virtual void	setDiagonal (const Scalar scalar)
	This method replaces the diagonal by a diagonal value.
virtual void	scale (const Vector &scaling)
	This method scales all values with a vector.
virtual void	scale (const Scalar scaling)
	This method scales all matrix values with a scalar.
virtual Scalar	getValue (IndexType i, IndexType j) const
	returns a copy of the value at the passed global indexes.
virtual IndexType	getNumValues () const
	Get the total number of non-zero values in the matrix.
virtual void	matrixTimesVector (Vector &result, const Scalar alpha, const Vector &x, const Scalar beta, const Vector &y) const
	matrixTimesVector computes result = alpha * this * x + beta * y
virtual void	matrixTimesScalar (const Matrix &other, const Scalar alpha)
	matrixTimesScalar computes this = alpha * other
virtual void	matrixTimesMatrix (Matrix &result, const Scalar alpha, const Matrix &B, const Scalar beta, const Matrix &C) const
	matrixTimesMatrix computes result = alpha * this * B + beta * C
virtual IndexType	getLocalNumValues () const
	Getter routine for the local number of stored values.
virtual IndexType	getLocalNumRows () const
	Getter routine for the local number of rows.
virtual IndexType	getLocalNumColumns () const
	Getter routine for the local number of rows and columns.
virtual void	setContext (const ContextPtr context)
	specifies on which compute back end the matrix operations should take place.
virtual ContextPtr	getContextPtr () const
	Getter routine for the context.
virtual MatrixKind	getMatrixKind () const
	Each derived matrix must give info about its kind (DENSE or SPARSE).
virtual void	prefetch () const
	Prefetch matrix data to its 'preferred' context location.
virtual void	wait () const
	wait for a possibly running prefetch.
virtual void	invert (const Matrix &other)
	Compute the inverse of a matrix.
virtual Scalar	maxDiffNorm (const Matrix &other) const
	returns the max norm of ( this - other )
virtual std::auto_ptr< Matrix >	create () const
	Constructor function which creates a 'zero' matrix of same type as a given matrix.
virtual std::auto_ptr< Matrix >	copy () const
	Constructor function which creates a copy of this matrix.
virtual Scalar::ScalarType	getValueType () const
	Query the value type of the matrix elements, e.g.
virtual bool	hasDiagonalProperty () const
	hasDiagonalProperty returns the diagonalProperty of the local storage.
virtual void	resetDiagonalProperty ()
	resetDiagonalProperty rechecks the storages for their diagonal property
virtual size_t	getMemoryUsage () const
	getMemoryUsage returns the global memory that is allocated to hold this matrix.
std::auto_ptr< _LAMAArray >	createArray () const
	This routine creates a LAMA array with the same value type as the matrix.
Scalar	operator() (IndexType i, IndexType j) const
	returns a copy of the value at the passed global indexes.
virtual void	writeAt (std::ostream &stream) const
	Write some information about this to the passed stream.
IndexType	getNumRows () const
	Returns the number of global rows.
IndexType	getNumColumns () const
	Returns the number of columns.
double	getSparsityRate () const
virtual void	matrix2CSRGraph (IndexType *xadj, IndexType *adjncy, IndexType *vwgt, CommunicatorPtr comm, const IndexType *globalRowIndices=NULL, IndexType *vtxdist=NULL) const
	transformation from matrix type to a csr graph
const Distribution &	getColDistribution () const
	gets a constant reference to the column distribution.
DistributionPtr	getColDistributionPtr () const
	gets a pointer to the column distribution.
virtual void	setContext (const ContextPtr localContext, const ContextPtr haloContext)
	Only sparse matrices will override this method, others will ignore second argument.
const Context &	getContext () const
SyncKind	getCommunicationKind () const
	get the communication kind.
SyncKind	getComputeKind () const
	get the compute kind.
void	setCommunicationKind (SyncKind communicationKind)
	set the communication kind.
virtual void	setComputeKind (SyncKind computeKind)
	set the compute kind.
void	inheritAttributes (const Matrix &other)
	Inherit context and kind arguments from another matrix.
std::auto_ptr< Matrix >	create (const IndexType numRows, const IndexType numColumns) const
	Constructor creates a replicated matrix of same type as a given matrix.
std::auto_ptr< Matrix >	create (const IndexType size) const
	Constructor creates a distributed zero matrix of same type as a given matrix.
std::auto_ptr< Matrix >	create (DistributionPtr rowDistribution, DistributionPtr colDistribution) const
	Constructor creates a distributed zero matrix of same type as a given matrix.
std::auto_ptr< Matrix >	create (DistributionPtr distribution) const
	Constructor creates a distributed zero matrix of same type as a given matrix.
VectorPtr	createDenseVector (DistributionPtr distribution, const Scalar value) const
	Constructor creates a distributed dense vector of same type as a given matrix.
const Distribution &	getDistribution () const
DistributionPtr	getDistributionPtr () const
Protected Member Functions
void	setReplicatedMatrix (const IndexType numRows, const IndexType numColumns)
	Set the global/local size of replicated matrix.
void	setDistributedMatrix (DistributionPtr distribution, DistributionPtr colDistribution)
	Set the global and local size of distributed matrix.
void	checkSettings ()
void	swapMatrix (Matrix &other)
void	swap (Distributed &other)
void	setDistributionPtr (DistributionPtr distributionPtr)
Protected Attributes
DistributionPtr	mColDistribution
IndexType	mNumRows
IndexType	mNumColumns
Private Member Functions
	LAMA_LOG_DECL_STATIC_LOGGER (logger)
Private Attributes
MatrixPtr	mMatrix

---

Member Typedef Documentation

typedef const Matrix& lama::Matrix::ExpressionMemberType [inherited]

ExpressionMemberType is the type that is used the template Expression to store a Vector.

typedef std::string::const_iterator lama::MetaMatrix::StringIterator

---

Member Enumeration Documentation

enum lama::Matrix::MatrixKind [inherited]

MatrixKind describes if a matrix is dense or sparse.

Enumerator:

DENSE	matrix kind for a dense matrix
SPARSE	matrix kind for a sparse matrix

enum lama::Matrix::SyncKind [inherited]

SyncKind describes if the communication and computation should be done synchronously or asynchronously.

Enumerator:

ASYNCHRONOUS
SYNCHRONOUS

---

Constructor & Destructor Documentation

lama::MetaMatrix::MetaMatrix	(	Matrix &	other,
		const std::string &	config
	)

Construct a square matrix with the given size and the specified distribution.

Parameters:

[in]	matrixInput	Specifies the file name of the Matrix which used to create the generated matrix.
[in]	config	Configuration which will be parsed to generate the defined matrix

References interpreteArgument().

lama::MetaMatrix::~MetaMatrix

(

)

[virtual]

virtual destructor of MetaMatrix

---

Member Function Documentation

void lama::MetaMatrix::allocate	(	const IndexType	numRows,
		const IndexType	numColumns
	)		[virtual]

Reallocate this matrix to a replicated zero-matrix of the given shape.

Parameters:

[in]	numRows	number of rows
[in]	numColumns	number of columns

Remarks:

The call allocate( 0, 0 ) implies a clear on all arrays used internally for the presentation of the matrix data.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::allocate	(	DistributionPtr	rowDistribution,
		DistributionPtr	colDistribution
	)		[virtual]

Reallocate this matrix to a distributed zero-matrix by the given distributions.

Parameters:

[in]	distribution	is row distribution, number of rows given by getGlobalSize()
[in]	colDistribution	is col distribution, number of columns given by getGlobalSize()

The distributions specify the new global and the new local sizes for a distributed matrix.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::assign

(

const Matrix &

other

)

[virtual]

This method assigns a matrix to this matrix with automatic conversion to the matrix type and the current row / column distribution of *this.

Note: other.getNumRows() == getNumRows(), other.getNumColumns() == getNumColumns() is mandatory

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::assign

(

const _MatrixStorage &

other

)

[virtual]

This method assigns replicated/global matrix storage data to this matrix.

Note: the current matrix data will be overridden.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::assign	(	const _MatrixStorage &	storage,
		DistributionPtr	rowDist,
		DistributionPtr	colDist
	)		[virtual]

Assign local storage for a distributed matrix.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::buildLocalStorage

(

_MatrixStorage &

storage

)

const [virtual]

Get the local part (no splitted columns) of a matrix as if colDist is replicated.

Parameters:

[out]

storage

will contain the local part of the matrix with all columns.

As splitting of columns is differently handled for sparse and dense matrices, this method is useful for conversion between them. An alternative solution of copying the whole matrix and replication of columns might be too expensive.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::Matrix::checkSettings

(

)

[protected, inherited]

Reimplemented in lama::SparseMatrix< T >, and lama::SparseMatrix< ValueType >.

References lama::Matrix::getColDistribution(), lama::Distributed::getDistribution(), LAMA_THROWEXCEPTION, lama::Matrix::mColDistribution, lama::Matrix::mNumColumns, and lama::Matrix::mNumRows.

Referenced by lama::Matrix::Matrix().

void lama::MetaMatrix::clear

(

)

[virtual]

Clear the full matrix, resets global and local sizes to 0.

     CSRSparseMatrix<double> a ( ... );
     a = CSRSparseMatrix<double> ();     \\ will free all arrays
     a.clear();                          \\ same functionality, clears involved arrays

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

std::auto_ptr< Matrix > lama::MetaMatrix::copy

(

)

const [virtual]

Constructor function which creates a copy of this matrix.

 std::auto_ptr<Matrix> newMatrix = matrix.copy();
 // More convenient to use, but exactly same as follows:
 std::auto_ptr<Matrix> newMatrix = matrix.create(); *newMatrix = matrix;

This method is a workaround to call the copy constructor of a derived matrix class where the derived class is not known at compile time.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

Referenced by interpreteArgument().

std::auto_ptr< Matrix > lama::MetaMatrix::create

(

)

const [virtual]

Constructor function which creates a 'zero' matrix of same type as a given matrix.

 void sub( ..., const Matrix& matrix, ...)
 {
     ...
     // Create a copy of the input matrix

     std::auto_ptr<Matrix> newMatrix = matrix.create();
     *newMatrix = matrix;

     // Create a unity matrix of same type and same row distribution as matrix

     std::auto_ptr<Matrix> newMatrix = matrix.create();
     newMatrix->allocate( matrix.getRowDistributionPtr(), matrix.getRowDistributionPtr() );
     newMatrix->setIdentity();
     ...
 }

This method is a workaround to call the constructor of a derived matrix class where the derived class is not known at compile time.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

std::auto_ptr< Matrix > lama::Matrix::create	(	const IndexType	numRows,
		const IndexType	numColumns
	)		const [inherited]

Constructor creates a replicated matrix of same type as a given matrix.

References lama::Matrix::create().

std::auto_ptr< Matrix > lama::Matrix::create

(

const IndexType

size

)

const [inherited]

Constructor creates a distributed zero matrix of same type as a given matrix.

References lama::Matrix::create().

std::auto_ptr< Matrix > lama::Matrix::create	(	DistributionPtr	rowDistribution,
		DistributionPtr	colDistribution
	)		const [inherited]

Constructor creates a distributed zero matrix of same type as a given matrix.

References lama::Matrix::create().

std::auto_ptr< Matrix > lama::Matrix::create

(

DistributionPtr

distribution

)

const [inherited]

Constructor creates a distributed zero matrix of same type as a given matrix.

References lama::Matrix::create().

std::auto_ptr< _LAMAArray > lama::Matrix::createArray

(

)

const [inherited]

This routine creates a LAMA array with the same value type as the matrix.

: returns an auto pointer to the LAMA array.

Same as _LAMAArray::create( this.getValueType() )

Value type is known only at runtime, so pointer to the base class is returned. Auto pointer indicates that calling routine takes ownership of the allocated array.

References lama::Matrix::create(), and lama::Matrix::getValueType().

VectorPtr lama::Matrix::createDenseVector	(	DistributionPtr	distribution,
		const Scalar	value
	)		const [inherited]

Constructor creates a distributed dense vector of same type as a given matrix.

References lama::Scalar::DOUBLE, lama::Scalar::FLOAT, lama::Scalar::getValue(), lama::Matrix::getValueType(), and LAMA_THROWEXCEPTION.

const Distribution & lama::Matrix::getColDistribution

(

)

const [inline, inherited]

gets a constant reference to the column distribution.

Returns:

a constant reference to the column distribution.

References LAMA_ASSERT_ERROR, and lama::Matrix::mColDistribution.

Referenced by lama::DenseMatrix< T >::assignSparse(), lama::Matrix::checkSettings(), lama::LUSolver::computeLUFactorization(), lama::InverseSolver::decompose(), lama::DenseMatrix< T >::DenseMatrix(), lama::DenseMatrixOps::invert(), lama::InverseSolver::invert(), lama::DenseMatrixOps::invertReplicated(), lama::SpecializedJacobi::iterateTyped(), lama::Matrix::Matrix(), lama::DenseMatrix< T >::matrixTimesMatrix(), lama::SparseMatrix< T >::matrixTimesMatrixImpl(), lama::CRTPMatrix< DenseMatrix< T >, T >::matrixTimesVector(), lama::SparseMatrix< T >::matrixTimesVectorNImpl(), lama::DenseMatrix< T >::maxDiffNorm(), lama::SparseMatrix< T >::maxDiffNorm(), lama::DenseMatrix< T >::maxDiffNormImpl(), lama::SparseMatrix< T >::maxDiffNormImpl(), lama::Matrix::operator=(), lama::LUSolver::solve(), and lama::Solver::solveInit().

DistributionPtr lama::Matrix::getColDistributionPtr

(

)

const [inline, inherited]

gets a pointer to the column distribution.

Returns:

a pointer to the column distribution.

References LAMA_ASSERT_ERROR, and lama::Matrix::mColDistribution.

Referenced by lama::SparseMatrix< T >::assign(), lama::DenseMatrix< T >::assign(), lama::DenseMatrix< T >::assignSparse(), lama::SparseMatrix< T >::assignTransposeImpl(), lama::DenseMatrix< T >::copyDenseMatrix(), lama::MatrixCreator< T >::fillRandom(), lama::DenseMatrixOps::invert(), lama::DenseMatrix< T >::invert(), lama::DenseMatrix< T >::matrixTimesMatrix(), lama::SparseMatrix< T >::matrixTimesMatrixImpl(), and lama::SparseMatrix< T >::matrixTimesVectorNImpl().

Matrix::SyncKind lama::Matrix::getCommunicationKind

(

)

const [inline, inherited]

get the communication kind.

Returns:

the communication kind.

References lama::Matrix::mCommunicationKind.

Referenced by lama::Matrix::inheritAttributes(), lama::SpecializedJacobi::iterateTyped(), and lama::DenseMatrix< T >::matrixTimesVectorImpl().

Matrix::SyncKind lama::Matrix::getComputeKind

(

)

const [inline, inherited]

get the compute kind.

Returns:

the compute kind.

References lama::Matrix::mComputeKind.

Referenced by lama::Matrix::inheritAttributes().

const Context& lama::Matrix::getContext

(

)

const [inline, inherited]

Reimplemented in lama::SparseMatrix< T >, and lama::SparseMatrix< ValueType >.

ContextPtr lama::MetaMatrix::getContextPtr

(

)

const [virtual]

Getter routine for the context.

Note: Only for SparseMatrix the context of the halo can be queried.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::getDiagonal

(

Vector &

diagonal

)

const [virtual]

This method returns the diagonal.

Parameters:

[out]

diagonal

is the destination array

Calculations are dependent to the diagonal property.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

const Distribution & lama::Distributed::getDistribution

(

)

const [inline, inherited]

References lama::Distributed::mDistribution.

Referenced by lama::SparseMatrix< T >::assignTransposeImpl(), lama::Matrix::checkSettings(), lama::LUSolver::computeLUFactorization(), lama::InverseSolver::decompose(), lama::DenseMatrix< T >::DenseMatrix(), lama::DenseVector< T >::DenseVector(), lama::DenseVector< T >::dotProduct(), lama::MatrixCreator< T >::fillRandom(), lama::SparseMatrix< T >::getLocalRow(), lama::SparseMatrix< T >::getRow(), lama::DenseMatrix< T >::getRow(), lama::DenseMatrixOps::invert(), lama::InverseSolver::invert(), lama::DenseMatrixOps::invertCyclic(), lama::DenseMatrixOps::invertReplicated(), lama::Matrix::Matrix(), lama::DenseMatrix< T >::matrixTimesMatrix(), lama::SparseMatrix< T >::matrixTimesMatrixImpl(), lama::CRTPMatrix< DenseMatrix< T >, T >::matrixTimesVector(), lama::SparseMatrix< T >::matrixTimesVector(), lama::SparseMatrix< T >::matrixTimesVectorNImpl(), lama::DenseMatrix< T >::maxDiffNorm(), lama::SparseMatrix< T >::maxDiffNorm(), lama::DenseMatrix< T >::maxDiffNormImpl(), lama::SparseMatrix< T >::maxDiffNormImpl(), lama::Matrix::operator=(), lama::SparseMatrix< T >::scale(), lama::SparseMatrix< T >::setDiagonal(), lama::LUSolver::solve(), lama::Solver::solveInit(), lama::Vector::Vector(), and lama::Vector::~Vector().

DistributionPtr lama::Distributed::getDistributionPtr

(

)

const [inline, inherited]

References lama::Distributed::mDistribution.

Referenced by lama::SparseMatrix< T >::assign(), lama::DenseMatrix< T >::assign(), lama::DenseVector< T >::assign(), lama::DenseMatrix< T >::assignSparse(), lama::SparseMatrix< T >::assignTransposeImpl(), lama::DenseMatrix< T >::copyDenseMatrix(), lama::DenseVector< T >::DenseVector(), lama::MatrixCreator< T >::fillRandom(), lama::SingleGridSetup::initialize(), lama::CG::initialize(), lama::DefaultJacobi::initialize(), lama::GMRES::initialize(), lama::DenseMatrixOps::invert(), lama::DenseMatrix< T >::invert(), lama::DenseMatrixOps::invertCyclic(), lama::GMRES::iterate(), lama::SparseMatrix< T >::matrixTimesMatrixImpl(), lama::CRTPMatrix< DenseMatrix< T >, T >::matrixTimesVector(), lama::Vector::operator=(), lama::Vector::size(), and lama::Vector::writeAt().

IndexType lama::MetaMatrix::getLocalNumColumns

(

)

const [virtual]

Getter routine for the local number of rows and columns.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

IndexType lama::MetaMatrix::getLocalNumRows

(

)

const [virtual]

Getter routine for the local number of rows.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

IndexType lama::MetaMatrix::getLocalNumValues

(

)

const [virtual]

Getter routine for the local number of stored values.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

Matrix::MatrixKind lama::MetaMatrix::getMatrixKind

(

)

const [virtual]

Each derived matrix must give info about its kind (DENSE or SPARSE).

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

size_t lama::MetaMatrix::getMemoryUsage

(

)

const [virtual]

getMemoryUsage returns the global memory that is allocated to hold this matrix.

getMemoryUsage returns the global memory that is allocated to hold this matrix. For a distributed matrix all partitions are summed together.

Returns:

the memory consumption of this matrix.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

IndexType lama::Matrix::getNumColumns

(

)

const [inline, inherited]

Returns the number of columns.

Returns:

the number of columns.

References lama::Matrix::mNumColumns.

Referenced by lama::DenseMatrix< T >::assignSparse(), lama::LUSolver::computeLUFactorization(), lama::InverseSolver::decompose(), lama::DenseMatrix< T >::DenseMatrix(), lama::MatrixCreator< T >::fillRandom(), lama::SparseMatrix< T >::getLocalNumColumns(), lama::InverseSolver::invert(), lama::DenseMatrix< T >::invert(), lama::DenseMatrixOps::invertCyclic(), lama::MatrixConfigGrammar::MatrixConfigGrammar(), lama::Matrix::operator=(), lama::LUSolver::solve(), and lama::Solver::solveInit().

IndexType lama::Matrix::getNumRows

(

)

const [inline, inherited]

Returns the number of global rows.

Returns:

the number of rows.

References lama::Matrix::mNumRows.

Referenced by lama::InverseSolver::computeInverse(), lama::LUSolver::computeLUFactorization(), lama::InverseSolver::decompose(), lama::SparseMatrix< T >::getLocalNumRows(), lama::LUSolver::initialize(), lama::DenseMatrixOps::invert(), lama::InverseSolver::invert(), lama::DenseMatrix< T >::invert(), lama::DenseMatrixOps::invertCyclic(), lama::SpecializedJacobi::iterateTyped(), lama::MatrixConfigGrammar::MatrixConfigGrammar(), lama::Matrix::operator=(), lama::LUSolver::solve(), and lama::Solver::solveInit().

IndexType lama::MetaMatrix::getNumValues

(

)

const [virtual]

Get the total number of non-zero values in the matrix.

An element is considered to be non-zero if its absolute value is greater equal than mEpsilon. Zero diagonal elements are also counted if this->hasDiagonalProperty() is given.

This routine does not count zero elements even if they are stored (e.g. for dense or dia storage data).

Returns:

the number of non-zero values in this matrix.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::getRow	(	Vector &	row,
		const IndexType	globalRowIndex
	)		const [virtual]

This method returns one row of the matrix.

Parameters:

[out]

row

is a replicated vector with all values of the row

Note: the value type of the vector should be the same type as the matrix (otherwise conversion) and it should be a replicated vector (otherwise reallocation)

Unclear: should the distribution always be unchanged ?

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

double lama::Matrix::getSparsityRate

(

)

const [inherited]

References lama::Matrix::getNumValues(), lama::Matrix::mNumColumns, and lama::Matrix::mNumRows.

const char * lama::MetaMatrix::getTypeName

(

)

const [virtual]

Virtual method that delivers the class name to which a matrix belongs.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

Scalar lama::MetaMatrix::getValue	(	IndexType	i,
		IndexType	j
	)		const [virtual]

returns a copy of the value at the passed global indexes.

Parameters:

[in]	i	the global row index
[in]	j	the global column index

Returns:

a copy of the value at the passed global position.

As this operation requires communication ins SPMD mode it can be very inefficient in some situations.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

Scalar::ScalarType lama::MetaMatrix::getValueType

(

)

const [virtual]

Query the value type of the matrix elements, e.g.

DOUBLE or FLOAT.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

bool lama::MetaMatrix::hasDiagonalProperty

(

)

const [virtual]

hasDiagonalProperty returns the diagonalProperty of the local storage.

Returns:

if the diagonal property is full filled.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::Matrix::inheritAttributes

(

const Matrix &

other

)

[inherited]

Inherit context and kind arguments from another matrix.

This routine will also be used by copy constructors in base classes.

References lama::Matrix::getCommunicationKind(), lama::Matrix::getComputeKind(), lama::Matrix::getContextPtr(), lama::Matrix::setCommunicationKind(), lama::Matrix::setComputeKind(), and lama::Matrix::setContext().

void lama::MetaMatrix::interpreteArgument	(	Matrix &	other,
		const std::string &	arg
	)

References copy(), and parseConfiguration().

Referenced by MetaMatrix().

void lama::MetaMatrix::invert

(

const Matrix &

other

)

[virtual]

Compute the inverse of a matrix.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

lama::MetaMatrix::LAMA_LOG_DECL_STATIC_LOGGER

(

logger

)

[private]

Reimplemented from lama::Matrix.

void lama::Matrix::matrix2CSRGraph	(	IndexType *	xadj,
		IndexType *	adjncy,
		IndexType *	vwgt,
		CommunicatorPtr	comm,
		const IndexType *	globalRowIndices = NULL,
		IndexType *	vtxdist = NULL
	)		const [virtual, inherited]

transformation from matrix type to a csr graph

transformation from matrix type to a csr graph, so that it (Par)Metis can work with it.

Parameters:

[out]	xadj	the ia array of the csr graph
[out]	adjncy	the ja array of the csr graph

References LAMA_THROWEXCEPTION.

void lama::MetaMatrix::matrixTimesMatrix	(	Matrix &	result,
		const Scalar	alpha,
		const Matrix &	B,
		const Scalar	beta,
		const Matrix &	C
	)		const [virtual]

matrixTimesMatrix computes result = alpha * this * B + beta * C

Parameters:

[out]	result	the Matrix to store the result to
[in]	alpha	the Scalar alpha of the expression
[in]	B	the Matrix B of the expression
[in]	beta	the Scalar beta of the expression
[in]	C	the Matrix C of the expression

matrixTimesMatrix computes result = alpha * this * x + beta * y.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::matrixTimesScalar	(	const Matrix &	other,
		const Scalar	alpha
	)		[virtual]

matrixTimesScalar computes this = alpha * other

Parameters:

[out]	other	the Matrix to mutliply
[in]	alpha	the Scalar of the expression

matrixTimesScalar computes this = alpha * other.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::matrixTimesVector	(	Vector &	result,
		const Scalar	alpha,
		const Vector &	x,
		const Scalar	beta,
		const Vector &	y
	)		const [virtual]

matrixTimesVector computes result = alpha * this * x + beta * y

Parameters:

[out]	result	the Vector to store the result to
[in]	alpha	the Scalar alpha of the expression
[in]	x	the Vector x of the expression
[in]	beta	the Scalar beta of the expression
[in]	y	the Vector y of the expression

matrixTimesVector computes result = alpha * this * x + beta * y. If result == x or result == y new storage is allocated to store the result.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

Scalar lama::MetaMatrix::maxDiffNorm

(

const Matrix &

other

)

const [virtual]

returns the max norm of ( this - other )

Parameters:

[in]

other

another matrix with the same shape as this matrix

Returns:

the max norm of ( this - other )

The maximal value is given by the largest difference between two elements at the same position of the matrices.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

Scalar lama::Matrix::operator()	(	IndexType	i,
		IndexType	j
	)		const [inherited]

returns a copy of the value at the passed global indexes.

Parameters:

[in]	i	the global row index
[in]	j	the global column index

Returns:

a copy of the value at the passed global position.

As this operator requires communication ins SPMD mode it can be very inefficient in some situations.

References lama::Matrix::getValue().

void lama::MetaMatrix::parseConfiguration	(	Matrix &	other,
		const std::string &	configuration
	)

References LAMA_ASSERT, LAMA_THROWEXCEPTION, and mMatrix.

Referenced by interpreteArgument().

void lama::MetaMatrix::prefetch

(

)

const [virtual]

Prefetch matrix data to its 'preferred' context location.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::redistribute	(	DistributionPtr	rowDistribution,
		DistributionPtr	colDistribution
	)		[virtual]

This method allows any arbitrary redistribution of the matrix.

Parameters:

[in]	rowDistribution	is new distribution of rows, global size must be mNumRows
[in]	colDistribution	is new distribution of columns, global size must be mNumColumns

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::resetDiagonalProperty

(

)

[virtual]

resetDiagonalProperty rechecks the storages for their diagonal property

Returns:

if the diagonal property is full filled.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::scale

(

const Vector &

scaling

)

[virtual]

This method scales all values with a vector.

Parameters:

[in]

values

is the source array

row wise calculations

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::scale

(

const Scalar

scaling

)

[virtual]

This method scales all matrix values with a scalar.

Parameters:

[in]

value

is the source value

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::Matrix::setCommunicationKind

(

SyncKind

communicationKind

)

[inherited]

set the communication kind.

Parameters:

[in]

communicationKind

the communication kind.

References lama::Matrix::mCommunicationKind.

Referenced by lama::Matrix::inheritAttributes().

void lama::Matrix::setComputeKind

(

SyncKind

computeKind

)

[virtual, inherited]

set the compute kind.

Parameters:

[in]

computeKind

the compute kind.

Reimplemented in lama::SparseMatrix< T >, and lama::SparseMatrix< ValueType >.

References lama::Matrix::mComputeKind.

Referenced by lama::Matrix::inheritAttributes().

void lama::MetaMatrix::setContext

(

const ContextPtr

context

)

[virtual]

specifies on which compute back end the matrix operations should take place.

Parameters:

[in]

context

the compute back to use for calculations with matrix

Note: Only for sparse matrices it is possible to specify separate locations for local and halo computations.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::Matrix::setContext	(	const ContextPtr	localContext,
		const ContextPtr	haloContext
	)		[virtual, inherited]

Only sparse matrices will override this method, others will ignore second argument.

Reimplemented in lama::SparseMatrix< T >, and lama::SparseMatrix< ValueType >.

References lama::Matrix::setContext().

void lama::MetaMatrix::setDiagonal

(

const Vector &

diagonal

)

[virtual]

This method replaces the diagonal.

Parameters:

[in]

diagonal

is the source array

Calculations are dependent to the diagonal property

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::MetaMatrix::setDiagonal

(

const Scalar

scalar

)

[virtual]

This method replaces the diagonal by a diagonal value.

Parameters:

[in]

scalar

is the source value

Calculations are dependent to the diagonal property

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::Matrix::setDistributedMatrix	(	DistributionPtr	distribution,
		DistributionPtr	colDistribution
	)		[protected, inherited]

Set the global and local size of distributed matrix.

Parameters:

[in]	distribution	is distribution for rows
[in]	colDistribution	is distribution for columns

Global and local size is given implicitly by the distributions itself.

References LAMA_ASSERT_ERROR, lama::Matrix::mColDistribution, lama::Matrix::mNumColumns, lama::Matrix::mNumRows, and lama::Distributed::setDistributionPtr().

Referenced by lama::DenseMatrix< T >::allocate(), lama::SimpleStorageStrategy< ValueType >::applyStrategy(), lama::DenseMatrix< T >::assign(), lama::DenseMatrix< T >::assignSparse(), lama::COOSparseMatrix< T >::COOSparseMatrix(), lama::DenseMatrix< T >::copyDenseMatrix(), lama::CSRSparseMatrix< T >::CSRSparseMatrix(), lama::DIASparseMatrix< T >::DIASparseMatrix(), lama::ELLSparseMatrix< T >::ELLSparseMatrix(), lama::JDSSparseMatrix< T >::JDSSparseMatrix(), lama::Matrix::Matrix(), lama::Matrix::setReplicatedMatrix(), lama::DenseMatrix< T >::splitColumns(), and lama::XXXSparseMatrix< T >::XXXSparseMatrix().

void lama::Distributed::setDistributionPtr

(

DistributionPtr

distributionPtr

)

[protected, inherited]

References lama::Distributed::mDistribution.

Referenced by lama::Vector::resize(), and lama::Matrix::setDistributedMatrix().

void lama::MetaMatrix::setIdentity

(

)

[virtual]

Operator that sets the matrix to the identity matrix.

 void sub( ..., Matrix& a, ... )
 ...
 LAMA_ASSERT_EQUAL_DEBUG( a.getNumRows(), a.getNumColumns() );
 A.setIdentity();

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::Matrix::setReplicatedMatrix	(	const IndexType	numRows,
		const IndexType	numColumns
	)		[protected, inherited]

Set the global/local size of replicated matrix.

Parameters:

[in]	numRows	number of rows, must be non-negative.
[in]	numColumns	number of columns, must be non-negative.

References lama::Matrix::setDistributedMatrix().

Referenced by lama::DenseMatrix< T >::allocate(), lama::DenseMatrix< T >::assign(), lama::DenseMatrix< T >::clear(), and lama::DenseMatrix< T >::DenseMatrix().

void lama::Distributed::swap

(

Distributed &

other

)

[protected, inherited]

References lama::Distributed::mDistribution.

Referenced by lama::Matrix::swapMatrix().

void lama::Matrix::swapMatrix

(

Matrix &

other

)

[protected, inherited]

References lama::Matrix::mColDistribution, lama::Matrix::mNumColumns, lama::Matrix::mNumRows, and lama::Distributed::swap().

Referenced by lama::DenseMatrix< T >::swap().

void lama::MetaMatrix::wait

(

)

const [virtual]

wait for a possibly running prefetch.

Implements lama::Matrix.

References LAMA_ASSERT, and mMatrix.

void lama::Matrix::writeAt

(

std::ostream &

stream

)

const [virtual, inherited]

Write some information about this to the passed stream.

Parameters:

[out]

stream

the stream to write to.

Reimplemented from Printable.

Reimplemented in lama::SparseMatrix< T >, lama::SparseMatrix< ValueType >, and lama::DenseMatrix< T >.

References lama::Matrix::mNumColumns, and lama::Matrix::mNumRows.

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Field Documentation

DistributionPtr lama::Matrix::mColDistribution [protected, inherited]

Referenced by lama::Matrix::checkSettings(), lama::Matrix::getColDistribution(), lama::Matrix::getColDistributionPtr(), lama::DenseMatrix< T >::redistribute(), lama::Matrix::setDistributedMatrix(), and lama::Matrix::swapMatrix().

MatrixPtr lama::MetaMatrix::mMatrix [private]

Referenced by allocate(), assign(), buildLocalStorage(), clear(), copy(), create(), getContextPtr(), getDiagonal(), getLocalNumColumns(), getLocalNumRows(), getLocalNumValues(), getMatrixKind(), getMemoryUsage(), getNumValues(), getRow(), getTypeName(), getValue(), getValueType(), hasDiagonalProperty(), invert(), matrixTimesMatrix(), matrixTimesScalar(), matrixTimesVector(), maxDiffNorm(), parseConfiguration(), prefetch(), redistribute(), resetDiagonalProperty(), scale(), setContext(), setDiagonal(), setIdentity(), and wait().

IndexType lama::Matrix::mNumColumns [protected, inherited]

Referenced by lama::Matrix::checkSettings(), lama::DenseMatrix< T >::DenseMatrix(), lama::Matrix::getNumColumns(), lama::Matrix::getSparsityRate(), lama::Matrix::Matrix(), lama::Matrix::setDistributedMatrix(), lama::Matrix::swapMatrix(), and lama::Matrix::writeAt().

IndexType lama::Matrix::mNumRows [protected, inherited]

Referenced by lama::Matrix::checkSettings(), lama::DenseMatrix< T >::DenseMatrix(), lama::Matrix::getNumRows(), lama::Matrix::getSparsityRate(), lama::Matrix::Matrix(), lama::Matrix::setDistributedMatrix(), lama::Matrix::swapMatrix(), and lama::Matrix::writeAt().

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

• /home/brandes/workspace/LAMA/src/lama/matrix/MetaMatrix.hpp
• /home/brandes/workspace/LAMA/src/lama/matrix/MetaMatrix.cpp