#include <deal.II/lac/petsc_sparse_matrix.h>

Inheritance diagram for PETScWrappers::SparseMatrix:

Classes
struct	Traits

Public Member Functions
	SparseMatrix ()

	SparseMatrix (const size_type m, const size_type n, const size_type n_nonzero_per_row, const bool is_symmetric=false)

	SparseMatrix (const size_type m, const size_type n, const std::vector< size_type > &row_lengths, const bool is_symmetric=false)

template<typename SparsityPatternType >
	SparseMatrix (const SparsityPatternType &sparsity_pattern, const bool preset_nonzero_locations=true)

SparseMatrix &	operator= (const double d)

	SparseMatrix (const SparseMatrix &)=delete

SparseMatrix &	operator= (const SparseMatrix &)=delete

void	reinit (const size_type m, const size_type n, const size_type n_nonzero_per_row, const bool is_symmetric=false)

void	reinit (const size_type m, const size_type n, const std::vector< size_type > &row_lengths, const bool is_symmetric=false)

template<typename SparsityPatternType >
void	reinit (const SparsityPatternType &sparsity_pattern, const bool preset_nonzero_locations=true)

virtual const MPI_Comm &	get_mpi_communicator () const override

size_t	m () const

size_t	n () const

void	mmult (SparseMatrix &C, const SparseMatrix &B, const MPI::Vector &V=MPI::Vector()) const

void	Tmmult (SparseMatrix &C, const SparseMatrix &B, const MPI::Vector &V=MPI::Vector()) const

Public Member Functions inherited from PETScWrappers::MatrixBase
	MatrixBase ()

	MatrixBase (const MatrixBase &)=delete

MatrixBase &	operator= (const MatrixBase &)=delete

virtual	~MatrixBase () override

MatrixBase &	operator= (const value_type d)

void	clear ()

void	set (const size_type i, const size_type j, const PetscScalar value)

void	set (const std::vector< size_type > &indices, const FullMatrix< PetscScalar > &full_matrix, const bool elide_zero_values=false)

void	set (const std::vector< size_type > &row_indices, const std::vector< size_type > &col_indices, const FullMatrix< PetscScalar > &full_matrix, const bool elide_zero_values=false)

void	set (const size_type row, const std::vector< size_type > &col_indices, const std::vector< PetscScalar > &values, const bool elide_zero_values=false)

void	set (const size_type row, const size_type n_cols, const size_type col_indices, const PetscScalar values, const bool elide_zero_values=false)

void	add (const size_type i, const size_type j, const PetscScalar value)

void	add (const std::vector< size_type > &indices, const FullMatrix< PetscScalar > &full_matrix, const bool elide_zero_values=true)

void	add (const std::vector< size_type > &row_indices, const std::vector< size_type > &col_indices, const FullMatrix< PetscScalar > &full_matrix, const bool elide_zero_values=true)

void	add (const size_type row, const std::vector< size_type > &col_indices, const std::vector< PetscScalar > &values, const bool elide_zero_values=true)

void	add (const size_type row, const size_type n_cols, const size_type col_indices, const PetscScalar values, const bool elide_zero_values=true, const bool col_indices_are_sorted=false)

void	clear_row (const size_type row, const PetscScalar new_diag_value=0)

void	clear_rows (const std::vector< size_type > &rows, const PetscScalar new_diag_value=0)

void	compress (const VectorOperation::values operation)

PetscScalar	operator() (const size_type i, const size_type j) const

PetscScalar	el (const size_type i, const size_type j) const

PetscScalar	diag_element (const size_type i) const

size_type	m () const

size_type	n () const

size_type	local_size () const

std::pair< size_type, size_type >	local_range () const

bool	in_local_range (const size_type index) const

size_type	n_nonzero_elements () const

size_type	row_length (const size_type row) const

PetscReal	l1_norm () const

PetscReal	linfty_norm () const

PetscReal	frobenius_norm () const

PetscScalar	matrix_norm_square (const VectorBase &v) const

PetscScalar	matrix_scalar_product (const VectorBase &u, const VectorBase &v) const

PetscScalar	trace () const

MatrixBase &	operator*= (const PetscScalar factor)

MatrixBase &	operator/= (const PetscScalar factor)

MatrixBase &	add (const PetscScalar factor, const MatrixBase &other)

MatrixBase &	add (const MatrixBase &other, const PetscScalar factor)

void	vmult (VectorBase &dst, const VectorBase &src) const

void	Tvmult (VectorBase &dst, const VectorBase &src) const

void	vmult_add (VectorBase &dst, const VectorBase &src) const

void	Tvmult_add (VectorBase &dst, const VectorBase &src) const

PetscScalar	residual (VectorBase &dst, const VectorBase &x, const VectorBase &b) const

const_iterator	begin () const

const_iterator	end () const

const_iterator	begin (const size_type r) const

const_iterator	end (const size_type r) const

	operator Mat () const

Mat &	petsc_matrix ()

void	transpose ()

PetscBool	is_symmetric (const double tolerance=1.e-12)

PetscBool	is_hermitian (const double tolerance=1.e-12)

void	write_ascii (const PetscViewerFormat format=PETSC_VIEWER_DEFAULT)

void	print (std::ostream &out, const bool alternative_output=false) const

std::size_t	memory_consumption () const

Public Member Functions inherited from Subscriptor
	Subscriptor ()

	Subscriptor (const Subscriptor &)

	Subscriptor (Subscriptor &&) noexcept

virtual	~Subscriptor ()

Subscriptor &	operator= (const Subscriptor &)

Subscriptor &	operator= (Subscriptor &&) noexcept

void	subscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

void	unsubscribe (std::atomic< bool > *const validity, const std::string &identifier="") const

unsigned int	n_subscriptions () const

template<typename StreamType >
void	list_subscribers (StreamType &stream) const

void	list_subscribers () const

template<class Archive >
void	serialize (Archive &ar, const unsigned int version)

Private Member Functions
void	do_reinit (const size_type m, const size_type n, const size_type n_nonzero_per_row, const bool is_symmetric=false)

void	do_reinit (const size_type m, const size_type n, const std::vector< size_type > &row_lengths, const bool is_symmetric=false)

template<typename SparsityPatternType >
void	do_reinit (const SparsityPatternType &sparsity_pattern, const bool preset_nonzero_locations)

Friends
class	BlockMatrixBase< SparseMatrix >

Additional Inherited Members
Public Types inherited from PETScWrappers::MatrixBase
using	const_iterator = MatrixIterators::const_iterator

using	size_type = types::global_dof_index

using	value_type = PetscScalar

Static Public Member Functions inherited from PETScWrappers::MatrixBase
static ::ExceptionBase &	ExcSourceEqualsDestination ()

static ::ExceptionBase &	ExcWrongMode (int arg1, int arg2)

Static Public Member Functions inherited from Subscriptor
static ::ExceptionBase &	ExcInUse (int arg1, std::string arg2, std::string arg3)

static ::ExceptionBase &	ExcNoSubscriber (std::string arg1, std::string arg2)

Protected Member Functions inherited from PETScWrappers::MatrixBase
void	prepare_action (const VectorOperation::values new_action)

void	assert_is_compressed ()

void	prepare_add ()

void	prepare_set ()

void	mmult (MatrixBase &C, const MatrixBase &B, const VectorBase &V) const

void	Tmmult (MatrixBase &C, const MatrixBase &B, const VectorBase &V) const

Protected Attributes inherited from PETScWrappers::MatrixBase
Mat	matrix

VectorOperation::values	last_action

Detailed Description

Implementation of a sequential sparse matrix class based on PETSc. All the functionality is actually in the base class, except for the calls to generate a sequential sparse matrix. This is possible since PETSc only works on an abstract matrix type and internally distributes to functions that do the actual work depending on the actual matrix type (much like using virtual functions). Only the functions creating a matrix of specific type differ, and are implemented in this particular class.

Author: Wolfgang Bangerth, 2004

Definition at line 51 of file petsc_sparse_matrix.h.

Constructor & Destructor Documentation

◆ SparseMatrix() [1/5]

SparseMatrix< number >::SparseMatrix ( )

Default constructor. Create an empty matrix.

Definition at line 30 of file petsc_sparse_matrix.cc.

◆ SparseMatrix() [2/5]

SparseMatrix< number >::SparseMatrix	(	const size_type	m,
		const size_type	n,
		const size_type	n_nonzero_per_row,
		const bool	is_symmetric = `false`
	)

Create a sparse matrix of dimensions m times n, with an initial guess of n_nonzero_per_row nonzero elements per row. PETSc is able to cope with the situation that more than this number of elements is later allocated for a row, but this involves copying data, and is thus expensive.

The is_symmetric flag determines whether we should tell PETSc that the matrix is going to be symmetric (as indicated by the call MatSetOption(mat, MAT_SYMMETRIC). Note that the PETSc documentation states that one cannot form an ILU decomposition of a matrix for which this flag has been set to true, only an ICC. The default value of this flag is false.

Definition at line 40 of file petsc_sparse_matrix.cc.

◆ SparseMatrix() [3/5]

SparseMatrix< number >::SparseMatrix	(	const size_type	m,
		const size_type	n,
		const std::vector< size_type > &	row_lengths,
		const bool	is_symmetric = `false`
	)

Initialize a rectangular matrix with m rows and n columns. The maximal number of nonzero entries for each row separately is given by the row_lengths array.

Just as for the other constructors: PETSc is able to cope with the situation that more than this number of elements is later allocated for a row, but this involves copying data, and is thus expensive.

The is_symmetric flag determines whether we should tell PETSc that the matrix is going to be symmetric (as indicated by the call MatSetOption(mat, MAT_SYMMETRIC). Note that the PETSc documentation states that one cannot form an ILU decomposition of a matrix for which this flag has been set to true, only an ICC. The default value of this flag is false.

Definition at line 50 of file petsc_sparse_matrix.cc.

◆ SparseMatrix() [4/5]

template<typename SparsityPatternType >

SparseMatrix< SparsityPatternType >::SparseMatrix	(	const SparsityPatternType &	sparsity_pattern,
		const bool	preset_nonzero_locations = `true`
	)

explicit

Initialize a sparse matrix using the given sparsity pattern.

Note that PETSc can be very slow if you do not provide it with a good estimate of the lengths of rows. Using the present function is a very efficient way to do this, as it uses the exact number of nonzero entries for each row of the matrix by using the given sparsity pattern argument. If the preset_nonzero_locations flag is true, this function in addition not only sets the correct row sizes up front, but also pre-allocated the correct nonzero entries in the matrix.

PETsc allows to later add additional nonzero entries to a matrix, by simply writing to these elements. However, this will then lead to additional memory allocations which are very inefficient and will greatly slow down your program. It is therefore significantly more efficient to get memory allocation right from the start.

Definition at line 61 of file petsc_sparse_matrix.cc.

◆ SparseMatrix() [5/5]

PETScWrappers::SparseMatrix::SparseMatrix ( const SparseMatrix & )

delete

The copy constructor is deleted.

Member Function Documentation

◆ operator=() [1/2]

SparseMatrix & SparseMatrix< number >::operator= ( const double d )

This operator assigns a scalar to a matrix. Since this does usually not make much sense (should we set all matrix entries to this value? Only the nonzero entries of the sparsity pattern?), this operation is only allowed if the actual value to be assigned is zero. This operator only exists to allow for the obvious notation matrix=0, which sets all elements of the matrix to zero, but keep the sparsity pattern previously used.

Definition at line 70 of file petsc_sparse_matrix.cc.

◆ operator=() [2/2]

SparseMatrix& PETScWrappers::SparseMatrix::operator= ( const SparseMatrix & )

delete

The copy assignment operator is deleted.

◆ reinit() [1/3]

void SparseMatrix< number >::reinit	(	const size_type	m,
		const size_type	n,
		const size_type	n_nonzero_per_row,
		const bool	is_symmetric = `false`
	)

Throw away the present matrix and generate one that has the same properties as if it were created by the constructor of this class with the same argument list as the present function.

Definition at line 79 of file petsc_sparse_matrix.cc.

◆ reinit() [2/3]

void SparseMatrix< number >::reinit	(	const size_type	m,
		const size_type	n,
		const std::vector< size_type > &	row_lengths,
		const bool	is_symmetric = `false`
	)

Throw away the present matrix and generate one that has the same properties as if it were created by the constructor of this class with the same argument list as the present function.

Definition at line 95 of file petsc_sparse_matrix.cc.

◆ reinit() [3/3]

template<typename SparsityPatternType >

void SparseMatrix< SparsityPatternType >::reinit	(	const SparsityPatternType &	sparsity_pattern,
		const bool	preset_nonzero_locations = `true`
	)

Initialize a sparse matrix using the given sparsity pattern.

Note that PETSc can be very slow if you do not provide it with a good estimate of the lengths of rows. Using the present function is a very efficient way to do this, as it uses the exact number of nonzero entries for each row of the matrix by using the given sparsity pattern argument. If the preset_nonzero_locations flag is true, this function in addition not only sets the correct row sizes up front, but also pre-allocated the correct nonzero entries in the matrix.

PETsc allows to later add additional nonzero entries to a matrix, by simply writing to these elements. However, this will then lead to additional memory allocations which are very inefficient and will greatly slow down your program. It is therefore significantly more efficient to get memory allocation right from the start.

Despite the fact that it would seem to be an obvious win, setting the preset_nonzero_locations flag to true doesn't seem to accelerate program. Rather on the contrary, it seems to be able to slow down entire programs somewhat. This is surprising, since we can use efficient function calls into PETSc that allow to create multiple entries at once; nevertheless, given the fact that it is inefficient, the respective flag has a default value equal to false.

Definition at line 112 of file petsc_sparse_matrix.cc.

◆ get_mpi_communicator()

const MPI_Comm & SparseMatrix< number >::get_mpi_communicator ( ) const

overridevirtual

Return a reference to the MPI communicator object in use with this matrix. Since this is a sequential matrix, it returns the MPI_COMM_SELF communicator.

Implements PETScWrappers::MatrixBase.

Definition at line 126 of file petsc_sparse_matrix.cc.

◆ m()

size_t SparseMatrix< number >::m ( ) const

Return the number of rows of this matrix.

Definition at line 248 of file petsc_sparse_matrix.cc.

◆ n()

size_t SparseMatrix< number >::n ( ) const

Return the number of columns of this matrix.

Definition at line 258 of file petsc_sparse_matrix.cc.

◆ mmult()

void SparseMatrix< number >::mmult	(	SparseMatrix &	C,
		const SparseMatrix &	B,
		const MPI::Vector &	V = `MPI::Vector()`
	)		const

Perform the matrix-matrix multiplication \(C = AB\), or, \(C = A \text{diag}(V) B\) given a compatible vector \(V\).

This function calls MatrixBase::mmult() to do the actual work.

Definition at line 268 of file petsc_sparse_matrix.cc.

◆ Tmmult()

void SparseMatrix< number >::Tmmult	(	SparseMatrix &	C,
		const SparseMatrix &	B,
		const MPI::Vector &	V = `MPI::Vector()`
	)		const

Perform the matrix-matrix multiplication with the transpose of this, i.e., \(C = A^T B\), or, \(C = A^T \text{diag}(V) B\) given a compatible vector \(V\).

This function calls MatrixBase::Tmmult() to do the actual work.

Definition at line 279 of file petsc_sparse_matrix.cc.

◆ do_reinit() [1/3]

void SparseMatrix< number >::do_reinit	(	const size_type	m,
		const size_type	n,
		const size_type	n_nonzero_per_row,
		const bool	is_symmetric = `false`
	)

private

Do the actual work for the respective reinit() function and the matching constructor, i.e. create a matrix. Getting rid of the previous matrix is left to the caller.

Definition at line 138 of file petsc_sparse_matrix.cc.

◆ do_reinit() [2/3]

void SparseMatrix< number >::do_reinit	(	const size_type	m,
		const size_type	n,
		const std::vector< size_type > &	row_lengths,
		const bool	is_symmetric = `false`
	)

private

Same as previous function.

Definition at line 160 of file petsc_sparse_matrix.cc.

◆ do_reinit() [3/3]

template<typename SparsityPatternType >

void SparseMatrix< SparsityPatternType >::do_reinit	(	const SparsityPatternType &	sparsity_pattern,
		const bool	preset_nonzero_locations
	)

private

Same as previous function.

Definition at line 194 of file petsc_sparse_matrix.cc.

Friends And Related Function Documentation

◆ BlockMatrixBase< SparseMatrix >

friend class BlockMatrixBase< SparseMatrix >

friend

To allow calling protected prepare_add() and prepare_set().

Definition at line 286 of file petsc_sparse_matrix.h.

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

deal.II/lac/petsc_sparse_matrix.h
source/lac/petsc_sparse_matrix.cc

Classes

Public Member Functions

Private Member Functions

Friends

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ SparseMatrix() [1/5]

◆ SparseMatrix() [2/5]

◆ SparseMatrix() [3/5]

◆ SparseMatrix() [4/5]

◆ SparseMatrix() [5/5]

Member Function Documentation

◆ operator=() [1/2]

◆ operator=() [2/2]

◆ reinit() [1/3]

◆ reinit() [2/3]

◆ reinit() [3/3]

◆ get_mpi_communicator()

◆ m()

◆ n()

◆ mmult()

◆ Tmmult()

◆ do_reinit() [1/3]

◆ do_reinit() [2/3]

◆ do_reinit() [3/3]

Friends And Related Function Documentation

◆ BlockMatrixBase< SparseMatrix >