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

Inheritance diagram for LinearAlgebra::distributed::BlockVector< Number >:

Public Types
typedef BlockVectorBase< Vector< Number > >	BaseClass

typedef BaseClass::BlockType	BlockType

typedef BaseClass::value_type	value_type

Public Types inherited from BlockVectorBase< Vector< Number > >
typedef Vector< Number >	BlockType

typedef BlockType::real_type	real_type

Public Member Functions
1: Basic operations
	BlockVector (const size_type num_blocks=0, const size_type block_size=0)

	BlockVector (const BlockVector< Number > &V)

template<typename OtherNumber >
	BlockVector (const BlockVector< OtherNumber > &v)

	BlockVector (const std::vector< size_type > &block_sizes)

	BlockVector (const std::vector< IndexSet > &local_ranges, const std::vector< IndexSet > &ghost_indices, const MPI_Comm communicator)

	BlockVector (const std::vector< IndexSet > &local_ranges, const MPI_Comm communicator)

virtual BlockVector &	operator= (const value_type s) override

BlockVector &	operator= (const BlockVector &V)

template<class Number2 >
BlockVector &	operator= (const BlockVector< Number2 > &V)

BlockVector &	operator= (const Vector< Number > &V)

BlockVector< Number > &	operator= (const PETScWrappers::MPI::BlockVector &petsc_vec)

BlockVector< Number > &	operator= (const TrilinosWrappers::MPI::BlockVector &trilinos_vec)

void	reinit (const size_type num_blocks, const size_type block_size=0, const bool omit_zeroing_entries=false)

void	reinit (const std::vector< size_type > &N, const bool omit_zeroing_entries=false)

template<typename Number2 >
void	reinit (const BlockVector< Number2 > &V, const bool omit_zeroing_entries=false)

virtual void	compress (::VectorOperation::values operation) override

void	update_ghost_values () const

void	zero_out_ghosts () const

bool	has_ghost_elements () const

template<typename OtherNumber >
void	add (const std::vector< size_type > &indices, const ::Vector< OtherNumber > &values)

void	sadd (const Number s, const BlockVector< Number > &V)

void	equ (const Number a, const BlockVector< Number > &u, const Number b, const BlockVector< Number > &v)

void	sadd (const Number s, const Number a, const BlockVector< Number > &V, const Number b, const BlockVector< Number > &W)

virtual bool	all_zero () const override

virtual Number	mean_value () const override

real_type	lp_norm (const real_type p) const

void	swap (BlockVector< Number > &v)

2: Implementation of VectorSpaceVector
virtual void	reinit (const VectorSpaceVector< Number > &V, const bool omit_zeroing_entries=false) override

virtual BlockVector< Number > &	operator*= (const Number factor) override

virtual BlockVector< Number > &	operator/= (const Number factor) override

virtual BlockVector< Number > &	operator+= (const VectorSpaceVector< Number > &V) override

virtual BlockVector< Number > &	operator-= (const VectorSpaceVector< Number > &V) override

virtual void	import (const LinearAlgebra::ReadWriteVector< Number > &V, VectorOperation::values operation, std::shared_ptr< const CommunicationPatternBase > communication_pattern=std::shared_ptr< const CommunicationPatternBase >()) override

virtual Number	operator* (const VectorSpaceVector< Number > &V) const override

template<typename FullMatrixType >
void	multivector_inner_product (FullMatrixType &matrix, const BlockVector< Number > &V, const bool symmetric=false) const

template<typename FullMatrixType >
Number	multivector_inner_product_with_metric (const FullMatrixType &matrix, const BlockVector< Number > &V, const bool symmetric=false) const

template<typename FullMatrixType >
void	mmult (BlockVector< Number > &V, const FullMatrixType &matrix, const Number s=Number(0.), const Number b=Number(1.)) const

virtual void	add (const Number a) override

virtual void	add (const Number a, const VectorSpaceVector< Number > &V) override

virtual void	add (const Number a, const VectorSpaceVector< Number > &V, const Number b, const VectorSpaceVector< Number > &W) override

virtual void	add (const std::vector< size_type > &indices, const std::vector< Number > &values)

virtual void	sadd (const Number s, const Number a, const VectorSpaceVector< Number > &V) override

virtual void	scale (const VectorSpaceVector< Number > &scaling_factors) override

virtual void	equ (const Number a, const VectorSpaceVector< Number > &V) override

virtual real_type	l1_norm () const override

virtual real_type	l2_norm () const override

real_type	norm_sqr () const

virtual real_type	linfty_norm () const override

virtual Number	add_and_dot (const Number a, const VectorSpaceVector< Number > &V, const VectorSpaceVector< Number > &W) override

virtual size_type	size () const override

virtual ::IndexSet	locally_owned_elements () const override

virtual void	print (std::ostream &out, const unsigned int precision=3, const bool scientific=true, const bool across=true) const override

virtual std::size_t	memory_consumption () const override

Public Member Functions inherited from BlockVectorBase< Vector< Number > >
	BlockVectorBase ()=default

	BlockVectorBase (const BlockVectorBase &)=default

	BlockVectorBase (BlockVectorBase &&) noexcept=default

void	collect_sizes ()

void	compress (::VectorOperation::values operation)

BlockType &	block (const unsigned int i)

const BlockType &	block (const unsigned int i) const

const BlockIndices &	get_block_indices () const

unsigned int	n_blocks () const

std::size_t	size () const

IndexSet	locally_owned_elements () const

iterator	begin ()

const_iterator	begin () const

iterator	end ()

const_iterator	end () const

value_type	operator() (const size_type i) const

reference	operator() (const size_type i)

value_type	operator[] (const size_type i) const

reference	operator[] (const size_type i)

void	extract_subvector_to (const std::vector< size_type > &indices, std::vector< OtherNumber > &values) const

void	extract_subvector_to (ForwardIterator indices_begin, const ForwardIterator indices_end, OutputIterator values_begin) const

BlockVectorBase &	operator= (const value_type s)

BlockVectorBase &	operator= (const BlockVectorBase &V)

BlockVectorBase &	operator= (BlockVectorBase &&)=default

BlockVectorBase &	operator= (const BlockVectorBase< VectorType2 > &V)

BlockVectorBase &	operator= (const Vector< Number > &v)

bool	operator== (const BlockVectorBase< VectorType2 > &v) const

value_type	operator* (const BlockVectorBase &V) const

real_type	norm_sqr () const

value_type	mean_value () const

real_type	l1_norm () const

real_type	l2_norm () const

real_type	linfty_norm () const

value_type	add_and_dot (const value_type a, const BlockVectorBase &V, const BlockVectorBase &W)

bool	in_local_range (const size_type global_index) const

bool	all_zero () const

bool	is_non_negative () const

BlockVectorBase &	operator+= (const BlockVectorBase &V)

BlockVectorBase &	operator-= (const BlockVectorBase &V)

void	add (const std::vector< size_type > &indices, const std::vector< Number > &values)

void	add (const std::vector< size_type > &indices, const Vector< Number > &values)

void	add (const size_type n_elements, const size_type indices, const Number values)

void	add (const value_type s)

void	add (const value_type a, const BlockVectorBase &V)

void	add (const value_type a, const BlockVectorBase &V, const value_type b, const BlockVectorBase &W)

void	sadd (const value_type s, const BlockVectorBase &V)

void	sadd (const value_type s, const value_type a, const BlockVectorBase &V)

void	sadd (const value_type s, const value_type a, const BlockVectorBase &V, const value_type b, const BlockVectorBase &W)

void	sadd (const value_type s, const value_type a, const BlockVectorBase &V, const value_type b, const BlockVectorBase &W, const value_type c, const BlockVectorBase &X)

BlockVectorBase &	operator*= (const value_type factor)

BlockVectorBase &	operator/= (const value_type factor)

void	scale (const BlockVector2 &v)

void	equ (const value_type a, const BlockVector2 &V)

void	equ (const value_type a, const BlockVectorBase &V, const value_type b, const BlockVectorBase &W)

void	update_ghost_values () 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 (const char *identifier=nullptr) const

void	unsubscribe (const char *identifier=nullptr) const

unsigned int	n_subscriptions () const

void	list_subscribers () const

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

Public Member Functions inherited from LinearAlgebra::VectorSpaceVector< Number >
virtual VectorSpaceVector< Number > &	operator= (const Number s)=0

virtual void	compress (VectorOperation::values)

virtual	~VectorSpaceVector ()=default

Static Public Member Functions
static ::ExceptionBase &	ExcVectorTypeNotCompatible ()

static ::ExceptionBase &	ExcIteratorRangeDoesNotMatchVectorSize ()

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)

Static Private Attributes
static constexpr unsigned int	communication_block_size = 20

Additional Inherited Members
Protected Attributes inherited from BlockVectorBase< Vector< Number > >
std::vector< Vector< Number > >	components

BlockIndices	block_indices

Detailed Description

template<typename Number>
class LinearAlgebra::distributed::BlockVector< Number >

An implementation of block vectors based on distributed deal.II vectors. While the base class provides for most of the interface, this class handles the actual allocation of vectors and provides functions that are specific to the underlying vector type.

Note: Instantiations for this template are provided for <float> and <double>; others can be generated in application programs (see the section on Template instantiations in the manual).

See also: Block (linear algebra)

Author: Katharina Kormann, Martin Kronbichler, 2011

Definition at line 81 of file la_parallel_block_vector.h.

Member Typedef Documentation

◆ BaseClass

template<typename Number>

typedef BlockVectorBase<Vector<Number> > LinearAlgebra::distributed::BlockVector< Number >::BaseClass

Typedef the base class for simpler access to its own typedefs.

Definition at line 101 of file la_parallel_block_vector.h.

◆ BlockType

template<typename Number>

typedef BaseClass::BlockType LinearAlgebra::distributed::BlockVector< Number >::BlockType

Typedef the type of the underlying vector.

Definition at line 106 of file la_parallel_block_vector.h.

◆ value_type

template<typename Number>

typedef BaseClass::value_type LinearAlgebra::distributed::BlockVector< Number >::value_type

Import the typedefs from the base class.

Definition at line 111 of file la_parallel_block_vector.h.

Constructor & Destructor Documentation

◆ BlockVector() [1/6]

template<typename Number>

LinearAlgebra::distributed::BlockVector< Number >::BlockVector	(	const size_type	num_blocks = `0`,
		const size_type	block_size = `0`
	)

explicit

Constructor. There are three ways to use this constructor. First, without any arguments, it generates an object with no blocks. Given one argument, it initializes num_blocks blocks, but these blocks have size zero. The third variant finally initializes all blocks to the same size block_size.

Confer the other constructor further down if you intend to use blocks of different sizes.

◆ BlockVector() [2/6]

template<typename Number>

LinearAlgebra::distributed::BlockVector< Number >::BlockVector ( const BlockVector< Number > & V )

Copy-Constructor. Dimension set to that of V, all components are copied from V

◆ BlockVector() [3/6]

template<typename Number>

template<typename OtherNumber >

LinearAlgebra::distributed::BlockVector< Number >::BlockVector ( const BlockVector< OtherNumber > & v )

explicit

Copy constructor taking a BlockVector of another data type. This will fail if there is no conversion path from OtherNumber to Number. Note that you may lose accuracy when copying to a BlockVector with data elements with less accuracy.

Older versions of gcc did not honor the explicit keyword on template constructors. In such cases, it is easy to accidentally write code that can be very inefficient, since the compiler starts performing hidden conversions. To avoid this, this function is disabled if we have detected a broken compiler during configuration.

◆ BlockVector() [4/6]

template<typename Number>

LinearAlgebra::distributed::BlockVector< Number >::BlockVector ( const std::vector< size_type > & block_sizes )

Constructor. Set the number of blocks to block_sizes.size() and initialize each block with block_sizes[i] zero elements.

◆ BlockVector() [5/6]

template<typename Number>

LinearAlgebra::distributed::BlockVector< Number >::BlockVector	(	const std::vector< IndexSet > &	local_ranges,
		const std::vector< IndexSet > &	ghost_indices,
		const MPI_Comm	communicator
	)

Construct a block vector with an IndexSet for the local range and ghost entries for each block.

◆ BlockVector() [6/6]

template<typename Number>

LinearAlgebra::distributed::BlockVector< Number >::BlockVector	(	const std::vector< IndexSet > &	local_ranges,
		const MPI_Comm	communicator
	)

Same as above but the ghost indices are assumed to be empty.

Member Function Documentation

◆ operator=() [1/6]

template<typename Number>

virtual BlockVector& LinearAlgebra::distributed::BlockVector< Number >::operator= ( const value_type s )

overridevirtual

Copy operator: fill all components of the vector with the given scalar value.

◆ operator=() [2/6]

template<typename Number>

BlockVector& LinearAlgebra::distributed::BlockVector< Number >::operator= ( const BlockVector< Number > & V )

Copy operator for arguments of the same type. Resize the present vector if necessary.

◆ operator=() [3/6]

template<typename Number>

template<class Number2 >

BlockVector& LinearAlgebra::distributed::BlockVector< Number >::operator= ( const BlockVector< Number2 > & V )

Copy operator for template arguments of different types. Resize the present vector if necessary.

◆ operator=() [4/6]

template<typename Number>

BlockVector& LinearAlgebra::distributed::BlockVector< Number >::operator= ( const Vector< Number > & V )

Copy a regular vector into a block vector.

◆ operator=() [5/6]

template<typename Number>

BlockVector<Number>& LinearAlgebra::distributed::BlockVector< Number >::operator= ( const PETScWrappers::MPI::BlockVector< Number > & petsc_vec )

Copy the content of a PETSc vector into the calling vector. This function assumes that the vectors layouts have already been initialized to match.

This operator is only available if deal.II was configured with PETSc.

◆ operator=() [6/6]

template<typename Number>

BlockVector<Number>& LinearAlgebra::distributed::BlockVector< Number >::operator= ( const TrilinosWrappers::MPI::BlockVector< Number > & trilinos_vec )

Copy the content of a Trilinos vector into the calling vector. This function assumes that the vectors layouts have already been initialized to match.

This operator is only available if deal.II was configured with Trilinos.

◆ reinit() [1/4]

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::reinit	(	const size_type	num_blocks,
		const size_type	block_size = `0`,
		const bool	omit_zeroing_entries = `false`
	)

Reinitialize the BlockVector to contain num_blocks blocks of size block_size each.

If the second argument is left at its default value, then the block vector allocates the specified number of blocks but leaves them at zero size. You then need to later reinitialize the individual blocks, and call collect_sizes() to update the block system's knowledge of its individual block's sizes.

If omit_zeroing_entries==false, the vector is filled with zeros.

◆ reinit() [2/4]

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::reinit	(	const std::vector< size_type > &	N,
		const bool	omit_zeroing_entries = `false`
	)

Reinitialize the BlockVector such that it contains block_sizes.size() blocks. Each block is reinitialized to dimension block_sizes[i].

If the number of blocks is the same as before this function was called, all vectors remain the same and reinit() is called for each vector.

If omit_zeroing_entries==false, the vector is filled with zeros.

Note that you must call this (or the other reinit() functions) function, rather than calling the reinit() functions of an individual block, to allow the block vector to update its caches of vector sizes. If you call reinit() on one of the blocks, then subsequent actions on this object may yield unpredictable results since they may be routed to the wrong block.

◆ reinit() [3/4]

template<typename Number>

template<typename Number2 >

void LinearAlgebra::distributed::BlockVector< Number >::reinit	(	const BlockVector< Number2 > &	V,
		const bool	omit_zeroing_entries = `false`
	)

Change the dimension to that of the vector V. The same applies as for the other reinit() function.

The elements of V are not copied, i.e. this function is the same as calling reinit (V.size(), omit_zeroing_entries).

Note that you must call this (or the other reinit() functions) function, rather than calling the reinit() functions of an individual block, to allow the block vector to update its caches of vector sizes. If you call reinit() of one of the blocks, then subsequent actions of this object may yield unpredictable results since they may be routed to the wrong block.

◆ compress()

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::compress ( ::VectorOperation::values operation )

overridevirtual

This function copies the data that has accumulated in the data buffer for ghost indices to the owning processor. For the meaning of the argument operation, see the entry on Compressing distributed vectors and matrices in the glossary.

There are two variants for this function. If called with argument VectorOperation::add adds all the data accumulated in ghost elements to the respective elements on the owning processor and clears the ghost array afterwards. If called with argument VectorOperation::insert, a set operation is performed. Since setting elements in a vector with ghost elements is ambiguous (as one can set both the element on the ghost site as well as the owning site), this operation makes the assumption that all data is set correctly on the owning processor. Upon call of compress(VectorOperation::insert), all ghost entries are therefore simply zeroed out (using zero_ghost_values()). In debug mode, a check is performed that makes sure that the data set is actually consistent between processors, i.e., whenever a non-zero ghost element is found, it is compared to the value on the owning processor and an exception is thrown if these elements do not agree.

◆ update_ghost_values()

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::update_ghost_values ( ) const

Fills the data field for ghost indices with the values stored in the respective positions of the owning processor. This function is needed before reading from ghosts. The function is const even though ghost data is changed. This is needed to allow functions with a const vector to perform the data exchange without creating temporaries.

◆ zero_out_ghosts()

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::zero_out_ghosts ( ) const

This method zeros the entries on ghost dofs, but does not touch locally owned DoFs.

After calling this method, read access to ghost elements of the vector is forbidden and an exception is thrown. Only write access to ghost elements is allowed in this state.

◆ has_ghost_elements()

template<typename Number>

bool LinearAlgebra::distributed::BlockVector< Number >::has_ghost_elements ( ) const

Return if this Vector contains ghost elements.

◆ add() [1/5]

template<typename Number>

template<typename OtherNumber >

void LinearAlgebra::distributed::BlockVector< Number >::add	(	const std::vector< size_type > &	indices,
		const ::Vector< OtherNumber > &	values
	)

This is a collective add operation that adds a whole set of values stored in values to the vector components specified by indices.

◆ sadd() [1/3]

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::sadd	(	const Number	s,
		const BlockVector< Number > &	V
	)

Scaling and simple vector addition, i.e. *this = s*(*this)+V.

◆ equ() [1/2]

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::equ	(	const Number	a,
		const BlockVector< Number > &	u,
		const Number	b,
		const BlockVector< Number > &	v
	)

Assignment *this = a*u + b*v.

This function is deprecated.

◆ sadd() [2/3]

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::sadd	(	const Number	s,
		const Number	a,
		const BlockVector< Number > &	V,
		const Number	b,
		const BlockVector< Number > &	W
	)

Scaling and multiple addition.

This function is deprecated.

◆ all_zero()

template<typename Number>

virtual bool LinearAlgebra::distributed::BlockVector< Number >::all_zero ( ) const

overridevirtual

Return whether the vector contains only elements with value zero. This function is mainly for internal consistency checks and should seldom be used when not in debug mode since it uses quite some time.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ mean_value()

template<typename Number>

virtual Number LinearAlgebra::distributed::BlockVector< Number >::mean_value ( ) const

overridevirtual

Compute the mean value of all the entries in the vector.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ lp_norm()

template<typename Number>

real_type LinearAlgebra::distributed::BlockVector< Number >::lp_norm ( const real_type p ) const

\(l_p\)-norm of the vector. The pth root of the sum of the pth powers of the absolute values of the elements.

◆ swap()

template<typename Number>

void LinearAlgebra::distributed::BlockVector< Number >::swap ( BlockVector< Number > & v )

Swap the contents of this vector and the other vector v. One could do this operation with a temporary variable and copying over the data elements, but this function is significantly more efficient since it only swaps the pointers to the data of the two vectors and therefore does not need to allocate temporary storage and move data around.

Limitation: right now this function only works if both vectors have the same number of blocks. If needed, the numbers of blocks should be exchanged, too.

This function is analogous to the swap() function of all C++ standard containers. Also, there is a global function swap(u,v) that simply calls u.swap(v), again in analogy to standard functions.

◆ reinit() [4/4]

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::reinit	(	const VectorSpaceVector< Number > &	V,
		const bool	omit_zeroing_entries = `false`
	)

overridevirtual

Change the dimension to that of the vector V. The elements of V are not copied.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ operator*=()

template<typename Number>

virtual BlockVector<Number>& LinearAlgebra::distributed::BlockVector< Number >::operator*= ( const Number factor )

overridevirtual

Multiply the entire vector by a fixed factor.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ operator/=()

template<typename Number>

virtual BlockVector<Number>& LinearAlgebra::distributed::BlockVector< Number >::operator/= ( const Number factor )

overridevirtual

Divide the entire vector by a fixed factor.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ operator+=()

template<typename Number>

virtual BlockVector<Number>& LinearAlgebra::distributed::BlockVector< Number >::operator+= ( const VectorSpaceVector< Number > & V )

overridevirtual

Add the vector V to the present one.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ operator-=()

template<typename Number>

virtual BlockVector<Number>& LinearAlgebra::distributed::BlockVector< Number >::operator-= ( const VectorSpaceVector< Number > & V )

overridevirtual

Subtract the vector V from the present one.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ import()

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::import	(	const LinearAlgebra::ReadWriteVector< Number > &	V,
		VectorOperation::values	operation,
		std::shared_ptr< const CommunicationPatternBase >	communication_pattern = `std::shared_ptr< const CommunicationPatternBase >()`
	)

overridevirtual

Import all the elements present in the vector's IndexSet from the input vector V. VectorOperation::values operation is used to decide if the elements in V should be added to the current vector or replace the current elements. The last parameter can be used if the same communication pattern is used multiple times. This can be used to improve performance.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ operator*()

template<typename Number>

virtual Number LinearAlgebra::distributed::BlockVector< Number >::operator* ( const VectorSpaceVector< Number > & V ) const

overridevirtual

Return the scalar product of two vectors.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ multivector_inner_product()

template<typename Number>

template<typename FullMatrixType >

void LinearAlgebra::distributed::BlockVector< Number >::multivector_inner_product	(	FullMatrixType &	matrix,
		const BlockVector< Number > &	V,
		const bool	symmetric = `false`
	)		const

Calculate the scalar product between each block of this vector and V and store the result in a full matrix matrix. This function computes the result by forming \(A_{ij}=U_i \cdot V_j\) where \(U_i\) and \(V_j\) indicate the \(i\)th block (not element!) of \(U\) and the \(j\)th block of \(V\), respectively. If symmetric is true, it is assumed that inner product results in a square symmetric matrix and almost half of the scalar products can be avoided.

Obviously, this function can only be used if all blocks of both vectors are of the same size.

Note: Internally, a single global reduction will be called to accumulate scalar product between locally owned degrees of freedom.

◆ multivector_inner_product_with_metric()

template<typename Number>

template<typename FullMatrixType >

Number LinearAlgebra::distributed::BlockVector< Number >::multivector_inner_product_with_metric	(	const FullMatrixType &	matrix,
		const BlockVector< Number > &	V,
		const bool	symmetric = `false`
	)		const

Calculate the scalar product between each block of this vector and V using a metric tensor matrix. This function computes the result of \( \sum_{ij} A^{ij} U_i \cdot V_j\) where \(U_i\) and \(V_j\) indicate the \(i\)th block (not element) of \(U\) and the \(j\)th block of \(V\), respectively. If symmetric is true, it is assumed that \(U_i \cdot V_j\) and \(A^{ij}\) are symmetric matrices and almost half of the scalar products can be avoided.

Obviously, this function can only be used if all blocks of both vectors are of the same size.

Note: Internally, a single global reduction will be called to accumulate the scalar product between locally owned degrees of freedom.

◆ mmult()

template<typename Number>

template<typename FullMatrixType >

void LinearAlgebra::distributed::BlockVector< Number >::mmult	(	BlockVector< Number > &	V,
		const FullMatrixType &	matrix,
		const Number	s = `Number(0.)`,
		const Number	b = `Number(1.)`
	)		const

Set each block of this vector as follows: \(V^i = s V^i + b \sum_{j} U_j A^{ji}\) where \(V^i\) and \(U_j\) indicate the \(i\)th block (not element) of \(V\) and the \(j\)th block of \(U\), respectively.

Obviously, this function can only be used if all blocks of both vectors are of the same size.

◆ add() [2/5]

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::add ( const Number a )

overridevirtual

Add a to all components. Note that a is a scalar not a vector.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ add() [3/5]

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::add	(	const Number	a,
		const VectorSpaceVector< Number > &	V
	)

overridevirtual

Simple addition of a multiple of a vector, i.e. *this += a*V.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ add() [4/5]

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::add	(	const Number	a,
		const VectorSpaceVector< Number > &	V,
		const Number	b,
		const VectorSpaceVector< Number > &	W
	)

overridevirtual

Multiple addition of scaled vectors, i.e. *this += a*V+b*W.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ add() [5/5]

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::add	(	const std::vector< size_type > &	indices,
		const std::vector< Number > &	values
	)

virtual

A collective add operation: This function adds a whole set of values stored in values to the vector components specified by indices.

◆ sadd() [3/3]

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::sadd	(	const Number	s,
		const Number	a,
		const VectorSpaceVector< Number > &	V
	)

overridevirtual

Scaling and simple addition of a multiple of a vector, i.e. *this = s*(*this)+a*V.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ scale()

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::scale ( const VectorSpaceVector< Number > & scaling_factors )

overridevirtual

Scale each element of this vector by the corresponding element in the argument. This function is mostly meant to simulate multiplication (and immediate re-assignment) by a diagonal scaling matrix.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ equ() [2/2]

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::equ	(	const Number	a,
		const VectorSpaceVector< Number > &	V
	)

overridevirtual

Assignment *this = a*V.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ l1_norm()

template<typename Number>

virtual real_type LinearAlgebra::distributed::BlockVector< Number >::l1_norm ( ) const

overridevirtual

Return the l₁ norm of the vector (i.e., the sum of the absolute values of all entries among all processors).

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ l2_norm()

template<typename Number>

virtual real_type LinearAlgebra::distributed::BlockVector< Number >::l2_norm ( ) const

overridevirtual

Return the \(l_2\) norm of the vector (i.e., the square root of the sum of the square of all entries among all processors).

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ norm_sqr()

template<typename Number>

real_type LinearAlgebra::distributed::BlockVector< Number >::norm_sqr ( ) const

Return the square of the \(l_2\) norm of the vector.

◆ linfty_norm()

template<typename Number>

virtual real_type LinearAlgebra::distributed::BlockVector< Number >::linfty_norm ( ) const

overridevirtual

Return the maximum norm of the vector (i.e., the maximum absolute value among all entries and among all processors).

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ add_and_dot()

template<typename Number>

virtual Number LinearAlgebra::distributed::BlockVector< Number >::add_and_dot	(	const Number	a,
		const VectorSpaceVector< Number > &	V,
		const VectorSpaceVector< Number > &	W
	)

overridevirtual

Perform a combined operation of a vector addition and a subsequent inner product, returning the value of the inner product. In other words, the result of this function is the same as if the user called

this->add(a, V);

return_value = *this * W;

The reason this function exists is that this operation involves less memory transfer than calling the two functions separately. This method only needs to load three vectors, this, V, W, whereas calling separate methods means to load the calling vector this twice. Since most vector operations are memory transfer limited, this reduces the time by 25% (or 50% if W equals this).

For complex-valued vectors, the scalar product in the second step is implemented as \(\left<v,w\right>=\sum_i v_i \bar{w_i}\).

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ size()

template<typename Number>

virtual size_type LinearAlgebra::distributed::BlockVector< Number >::size ( ) const

overridevirtual

Return the global size of the vector, equal to the sum of the number of locally owned indices among all processors.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ locally_owned_elements()

template<typename Number>

virtual ::IndexSet LinearAlgebra::distributed::BlockVector< Number >::locally_owned_elements ( ) const

overridevirtual

Return an index set that describes which elements of this vector are owned by the current processor. As a consequence, the index sets returned on different processors if this is a distributed vector will form disjoint sets that add up to the complete index set. Obviously, if a vector is created on only one processor, then the result would satisfy

vec.locally_owned_elements() == complete_index_set(vec.size())

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ print()

template<typename Number>

virtual void LinearAlgebra::distributed::BlockVector< Number >::print	(	std::ostream &	out,
		const unsigned int	precision = `3`,
		const bool	scientific = `true`,
		const bool	across = `true`
	)		const

overridevirtual

Print the vector to the output stream out.

Implements LinearAlgebra::VectorSpaceVector< Number >.

◆ memory_consumption()

template<typename Number>

virtual std::size_t LinearAlgebra::distributed::BlockVector< Number >::memory_consumption ( ) const

overridevirtual

Return the memory consumption of this class in bytes.

Implements LinearAlgebra::VectorSpaceVector< Number >.

Member Data Documentation

◆ communication_block_size

template<typename Number>

constexpr unsigned int LinearAlgebra::distributed::BlockVector< Number >::communication_block_size = 20

staticprivate

The chunks size to split communication in update_ghost_values() and compress() calls.

Most common MPI implementations will get slow when too many messages/requests are outstanding. Even when messages are small, say 1 kB only, we should collect enough data with communication_block_size to cover typical infiniband latencies which are around a few microseconds. Sending 20 kB at a throughput of 5 GB/s takes 4 microseconds, so we should arrive at the bandwidth dominated regime then which is good enough.

Definition at line 95 of file la_parallel_block_vector.h.

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

deal.II/lac/la_parallel_block_vector.h

Public Types

Public Member Functions

Static Public Member Functions

Static Private Attributes

Additional Inherited Members

Detailed Description

template<typename Number> class LinearAlgebra::distributed::BlockVector< Number >

Member Typedef Documentation

◆ BaseClass

◆ BlockType

◆ value_type

Constructor & Destructor Documentation

◆ BlockVector() [1/6]

◆ BlockVector() [2/6]

◆ BlockVector() [3/6]

◆ BlockVector() [4/6]

◆ BlockVector() [5/6]

◆ BlockVector() [6/6]

Member Function Documentation

◆ operator=() [1/6]

◆ operator=() [2/6]

◆ operator=() [3/6]

◆ operator=() [4/6]

◆ operator=() [5/6]

◆ operator=() [6/6]

◆ reinit() [1/4]

◆ reinit() [2/4]

◆ reinit() [3/4]

◆ compress()

◆ update_ghost_values()

◆ zero_out_ghosts()

◆ has_ghost_elements()

◆ add() [1/5]

◆ sadd() [1/3]

◆ equ() [1/2]

◆ sadd() [2/3]

◆ all_zero()

◆ mean_value()

◆ lp_norm()

◆ swap()

◆ reinit() [4/4]

◆ operator*=()

◆ operator/=()

◆ operator+=()

◆ operator-=()

◆ import()

◆ operator*()

◆ multivector_inner_product()

◆ multivector_inner_product_with_metric()

◆ mmult()

◆ add() [2/5]

◆ add() [3/5]

◆ add() [4/5]

◆ add() [5/5]

◆ sadd() [3/3]

◆ scale()

◆ equ() [2/2]

◆ l1_norm()

◆ l2_norm()

◆ norm_sqr()

◆ linfty_norm()

◆ add_and_dot()

◆ size()

◆ locally_owned_elements()

◆ print()

◆ memory_consumption()

Member Data Documentation

◆ communication_block_size

template<typename Number>
class LinearAlgebra::distributed::BlockVector< Number >