Level 1: Vectors, Matrices and basic operations

Collaboration diagram for Level 1: Vectors, Matrices and basic operations:

Modules
	Basic container independent subroutines
	Useful Typedefs
	Sparse matrix formats
	Dense matrix formats
	Vector view
	MPI backend
	The tag dispatch system

Functions
template<class from_ContainerType , class ContainerType , class ... Params>
void	dg::assign (const from_ContainerType &from, ContainerType &to, Params &&... ps)
	Generic way to assign the contents of a from_ContainerType object to a ContainerType object optionally given additional parameters. More...
template<class ContainerType , class from_ContainerType , class ... Params>
ContainerType	dg::construct (const from_ContainerType &from, Params &&... ps)
	Generic way to construct an object of ContainerType given a from_ContainerType object and optional additional parameters. More...
template<class MatrixType , class ContainerType1 , class ContainerType2 >
void	dg::apply (get_value_type< ContainerType1 > alpha, MatrixType &&M, const ContainerType1 &x, get_value_type< ContainerType1 > beta, ContainerType2 &y)
	\( y = \alpha M(x) + \beta y \); (alias for dg::blas2::symv) More...
template<class MatrixType , class ContainerType1 , class ContainerType2 >
void	dg::apply (MatrixType &&M, const ContainerType1 &x, ContainerType2 &y)
	\( y = M( x)\); (alias for dg::blas2::symv) More...

Detailed Description

Function Documentation

apply() [1/2]

template<class MatrixType , class ContainerType1 , class ContainerType2 >

void dg::apply ( get_value_type< ContainerType1 >  alpha, MatrixType &&  M, const ContainerType1 &  x, get_value_type< ContainerType1 >  beta, ContainerType2 &  y  )

inline

\( y = \alpha M(x) + \beta y \); (alias for dg::blas2::symv)

This Alias exists for code readability: if your matrix is not actually a matrix but a functor then it may seem unnatural to write blas2::symv in your code especially if M is non-linear.

apply() [2/2]

template<class MatrixType , class ContainerType1 , class ContainerType2 >

void dg::apply ( MatrixType &&  M, const ContainerType1 &  x, ContainerType2 &  y  )

inline

\( y = M( x)\); (alias for dg::blas2::symv)

This Alias exists for code readability: if your matrix is not actually a matrix but a functor then it may seem unnatural to write blas2::symv in your code especially if M is non-linear.

assign()

template<class from_ContainerType , class ContainerType , class ... Params>

void dg::assign ( const from_ContainerType &  from, ContainerType &  to, Params &&...  ps  )

inline

Generic way to assign the contents of a from_ContainerType object to a ContainerType object optionally given additional parameters.

The idea of this function is to convert between types with the same data layout but different execution policies (e.g. from a thrust::host_vector to a thrust::device_vector). If the layout differs, additional parameters can be used to achieve what you want.

For example

dg::HVec host( 100, 1.);
dg::DVec device(100);
dg::assign( host, device );
//let us construct a std::vector of 3 dg::DVec from a host vector
std::vector<dg::DVec> device_vec(3);
dg::assign( host, device_vec, 3);

Parameters

from	source vector
to	target vector contains a copy of from on output (memory is automatically resized if necessary)
ps	additional parameters usable for the transfer operation

Note

it is possible to assign a from_ContainerType to a std::array<ContainerType, N> (all elements are initialized with from_ContainerType) and also a std::vector<ContainerType> ( the desired size of the std::vector must be provided as an additional parameter)

Template Parameters

from_ContainerType	must have the same data policy derived from AnyVectorTag as ContainerType (with the exception of std::array and std::vector) but can have different execution policy
Params	in some cases additional parameters that are necessary to assign objects of Type ContainerType
ContainerType	Any class for which a specialization of TensorTraits exists and which fulfills the requirements of the there defined data and execution policies derived from AnyVectorTag and AnyPolicyTag. Among others dg::HVec (serial), dg::DVec (cuda / omp), dg::MHVec (mpi + serial) or dg::MDVec (mpi + cuda / omp) std::vector<dg::DVec> (vector of shared device vectors), std::array<double, 4> (array of 4 doubles) or std::map < std::string, dg::DVec> ( a map of named vectors) double (scalar) and other primitive types ... If there are several ContainerTypes in the argument list, then TensorTraits must exist for all of them

See also

See The dg dispatch system for a detailed explanation of our type dispatch system

construct()

template<class ContainerType , class from_ContainerType , class ... Params>

ContainerType dg::construct ( const from_ContainerType &  from, Params &&...  ps  )

inline

Generic way to construct an object of ContainerType given a from_ContainerType object and optional additional parameters.

The idea of this function is to convert between types with the same data layout but different execution policies (e.g. from a thrust::host_vector to a thrust::device_vector) If the layout differs, additional parameters can be used to achieve what you want.

For example

dg::HVec host( 100, 1.);
dg::DVec device = dg::construct<dg::DVec>( host );
std::array<dg::DVec, 3> device_arr = dg::construct<std::array<dg::DVec, 3>>( host );
//let us construct a std::vector of 3 dg::DVec from a host vector
std::vector<dg::DVec> device_vec = dg::construct<std::vector<dg::DVec>>( host, 3);

Parameters

from	source vector
ps	additional parameters necessary to construct a ContainerType object

Returns

from converted to the new format (memory is allocated accordingly)

Note

it is possible to construct a std::array<ContainerType, N> (all elements are initialized with from_ContainerType) and also a std::vector<ContainerType> ( the desired size of the std::vector must be provided as an additional parameter) given a from_ContainerType

Template Parameters

from_ContainerType	must have the same data policy derived from AnyVectorTag as ContainerType (with the exception of std::array and std::vector) but can have different execution policy
Params	in some cases additional parameters that are necessary to construct objects of Type ContainerType
ContainerType	Any class for which a specialization of TensorTraits exists and which fulfills the requirements of the there defined data and execution policies derived from AnyVectorTag and AnyPolicyTag. Among others dg::HVec (serial), dg::DVec (cuda / omp), dg::MHVec (mpi + serial) or dg::MDVec (mpi + cuda / omp) std::vector<dg::DVec> (vector of shared device vectors), std::array<double, 4> (array of 4 doubles) or std::map < std::string, dg::DVec> ( a map of named vectors) double (scalar) and other primitive types ... If there are several ContainerTypes in the argument list, then TensorTraits must exist for all of them

See also

See The dg dispatch system for a detailed explanation of our type dispatch system