gko::experimental::reorder::ScaledReordered< ValueType, IndexType > Class Template Reference

Provides an interface to wrap reorderings like Rcm and diagonal scaling like equilibration around a LinOp like e.g. More...

#include <ginkgo/core/reorder/scaled_reordered.hpp>

Inheritance diagram for gko::experimental::reorder::ScaledReordered< ValueType, IndexType >:

Collaboration diagram for gko::experimental::reorder::ScaledReordered< ValueType, IndexType >:

Classes
struct	parameters_type
class	Factory

Public Types
using	value_type = ValueType
using	index_type = IndexType
using	ReorderingBaseFactory
Public Types inherited from gko::EnablePolymorphicAssignment< ScaledReordered< default_precision, int32 > >
using	result_type

Public Member Functions
std::shared_ptr< const LinOp >	get_system_matrix () const
std::shared_ptr< const LinOp >	get_inner_operator () const
const parameters_type &	get_parameters () const
Public Member Functions inherited from gko::EnableLinOp< ScaledReordered< default_precision, int32 > >
const ScaledReordered< default_precision, int32 > *	apply (ptr_param< const LinOp > b, ptr_param< LinOp > x) const
Public Member Functions inherited from gko::EnablePolymorphicAssignment< ScaledReordered< default_precision, int32 > >
void	convert_to (result_type *result) const override
void	move_to (result_type *result) override

Static Public Member Functions
static auto	build () -> decltype(Factory::create())

Friends
class	EnableLinOp< ScaledReordered, LinOp >
class	EnablePolymorphicObject< ScaledReordered, LinOp >

Detailed Description

template<typename ValueType = default_precision, typename IndexType = int32>
class gko::experimental::reorder::ScaledReordered< ValueType, IndexType >

Provides an interface to wrap reorderings like Rcm and diagonal scaling like equilibration around a LinOp like e.g.

a sparse direct solver.

Reorderings can be useful for reducing fill-in in the numerical factorization phase of direct solvers, diagonal scaling can help improve the numerical stability by reducing the condition number of the system matrix.

With a permutation matrix P, a row scaling R and a column scaling C, the inner operator is applied to the system matrix P*R*A*C*P^T instead of A. Instead of A*x = b, the inner operator attempts to solve the equivalent linear system P*R*A*C*P^T*y = P*R*b and retrieves the solution x = C*P^T*y. Note: The inner system matrix is computed from a clone of A, so the original system matrix is not changed.

Template Parameters

ValueType	Type of the values of all matrices used in this class
IndexType	Type of the indices of all matrices used in this class

Member Typedef Documentation

ReorderingBaseFactory

template<typename ValueType = default_precision, typename IndexType = int32>

using gko::experimental::reorder::ScaledReordered< ValueType, IndexType >::ReorderingBaseFactory

Initial value:

 
        AbstractFactory<gko::reorder::ReorderingBase<IndexType>,
                        gko::reorder::ReorderingBaseArgs>

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

• ginkgo/core/reorder/scaled_reordered.hpp