integer, parameter	stack_max =64

integer	stack_pos =0

logical, dimension(stack_max)	firstcall

double precision function	stopc (x, b, r, ipar, dpar)

subroutine	pcond_dummy (u, v, ipar)

subroutine	pcond_dummy_cmplx (u, v, ipar)

recursive subroutine	itersolver (A, x, b, Solver, ndim, DotF, NormF, MatvecF, PrecF, StopcF)

Member Function/Subroutine Documentation

recursive subroutine itersolve::itersolver	(	type(matrix_t), target	A,
		real(kind=dp), dimension(:)	x,
		real(kind=dp), dimension(:)	b,
		type(solver_t)	Solver,
		integer, optional	ndim,
		integer(kind=addrint), optional	DotF,
		integer(kind=addrint), optional	NormF,
		integer(kind=addrint), optional	MatvecF,
		integer(kind=addrint), optional	PrecF,
		integer(kind=addrint), optional	StopcF
	)

The routine that decides which linear system solver to call, and calls it. There are two main sources of iterations within Elmer. 1) The old HUTiter C++ library that includes the most classic iterative Krylov methods. 2) The internal MODULE IterativeMethods that includes some classic iterative methods and also some more recent Krylov methods.

References generalutils::allocatematrix(), crsmatrix::crs_blockdiagonal(), crsmatrix::crs_complexdiagprecondition(), crsmatrix::crs_complexilut(), crsmatrix::crs_complexincompletelu(), crsmatrix::crs_complexluprecondition(), crsmatrix::crs_complexmatrixvectorprod(), crsmatrix::crs_diagprecondition(), crsmatrix::crs_ilut(), crsmatrix::crs_incompletelu(), crsmatrix::crs_luprecondition(), crsmatrix::crs_matrixvectorprod(), messages::error(), messages::fatal(), messages::info(), iterativemethods::itermethod_bicgstabl(), iterativemethods::itermethod_gcr(), iterativemethods::itermethod_jacobi(), iterativemethods::itermethod_richardson(), iterativemethods::itermethod_sgs(), iterativemethods::itermethod_z_bicgstabl(), iterativemethods::itermethod_z_gcr(), listmatrix::list_addtomatrixelement(), listmatrix::list_tocrsmatrix(), lists::listgetconstreal(), lists::listgetcreal(), lists::listgetinteger(), lists::listgetlogical(), lists::listgetstring(), multigridprec(), pcond_dummy(), pcond_dummy_cmplx(), solver(), stopc(), vankaprec(), and messages::warn().

Referenced by multigrid::amgsolve(), eigensolve::arpackeigensolve(), eigensolve::arpackeigensolvecomplex(), eigensolve::arpackstabeigensolve(), blocksolve::blockkryloviter(), blocksolve::blockmatrixprec(), multigrid::cmgsolve(), fetisolve::feti(), gebhardtfactors(), modeldescription::getnodalelementsize(), multigrid::gmgsolve(), solverutils::mortarrobinsolver(), multigrid::pmgsolve(), freesurface::poissonsolve(), radiationfactors(), sparitersolve::solve(), and solverutils::solvelinearsystem().

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subroutine itersolve::pcond_dummy	(	real(kind=dp), dimension(huti_ndim)	u,
		real(kind=dp), dimension(huti_ndim)	v,
		integer, dimension(*)	ipar
	)

Dummy preconditioner, if linear system scaling is active this corresponds to diagonal preconditioning.

Referenced by itersolver().

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subroutine itersolve::pcond_dummy_cmplx	(	complex(kind=dp), dimension(huti_ndim)	u,
		complex(kind=dp), dimension(huti_ndim)	v,
		integer, dimension(*)	ipar
	)

Complex dummy preconditioner, if linear system scaling is active this corresponds to diagonal preconditioning.

Referenced by itersolver().

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double precision function itersolve::stopc	(	double precision, dimension(*)	x,
		double precision, dimension(*)	b,
		double precision, dimension(*)	r,
		integer, dimension(*)	ipar,
		double precision, dimension(*)	dpar
	)

We don't use the backward error estimate e = ||Ax-b||/(||A|| ||x|| + ||b||) as stopping criteriation.

References crsmatrix::crs_matrixvectormultiply().

Referenced by itersolver().

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Member Data Documentation

logical, dimension(stack_max) itersolve::firstcall

integer, parameter itersolve::stack_max =64

integer itersolve::stack_pos =0

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

IterSolve.src