Subroutine mld_precset

mld_precset(p,what,val,info)

This routine sets the parameters defining the preconditioner. More precisely, the parameter identified by what is assigned the value contained in val.

Arguments

p	type(mld_xprec_type), intent(inout).
	The preconditioner data structure. Note that x must be chosen according to the real/complex, single/double precision version of MLD2P4 under use.
what	integer, intent(in).
	The number identifying the parameter to be set. A mnemonic constant has been associated to each of these numbers, as reported in Tables 2-5.
val	integer or character(len=*) or real(psb_spk_) or real(psb_dpk_), intent(in).
	The value of the parameter to be set. The list of allowed values and the corresponding data types is given in Tables 2-5. When the value is of type character(len=*), it is also treated as case insensitive.
info	integer, intent(out).
	Error code. If no error, 0 is returned. See Section 7 for details.

A variety of (one-level and multi-level) preconditioners can be obtained by a suitable setting of the preconditioner parameters. These parameters can be logically divided into four groups, i.e. parameters defining

1. the type of multi-level preconditioner;
2. the one-level preconditioner used as smoother;
3. the aggregation algorithm;
4. the coarse-space correction at the coarsest level.

A list of the parameters that can be set, along with their allowed and default values, is given in Tables 2-5. For a detailed description of the meaning of the parameters, please refer to Section 4.

Table 2: Parameters defining the type of multi-level preconditioner.

what	DATA TYPE	val	DEFAULT	COMMENTS
mld_ml_type_	character(len=*)	'ADD' 'MULT'	'MULT'	Basic multi-level framework: additive or multiplicative among the levels (always additive inside a level).
mld_smoother_type_	character(len=*)	'DIAG' 'BJAC' 'AS'	'AS'	Basic one-level preconditioner (i.e. smoother): diagonal, block Jacobi, AS.
mld_smoother_pos_	character(len=*)	'PRE' 'POST' 'TWOSIDE'	'POST'	``Position'' of the smoother: pre-smoother, post-smoother, pre- and post-smoother.

Table 3: Parameters defining the one-level preconditioner used as smoother.

what	DATA TYPE	val	DEFAULT	COMMENTS
mld_sub_ovr_	integer	any int. num. $\ge 0$	1	Number of overlap layers.
mld_sub_restr_	character(len=*)	'HALO' 'NONE'	'HALO'	Type of restriction operator: 'HALO' for taking into account the overlap, 'NONE' for neglecting it.
mld_sub_prol_	character(len=*)	'SUM' 'NONE'	'NONE'	Type of prolongation operator: 'SUM' for adding the contributions from the overlap, 'NONE' for neglecting them.
mld_sub_solve_	character(len=*)	'ILU' 'MILU' 'ILUT' 'UMF' 'SLU'	'UMF'	Local solver: ILU($p$), MILU($p$), ILU($p,t$), LU from UMFPACK, LU from SuperLU (plus triangular solve).
mld_sub_fillin_	integer	Any int. num. $\ge 0$	0	Fill-in level $p$ of the incomplete LU factorizations.
mld_sub_iluthrs_	real(kind_parameter)	Any real num. $\ge 0$	0	Drop tolerance $t$ in the ILU($p,t$) factorization.
mld_sub_ren_	character(len=*)	'RENUM_NONE' 'RENUM_GLOBAL'	'RENUM_NONE'	Row and column reordering of the local submatrices: no reordering, reordering according to the global numbering of the rows and columns of the whole matrix.

Table 4: Parameters defining the aggregation algorithm.

what	DATA TYPE	val	DEFAULT	COMMENTS
mld_aggr_alg_	character(len=*)	'DEC'	'DEC'	Aggregation algorithm. Currently, only the decoupled aggregation is available.
mld_aggr_kind_	character(len=*)	'SMOOTH' 'RAW'	'SMOOTH'	Type of aggregation: smoothed, raw (i.e. using the tentative prolongator).
mld_aggr_thresh_	real(kind_parameter)	Any real num. $\in [0, 1]$	0	Threshold $\theta$ in the aggregation algorithm.
mld_aggr_eig_	character(len=*)	'A_NORMI'	'A_NORMI'	Estimate of the eigenvalue $D^{-1}A$ with largest modulus, to build the damping parameter $\omega$ in the smoothed aggregation. Currently, only the infinity norm of the matrix is available.
mld_aggr_damp_	real(kind_parameter)	Any real num.	$4/(3\vert\vert D^{-1}A\vert\vert _\infty)$	Damping parameter $\omega$ in the smoothed aggregation algorithm. If the user specifies a negative value, then $\omega$ is set to its default value; otherwise, $\omega$ is set to the value provided by the user. In the latter case no estimate of the eigenvalue of $D^{-1}A$ with largest modulus is computed.

Table 5: Parameters defining the coarse-space correction at the coarsest level.

what	DATA TYPE	val	DEFAULT	COMMENTS
mld_coarse_mat_	character(len=*)	'DISTR' 'REPL'	'DISTR'	Coarsest matrix: distributed among the processors or replicated on each of them.
mld_coarse_solve_	character(len=*)	'BJAC' 'UMF' 'SLU' 'SLUDIST'	'BJAC'	Solver used at the coarsest level: block Jacobi, sequential LU from UMFPACK, sequential LU from SuperLU, distributed LU from SuperLU_Dist. 'BJAC' and 'SLUDIST' require the coarsest matrix to be distributed, while 'UMF' and 'SLU' require it to be replicated.
mld_coarse_subsolve_	character(len=*)	'ILU' 'MILU' 'ILUT' 'UMF' 'SLU'	'UMF'	Solver for the diagonal blocks of the coarse matrix, in case the block Jacobi solver is chosen as coarsest-level solver: ILU($p$), MILU($p$), ILU($p,t$), LU from UMFPACK, LU from SuperLU, plus triangular solve.
mld_coarse_sweeps_	integer	Any int. num. $> 0$	4	Number of Block-Jacobi sweeps when 'BJAC' is used as coarsest-level solver.
mld_coarse_fillin_	integer	Any int. num. $\ge 0$	0	Fill-in level $p$ of the incomplete LU factorizations.
mld_coarse_iluthrs_	real(kind_parameter)	Any real. num. $\ge 0$	0	Drop tolerance $t$ in the ILU($p,t$) factorization.