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 coarsest-level correction.

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 4.1.

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=*)	'JACOBI' 'BJAC' 'AS'	'AS'	Basic one-level preconditioner (i.e. smoother): point-Jacobi, block-Jacobi, AS.
mld_smoother_pos_	character(len=*)	'PRE' 'POST' 'TWOSIDE'	'TWOSIDE'	``Position'' of the smoother in the multilevel framework: pre-smoother, post-smoother, pre- and post-smoother. Ignored if mld_ml_type_ is set to 'ADD'.
mld_smoother_sweeps_	integer	Any int. num. $> 0$	1	Number of sweeps of the (pre-/post) smoother. When mld_ml_type_ is set to 'MULT', it sets the default value for both mld_ smoother_sweeps_pre_ and mld_smoother_sweeps_post_.
mld_smoother_sweeps_pre_	integer	Any int. num. $> 0$	1	Number of sweeps of the pre-smoother. Used if mld_ml_type_ is set to 'MULT' and mld_smoother_pos_ is 'PRE' or 'TWOSIDE'.
mld_smoother_sweeps_post_	integer	Any int. num. $> 0$	1	Number of sweeps of the post-smoother. Used if mld_ml_type_ is set to 'MULT' and mld_smoother_pos_ is 'POST' or 'TWOSIDE'.

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=*)	'DSCALE' 'ILU' 'MILU' 'ILUT' 'UMF' 'SLU'	'ILU'	Local solver for block-Jacobi and AS smoothers: diagonal scale (point Jacobi), 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=*)	'SMOOTHED' 'NONSMOOTHED'	'SMOOTHED'	Type of aggregation: smoothed, nonsmoothed (i.e. using the tentative prolongator).
mld_aggr_thresh_	real(kind_parameter)	Any real num. $\in [0, 1]$	$0.08/2^{(l-1)}$	Threshold $\theta$ in the aggregation algorithm. Note that the default threshold varies at each level $l$, where $l=1$ corresponds to the fine level (see [28]). Conversely a value of theta chosen by the user is set to the same value at all levels.
mld_aggr_omega_alg_	character(len=*)	'EIG_EST' 'USER_CHOICE'	'EIG_EST'	How the damping parameter $\omega$ in the smoothed aggregation should be computed: either via an estimate of the spectral radius of $D^{-1}A$, or explicily specified by the user.
mld_aggr_eig_	character(len=*)	'A_NORMI'	'A_NORMI'	How to estimate the spectral radius of $D^{-1}A$. Currently only the infinity norm estimate is available.
mld_aggr_omega_val_	real(kind_parameter)	Any nonnegative real num.	$4/(3\rho(D^{-1}A))$	Damping parameter $\omega$ in the smoothed aggregation algorithm. It must be set by the user if USER_CHOICE was specified for mld_aggr_omega_alg_, otherwise it is computed by the library, using the selected estimate of the spectral radius $\rho(D^{-1}A)$ of $D^{-1}A$.

Table 5: Parameters defining the coarsest-level correction.

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=*)	'JACOBI' 'BJAC' 'UMF' 'SLU' 'ILU' 'MILU' 'ILUT' 'SLUDIST'	'BJAC'	Solver used at the coarsest level: point-Jacobi, block-Jacobi, sequential incomplete LU (three variants), sequential LU from UMFPACK, sequential LU from SuperLU, distributed LU from SuperLU_Dist. 'JACOBI', 'BJAC' and'SLUDIST' requires the coarsest matrix to be distributed, while the others require it to be replicated.
mld_coarse_subsolve_	character(len=*)	'ILU' 'MILU' 'ILUT' 'UMF' 'SLU'	See note	Solver for the diagonal blocks of the coarse matrix, in case the point-Jacobi or 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 point-Jacobi or block-Jacobi sweeps of the 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.
Note: defaults for mld_coarse_subsolve_ are chosen as
- single precision version: 'SLU' if installed, 'ILU' otherwise,
- double precision version: 'UMF' if installed, else 'SLU' if installed, 'ILU' otherwise.