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mld2p4:
docs/pdf/Makefile docs/pdf/abstract.tex docs/pdf/background.tex docs/pdf/bibliography.tex docs/pdf/building.tex docs/pdf/conventions.tex docs/pdf/distribution.tex docs/pdf/errors.tex docs/pdf/gettingstarted.tex docs/pdf/license.tex docs/pdf/overview.tex docs/pdf/userguide.tex docs/pdf/userinterface.tex mlprec/mld_cprecinit.f90 mlprec/mld_cprecset.f90 mlprec/mld_dprecinit.f90 mlprec/mld_dprecset.f90 mlprec/mld_sprecinit.f90 mlprec/mld_sprecset.f90 mlprec/mld_zprecinit.f90 mlprec/mld_zprecset.f90 Latest documentation. Fixed inconsistent initialization in precinit. Fixed tipographical conventions in precset.
This commit is contained in:
Salvatore Filippone
+3
-2
@@ -85,8 +85,9 @@
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TOPFILE = userguide.tex
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SECFILE = title.tex abstract.tex overview.tex conventions.tex distribution.tex \
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building.tex gettingstarted.tex advanced.tex errors.tex \
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listofroutines.tex bibliography.tex userinterface.tex background.tex
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building.tex background.tex gettingstarted.tex userinterface.tex \
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errors.tex bibliography.tex license.tex
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# advanced.tex listofroutines.tex
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FIGDIR = figures
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XPDFFLAGS =
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@@ -5,7 +5,7 @@ It implements various versions of one-level additive and of multi-level additive
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and hybrid Schwarz algorithms. In the multi-level case, a purely algebraic approach
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is applied to generate coarse-level corrections, so that no geometric background is needed
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concerning the matrix to be preconditioned. The matrix is required to be square, real
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or complex, with a symmetric sparsity pattern
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or complex, with a symmetric sparsity pattern.
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MLD2P4 has been designed to provide scalable and easy-to-use preconditioners in the
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context of the PSBLAS (Parallel Sparse Basic Linear Algebra Subprograms)
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@@ -14,12 +14,9 @@ available in this framework. MLD2P4 enables the user to easily specify different
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of a generic algebraic multilevel Schwarz preconditioner, thus allowing to search
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for the ``best'' preconditioner for the problem at hand. The package has been designed
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employing object-oriented techniques, using Fortran 95 and MPI, with interfaces to
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additional external libraries such as UMFPACK, SuperLU and SuperLU\_Dist, that
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additional third party libraries such as UMFPACK, SuperLU and SuperLU\_Dist, that
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can be exploited in building multi-level preconditioners.
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The software is freely distributable, under the terms of the license
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in Appendix~\ref{sec:distribution}.
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This guide provides a brief description of the functionalities and
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the user interface of MLD2P4.
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\end{abstract}
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+57
-48
@@ -1,6 +1,6 @@
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\section{Multi-level Domain Decomposition Background\label{sec:background}}
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\markboth{\underline{MLD2P4 User's and Reference Guide}}
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{\underline{\ref{sec:background} Background}}
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\markboth{\textsc{MLD2P4 User's and Reference Guide}}
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{\textsc{\ref{sec:background} Multi-level Domain Decomposition Background}}
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\emph{Domain Decomposition} (DD) preconditioners, coupled with Krylov iterative
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solvers, are widely used in the parallel solution of large and sparse linear systems.
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@@ -17,7 +17,7 @@ solution of the original problem from the local solutions
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\emph{Additive Schwarz} preconditioners are DD preconditioners using overlapping
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submatrices, i.e.\ with some common rows, to couple the local information
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related to the submatrices (see, e.g., \cite{dd2_96}).
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The main motivations for choosing Additive Schwarz preconditioners are their
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The main motivation for choosing Additive Schwarz preconditioners is their
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intrinsic parallelism. A drawback of these
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preconditioners is that the number of iterations of the preconditioned solvers
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generally grows with the number of submatrices. This may be a serious limitation
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@@ -29,16 +29,16 @@ in a coarse space, which globally couples the information related to the single
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submatrices.
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\emph{Two-level Schwarz} preconditioners are obtained
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by combining basic (one-level) Schwarz preconditioners with coarse-level
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corrections. In this context, the one-level preconditioner is often
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called smoother. Different two-level preconditioners are obtained by varying the
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choice of the smoother, of the coarse-level correction and the
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by combining basic (one-level) Schwarz preconditioners with a coarse-level
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correction. In this context, the one-level preconditioner is often
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called `smoother'. Different two-level preconditioners are obtained by varying the
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choice of the smoother and of the coarse-level correction, and the
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way they are combined \cite{dd2_96}. The same reasoning can be applied starting
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from the coarse-level system, i.e.\ a coarse-space correction can be built
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from this system, thus obtaining \emph{multi-level} preconditioners.
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It is worth noting that optimal preconditioners do not necessarily correspond
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to minimum execution times. Indeed, to obtain effective multilevel preconditioners
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to minimum execution times. Indeed, to obtain effective multi-level preconditioners
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a tradeoff between optimality of convergence and the cost of building and applying
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the coarse-space corrections must be achieved. The choice of the number of levels,
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i.e.\ of the coarse-space corrections, also affects the effectiveness of the
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@@ -74,7 +74,7 @@ we first provide a sketch of the AS preconditioners.
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Given the linear system \Ref{system1},
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where $A=(a_{ij}) \in \Re^{n \times n}$ is a
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nonsingular sparse matrix with a symmetric non-zero pattern,
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nonsingular sparse matrix with a symmetric nonzero pattern,
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let $G=(W,E)$ be the adjacency graph of $A$, where $W=\{1, 2, \ldots, n\}$
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and $E=\{(i,j) : a_{ij} \neq 0\}$ are the vertex set and the edge set of $G$,
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respectively. Two vertices are called adjacent if there is an edge connecting
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@@ -84,7 +84,7 @@ Given a 0-overlap (or non-overlapping) partition of $W$,
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i.e.\ a set of $m$ disjoint nonempty sets $W_i^0 \subset W$ such that
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$\cup_{i=1}^m W_i^0 = W$, a $\delta$-overlap
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partition of $W$ is obtained by considering the sets
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$W_i^\delta \supset W_i^{\delta-1}$, obtained by including the vertices that
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$W_i^\delta \supset W_i^{\delta-1}$ obtained by including the vertices that
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are adjacent to any vertex in $W_i^{\delta-1}$.
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Let $n_i^\delta$ be the size of $W_i^\delta$ and $R_i^{\delta} \in
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@@ -107,12 +107,16 @@ to a vector $v \in \Re^n$ within a Krylov solver requires the following
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three steps:
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\begin{enumerate}
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\item restriction of $v$ as $v_i = R_i^{\delta} v$, $i=1,\ldots,m$;
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\item (approximate) solution of the linear systems $A_i^\delta w_i = v_i$,
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\item solution of the linear systems $A_i^\delta w_i = v_i$,
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$i=1,\ldots,m$;
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\item prolongation and sum of the $w_i$'s, i.e. $w = \sum_{i=1}^m (R_i^{\delta})^T w_i$.
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\end{enumerate}
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Note that the linear systems at step 2 are usually solved approximately,
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e.g.\ using incomplete LU factorizations such as ILU($p$), MILU($p$) and
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ILU($p,t$) \cite[Chapter 10]{Saad_book}.
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A variant of the classical AS preconditioner that outperforms it
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in terms of both convergence rate and of computation and communication
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in terms of convergence rate and of computation and communication
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time on parallel distributed-memory computers is the so-called \emph{Restricted AS
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(RAS)} preconditioner~\cite{CAI_SARKIS,EFSTATHIOU}. It
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is obtained by zeroing the components of $w_i$ corresponding to the
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@@ -207,16 +211,21 @@ On the other hand, the use of few processors often leads to local sumatrices tha
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are too expensive to be processed on single processors, because of memory and/or
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computing requirements. Therefore, it seems natural to use a recursive approach,
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in which the coarse-level correction is re-applied starting from the current
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coarse-level system. The corresponding preconditioners are called \emph{multi-level}.
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One more reason for the multi-level approach is that it may significantly
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reduce the computational cost of preconditioning with respect to the two-level case
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(see \cite[Chapter 3]{dd2_96}). Additive and hybrid multilevel preconditioners
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are obtained as direct extensions of the two-level counterparts.
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The algorithm for applying a multi-level version of the two-level hybrid
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post-smoothed preconditioner is reported in Figure~\ref{fig:mlhpost_alg}.
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Other combinations of the smoothers and coarse-level corrections are possible, leading to variants
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of the previous algorithms. For a detailed descrition of them, the reader is
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coarse-level system. The corresponding preconditioners, called \emph{multi-level}
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preconditioners, can significantly reduce the computational cost of preconditioning
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with respect to the two-level case (see \cite[Chapter 3]{dd2_96}).
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Additive and hybrid multilevel preconditioners
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are obtained as direct extensions of the two-level counterparts.
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For a detailed descrition of them, the reader is
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referred to \cite[Chapter 3]{dd2_96}.
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The algorithm for the application of a multi-level hybrid
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post-smoothed preconditioner $M$ to a vector $v$, i.e.\ for the
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computation of $w=M^{-1}v$ is reported, for
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example, in Figure~\ref{fig:mlhpost_alg}. Here the number of levels
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is denoted by $nlev$ and the levels are numbered in increasing order starting
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from the finest one, i.e.\ the finest level is level 1; the coarse matrix
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and the corresponding basic preconditioner at each level $l$ are denoted by $A_l$ and
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$M_l$, respectively, with $A_1=A$.
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%
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\begin{figure}[t]
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\begin{center}
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@@ -224,40 +233,41 @@ referred to \cite[Chapter 3]{dd2_96}.
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\begin{minipage}{.85\textwidth} {\small
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\begin{tabbing}
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\quad \=\quad \=\quad \=\quad \\[-1mm]
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! assigned the finest matrix\\
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$A_1 \leftarrow A$;\\[1mm]
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! defined the number of levels $nlev$ \\[1mm]
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! defined $nlev-1$ prolongators\\
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$R_l^T, l=2, \ldots, nlev$;\\[1mm]
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! defined $nlev-1$ coarser matrices\\
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$A_l \leftarrow R_lA_{l-1}R_l^T, \; l=2, \ldots, nlev$;\\[1mm]
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! defined the $nlev-1$ basic Schwarz preconditioners\\
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$M_l$, basic preconditioner for $A_l \; l=1, \ldots, nlev-1$;\\[1mm]
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! assigned a vector $v$\\
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$v_1 \leftarrow v$; \\[2mm]
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%
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%! assign the finest matrix\\
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%$A_1 \leftarrow A$;\\[1mm]
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%! define the number of levels $nlev$ \\[1mm]
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%! define $nlev-1$ prolongators\\
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%$R_l^T, l=2, \ldots, nlev$;\\[1mm]
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%! define $nlev-1$ coarser matrices\\
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%$A_l \leftarrow R_lA_{l-1}R_l^T, \; l=2, \ldots, nlev$;\\[1mm]
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%! define the $nlev-1$ basic Schwarz preconditioners\\
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%$M_l$, basic preconditioner for $A_l \; l=1, \ldots, nlev-1$;\\[1mm]
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%$! assign a vector $v$\\
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%
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$v_1 = v$; \\[2mm]
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\textbf{for $l=2, nlev$ do}\\[1mm]
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\> ! transfer $v_{l-1}$ to the next coarser level\\
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\> $v_l \leftarrow R_lv_{l-1}$; \\[1mm]
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\> $v_l = R_lv_{l-1}$ \\[1mm]
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\textbf{endfor} \\[2mm]
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! apply the coarsest-level correction\\[1mm]
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$y_{nlev} \leftarrow A_{nlev}^{-1}*v_{nlev}$;\\[2mm]
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$y_{nlev} = A_{nlev}^{-1} v_{nlev}$\\[2mm]
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\textbf{for $l=nlev -1 , 1, -1$ do}\\[1mm]
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\> ! transfer $y_{l+1}$ to the next finer level\\
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\> $y_l \leftarrow R_{l+1}^T*y_{l+1}$;\\[1mm]
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\> $y_l = R_{l+1}^T y_{l+1}$;\\[1mm]
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\> ! compute the residual at the current level\\
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\> $r_l \leftarrow v_l-A_l^{-1}*y_l$;\\[1mm]
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\> ! apply the basic Schwarz preconditioner to $r_l$\\
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\> $r_l \leftarrow M_l^{-1}*r_l$\\[1mm]
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\> $r_l = v_l-A_l^{-1} y_l$;\\[1mm]
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\> ! apply the basic Schwarz preconditioner to the residual\\
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\> $r_l = M_l^{-1} r_l$\\[1mm]
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\> ! update $y_l$\\
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\> $y_l \leftarrow y_l+r_l$\\
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\> $y_l = y_l+r_l$\\
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\textbf{endfor} \\[1mm]
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! preconditioned vector
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$w \leftarrow y_1$;
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$w = y_1$;
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\end{tabbing}
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}
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\end{minipage}
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}
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\caption{Multi-level hybrid post-smoothed preconditioner.\label{fig:mlhpost_alg}}
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\caption{Application of the multi-level hybrid post-smoothed preconditioner.\label{fig:mlhpost_alg}}
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\end{center}
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\end{figure}
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%
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@@ -265,7 +275,7 @@ $w \leftarrow y_1$;
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\subsection{Smoothed Aggregation\label{sec:aggregation}}
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To define the restriction operator $R_C$, which is used to compute
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In order to define the restriction operator $R_C$, which is used to compute
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the coarse-level matrix $A_C$, MLD2P4 uses the \emph{smoothed aggregation}
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algorithm described in \cite{BREZINA_VANEK,VANEK_MANDEL_BREZINA}.
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The basic idea of this algorithm is to build a coarse set of vertices
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@@ -283,16 +293,15 @@ Three main steps can be identified in the smoothed aggregation procedure:
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%\textbf{NOTA: Controllare cosa fa trilinos dopo il primo passo.}
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To perform the coarsening step, we have implemented the aggregation algorithm sketched
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in \cite{apnum_07}. According to \cite{BREZINA_VANEK}, a modification of this algorithm
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has been actually considered,
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in \cite{apnum_07}. According to \cite{VANEK_MANDEL_BREZINA}, a modification of
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this algorithm has been actually considered,
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in which each aggregate $N_r$ is made of vertices of $W$ that are \emph{strongly coupled}
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to a certain root vertex $r \in W$, i.e.\
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\[ N_r = \left\{s \in W: |a_{rs}| > \theta \sqrt{|a_{rr}a_{ss}|} \right\}
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\cup \left\{ r \right\} ,
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\]
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for a given $\theta \in [0,1]$. \textbf{L'ALGORITMO USA IL MAGGIORE STRETTO? ALTRIMENTI
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CON THETA=0 AGGREGHIAMO ANCHE I VERTICI CON COEFFICIENTE CORRISPONDENTE NULLO}
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Since the previous algorithm has a sequential nature, a \emph{decoupled} version of
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for a given $\theta \in [0,1]$.
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Since this algorithm has a sequential nature, a \emph{decoupled} version of
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it has been chosen, where each processor $i$ independently applies the algorithm to
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the set of vertices $W_i^0$ assigned to it in the initial data distribution. This
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version is embarrassingly parallel, since it does not require any data communication.
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@@ -1,7 +1,8 @@
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\section{Bibliography\label{sec:bib}}
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\markboth{\underline{MLD2P4 User's and Reference Guide}}
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{\underline{\ref{sec:bib} Bibliography}}
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\let\refname\relax
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%\section{Bibliography\label{sec:bib}}
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\markboth{\textsc{MLD2P4 User's and Reference Guide}}
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{\textsc{References}}
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%\let\refname\relax
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\begin{thebibliography}{99}
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%
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@@ -146,6 +147,11 @@ ACM Transactions on Mathematical Software, 29, 2, 2003, 110--140.
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%{\em Fortran 95/2003 explained.}
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%{Oxford University Press}, 2004.
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%
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\bibitem{Saad_book}
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Y.~Saad,
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\emph{Iterative methods for sparse linear systems}, 2nd edition,
|
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SIAM, 2003
|
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|
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\bibitem{dd2_96}
|
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B.~Smith, P.~Bjorstad, W.~Gropp,
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{\em Domain Decomposition: Parallel Multilevel Methods for Elliptic
|
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|
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+12
-8
@@ -1,9 +1,13 @@
|
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\section{Configuring and Building MLD2P4\label{sec:configuring}}
|
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\markboth{\underline{MLD2P4 User's and Reference Guide}}
|
||||
{\underline{\ref{sec:configuring} Configuring and Building}}
|
||||
- uso di GNU autoconf e automake \\
|
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- software di base necessario (MPI, BLACS, BLAS, PSBLAS, UMFPACK ? - specificare versioni)\\
|
||||
- software opzionale (SuperLU, SuperLUdist - specificare versioni e opzioni di configure)\\
|
||||
- sistemi operativi e compilatori su cui MLD2P4 e' stato costruito con successo \\
|
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\section{Configuring and Building MLD2P4\label{sec:building}}
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:building} Configuring and Building MLD2P4}}
|
||||
- uso di GNU autoconf e automake, con riferimento alla compilazione delle varie versioni
|
||||
(reale/complessa, singola/doppia precisione) \\
|
||||
- software di base (MPI, BLACS, BLAS, PSBLAS - specificare versioni)\\
|
||||
- software `third party" (UMFPACK, SuperLU, SuperLUdist - specificare versioni e opzioni di
|
||||
configure, dire che UMFPACK e SuperLU sono richiesti, rispettivamente, dalle versioni in
|
||||
singola ed in doppia precisione.)\\
|
||||
- sistemi operativi e compilatori su cui MLD2P4 e' stato implementato con successo \\
|
||||
- sono previste opzioni di configurazione per il debugging o per il profiling? \\
|
||||
- albero delle directory generato al momento dell'installazione\\
|
||||
- albero delle directory generato al momento dell'installazione, con brevissima
|
||||
descrizione del contenuto delle directory - aggiungere la directory \texttt{examples}\\
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
\section{Notational Conventions\label{sec:conventions}}
|
||||
\markboth{\underline{MLD2P4 User's and Reference Guide}}
|
||||
{\underline{\ref{sec:conventions} Notational conventions}}
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:conventions} Notational Conventions}}
|
||||
|
||||
- caratteri tipografici usati nella guida (vedi guida ML recente e guida Aztec) \\
|
||||
- convenzioni sui nomi di routine (differenza nei nomi tra high-level e medium-level),
|
||||
strutture dati, moduli, costanti, etc. (vedi guida psblas) \\
|
||||
- convenzioni sui nomi di routine (anche differenza nei nomi tra high-level e
|
||||
medium-level?), strutture dati, moduli, costanti, etc. (vedi guida psblas) \\
|
||||
- versione reale e complessa, singola e doppia precisione\\
|
||||
@@ -1,44 +1,7 @@
|
||||
\section{License\label{sec:distribution}}
|
||||
\markboth{\underline{MLD2P4 User's and Reference Guide}}
|
||||
{\underline{\ref{sec:distribution} License}}
|
||||
\section{Code Distribution\label{sec:distribution}}
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:distribution} Code Distribution}}
|
||||
|
||||
The MLD2P4 is freely distributable under the following copyright
|
||||
terms: {\small
|
||||
\begin{verbatim}
|
||||
MLD2P4 version 1.0
|
||||
MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
based on PSBLAS (Parallel Sparse BLAS version 2.3)
|
||||
|
||||
(C) Copyright 2008
|
||||
|
||||
Salvatore Filippone University of Rome Tor Vergata
|
||||
Alfredo Buttari University of Rome Tor Vergata
|
||||
Pasqua D'Ambra ICAR-CNR, Naples
|
||||
Daniela di Serafino Second University of Naples
|
||||
|
||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions
|
||||
are met:
|
||||
1. Redistributions of source code must retain the above copyright
|
||||
notice, this list of conditions and the following disclaimer.
|
||||
2. Redistributions in binary form must reproduce the above copyright
|
||||
notice, this list of conditions, and the following disclaimer in the
|
||||
documentation and/or other materials provided with the distribution.
|
||||
3. The name of the MLD2P4 group or the names of its contributors may
|
||||
not be used to endorse or promote products derived from this
|
||||
software without specific written permission.
|
||||
|
||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
||||
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
|
||||
TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
||||
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE MLD2P4 GROUP OR ITS CONTRIBUTORS
|
||||
BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
||||
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
||||
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
||||
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
||||
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
||||
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
||||
POSSIBILITY OF SUCH DAMAGE.
|
||||
\end{verbatim}
|
||||
}
|
||||
\noindent
|
||||
- sito web sul quale e' disponibile il software\\
|
||||
- modalita' di uso con cenno alla licenza (i dettagli sulla licenza vanno in appendice)
|
||||
+2
-2
@@ -1,6 +1,6 @@
|
||||
\section{Error Handling}\label{sec:errors}
|
||||
\markboth{\underline{MLD2P4 User's and Reference Guide}}
|
||||
{\underline{\ref{sec:errors} Error handling}}
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:errors} Error handling}}
|
||||
|
||||
Error handling
|
||||
- Breve descrizione con rinvio alla guida di PSBLAS
|
||||
|
||||
+110
-89
@@ -1,6 +1,6 @@
|
||||
\section{Getting Started\label{sec:started}}
|
||||
\markboth{\underline{MLD2P4 User's and Reference Guide}}
|
||||
{\underline{\ref{sec:started} Getting started}}
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:started} Getting Started}}
|
||||
|
||||
We describe the basics for building and applying MLD2P4 one-level and multi-level
|
||||
Schwarz preconditioners with the Krylov solvers included in PSBLAS \cite{PSBLASGUIDE}.
|
||||
@@ -17,15 +17,16 @@ The following steps are required:
|
||||
a preconditioner type chosen by the user}. This is performed by the routine
|
||||
\verb|mld_precinit|, which also sets defaults for each preconditioner
|
||||
type selected by the user. The defaults associated to each preconditioner
|
||||
type are listed in Table~\ref{tab:precinit}, where the strings used by
|
||||
type are given in Table~\ref{tab:precinit}, where the strings used by
|
||||
\verb|mld_precinit| to identify the preconditioner types are also given.
|
||||
Note that these strings are valid also if uppercase letters are substituted by
|
||||
corresponding lowercase ones.
|
||||
\item \emph{Modify the selected preconditioner type, by properly setting
|
||||
preconditioner parameters.} This is performed by the routine \verb|mld_precset|.
|
||||
This routine must be called only if the user wants to modify the default values
|
||||
of the parameters associated to the selected preconditioner type, to obtain a variant
|
||||
of the preconditioner.
|
||||
Examples of use of \verb|mld_precset| is given in Section~\ref{sec:examples};
|
||||
a complete list of all the
|
||||
of the preconditioner. Examples of use of \verb|mld_precset| are given in
|
||||
Section~\ref{sec:examples}; a complete list of all the
|
||||
preconditioner parameters and their allowed and default values is provided in
|
||||
Section~\ref{sec:userinterface}, Tables~\ref{tab:p_type}-\ref{tab:p_coarse}.
|
||||
\item \emph{Build the preconditioner for a given matrix.} This is performed by
|
||||
@@ -39,39 +40,43 @@ The following steps are required:
|
||||
be performed when the preconditioner is no more used.
|
||||
\end{enumerate}
|
||||
A detailed description of the above routines is given in Section~\ref{sec:userinterface}.
|
||||
|
||||
Note that the Fortran 95 module \verb|mld_prec_mod| must be used in the program
|
||||
calling the MLD2P4 routines; this requires also the use of the
|
||||
\verb|psb_base_mod| for the sparse matrix and communication descriptor
|
||||
data types, as well as for the kind parameters for vectors, and the
|
||||
use of the module \verb|psb_krylov_mod| for interfacing with the
|
||||
Krylov solvers. Note that the include path for MLD2P4 must override
|
||||
those for the base PSBLAS, e.g. they must come first in the sequence
|
||||
passed to the compiler, as the MLD2P4 version of the Krylov interfaces
|
||||
must override that of PSBLAS. This will change in the future when the
|
||||
support for the \verb|class| statement becomes widespread in Fortran
|
||||
compilers.
|
||||
Examples showing the basic use of MLD2P4 are reported in Section~\ref{sec:examples}.
|
||||
|
||||
\noindent
|
||||
\textbf{Remark.} The coarsest-level solver used by the default two-level
|
||||
Note that the Fortran 95 module \verb|mld_prec_mod|, containing the definition of the
|
||||
preconditioner data type and the interfaces to the routines of MLD2P4,
|
||||
must be used in any program calling such routines.
|
||||
The modules \verb|psb_base_mod|, for the sparse matrix and communication descriptor
|
||||
data types, and \verb|psb_krylov_mod|, for interfacing with the
|
||||
Krylov solvers, must be also used (see Section~\ref{sec:examples}).
|
||||
|
||||
\ \\
|
||||
\textbf{Remark 1.} The coarsest-level solver used by the default two-level
|
||||
preconditioner has been chosen by taking into account that, on parallel
|
||||
machines, it often leads to the smallest execution time when applied to
|
||||
linear systems coming from finite-difference discretizations of basic
|
||||
elliptic PDE problems, considered as standard tests for multi-level Schwarz
|
||||
preconditioners \cite{aaecc_07,apnum_07}. However, this solver does
|
||||
not necessarily to the smallest number of iterations of the
|
||||
not necessarily correspond to the smallest number of iterations of the
|
||||
preconditioned Krylov method, which is usually obtained by applying a
|
||||
direct solver, e.g.\ based on the LU factorization, on a matrix
|
||||
replicated at the coarsest level (see Section~\ref{sec:userinterface}
|
||||
for coarsest-level solvers available in MLD2P4).
|
||||
a direct solver to the coarsest-level system, e.g.\ based on the LU
|
||||
factorization (see Section~\ref{sec:userinterface}
|
||||
for the coarsest-level solvers available in MLD2P4).
|
||||
|
||||
\ \\
|
||||
\textbf{Remark 2.} The include path for MLD2P4 must override
|
||||
those for PSBLAS, e.g.\ the latter must come first in the sequence
|
||||
passed to the compiler, as the MLD2P4 version of the Krylov solver
|
||||
interfaces must override that of PSBLAS. This will change in the future
|
||||
when the support for the \verb|class| statement becomes widespread in Fortran
|
||||
compilers.
|
||||
|
||||
|
||||
\begin{table}[th]
|
||||
{
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{6.7cm}|}
|
||||
%{\small
|
||||
\begin{tabular}{|l|l|p{6.4cm}|}
|
||||
\hline
|
||||
\emph{Type} & \emph{String} & \emph{Default preconditioner} \\ \hline
|
||||
\textsc{type} & \textsc{string} & \textsc{default preconditioner} \\ \hline
|
||||
No preconditioner &\verb|'NOPREC'|& (Considered only to use the PSBLAS
|
||||
Krylov solvers with no preconditioner.) \\
|
||||
Diagonal & \verb|'DIAG'| & --- \\
|
||||
@@ -80,18 +85,23 @@ Additive Schwarz & \verb|'AS'| & Restricted Additive Schwarz (RAS),
|
||||
with overlap 1 and ILU(0) on the local blocks. \\
|
||||
Multilevel &\verb|'ML'| & Multi-level hybrid preconditioner (additive on the
|
||||
same level and multiplicative through the levels),
|
||||
with post-smoothing only. Number of levels: 2;
|
||||
post-smoother: RAS with overlap 1 and with ILU(0)
|
||||
on the local blocks; coarsest matrix: distributed
|
||||
among the processors; (approximate) coarse-level
|
||||
solver: 4 sweeps of the block-Jacobi solver,
|
||||
with the UMFPACK LU factorization
|
||||
on the blocks (double precision versions) or
|
||||
\textbf{XXXXXXXXX} (single precision versions)\\
|
||||
with post-smoothing only.
|
||||
Number of levels: 2.
|
||||
Post-smoother: RAS with overlap 1 and ILU(0)
|
||||
on the local blocks.
|
||||
Aggregation: smoothed aggregation with
|
||||
threshold $\theta = 0$.
|
||||
Coarsest matrix: distributed among the processors.
|
||||
Coarse-level solver:
|
||||
4 sweeps of the block-Jacobi solver,
|
||||
with LU factorization of the blocks
|
||||
(UMFPACK for the double precision versions and
|
||||
SuperLU for the single precision ones) \\
|
||||
\hline
|
||||
\end{tabular}
|
||||
%}
|
||||
\end{center}
|
||||
}
|
||||
|
||||
\caption{Preconditioner types, corresponding strings and default choices.
|
||||
\label{tab:precinit}}
|
||||
\end{table}
|
||||
@@ -103,31 +113,32 @@ multi-level preconditioner available in the real double precision version
|
||||
of MLD2P4 (see Table~\ref{tab:precinit}). This preconditioner is chosen
|
||||
by simply specifying \verb|'ML'| as second argument of \verb|mld_precinit|
|
||||
(a call to \verb|mld_precset| is not needed) and is applied with the BiCGSTAB
|
||||
solver provided by PSBLAS. The setup and application of the default multi-level
|
||||
preconditioners for the real single precision and the complex, single and double
|
||||
precision, versions are obtained with straightforward modifications of the example.
|
||||
solver provided by PSBLAS. As previously observed, the modules \verb|psb_base_mod|,
|
||||
\verb|mld_prec_mod| and \verb|psb_krylov_mod| must be used by the example program.
|
||||
|
||||
|
||||
The part of the code concerning the
|
||||
reading and assembling of the sparse matrix and the right-hand side vector, performed
|
||||
through the PSBLAS routines for sparse matrix and vector management, is not reported
|
||||
here for brevity; the statements concerning the deallocation of the PSBLAS data structure
|
||||
are neglected too.
|
||||
The complete code can be found in the example program file \verb|example_ml.f90|
|
||||
in the directory \textbf{XXXXXX (COMPLETARE. DIRE CHE I FILE IN REALTA' SONO DUE, UNO CON
|
||||
LA GENERAZIONE DELLA MATRICE ED UNO CON LA LETTURA).} Note that the modules \verb|psb_base_mod|
|
||||
and \verb|psb_util_mod| at the beginning of the code are required by PSBLAS.
|
||||
\textbf{O psb\_base\_mod} E' RICHIESTO ANCHE DA MLD2P4?)
|
||||
For details on the use of the PSBLAS routines, see the PSBLAS User's Guide \cite{PSBLASGUIDE}.
|
||||
here for brevity; the statements concerning the deallocation of the PSBLAS
|
||||
data structure are neglected too.
|
||||
The complete code can be found in the example program file \verb|mld_dexample_ml.f90|,
|
||||
in the directory \verb|examples/fileread| of the MLD2P4 tree (see
|
||||
Section~\ref{sec:building}).
|
||||
For details on the use of the PSBLAS routines, see the PSBLAS User's
|
||||
Guide \cite{PSBLASGUIDE}.
|
||||
|
||||
\textbf{LE FIGURE SONO DECENTRATE, NONOSTANTE IL CENTER. CI VUOLE UNA MINIPAGE?}
|
||||
The setup and application of the default multi-level
|
||||
preconditioners for the real single precision and the complex, single and double
|
||||
precision, versions are obtained with straightforward modifications of the previous
|
||||
example (see Section~\ref{sec:userinterface} for details). If these versions are installed,
|
||||
the corresponding Fortran 95 codes are available in \verb|examples/fileread/| with these.
|
||||
|
||||
\begin{figure}[tbp]
|
||||
\begin{center}
|
||||
\begin{minipage}{.90\textwidth}
|
||||
{\small
|
||||
\begin{verbatim}
|
||||
use psb_base_mod
|
||||
use psb_util_mod
|
||||
use mld_prec_mod
|
||||
use psb_krylov_mod
|
||||
... ...
|
||||
@@ -138,6 +149,8 @@ For details on the use of the PSBLAS routines, see the PSBLAS User's Guide \cite
|
||||
type(psb_desc_type) :: desc_A
|
||||
! preconditioner
|
||||
type(mld_dprec_type) :: P
|
||||
! right-hand side and solution vectors
|
||||
real(kind(1.d0)) :: b(:), x(:)
|
||||
... ...
|
||||
!
|
||||
! initialize the parallel environment
|
||||
@@ -145,20 +158,18 @@ For details on the use of the PSBLAS routines, see the PSBLAS User's Guide \cite
|
||||
call psb_info(ictxt,iam,np)
|
||||
... ...
|
||||
!
|
||||
! read and assemble the matrix A and the right-hand
|
||||
! side b using PSBLAS routines for sparse matrix /
|
||||
! vector management
|
||||
! read and assemble the matrix A and the right-hand side b
|
||||
! using PSBLAS routines for sparse matrix / vector management
|
||||
... ...
|
||||
!
|
||||
! initialize the default multi-level preconditioner,
|
||||
! i.e. two-level hybrid Schwarz, using RAS (with
|
||||
! overlap 1 and ILU(0) on the blocks) as post-smoother
|
||||
! and 4 block-Jacobi sweeps (with UMFPACK LU on the
|
||||
! blocks) as distributed coarse-level solver
|
||||
! initialize the default multi-level preconditioner, i.e. hybrid
|
||||
! Schwarz, using RAS (with overlap 1 and ILU(0) on the blocks)
|
||||
! as post-smoother and 4 block-Jacobi sweeps (with UMFPACK LU
|
||||
! on the blocks) as distributed coarse-level solver
|
||||
call mld_precinit(P,'ML',info)
|
||||
!
|
||||
! build the preconditioner
|
||||
call psb_precbld(A,P,desc_A,info)
|
||||
call mld_precbld(A,desc_A,P,info)
|
||||
!
|
||||
! set the solver parameters and the initial guess
|
||||
... ...
|
||||
@@ -178,85 +189,94 @@ For details on the use of the PSBLAS routines, see the PSBLAS User's Guide \cite
|
||||
stop
|
||||
\end{verbatim}
|
||||
}
|
||||
\end{minipage}
|
||||
\caption{Setup and application of the default multi-level Schwarz preconditioner.
|
||||
\label{fig:ex_default}}
|
||||
\end{center}
|
||||
\end{figure}
|
||||
|
||||
Different versions of multilevel preconditioner can be obtained by changing
|
||||
Different versions of multi-level preconditioners can be obtained by changing
|
||||
the default values of the preconditioner parameters. The code reported in
|
||||
Figure~\ref{fig:ex_3lh} shows how to set a three-level hybrid Schwarz
|
||||
preconditioner, which uses block Jacobi with ILU(0) on the
|
||||
local blocks as post-smoother, a coarsest matrix replicated on the processors,
|
||||
and the LU factorization from UMFPACK~\cite{UMFPACK}, version 4.4, as coarse-level solver.
|
||||
local blocks as post-smoother, has a coarsest matrix replicated on the processors,
|
||||
and solves the coarsest-level system with the LU factorization from UMFPACK~\cite{UMFPACK}.
|
||||
The number of levels is specified by using \verb|mld_precinit|; the other
|
||||
preconditioner parameters are set by calling \verb|mld_precset|. Note that
|
||||
the type of multilevel framework (i.e.\ multiplicative among the levels
|
||||
with post-smoothing only) is not specified since it is the default
|
||||
set by \verb|mld_precinit|. Figure~\ref{fig:ex_3la} shows how to
|
||||
set by \verb|mld_precinit|.
|
||||
|
||||
Figure~\ref{fig:ex_3la} shows how to
|
||||
set a three-level additive Schwarz preconditioner,
|
||||
which applies RAS, with overlap 1 and ILU(0) on the blocks,
|
||||
as pre- and post-smoother, and five block-Jacobi sweeps, with
|
||||
which uses RAS, with overlap 1 and ILU(0) on the blocks,
|
||||
as pre- and post-smoother, and applies five block-Jacobi sweeps, with
|
||||
the UMFPACK LU factorization on the blocks, as distributed coarsest-level
|
||||
solver. Again, \verb|mld_precset| is used only to set
|
||||
non-default values of the parameters (see Tables~\ref{tab:p_type}-\ref{tab:p_coarse}).
|
||||
In both cases, the construction and the application of the preconditioner
|
||||
are carried out as for the default multi-level preconditioner.
|
||||
The code fragments shown in in Figures~\ref{fig:ex_3lh}-\ref{fig:ex_3la} are
|
||||
included in the example program file \verb|example_ml.f90|.
|
||||
\textbf{LO STESSO PROGRAMMA CONTIENE I TRE ESEMPI, CON UN SWITCH TRA L'UNO E L'ALTRO
|
||||
O FACCIAMO 3 PROGRAMMI DISTINTI? NON RICORDO CHE COSA ABBIAMO DECISO.
|
||||
PASQUA: ABBIAMO DETTO CHE ERA PREFERIBILE UN UNICO PROGRAMMA CON SWITCH.}
|
||||
included in the example program file \verb|mld_dexample_ml.f90| too.
|
||||
|
||||
Finally, Figure~\ref{fig:ex_1l} shows the setup of a one-level
|
||||
additive Schwarz preconditioner, i.e. RAS with overlap 2. The corresponding code,
|
||||
including also the application of the preconditioner is in the example
|
||||
program file \verb|example_1lev.f90|.
|
||||
additive Schwarz preconditioner, i.e.\ RAS with overlap 2. The corresponding
|
||||
example program is available in \verb|mld_dexample_1lev.f90|.
|
||||
|
||||
\begin{figure}[tbp]
|
||||
For all the previous preconditioners, example programs where the sparse matrix and
|
||||
the right-hand side are generated by discretizing a Poisson equation with Dirichlet
|
||||
boundary conditions are also available in the directory \verb|examples/pdegen|.
|
||||
|
||||
|
||||
\begin{figure}[tbh]
|
||||
\begin{center}
|
||||
\begin{minipage}{.90\textwidth}
|
||||
{\small
|
||||
\begin{verbatim}
|
||||
... ...
|
||||
! set a three-level hybrid Schwarz preconditioner,
|
||||
! which uses block Jacobi (with ILU(0) on the blocks)
|
||||
! as post-smoother, a coarsest matrix replicated on the
|
||||
! processors, and the LU factorization from UMFPACK
|
||||
! as coarse-level solver
|
||||
! set a three-level hybrid Schwarz preconditioner, which uses
|
||||
! block Jacobi (with ILU(0) on the blocks) as post-smoother,
|
||||
! a coarsest matrix replicated on the processors, and the
|
||||
! LU factorization from UMFPACK as coarse-level solver
|
||||
call mld_precinit(P,'ML',info,nlev=3)
|
||||
call_mld_precset(P,mld_smoother_type_,'BJAC',info)
|
||||
call mld_precset(P,mld_coarse_mat,'REPL')
|
||||
call mld_precset(P,mld_coarse_solve,'UMF')
|
||||
call mld_precset(P,mld_coarse_mat_,'REPL',info)
|
||||
call mld_precset(P,mld_coarse_solve_,'UMF',info)
|
||||
... ...
|
||||
\end{verbatim}
|
||||
}
|
||||
\end{minipage}
|
||||
|
||||
\caption{Setup of a hybrid three-level Schwarz preconditioner.\label{fig:ex_3lh}}
|
||||
\end{center}
|
||||
\end{figure}
|
||||
|
||||
\begin{figure}[htb]
|
||||
\begin{figure}[tbh]
|
||||
\begin{center}
|
||||
\begin{minipage}{.90\textwidth}
|
||||
{\small
|
||||
\begin{verbatim}
|
||||
... ...
|
||||
! set a three-level additive Schwarz preconditioner,
|
||||
! which uses RAS (with overlap 1 and ILU(0) on the blocks)
|
||||
! as pre- and post-smoother, and 5 block-Jacobi sweeps
|
||||
! (with UMFPACK LU on the blocks) as distributed
|
||||
! coarsest-level solver
|
||||
! set a three-level additive Schwarz preconditioner, which uses
|
||||
! RAS (with overlap 1 and ILU(0) on the blocks) as pre- and
|
||||
! post-smoother, and 5 block-Jacobi sweeps (with UMFPACK LU
|
||||
! on the blocks) as distributed coarsest-level solver
|
||||
call mld_precinit(P,'ML',info,nlev=3)
|
||||
call mld_precset(P,mld_ml_type_,'ADD',info)
|
||||
call_mld_precset(P,mld_smoother_pos_,'TWOSIDE',info)
|
||||
call mld_precset(P,mld_coarse_sweeps_,5)
|
||||
call mld_precset(P,mld_coarse_sweeps_,5,info)
|
||||
... ...
|
||||
\end{verbatim}
|
||||
}
|
||||
\end{minipage}
|
||||
|
||||
\caption{Setup of an additive three-level Schwarz preconditioner.\label{fig:ex_3la}}
|
||||
\end{center}
|
||||
\end{figure}
|
||||
|
||||
\begin{figure}[htb]
|
||||
\begin{figure}[tbh]
|
||||
\begin{center}
|
||||
\begin{minipage}{.90\textwidth}
|
||||
{\small
|
||||
\begin{verbatim}
|
||||
... ...
|
||||
@@ -266,12 +286,13 @@ program file \verb|example_1lev.f90|.
|
||||
... ...
|
||||
\end{verbatim}
|
||||
}
|
||||
\end{minipage}
|
||||
\caption{Setup of a one-level Schwarz preconditioner.\label{fig:ex_1l}}
|
||||
\end{center}
|
||||
\end{figure}
|
||||
|
||||
\ \\
|
||||
\textbf{Remark.} Any PSBLAS-based program using the basic preconditioners
|
||||
\textbf{Remark 3.} Any PSBLAS-based program using the basic preconditioners
|
||||
implemented in PSBLAS 2.0, i.e.\ the diagonal and block-Jacobi ones,
|
||||
can use the diagonal and block-Jacobi preconditioners
|
||||
implemented in MLD2P4 without any change in the code.
|
||||
|
||||
@@ -0,0 +1,44 @@
|
||||
\section{License\label{sec:distribution}}
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:distribution} License}}
|
||||
|
||||
The MLD2P4 is freely distributable under the following copyright
|
||||
terms: {\small
|
||||
\begin{verbatim}
|
||||
MLD2P4 version 1.0
|
||||
MultiLevel Domain Decomposition Parallel Preconditioners Package
|
||||
based on PSBLAS (Parallel Sparse BLAS version 2.3)
|
||||
|
||||
(C) Copyright 2008
|
||||
|
||||
Salvatore Filippone University of Rome Tor Vergata
|
||||
Alfredo Buttari University of Rome Tor Vergata
|
||||
Pasqua D'Ambra ICAR-CNR, Naples
|
||||
Daniela di Serafino Second University of Naples
|
||||
|
||||
|
||||
Redistribution and use in source and binary forms, with or without
|
||||
modification, are permitted provided that the following conditions
|
||||
are met:
|
||||
1. Redistributions of source code must retain the above copyright
|
||||
notice, this list of conditions and the following disclaimer.
|
||||
2. Redistributions in binary form must reproduce the above copyright
|
||||
notice, this list of conditions, and the following disclaimer in the
|
||||
documentation and/or other materials provided with the distribution.
|
||||
3. The name of the MLD2P4 group or the names of its contributors may
|
||||
not be used to endorse or promote products derived from this
|
||||
software without specific written permission.
|
||||
|
||||
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
|
||||
``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED
|
||||
TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
||||
PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE MLD2P4 GROUP OR ITS CONTRIBUTORS
|
||||
BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
||||
CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
||||
SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
||||
INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
||||
CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
||||
ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
||||
POSSIBILITY OF SUCH DAMAGE.
|
||||
\end{verbatim}
|
||||
}
|
||||
@@ -1,8 +1,7 @@
|
||||
\section{General Overview\label{sec:overview}}
|
||||
|
||||
\markboth{\underline{MLD2P4 User's and Reference Guide}}
|
||||
{\underline{\ref{sec:overview} General Overview}}
|
||||
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:overview} General Overview}}
|
||||
|
||||
The \textsc{Multi-Level Domain Decomposition Parallel Preconditioners Package based on
|
||||
PSBLAS (MLD2P4}) provides \emph{multi-level Schwarz preconditioners}~\cite{dd2_96},
|
||||
to be used in the iterative solutions of sparse linear systems:
|
||||
@@ -31,9 +30,9 @@ as algebraic coarsening strategy~\cite{BREZINA_VANEK,VANEK_MANDEL_BREZINA}.
|
||||
The package is written in \emph{Fortran~95}, following an
|
||||
\emph{object-oriented approach} through the exploitation of features
|
||||
such as abstract data type creation, functional
|
||||
overloading and dynamic memory management.% , while providing a smooth
|
||||
overloading and dynamic memory management.
|
||||
% , while providing a smooth
|
||||
% path towards the integration in legacy application codes.
|
||||
% \textbf{NON MI PIACE QUESTO PERIODO, E' TROPPO LUNGO. RIUSCITE A SCRIVERLO MEGLIO?}
|
||||
The parallel implementation is based
|
||||
on a Single Program Multiple Data (SPMD) paradigm for distributed-memory architectures.
|
||||
Single and double precision implementations of MLD2P4 are available for both the
|
||||
@@ -42,7 +41,7 @@ real and the complex case, that can be used through a single interface.
|
||||
|
||||
MLD2P4 has been designed to implement scalable and easy-to-use multilevel preconditioners
|
||||
in the context of the \emph{PSBLAS (Parallel Sparse BLAS)
|
||||
computational framework}~\cite{psblas_00}.
|
||||
computational framework}~\cite{psblas_00}.
|
||||
PSBLAS is a library originally developed to address the parallel implementation of
|
||||
iterative solvers for sparse linear system, by providing basic linear algebra
|
||||
operators and data management facilities for distributed sparse matrices; it
|
||||
@@ -71,7 +70,7 @@ by expert users to build new versions of multi-level Schwarz preconditioners.
|
||||
We provide here a description of the upper-layer routines, but not of the
|
||||
medium-layer ones.
|
||||
|
||||
This guide is organized as follows: \textbf{ORGANIZZAZIONE DELLA GUIDA}
|
||||
This guide is organized as follows. \textbf{ORGANIZZAZIONE DELLA GUIDA}
|
||||
|
||||
%%% Local Variables:
|
||||
%%% mode: latex
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
\documentclass[a4paper]{article}
|
||||
\documentclass[a4paper,twoside,11pt]{article}
|
||||
\usepackage{pstricks}
|
||||
\usepackage{fancybox}
|
||||
\usepackage{amsfonts}
|
||||
@@ -112,6 +112,7 @@
|
||||
|
||||
\include{overview}
|
||||
\include{conventions}
|
||||
\include{distribution}
|
||||
\include{building}
|
||||
\include{background}
|
||||
\include{gettingstarted}
|
||||
@@ -121,12 +122,11 @@
|
||||
%\include{listofroutines}
|
||||
\cleardoublepage
|
||||
\appendix
|
||||
\include{distribution}
|
||||
|
||||
\include{license}
|
||||
\cleardoublepage
|
||||
|
||||
\include{bibliography}
|
||||
|
||||
|
||||
\end{document}
|
||||
%%% Local Variables:
|
||||
%%% mode: latex
|
||||
|
||||
+420
-395
@@ -1,395 +1,420 @@
|
||||
\section{User Interface\label{sec:userinterface}}
|
||||
\markboth{\underline{MLD2P4 User's and Reference Guide}}
|
||||
{\underline{\ref{sec:userinterface} User Interface}}
|
||||
|
||||
The basic user interface of MLD2P4 consists of six routines. The four routines \verb|mld_precinit|,
|
||||
\verb|mld_precset|, \verb|mld_precbld| and \verb|mld_precaply| encapsulate all the functionalities for the setup and application of any one-level and multi-level
|
||||
preconditioner implemented in the package.
|
||||
The routine \verb|mld_precfree| deallocates the preconditioner data structure, while
|
||||
\verb|mld_precdescr| prints a description of the preconditioner setup by the user.
|
||||
|
||||
For each routine, the same user interface is overloaded with
|
||||
respect to the real/complex case and the single/double precision;
|
||||
arguments with appropriate data types must be passed to the routine,
|
||||
i.e.
|
||||
\begin{itemize}
|
||||
\item the sparse matrix data structure, containing the matrix to be
|
||||
preconditioned, must be of type \verb|mld_|\emph{x}\verb|spmat_type|
|
||||
with \emph{x} = \verb|s| for real single precision, \emph{x} = \verb|d|
|
||||
for real double precision, \emph{x} = \verb|c| for complex single precision,
|
||||
\emph{x} = \verb|z| for complex double precision;
|
||||
\item the preconditioner data structure must be of type
|
||||
\verb|mld_|\emph{x}\verb|prec_type|, with \emph{x} =
|
||||
\verb|s|, \verb|d|, \verb|c|, \verb|z|, according to the sparse
|
||||
matrix data structure;
|
||||
\item the arrays containing the vectors $v$ and $w$ involved in
|
||||
the preconditioner application $w=M^{-1}v$ must be of type
|
||||
\emph{type}\verb|(|\emph{kind\_parameter}\verb|)|, with \emph{type} =
|
||||
\verb|real|, \verb|complex| and \emph{kind\_parameter} = \verb|kind(1.e0)|,
|
||||
\verb|kind(1.d0)|, according to the sparse matrix and preconditioner
|
||||
data structure; note that the PSBLAS module provides the constants \verb|psb_spk_|
|
||||
= \verb|kind(1.e0)| and \verb|psb_dpk_| = \verb|kind(1.d0)|;
|
||||
\item real parameters defining the preconditioner must be declared
|
||||
according to the precision of the previous data structures
|
||||
(see Section~\ref{sec:precset}).
|
||||
\end{itemize}
|
||||
A description of each routine is given in the remainder of this section.
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precinit\label{sec:precinit}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precinit(p,ptype,info)| \\
|
||||
\verb|mld_precinit(p,ptype,info,nlev)| \\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine allocates and initializes the preconditioner data structure,
|
||||
according to the preconditioner type chosen by the user.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{11.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x}
|
||||
must be chosen according to the real/complex, single/double
|
||||
precision version of MLD2P4 under use.\\
|
||||
\verb|ptype| & \verb|character(len=*), intent(in)|.\\
|
||||
& The type of preconditioner. Its values are specified in Table~\ref{tab:precinit}.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. See Section~\ref{sec:errors} for details.\\
|
||||
\verb|nlev| & \verb|integer, optional, intent(in)|.\\
|
||||
& The number of levels of the multilevel preconditioner.
|
||||
If \verb|nlev| is not present and \verb|ptype|='ML'/'ml',
|
||||
then \verb|nlev|=2 is assumed. Otherwise, \verb|nlev| is ignored.
|
||||
\end{tabular}
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precset\label{sec:precset}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precset(p,what,val,info)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine sets the parameters defining the preconditioner. More
|
||||
precisely, the parameter identified by \verb|what| is assigned the value
|
||||
contained in \verb|val|.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{11.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must
|
||||
be chosen according to the real/complex, single/double precision
|
||||
version of MLD2P4 under use.\\
|
||||
\verb|what| & \verb|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~\ref{tab:p_type}-\ref{tab:p_coarse}.\\
|
||||
\verb|val | & \verb|integer| \emph{or} \verb|character(len=*)| \emph{or}
|
||||
\verb|real(psb_spk_)| \emph{or} \verb|real(psb_dpk_)|,
|
||||
\verb|intent(in)|.\\
|
||||
& The value of the parameter to be set. The list of allowed
|
||||
values and the corresponding data types is given in
|
||||
Table~\ref{tab:params}.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. See Section~\ref{sec:errors} for details.\\
|
||||
%\verb|ilev| & \verb|integer, optional, intent(in)|.\\
|
||||
% & For the multilevel preconditioner, the level at which the
|
||||
% preconditioner parameter has to be set.
|
||||
% The levels are numbered in increasing
|
||||
% order starting from the finest one, i.e.\ level 1 is the finest level.
|
||||
% If \verb|ilev| is not present, the parameter identified by \verb|what|
|
||||
% is set at all the appropriate levels (see Table~\ref{tab:params}).
|
||||
\end{tabular}
|
||||
|
||||
\ \\
|
||||
A variety of (one-level and multi-level) preconditioner can be obtained
|
||||
by a suitable setting of the preconditioner parameters. These parameters
|
||||
can be logically divided into four groups, i.e.\ parameters defining
|
||||
\begin{enumerate}
|
||||
\item the type of multi-level preconditioner;
|
||||
\item the one-level preconditioner to be used as smoother;
|
||||
\item the aggregation algorithm;
|
||||
\item the coarse-space correction at the coarsest level.
|
||||
\end{enumerate}
|
||||
|
||||
A list of the parameters that can be set, along with their allowed and
|
||||
default values, is given in Tables~\ref{tab:p_type}-\ref{tab:p_coarse}.
|
||||
%Note that the routine allows to set different features of the
|
||||
%preconditioner at each level through the use of \verb|ilev|.
|
||||
%This should be done by users with experience in the field of
|
||||
%multi-level preconditioners. Non-expert users are recommended
|
||||
%to call \verb| mld_precset| without specifying \verb|ilev|.
|
||||
\textbf{CORREGGERE LA ROUTINE E LA DOC INTERNA - ilev NON E' PIU'
|
||||
ACCESSIBILE ALL'UTENTE.}
|
||||
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \emph{data type} & \verb|val| & \emph{default} &
|
||||
\emph{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{type of the multi-level preconditioner}}\\ \hline
|
||||
\verb|mld_ml_type_| & \verb|character(len=*)|
|
||||
& 'ADD' \ \ \ 'MULT'
|
||||
& 'MULT'
|
||||
& basic multi-level framework: additive or multiplicative
|
||||
among the levels always additive inside a level) \\
|
||||
\verb|mld_smoother_type_|& \verb|character(len=*)|
|
||||
& 'DIAG' \ \ \ 'BJAC' \ \ \ 'AS'
|
||||
& 'AS'
|
||||
& basic one-level preconditioner (i.e.\ smoother) of the
|
||||
multi-level preconditioner \\
|
||||
\verb|mld_smoother_pos_| & \verb|character(len=*)|
|
||||
& 'PRE' \ \ \ 'POST' \ \ \ 'TWOSIDE'
|
||||
& 'POST'
|
||||
& ``position'' of the smoother: pre-smoother, post-smoother,
|
||||
pre-/post-smoother \\
|
||||
\hline
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the type of multi-level preconditioner.
|
||||
\label{tab:p_type}}
|
||||
\end{sidewaystable}
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \emph{data type} & \verb|val| & \emph{default} &
|
||||
\emph{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{basic one-level preconditioner (smoother)}} \\ \hline
|
||||
\verb|mld_sub_ovr| & \verb|integer|
|
||||
& any number $\ge 0$
|
||||
& 1
|
||||
& number of overlap in the basic Schwarz preconditioner \\
|
||||
\verb|mld_sub_restr_| & \verb|character(len=*)|
|
||||
& 'HALO' \ \ \ 'NONE'
|
||||
& 'HALO'
|
||||
& type of restriction operator used in basic Schwarz preconditioner: 'HALO' for taking into account contributions from the overlap \\
|
||||
\verb|mld_sub_prol_| & \verb|character(len=*)|
|
||||
& 'SUM' \ \ \ 'NONE'
|
||||
& 'NONE'
|
||||
& type of prolongator operator used in basic Schwarz preconditioner: 'NONE' for neglecting contributions from the overlap \\
|
||||
\verb|mld_sub_solve_| & \verb|character(len=*)|
|
||||
& 'ILU' \ \ \ 'MILU' \ \ \ 'ILUT' \ \ \ 'UMF' \ \ \ 'SLU'
|
||||
& 'UMF'
|
||||
& available local solver: 'ILU' for incomplete LU, 'MILU' for modified incomplete LU, 'ILUT'
|
||||
for incomplete LU with threshold, 'UMF' for complete LU using UMFPACK~\cite{UMFPACK} version 4.4, 'SLU' for complete LU using SuperLU~\cite{SUPERLU}, version 3.0 \\
|
||||
\verb|mld_sub_fillin_| & \verb|integer|
|
||||
& any number $\ge 0$
|
||||
& 0
|
||||
& fill-in level for 'ILU', 'MILU' and 'ILUT' of local blocks\\
|
||||
\verb|mld_sub_thresh_| & \verb|real|
|
||||
& any number $\ge 0.$
|
||||
& 0.
|
||||
& drop tolerance for 'ILUT' \\
|
||||
\verb|mld_sub_ren_| & \verb|character(len=*)|
|
||||
& 'RENUM\_NONE', 'RENUM\_GLOBAL' %, 'RENUM\_GPS'
|
||||
&
|
||||
& reordering algorithm for the local blocks \\
|
||||
\hline
|
||||
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the basic one-level preconditioner (smoother).
|
||||
\label{tab:p_smoother}}
|
||||
\end{sidewaystable}
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \emph{data type} & \verb|val| & \emph{default} &
|
||||
\emph{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{aggregation algorithm}} \\ \hline
|
||||
\verb|mld_aggr_alg_| & \verb|character(len=*)|
|
||||
& 'DEC'
|
||||
& 'DEC'
|
||||
& define the aggregation scheme. Now, only decoupled aggregation is available\\
|
||||
\verb|mld_aggr_kind_| & \verb|character(len=*)|
|
||||
& 'SMOOTH', 'RAW'
|
||||
& 'SMOOTH'
|
||||
& define the type of aggregation technique (smoothed or nonsmoothed). \\
|
||||
\verb|mld_aggr_thresh_| & \verb|real|
|
||||
& any number $\in [0, 1]$
|
||||
& 0.
|
||||
& dropping threshold in aggregation \\
|
||||
\verb|mld_aggr_eig_| & \verb|character(len=*)|
|
||||
& 'A\_NORMI'
|
||||
&
|
||||
& define the algorithm to evaluate the maximum eigenvalue of $D^{-1}A$ for smoothed
|
||||
aggregation. Currently only the infinity norm of the matrix A is available\\
|
||||
\hline
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the aggregation algorithm.
|
||||
\label{tab:p_aggregation}}
|
||||
\end{sidewaystable}
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \emph{data type} & \verb|val| & \emph{default} &
|
||||
\emph{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{coarse-space correction at the coarsest level}}\\ \hline
|
||||
\verb|mld_coarse_mat_| & \verb|character(len=*)|
|
||||
& 'DISTR', 'REPL'
|
||||
& 'DISTR'
|
||||
& Coarse matrix: distributed or replicated \\
|
||||
\verb|mld_coarse_solve_| & \verb|character(len=*)|
|
||||
& 'BJAC' \ \ \ 'UMF' \ \ \ 'SLU' \ \ \ 'SLUDIST'
|
||||
& 'BJAC'
|
||||
& Only 'BJAC' and 'SLUDIST' can be used for distributed coarse matrix. 'BJAC' corresponds to some sweeps of a block-Jacobi solver, while 'SLUDIST' corresponds
|
||||
to the use of the external package SuperLU\_Dist~\cite{SUPERLUDIST}, version 2.0, for distributed sparse factorization and solve. \\
|
||||
\verb|mld_coarse_subsolve_| & \verb|character(len=*)|
|
||||
& 'ILU' \ \ \ 'MILU' \ \ \ 'ILUT' \ \ \ 'UMF' \ \ \ 'SLU'
|
||||
& 'UMF'
|
||||
& available solver for diagonal local blocks of the coarse matrix, when 'BJAC' is used as coarse solver\\
|
||||
\verb|mld_coarse_sweeps_|& \verb|integer|
|
||||
& any number $> 0$
|
||||
& 4
|
||||
& number of Block-Jacobi sweeps when 'BJAC' is used as coarse solver \\
|
||||
\verb|mld_coarse_fillin_| & \verb|integer|
|
||||
& any number $\ge 0$
|
||||
& 0
|
||||
& fill-in level in incomplete factorization of local diagonal blocks of the coarse matrix, when 'BJAC' is used as coarse solver and 'ILU' or 'MILU' is used as local solver \textbf{MODIFICA NOME PARAM. NEL SW} \\
|
||||
\verb|mld_coarse_thresh_| & \verb|real|
|
||||
& any number $\ge 0.$
|
||||
& 0.
|
||||
& drop tolerance in incomplete factorization of local diagonal blocks of the coarse matrix, when 'BJAC' is used as coarse solver and 'ILUT' is used as local solver \\ \hline
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the coarse-space correction at the coarsest
|
||||
level.\label{tab:p_coarse}}
|
||||
\end{sidewaystable}
|
||||
|
||||
|
||||
\clearpage
|
||||
\subsection{Subroutine mld\_precbld\label{sec:precbld}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precbld(a,desc_a,p,info)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine builds the preconditioner according to the requirements made by
|
||||
the user through the routines \verb|mld_precinit| and \verb|mld_precset|.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{11.5cm}}
|
||||
\verb|a| & \verb|type(psb_|\emph{x}\verb|spmat_type), intent(in)|. \\
|
||||
& The sparse matrix structure containing the local part of the
|
||||
matrix to be preconditioned. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.
|
||||
See the PSBLAS User's Guide for details \cite{PSBLASGUIDE}.\\
|
||||
\verb|desc_a| & \verb|type(psb_desc_type), intent(in)|. \\
|
||||
& The communication descriptor of a. See the PSBLAS User's Guide for
|
||||
details \cite{PSBLASGUIDE}.\\
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. See Section~\ref{sec:errors} for details.\\
|
||||
\end{tabular}
|
||||
|
||||
\clearpage
|
||||
\subsection{Subroutine mld\_precaply\label{sec:precaply}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precaply(p,x,y,desc_a,info)|\\
|
||||
\verb|mld_precaply(p,x,y,desc_a,info,trans,work)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine computes $y = op(M^{-1})\, x$, where $M$ is a previously built
|
||||
preconditioner, stored in the \verb|p| data structure, and $op$
|
||||
denotes the preconditioner itself or its transpose, according to
|
||||
the value of \verb|trans|.
|
||||
Note that, when MLD2P4 is used with a Krylov solver from PSBLAS,
|
||||
\verb|mld_precaply| is called within the PSBLAS routine \verb|mld_krylov|
|
||||
and hence is completely transparent to the user.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{11.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure, containing the local part of $M$.
|
||||
Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|x| & \emph{type}\verb|(|\emph{kind\_parameter}\verb|), dimension(:), intent(in)|.\\
|
||||
& The local part of the vector $x$. Note that \emph{type} and
|
||||
\emph{kind\_parameter} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|y| & \emph{type}\verb|(|\emph{kind\_parameter}\verb|), dimension(:), intent(out)|.\\
|
||||
& The local part of the vector $y$. Note that \emph{type} and
|
||||
\emph{kind\_parameter} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|desc_a| & \verb|type(psb_desc_type), intent(in)|. \\
|
||||
& The communication descriptor associated to the matrix to be
|
||||
preconditioned.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. See Section~\ref{sec:errors} for details.\\
|
||||
\verb|trans| & \verb|character(len=1), optional, intent(in).|\\
|
||||
& If \verb|trans| = \verb|'N','n'| then $op(M^{-1}) = M^{-1}$;
|
||||
if \verb|trans| = \verb|'T','t'| then $op(M^{-1}) = M^{-T}$
|
||||
(transpose of $M^{-1})$; if \verb|trans| = \verb|'C','c'| then $op(M^{-1}) = M^{-C}$
|
||||
(conjugate transpose of $M^{-1})$.\\
|
||||
\verb|work| & \emph{type}\verb|(|\emph{kind\_parameter}\verb|), dimension(:), optional, target|.\\
|
||||
& Workspace. Its size should be at
|
||||
least \verb|4 * psb_cd_get_local_cols(desc_a)| (see the PSBLAS User's Guide).
|
||||
Note that \emph{type} and \emph{kind\_parameter} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\end{tabular}
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precfree\label{sec:precfree}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precfree(p,info)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine deallocates the preconditioner data structure.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{11.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. See Section~\ref{sec:errors} for details.\\
|
||||
\end{tabular}
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precdescr\label{sec:precdescr}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precdescr(p,iout)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine prints a description of the preconditioner
|
||||
to a file.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{10.6cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(in)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|iout| & \verb|integer, intent(in), optional|.\\
|
||||
& The id of the file where the preconditioner description
|
||||
will be printed, default is standard output.\\
|
||||
\end{tabular}
|
||||
|
||||
%%% Local Variables:
|
||||
%%% mode: latex
|
||||
%%% TeX-master: "userguide"
|
||||
%%% End:
|
||||
\section{User Interface\label{sec:userinterface}}
|
||||
\markboth{\textsc{MLD2P4 User's and Reference Guide}}
|
||||
{\textsc{\ref{sec:userinterface} User Interface}}
|
||||
|
||||
The basic user interface of MLD2P4 consists of six routines. The four routines \verb|mld_precinit|,
|
||||
\verb|mld_precset|, \verb|mld_precbld| and \verb|mld_precaply| encapsulate all the functionalities
|
||||
for the setup and the application of any one-level and multi-level
|
||||
preconditioner implemented in the package.
|
||||
The routine \verb|mld_precfree| deallocates the preconditioner data structure, while
|
||||
\verb|mld_prec\-descr| prints a description of the preconditioner setup by the user.
|
||||
|
||||
For each routine, the same user interface is overloaded with
|
||||
respect to the real/complex case and the single/double precision;
|
||||
arguments with appropriate data types must be passed to the routine,
|
||||
i.e.
|
||||
\begin{itemize}
|
||||
\item the sparse matrix data structure, containing the matrix to be
|
||||
preconditioned, must be of type \verb|mld_|\emph{x}\verb|spmat_type|
|
||||
with \emph{x} = \verb|s| for real single precision, \emph{x} = \verb|d|
|
||||
for real double precision, \emph{x} = \verb|c| for complex single precision,
|
||||
\emph{x} = \verb|z| for complex double precision;
|
||||
\item the preconditioner data structure must be of type
|
||||
\verb|mld_|\emph{x}\verb|prec_type|, with \emph{x} =
|
||||
\verb|s|, \verb|d|, \verb|c|, \verb|z|, according to the sparse
|
||||
matrix data structure;
|
||||
\item the arrays containing the vectors $v$ and $w$ involved in
|
||||
the preconditioner application $w=M^{-1}v$ must be of type
|
||||
\emph{type}\verb|(|\emph{kind\_parameter}\verb|)|, with \emph{type} =
|
||||
\verb|real|, \verb|complex| and \emph{kind\_parameter} = \verb|kind(1.e0)|,
|
||||
\verb|kind(1.d0)|, according to the sparse matrix and preconditioner
|
||||
data structure; note that the PSBLAS module \verb|psb_base_mod|
|
||||
provides the constants \verb|psb_spk_|
|
||||
= \verb|kind(1.e0)| and \verb|psb_dpk_| = \verb|kind(1.d0)|;
|
||||
\item real parameters defining the preconditioner must be declared
|
||||
according to the precision of the previous data structures
|
||||
(see Section~\ref{sec:precset}).
|
||||
\end{itemize}
|
||||
A description of each routine is given in the remainder of this section.
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precinit\label{sec:precinit}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precinit(p,ptype,info)| \\
|
||||
\verb|mld_precinit(p,ptype,info,nlev)| \\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine allocates and initializes the preconditioner data structure,
|
||||
according to the preconditioner type chosen by the user.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{10.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x}
|
||||
must be chosen according to the real/complex, single/double
|
||||
precision version of MLD2P4 under use.\\
|
||||
\verb|ptype| & \verb|character(len=*), intent(in)|.\\
|
||||
& The type of preconditioner. Its values are specified in Table~\ref{tab:precinit}.\\
|
||||
Note that the uppercase and lowercase letters can be used indifferently.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. If no error, 0 is returned. See Section~\ref{sec:errors} for details.\\
|
||||
\verb|nlev| & \verb|integer, optional, intent(in)|.\\
|
||||
& The number of levels of the multilevel preconditioner.
|
||||
If \verb|nlev| is not present and \verb|ptype|=\verb|'ML'|, \verb|'ml'|,
|
||||
then \verb|nlev|=2 is assumed. Otherwise, \verb|nlev| is ignored.\\
|
||||
\end{tabular}
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precset\label{sec:precset}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precset(p,what,val,info)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine sets the parameters defining the preconditioner. More
|
||||
precisely, the parameter identified by \verb|what| is assigned the value
|
||||
contained in \verb|val|.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{10.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must
|
||||
be chosen according to the real/complex, single/double precision
|
||||
version of MLD2P4 under use.\\
|
||||
\verb|what| & \verb|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~\ref{tab:p_type}-\ref{tab:p_coarse}.\\
|
||||
\verb|val | & \verb|integer| \emph{or} \verb|character(len=*)| \emph{or}
|
||||
\verb|real(psb_spk_)| \emph{or} \verb|real(psb_dpk_)|,
|
||||
\verb|intent(in)|.\\
|
||||
& The value of the parameter to be set. The list of allowed
|
||||
values and the corresponding data types is given in
|
||||
Tables~\ref{tab:p_type}-\ref{tab:p_coarse}.
|
||||
When the value is of type \verb|character(len=*)|,
|
||||
uppercase and lowercase letters can be used indifferently.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. If no error, 0 is returned. See Section~\ref{sec:errors}
|
||||
for details.\\
|
||||
%
|
||||
%\verb|ilev| & \verb|integer, optional, intent(in)|.\\
|
||||
% & For the multilevel preconditioner, the level at which the
|
||||
% preconditioner parameter has to be set.
|
||||
% The levels are numbered in increasing
|
||||
% order starting from the finest one, i.e.\ level 1 is the finest level.
|
||||
% If \verb|ilev| is not present, the parameter identified by \verb|what|
|
||||
% is set at all the appropriate levels (see Table~\ref{tab:params}).
|
||||
\end{tabular}
|
||||
|
||||
\ \\
|
||||
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
|
||||
\begin{enumerate}
|
||||
\item the type of multi-level preconditioner;
|
||||
\item the one-level preconditioner used as smoother;
|
||||
\item the aggregation algorithm;
|
||||
\item the coarse-space correction at the coarsest level.
|
||||
\end{enumerate}
|
||||
A list of the parameters that can be set, along with their allowed and
|
||||
default values, is given in Tables~\ref{tab:p_type}-\ref{tab:p_coarse}.
|
||||
For a better understanding of the meaning of the parameters, the user
|
||||
is referred to Section \ref{sec:background}.
|
||||
%
|
||||
%Note that the routine allows to set different features of the
|
||||
%preconditioner at each level through the use of \verb|ilev|.
|
||||
%This should be done by users with experience in the field of
|
||||
%multi-level preconditioners. Non-expert users are recommended
|
||||
%to call \verb| mld_precset| without specifying \verb|ilev|.
|
||||
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \textsc{data type} & \verb|val| & \textsc{default} &
|
||||
\textsc{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{type of the multi-level preconditioner}}\\ \hline
|
||||
\verb|mld_ml_type_| & \verb|character(len=*)|
|
||||
& \texttt{'ADD'} \ \ \ \texttt{'MULT'}
|
||||
& \texttt{'MULT'}
|
||||
& basic multi-level framework: additive or multiplicative
|
||||
among the levels (always additive inside a level) \\
|
||||
\verb|mld_smoother_type_|& \verb|character(len=*)|
|
||||
& \texttt{'DIAG'} \ \ \ \texttt{'BJAC'} \ \ \ \texttt{'AS'}
|
||||
& \texttt{'AS'}
|
||||
& basic one-level preconditioner (i.e.\ smoother) of the
|
||||
multi-level preconditioner: diagonal, block Jacobi,
|
||||
AS \\
|
||||
\verb|mld_smoother_pos_| & \verb|character(len=*)|
|
||||
& \texttt{'PRE'} \ \ \ \texttt{'POST'} \ \ \ \texttt{'TWOSIDE'}
|
||||
& \texttt{'POST'}
|
||||
& ``position'' of the smoother: pre-smoother, post-smoother,
|
||||
pre- and post-smoother \\
|
||||
\hline
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the type of multi-level preconditioner.
|
||||
\label{tab:p_type}}
|
||||
\end{sidewaystable}
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2.6cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \textsc{data type} & \verb|val| & \textsc{default} &
|
||||
\textsc{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{basic one-level preconditioner (smoother)}} \\ \hline
|
||||
\verb|mld_sub_ovr_| & \verb|integer|
|
||||
& any integer number $\ge 0$
|
||||
& 1
|
||||
& Number of overlap layers. \\
|
||||
\verb|mld_sub_restr_| & \verb|character(len=*)|
|
||||
& \texttt{'HALO'} \ \ \ \ \ \texttt{'NONE'}
|
||||
& \texttt{'HALO'}
|
||||
& Type of restriction operator:
|
||||
\texttt{'HALO'} for taking into account the overlap, \texttt{'NONE'}
|
||||
for neglecting it. \\
|
||||
\verb|mld_sub_prol_| & \verb|character(len=*)|
|
||||
& \texttt{'SUM'} \ \ \ \ \ \texttt{'NONE'}
|
||||
& \texttt{'NONE'}
|
||||
& Type of prolongator operator:
|
||||
\texttt{'SUM'} for adding the contributions from the overlap, \texttt{'NONE'}
|
||||
for neglecting them. \\
|
||||
\verb|mld_sub_solve_| & \verb|character(len=*)|
|
||||
& \texttt{'ILU'} \ \ \ \ \ \texttt{'MILU'} \ \ \ \ \ \texttt{'ILUT'} \ \ \ \ \
|
||||
\texttt{'UMF'} \ \ \ \ \ \texttt{'SLU'}
|
||||
& \texttt{'UMF'}
|
||||
& Local solver: ILU($p$), MILU($p$), ILU($p,t$), LU from UMFPACK, LU from SuperLU,
|
||||
plus triangular solve. \\
|
||||
\verb|mld_sub_fillin_| & \verb|integer|
|
||||
& any integer number $\ge 0$
|
||||
& 0
|
||||
& Fill-in level $p$ of the incomplete LU factorizations. \\
|
||||
\verb|mld_sub_thresh_| & \verb|real(|\emph{kind\_parameter}\verb|)|
|
||||
& any real number $\ge 0$
|
||||
& \texttt{0.e0} (or \texttt{0.d0})
|
||||
& Drop tolerance $t$ in the ILU($p,t$) factorization. \\
|
||||
\verb|mld_sub_ren_| & \verb|character(len=*)|
|
||||
& \texttt{'RENUM\_NONE'}, \texttt{'RENUM\_GLOBAL'} %, \texttt{'RENUM_GPS'}
|
||||
& \texttt{'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. \\
|
||||
\hline
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the one-level preconditioner used as smoother.
|
||||
\label{tab:p_smoother}}
|
||||
\end{sidewaystable}
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2.6cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \textsc{data type} & \verb|val| & \textsc{default} &
|
||||
\textsc{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{aggregation algorithm}} \\ \hline
|
||||
\verb|mld_aggr_alg_| & \verb|character(len=*)|
|
||||
& \texttt{'DEC'}
|
||||
& \texttt{'DEC'}
|
||||
& Aggregation algorithm. Currently, only the decoupled aggregation is available. \\
|
||||
\verb|mld_aggr_kind_| & \verb|character(len=*)|
|
||||
& \texttt{'SMOOTH'} \ \ \ \ \ \texttt{'RAW'}
|
||||
& \texttt{'SMOOTH'}
|
||||
& Type of aggregation: smoothed or raw, i.e.\ using the tentative prolongator. \\
|
||||
\verb|mld_aggr_thresh_| & \verb|real(|\emph{kind\_parameter}\verb|)|
|
||||
& any real number $\in [0, 1]$
|
||||
& \texttt{0.e0} (or \texttt{0.d0})
|
||||
& The threshold $\theta$ in the aggregation algorithm. \\
|
||||
\verb|mld_aggr_eig_| & \verb|character(len=*)|
|
||||
& \texttt{'A\_NORMI'}
|
||||
& \texttt{'A\_NORMI'}
|
||||
& Estimate of the maximum eigenvalue of $D^{-1}A$
|
||||
for the smoothed aggregation. Currently, only the infinity norm of
|
||||
the matrix is available. \\
|
||||
\hline
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the aggregation algorithm.
|
||||
\label{tab:p_aggregation}}
|
||||
\end{sidewaystable}
|
||||
|
||||
\begin{sidewaystable}
|
||||
\begin{center}
|
||||
\begin{tabular}{|l|l|p{2.6cm}|l|p{7cm}|}
|
||||
\hline
|
||||
\verb|what| & \textsc{data type} & \verb|val| & \textsc{default} &
|
||||
\textsc{comments} \\ \hline
|
||||
%\multicolumn{5}{|c|}{\emph{coarse-space correction at the coarsest level}}\\ \hline
|
||||
\verb|mld_coarse_mat_| & \verb|character(len=*)|
|
||||
& \texttt{'DISTR'} \ \ \ \ \ \texttt{'REPL'}
|
||||
& \texttt{'DISTR'}
|
||||
& Coarsest matrix: distributed among the processors or replicated on each of them. \\
|
||||
\verb|mld_coarse_solve_| & \verb|character(len=*)|
|
||||
& \texttt{'BJAC'} \ \ \ \ \ \texttt{'UMF'} \ \ \ \ \ \ \ \ \texttt{'SLU'}
|
||||
\ \ \ \ \ \texttt{'SLUDIST'}
|
||||
& \texttt{'BJAC'}
|
||||
& Solver used at the coarsest level: block Jacobi, sequential LU from UMFPACK,
|
||||
sequential LU from SuperLU, or distributed LU from SuperLU\_Dist.
|
||||
If the coarsest matrix is distributed, only \texttt{'BJAC'} and \texttt{'SLUDIST'}
|
||||
can be chosen; if it is replicated, only \emph{'BJAC'} or \texttt{'SLUDIST'} can
|
||||
be selected. \\
|
||||
\verb|mld_coarse_subsolve_| & \verb|character(len=*)|
|
||||
& \texttt{'ILU'} \ \ \ \ \ \ \ \texttt{'MILU'} \ \ \ \ \ \ \ \ \texttt{'ILUT'}
|
||||
\ \ \ \ \ \ \ \texttt{'UMF'} \ \ \ \ \ \ \ \texttt{'SLU'}
|
||||
& \texttt{'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. \\
|
||||
\verb|mld_coarse_sweeps_|& \verb|integer|
|
||||
& any integer number $> 0$
|
||||
& \texttt{4}
|
||||
& Number of Block-Jacobi sweeps when 'BJAC' is used as coarsest-level solver. \\
|
||||
\verb|mld_coarse_fillin_| & \verb|integer|
|
||||
& any integer number $\ge 0$
|
||||
& \texttt{0}
|
||||
& Fill-in level $p$ of the incomplete LU factorizations. \\
|
||||
\verb|mld_coarse_thresh_| & \verb|real(|\emph{kind\_parameter}\verb|)|
|
||||
& any real number $\ge 0$
|
||||
& \texttt{0.d0} (or \texttt{0.e0})
|
||||
& Drop tolerance $t$ in the ILU($p,t$) factorization. \\
|
||||
\hline
|
||||
\end{tabular}
|
||||
\end{center}
|
||||
\caption{Parameters defining the coarse-space correction at the coarsest
|
||||
level.\label{tab:p_coarse}}
|
||||
\end{sidewaystable}
|
||||
|
||||
|
||||
\clearpage
|
||||
\subsection{Subroutine mld\_precbld\label{sec:precbld}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precbld(a,desc_a,p,info)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine builds the preconditioner according to the requirements made by
|
||||
the user through the routines \verb|mld_precinit| and \verb|mld_precset|.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{10.5cm}}
|
||||
\verb|a| & \verb|type(psb_|\emph{x}\verb|spmat_type), intent(in)|. \\
|
||||
& The sparse matrix structure containing the local part of the
|
||||
matrix to be preconditioned. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.
|
||||
See the PSBLAS User's Guide for details \cite{PSBLASGUIDE}.\\
|
||||
\verb|desc_a| & \verb|type(psb_desc_type), intent(in)|. \\
|
||||
& The communication descriptor of \verb|a|. See the PSBLAS User's Guide for
|
||||
details \cite{PSBLASGUIDE}.\\
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. If no error, 0 is returned. See Section~\ref{sec:errors} for details.\\
|
||||
\end{tabular}
|
||||
|
||||
\clearpage
|
||||
\subsection{Subroutine mld\_precaply\label{sec:precaply}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precaply(p,x,y,desc_a,info)|\\
|
||||
\verb|mld_precaply(p,x,y,desc_a,info,trans,work)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine computes $y = op(M^{-1})\, x$, where $M$ is a previously built
|
||||
preconditioner, stored into \verb|p|, and $op$
|
||||
denotes the preconditioner itself or its transpose, according to
|
||||
the value of \verb|trans|.
|
||||
Note that, when MLD2P4 is used with a Krylov solver from PSBLAS,
|
||||
\verb|mld_precaply| is called within the PSBLAS routine \verb|mld_krylov|
|
||||
and hence it is completely transparent to the user.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{10.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure, containing the local part of $M$.
|
||||
Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|x| & \emph{type}\verb|(|\emph{kind\_parameter}\verb|), dimension(:), intent(in)|.\\
|
||||
& The local part of the vector $x$. Note that \emph{type} and
|
||||
\emph{kind\_parameter} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|y| & \emph{type}\verb|(|\emph{kind\_parameter}\verb|), dimension(:), intent(out)|.\\
|
||||
& The local part of the vector $y$. Note that \emph{type} and
|
||||
\emph{kind\_parameter} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|desc_a| & \verb|type(psb_desc_type), intent(in)|. \\
|
||||
& The communication descriptor associated to the matrix to be
|
||||
preconditioned.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. If no error, 0 is returned. See Section~\ref{sec:errors} for details.\\
|
||||
\verb|trans| & \verb|character(len=1), optional, intent(in).|\\
|
||||
& If \verb|trans| = \verb|'N','n'| then $op(M^{-1}) = M^{-1}$;
|
||||
if \verb|trans| = \verb|'T','t'| then $op(M^{-1}) = M^{-T}$
|
||||
(transpose of $M^{-1})$; if \verb|trans| = \verb|'C','c'| then $op(M^{-1}) = M^{-C}$
|
||||
(conjugate transpose of $M^{-1})$.\\
|
||||
\verb|work| & \emph{type}\verb|(|\emph{kind\_parameter}\verb|), dimension(:), optional, target|.\\
|
||||
& Workspace. Its size should be at
|
||||
least \verb|4 * psb_cd_get_local_cols(desc_a)| (see the PSBLAS User's Guide).
|
||||
Note that \emph{type} and \emph{kind\_parameter} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\end{tabular}
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precfree\label{sec:precfree}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precfree(p,info)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine deallocates the preconditioner data structure.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{10.5cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(inout)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. If no error, 0 is returned. See Section~\ref{sec:errors} for details.\\
|
||||
\end{tabular}
|
||||
|
||||
|
||||
\subsection{Subroutine mld\_precdescr\label{sec:precdescr}}
|
||||
|
||||
\begin{center}
|
||||
\verb|mld_precdescr(p,info,iout)|\\
|
||||
\end{center}
|
||||
|
||||
\noindent
|
||||
This routine prints a description of the preconditioner
|
||||
to the standard output or to a file.
|
||||
|
||||
\subsubsection*{Arguments}
|
||||
|
||||
\begin{tabular}{p{1.2cm}p{10.6cm}}
|
||||
\verb|p| & \verb|type(mld_|\emph{x}\verb|prec_type), intent(in)|.\\
|
||||
& The preconditioner data structure. Note that \emph{x} must be chosen according
|
||||
to the real/complex, single/double precision version of MLD2P4 under use.\\
|
||||
\verb|info| & \verb|integer, intent(out)|.\\
|
||||
& Error code. If no error, 0 is returned. See Section~\ref{sec:errors} for details.\\
|
||||
\verb|iout| & \verb|integer, intent(in), optional|.\\
|
||||
& The id of the file where the preconditioner description
|
||||
will be printed; the default is the standard output.\\
|
||||
\end{tabular}
|
||||
|
||||
%%% Local Variables:
|
||||
%%% mode: latex
|
||||
%%% TeX-master: "userguide"
|
||||
%%% End:
|
||||
|
||||
+67
-66
@@ -117,12 +117,12 @@ subroutine mld_cprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -133,12 +133,12 @@ subroutine mld_cprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -149,14 +149,14 @@ subroutine mld_cprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
case ('AS')
|
||||
@@ -166,15 +166,15 @@ subroutine mld_cprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
|
||||
case ('ML')
|
||||
@@ -189,61 +189,62 @@ subroutine mld_cprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
if (nlev_ == 1) return
|
||||
|
||||
do ilev_ = 2, nlev_ -1
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
end do
|
||||
ilev_ = nlev_
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_solve_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 4
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
|
||||
case default
|
||||
write(0,*) name,': Warning: Unknown preconditioner type request "',ptype,'"'
|
||||
|
||||
@@ -244,6 +244,8 @@ subroutine mld_cprecseti(p,what,val,info,ilev)
|
||||
select case (val)
|
||||
case(mld_umf_, mld_slu_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_repl_mat_
|
||||
case(mld_bjac_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
case default
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
end select
|
||||
|
||||
+67
-66
@@ -117,12 +117,12 @@ subroutine mld_dprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -133,12 +133,12 @@ subroutine mld_dprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -149,14 +149,14 @@ subroutine mld_dprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
case ('AS')
|
||||
@@ -166,15 +166,15 @@ subroutine mld_dprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
|
||||
case ('ML')
|
||||
@@ -189,61 +189,62 @@ subroutine mld_dprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
if (nlev_ == 1) return
|
||||
|
||||
do ilev_ = 2, nlev_ -1
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
end do
|
||||
ilev_ = nlev_
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_solve_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 4
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
|
||||
case default
|
||||
write(0,*) name,': Warning: Unknown preconditioner type request "',ptype,'"'
|
||||
|
||||
@@ -244,6 +244,8 @@ subroutine mld_dprecseti(p,what,val,info,ilev)
|
||||
select case (val)
|
||||
case(mld_umf_, mld_slu_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_repl_mat_
|
||||
case(mld_bjac_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
case default
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
end select
|
||||
|
||||
+67
-66
@@ -117,12 +117,12 @@ subroutine mld_sprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -133,12 +133,12 @@ subroutine mld_sprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -149,14 +149,14 @@ subroutine mld_sprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
case ('AS')
|
||||
@@ -166,15 +166,15 @@ subroutine mld_sprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
|
||||
case ('ML')
|
||||
@@ -189,61 +189,62 @@ subroutine mld_sprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
if (nlev_ == 1) return
|
||||
|
||||
do ilev_ = 2, nlev_ -1
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
end do
|
||||
ilev_ = nlev_
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = szero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_solve_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 4
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.e0/3.e0
|
||||
|
||||
case default
|
||||
write(0,*) name,': Warning: Unknown preconditioner type request "',ptype,'"'
|
||||
|
||||
@@ -244,6 +244,8 @@ subroutine mld_sprecseti(p,what,val,info,ilev)
|
||||
select case (val)
|
||||
case(mld_umf_, mld_slu_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_repl_mat_
|
||||
case(mld_bjac_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
case default
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
end select
|
||||
|
||||
+67
-66
@@ -117,12 +117,12 @@ subroutine mld_zprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_noprec_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -133,12 +133,12 @@ subroutine mld_zprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_diag_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_f_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
@@ -149,14 +149,14 @@ subroutine mld_zprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
case ('AS')
|
||||
@@ -166,15 +166,15 @@ subroutine mld_zprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
|
||||
|
||||
case ('ML')
|
||||
@@ -189,61 +189,62 @@ subroutine mld_zprecinit(p,ptype,info,nlev)
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_as_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_halo_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
if (nlev_ == 1) return
|
||||
|
||||
do ilev_ = 2, nlev_ -1
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 1
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
end do
|
||||
ilev_ = nlev_
|
||||
if (info == 0) call psb_realloc(mld_ifpsz_,p%baseprecv(ilev_)%iprcparm,info)
|
||||
if (info == 0) call psb_realloc(mld_rfpsz_,p%baseprecv(ilev_)%rprcparm,info)
|
||||
if (info /= 0) return
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(:) = 0
|
||||
p%baseprecv(ilev_)%rprcparm(:) = dzero
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_solve_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_type_) = mld_bjac_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_restr_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_prol_) = psb_none_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ren_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_ovr_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_ml_type_) = mld_mult_ml_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_alg_) = mld_dec_aggr_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_kind_) = mld_smooth_prol_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_pos_) = mld_post_smooth_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_aggr_eig_) = mld_max_norm_
|
||||
p%baseprecv(ilev_)%iprcparm(mld_sub_fillin_) = 0
|
||||
p%baseprecv(ilev_)%iprcparm(mld_smoother_sweeps_) = 4
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
p%baseprecv(ilev_)%rprcparm(mld_aggr_damp_) = 4.d0/3.d0
|
||||
|
||||
case default
|
||||
write(0,*) name,': Warning: Unknown preconditioner type request "',ptype,'"'
|
||||
|
||||
@@ -244,6 +244,8 @@ subroutine mld_zprecseti(p,what,val,info,ilev)
|
||||
select case (val)
|
||||
case(mld_umf_, mld_slu_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_repl_mat_
|
||||
case(mld_bjac_)
|
||||
p%baseprecv(nlev_)%iprcparm(mld_sub_solve_) = mld_ilu_n_
|
||||
case default
|
||||
p%baseprecv(nlev_)%iprcparm(mld_coarse_mat_) = mld_distr_mat_
|
||||
end select
|
||||
|
||||
Reference in New Issue
Block a user