diff --git a/README b/README.md similarity index 97% rename from README rename to README.md index f8b2f1c8..b0def0e7 100644 --- a/README +++ b/README.md @@ -70,9 +70,12 @@ NOTES settings, but the rest of the application needs not be changed. -Contributors +The MLD2P4 team. +--------------- +Project lead: +Salvatore Filippone -Salvatore Filippone +Contributors: Pasqua D'Ambra Daniela di Serafino Ambra Abdullahi Hassan diff --git a/docs/html/contents.png b/docs/html/contents.png deleted file mode 100644 index 0c752c66..00000000 Binary files a/docs/html/contents.png and /dev/null differ diff --git a/docs/html/crossref.png b/docs/html/crossref.png deleted file mode 100644 index 7dd2dddf..00000000 Binary files a/docs/html/crossref.png and /dev/null differ diff --git a/docs/html/img1.png b/docs/html/img1.png deleted file mode 100644 index 6e9422be..00000000 Binary files a/docs/html/img1.png and /dev/null differ diff --git a/docs/html/img10.png b/docs/html/img10.png deleted file mode 100644 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- -next -up -previous - -contents -
- Next: Abstract -   Contents -
-
- -MLD2P4 -
-
-User's and Reference Guide -
A guide for the MultiLevel Domain Decomposition -Parallel Preconditioners Package -based on PSBLAS -
-
-
-
Pasqua D'Ambra -
IAC-CNR, Naples, Italy -
-
-
-
Daniela di Serafino -
University of Campania “Luigi Vanvitelli”, Caserta, Italy -
-
-
-
Salvatore Filippone -
Cranfield University, Cranfield, United Kingdom -
-
-
-
-
-
-
-
-
-
-
-Software version: 2.2 -
-July 31, 2018 - -
- - -

- -

- -

- - - - - -
- - - diff --git a/docs/html/next.png b/docs/html/next.png deleted file mode 100644 index 1628652a..00000000 Binary files a/docs/html/next.png and /dev/null differ diff --git a/docs/html/next_g.png b/docs/html/next_g.png deleted file mode 100644 index 9d3f5912..00000000 Binary files a/docs/html/next_g.png and /dev/null differ diff --git a/docs/html/node1.html b/docs/html/node1.html deleted file mode 100644 index fc552ff5..00000000 --- a/docs/html/node1.html +++ /dev/null @@ -1,117 +0,0 @@ - - - - - -Abstract - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Contents - Up: userhtml - Previous: userhtml -   Contents -
-
- - -

-Abstract -

- -MLD2P4 (MULTILEVEL DOMAIN DECOMPOSITION PARALLEL PRECONDITIONERS PACKAGE -BASED ON PSBLAS) is a package of parallel algebraic multilevel preconditioners. -The first release of MLD2P4 made available multilevel additive and hybrid Schwarz -preconditioners, as well as one-level additive Schwarz preconditioners. The package -has been extended to include further multilevel cycles and smoothers widely used in -multigrid methods. In the multilevel case, a purely algebraic approach is applied to -generate coarse-level corrections, so that no geometric background is needed -concerning the matrix to be preconditioned. The matrix is assumed to be square, -real or complex. - -

-MLD2P4 has been designed to provide scalable and easy-to-use preconditioners -in the context of the PSBLAS (Parallel Sparse Basic Linear Algebra Subprograms) -computational framework and can be used in conjuction with the Krylov solvers -available in this framework. MLD2P4 enables the user to easily specify different -features of an algebraic multilevel preconditioner, thus allowing to search -for the “best” preconditioner for the problem at hand. - -

-The package employs object-oriented design techniques in -Fortran 2003, with interfaces to additional third party libraries -such as MUMPS, UMFPACK, SuperLU, and SuperLU_Dist, which -can be exploited in building multilevel preconditioners. The parallel -implementation is based on a Single Program Multiple Data (SPMD) -paradigm; the inter-process communication is based on MPI and -is managed mainly through PSBLAS. - -

-This guide provides a brief description of the functionalities and -the user interface of MLD2P4. - - -

- - - -

- - -next - -up - -previous - -contents -
- Next: Contents - Up: userhtml - Previous: userhtml -   Contents
- - - - diff --git a/docs/html/node10.html b/docs/html/node10.html deleted file mode 100644 index 37ec11f4..00000000 --- a/docs/html/node10.html +++ /dev/null @@ -1,67 +0,0 @@ - - - - - -Bug reporting - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Example and test programs - Up: Configuring and Building MLD2P4 - Previous: Configuration options -   Contents -
-
- - -

-Bug reporting -

-If you find any bugs in our codes, please report them through our -issues page on
https://github.com/sfilippone/mld2p4-2/issues -
-To enable us to track the bug, please provide a log from the failing -application, the test conditions, and ideally a self-contained test -program reproducing the issue. - -

- -

- - - diff --git a/docs/html/node11.html b/docs/html/node11.html deleted file mode 100644 index 13e572cb..00000000 --- a/docs/html/node11.html +++ /dev/null @@ -1,80 +0,0 @@ - - - - - -Example and test programs - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Multigrid Background - Up: Configuring and Building MLD2P4 - Previous: Bug reporting -   Contents -
-
- - -

-
-Example and test programs -

-The package contains the examples and tests directories; -both of them are further divided into fileread and -pdegen subdirectories. Their purpose is as follows: -
-
examples
-
contains a set of simple example programs with a - predefined choice of preconditioners, selectable via integer - values. These are intended to get an acquaintance with the - multilevel preconditioners available in MLD2P4. -
-
tests
-
contains a set of more sophisticated examples that - will allow the user, via the input files in the runs - subdirectories, to experiment with the full range of preconditioners - implemented in the package. -
-
-The fileread directories contain sample programs that read -sparse matrices from files, according to the Matrix Market or the -Harwell-Boeing storage format; the pdegen programs generate -matrices in full parallel mode from the discretization of a sample partial -differential equation. - -
- - - diff --git a/docs/html/node12.html b/docs/html/node12.html deleted file mode 100644 index 0a40de2f..00000000 --- a/docs/html/node12.html +++ /dev/null @@ -1,163 +0,0 @@ - - - - - -Multigrid Background - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: AMG preconditioners - Up: userhtml - Previous: Example and test programs -   Contents -
-
- - -

-
-Multigrid Background -

- - -

-Multigrid preconditioners, coupled with Krylov iterative -solvers, are widely used in the parallel solution of large and sparse linear systems, -because of their optimality in the solution of linear systems arising from the -discretization of scalar elliptic Partial Differential Equations (PDEs) on regular grids. -Optimality, also known as algorithmic scalability, is the property -of having a computational cost per iteration that depends linearly on -the problem size, and a convergence rate that is independent of the problem size. - -

-Multigrid preconditioners are based on a recursive application of a two-grid process -consisting of smoother iterations and a coarse-space (or coarse-level) correction. -The smoothers may be either basic iterative methods, such as the Jacobi and Gauss-Seidel ones, -or more complex subspace-correction methods, such as the Schwarz ones. -The coarse-space correction consists of solving, in an appropriately chosen -coarse space, the residual equation associated with the approximate solution computed -by the smoother, and of using the solution of this equation to correct the -previous approximation. The transfer of information between the original -(fine) space and the coarse one is performed by using suitable restriction and -prolongation operators. The construction of the coarse space and the corresponding -transfer operators is carried out by applying a so-called coarsening algorithm to the system -matrix. Two main approaches can be used to perform coarsening: the geometric approach, -which exploits the knowledge of some physical grid associated with the matrix -and requires the user to define transfer operators from the fine -to the coarse level and vice versa, and the algebraic approach, which builds -the coarse-space correction and the associate transfer operators using only matrix -information. The first approach may be difficult when the system comes from -discretizations on complex geometries; -furthermore, ad hoc one-level smoothers may be required to get an efficient -interplay between fine and coarse levels, e.g., when matrices with highly varying coefficients -are considered. The second approach performs a fully automatic coarsening and enforces the -interplay between fine and coarse level by suitably choosing the coarse space and -the coarse-to-fine interpolation (see, e.g., [3,24,22] for details.) - -

-MLD2P4 uses a pure algebraic approach, based on the smoothed -aggregation algorithm [2,26], -for building the sequence of coarse matrices and transfer operators, -starting from the original one. -A decoupled version of this algorithm is implemented, where the smoothed -aggregation is applied locally to each submatrix [25]. -A brief description of the AMG preconditioners implemented in MLD2P4 is given in -Sections 4.1-4.3. For further details the reader -is referred to [4,5,7,8]. - -

-We note that optimal multigrid preconditioners do not necessarily correspond -to minimum execution times in a parallel setting. Indeed, to obtain effective parallel -multigrid preconditioners, a tradeoff between the optimality and the cost of building and -applying the smoothers and the coarse-space corrections must be achieved. Effective -parallel preconditioners require algorithmic scalability to be coupled with implementation -scalability, i.e., a computational cost per iteration which remains (almost) constant as -the number of parallel processors increases. - -

- -

- -Subsections - - - - -
- - -next - -up - -previous - -contents -
- Next: AMG preconditioners - Up: userhtml - Previous: Example and test programs -   Contents
- - - - diff --git a/docs/html/node13.html b/docs/html/node13.html deleted file mode 100644 index 26b49b23..00000000 --- a/docs/html/node13.html +++ /dev/null @@ -1,324 +0,0 @@ - - - - - -AMG preconditioners - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Smoothed Aggregation - Up: Multigrid Background - Previous: Multigrid Background -   Contents -
-
- - -

-
-AMG preconditioners -

-

-In order to describe the AMG preconditioners available in MLD2P4, we consider a -linear system - -
-

- - - - - - -
\begin{displaymath} -Ax=b, -\end{displaymath} -(2)
-

-where -$A=(a_{ij}) \in \mathbb{R}^{n \times n}$ is a nonsingular sparse matrix; -for ease of presentation we assume $A$ has a symmetric sparsity -pattern. - -

-Let us consider as finest index space the set of row (column) indices of $A$, i.e., - -$\Omega = \{1, 2, \ldots, n\}$. -Any algebraic multilevel preconditioners implemented in MLD2P4 generates -a hierarchy of index spaces and a corresponding hierarchy of matrices, - -

-
- - -\begin{displaymath}\Omega^1 \equiv \Omega \supset \Omega^2 \supset \ldots \supset \Omega^{nlev}, -\quad A^1 \equiv A, A^2, \ldots, A^{nlev}, \end{displaymath} -
-
-

-by using the information contained in $A$, without assuming any -knowledge of the geometry of the problem from which $A$ originates. -A vector space -$\mathbb{R}^{n_{k}}$ is associated with $\Omega^k$, -where $n_k$ is the size of $\Omega^k$. -For all $k < nlev$, a restriction operator and a prolongation one are built, -which connect two levels $k$ and $k+1$: - -

-
- - -\begin{displaymath} -P^k \in \mathbb{R}^{n_k \times n_{k+1}}, \quad -R^k \in \mathbb{R}^{n_{k+1}\times n_k}; -\end{displaymath} -
-
-

-the matrix $A^{k+1}$ is computed by using the previous operators according -to the Galerkin approach, i.e., - -

-
- - -\begin{displaymath} -A^{k+1}=R^kA^kP^k. -\end{displaymath} -
-
-

-In the current implementation of MLD2P4 we have $R^k=(P^k)^T$ -A smoother with iteration matrix $M^k$ is set up at each level $k < nlev$, and a solver -is set up at the coarsest level, so that they are ready for application -(for example, setting up a solver based on the $LU$ factorization means computing -and storing the $L$ and $U$ factors). The construction of the hierarchy of AMG components -described so far corresponds to the so-called build phase of the preconditioner. - -

- -

- - - -
Figure 1: -Application phase of a V-cycle preconditioner.
-
- -\framebox{ -\begin{minipage}{.85\textwidth} -\begin{tabbing} -\quad \=\quad \=\quad... -...[1mm] -\>endif \\ [1mm] -\>return $u^k$\ \\ [1mm] -end -\end{tabbing}\end{minipage}} - -
-
- -

-The components produced in the build phase may be combined in several ways -to obtain different multilevel preconditioners; -this is done in the application phase, i.e., in the computation of a vector -of type $w=B^{-1}v$, where $B$ denotes the preconditioner, usually within an iteration -of a Krylov solver [21]. An example of such a combination, known as -V-cycle, is given in Figure 1. In this case, a single iteration -of the same smoother is used before and after the the recursive call to the V-cycle (i.e., -in the pre-smoothing and post-smoothing phases); however, different choices can be -performed. Other cycles can be defined; in MLD2P4, we implemented the standard V-cycle -and W-cycle [3], and a version of the K-cycle described -in [20]. - -

- -

- - -next - -up - -previous - -contents -
- Next: Smoothed Aggregation - Up: Multigrid Background - Previous: Multigrid Background -   Contents
- - - - diff --git a/docs/html/node14.html b/docs/html/node14.html deleted file mode 100644 index e560ac94..00000000 --- a/docs/html/node14.html +++ /dev/null @@ -1,415 +0,0 @@ - - - - - -Smoothed Aggregation - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Smoothers and coarsest-level solvers - Up: Multigrid Background - Previous: AMG preconditioners -   Contents -
-
- - -

-
-Smoothed Aggregation -

-

-In order to define the prolongator $P^k$, used to compute -the coarse-level matrix $A^{k+1}$, MLD2P4 uses the smoothed aggregation -algorithm described in [2,26]. -The basic idea of this algorithm is to build a coarse set of indices -$\Omega^{k+1}$ by suitably grouping the indices of $\Omega^k$ into disjoint -subsets (aggregates), and to define the coarse-to-fine space transfer operator -$P^k$ by applying a suitable smoother to a simple piecewise constant -prolongation operator, with the aim of improving the quality of the coarse-space correction. - -

-Three main steps can be identified in the smoothed aggregation procedure: - -

    -
  1. aggregation of the indices of $\Omega^k$ to obtain $\Omega^{k+1}$; -
    2. -
  2. construction of the prolongator $P^k$; -
    3. -
  3. application of $P^k$ and $R^k=(P^k)^T$ to build $A^{k+1}$. -
    4. -
-

-In order to perform the coarsening step, the smoothed aggregation algorithm -described in [26] is used. In this algorithm, -each index -$j \in \Omega^{k+1}$ corresponds to an aggregate $\Omega^k_j$ of $\Omega^k$, -consisting of a suitably chosen index -$i \in \Omega^k$ and indices that are (usually) contained in a -strongly-coupled neighborood of $i$, i.e., - -
-

- - - - - - -
\begin{displaymath} -\Omega^k_j \subset \mathcal{N}_i^k(\theta) = -\left\{ r \i... -...vert a_{ii}^ka_{rr}^k\vert} \right \} \cup \left\{ i \right\}, -\end{displaymath} -(3)
-

-for a given threshold -$\theta \in [0,1]$ (see [26] for the details). -Since this algorithm has a sequential nature, a decoupled -version of it is applied, where each processor independently executes -the algorithm on the set of indices assigned to it in the initial data -distribution. This version is embarrassingly parallel, since it does not require any data -communication. On the other hand, it may produce some nonuniform aggregates -and is strongly dependent on the number of processors and on the initial partitioning -of the matrix $A$. Nevertheless, this parallel algorithm has been chosen for -MLD2P4, since it has been shown to produce good results in practice -[5,7,25]. - -

-The prolongator $P^k$ is built starting from a tentative prolongator - -$\bar{P}^k \in \mathbb{R}^{n_k \times n_{k+1}}$, defined as - -
-

- - - - - - -
\begin{displaymath} -\bar{P}^k =(\bar{p}_{ij}^k), \quad \bar{p}_{ij}^k = -\left\{... -...Omega^k_j, \\ -0 & \quad \mbox{otherwise}, -\end{array} \right. -\end{displaymath} -(4)
-

-where $\Omega^k_j$ is the aggregate of $\Omega^k$ -corresponding to the index -$j \in \Omega^{k+1}$. -$P^k$ is obtained by applying to $\bar{P}^k$ a smoother - -$S^k \in \mathbb{R}^{n_k \times n_k}$: - -

-
- - -\begin{displaymath} -P^k = S^k \bar{P}^k, -\end{displaymath} -
-
-

-in order to remove nonsmooth components from the range of the prolongator, -and hence to improve the convergence properties of the multilevel -method [2,24]. -A simple choice for $S^k$ is the damped Jacobi smoother: - -

-
- - -\begin{displaymath} -S^k = I - \omega^k (D^k)^{-1} A^k_F , -\end{displaymath} -
-
-

-where $D^k$ is the diagonal matrix with the same diagonal entries as $A^k$, - -$A^k_F = (\bar{a}_{ij}^k)$ is the filtered matrix defined as - -
-
- - - - - - -
\begin{displaymath} -\bar{a}_{ij}^k = -\left \{ \begin{array}{ll} -a_{ij}^k & \m... -...ii}^k = a_{ii}^k - \sum_{j \ne i} (a_{ij}^k - \bar{a}_{ij}^k), -\end{displaymath} -(5)
-

-and $\omega^k$ is an approximation of $4/(3\rho^k)$, where -$\rho^k$ is the spectral radius of -$(D^k)^{-1}A^k_F$ [2]. -In MLD2P4 this approximation is obtained by using -$\Vert A^k_F \Vert _\infty$ as an estimate -of $\rho^k$. Note that for systems coming from uniformly elliptic -problems, filtering the matrix $A^k$ has little or no effect, and -$A^k$ can be used instead of $A^k_F$. The latter choice is the default in MLD2P4. - -

- -

- - -next - -up - -previous - -contents -
- Next: Smoothers and coarsest-level solvers - Up: Multigrid Background - Previous: AMG preconditioners -   Contents
- - - - diff --git a/docs/html/node15.html b/docs/html/node15.html deleted file mode 100644 index f45480f8..00000000 --- a/docs/html/node15.html +++ /dev/null @@ -1,289 +0,0 @@ - - - - - -Smoothers and coarsest-level solvers - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Getting Started - Up: Multigrid Background - Previous: Smoothed Aggregation -   Contents -
-
- - -

-
-Smoothers and coarsest-level solvers -

-

-The smoothers implemented in MLD2P4 include the Jacobi and block-Jacobi methods, -a hybrid version of the forward and backward Gauss-Seidel methods, and the -additive Schwarz (AS) ones (see, e.g., [21,22]). - -

-The hybrid Gauss-Seidel -version is considered because the original Gauss-Seidel method is inherently sequential. -At each iteration of the hybrid version, each parallel process uses the most recent values -of its own local variables and the values of the non-local variables computed at the -previous iteration, obtained by exchanging data with other processes before -the beginning of the current iteration. - -

-In the AS methods, the index space $\Omega^k$ is divided into $m_k$ -subsets $\Omega^k_i$ of size $n_{k,i}$, possibly -overlapping. For each $i$ we consider the restriction -operator -$R_i^k \in \mathbb{R}^{n_{k,i} \times n_k}$ -that maps a vector $x^k$ to the vector $x_i^k$ made of the components of $x^k$ -with indices in $\Omega^k_i$, and the prolongation operator - -$P^k_i = (R_i^k)^T$. These operators are then used to build - -$A_i^k=R_i^kA^kP_i^k$, which is the restriction of $A^k$ to the index -space $\Omega^k_i$. -The classical AS preconditioner $M^k_{AS}$ is defined as - -

-
- - -\begin{displaymath} -( M^k_{AS} )^{-1} = \sum_{i=1}^{m_k} P_i^k (A_i^k)^{-1} R_i^{k}, -\end{displaymath} -
-
-

-where $A_i^k$ is supposed to be nonsingular. We observe that an approximate -inverse of $A_i^k$ is usually considered instead of $(A_i^k)^{-1}$. -The setup of $M^k_{AS}$ during the multilevel build phase -involves - - -The computation of -$z^k=M^k_{AS}w^k$, with -$w^k \in \mathbb{R}^{n_k}$, during the -multilevel application phase, requires - - -Variants of the classical AS method, which use modifications of the -restriction and prolongation operators, are also implemented in MLD2P4. -Among them, the Restricted AS (RAS) preconditioner usually -outperforms the classical AS preconditioner in terms of convergence -rate and of computation and communication time on parallel distributed-memory -computers, and is therefore the most widely used among the AS -preconditioners [6]. - -

-Direct solvers based on sparse LU factorizations, implemented in the -third-party libraries reported in Section 3.2, can be applied -as coarsest-level solvers by MLD2P4. Native inexact solvers based on -incomplete LU factorizations, as well as Jacobi, hybrid (forward) Gauss-Seidel, -and block Jacobi preconditioners are also available. Direct solvers usually -lead to more effective preconditioners in terms of algorithmic scalability; -however, this does not guarantee parallel efficiency. - -

- -

- - -next - -up - -previous - -contents -
- Next: Getting Started - Up: Multigrid Background - Previous: Smoothed Aggregation -   Contents
- - - - diff --git a/docs/html/node16.html b/docs/html/node16.html deleted file mode 100644 index f7334336..00000000 --- a/docs/html/node16.html +++ /dev/null @@ -1,237 +0,0 @@ - - - - - -Getting Started - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Examples - Up: userhtml - Previous: Smoothers and coarsest-level solvers -   Contents -
-
- - -

-
-Getting Started -

-

-We describe the basics for building and applying MLD2P4 one-level and multilevel -(i.e., AMG) preconditioners with the Krylov solvers included in PSBLAS [13]. -The following steps are required: - - -

    -
  1. Declare the preconditioner data structure. It is a derived data type, - mld_xprec_ type, where x may be s, d, c - or z, according to the basic data type of the sparse matrix - (s = real single precision; d = real double precision; - c = complex single precision; z = complex double precision). - This data structure is accessed by the user only through the MLD2P4 routines, - following an object-oriented approach. -
    2. -
  2. Allocate and initialize the preconditioner data structure, according to - a preconditioner type chosen by the user. This is performed by the routine - init, which also sets defaults for each preconditioner - type selected by the user. The preconditioner types and the defaults associated - with them are given in Table 1, where the strings used by - init to identify the preconditioner types are also given. - Note that these strings are valid also if uppercase letters are substituted by - corresponding lowercase ones. -
    3. -
  3. Modify the selected preconditioner type, by properly setting - preconditioner parameters. This is performed by the routine set. - This routine must be called only if the user wants to modify the default values - of the parameters associated with the selected preconditioner type, to obtain a variant - of that preconditioner. Examples of use of set are given in - Section 5.1; a complete list of all the - preconditioner parameters and their allowed and default values is provided in - Section 6, Tables 2-8. -
    4. -
  4. Build the preconditioner for a given matrix. If the selected preconditioner - is multilevel, then two steps must be performed, as specified next. -
    -
    4.1
    -
    Build the aggregation hierarchy for a given matrix. This is -performed by the routine hierarchy_build. -
    -
    4.2
    -
    Build the preconditioner for a given matrix. This is performed -by the routine smoothers_build. -
    -
    - If the selected preconditioner is one-level, it is built in a single step, -performed by the routine bld. -
    5. -
  5. Apply the preconditioner at each iteration of a Krylov solver. - This is performed by the method apply. When using the PSBLAS Krylov solvers, - this step is completely transparent to the user, since apply is called - by the PSBLAS routine implementing the Krylov solver (psb_krylov). -
    6. -
  6. Free the preconditioner data structure. This is performed by - the routine free. This step is complementary to step 1 and should - be performed when the preconditioner is no more used. -
    7. -
-

-All the previous routines are available as methods of the preconditioner object. -A detailed description of them is given in Section 6. -Examples showing the basic use of MLD2P4 are reported in Section 5.1. - -

- -

-
- - - -
Table 1: -Preconditioner types, corresponding strings and default choices. -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
TYPESTRINGDEFAULT PRECONDITIONER
No preconditioner'NONE'Considered to use the PSBLAS - Krylov solvers with no preconditioner.
Diagonal'DIAG' or 'JACOBI'Diagonal preconditioner. - For any zero diagonal entry of the matrix to be preconditioned, - the corresponding entry of the preconditioner is set to 1.
Gauss-Seidel'GS'Hybrid Gauss-Seidel (forward), that is, - global block Jacobi with - Gauss-Seidel as local solver.
Symmetrized Gauss-Seidel'FBGS'Symmetrized hybrid Gauss-Seidel,that is, - forward Gauss-Seidel followed by - backward Gauss-Seidel.
Block Jacobi'BJAC'Block-Jacobi with ILU(0) on the local blocks.
Additive Schwarz'AS'Additive Schwarz (AS), - with overlap 1 and ILU(0) on the local blocks.
Multilevel'ML'V-cycle with one hybrid forward Gauss-Seidel - (GS) sweep as pre-smoother and one hybrid backward - GS sweep as post-smoother, basic smoothed aggregation - as coarsening algorithm, and LU (plus triangular solve) - as coarsest-level solver. See the default values in - Tables 2-8 - for further details of the preconditioner.
- -
-

-
-

-Note that the module 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 psb_base_mod, for the sparse matrix and communication descriptor -data types, and psb_krylov_mod, for interfacing with the -Krylov solvers, must be also used (see Section 5.1). -
 -

-Remark 1. Coarsest-level solvers based on the LU factorization, -such as those implemented in UMFPACK, MUMPS, SuperLU, and SuperLU_Dist, -usually lead to smaller numbers of preconditioned Krylov -iterations than inexact solvers, when the linear system comes from -a standard discretization of basic scalar elliptic PDE problems. However, -this does not necessarily correspond to the smallest execution time -on parallel computers. - -

- -

- -Subsections - - - - -
- - -next - -up - -previous - -contents -
- Next: Examples - Up: userhtml - Previous: Smoothers and coarsest-level solvers -   Contents
- - - - diff --git a/docs/html/node17.html b/docs/html/node17.html deleted file mode 100644 index bb8015ed..00000000 --- a/docs/html/node17.html +++ /dev/null @@ -1,315 +0,0 @@ - - - - - -Examples - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: User Interface - Up: Getting Started - Previous: Getting Started -   Contents -
-
- - -

-
-Examples -

-

-The code reported in Figure 2 shows how to set and apply the default -multilevel preconditioner available in the real double precision version -of MLD2P4 (see Table 1). This preconditioner is chosen -by simply specifying 'ML' as the second argument of P%init -(a call to P%set is not needed) and is applied with the CG -solver provided by PSBLAS (the matrix of the system to be solved is -assumed to be positive definite). As previously observed, the modules -psb_base_mod, mld_prec_mod and 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 mld_dexample_ml.f90, -in the directory examples/fileread of the MLD2P4 implementation (see -Section 3.5). A sample test problem along with the relevant -input data is available in examples/fileread/runs. -For details on the use of the PSBLAS routines, see the PSBLAS User's -Guide [13]. - -

-The setup and application of the default multilevel preconditioner -for the real single precision and the complex, single and double -precision, versions are obtained with straightforward modifications of the previous -example (see Section 6 for details). If these versions are installed, -the corresponding codes are available in examples/fileread/. - -

- -

- - - -
Figure 2: -setup and application of the default multilevel preconditioner (example 1). -
-
-
- -
-
-  use psb_base_mod
-  use mld_prec_mod
-  use psb_krylov_mod
-... ...
-!
-! sparse matrix
-  type(psb_dspmat_type) :: A
-! sparse matrix descriptor
-  type(psb_desc_type)   :: desc_A
-! preconditioner
-  type(mld_dprec_type)  :: P
-! right-hand side and solution vectors
-  type(psb_d_vect_type) :: b, x
-... ...
-!
-! initialize the parallel environment
-  call psb_init(ictxt)
-  call psb_info(ictxt,iam,np)
-... ...
-!
-! read and assemble the spd matrix A and the right-hand side b 
-! using PSBLAS routines for sparse matrix / vector management
-... ...
-!
-! initialize the default multilevel preconditioner, i.e. V-cycle
-! with basic smoothed aggregation, 1 hybrid forward/backward
-! GS sweep as pre/post-smoother and UMFPACK as coarsest-level
-! solver
-  call P%init('ML',info)
-!
-! build the preconditioner
-  call P%hierarchy_build(A,desc_A,info)
-  call P%smoothers_build(A,desc_A,info)
-
-!
-! set the solver parameters and the initial guess
-  ... ...
-!
-! solve Ax=b with preconditioned CG
-  call psb_krylov('CG',A,P,b,x,tol,desc_A,info)
-  ... ...
-!
-! deallocate the preconditioner
-  call P%free(info)
-!
-! deallocate other data structures
-  ... ...
-!
-! exit the parallel environment
-  call psb_exit(ictxt)
-  stop
-
-
-
- -
-
- -

-Different versions of the multilevel preconditioner can be obtained by changing -the default values of the preconditioner parameters. The code reported in -Figure 3 shows how to set a V-cycle preconditioner -which applies 1 block-Jacobi sweep as pre- and post-smoother, -and solves the coarsest-level system with 8 block-Jacobi sweeps. -Note that the ILU(0) factorization (plus triangular solve) is used as -local solver for the block-Jacobi sweeps, since this is the default associated -with block-Jacobi and set by P%init. -Furthermore, specifying block-Jacobi as coarsest-level -solver implies that the coarsest-level matrix is distributed -among the processes. -Figure 4 shows how to set a W-cycle preconditioner which -applies 2 hybrid Gauss-Seidel sweeps as pre- and post-smoother, -and solves the coarsest-level system with the multifrontal LU factorization -implemented in MUMPS. It is specified that the coarsest-level -matrix is distributed, since MUMPS can be used on both -replicated and distributed matrices, and by default -it is used on replicated ones. -The code fragments shown in Figures 3 and 4 are -included in the example program file mld_dexample_ml.f90 too. - -

-Finally, Figure 5 shows the setup of a one-level -additive Schwarz preconditioner, i.e., RAS with overlap 2. -Note also that a Krylov method different from CG must be used to solve -the preconditioned system, since the preconditione in nonsymmetric. -The corresponding example program is available in the file -mld_dexample_1lev.f90. - -

-For all the previous preconditioners, example programs where the sparse matrix and -the right-hand side are generated by discretizing a PDE with Dirichlet -boundary conditions are also available in the directory examples/pdegen. - -

- -

- - - -
Figure 3: -setup of a multilevel preconditioner
-
-
- -
-
-... ...
-! build a V-cycle preconditioner with 1 block-Jacobi sweep (with 
-! ILU(0) on the blocks) as pre- and post-smoother, and 8  block-Jacobi
-! sweeps (with ILU(0) on the blocks) as coarsest-level solver
-  call P%init('ML',info)
-  call_P%set('SMOOTHER_TYPE','BJAC',info)
-  call P%set('COARSE_SOLVE','BJAC',info)
-  call P%set('COARSE_SWEEPS',8,info)
-  call P%hierarchy_build(A,desc_A,info)
-  call P%smoothers_build(A,desc_A,info)
-... ...
-
-
-
-
-

-

-
-
- -

- -

- - - -
Figure 4: -setup of a multilevel preconditioner
-
-
- -
-
-... ...
-! build a W-cycle preconditioner with 2 hybrid Gauss-Seidel sweeps
-! as pre- and post-smoother, a distributed coarsest
-! matrix, and MUMPS as coarsest-level solver
-  call P%init('ML',info)
-  call P%set('ML_CYCLE','WCYCLE',info)
-  call P%set('SMOOTHER_TYPE','FBGS',info)
-  call P%set('SMOOTHER_SWEEPS',2,info)
-  call P%set('COARSE_SOLVE','MUMPS',info)
-  call P%set('COARSE_MAT','DIST',info)
-  call P%hierarchy_build(A,desc_A,info)
-  call P%smoothers_build(A,desc_A,info)
-... ...
-
-
-
- -
-
- -

- -

- - - -
Figure 5: -setup of a one-level Schwarz preconditioner.
-
-
- -
-
-... ...
-! set RAS with overlap 2 and ILU(0) on the local blocks
-  call P%init('AS',info)
-  call P%set('SUB_OVR',2,info)
-  call P%bld(A,desc_A,info)
-... ...
-! solve Ax=b with preconditioned BiCGSTAB
-  call psb_krylov('BICGSTAB',A,P,b,x,tol,desc_A,info)
-
-
-
- -
-
- -

- -

- - -next - -up - -previous - -contents -
- Next: User Interface - Up: Getting Started - Previous: Getting Started -   Contents
- - - - diff --git a/docs/html/node18.html b/docs/html/node18.html deleted file mode 100644 index 82317e7a..00000000 --- a/docs/html/node18.html +++ /dev/null @@ -1,174 +0,0 @@ - - - - - -User Interface - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method init - Up: userhtml - Previous: Examples -   Contents -
-
- - -

-
-User Interface -

-

-The basic user interface of MLD2P4 consists of eight methods. The six -methods init, set, build, -hierarchy_build, smoothers_build and apply -encapsulate all the functionalities for the setup and the application -of any multilevel and one-level preconditioner implemented in the -package. -The method free deallocates the preconditioner data structure, while -descr prints a description of the preconditioner setup by the user. -For backward compatibility, methods are also accessible as -stand-alone subroutines. - -

-For each method, 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 method, -i.e., - -

-A description of each method is given in the remainder of this section. - -

- -

- -

- -Subsections - - - - -
- - -next - -up - -previous - -contents -
- Next: Method init - Up: userhtml - Previous: Examples -   Contents
- - - - diff --git a/docs/html/node19.html b/docs/html/node19.html deleted file mode 100644 index 9b821f2f..00000000 --- a/docs/html/node19.html +++ /dev/null @@ -1,138 +0,0 @@ - - - - - -Method init - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method set - Up: User Interface - Previous: User Interface -   Contents -
-
- - -

-
-Method init -

-

- -

call p%init(icontx,ptype,info) -
-

- -This method allocates and initializes the preconditioner -p, according to the preconditioner type chosen by the user. - -

-Arguments -

- -

- - - - - - - - - - - - - - - - - - - - - - -
-icontxt integer, intent(in).
- The communication context.
-ptype character(len=*), intent(in).
- The type of preconditioner. Its values are specified - in Table 1.
- Note that the strings are case insensitive.
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-

-For compatibility with the previous versions of MLD2P4, this method can be also invoked -as follows: - -

- -

call mld_precinit(p,ptype,info) -
-

- -

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- -next - -up - -previous - -contents -
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-
- - -

-
-Method set -

-

- -

call p%set(what,val,info [,ilev, ilmax, pos, idx]) -
-

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

-Arguments -

- -

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-what character(len=*).
- The parameter to be set. It can be specified through its name; - the string is case-insensitive. See - Tables 2-8.
-val integer or character(len=*) or - real(psb_spk_) or real(psb_dpk_), - intent(in).
- The value of the parameter to be set. The list of allowed - values and the corresponding data types is given in - Tables 2-8. - When the value is of type character(len=*), - it is also treated as case insensitive.
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 - for details.
-ilev 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 ilev is not present, the parameter identified by what - is set at all the appropriate levels (see - Tables 2-8).
-ilmax integer, optional, intent(in).
- For the multilevel preconditioner, when both - ilev and ilmax are present, the settings - are applied at all levels ilev:ilmax. When - ilev is present but ilmax is not, then - the default is ilmax=ilev. - The levels are numbered in increasing - order starting from the finest one, i.e., level 1 is the finest level.
-pos charater(len=*), optional, intent(in).
- Whether the other arguments apply only to the pre-smoother ('PRE') - or to the post-smoother ('POST'). If pos is not present, - the other arguments are applied to both smoothers. - If the preconditioner is one-level or the parameter identified by what - does not concern the smoothers, pos is ignored.
-idx integer, optional, intent(in).
- An auxiliary input argument that can be passed to the - underlying objects. -
-

-For compatibility with the previous versions of MLD2P4, this method can be also invoked -as follows: - -

- -

call mld_precset(p,what,val,info) -
-

- -However, in this case the optional arguments ilev, -ilmax, pos and idx -cannot be used. -
 -

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

    -
  1. the type of multilevel cycle and how many cycles must be applied; -
    2. -
  2. the aggregation algorithm; -
    3. -
  3. the coarse-space correction at the coarsest level (for multilevel - preconditioners only); -
    4. -
  4. the smoother of the multilevel preconditioners, or the one-level - preconditioner. - -

    -

    5. -
-A list of the parameters that can be set, along with their allowed and -default values, is given in Tables 2-8. -For a description of the meaning of the parameters, please -refer also to Section 4. -
 -

-Remark 2. A smoother is usually obtained by combining two objects: -a smoother (SMOOTHER_TYPE) and a local solver (SUB_SOLVE), -as specified in Tables 7-8. -For example, the block-Jacobi smoother using -ILU(0) on the blocks is obtained by combining the block-Jacobi smoother -object with the ILU(0) solver object. Similarly, -the hybrid Gauss-Seidel smoother (see Note in Table 7) -is obtained by combining the block-Jacobi smoother object with a single sweep -of the Gauss-Seidel solver object, while the point-Jacobi smoother is the -result of combining the block-Jacobi smoother object with a single sweep -of the pointwise-Jacobi solver object. However, for simplicity, shortcuts are -provided to set point-Jacobi, hybrid (forward) Gauss-Seidel, and -hybrid backward Gauss-Seidel, i.e., the previous smoothers can be defined -by setting only SMOOTHER_TYPE to appropriate values (see -Tables 7), i.e., without setting -SUB_SOLVE too. - -

-The smoother and solver objects are arranged in a -hierarchical manner. When specifying a smoother object, its parameters, -including the local solver, are set to their default values, and when a solver -object is specified, its defaults are also set, overriding in both -cases any previous settings even if explicitly specified. Therefore if -the user sets a smoother, and wishes to use a solver -different from the default one, the call to set the solver must come -after the call to set the smoother. - -

-Similar considerations apply to the point-Jacobi, Gauss-Seidel and block-Jacobi -coarsest-level solvers, and shortcuts are available -in this case too (see Table 5). -
 -

-Remark 3. In general, a coarsest-level solver cannot be used with -both the replicated and distributed coarsest-matrix layout; -therefore, setting the solver after the layout may change the layout. -Similarly, setting the layout after the solver may change the solver. - -

-More precisely, UMFPACK and SuperLU require the coarsest-level -matrix to be replicated, while SuperLU_Dist requires it to be distributed. -In these cases, setting the coarsest-level solver implies that -the layout is redefined according to the solver, ovverriding any -previous settings. MUMPS, point-Jacobi, -hybrid Gauss-Seidel and block-Jacobi can be applied to -replicated and distributed matrices, thus their choice -does not modify any previously specified layout. -It is worth noting that, when the matrix is replicated, -the point-Jacobi, hybrid Gauss-Seidel and block-Jacobi solvers -reduce to the corresponding local solver objects (see Remark 2). -For the point-Jacobi and Gauss-Seidel solvers, these objects -correspond to a single point-Jacobi sweep and a single -Gauss-Seidel sweep, respectively, which are very poor solvers. - -

-On the other hand, the distributed layout can be used with any solver -but UMFPACK and SuperLU; therefore, if any of these two solvers has already -been selected, the coarsest-level solver is changed to block-Jacobi, -with the previously chosen solver applied to the local blocks. -Likewise, the replicated layout can be used with any solver but SuperLu_Dist; -therefore, if SuperLu_Dist has been previously set, the coarsest-level -solver is changed to the default sequential solver. - -

-Remark 4. The argument idx can be used to allow finer -control for those solvers; for instance, by specifying the keyword -MUMPS_IPAR_ENTRY and an appropriate value for idx, it is -possible to set any entry in the MUMPS integer control array. -See also Sec. 7. - -

- -

-
- - - -
Table 2: -Parameters defining the multilevel cycle and the number of cycles to -be applied. -
-
- - - - - - - - - - - - - - - - - - - -
whatDATA TYPEvalDEFAULTCOMMENTS
'ML_CYCLE'character(len=*)'VCYCLE' -

-'WCYCLE' -

-'KCYCLE' -

-'MULT' -

-'ADD'

'VCYCLE'Multilevel cycle: V-cycle, W-cycle, K-cycle, hybrid Multiplicative Schwarz, - and Additive Schwarz. -

-Note that hybrid Multiplicative Schwarz is equivalent to V-cycle and - is included for compatibility with previous versions of MLD2P4.

'OUTER_SWEEPS'integerAny integer -

-number $\ge 1$

1Number of multilevel cycles.
-
-
-

-
-

- -

-
- - - -
Table 3: -Parameters defining the aggregation algorithm. -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
whatDATA TYPEvalDEFAULTCOMMENTS
'MIN_COARSE_SIZE'integerAny number -

-$> 0$

 -$\lfloor 40 \sqrt[3]{n} \rfloor$, where $n$ is the dimension - of the matrix at the finest levelCoarse size threshold. The aggregation stops - if the global number of variables of the - computed coarsest matrix - is lower than or equal to this threshold - (see Note).
'MIN_CR_RATIO'realAny number -

-$> 1$

1.5Minimum coarsening ratio. The aggregation stops - if the ratio between the matrix dimensions - at two consecutive levels is lower than or equal to this - threshold (see Note).
'MAX_LEVS'integerAny integer -

-number $> 1$

20Maximum number of levels. The aggregation stops - if the number of levels reaches this value (see Note).
'PAR_AGGR_ALG'character(len=*)'DEC', 'SYMDEC''DEC'Parallel aggregation algorithm. -

-Currently, only the - decoupled aggregation (DEC) is available; the - SYMDEC option applies decoupled - aggregation to the sparsity pattern - of $A+A^T$.

'AGGR_TYPE'character(len=*)'SOC1''SOC1', - 'SOC2'Type of aggregation algorithm: currently, - we implement to measures of strength of - connection, the one by Vanek, Mandel - and Brezina [26], - and the one by Gratton et al [16].
'AGGR_PROL'character(len=*)'SMOOTHED', 'UNSMOOTHED''SMOOTHED'Prolongator used by the aggregation algorithm: smoothed or unsmoothed - (i.e., tentative prolongator).
Note. The aggregation algorithm stops when -at least one of the following criteria is met: -the coarse size threshold, the
minimum coarsening ratio, or the maximum number -of levels is reached. Therefore, the actual number of levels may be
smaller than the specified maximum number -of levels.
-
-
-

-
-

- -

-
- - - -
Table 4: -Parameters defining the aggregation algorithm (continued). -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
whatDATA TYPEvalDEFAULTCOMMENTS
'AGGR_ORD'character(len=*)'NATURAL' -

-'DEGREE'

'NATURAL'Initial ordering of indices for the aggregation - algorithm: either natural ordering or sorted by - descending degrees of the nodes in the - matrix graph.
'AGGR_THRESH'real(kind_parameter)Any real -

-number $\in [0, 1]$

0.01The threshold $\theta$ in the aggregation algorithm, - see (3) in Section 4.2. - See also the note at the bottom of this table.
'AGGR_FILTER'character(len=*)'FILTER' -

-'NOFILTER'

'NOFILTER'Matrix used in computing the smoothed - prolongator: filtered or unfiltered (see (5) in Section 4.2).
Note. Different thresholds at different levels, such as -those used in [26, Section 5.1], can be easily set by -invoking the rou-
tine set with -the parameter ilev.
-
-
-

-
-

- -

-
- - - -
Table 5: -Parameters defining the coarse-space correction at the coarsest -level.
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
whatDATA TYPEvalDEFAULTCOMMENTS
'COARSE_MAT'character(len=*)'DIST' -

-'REPL'

'REPL'Coarsest matrix layout: distributed among the processes or - replicated on each of them.
'COARSE_SOLVE'character(len=*)'MUMPS' -

-'UMF' -

-'SLU' -

-'SLUDIST' -

-'JACOBI' -

-'GS' -

-'BJAC'

See Note.Solver used at the coarsest level: sequential - LU from MUMPS, UMFPACK, or SuperLU - (plus triangular solve); - distributed LU from MUMPS or SuperLU_Dist - (plus triangular solve); - point-Jacobi, hybrid Gauss-Seidel or block-Jacobi. -

-Note that UMF and SLU require the coarsest - matrix to be replicated, SLUDIST, JACOBI, - GS and BJAC require it to be - distributed, and MUMPS can be used with either - a replicated or a distributed matrix. When any of the previous - solvers is specified, the matrix layout is set to a default - value which allows the use of the solver (see Remark 3, p. 24). - Note also that UMFPACK and SuperLU_Dist - are available only in double precision.

'COARSE_SUBSOLVE'character(len=*)'ILU' -

-'ILUT' -

-'MILU' -

-'MUMPS' -

-'SLU' -

-'UMF'

See Note.Solver for the diagonal blocks of the coarse matrix, - in case the block Jacobi solver - is chosen as coarsest-level solver: ILU($p$), ILU($p,t$), - MILU($p$), LU from MUMPS, SuperLU or UMFPACK - (plus triangular solve). - Note that UMFPACK and SuperLU_Dist - are available only in double precision.
Note. Defaults for COARSE_SOLVE and -COARSE_SUBSOLVE are chosen in the following order:
single precision version - MUMPS if installed, - then SLU if installed, - ILU otherwise;
double precision version - UMF if installed, - then MUMPS if installed, then SLU if - installed, ILU otherwise.
-
-
-

-
-

- -

-
- - - -
Table 6: -Parameters defining the coarse-space correction at the coarsest -level (continued).
-
- - - - - - - - - - - - - - - - - - - - - - - - - -
whatDATA TYPEvalDEFAULTCOMMENTS
'COARSE_SWEEPS'integerAny integer -

-number $> 0$

10Number of sweeps when JACOBI, GS or BJAC - is chosen as coarsest-level solver.
'COARSE_FILLIN'integerAny integer -

-number $\ge 0$

0Fill-in level $p$ of the ILU factorizations.
'COARSE_ILUTHRS'real(kind_parameter)Any real -

-number $\ge 0$

0Drop tolerance $t$ in the ILU($p,t$) factorization.
-
-
-

-
-

- -

-
- - - -
Table 7: -Parameters defining the smoother or the details of the one-level preconditioner. -
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-what DATA TYPE val DEFAULT -COMMENTS
-'SMOOTHER_TYPE' character(len=*) - 'JACOBI' -

-'GS' -

-'BGS' -

-'BJAC' - -

-'AS' -

'FBGS' - Type of smoother used in the multilevel preconditioner: - point-Jacobi, hybrid (forward) Gauss-Seidel, - hybrid backward Gauss-Seidel, block-Jacobi, and - Additive Schwarz. -

-It is ignored by one-level preconditioners.

-'SUB_SOLVE' character(len=*) - 'JACOBI' -

-'GS' -

-'BGS' -

-'ILU' -

-'ILUT' -

-'MILU' -

-'MUMPS' -

-'SLU' -

-'UMF' -

GS and BGS for pre- and post-smoothers - of multilevel preconditioners, respectively -

-ILU for block-Jacobi and Additive Schwarz - one-level preconditioners -

The local solver to be used with the smoother or one-level - preconditioner (see Remark 2, page 24): point-Jacobi, - hybrid (forward) Gauss-Seidel, hybrid backward - Gauss-Seidel, ILU($p$), ILU($p,t$), MILU($p$), - LU from MUMPS, SuperLU or UMFPACK - (plus triangular solve). See Note for details on hybrid - Gauss-Seidel.
-'SMOOTHER_SWEEPS' integer - Any integer -

-number $\ge 0$ -

1 - Number of sweeps of the smoother or one-level preconditioner. - In the multilevel case, no pre-smother or - post-smoother is used if this parameter is set to 0 - together with pos='PRE' or pos='POST, - respectively.
-'SUB_OVR' integer - Any integer -

-number $\ge 0$ -

1 - Number of overlap layers, for Additive Schwarz only.
-
-

-
-

- -

-
- - - -
Table 8: -Parameters defining the smoother or the details of the one-level preconditioner -(continued).
-
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-what DATA TYPE val DEFAULT -COMMENTS
-'SUB_RESTR' character(len=*) - 'HALO' -

-'NONE' -

'HALO' - Type of restriction operator, for Additive Schwarz only: - HALO for taking into account the overlap, NONE - for neglecting it. -

-Note that HALO must be chosen for - the classical Addditive Schwarz smoother and its RAS variant.

-'SUB_PROL' character(len=*) - 'SUM' -

-'NONE' -

'NONE' - Type of prolongation operator, for Additive Schwarz only: - SUM for adding the contributions from the overlap, NONE - for neglecting them. -

-Note that SUM must be chosen for the classical Additive - Schwarz smoother, and NONE for its RAS variant.

-'SUB_FILLIN' integer - Any integer -

-number $\ge 0$ -

0 - Fill-in level $p$ of the incomplete LU factorizations.
-'SUB_ILUTHRS' real(kind_parameter) - Any real number $\ge 0$ - 0 - Drop tolerance $t$ in the ILU($p,t$) factorization.
'MUMPS_LOC_GLOB' character(len=*) - LOCAL_SOLVER' -

-GLOBAL_SOLVER' -

GLOBAL_SOLVER' - Whether MUMPS should be used as a - distributed solver, or as a serial solver - acting only on the part of the matrix local - to each process.
'MUMPS_IPAR_ENTRY' integer - Any integer number - 0 - Set an entry in the MUMPS integer control array, as - chosen via the idx optional argument.
'MUMPS_RPAR_ENTRY' real - Any real number - 0 - Set an entry in the MUMPS real control array, as - chosen via the idx optional argument.
-
-

-
-

- -

- -

- - -next - -up - -previous - -contents -
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-
- - -

-
-Method hierarchy_build -

-

- -

call p%hierarchy_build(a,desc_a,info) -
-

- -This method builds the hierarchy of matrices and restriction/prolongation -operators for the multilevel preconditioner p, according to the requirements -made by the user through the methods init and set. - -

-Arguments -

- -

- - - - - - - - - - - - - - - - - - - -
-a type(psb_xspmat_type), intent(in).
- The sparse matrix structure containing the local part of the - matrix to be preconditioned. Note that 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 [13].
-desc_a type(psb_desc_type), intent(in).
- The communication descriptor of a. See the PSBLAS User's Guide for - details [13].
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-

- -

- -

- - -next - -up - -previous - -contents -
- Next: Method smoothers_build - Up: User Interface - Previous: Method set -   Contents
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-
- - -

-
-Method smoothers_build -

-

- -

call p%smoothers_build(a,desc_a,p,info[,amold,vmold,imold]) -
-

- -This method builds the smoothers and the coarsest-level solvers for the -multilevel preconditioner p, according to the requirements made by -the user through the methods init and set, and based on the aggregation -hierarchy produced by a previous call to hierarchy_build -(see Section 6.3). - -

-Arguments -

- -

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-a type(psb_xspmat_type), intent(in).
- The sparse matrix structure containing the local part of the - matrix to be preconditioned. Note that 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 [13].
-desc_a type(psb_desc_type), intent(in).
- The communication descriptor of a. See the PSBLAS User's Guide for - details [13].
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-amold class(psb_x_base_sparse_mat), intent(in), optional.
- The desired dynamic type for internal matrix - components; this allows e.g. running on GPUs; it needs not be the - same on all processes. See the PSBLAS User's Guide for - details [13].
- vmold class(psb_x_base_vect_type), intent(in), optional.
- The desired dynamic type for internal vector - components; this allows e.g. running on GPUs.
- imold class(psb_i_base_vect_type), intent(in), optional.
- The desired dynamic type for internal integer vector - components; this allows e.g. running on GPUs.
-

- -

- -

- - -next - -up - -previous - -contents -
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-
- - -

-
-Method build -

-

- -

call p%build(a,desc_a,info[,amold,vmold,imold]) -
-

- -This method builds the preconditioner p according to the requirements -made by the user through the methods init and set -(see Sections 6.3 and 6.4 for -multilevel preconditioners). It is mostly provided for backward -compatibility; indeed, it is internally implemented by invoking the -two previous methods hierarchy_build and -smoothers_build, whose nomenclature would however be somewhat -unnatural when dealing with simple one-level preconditioners. - -

-Arguments -

- -

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-a type(psb_xspmat_type), intent(in).
- The sparse matrix structure containing the local part of the - matrix to be preconditioned. Note that 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 [13].
-desc_a type(psb_desc_type), intent(in).
- The communication descriptor of a. See the PSBLAS User's Guide for - details [13].
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-amold class(psb_x_base_sparse_mat), intent(in), optional.
- The desired dynamic type for internal matrix - components; this allows e.g. running on GPUs; it needs not be the - same on all processes. See the PSBLAS User's Guide for - details [13].
- vmold class(psb_x_base_vect_type), intent(in), optional.
- The desired dynamic type for internal vector - components; this allows e.g. running on GPUs.
- imold class(psb_i_base_vect_type), intent(in), optional.
- The desired dynamic type for internal integer vector - components; this allows e.g. running on GPUs.
-

-For compatibility with the previous versions of MLD2P4, this method can be also invoked -as follows: - -

- -

call mld_precbld(p,what,val,info[,amold,vmold,imold]) -
-

- -The method can be used to build multilevel preconditioners too. - -

- -

- - -next - -up - -previous - -contents -
- Next: Method apply - Up: User Interface - Previous: Method smoothers_build -   Contents
- - - - diff --git a/docs/html/node24.html b/docs/html/node24.html deleted file mode 100644 index 447807ca..00000000 --- a/docs/html/node24.html +++ /dev/null @@ -1,215 +0,0 @@ - - - - - -Method apply - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method free - Up: User Interface - Previous: Method build -   Contents -
-
- - -

-
-Method apply -

-

- -

call p%apply(x,y,desc_a,info [,trans,work]) -
-

- -This method computes -$y = op(B^{-1})\, x$, where $B$ is a previously built -preconditioner, stored into p, and $op$ -denotes the preconditioner itself or its transpose, according to -the value of trans. -Note that, when MLD2P4 is used with a Krylov solver from PSBLAS, -p%apply is called within the PSBLAS method psb_krylov -and hence it is completely transparent to the user. - -

-Arguments -

- -

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
-x type(kind_parameter), dimension(:), intent(in).
- The local part of the vector $x$. Note that type and - kind_parameter must be chosen according - to the real/complex, single/double precision version of MLD2P4 under use.
-y type(kind_parameter), dimension(:), intent(out).
- The local part of the vector $y$. Note that type and - kind_parameter must be chosen according - to the real/complex, single/double precision version of MLD2P4 under use.
-desc_a type(psb_desc_type), intent(in).
- The communication descriptor associated to the matrix to be - preconditioned.
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-trans character(len=1), optional, intent(in).
- If trans = 'N','n' then -$op(B^{-1}) = B^{-1}$; - if trans = 'T','t' then -$op(B^{-1}) = B^{-T}$ - (transpose of $B^{-1})$; if trans = 'C','c' then -$op(B^{-1}) = B^{-C}$ - (conjugate transpose of $B^{-1})$.
-work type(kind_parameter), dimension(:), optional, target.
- Workspace. Its size should be at - least 4 * psb_cd_get_local_ cols(desc_a) (see the PSBLAS User's Guide). - Note that type and kind_parameter must be chosen according - to the real/complex, single/double precision version of MLD2P4 under use.
-

-For compatibility with the previous versions of MLD2P4, this method can be also invoked -as follows: - -

- -

call mld_precaply(p,what,val,info) -
-

- -

- -

- - -next - -up - -previous - -contents -
- Next: Method free - Up: User Interface - Previous: Method build -   Contents
- - - - diff --git a/docs/html/node25.html b/docs/html/node25.html deleted file mode 100644 index 23211355..00000000 --- a/docs/html/node25.html +++ /dev/null @@ -1,93 +0,0 @@ - - - - - -Method free - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method descr - Up: User Interface - Previous: Method apply -   Contents -
-
- - -

-
-Method free -

-

- -

call p%free(p,info) -
-

- -This method deallocates the preconditioner data structure p. - -

-Arguments -

- -

- - - - - - - -
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-

-For compatibility with the previous versions of MLD2P4, this method can be also invoked -as follows: - -

- -

call mld_precfree(p,info) -
-

- -

- -

- - - diff --git a/docs/html/node26.html b/docs/html/node26.html deleted file mode 100644 index f07bcf9f..00000000 --- a/docs/html/node26.html +++ /dev/null @@ -1,125 +0,0 @@ - - - - - -Method descr - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Auxiliary Methods - Up: User Interface - Previous: Method free -   Contents -
-
- - -

-
-Method descr -

-

- -

call p%descr(info, [iout]) -
-

- -This method prints a description of the preconditioner p to the standard output or -to a file. It must be called after hierachy_build and smoothers_build, -or build, have been called. - -

-Arguments -

- -

- - - - - - - - - - - - - -
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-iout integer, intent(in), optional.
- The id of the file where the preconditioner description - will be printed; the default is the standard output.
-

-For compatibility with the previous versions of MLD2P4, this method can be also invoked -as follows: - -

- -

call mld_precdescr(p,info [,iout]) -
-

- -

- - -next - -up - -previous - -contents -
- Next: Auxiliary Methods - Up: User Interface - Previous: Method free -   Contents
- - - - diff --git a/docs/html/node27.html b/docs/html/node27.html deleted file mode 100644 index 64b9a5db..00000000 --- a/docs/html/node27.html +++ /dev/null @@ -1,79 +0,0 @@ - - - - - -Auxiliary Methods - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method: dump - Up: User Interface - Previous: Method descr -   Contents -
-
- - -

-
-Auxiliary Methods -

-Various functionalities are implemented as additional methods of the -preconditioner object. - -

- -

- -Subsections - - - -
- - - diff --git a/docs/html/node28.html b/docs/html/node28.html deleted file mode 100644 index 813e8e25..00000000 --- a/docs/html/node28.html +++ /dev/null @@ -1,94 +0,0 @@ - - - - - -Method: dump - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method: clone - Up: Auxiliary Methods - Previous: Auxiliary Methods -   Contents -
-
- - -

-Method: dump -

-

- -

call p%dump(info[,istart,iend,prefix,head,ac,rp,smoother,solver,global_num]) -
-

- -Dump on file. - -

-Arguments -

- -

- - - - - - - - - - - - - -
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-amold class(psb_x_base_sparse_mat), intent(in), optional.
- The desired dynamic type for internal matrix - components; this allows e.g. running on GPUs; it needs not be the - same on all processes. See the PSBLAS User's Guide for - details [13].
-

- -

- - - diff --git a/docs/html/node29.html b/docs/html/node29.html deleted file mode 100644 index da717d1c..00000000 --- a/docs/html/node29.html +++ /dev/null @@ -1,92 +0,0 @@ - - - - - -Method: clone - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method: sizeof - Up: Auxiliary Methods - Previous: Method: dump -   Contents -
-
- - -

-Method: clone -

-

- -

call p%clone(pout,info) -
-

- -Create a (deep) copy of the preconditioner object. - -

-Arguments -

- -

- - - - - - - - - - - - - -
-pout type(mld_xprec_type), intent(out).
- The copy of the preconditioner data structure. Note - that x must be chosen according - to the real/complex, single/double precision version of MLD2P4 under use.
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-

- -

- - - diff --git a/docs/html/node3.html b/docs/html/node3.html deleted file mode 100644 index b7f7bd1d..00000000 --- a/docs/html/node3.html +++ /dev/null @@ -1,208 +0,0 @@ - - - - - -General Overview - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Code Distribution - Up: userhtml - Previous: Contents -   Contents -
-
- - -

-
-General Overview -

-

-The MULTILEVEL DOMAIN DECOMPOSITION PARALLEL PRECONDITIONERS PACKAGE BASED ON -PSBLAS (MLD2P4) provides parallel Algebraic MultiGrid (AMG) and Domain -Decomposition preconditioners (see, e.g., [3,24,22]), -to be used in the iterative solution of linear systems, - -
-

- - - - - - -
\begin{displaymath} -Ax=b, -\end{displaymath} -(1)
-

-where $A$ is a square, real or complex, sparse matrix. -The name of the package comes from its original implementation, containing -multilevel additive and hybrid Schwarz preconditioners, as well as one-level additive -Schwarz preconditioners. The current version extends the original plan by including -multilevel cycles and smoothers widely used in multigrid methods. - -

-The multilevel preconditioners implemented in MLD2P4 are obtained by combining -AMG cycles with smoothers and coarsest-level solvers. The V-, W-, and -K-cycles [3,20] are available, which allow to define -almost all the preconditioners in the package, including the multilevel hybrid -Schwarz ones; a specific cycle is implemented to obtain multilevel additive -Schwarz preconditioners. The Jacobi, hybrid -forward/backward Gauss-Seidel, block-Jacobi, and additive Schwarz methods -are available as smoothers. An algebraic approach is used to generate a hierarchy of -coarse-level matrices and operators, without explicitly using any information on the -geometry of the original problem, e.g., the discretization of a PDE. To this end, -the smoothed aggregation technique [2,26] -is applied. Either exact or approximate solvers can be used on the coarsest-level -system. Specifically, different sparse LU factorizations from external -packages, and native incomplete LU factorizations and Jacobi, hybrid Gauss-Seidel, -and block-Jacobi solvers are available. All smoothers can be also exploited as one-level -preconditioners. - -

-MLD2P4 is written in Fortran 2003, following an -object-oriented design through the exploitation of features -such as abstract data type creation, type extension, functional overloading, and -dynamic memory management. The parallel implementation is based on a Single Program Multiple Data -(SPMD) paradigm. Single and -double precision implementations of MLD2P4 are available for both the -real and the complex case, which 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 PSBLAS (Parallel Sparse BLAS) -computational framework [15,14]. PSBLAS provides basic linear algebra -operators and data management facilities for distributed sparse matrices, -as well as parallel Krylov solvers which can be used with the MLD2P4 preconditioners. -The choice of PSBLAS has been mainly motivated by the need of having -a portable and efficient software infrastructure implementing “de facto” standard -parallel sparse linear algebra kernels, to pursue goals such as performance, -portability, modularity ed extensibility in the development of the preconditioner -package. On the other hand, the implementation of MLD2P4 has led to some -revisions and extentions of the original PSBLAS kernels. -The inter-process comunication required by MLD2P4 is encapsulated -in the PSBLAS routines; -therefore, MLD2P4 can be run on any parallel machine where PSBLAS -implementations are available. - -

-MLD2P4 has a layered and modular software architecture where three main layers can be -identified. The lower layer consists of the PSBLAS kernels, the middle one implements -the construction and application phases of the preconditioners, and the upper one -provides a uniform interface to all the preconditioners. -This architecture allows for different levels of use of the package: -few black-box routines at the upper layer allow all users to easily -build and apply any preconditioner available in MLD2P4; -facilities are also available allowing expert users to extend the set of smoothers -and solvers for building new versions of the preconditioners (see -Section 7). - -

-We note that the user interface of MLD2P4 2.1 has been extended with respect to the -previous versions in order to separate the construction of the multilevel hierarchy from -the construction of the smoothers and solvers, and to allow for more flexibility -at each level. The software architecture described in [8] has significantly -evolved too, in order to fully exploit the Fortran 2003 features implemented in PSBLAS 3. -However, compatibility with previous versions has been preserved. - -

-This guide is organized as follows. General information on the distribution of the source -code is reported in Section 2, while details on the configuration -and installation of the package are given in Section 3. A short description -of the preconditioners implemented in MLD2P4 is provided in Section 4, -to help the users in choosing among them. The basics for building and applying the -preconditioners with the Krylov solvers implemented in PSBLAS are reported -in Section 5, where the Fortran codes of a few sample programs -are also shown. A reference guide for the user interface routines is provided -in Section 6. Information on the extension of the package -through the addition of new smoothers and solvers is reported in Section 7. -The error handling mechanism used by the package -is briefly described in Section 8. The copyright terms concerning the -distribution and modification of MLD2P4 are reported in Appendix A. - -

- -

- - -next - -up - -previous - -contents -
- Next: Code Distribution - Up: userhtml - Previous: Contents -   Contents
- - - - diff --git a/docs/html/node30.html b/docs/html/node30.html deleted file mode 100644 index 873b2304..00000000 --- a/docs/html/node30.html +++ /dev/null @@ -1,67 +0,0 @@ - - - - - -Method: sizeof - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method: allocate_wrk - Up: Auxiliary Methods - Previous: Method: clone -   Contents -
-
- - -

-Method: sizeof -

-

- -

sz = p%sizeof() -
-

- -Return memory footprint in bytes. - -

- -

- - - diff --git a/docs/html/node31.html b/docs/html/node31.html deleted file mode 100644 index 1243f28c..00000000 --- a/docs/html/node31.html +++ /dev/null @@ -1,127 +0,0 @@ - - - - - -Method: allocate_wrk - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Method: free_wrk - Up: Auxiliary Methods - Previous: Method: sizeof -   Contents -
-
- - -

-Method: allocate_wrk -

-

- -

call p%allocate_wrk(info[, vmold]) -
-

- -Allocate internal work vectors. Each application of the preconditioner -uses a number of work vectors which are allocated internally as -necessary; therefore allocation and deallocation of memory occurs -multiple times during the execution of a Krylov method. In most cases -this strategy is perfectly acceptable, but -on some platforms, most notably GPUs, memory allocation is -a slow operation, and the default behaviour would lead to a -slowdown. This method allows to trade space for time by preallocating -the internal workspace outside of the invocation of a Krylov -method. When using GPUs or other specialized devices, the vmold -argument is also necessary to ensure the internal work vectors are of -the appropriate dynamic type to exploit the accelerator hardware; when -allocation occurs internally this is taken care of based on the dynamic -type of the x argument to the apply method. - -

-Arguments -

- -

- - - - - - - - - - - - - -
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
- vmold class(psb_x_base_vect_type), intent(in), optional.
- The desired dynamic type for internal vector - components; this allows e.g. running on GPUs.
-

- -

- - -next - -up - -previous - -contents -
- Next: Method: free_wrk - Up: Auxiliary Methods - Previous: Method: sizeof -   Contents
- - - - diff --git a/docs/html/node32.html b/docs/html/node32.html deleted file mode 100644 index 5805fd18..00000000 --- a/docs/html/node32.html +++ /dev/null @@ -1,85 +0,0 @@ - - - - - -Method: free_wrk - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Adding new smoother and - Up: Auxiliary Methods - Previous: Method: allocate_wrk -   Contents -
-
- - -

-Method: free_wrk -

-

- -

call p%free_wrk(info) -
-

- -Deallocate internal work vectors. - -

-Arguments -

- -

- - - - - - - -
-info integer, intent(out).
- Error code. If no error, 0 is returned. See Section 8 for details.
-

- -

- -

- -

- - - diff --git a/docs/html/node33.html b/docs/html/node33.html deleted file mode 100644 index c6b77a4c..00000000 --- a/docs/html/node33.html +++ /dev/null @@ -1,186 +0,0 @@ - - - - - -Adding new smoother and solver objects to MLD2P4 - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Error Handling - Up: userhtml - Previous: Method: free_wrk -   Contents -
-
- - -

-
-Adding new smoother and solver objects to MLD2P4 -

-

-Developers can add completely new smoother and/or solver classes -derived from the base objects in the library (see Remark 2 in Section 6.2), -without recompiling the library itself. - -

-To do so, it is necessary first to select the base type to be extended. -In our experience, it is quite likely that the new application needs -only the definition of a “solver” object, which is almost -always acting only on the local part of the distributed matrix. -The parallel actions required to connect the various solver objects -are most often already provided by the block-Jacobi or the additive -Schwarz smoothers. To define a new solver, the developer will then -have to define its components and methods, perhaps taking one of the -predefined solvers as a starting point, if possible. - -

-Once the new smoother/solver class has been developed, to use it in -the context of the multilevel preconditioners it is necessary to: - -

-The new solver object is then dynamically included in the -preconditioner structure, and acts as a mold to which the -preconditioner will conform, even though the MLD2P4 library has not -been modified to account for this new development. - -

-It is possible to define new values for the keyword WHAT in the -set routine; if the library code does not recognize a keyword, -it passes it down the composition hierarchy (levels containing -smoothers containing in turn solvers), so that it can be eventually caught by -the new solver. By the same token, any keyword/value pair that does not pertain to -a given smoother should be passed down to the contained solver, and -any keyword/value pair that does not pertain to a given solver is by -default ignored. - -

-An example is provided in the source code distribution under the -folder tests/newslv. In this example we are implementing a new -incomplete factorization variant (which is simply the ILU(0) -factorization under a new name). Because of the specifics of this case, it is -possible to reuse the basic structure of the ILU solver, with its -L/D/U components and the methods needed to apply the solver; only a -few methods, such as the description and most importantly the build, -need to be ovverridden (rewritten). - -

-The interfaces for the calls shown above are defined using - -

- - - - - - - - - - - - -
-smoother class(mld_x_base_smoother_type)
- The user-defined new smoother to be employed in the - preconditioner.
-solver class(mld_x_base_solver_type)
- The user-defined new solver to be employed in the - preconditioner. -
-The other arguments are defined in the way described in -Sec. 6.2. As an example, in the tests/newslv -code we define a new object of type mld_d_tlu_solver_type, and -we pass it as follows: -
-  ! sparse matrix and preconditioner
-  type(psb_dspmat_type) :: a
-  type(mld_dprec_type)  :: prec
-  type(mld_d_tlu_solver_type) :: tlusv
-
-......
-  !
-  !  prepare the preconditioner: an ML with defaults, but with TLU solver at
-  !  intermediate levels. All other parameters are at default values. 
-  !  
-  call prec%init('ML',       info)
-  call prec%hierarchy_build(a,desc_a,info)
-  nlv = prec%get_nlevs()
-  call prec%set(tlusv,   info,ilev=1,ilmax=max(1,nlv-1))
-  call prec%smoothers_build(a,desc_a,info)
-
- -
- - -next - -up - -previous - -contents -
- Next: Error Handling - Up: userhtml - Previous: Method: free_wrk -   Contents
- - - - diff --git a/docs/html/node34.html b/docs/html/node34.html deleted file mode 100644 index a32c73cd..00000000 --- a/docs/html/node34.html +++ /dev/null @@ -1,75 +0,0 @@ - - - - - -Error Handling - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: License - Up: userhtml - Previous: Adding new smoother and -   Contents -
-
- - -

-
-Error Handling -

-

-The error handling in MLD2P4 is based on the PSBLAS error -handling. Error conditions are signaled via an integer argument -info; whenever an error condition is detected, an error trace -stack is built by the library up to the top-level, user-callable -routine. This routine will then decide, according to the user -preferences, whether the error should be handled by terminating the -program or by returning the error condition to the user code, which -will then take action, and whether -an error message should be printed. These options may be set by using -the PSBLAS error handling routines; for further details see the PSBLAS -User's Guide [13]. - -

- - -

- - - diff --git a/docs/html/node35.html b/docs/html/node35.html deleted file mode 100644 index 369bfe3a..00000000 --- a/docs/html/node35.html +++ /dev/null @@ -1,98 +0,0 @@ - - - - - -License - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Bibliography - Up: userhtml - Previous: Error Handling -   Contents -
-
- - -

-
-License -

-

-The MLD2P4 is freely distributable under the following copyright -terms: 

 
- 
-                           MLD2P4  version 2.1
-  MultiLevel Domain Decomposition Parallel Preconditioners Package
-             based on PSBLAS (Parallel Sparse BLAS version 3.5)
-  
-  (C) Copyright 2008, 2010, 2012, 2015, 2017
-
-  Salvatore Filippone    Cranfield University, Cranfield, UK
-  Pasqua D'Ambra         IAC-CNR, Naples, IT
-  Daniela di Serafino    University of Campania L. Vanvitelli, Caserta, IT
-
-  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.
-
- - -
- - - diff --git a/docs/html/node36.html b/docs/html/node36.html deleted file mode 100644 index 0504c1f0..00000000 --- a/docs/html/node36.html +++ /dev/null @@ -1,207 +0,0 @@ - - - - - -Bibliography - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: About this document ... - Up: userhtml - Previous: License -   Contents -

- - -

-Bibliography -

- -

-

1 -
-P. R. Amestoy, C. Ashcraft, O. Boiteau, A. Buttari, J. L'Excellent, C. Weisbecker, -Improving multifrontal methods by means of block low-rank representations, -SIAM Journal on Scientific Computing, volume 37 (3), 2015, A1452-A1474. -See also http://mumps.enseeiht.fr. -

2 -
-M. Brezina, P. Vanek, -A Black-Box Iterative Solver Based on a Two-Level Schwarz Method, -Computing, 63, 1999, 233-263. -

3 -
-W. L. Briggs, V. E. Henson, S. F. McCormick, -A Multigrid Tutorial, Second Edition, -SIAM, 2000. -

4 -
-A. Buttari, P. D'Ambra, D. di Serafino, S. Filippone, -Extending PSBLAS to Build Parallel Schwarz Preconditioners, -in J. Dongarra, K. Madsen, J. Wasniewski, editors, -Proceedings of PARA 04 Workshop on State of the Art -in Scientific Computing, Lecture Notes in Computer Science, -Springer, 2005, 593-602. -

5 -
-A. Buttari, P. D'Ambra, D. di Serafino, S. Filippone, -2LEV-D2P4: a package of high-performance preconditioners -for scientific and engineering applications, -Applicable Algebra in Engineering, Communications and Computing, -18 (3) 2007, 223-239. -

6 -
-X. C. Cai, M. Sarkis, -A Restricted Additive Schwarz Preconditioner for General Sparse Linear Systems, -SIAM Journal on Scientific Computing, 21 (2), 1999, 792-797. -

7 -
-P. D'Ambra, S. Filippone, D. di Serafino, -On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners, -Applied Numerical Mathematics, Elsevier Science, -57 (11-12), 2007, 1181-1196. -

8 -
-P. D'Ambra, D. di Serafino, S. Filippone, -MLD2P4: a Package of Parallel Multilevel -Algebraic Domain Decomposition Preconditioners -in Fortran 95, ACM Trans. Math. Softw., 37(3), 2010, art. 30. -

9 -
-T. A. Davis, -Algorithm 832: UMFPACK - an Unsymmetric-pattern Multifrontal -Method with a Column Pre-ordering Strategy, -ACM Transactions on Mathematical Software, 30, 2004, 196-199. -(See also http://www.cise.ufl.edu/~davis/) -

10 -
-J. W. Demmel, S. C. Eisenstat, J. R. Gilbert, X. S. Li, J. W. H. Liu, -A supernodal approach to sparse partial pivoting, -SIAM Journal on Matrix Analysis and Applications, 20 (3), 1999, 720-755. -

11 -
-J. J. Dongarra, J. Du Croz, I. S. Duff, S. Hammarling, -A set of Level 3 Basic Linear Algebra Subprograms, -ACM Transactions on Mathematical Software, 16 (1) 1990, 1-17. -

12 -
-J. J. Dongarra, J. Du Croz, S. Hammarling, R. J. Hanson, -An extended set of FORTRAN Basic Linear Algebra Subprograms, -ACM Transactions on Mathematical Software, 14 (1) 1988, 1-17. -

13 -
-S. Filippone, A. Buttari, -PSBLAS 3.5.0 User's Guide. A Reference Guide for the Parallel Sparse BLAS Library, 2012, -available from https://github.com/sfilippone/psblas3/tree/master/docs. -

14 -
-S. Filippone, A. Buttari, -Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003. -ACM Transactions on on Mathematical Software, 38 (4), 2012, art. 23. -

15 -
-S. Filippone, M. Colajanni, -PSBLAS: A Library for Parallel Linear Algebra -Computation on Sparse Matrices, -ACM Transactions on Mathematical Software, 26 (4), 2000, 527-550. -

16 -
-S. Gratton, P. Henon, P. Jiranek and X. Vasseur, - Reducing complexity of algebraic multigrid by aggregation, -Numerical Lin. Algebra with Applications, 2016, 23:501-518 - -

-

17 -
-W. Gropp, S. Huss-Lederman, A. Lumsdaine, E. Lusk, B. Nitzberg, W. Saphir, M. Snir, -MPI: The Complete Reference. Volume 2 - The MPI-2 Extensions, -MIT Press, 1998. -

18 -
-C. L. Lawson, R. J. Hanson, D. Kincaid, F. T. Krogh, -Basic Linear Algebra Subprograms for FORTRAN usage, -ACM Transactions on Mathematical Software, 5 (3), 1979, 308-323. -

19 -
-X. S. Li, J. W. Demmel, -SuperLU_DIST: A Scalable Distributed-memory -Sparse Direct Solver for Unsymmetric Linear Systems, -ACM Transactions on Mathematical Software, 29 (2), 2003, 110-140. -

20 -
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21 -
-Y. Saad, -Iterative methods for sparse linear systems, 2nd edition, SIAM, 2003. -

22 -
-B. Smith, P. Bjorstad, W. Gropp, -Domain Decomposition: Parallel Multilevel Methods for Elliptic -Partial Differential Equations, -Cambridge University Press, 1996. -

23 -
-M. Snir, S. Otto, S. Huss-Lederman, D. Walker, J. Dongarra, -MPI: The Complete Reference. Volume 1 - The MPI Core, second edition, -MIT Press, 1998. -

24 -
-K. Stüben, -An Introduction to Algebraic Multigrid, -in A. Schüller, U. Trottenberg, C. Oosterlee, Multigrid, -Academic Press, 2001. -

25 -
-R. S. Tuminaro, C. Tong, -Parallel Smoothed Aggregation Multigrid: Aggregation Strategies on Massively Parallel Machines, in J. Donnelley, editor, Proceedings of SuperComputing 2000, Dallas, 2000. -

26 -
-P. Vanek, J. Mandel, M. Brezina, -Algebraic Multigrid by Smoothed Aggregation for Second and Fourth Order Elliptic Problems, -Computing, 56 (3) 1996, 179-196. - -

-

- -

-

- - - diff --git a/docs/html/node37.html b/docs/html/node37.html deleted file mode 100644 index 0d8df894..00000000 --- a/docs/html/node37.html +++ /dev/null @@ -1,67 +0,0 @@ - - - - - -About this document ... - - - - - - - - - - - - - - - - -
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- - -

-About this document ... -

-

-This document was generated using the -LaTeX2HTML translator Version 2018 (Released Feb 1, 2018) -

-Copyright © 1993, 1994, 1995, 1996, -Nikos Drakos, -Computer Based Learning Unit, University of Leeds. -
-Copyright © 1997, 1998, 1999, -Ross Moore, -Mathematics Department, Macquarie University, Sydney. -

-The command line arguments were:
- latex2html -local_icons -noaddress -dir ../../html userhtml.tex -

-The translation was initiated on 2018-11-29 -

- - - diff --git a/docs/html/node4.html b/docs/html/node4.html deleted file mode 100644 index c478e331..00000000 --- a/docs/html/node4.html +++ /dev/null @@ -1,105 +0,0 @@ - - - - - -Code Distribution - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Contributors - Up: userhtml - Previous: General Overview -   Contents -
-
- - -

-
-Code Distribution -

-

- -MLD2P4 is available from the web site - -

https://github.com/sfilippone/mld2p4-2 -
-where contact points for further information can be also found. - -

-The software is available under a modified BSD license, as specified -in Appendix A; please note that some of the optional -third party libraries may be licensed under a different and more -stringent license, most notably the GPL, and this should be taken into -account when treating derived works. - -

-The library defines a version string with the -constant - -

-
- - -\begin{displaymath}\verb\vert mld_version_string_\vert\end{displaymath} -
-
-

-whose current value is 2.1.0. - -

- -

- -Subsections - - - -
- - - diff --git a/docs/html/node5.html b/docs/html/node5.html deleted file mode 100644 index a15ea834..00000000 --- a/docs/html/node5.html +++ /dev/null @@ -1,81 +0,0 @@ - - - - - -Contributors - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Configuring and Building MLD2P4 - Up: Code Distribution - Previous: Code Distribution -   Contents -
-
- - -

-Contributors -

-Contributors to version 2: - - -Contributors to version 1: - - - -
- - - diff --git a/docs/html/node6.html b/docs/html/node6.html deleted file mode 100644 index 54be0f4b..00000000 --- a/docs/html/node6.html +++ /dev/null @@ -1,128 +0,0 @@ - - - - - -Configuring and Building MLD2P4 - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Prerequisites - Up: userhtml - Previous: Contributors -   Contents -
-
- - -

-
-Configuring and Building MLD2P4 -

- -In order to build MLD2P4 it is necessary to set up a Makefile with appropriate -system-dependent variables; this is done by means of the configure -script. The distribution also includes the autoconf and automake -sources employed to generate the script, but usually this is not needed -to build the software. - -

-MLD2P4 is implemented almost entirely in Fortran 2003, with some -interfaces to external libraries in C; the Fortran compiler -must support the Fortran 2003 standard plus the extension MOLD= -feature, which enhances the usability of ALLOCATE. -Many compilers do this; in particular, this is -supported by the GNU Fortran compiler, for which we -recommend to use at least version 4.8. -The software defines data types and interfaces for -real and complex data, in both single and double precision. - -

-Building MLD2P4 requires some base libraries (see Section 3.1); -interfaces to optional third-party libraries, which extend the functionalities of MLD2P4 -(see Section 3.2), are also available. Many Linux distributions -(e.g., Ubuntu, Fedora, CentOS) provide precompiled packages for the prerequisite and -optional software. In many cases these packages are split between a runtime part and a -“developer” part; in order to build MLD2P4 you need both. A description of the base and -optional software used by MLD2P4 is given in the next sections. - -

- -

- -Subsections - - - - -
- - -next - -up - -previous - -contents -
- Next: Prerequisites - Up: userhtml - Previous: Contributors -   Contents
- - - - diff --git a/docs/html/node7.html b/docs/html/node7.html deleted file mode 100644 index 7eed7f21..00000000 --- a/docs/html/node7.html +++ /dev/null @@ -1,133 +0,0 @@ - - - - - -Prerequisites - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Optional third party libraries - Up: Configuring and Building MLD2P4 - Previous: Configuring and Building MLD2P4 -   Contents -
-
- - -

-
-Prerequisites -

-

-The following base libraries are needed: -

-
BLAS
-
[11,12,18] Many vendors provide optimized versions - of BLAS; if no vendor version is - available for a given platform, the ATLAS software - (math-atlas.sourceforge.net) - may be employed. The reference BLAS from Netlib - (www.netlib.org/blas) are meant to define the standard - behaviour of the BLAS interface, so they are not optimized for any - particular plaftorm, and should only be used as a last - resort. Note that BLAS computations form a relatively small part of - the MLD2P4/PSBLAS computations; they are however critical when using - preconditioners based on MUMPS, UMFPACK or SuperLU third party - libraries. Note that UMFPACK requires a full LAPACK library; our -experience is that configuring ATLAS for building full LAPACK does not -work in the correct way. Our advice is first to download the LAPACK tarfile from -www.netlib.org/lapack and install it independently of ATLAS. In this case, -you need to modify the OPTS and NOOPT definitions for including -fPIC compilation option -in the make.inc file of the LAPACK library. -
-
MPI
-
[17,23] A version of MPI is available on most - high-performance computing systems. - -
-
PSBLAS
-
[13,15] Parallel Sparse BLAS (PSBLAS) is - available from github.com/sfilippone/psblas3; version - 3.5.0 (or later) is required. Indeed, all the prerequisites - listed so far are also prerequisites of PSBLAS. -
-
-Please note that the four previous libraries must have Fortran -interfaces compatible with MLD2P4; -usually this means that they should all be built with the same -compiler as MLD2P4. - -

- -

- - -next - -up - -previous - -contents -
- Next: Optional third party libraries - Up: Configuring and Building MLD2P4 - Previous: Configuring and Building MLD2P4 -   Contents
- - - - diff --git a/docs/html/node8.html b/docs/html/node8.html deleted file mode 100644 index b008d3ae..00000000 --- a/docs/html/node8.html +++ /dev/null @@ -1,136 +0,0 @@ - - - - - -Optional third party libraries - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Configuration options - Up: Configuring and Building MLD2P4 - Previous: Prerequisites -   Contents -
-
- - -

-
-Optional third party libraries -

-

-We provide interfaces to the following third-party software libraries; -note that these are optional, but if you enable them some defaults -for multilevel preconditioners may change to reflect their presence. - -

-

-
UMFPACK
-
[9] - A sparse LU factorization package included in the SuiteSparse library, available from - faculty.cse.tamu.edu/davis/suitesparse.html; - it provides sequential factorization and triangular system solution for double - precision real and complex data. We tested version 4.5.4 of SuiteSparse. - Note that for configuring SuiteSparse you should provide the right path to the BLAS - and LAPACK libraries in the SuiteSparse_config/SuiteSparse_config.mk file. -
-
MUMPS
-
[1] - A sparse LU factorization package available from mumps.enseeiht.fr; - it provides sequential and parallel factorizations and triangular system solution - for single and double precision, real and complex data. - We tested versions 4.10.0 and 5.0.1. -
-
SuperLU
-
[10] - A sparse LU factorization package available from - crd.lbl.gov/~xiaoye/SuperLU/; it provides sequential - factorization and triangular system solution for single and double precision, - real and complex data. We tested versions 4.3 and 5.0. If you installed BLAS from - ATLAS, remember to define the BLASLIB variable in the make.inc file. - -
-
SuperLU_Dist
-
[19] - A sparse LU factorization package available - from the same site as SuperLU; it provides parallel factorization and - triangular system solution for double precision real and complex data. - We tested versions 3.3 and 4.2. If you installed BLAS from - ATLAS, remember to define the BLASLIB variable in the make.inc file and - to add the -std=c99 option to the C compiler options. - Note that this library requires the ParMETIS - library for parallel graph partitioning and fill-reducing matrix ordering, available from - glaros.dtc.umn.edu/gkhome/metis/parmetis/overview. -
-
-

- -

- - -next - -up - -previous - -contents -
- Next: Configuration options - Up: Configuring and Building MLD2P4 - Previous: Prerequisites -   Contents
- - - - diff --git a/docs/html/node9.html b/docs/html/node9.html deleted file mode 100644 index 212118d8..00000000 --- a/docs/html/node9.html +++ /dev/null @@ -1,292 +0,0 @@ - - - - - -Configuration options - - - - - - - - - - - - - - - - - - -
- -next - -up - -previous - -contents -
- Next: Bug reporting - Up: Configuring and Building MLD2P4 - Previous: Optional third party libraries -   Contents -
-
- - -

-Configuration options -

-

-In order to build MLD2P4, the first step is to use the configure script -in the main directory to generate the necessary makefile. - -

-As a minimal example consider the following: -

-./configure --with-psblas=PSB-INSTALL-DIR
-
-which assumes that the various MPI compilers and support libraries are -available in the standard directories on the system, and specifies -only the PSBLAS install directory (note that the latter directory must -be specified with an absolute path). -The full set of options may be looked at by issuing the command -./configure --help, which produces: -
-`configure' configures MLD2P4 2.1.1 to adapt to many kinds of systems.
-
-Usage: ./configure [OPTION]... [VAR=VALUE]...
-
-To assign environment variables (e.g., CC, CFLAGS...), specify them as
-VAR=VALUE.  See below for descriptions of some of the useful variables.
-
-Defaults for the options are specified in brackets.
-
-Configuration:
-  -h, --help              display this help and exit
-      --help=short        display options specific to this package
-      --help=recursive    display the short help of all the included packages
-  -V, --version           display version information and exit
-  -q, --quiet, --silent   do not print `checking ...' messages
-      --cache-file=FILE   cache test results in FILE [disabled]
-  -C, --config-cache      alias for `--cache-file=config.cache'
-  -n, --no-create         do not create output files
-      --srcdir=DIR        find the sources in DIR [configure dir or `..']
-
-Installation directories:
-  --prefix=PREFIX         install architecture-independent files in PREFIX
-                          [/usr/local]
-  --exec-prefix=EPREFIX   install architecture-dependent files in EPREFIX
-                          [PREFIX]
-
-By default, `make install' will install all the files in
-`/usr/local/bin', `/usr/local/lib' etc.  You can specify
-an installation prefix other than `/usr/local' using `--prefix',
-for instance `--prefix=$HOME'.
-
-For better control, use the options below.
-
-Fine tuning of the installation directories:
-  --bindir=DIR            user executables [EPREFIX/bin]
-  --sbindir=DIR           system admin executables [EPREFIX/sbin]
-  --libexecdir=DIR        program executables [EPREFIX/libexec]
-  --sysconfdir=DIR        read-only single-machine data [PREFIX/etc]
-  --sharedstatedir=DIR    modifiable architecture-independent data [PREFIX/com]
-  --localstatedir=DIR     modifiable single-machine data [PREFIX/var]
-  --libdir=DIR            object code libraries [EPREFIX/lib]
-  --includedir=DIR        C header files [PREFIX/include]
-  --oldincludedir=DIR     C header files for non-gcc [/usr/include]
-  --datarootdir=DIR       read-only arch.-independent data root [PREFIX/share]
-  --datadir=DIR           read-only architecture-independent data [DATAROOTDIR]
-  --infodir=DIR           info documentation [DATAROOTDIR/info]
-  --localedir=DIR         locale-dependent data [DATAROOTDIR/locale]
-  --mandir=DIR            man documentation [DATAROOTDIR/man]
-  --docdir=DIR            documentation root [DATAROOTDIR/doc/mld2p4]
-  --htmldir=DIR           html documentation [DOCDIR]
-  --dvidir=DIR            dvi documentation [DOCDIR]
-  --pdfdir=DIR            pdf documentation [DOCDIR]
-  --psdir=DIR             ps documentation [DOCDIR]
-
-Program names:
-  --program-prefix=PREFIX            prepend PREFIX to installed program names
-  --program-suffix=SUFFIX            append SUFFIX to installed program names
-  --program-transform-name=PROGRAM   run sed PROGRAM on installed program names
-
-Optional Features:
-  --disable-option-checking  ignore unrecognized --enable/--with options
-  --disable-FEATURE       do not include FEATURE (same as --enable-FEATURE=no)
-  --enable-FEATURE[=ARG]  include FEATURE [ARG=yes]
-  --enable-silent-rules   less verbose build output (undo: "make V=1")
-  --disable-silent-rules  verbose build output (undo: "make V=0")
-  --enable-dependency-tracking
-                          do not reject slow dependency extractors
-  --disable-dependency-tracking
-                          speeds up one-time build
-  --enable-serial         Specify whether to enable a fake mpi library to run
-                          in serial mode.
-  --enable-long-integers  Specify usage of 64 bits integers.
-
-Optional Packages:
-  --with-PACKAGE[=ARG]    use PACKAGE [ARG=yes]
-  --without-PACKAGE       do not use PACKAGE (same as --with-PACKAGE=no)
-  --with-psblas=DIR       The install directory for PSBLAS, for example,
-                          --with-psblas=/opt/packages/psblas-3.5
-  --with-psblas-incdir=DIR
-                          Specify the directory for PSBLAS C includes.
-  --with-psblas-moddir=DIR
-                          Specify the directory for PSBLAS Fortran modules.
-  --with-psblas-libdir=DIR
-                          Specify the directory for PSBLAS library.
-  --with-ccopt            additional [CCOPT] flags to be added: will prepend
-                          to [CCOPT]
-  --with-fcopt            additional [FCOPT] flags to be added: will prepend
-                          to [FCOPT]
-  --with-libs             List additional link flags here. For example,
-                          --with-libs=-lspecial_system_lib or
-                          --with-libs=-L/path/to/libs
-  --with-clibs            additional [CLIBS] flags to be added: will prepend
-                          to [CLIBS]
-  --with-flibs            additional [FLIBS] flags to be added: will prepend
-                          to [FLIBS]
-  --with-library-path     additional [LIBRARYPATH] flags to be added: will
-                          prepend to [LIBRARYPATH]
-  --with-include-path     additional [INCLUDEPATH] flags to be added: will
-                          prepend to [INCLUDEPATH]
-  --with-module-path      additional [MODULE_PATH] flags to be added: will
-                          prepend to [MODULE_PATH]
-  --with-extra-libs       List additional link flags here. For example,
-                          --with-extra-libs=-lspecial_system_lib or
-                          --with-extra-libs=-L/path/to/libs
-  --with-blas=<lib>       use BLAS library <lib>
-  --with-blasdir=<dir>    search for BLAS library in <dir>
-  --with-lapack=<lib>     use LAPACK library <lib>
-  --with-mumps=LIBNAME    Specify the libname for MUMPS. Default: autodetect
-                          with minimum "-lmumps_common -lpord"
-  --with-mumpsdir=DIR     Specify the directory for MUMPS library and
-                          includes. Note: you will need to add auxiliary
-                          libraries with --extra-libs; this depends on how
-                          MUMPS was configured and installed, at a minimum you
-                          will need SCALAPACK and BLAS
-  --with-mumpsincdir=DIR  Specify the directory for MUMPS includes.
-  --with-mumpsmoddir=DIR  Specify the directory for MUMPS Fortran modules.
-  --with-mumpslibdir=DIR  Specify the directory for MUMPS library.
-  --with-umfpack=LIBNAME  Specify the library name for UMFPACK and its support
-                          libraries. Default: "-lumfpack -lamd"
-  --with-umfpackdir=DIR   Specify the directory for UMFPACK library and
-                          includes.
-  --with-umfpackincdir=DIR
-                          Specify the directory for UMFPACK includes.
-  --with-umfpacklibdir=DIR
-                          Specify the directory for UMFPACK library.
-  --with-superlu=LIBNAME  Specify the library name for SUPERLU library.
-                          Default: "-lsuperlu"
-  --with-superludir=DIR   Specify the directory for SUPERLU library and
-                          includes.
-  --with-superluincdir=DIR
-                          Specify the directory for SUPERLU includes.
-  --with-superlulibdir=DIR
-                          Specify the directory for SUPERLU library.
-  --with-superludist=LIBNAME
-                          Specify the libname for SUPERLUDIST library.
-                          Requires you also specify SuperLU. Default:
-                          "-lsuperlu_dist"
-  --with-superludistdir=DIR
-                          Specify the directory for SUPERLUDIST library and
-                          includes.
-  --with-superludistincdir=DIR
-                          Specify the directory for SUPERLUDIST includes.
-  --with-superludistlibdir=DIR
-                          Specify the directory for SUPERLUDIST library.
-
-Some influential environment variables:
-  FC          Fortran compiler command
-  FCFLAGS     Fortran compiler flags
-  LDFLAGS     linker flags, e.g. -L<lib dir> if you have libraries in a
-              nonstandard directory <lib dir>
-  LIBS        libraries to pass to the linker, e.g. -l<library>
-  CC          C compiler command
-  CFLAGS      C compiler flags
-  CPPFLAGS    (Objective) C/C++ preprocessor flags, e.g. -I<include dir> if
-              you have headers in a nonstandard directory <include dir>
-  MPICC       MPI C compiler command
-  MPIFC       MPI Fortran compiler command
-  CPP         C preprocessor
-
-Use these variables to override the choices made by `configure' or to help
-it to find libraries and programs with nonstandard names/locations.
-
-Report bugs to <https://github.com/sfilippone/mld2p4-2/issues>.
-
-

-For instance, if a user has built and installed PSBLAS 3.5 under the -/opt directory and is -using the SuiteSparse package (which includes UMFPACK), then MLD2P4 -might be configured with: -

- ./configure --with-psblas=/opt/psblas-3.5/ \
- --with-umfpackincdir=/usr/include/suitesparse/
-
-Once the configure script has completed execution, it will have -generated the file Make.inc which will then be used by all -Makefiles in the directory tree; this file will be copied in the -install directory under the name Make.inc.MLD2P4. - -

-To use the MUMPS solver package, -the user has to add the appropriate options to the configure script; -by default we are looking for the libraries --ldmumps -lsmumps -lzmumps -lcmumps -mumps_common -lpord. -MUMPS often uses additional packages such as ScaLAPACK, ParMETIS, -SCOTCH, as well as enabling OpenMP; in such cases it is necessary to -add linker options with the --with-extra-libs configure option. - -

-To build the library the user will now enter -

-make
-
-followed (optionally) by -
-make install
-
-
- - -next - -up - -previous - -contents -
- Next: Bug reporting - Up: Configuring and Building MLD2P4 - Previous: Optional third party libraries -   Contents
- - - - diff --git a/docs/html/prev.png b/docs/html/prev.png deleted file mode 100644 index e60b8b40..00000000 Binary files a/docs/html/prev.png and /dev/null differ diff --git a/docs/html/prev_g.png b/docs/html/prev_g.png deleted file mode 100644 index 476d9568..00000000 Binary files a/docs/html/prev_g.png and /dev/null differ diff --git a/docs/html/up.png b/docs/html/up.png deleted file mode 100644 index 3937e168..00000000 Binary files a/docs/html/up.png and /dev/null differ diff --git a/docs/html/up_g.png b/docs/html/up_g.png deleted file mode 100644 index 54ceb683..00000000 Binary files a/docs/html/up_g.png and /dev/null differ diff --git a/docs/html/userhtml.css b/docs/html/userhtml.css deleted file mode 100644 index d1824aff..00000000 --- a/docs/html/userhtml.css +++ /dev/null @@ -1,30 +0,0 @@ -/* Century Schoolbook font is very similar to Computer Modern Math: cmmi */ -.MATH { font-family: "Century Schoolbook", serif; } -.MATH I { font-family: "Century Schoolbook", serif; font-style: italic } -.BOLDMATH { font-family: "Century Schoolbook", serif; font-weight: bold } - -/* implement both fixed-size and relative sizes */ -SMALL.XTINY { font-size : xx-small } -SMALL.TINY { font-size : x-small } -SMALL.SCRIPTSIZE { font-size : smaller } -SMALL.FOOTNOTESIZE { font-size : small } -SMALL.SMALL { } -BIG.LARGE { } -BIG.XLARGE { font-size : large } -BIG.XXLARGE { font-size : x-large } -BIG.HUGE { font-size : larger } -BIG.XHUGE { font-size : xx-large } - -/* heading styles */ -H1 { } -H2 { } -H3 { } -H4 { } -H5 { } - -/* mathematics styles */ -DIV.displaymath { } /* math displays */ -TD.eqno { } /* equation-number cells */ - - -/* document-specific styles come next */ diff --git a/docs/html/userhtml.html b/docs/html/userhtml.html deleted file mode 100644 index 1f0d2ee7..00000000 --- a/docs/html/userhtml.html +++ /dev/null @@ -1,184 +0,0 @@ - - - - - -userhtml - - - - - - - - - - - - - - - -
- -next -up -previous - -contents -
- Next: Abstract -   Contents -
-
- -MLD2P4 -
-
-User's and Reference Guide -
A guide for the MultiLevel Domain Decomposition -Parallel Preconditioners Package -based on PSBLAS -
-
-
-
Pasqua D'Ambra -
IAC-CNR, Naples, Italy -
-
-
-
Daniela di Serafino -
University of Campania “Luigi Vanvitelli”, Caserta, Italy -
-
-
-
Salvatore Filippone -
Cranfield University, Cranfield, United Kingdom -
-
-
-
-
-
-
-
-
-
-
-Software version: 2.2 -
-July 31, 2018 - -
- - -

- -

- -

- - - - - -
- - -