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mld2p4: final fixes for 1.1 release.

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Salvatore Filippone
2009-03-16 08:47:03 +00:00
parent 5e0cfebc6d
commit 73dac6d963
56 changed files with 1275 additions and 1325 deletions
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docs/html/node3.html
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@@ -63,7 +63,7 @@ General Overview
<P>
The M<SMALL>ULTI-</SMALL>L<SMALL>EVEL </SMALL>D<SMALL>OMAIN </SMALL>D<SMALL>ECOMPOSITION </SMALL>P<SMALL>ARALLEL </SMALL>P<SMALL>RECONDITIONERS </SMALL>P<SMALL>ACKAGE BASED ON
</SMALL>PSBLAS (MLD2P4) provides <I>multi-level Schwarz preconditioners</I>&nbsp;[<A
HREF="node25.html#dd2_96">20</A>],
HREF="node25.html#dd2_96">21</A>],
to be used in the iterative solutions of sparse linear systems:
<BR>
<DIV ALIGN="RIGHT">
@@ -102,7 +102,7 @@ explicitly using any information on the geometry of the original problem (e.g. t
discretization of a PDE). The <I>smoothed aggregation</I> technique is applied
as algebraic coarsening strategy&nbsp;[<A
HREF="node25.html#BREZINA_VANEK">1</A>,<A
HREF="node25.html#VANEK_MANDEL_BREZINA">24</A>].
HREF="node25.html#VANEK_MANDEL_BREZINA">25</A>].
</LI>
</UL>
@@ -120,7 +120,7 @@ real and the complex case, that can be used through a single interface.
MLD2P4 has been designed to implement scalable and easy-to-use multilevel preconditioners
in the context of the <I>PSBLAS (Parallel Sparse BLAS)
computational framework</I>&nbsp;[<A
HREF="node25.html#psblas_00">15</A>].
HREF="node25.html#psblas_00">16</A>].
PSBLAS is a library originally developed to address the parallel implementation of
iterative solvers for sparse linear system, by providing basic linear algebra
operators and data management facilities for distributed sparse matrices; it
@@ -133,10 +133,10 @@ portability, modularity ed extensibility in the development of the preconditione
package. On the other hand, the implementation of MLD2P4 has led to some
revisions and extentions of the PSBLAS kernels, leading to the
recent PSBLAS 2.0 version&nbsp;[<A
HREF="node25.html#PSBLASGUIDE">14</A>]. The inter-process comunication required
HREF="node25.html#PSBLASGUIDE">15</A>]. The inter-process comunication required
by MLD2P4 is encapsulated into the PSBLAS routines, except few cases where
MPI&nbsp;[<A
HREF="node25.html#MPI1">21</A>] is explicitly called. Therefore, MLD2P4 can be run on any parallel
HREF="node25.html#MPI1">22</A>] is explicitly called. Therefore, MLD2P4 can be run on any parallel
machine where PSBLAS and MPI implementations are available.
<P>