Documentation changes. We have barely begun.....
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Salvatore Filippone
2011-12-16 16:45:25 +00:00
parent c730f15b58
commit 844a942947
243 changed files with 14860 additions and 15182 deletions
+33 -37
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@@ -26,26 +26,26 @@ original version by: Nikos Drakos, CBLU, University of Leeds
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@@ -71,22 +71,17 @@ influenced by the structure of the ScaLAPACK parallel
library. The layered structure of the PSBLAS library
is shown in figure&nbsp;<A HREF="#fig:psblas">1</A>; lower layers of the library
indicate an encapsulation relationship with upper layers. The ongoing
discussion focuses on the Fortran&nbsp;95 layer immediately below the
discussion focuses on the Fortran&nbsp;2003 layer immediately below the
application layer.
The serial parts of the computation on each process are executed through
calls to the serial sparse BLAS subroutines. In a similar way, the
inter-process message exchanges are implemented through the Basic
calls to the serial sparse BLAS subroutines.
In a similar way, the inter-process message exchanges are encapsulated
in an applicaiton layer that has been strongly inspired by the Basic
Linear Algebra Communication Subroutines (BLACS) library&nbsp;[<A
HREF="node108.html#BLACS">7</A>]
that guarantees a portable and efficient communication layer. The
Message Passing Interface code is encapsulated within the BLACS
layer. However, in some cases, MPI routines are directly used either
to improve efficiency or to implement communication patterns for which
the BLACS package doesn't provide any method.
<P>
In any case we provide wrappers around the BLACS routines so that the
user does not need to delve into their details (see Sec.&nbsp;<A HREF="node73.html#sec:parenv">7</A>).
HREF="node107.html#BLACS">7</A>].
Usually there is no need to deal directly with MPI; however, in some
cases, MPI routines are used directly to improve efficiency. For
further details on our communication layer see Sec.&nbsp;<A HREF="node72.html#sec:parenv">7</A>.
<P>
@@ -135,13 +130,14 @@ is equivalent to a partition of the discretization mesh into <EM>sub-domains</EM
Our library supports any distribution that keeps together
the coefficients of each matrix row; there are no other constraints on
the variable assignment.
This choice is consistent with data distributions commonly used in
ScaLAPACK such as <code>CYCLIC(N)</code> and <code>BLOCK</code>,
This choice is consistent with simple data distributions
such as <code>CYCLIC(N)</code> and <code>BLOCK</code>,
as well as completely arbitrary assignments of
equation indices to processes. In particular it is consistent with the
equation indices to processes.
In particular it is consistent with the
usage of graph partitioning tools commonly available in the
literature, e.g. METIS&nbsp;[<A
HREF="node108.html#METIS">13</A>].
HREF="node107.html#METIS">13</A>].
Dense vectors conform to sparse
matrices, that is, the entries of a vector follow the same distribution
of the matrix rows.
@@ -161,38 +157,38 @@ bottleneck would make this option unattractive in most cases.
<A NAME="CHILD_LINKS"><STRONG>Subsections</STRONG></A>
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