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 docs/psblas-3.0.pdf
 docs/src/Makefile
 docs/src/biblio.tex
 docs/src/intro.tex
 docs/src/userguide.tex
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Started work on docs.
psblas3-type-indexed
Salvatore Filippone 13 years ago
parent edeb859033
commit c730f15b58

@ -25,7 +25,7 @@ original version by: Nikos Drakos, CBLU, University of Leeds
<BODY >
<DL>
<DT><A NAME="foot165">...
<DT><A NAME="foot167">...
explicitly</A><A
HREF="node3.html#tex2html2"><SUP>1</SUP></A></DT>
<DD>In our prototype implementation we provide
@ -63,7 +63,7 @@ sample scatter/gather routines.
.
</PRE>
</DD>
<DT><A NAME="foot174">... domain</A><A
<DT><A NAME="foot176">... domain</A><A
HREF="node4.html#tex2html3"><SUP>2</SUP></A></DT>
<DD>This is
the normal situation when the pattern of the sparse matrix is
@ -104,7 +104,7 @@ sample scatter/gather routines.
.
</PRE>
</DD>
<DT><A NAME="foot6808">... follows</A><A
<DT><A NAME="foot6814">... follows</A><A
HREF="node102.html#tex2html29"><SUP>3</SUP></A></DT>
<DD>The string is case-insensitive

@ -106,7 +106,7 @@ Legal inputs to this subroutine are interpreted depending on the
WIDTH="42" HEIGHT="30" ALIGN="MIDDLE" BORDER="0"
SRC="img141.png"
ALT="$ptype$"> string as follows<A NAME="tex2html29"
HREF="footnode.html#foot6808"><SUP>3</SUP></A>:
HREF="footnode.html#foot6814"><SUP>3</SUP></A>:
<DL>
<DT><STRONG>NONE</STRONG></DT>
<DD>No preconditioning, i.e. the preconditioner is just a copy

@ -357,6 +357,8 @@ An integer value; 0 means no error has been detected.
<P>
<P>
<P>
<HR>
<!--Navigation Panel-->

@ -52,9 +52,14 @@ original version by: Nikos Drakos, CBLU, University of Leeds
<H2><A NAME="SECTION000130000000000000000">
Bibliography</A>
</H2><DL COMPACT><DD>
</H2><DL COMPACT><DD><P></P><DT><A NAME="DesPat:11">1</A>
<DD>
D.&nbsp;Barbieri, V.&nbsp;Cardellini, S.&nbsp;Filippone and D.&nbsp;Rouson
<EM>Design Patterns for Scientific Computations on Sparse Matrices</EM>,
HPSS 2011, Algorithms and Programming Tools for Next-Generation High-Performance Scientific Software, Bordeaux, Sep. 2011
<P>
<P></P><DT><A NAME="PARA04FOREST">1</A>
<P></P><DT><A NAME="PARA04FOREST">2</A>
<DD>
G.&nbsp;Bella, S.&nbsp;Filippone, A.&nbsp;De Maio and M.&nbsp;Testa,
<EM>A Simulation Model for Forest Fires</EM>,
@ -62,12 +67,12 @@ in J.&nbsp;Dongarra, K.&nbsp;Madsen, J.&nbsp;Wasniewski, editors,
Proceedings of PARA&nbsp;04 Workshop on State of the Art
in Scientific Computing, pp.&nbsp;546-553, Lecture Notes in Computer Science,
Springer, 2005.
<P></P><DT><A NAME="2007d">2</A>
<P></P><DT><A NAME="2007d">3</A>
<DD> A. Buttari, D. di Serafino, P. D'Ambra, S. Filippone,<BR>
2LEV-D2P4: a package of high-performance preconditioners,<BR>
Applicable Algebra in Engineering, Communications and Computing,
Volume 18, Number 3, May, 2007, pp. 223-239
<P></P><DT><A NAME="2007c">3</A>
<P></P><DT><A NAME="2007c">4</A>
<DD> P. D'Ambra, S. Filippone, D. Di Serafino<BR>
On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners
<BR>
@ -75,42 +80,48 @@ Applied Numerical Mathematics, Elsevier Science,
Volume 57, Issues 11-12, November-December 2007, Pages 1181-1196.
<P>
<P></P><DT><A NAME="BLAS2">4</A>
<P></P><DT><A NAME="BLAS2">5</A>
<DD>
Dongarra, J. J., DuCroz, J., Hammarling, S. and Hanson, R.,
An Extended Set of Fortran Basic Linear Algebra Subprograms,
ACM Trans. Math. Softw. vol.&nbsp;14, 1-17, 1988.
<P></P><DT><A NAME="BLAS3">5</A>
<P></P><DT><A NAME="BLAS3">6</A>
<DD>
Dongarra, J., DuCroz, J., Hammarling, S. and Duff, I.,
A Set of level 3 Basic Linear Algebra Subprograms,
ACM Trans. Math. Softw. vol.&nbsp;16, 1-17, 1990.
<P></P><DT><A NAME="BLACS">6</A>
<P></P><DT><A NAME="BLACS">7</A>
<DD>
J.&nbsp;J.&nbsp;Dongarra and R.&nbsp;C.&nbsp;Whaley,
<EM>A User's Guide to the BLACS v.&nbsp;1.1</EM>,
Lapack Working Note 94, Tech. Rep. UT-CS-95-281, University of
Tennessee, March 1995 (updated May 1997).
<P></P><DT><A NAME="sblas97">7</A>
<P></P><DT><A NAME="sblas97">8</A>
<DD>
I.&nbsp;Duff, M.&nbsp;Marrone, G.&nbsp;Radicati and C.&nbsp;Vittoli,
<EM>Level 3 Basic Linear Algebra Subprograms for Sparse Matrices:
a User Level Interface</EM>,
ACM Transactions on Mathematical Software, 23(3), pp.&nbsp;379-401, 1997.
<P></P><DT><A NAME="sblas02">8</A>
<P></P><DT><A NAME="sblas02">9</A>
<DD>
I.&nbsp;Duff, M.&nbsp;Heroux and R.&nbsp;Pozo,
<EM>An Overview of the Sparse Basic Linear
Algebra Subprograms: the New Standard from the BLAS Technical Forum</EM>,
ACM Transactions on Mathematical Software, 28(2), pp.&nbsp;239-267, 2002.
<P></P><DT><A NAME="PSBLAS">9</A>
<P></P><DT><A NAME="PSBLAS">10</A>
<DD>
S.&nbsp;Filippone and M.&nbsp;Colajanni,
<EM>PSBLAS: A Library for Parallel Linear Algebra
Computation on Sparse Matrices</EM>,
<BR>
ACM Transactions on Mathematical Software, 26(4), pp.&nbsp;527-550, 2000.
<P></P><DT><A NAME="KIVA3PSBLAS">10</A>
<P></P><DT><A NAME="Sparse03">11</A>
<DD>
S.&nbsp;Filippone and A.&nbsp;Buttari,
<EM>Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003</EM>,
<BR>
ACM Transactions on Mathematical Software, to appear.
<P></P><DT><A NAME="KIVA3PSBLAS">12</A>
<DD>
S.&nbsp;Filippone, P.&nbsp;D'Ambra, M.&nbsp;Colajanni,
<EM>Using a Parallel Library of Sparse Linear Algebra in a Fluid Dynamics
@ -118,7 +129,7 @@ Applications Code on Linux Clusters</EM>,
in G.&nbsp;Joubert, A.&nbsp;Murli, F.&nbsp;Peters, M.&nbsp;Vanneschi, editors,
Parallel Computing - Advances &amp; Current Issues,
pp.&nbsp;441-448, Imperial College Press, 2002.
<P></P><DT><A NAME="METIS">11</A>
<P></P><DT><A NAME="METIS">13</A>
<DD>
Karypis, G. and Kumar, V.,
<EM>METIS: Unstructured Graph Partitioning and Sparse Matrix
@ -126,25 +137,31 @@ Karypis, G. and Kumar, V.,
Minneapolis, MN 55455: University of Minnesota, Department of
Computer Science, 1995.
Internet Address: <code>http://www.cs.umn.edu/~karypis</code>.
<P></P><DT><A NAME="BLAS1">12</A>
<P></P><DT><A NAME="BLAS1">14</A>
<DD>
Lawson, C., Hanson, R., Kincaid, D. and Krogh, F.,
Basic Linear Algebra Subprograms for Fortran usage,
ACM Trans. Math. Softw. vol.&nbsp;5, 38-329, 1979.
<P>
<P></P><DT><A NAME="machiels">13</A>
<P></P><DT><A NAME="machiels">15</A>
<DD>
Machiels, L. and Deville, M.
<EM>Fortran 90: An entry to object-oriented programming for the solution
of partial differential equations.</EM>
ACM Trans. Math. Softw. vol.&nbsp;23, 32-49.
<P></P><DT><A NAME="metcalf">14</A>
<P></P><DT><A NAME="metcalf">16</A>
<DD>
Metcalf, M., Reid, J. and Cohen, M.
<EM>Fortran 95/2003 explained.</EM>
Oxford University Press, 2004.
<P></P><DT><A NAME="MPI1">15</A>
<P></P><DT><A NAME="RouXiaXu:11">17</A>
<DD>
Rouson, D.W.I., Xia, J., Xu, X.: Scientific Software Design: The
Object-Oriented Way. Cambridge University Press (2011)
<P>
<P></P><DT><A NAME="MPI1">18</A>
<DD>
M.&nbsp;Snir, S.&nbsp;Otto, S.&nbsp;Huss-Lederman, D.&nbsp;Walker and J.&nbsp;Dongarra,
<EM>MPI: The Complete Reference. Volume 1 - The MPI Core</EM>, second edition,

@ -63,7 +63,7 @@ Mathematics Department, Macquarie University, Sydney.
The command line arguments were: <BR>
<STRONG>latex2html</STRONG> <TT>-local_icons -noaddress -dir ../../html userhtml.tex</TT>
<P>
The translation was initiated by Salvatore Filippone on 2011-10-13
The translation was initiated by Salvatore Filippone on 2011-12-15
<BR><HR>
</BODY>

@ -129,7 +129,7 @@ figure&nbsp;<A HREF="node13.html#fig:spmattype">5</A>. The definitions for singl
complex data are identical except for the <code>real</code> declaration and
for the kind type parameter.
<DIV ALIGN="CENTER"><A NAME="fig:spmattype"></A><A NAME="670"></A>
<DIV ALIGN="CENTER"><A NAME="fig:spmattype"></A><A NAME="676"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 4:</STRONG>
The PSBLAS defined data type that

@ -129,7 +129,7 @@ figure&nbsp;<A HREF="#fig:spmattype">5</A>. The definitions for single precision
complex data are identical except for the <code>real</code> declaration and
for the kind type parameter.
<DIV ALIGN="CENTER"><A NAME="fig:spmattype"></A><A NAME="672"></A>
<DIV ALIGN="CENTER"><A NAME="fig:spmattype"></A><A NAME="678"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 5:</STRONG>
The PSBLAS defined data type that

@ -72,7 +72,7 @@ to be interpreted. This data structure is the basis of more complex
preconditioning strategies, which are the subject of further
research.
<DIV ALIGN="CENTER"><A NAME="fig:prectype"></A><A NAME="674"></A>
<DIV ALIGN="CENTER"><A NAME="fig:prectype"></A><A NAME="680"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 6:</STRONG>
The PSBLAS defined data type that contains a preconditioner.</CAPTION>

@ -69,14 +69,29 @@ addresses a distributed memory execution model operating with message
passing.
<P>
The PSBLAS library is internally implemented in
the Fortran&nbsp;95&nbsp;[<A
HREF="node108.html#metcalf">14</A>] programming language, with reuse and/or
The PSBLAS library version 3 is internally implemented in
the Fortran&nbsp;2003&nbsp;[<A
HREF="node108.html#metcalf">16</A>] programming language, with reuse and/or
adaptation of some existing Fortran&nbsp;77 software, and a handful of C
routines.
A similar approach has been advocated by a number of authors,
<P>
The use of Fortran&nbsp;2003 offers a number of advantages over Fortran&nbsp;95,
mostly in the handling of requirements for evolution and adaptation of
the library to new computing architectures and integration of
new algorithms.
For a detailed discussion of our design see&nbsp;[<A
HREF="node108.html#Sparse03">11</A>]; other
works tackling advanced programming in Fortran&nbsp;2003 include&nbsp;[<A
HREF="node108.html#DesPat:11">1</A>,<A
HREF="node108.html#RouXiaXu:11">17</A>]
<P>
Previous approaches have been based on mixing Fortran&nbsp;95, with its
support for object-based design, with other languages; these have
been advocated by a number of authors,
e.g.&nbsp;[<A
HREF="node108.html#machiels">13</A>]. Moreover, the Fortran&nbsp;95 facilities for dynamic
HREF="node108.html#machiels">15</A>]. Moreover, the Fortran&nbsp;95 facilities for dynamic
memory management and interface overloading greatly enhance the
usability of the PSBLAS
subroutines. In this way, the library can take care of runtime memory
@ -91,12 +106,12 @@ Fortran compiler from the Free Software Foundation (as of version 4.2).
The presentation of the
PSBLAS library follows the general structure of the proposal for
serial Sparse BLAS&nbsp;[<A
HREF="node108.html#sblas97">7</A>,<A
HREF="node108.html#sblas02">8</A>], which in its turn is based on the
HREF="node108.html#sblas97">8</A>,<A
HREF="node108.html#sblas02">9</A>], which in its turn is based on the
proposal for BLAS on dense matrices&nbsp;[<A
HREF="node108.html#BLAS1">12</A>,<A
HREF="node108.html#BLAS2">4</A>,<A
HREF="node108.html#BLAS3">5</A>].
HREF="node108.html#BLAS1">14</A>,<A
HREF="node108.html#BLAS2">5</A>,<A
HREF="node108.html#BLAS3">6</A>].
<P>
The applicability of sparse iterative solvers to many different areas

@ -81,7 +81,7 @@ call psb_geaxpby(alpha, x, beta, y, desc_a, info)
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1504"></A>
<DIV ALIGN="CENTER"><A NAME="1510"></A>
<TABLE>
<CAPTION><STRONG>Table 1:</STRONG>
Data types</CAPTION>

@ -116,7 +116,7 @@ dot \leftarrow x^H y
psb_gedot(x, y, desc_a, info)
</PRE>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1505"></A>
<DIV ALIGN="CENTER"><A NAME="1511"></A>
<TABLE>
<CAPTION><STRONG>Table 2:</STRONG>
Data types</CAPTION>

@ -77,7 +77,7 @@ 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
Linear Algebra Communication Subroutines (BLACS) library&nbsp;[<A
HREF="node108.html#BLACS">6</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
@ -90,7 +90,7 @@ user does not need to delve into their details (see Sec.&nbsp;<A HREF="node73.ht
<P>
<DIV ALIGN="CENTER"><A NAME="fig:psblas"></A><A NAME="224"></A>
<DIV ALIGN="CENTER"><A NAME="fig:psblas"></A><A NAME="226"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 1:</STRONG>
PSBLAS library components hierarchy.</CAPTION>
@ -141,7 +141,7 @@ as well as completely arbitrary assignments of
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">11</A>].
HREF="node108.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.
@ -152,7 +152,7 @@ process generates its own portion. We never require that the entire
matrix be available on a single node. However, it is possible
to hold the entire matrix in one process and distribute it
explicitly<A NAME="tex2html2"
HREF="footnode.html#foot165"><SUP>1</SUP></A>, even though the resulting
HREF="footnode.html#foot167"><SUP>1</SUP></A>, even though the resulting
bottleneck would make this option unattractive in most cases.
<P>

@ -101,7 +101,7 @@ is a rank one array.
call psb_gedots(res, x, y, desc_a, info)
</PRE>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1506"></A>
<DIV ALIGN="CENTER"><A NAME="1512"></A>
<TABLE>
<CAPTION><STRONG>Table 3:</STRONG>
Data types</CAPTION>

@ -109,7 +109,7 @@ psb_geamax(x, desc_a, info)
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1507"></A>
<DIV ALIGN="CENTER"><A NAME="1513"></A>
<TABLE>
<CAPTION><STRONG>Table 4:</STRONG>
Data types</CAPTION>

@ -84,7 +84,7 @@ call psb_geamaxs(res, x, desc_a, info)
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1508"></A>
<DIV ALIGN="CENTER"><A NAME="1514"></A>
<TABLE>
<CAPTION><STRONG>Table 5:</STRONG>
Data types</CAPTION>

@ -108,7 +108,7 @@ psb_geasum(x, desc_a, info)
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1509"></A>
<DIV ALIGN="CENTER"><A NAME="1515"></A>
<TABLE>
<CAPTION><STRONG>Table 6:</STRONG>
Data types</CAPTION>

@ -128,7 +128,7 @@ call psb_geasums(res, x, desc_a, info)
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1510"></A>
<DIV ALIGN="CENTER"><A NAME="1516"></A>
<TABLE>
<CAPTION><STRONG>Table 7:</STRONG>
Data types</CAPTION>

@ -103,7 +103,7 @@ nrm2 \leftarrow \sqrt{x^H x}
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1511"></A>
<DIV ALIGN="CENTER"><A NAME="1517"></A>
<TABLE>
<CAPTION><STRONG>Table 8:</STRONG>
Data types</CAPTION>

@ -84,7 +84,7 @@ call psb_genrm2s(res, x, desc_a, info)
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1512"></A>
<DIV ALIGN="CENTER"><A NAME="1518"></A>
<TABLE>
<CAPTION><STRONG>Table 9:</STRONG>
Data types</CAPTION>

@ -92,7 +92,7 @@ where:
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1513"></A>
<DIV ALIGN="CENTER"><A NAME="1519"></A>
<TABLE>
<CAPTION><STRONG>Table 10:</STRONG>
Data types</CAPTION>

@ -157,7 +157,7 @@ where:
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1514"></A>
<DIV ALIGN="CENTER"><A NAME="1520"></A>
<TABLE>
<CAPTION><STRONG>Table 11:</STRONG>
Data types</CAPTION>

@ -137,7 +137,7 @@ call psb_spsm(alpha, t, x, beta, y, desc_a, info,&amp;
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="1515"></A>
<DIV ALIGN="CENTER"><A NAME="1521"></A>
<TABLE>
<CAPTION><STRONG>Table 12:</STRONG>
Data types</CAPTION>

@ -112,7 +112,7 @@ on it. Whenever performing a computational step, such as a
matrix-vector product, the values associated with halo points are
requested from other domains. A boundary point of a given
domain is usually a halo point for some other domain<A NAME="tex2html3"
HREF="footnode.html#foot174"><SUP>2</SUP></A>; therefore
HREF="footnode.html#foot176"><SUP>2</SUP></A>; therefore
the cardinality of the boundary points set denotes the amount of data
sent to other domains.
</DD>
@ -126,8 +126,8 @@ Overlap points do not usually exist in the basic data
distributions; however they are a feature of Domain Decomposition
Schwarz preconditioners which are the subject of related research
work&nbsp;[<A
HREF="node108.html#2007c">3</A>,<A
HREF="node108.html#2007d">2</A>].
HREF="node108.html#2007c">4</A>,<A
HREF="node108.html#2007d">3</A>].
<P>
We denote the sets of internal, boundary and halo points for a given
@ -166,7 +166,7 @@ local rows) is <!-- MATH
<P>
<DIV ALIGN="CENTER"><A NAME="fig:points"></A><A NAME="226"></A>
<DIV ALIGN="CENTER"><A NAME="fig:points"></A><A NAME="228"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 2:</STRONG>
Point classfication.</CAPTION>

@ -87,7 +87,7 @@ where:
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="2749"></A>
<DIV ALIGN="CENTER"><A NAME="2755"></A>
<TABLE>
<CAPTION><STRONG>Table 13:</STRONG>
Data types</CAPTION>
@ -248,7 +248,7 @@ An integer value that contains an error code.
</DD>
</DL>
<DIV ALIGN="CENTER"><A NAME="fig:try8x8"></A><A NAME="2751"></A>
<DIV ALIGN="CENTER"><A NAME="fig:try8x8"></A><A NAME="2757"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 7:</STRONG>
Sample discretization mesh.</CAPTION>

@ -102,7 +102,7 @@ operators <IMG
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="2753"></A>
<DIV ALIGN="CENTER"><A NAME="2759"></A>
<TABLE>
<CAPTION><STRONG>Table 14:</STRONG>
Data types</CAPTION>
@ -288,7 +288,7 @@ their instances.
<P>
<DIV ALIGN="CENTER"><A NAME="fig:try8x8_ov"></A><A NAME="2755"></A>
<DIV ALIGN="CENTER"><A NAME="fig:try8x8_ov"></A><A NAME="2761"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 8:</STRONG>
Sample discretization mesh.</CAPTION>

@ -110,7 +110,7 @@ process <IMG
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="2757"></A>
<DIV ALIGN="CENTER"><A NAME="2763"></A>
<TABLE>
<CAPTION><STRONG>Table 15:</STRONG>
Data types</CAPTION>

@ -108,7 +108,7 @@ process <IMG
<P>
<BR><P></P>
<DIV ALIGN="CENTER"><A NAME="2758"></A>
<DIV ALIGN="CENTER"><A NAME="2764"></A>
<TABLE>
<CAPTION><STRONG>Table 16:</STRONG>
Data types</CAPTION>

@ -166,7 +166,7 @@ Specified as: an allocatable integer array of rank one.
The Fortran&nbsp;95 definition for <code>psb_desc_type</code> structures is
as follows:
<DIV ALIGN="CENTER"><A NAME="fig:desctype"></A><A NAME="668"></A>
<DIV ALIGN="CENTER"><A NAME="fig:desctype"></A><A NAME="674"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 3:</STRONG>
The PSBLAS defined data type that

@ -94,7 +94,7 @@ explicitly.
<P>
<DIV ALIGN="CENTER"><A NAME="fig:routerr"></A><A NAME="6475"></A>
<DIV ALIGN="CENTER"><A NAME="fig:routerr"></A><A NAME="6481"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 9:</STRONG>
The layout of a generic <TT>psb_foo</TT>
@ -124,7 +124,7 @@ called by <code>psb_spasb</code> ... by process 0 (i.e. the root process).
<P>
<DIV ALIGN="CENTER"><A NAME="fig:errormsg"></A><A NAME="6476"></A>
<DIV ALIGN="CENTER"><A NAME="fig:errormsg"></A><A NAME="6482"></A>
<TABLE>
<CAPTION ALIGN="BOTTOM"><STRONG>Figure 10:</STRONG>
A sample PSBLAS-2.0 error

File diff suppressed because it is too large Load Diff

@ -86,7 +86,7 @@
TOPFILE = userguide.tex
HTMLFILE = userhtml.tex
SECFILE = intro.tex commrout.tex datastruct.tex psbrout.tex toolsrout.tex\
methods.tex precs.tex penv.tex error.tex util.tex
methods.tex precs.tex penv.tex error.tex util.tex biblio.tex
FIGDIR = figures
XPDFFLAGS =

@ -0,0 +1,165 @@
\begin{thebibliography}{99}
\bibitem{DesPat:11}
D.~Barbieri, V.~Cardellini, S.~Filippone and D.~Rouson
{\em Design Patterns for Scientific Computations on Sparse Matrices},
HPSS 2011, Algorithms and Programming Tools for Next-Generation High-Performance Scientific Software, Bordeaux, Sep. 2011
\bibitem{PARA04FOREST}
G.~Bella, S.~Filippone, A.~De Maio and M.~Testa,
{\em A Simulation Model for Forest Fires},
in J.~Dongarra, K.~Madsen, J.~Wasniewski, editors,
Proceedings of PARA~04 Workshop on State of the Art
in Scientific Computing, pp.~546--553, Lecture Notes in Computer Science,
Springer, 2005.
\bibitem{2007d} A. Buttari, D. di Serafino, P. D'Ambra, S. Filippone,\newblock
2LEV-D2P4: a package of high-performance preconditioners,\newblock
Applicable Algebra in Engineering, Communications and Computing,
Volume 18, Number 3, May, 2007, pp. 223-239
%Published online: 13 February 2007, {\tt http://dx.doi.org/10.1007/s00200-007-0035-z}
%
\bibitem{2007c} P. D'Ambra, S. Filippone, D. Di Serafino\newblock
On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners
\newblock
Applied Numerical Mathematics, Elsevier Science,
Volume 57, Issues 11-12, November-December 2007, Pages 1181-1196.
%published online 3 February 2007, {\tt
% http://dx.doi.org/10.1016/j.apnum.2007.01.006}
\bibitem{BLAS2}
Dongarra, J. J., DuCroz, J., Hammarling, S. and Hanson, R.,
An Extended Set of {F}ortran {B}asic {L}inear {A}lgebra {S}ubprograms,
{ACM Trans. Math. Softw.} vol.~{14}, 1--17, 1988.
\bibitem{BLAS3}
Dongarra, J., DuCroz, J., Hammarling, S. and Duff, I.,
A Set of level 3 Basic Linear Algebra Subprograms,
{ACM Trans. Math. Softw.} vol.~{16}, 1--17, 1990.
%% \bibitem{DOUGLAS}
%% R.E.~Bank and C.C.~Douglas,
%% {\em SMMP: Sparse Matrix Multiplication Package},
%% Advances in Computational Mathematics, 1993, 1, 127-137.
%% (See also {\tt http://www.mgnet.org/~douglas/ccd-codes.html})
%
%
%% \bibitem{PARA04}
%% A.~Buttari, P.~D'Ambra, D.~di Serafino and S.~Filippone,
%% {\em 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, pp.~593--602, Lecture Notes in Computer Science,
%% Springer, 2005.
%
%% \bibitem{CAI_SAAD}
%% X.~C.~Cai and Y.~Saad,
%% {\em Overlapping Domain Decomposition Algorithms for General Sparse Matrices},
%% Numerical Linear Algebra with Applications, 3(3), pp.~221--237, 1996.
%% %
%% \bibitem{CAI_SARKIS}
%% X.C.~Cai and M.~Sarkis,
%% {\em A Restricted Additive Schwarz Preconditioner for General Sparse Linear Systems},
%% SIAM Journal on Scientific Computing, 21(2), pp.~792--797, 1999.
%
%% \bibitem{CAI_WIDLUND}
%% X.C.~Cai and O.~B.~Widlund,
%% {\em Domain Decomposition Algorithms for Indefinite Elliptic Problems},
%% SIAM Journal on Scientific and Statistical Computing, 13(1), pp.~243--258, 1992.
%
%% \bibitem{DD1}
%% T.~Chan and T.~Mathew,
%% {\em Domain Decomposition Algorithms},
%% in A.~Iserles, editor, Acta Numerica 1994, pp.~61--143, 1994.
%% Cambridge University Press.
%% %
%% \bibitem{APNUM06}
%% P.~D'Ambra, D.~di Serafino and S.~Filippone,
%% On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners,
%% Applied Numerical Mathematics, to appear, 2007.
%
%% \bibitem{UMFPACK}
%% T.A.~Davis,
%% {\em Algorithm 832: UMFPACK - an Unsymmetric-pattern Multifrontal
%% Method with a Column Pre-ordering Strategy},
%% ACM Transactions on Mathematical Software, 30, pp.~196--199, 2004.
%% (See also {\tt http://www.cise.ufl.edu/~davis/})
%% %
%% \bibitem{SUPERLU}
%% J.W.~Demmel, S.C.~Eisenstat, J.R.~Gilbert, X.S.~Li and J.W.H.~Liu,
%% A supernodal approach to sparse partial pivoting,
%% SIAM Journal on Matrix Analysis and Applications, 20(3), pp.~720--755, 1999.
%
\bibitem{BLACS}
J.~J.~Dongarra and R.~C.~Whaley,
{\em A User's Guide to the BLACS v.~1.1},
Lapack Working Note 94, Tech.\ Rep.\ UT-CS-95-281, University of
Tennessee, March 1995 (updated May 1997).
%
\bibitem{sblas97}
I.~Duff, M.~Marrone, G.~Radicati and C.~Vittoli,
{\em Level 3 Basic Linear Algebra Subprograms for Sparse Matrices:
a User Level Interface},
ACM Transactions on Mathematical Software, 23(3), pp.~379--401, 1997.
%
\bibitem{sblas02}
I.~Duff, M.~Heroux and R.~Pozo,
{\em An Overview of the Sparse Basic Linear
Algebra Subprograms: the New Standard from the BLAS Technical Forum},
ACM Transactions on Mathematical Software, 28(2), pp.~239--267, 2002.
\bibitem{PSBLAS}
S.~Filippone and M.~Colajanni,
{\em PSBLAS: A Library for Parallel Linear Algebra
Computation on Sparse Matrices},
\newblock
ACM Transactions on Mathematical Software, 26(4), pp.~527--550, 2000.
%
\bibitem{Sparse03}
S.~Filippone and A.~Buttari,
{\em Object-Oriented Techniques for Sparse Matrix Computations in Fortran 2003},
\newblock
ACM Transactions on Mathematical Software, to appear.
%
\bibitem{KIVA3PSBLAS}
S.~Filippone, P.~D'Ambra, M.~Colajanni,
{\em Using a Parallel Library of Sparse Linear Algebra in a Fluid Dynamics
Applications Code on Linux Clusters},
in G.~Joubert, A.~Murli, F.~Peters, M.~Vanneschi, editors,
Parallel Computing - Advances \& Current Issues,
pp.~441--448, Imperial College Press, 2002.
%
\bibitem{METIS}
Karypis, G. and Kumar, V.,
{\em {METIS}: Unstructured Graph Partitioning and Sparse Matrix
Ordering System}.
Minneapolis, MN 55455: University of Minnesota, Department of
Computer Science, 1995.
Internet Address: {\verb|http://www.cs.umn.edu/~karypis|}.
\bibitem{BLAS1}
Lawson, C., Hanson, R., Kincaid, D. and Krogh, F.,
Basic {L}inear {A}lgebra {S}ubprograms for {F}ortran usage,
{ACM Trans. Math. Softw.} vol.~{5}, 38--329, 1979.
\bibitem{machiels}
{Machiels, L. and Deville, M.}
{\em Fortran 90: An entry to object-oriented programming for the solution
of partial differential equations.}
{ACM Trans. Math. Softw.} vol.~{23}, 32--49.
\bibitem{metcalf}
{Metcalf, M., Reid, J. and Cohen, M.}
{\em Fortran 95/2003 explained.}
{Oxford University Press}, 2004.
%
%% \bibitem{DD2}
%% B.~Smith, P.~Bjorstad and W.~Gropp,
%% {\em Domain Decomposition: Parallel Multilevel Methods for Elliptic
%% Partial Differential Equations},
%% Cambridge University Press, 1996.
%
\bibitem{RouXiaXu:11}
Rouson, D.W.I., Xia, J., Xu, X.: {Scientific Software Design: The
Object-Oriented Way}. Cambridge University Press (2011)
\bibitem{MPI1}
M.~Snir, S.~Otto, S.~Huss-Lederman, D.~Walker and J.~Dongarra,
{\em MPI: The Complete Reference. Volume 1 - The MPI Core}, second edition,
MIT Press, 1998.
%
\end{thebibliography}

@ -11,11 +11,21 @@ dense matrix operations. The current implementation of PSBLAS
addresses a distributed memory execution model operating with message
passing.
The PSBLAS library is internally implemented in
the Fortran~95~\cite{metcalf} programming language, with reuse and/or
The PSBLAS library version 3 is internally implemented in
the Fortran~2003~\cite{metcalf} programming language, with reuse and/or
adaptation of some existing Fortran~77 software, and a handful of C
routines.
A similar approach has been advocated by a number of authors,
The use of Fortran~2003 offers a number of advantages over Fortran~95,
mostly in the handling of requirements for evolution and adaptation of
the library to new computing architectures and integration of
new algorithms.
For a detailed discussion of our design see~\cite{Sparse03}; other
works tackling advanced programming in Fortran~2003 include~\cite{DesPat:11,RouXiaXu:11}
Previous approaches have been based on mixing Fortran~95, with its
support for object-based design, with other languages; these have
been advocated by a number of authors,
e.g.~\cite{machiels}. Moreover, the Fortran~95 facilities for dynamic
memory management and interface overloading greatly enhance the
usability of the PSBLAS

@ -131,157 +131,7 @@ May 15th, 2010.
\include{methods}
\cleardoublepage
\begin{thebibliography}{99}
\bibitem{PARA04FOREST}
G.~Bella, S.~Filippone, A.~De Maio and M.~Testa,
{\em A Simulation Model for Forest Fires},
in J.~Dongarra, K.~Madsen, J.~Wasniewski, editors,
Proceedings of PARA~04 Workshop on State of the Art
in Scientific Computing, pp.~546--553, Lecture Notes in Computer Science,
Springer, 2005.
\bibitem{2007d} A. Buttari, D. di Serafino, P. D'Ambra, S. Filippone,\newblock
2LEV-D2P4: a package of high-performance preconditioners,\newblock
Applicable Algebra in Engineering, Communications and Computing,
Volume 18, Number 3, May, 2007, pp. 223-239
%Published online: 13 February 2007, {\tt http://dx.doi.org/10.1007/s00200-007-0035-z}
%
\bibitem{2007c} P. D'Ambra, S. Filippone, D. Di Serafino\newblock
On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners
\newblock
Applied Numerical Mathematics, Elsevier Science,
Volume 57, Issues 11-12, November-December 2007, Pages 1181-1196.
%published online 3 February 2007, {\tt
% http://dx.doi.org/10.1016/j.apnum.2007.01.006}
\bibitem{BLAS2}
Dongarra, J. J., DuCroz, J., Hammarling, S. and Hanson, R.,
An Extended Set of {F}ortran {B}asic {L}inear {A}lgebra {S}ubprograms,
{ACM Trans. Math. Softw.} vol.~{14}, 1--17, 1988.
\bibitem{BLAS3}
Dongarra, J., DuCroz, J., Hammarling, S. and Duff, I.,
A Set of level 3 Basic Linear Algebra Subprograms,
{ACM Trans. Math. Softw.} vol.~{16}, 1--17, 1990.
%% \bibitem{DOUGLAS}
%% R.E.~Bank and C.C.~Douglas,
%% {\em SMMP: Sparse Matrix Multiplication Package},
%% Advances in Computational Mathematics, 1993, 1, 127-137.
%% (See also {\tt http://www.mgnet.org/~douglas/ccd-codes.html})
%
%
%% \bibitem{PARA04}
%% A.~Buttari, P.~D'Ambra, D.~di Serafino and S.~Filippone,
%% {\em 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, pp.~593--602, Lecture Notes in Computer Science,
%% Springer, 2005.
%
%% \bibitem{CAI_SAAD}
%% X.~C.~Cai and Y.~Saad,
%% {\em Overlapping Domain Decomposition Algorithms for General Sparse Matrices},
%% Numerical Linear Algebra with Applications, 3(3), pp.~221--237, 1996.
%% %
%% \bibitem{CAI_SARKIS}
%% X.C.~Cai and M.~Sarkis,
%% {\em A Restricted Additive Schwarz Preconditioner for General Sparse Linear Systems},
%% SIAM Journal on Scientific Computing, 21(2), pp.~792--797, 1999.
%
%% \bibitem{CAI_WIDLUND}
%% X.C.~Cai and O.~B.~Widlund,
%% {\em Domain Decomposition Algorithms for Indefinite Elliptic Problems},
%% SIAM Journal on Scientific and Statistical Computing, 13(1), pp.~243--258, 1992.
%
%% \bibitem{DD1}
%% T.~Chan and T.~Mathew,
%% {\em Domain Decomposition Algorithms},
%% in A.~Iserles, editor, Acta Numerica 1994, pp.~61--143, 1994.
%% Cambridge University Press.
%% %
%% \bibitem{APNUM06}
%% P.~D'Ambra, D.~di Serafino and S.~Filippone,
%% On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners,
%% Applied Numerical Mathematics, to appear, 2007.
%
%% \bibitem{UMFPACK}
%% T.A.~Davis,
%% {\em Algorithm 832: UMFPACK - an Unsymmetric-pattern Multifrontal
%% Method with a Column Pre-ordering Strategy},
%% ACM Transactions on Mathematical Software, 30, pp.~196--199, 2004.
%% (See also {\tt http://www.cise.ufl.edu/~davis/})
%% %
%% \bibitem{SUPERLU}
%% J.W.~Demmel, S.C.~Eisenstat, J.R.~Gilbert, X.S.~Li and J.W.H.~Liu,
%% A supernodal approach to sparse partial pivoting,
%% SIAM Journal on Matrix Analysis and Applications, 20(3), pp.~720--755, 1999.
%
\bibitem{BLACS}
J.~J.~Dongarra and R.~C.~Whaley,
{\em A User's Guide to the BLACS v.~1.1},
Lapack Working Note 94, Tech.\ Rep.\ UT-CS-95-281, University of
Tennessee, March 1995 (updated May 1997).
%
\bibitem{sblas97}
I.~Duff, M.~Marrone, G.~Radicati and C.~Vittoli,
{\em Level 3 Basic Linear Algebra Subprograms for Sparse Matrices:
a User Level Interface},
ACM Transactions on Mathematical Software, 23(3), pp.~379--401, 1997.
%
\bibitem{sblas02}
I.~Duff, M.~Heroux and R.~Pozo,
{\em An Overview of the Sparse Basic Linear
Algebra Subprograms: the New Standard from the BLAS Technical Forum},
ACM Transactions on Mathematical Software, 28(2), pp.~239--267, 2002.
\bibitem{PSBLAS}
S.~Filippone and M.~Colajanni,
{\em PSBLAS: A Library for Parallel Linear Algebra
Computation on Sparse Matrices},
\newblock
ACM Transactions on Mathematical Software, 26(4), pp.~527--550, 2000.
%
\bibitem{KIVA3PSBLAS}
S.~Filippone, P.~D'Ambra, M.~Colajanni,
{\em Using a Parallel Library of Sparse Linear Algebra in a Fluid Dynamics
Applications Code on Linux Clusters},
in G.~Joubert, A.~Murli, F.~Peters, M.~Vanneschi, editors,
Parallel Computing - Advances \& Current Issues,
pp.~441--448, Imperial College Press, 2002.
%
\bibitem{METIS}
Karypis, G. and Kumar, V.,
{\em {METIS}: Unstructured Graph Partitioning and Sparse Matrix
Ordering System}.
Minneapolis, MN 55455: University of Minnesota, Department of
Computer Science, 1995.
Internet Address: {\verb|http://www.cs.umn.edu/~karypis|}.
\bibitem{BLAS1}
Lawson, C., Hanson, R., Kincaid, D. and Krogh, F.,
Basic {L}inear {A}lgebra {S}ubprograms for {F}ortran usage,
{ACM Trans. Math. Softw.} vol.~{5}, 38--329, 1979.
\bibitem{machiels}
{Machiels, L. and Deville, M.}
{\em Fortran 90: An entry to object-oriented programming for the solution
of partial differential equations.}
{ACM Trans. Math. Softw.} vol.~{23}, 32--49.
\bibitem{metcalf}
{Metcalf, M., Reid, J. and Cohen, M.}
{\em Fortran 95/2003 explained.}
{Oxford University Press}, 2004.
%
%% \bibitem{DD2}
%% B.~Smith, P.~Bjorstad and W.~Gropp,
%% {\em Domain Decomposition: Parallel Multilevel Methods for Elliptic
%% Partial Differential Equations},
%% Cambridge University Press, 1996.
%
\bibitem{MPI1}
M.~Snir, S.~Otto, S.~Huss-Lederman, D.~Walker and J.~Dongarra,
{\em MPI: The Complete Reference. Volume 1 - The MPI Core}, second edition,
MIT Press, 1998.
%
\end{thebibliography}
\input{biblio}
\end{document}
%%% Local Variables:

@ -112,156 +112,7 @@ May 15th, 2010
\cleardoublepage
\begin{thebibliography}{99}
\bibitem{PARA04FOREST}
G.~Bella, S.~Filippone, A.~De Maio and M.~Testa,
{\em A Simulation Model for Forest Fires},
in J.~Dongarra, K.~Madsen, J.~Wasniewski, editors,
Proceedings of PARA~04 Workshop on State of the Art
in Scientific Computing, pp.~546--553, Lecture Notes in Computer Science,
Springer, 2005.
\bibitem{2007d} A. Buttari, D. di Serafino, P. D'Ambra, S. Filippone,\newblock
2LEV-D2P4: a package of high-performance preconditioners,\newblock
Applicable Algebra in Engineering, Communications and Computing,
Volume 18, Number 3, May, 2007, pp. 223-239
%Published online: 13 February 2007, {\tt http://dx.doi.org/10.1007/s00200-007-0035-z}
%
\bibitem{2007c} P. D'Ambra, S. Filippone, D. Di Serafino\newblock
On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners
\newblock
Applied Numerical Mathematics, Elsevier Science,
Volume 57, Issues 11-12, November-December 2007, Pages 1181-1196.
%published online 3 February 2007, {\tt
% http://dx.doi.org/10.1016/j.apnum.2007.01.006}
\bibitem{BLAS2}
Dongarra, J. J., DuCroz, J., Hammarling, S. and Hanson, R.,
An Extended Set of {F}ortran {B}asic {L}inear {A}lgebra {S}ubprograms,
{ACM Trans. Math. Softw.} vol.~{14}, 1--17, 1988.
\bibitem{BLAS3}
Dongarra, J., DuCroz, J., Hammarling, S. and Duff, I.,
A Set of level 3 Basic Linear Algebra Subprograms,
{ACM Trans. Math. Softw.} vol.~{16}, 1--17, 1990.
%% \bibitem{DOUGLAS}
%% R.E.~Bank and C.C.~Douglas,
%% {\em SMMP: Sparse Matrix Multiplication Package},
%% Advances in Computational Mathematics, 1993, 1, 127-137.
%% (See also {\tt http://www.mgnet.org/~douglas/ccd-codes.html})
%
%
%% \bibitem{PARA04}
%% A.~Buttari, P.~D'Ambra, D.~di Serafino and S.~Filippone,
%% {\em 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, pp.~593--602, Lecture Notes in Computer Science,
%% Springer, 2005.
%
%% \bibitem{CAI_SAAD}
%% X.~C.~Cai and Y.~Saad,
%% {\em Overlapping Domain Decomposition Algorithms for General Sparse Matrices},
%% Numerical Linear Algebra with Applications, 3(3), pp.~221--237, 1996.
%% %
%% \bibitem{CAI_SARKIS}
%% X.C.~Cai and M.~Sarkis,
%% {\em A Restricted Additive Schwarz Preconditioner for General Sparse Linear Systems},
%% SIAM Journal on Scientific Computing, 21(2), pp.~792--797, 1999.
%
%% \bibitem{CAI_WIDLUND}
%% X.C.~Cai and O.~B.~Widlund,
%% {\em Domain Decomposition Algorithms for Indefinite Elliptic Problems},
%% SIAM Journal on Scientific and Statistical Computing, 13(1), pp.~243--258, 1992.
%
%% \bibitem{DD1}
%% T.~Chan and T.~Mathew,
%% {\em Domain Decomposition Algorithms},
%% in A.~Iserles, editor, Acta Numerica 1994, pp.~61--143, 1994.
%% Cambridge University Press.
%% %
%% \bibitem{APNUM06}
%% P.~D'Ambra, D.~di Serafino and S.~Filippone,
%% On the Development of PSBLAS-based Parallel Two-level Schwarz Preconditioners,
%% Applied Numerical Mathematics, to appear, 2007.
%
%% \bibitem{UMFPACK}
%% T.A.~Davis,
%% {\em Algorithm 832: UMFPACK - an Unsymmetric-pattern Multifrontal
%% Method with a Column Pre-ordering Strategy},
%% ACM Transactions on Mathematical Software, 30, pp.~196--199, 2004.
%% (See also {\tt http://www.cise.ufl.edu/~davis/})
%% %
%% \bibitem{SUPERLU}
%% J.W.~Demmel, S.C.~Eisenstat, J.R.~Gilbert, X.S.~Li and J.W.H.~Liu,
%% A supernodal approach to sparse partial pivoting,
%% SIAM Journal on Matrix Analysis and Applications, 20(3), pp.~720--755, 1999.
%
\bibitem{BLACS}
J.~J.~Dongarra and R.~C.~Whaley,
{\em A User's Guide to the BLACS v.~1.1},
Lapack Working Note 94, Tech.\ Rep.\ UT-CS-95-281, University of
Tennessee, March 1995 (updated May 1997).
%
\bibitem{sblas97}
I.~Duff, M.~Marrone, G.~Radicati and C.~Vittoli,
{\em Level 3 Basic Linear Algebra Subprograms for Sparse Matrices:
a User Level Interface},
ACM Transactions on Mathematical Software, 23(3), pp.~379--401, 1997.
%
\bibitem{sblas02}
I.~Duff, M.~Heroux and R.~Pozo,
{\em An Overview of the Sparse Basic Linear
Algebra Subprograms: the New Standard from the BLAS Technical Forum},
ACM Transactions on Mathematical Software, 28(2), pp.~239--267, 2002.
\bibitem{PSBLAS}
S.~Filippone and M.~Colajanni,
{\em PSBLAS: A Library for Parallel Linear Algebra
Computation on Sparse Matrices},
\newblock
ACM Transactions on Mathematical Software, 26(4), pp.~527--550, 2000.
%
\bibitem{KIVA3PSBLAS}
S.~Filippone, P.~D'Ambra, M.~Colajanni,
{\em Using a Parallel Library of Sparse Linear Algebra in a Fluid Dynamics
Applications Code on Linux Clusters},
in G.~Joubert, A.~Murli, F.~Peters, M.~Vanneschi, editors,
Parallel Computing - Advances \& Current Issues,
pp.~441--448, Imperial College Press, 2002.
%
\bibitem{METIS}
Karypis, G. and Kumar, V.,
{\em {METIS}: Unstructured Graph Partitioning and Sparse Matrix
Ordering System}.
Minneapolis, MN 55455: University of Minnesota, Department of
Computer Science, 1995.
Internet Address: {\verb|http://www.cs.umn.edu/~karypis|}.
\bibitem{BLAS1}
Lawson, C., Hanson, R., Kincaid, D. and Krogh, F.,
Basic {L}inear {A}lgebra {S}ubprograms for {F}ortran usage,
{ACM Trans. Math. Softw.} vol.~{5}, 38--329, 1979.
\bibitem{machiels}
{Machiels, L. and Deville, M.}
{\em Fortran 90: An entry to object-oriented programming for the solution
of partial differential equations.}
{ACM Trans. Math. Softw.} vol.~{23}, 32--49.
\bibitem{metcalf}
{Metcalf, M., Reid, J. and Cohen, M.}
{\em Fortran 95/2003 explained.}
{Oxford University Press}, 2004.
%
%% \bibitem{DD2}
%% B.~Smith, P.~Bjorstad and W.~Gropp,
%% {\em Domain Decomposition: Parallel Multilevel Methods for Elliptic
%% Partial Differential Equations},
%% Cambridge University Press, 1996.
%
\bibitem{MPI1}
M.~Snir, S.~Otto, S.~Huss-Lederman, D.~Walker and J.~Dongarra,
{\em MPI: The Complete Reference. Volume 1 - The MPI Core}, second edition,
MIT Press, 1998.
%
\end{thebibliography}
\input{biblio}
\end{document}
%%% Local Variables:

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