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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
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docs/src/intro.tex
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@@ -21,7 +21,11 @@ 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}
works discussing advanced programming in Fortran~2003
include~\cite{DesPat:11,RouXiaXu:11}; sufficient support for
Fortran~2003 is now available from many compilers, including the GNU
Fortran compiler from the Free Software Foundation (as of version 4.6).
Previous approaches have been based on mixing Fortran~95, with its
support for object-based design, with other languages; these have
@@ -32,12 +36,7 @@ usability of the PSBLAS
subroutines. In this way, the library can take care of runtime memory
requirements that are quite difficult or even impossible to predict at
implementation or compilation time.
In the current release we rely on the availability of the so-called
allocatable extensions, specified in TR~15581. Strictly speaking they
are outside the Fortran~95 standard; however they have been included
in the Fortran~2003 language standard, and are available in
practically all Fortran~95 compilers on the market, including the GNU
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~\cite{sblas97,sblas02}, which in its turn is based on the
@@ -84,20 +83,16 @@ influenced by the structure of the ScaLAPACK parallel
library. The layered structure of the PSBLAS library
is shown in figure~\ref{fig:psblas}; lower layers of the library
indicate an encapsulation relationship with upper layers. The ongoing
discussion focuses on the Fortran~95 layer immediately below the
discussion focuses on the Fortran~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
Linear Algebra Communication Subroutines (BLACS) library~\cite{BLACS}
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.
In any case we provide wrappers around the BLACS routines so that the
user does not need to delve into their details (see Sec.~\ref{sec:parenv}).
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~\cite{BLACS}.
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.~\ref{sec:parenv}.
%% We assume that the user program has initialized a BLACS process grid
%% with one column and as many rows as there are processes; the PSBLAS
%% initialization routines will take the communication context for this
@@ -136,10 +131,12 @@ sub-domains}.
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 \verb|CYCLIC(N)| and \verb|BLOCK|,
This choice is consistent with simple data distributions
%commonly used in ScaLAPACK
such as \verb|CYCLIC(N)| and \verb|BLOCK|,
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~\cite{METIS}.
Dense vectors conform to sparse