From e9fe376985c19bec63660493e713c969384381fa Mon Sep 17 00:00:00 2001
From: Markus Blatt <mblatt@dune-project.org>
Date: Thu, 7 Feb 2013 13:36:06 +0000
Subject: [PATCH] Moving the documentation for the parallel index sets to
dune-common.
The index sets themselves are already there.
Step 1: copying files from dune-istl to dune-common
[[Imported from SVN: r7110]]
---
doc/Makefile.am | 2 +-
doc/comm/Makefile.am | 54 +
doc/comm/buildindexset.hh | 55 +
doc/comm/communication.bib | 79 +
doc/comm/communication.tex | 543 ++++
doc/comm/figures/Makefile.am | 5 +
doc/comm/figures/darray.eps | 230 ++
doc/comm/figures/distarray.eps | 1278 +++++++++
doc/comm/figures/distindex.eps | 4736 ++++++++++++++++++++++++++++++++
doc/comm/indexset.cc | 55 +
doc/comm/poosc08.cc | 92 +
doc/comm/poosc08_test.cc | 155 ++
doc/comm/reverse.hh | 39 +
13 files changed, 7322 insertions(+), 1 deletion(-)
create mode 100644 doc/comm/Makefile.am
create mode 100644 doc/comm/buildindexset.hh
create mode 100644 doc/comm/communication.bib
create mode 100644 doc/comm/communication.tex
create mode 100644 doc/comm/figures/Makefile.am
create mode 100644 doc/comm/figures/darray.eps
create mode 100644 doc/comm/figures/distarray.eps
create mode 100644 doc/comm/figures/distindex.eps
create mode 100644 doc/comm/indexset.cc
create mode 100644 doc/comm/poosc08.cc
create mode 100644 doc/comm/poosc08_test.cc
create mode 100644 doc/comm/reverse.hh
diff --git a/doc/Makefile.am b/doc/Makefile.am
index 6102a59aa..caa75253a 100644
--- a/doc/Makefile.am
+++ b/doc/Makefile.am
@@ -1,7 +1,7 @@
# $Id$
# also build these sub directories
-SUBDIRS = doxygen buildsystem
+SUBDIRS = doxygen buildsystem comm
# setting like in dune-web
CURDIR=doc
diff --git a/doc/comm/Makefile.am b/doc/comm/Makefile.am
new file mode 100644
index 000000000..722b61b35
--- /dev/null
+++ b/doc/comm/Makefile.am
@@ -0,0 +1,54 @@
+# $Id: Makefile.am 1681 2012-08-31 11:30:17Z gruenich $
+
+SUBDIRS = figures
+
+MPIPROGRAMS = indexset poosc08 poosc08_test
+
+# programs just to build when "make check" is used
+check_PROGRAMS = $(MPIPROGRAMS)
+# list of tests to run (indicestest is special case)
+TESTS = $(MPIPROGRAMS)
+
+if BUILD_DOCS
+ DOCFILES = communication.pdf
+ EXTRA_DIST = $(DOCFILES)
+ EXTRAINSTALL = $(DOCFILES)
+endif
+
+# setting like in dune-web
+CURDIR=doc/istl/comm
+BASEDIR=../../..
+
+# install the docs
+docdir=$(datadir)/doc/dune-istl/comm
+
+include $(top_srcdir)/am/latex
+include $(top_srcdir)/am/webstuff
+include $(top_srcdir)/am/global-rules
+
+poosc08_SOURCES = poosc08.cc
+poosc08_CPPFLAGS = $(AM_CPPFLAGS) \
+ $(DUNEMPICPPFLAGS)
+poosc08_LDFLAGS = $(AM_LDFLAGS) \
+ $(DUNEMPILDFLAGS)
+poosc08_LDADD = \
+ $(DUNEMPILIBS) \
+ $(LDADD)
+
+poosc08_test_SOURCES = poosc08_test.cc
+poosc08_test_CPPFLAGS = $(AM_CPPFLAGS) \
+ $(DUNEMPICPPFLAGS)
+poosc08_test_LDFLAGS = $(AM_LDFLAGS) \
+ $(DUNEMPILDFLAGS)
+poosc08_test_LDADD = \
+ $(DUNEMPILIBS) \
+ $(LDADD)
+
+indexset_SOURCES = indexset.cc buildindexset.hh reverse.hh
+indexset_CPPFLAGS = $(AM_CPPFLAGS) \
+ $(DUNEMPICPPFLAGS)
+indexset_LDFLAGS = $(AM_LDFLAGS) \
+ $(DUNEMPILDFLAGS)
+indexset_LDADD = \
+ $(DUNEMPILIBS) \
+ $(LDADD)
diff --git a/doc/comm/buildindexset.hh b/doc/comm/buildindexset.hh
new file mode 100644
index 000000000..3a122ebfc
--- /dev/null
+++ b/doc/comm/buildindexset.hh
@@ -0,0 +1,55 @@
+// -*- tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 2 -*-
+// vi: set et ts=4 sw=2 sts=2:
+// $Id: buildindexset.hh 1565 2012-04-30 22:04:34Z mblatt $
+#ifndef BUILDINDEXSET_HH
+#define BUILDINDEXSET_HH
+
+
+#include <dune/common/parallel/indexset.hh>
+#include <dune/common/parallel/plocalindex.hh>
+
+/**
+ * @brief Flag for marking the indices.
+ */
+enum Flag {owner, overlap};
+
+// The type of local index we use
+typedef Dune::ParallelLocalIndex<Flag> LocalIndex;
+
+/**
+ * @brief Add indices to the example index set.
+ * @param indexSet The index set to build.
+ */
+template<class C, class TG, int N>
+void build(C& comm, Dune::ParallelIndexSet<TG,LocalIndex,N>& indexSet)
+{
+
+
+
+
+ // The rank of our process
+ int rank=comm.rank();
+
+ // Indicate that we add or remove indices.
+ indexSet.beginResize();
+
+ if(rank==0) {
+ indexSet.add(0, LocalIndex(0,overlap,true));
+ indexSet.add(2, LocalIndex(1,owner,true));
+ indexSet.add(6, LocalIndex(2,owner,true));
+ indexSet.add(3, LocalIndex(3,owner,true));
+ indexSet.add(5, LocalIndex(4,owner,true));
+ }
+
+ if(rank==1) {
+ indexSet.add(0, LocalIndex(0,owner,true));
+ indexSet.add(1, LocalIndex(1,owner,true));
+ indexSet.add(7, LocalIndex(2,owner,true));
+ indexSet.add(5, LocalIndex(3,overlap,true));
+ indexSet.add(4, LocalIndex(4,owner,true));
+ }
+
+ // Modification is over
+ indexSet.endResize();
+}
+#endif
diff --git a/doc/comm/communication.bib b/doc/comm/communication.bib
new file mode 100644
index 000000000..8cd508d4c
--- /dev/null
+++ b/doc/comm/communication.bib
@@ -0,0 +1,79 @@
+@InProceedings{ISTL,
+ author = {Markus Blatt and Peter Bastian},
+ title = {The Iterative Solver Template Library},
+ booktitle = {Applied Parallel Computing. State of the Art in Scientific Computing},
+ editor = {Bo K\r{a}gstr\"om and Erik Elmroth and Jack Dongarra and Jerzy Wa\'sniewski},
+ year = 2007,
+ volume = 4699,
+ series = {Lecture Notes in Computer Science},
+ publisher = {Springer},
+ pages = {666--675}
+}
+
+@Article{dune08-1,
+ author = {Peter Bastian and Markus Blatt and Andreas Dedner and Christian Engwer and Robert Kl\"ofkorn and Mario Ohlberger and Oliver Sander},
+ title = { A generic grid interface for parallel and adaptive scientific computing. Part I: abstract framework},
+ journal = {Computing},
+ year = 2008,
+ volume = 82,
+ number = {2--3},
+ pages = {103--119}
+}
+@Article{dune08-2,
+ author = {Peter Bastian and Markus Blatt and Andreas Dedner and Christian Engwer and Robert Kl\"ofkorn and Ralf Kornhuber and Mario Ohlberger and Oliver Sander},
+ title = { A generic grid interface for parallel and adaptive scientific computing. Part II: implementation and test in DUNE},
+ journal = {Computing},
+ year = 2008,
+ volume = 82,
+ number = {2--3} ,
+ pages = {121--138}
+}
+@Article{ISTLParallel,
+ author = {Markus Blatt and Peter Bastian},
+ title = {On the Generic Parallelisation of Iterative Solvers for
+ the Finite Element Method},
+ journal = {Int. J. Computational Science and
+ Engineering},
+ volume = {4},
+ number = {1},
+ pages = {56--69},
+ year = 2008
+}
+
+@Misc{DuneWeb,
+ author = {DUNE},
+ howpublished = {\texttt{http://www.dune-project.org/}}
+}
+@Misc{boost_mpi,
+ author = {D. Gregor and M. Troyer},
+ title = {{B}oost.{M}{P}{I}},
+ howpublished = {\texttt{http://www.boost.org/}},
+ year = 2006
+}
+
+@PhdThesis{gerlach02:janus,
+ author = {Jens Gerlach},
+ title = {Domain Engineering and Generic Programming for Parallel Scientific Computing},
+ school = {TU Berlin},
+ year = {2002}
+}
+
+@InProceedings{giloi95:_promot,
+ author = {W.K. Giloi and M. Kessler and A. Schramm},
+ title = {PROMOTER: A High Level, Object-Parallel Programming Language},
+ booktitle = {Proceedings of the International Conference on High Performance Computing},
+ year = {1995},
+ address = {New Dehli, India},
+ month = {December}
+}
+
+@inproceedings{nolte00:_taco,
+ author = {J\"{o}rg Nolte and Mitsuhisa Sato and Yutaka Ishikawa},
+ title = {TACO -- Dynamic Distributed Collections with Templates and Topologies},
+ booktitle = {Euro-Par '00: Proceedings from the 6th International Euro-Par Conference on Parallel Processing},
+ year = {2000},
+ isbn = {3-540-67956-1},
+ pages = {1071--1080},
+ publisher = {Springer-Verlag},
+ address = {London, UK},
+ }
\ No newline at end of file
diff --git a/doc/comm/communication.tex b/doc/comm/communication.tex
new file mode 100644
index 000000000..b72887f52
--- /dev/null
+++ b/doc/comm/communication.tex
@@ -0,0 +1,543 @@
+\documentclass[11pt]{article}
+\usepackage{multicol}
+\usepackage{ifthen}
+%\usepackage{multitoc}
+%\usepackage{german}
+%\usepackage{bibgerm}
+\usepackage{amsthm}
+\usepackage{amsmath}
+\usepackage{amsfonts}
+\usepackage{color}
+\usepackage{hyperref}
+\usepackage{psfrag}
+\usepackage{subfigure}
+\usepackage[dvips]{epsfig}
+\usepackage[dvips]{graphicx}
+\usepackage[a4paper,body={148mm,240mm,nohead}]{geometry}
+\usepackage[ansinew]{inputenc}
+\usepackage{listings}
+\lstset{language=C++, basicstyle=\ttfamily,
+ stringstyle=\ttfamily, commentstyle=\it, extendedchars=true}
+
+\newif\ifpdf
+\ifnum\ifx\pdfoutput\undefined0\else\pdfoutput\fi<1
+\pdffalse % we are not running PDFLaTeX
+\else
+\pdftrue % we are running PDFLaTeX
+\fi
+
+\ifpdf
+\usepackage[pdftex]{graphicx}
+\else
+\usepackage{graphicx}
+\fi
+
+\ifpdf
+\DeclareGraphicsExtensions{.pdf, .jpg, .tif}
+\else
+\DeclareGraphicsExtensions{.eps, .jpg}
+\fi
+
+%\theoremstyle{plain}
+\newtheorem{theorem}{Theorem}[section]
+\newtheorem{lemma}[theorem]{Lemma}
+
+\theoremstyle{definition}
+\newtheorem{definition}[theorem]{Definition}
+\newtheorem{class}[theorem]{Class}
+\newtheorem{algorithm}[theorem]{Algorithm}
+\theoremstyle{remark}
+\newtheorem{remark}[theorem]{Remark}
+
+\newcommand{\C}{\mathbb{C}}
+\newcommand{\R}{\mathbb{R}}
+\newcommand{\N}{\mathbb{N}}
+\newcommand{\Z}{\mathbb{Z}}
+\newcommand{\Q}{\mathbb{Q}}
+\newcommand{\K}{\mathbb{K}}
+\newcommand{\loc}{\mbox{loc}}
+
+\title{Communication within the Iterative Solver Template Library (ISTL)\thanks{Part of the
+ Distributed and Unified Numerics Environment (DUNE) which is
+ available from the site
+ \texttt{http://www.dune-project.org/}}}
+
+\author{%
+Markus Blatt\\
+Interdisziplinäres Zentrum für Wissenschaftliches Rechnen,\\
+Universität Heidelberg, Im Neuenheimer Feld 368, D-69120 Heidelberg, \\
+email: \texttt{Markus.Blatt@iwr.uni-heidelberg.de}}
+
+\date{April 27, 2005}
+
+\begin{document}
+
+\maketitle
+
+\begin{abstract}
+ This document describes usage and interface of the classes meant for
+ setting up the communication within a parallel programm using
+ ISTL. As most of the communication in distributed programm occur in
+ the same pattern it is often more efficient (and of course more easy
+ for the programmer) to build the communication pattern once in the
+ programm and then use multiple times (e.~g. at each iteration step
+ of an iterative solver).
+\end{abstract}
+
+\begin{multicols}{2}
+{\small\tableofcontents}
+\end{multicols}
+
+
+\section{Introduction}
+\label{sec:introduction}
+
+When using the data parallel programming model a set of processes
+works collectively on the same set of finite data objects. These might
+be elements of a finite element grid or vector entries in a linear algebra
+computation. Each process works on different partitions of the global
+data. Only for this partition it computes updated values.
+
+In large scale parallel codes it is advisable to store the data
+partition in a local data structure directly in the local memory of
+the process. Due to data dependencies the process needs to access data
+in the partition of other processes, too. This can either be done by
+communicating these values on demand between the processes whenever
+they are accessed. This results in data structures that are aware of
+the data distribution. Or by augmenting the partition of the process such
+that it additionally includes the data values that the other values
+depend on. Note that now the partitioning is not disjoint any more but
+overlapping. Of course the values other processes compute for need to
+be updated using communication at so called synchronisation points of
+the algorithm
+
+In the latter case the data structures do not need to know anything
+about the data distribution.
+This demands more effort from the parallel algorithm designer to make
+sure that the data used for computations is valid, i.e. contains an
+updated value if another process computes the data for it. Still it allows
+for fewer synchronisation points in the algorithms as even in collective
+operations all input data may already be updated from other processes
+due to a previous operation. Between the necessary synchronisation
+points one can take advantage of the fast local memory
+access.
+
+Consider representing a random access container $x$ on a set of
+processes ${\cal P}=\{0, \ldots, P-1\}$. It is represented by individual
+pieces $x^p$, where $x^p$ is the piece stored on
+process $p$ of the $P$ processes participating in the
+calculation. Although the global representation of the container is
+not available on any process, a process $p$ needs to know how the
+entries of its local piece $x^p$ correspond to the entries of the
+global container $x$, which would be used in a sequential program.
+
+\section{Communication Software Components}
+\label{sec:comm-softw-comp}
+
+From an abstract point of view a random access container $x: I
+\rightarrow K$ provides a
+mapping from an index set $I \subset \N_0$ onto a set of objects
+$K$. Note that we do not require $I$ to be consecutive. The piece
+$x_p$ of the container $x$ stored on process $p$ is a mapping $x_p:I_p
+\rightarrow K$, where $I_p \subset I$. Due to efficiency the entries
+of $x_p$ should be stored consecutively in memory.
+This means that for the local computation the data must be addressable
+by a consecutive index starting from $0$.
+
+When using adaptive
+discretisation methods there might be the need to reorder the indices
+after adding and/or deleting some of the discretisation
+points. Therefore this index does not need to be persistent
+and can easily be changed. We will call this index {\em\index{local index}local index}.
+
+For the communication phases of our algorithms these locally stored
+entries must also be addressable by a global identifier. It is used to
+store the received values at and to retrieve the values to be sent from the
+correct local position in the consecutive memory chunk. To ease the
+addition and removal of discretisation points this global identifier has
+to be persistent but does not need to be consecutive. We
+will call this global identifier {\em\index{global index}global index}.
+
+\subsection{ParallelIndexSet}
+ Let $I \subset \N_0$ be an arbitrary, not necessarily consecutive,
+ index set identifying all discretisation points of the computation.
+ Furthermore, let
+ $$({I}_p)_{p\in {\cal P}}, \quad
+ \bigcup\limits_{p \in {\cal P}} {I}_p = I$$ be an overlapping decomposition of the global index set
+ $I$ into the sets of indices ${I}_p$ corresponding to the
+ global indices of the values stored locally in the chunk of process $p$.
+
+ Then the class
+ \begin{lstlisting}{}
+ template<typename TG, typename TL> class ParallelIndexSet;
+ \end{lstlisting}
+ realises the one to one mapping
+ $$
+ \gamma_p\::\: {I}_p \longrightarrow {I}^{\loc}_p := [0, n_p)
+ $$
+ of the globally unique index onto the local index.
+
+ The template parameter \lstinline!TG! is the type of the global
+ index and
+ \lstinline!TL! is the type of the local index. The only prerequisite
+ of \lstinline!TG! is that objects of this type are comparable using
+ the less-than-operator \lstinline!<!. Not that this prerequisite
+ still allows attaching further
+ information to the global index or even using this information as
+ the global index. The type \lstinline!TL! has to
+ be convertible to \lstinline!std::size_t! as it is used to address array
+ elements.
+
+ The pairs of global and local indices are
+ ordered by ascending global index. It is possible to access the pairs via
+\lstinline!operator[](TG& global)! in $log(n)$ time, where $n$ is the
+number of pairs in the set. In an efficient code it is advisable to
+access the index pairs using the provided iterators over the index pairs.
+
+Due to the ordering, the index set can only be changed, i.e. index pairs
+added or deleted, in a special resize phase. By calling the functions
+\lstinline!beginResize()! and \lstinline!endResize()! the programmer
+indicates that the resize phase starts and ends, respectively. During
+the call of \lstinline!endResize()! the deleted indices will be
+removed and the added index pairs will be sorted and merged with the existing
+ones.
+
+\subsection{ParallelLocalIndex}
+When dealing with overlapping index sets in distributed computing
+there often is the need to distinguish different partitions of an index
+set.%, e.g. $I_i$ and $\tilde{I}_i\setminus I_i$ as introduced in Section \ref{sec:domain_decomposition}.
+
+This is accomplished by using the class
+\begin{lstlisting}{}
+ template<typename TA> class ParallelLocalIndex;
+\end{lstlisting}
+as the type for the local index of class \lstinline!ParallelIndexSet!.
+Here the template parameter \lstinline!TA! is the type of the
+attributes used, e.g. an enumeration \lstinline!Flags! defined by
+\begin{lstlisting}
+ enum Flags {owner, ghost};
+\end{lstlisting}
+where
+\lstinline!owner! marks the indices $k \in I_p$ owned by process
+$p$ and \lstinline!ghost! the indices $k\not\in I_p$ owned
+by other processes.
+
+As an example let us look at an array distributed between two
+processes. In Figure \ref{fig:redistarray} one can see the array
+$a$ as it appears in a sequential program. Below there are two
+different distributions of that array. The local views $s_0$ and
+$s_1$ are the parts process $0$ and $1$ store in the case that $a$ is
+divided into two
+blocks. The local views $t_0$ and $t_1$ are the parts of $a$ that
+process $0$ and $1$ store in the case that $a$ is divided into 4
+blocks and process
+$0$ stores the first and third block and process $1$ the second and
+fourth block. The decompositions have an overlap of one and the indices have
+the attributes \lstinline!owner! and \lstinline!ghost! visualised by
+white and shaded cells, respectively.
+The index sets $I_s$ and $I_t$ corresponding to the decompositions $s_p$
+and $t_p$, $p \in \{0,1\}$, are shown in Figure \ref{fig:redistindex} as sets of triples
+$(g,l,a)$. Here $g$ is the global index, $l$ is the local index and
+$a$ is the attribute (either o for \lstinline!owner! or {g}
+for \lstinline!ghost!).
+\begin{figure}%[b]
+ \centering
+ \psfrag{Is}{$I_s$}
+ \psfrag{It}{$I_t$}
+ \epsfig{file=figures/distindex.eps,width=.5\textwidth}
+ \caption{Index sets for array redistribution}
+ \label{fig:redistindex}
+\end{figure}
+\begin{figure*}%[b]
+ \centering
+ \psfrag{a0:}{$s_0$:}
+ \psfrag{a1:}{$s_1$:}
+ \psfrag{b0:}{$t_0$:}
+ \psfrag{b1:}{$t_1$:}
+ \epsfig{file=figures/distarray.eps,width=.9\textwidth}
+ \caption{Redistributed array}
+ \label{fig:redistarray}
+\end{figure*}
+
+The following code snippet demonstrates how to set up the index set
+$I_s$ on process $0$:
+\lstinputlisting[linerange={53-57,59-61,67-67}]{poosc08_test.cc}
+\subsection{Remote Indices}
+\label{sec:remote-indices}
+
+To set up communication between the processes every process needs to
+know which indices are also known to other processes and which
+attributes are attached to them on the remote side.
+There are scenarios where data is exchanged between different
+index sets, e.g. if the data is agglomerated on lesser processes or
+redistributed. Therefore communication is allowed to occur between different
+decompositions of the same index set.
+
+
+Let $I \subset \N$ be the global index set and
+$$
+(I^s_p)_{p\in{\cal P}},\quad \bigcup_{p\in{\cal P}} I^s_p = I,\quad
+\text{ and } \quad
+(I^t_p)_{p\in{\cal P}}, \quad\bigcup_{p\in{\cal P}} I^t_p = I
+$$ be two overlapping
+decompositions of the same index set $I$. Then an instance of class
+\lstinline!RemoteIndices! on process $p \in {\cal P}$
+stores the sets of triples
+\begin{equation}
+ \label{eq:ri_s_set}
+ \begin{split}
+ r_{p \rightarrow q}^{s} = \{ (g,(l,a),b) \,|\, g \in I^s_q \wedge g \in I_p^t,
+l=\gamma_p^s(g), a = \alpha_p^s(l), b =
+\alpha_q^t(\gamma_q^t(g))\}
+\end{split}
+\end{equation}
+and
+\begin{equation}
+ \label{eq:ri_t_set}
+ \begin{split}
+ r_{p \rightarrow q}^{t} = \{ (g,(l,a),b) \,|\, g \in I^s_q \wedge g \in I_p^t,
+ l=\gamma_p^t(g), a = \alpha_p^t(l), b =
+ \alpha_p^s(\gamma_p^s(g))\}\,,
+ \end{split}
+\end{equation}
+for all $q\in{\cal P}$.
+Here $\alpha^s_p$ and $\alpha^t_p$ denote the mapping of local
+indices on process $p$ onto attributes for the index set $I^s_p$ and
+$I^t_p$ as realised by \lstinline!ParallelLocalIndex!.
+Note that the sets $r_{p \rightarrow q}^{s}$ and $r_{p \rightarrow
+ q}^{t}$ will only be nonempty if the processes $p$ and $q$ manage
+overlapping index sets.
+
+For our example in Figure \ref{fig:redistarray} and Figure
+\ref{fig:redistindex} the interface between $I_s$ and $I_t$ on process
+$0$ is:
+\begin{align*}
+ r_{0\rightarrow 0}^{s} = \{&(0,(0,o),o), (1,(1,o),o), (2,(2,o),o),
+ (3,(3,o),g), (5,(5,o),g), (6,(6,g),o)\}\\
+ r_{0\rightarrow 0}^{t} = \{&(0,(0,o),o), (1,(1,o),o), (2,(2,o),o),
+ (3,(3,g),o), (5,(4,g),o), (6,(5,o),g)\}\\
+ r_{0\rightarrow 1}^{s} = \{&(2(2,o),g), (3,(3,o),o), (4,(4,o),o),
+ (5,(5,o),o), (6,(6,g),g)\}\\
+ r_{0\rightarrow 1}^{t} = \{&(5,(4,g),g), (6,(5,o),o), (7,(6,o),o),
+ (8,(7,o),o), (9,(8,g),o)\}
+\end{align*}
+This information can either be calculated automatically by
+communicating all indices in a ring or set up by hand if the user has
+this information available. Assuming that \lstinline!sis! is the index set
+$I_s$ and \lstinline!tis! the index set $I_t$ set up as described in
+the previous subsection and \lstinline!comm! is an MPI communicator
+then the simple call
+\lstinputlisting[linerange={83-84}]{poosc08_test.cc}
+on all processes automatically calculates this information and
+stores it in \lstinline!riRedist!. For a
+parallel calculation on the local views $s_0$ and $s_1$ calling
+\lstinputlisting[linerange={86-87}]{poosc08_test.cc}
+on all processes builds the necessary information in \lstinline!riS!.
+
+\subsection{Communication Interface}
+\label{sec:comm-interf}
+
+With the information provided by class \lstinline!RemoteIndices! the
+user can set up arbitrary communication interfaces. These interfaces
+are realised in \lstinline!template<typename T> class Interface!,
+where the template parameter \lstinline!T! is the custom type of the
+\lstinline!ParallelIndexSet! representing the index sets.
+Using the attributes attached to the indices by
+\lstinline!ParallelLocalIndex! the user can select subsets of the
+indices for exchanging data, e.g. send data from indices marked
+as \lstinline!owner! to indices marked as \lstinline!ghost!.
+
+Basically the interface on process $p$ manages two sets for each
+process $q$ it shares common indices with:
+
+$$
+i_{p\rightarrow q}^{s} = \{ l | (g,(l,a),b) \in r_{p\rightarrow q}^{s} |
+a \in A_s \wedge b \in A_t\}
+$$
+and
+$$
+i_{p\rightarrow q}^{t} = \{ l | (g, (l,a), b) \in r_{p\rightarrow q}^{t} |
+a \in A_t \wedge b \in A_s\}\,,
+$$
+where $A_s$ and $A_t$ are the attributes marking the indices where the
+source and target of the communication will be, respectively.
+
+In our example these sets on process $0$ will be stored for
+communication if $A_s=\{o\}$ and $A_t=\{o, g\}$:
+\begin{align*}
+ i_{0\rightarrow 0}^{s} = \{0, 1, 3, 5\}\quad & \quad
+ i_{0\rightarrow 0}^{t} = \{0, 1, 3, 4\}\\
+ i_{0\rightarrow 1}^{s} = \{2, 3, 4, 5\}\quad & \quad
+ i_{0\rightarrow 1}^{t} = \{5, 6, 7, 8\}\,.
+\end{align*}
+
+The following code snippet would build the interface above in
+\lstinline!infRedist! as well as the interface \lstinline!infS!
+to communicate between
+indices marked as \lstinline!owner! and \lstinline!ghost! on the local
+array views $s_0$ and $s_1$:
+\lstinputlisting[linerange={89-97}]{poosc08_test.cc}
+
+\subsection{Communicator}
+\label{sec:communicator}
+
+Using the classes from the previous sections all information about the
+communication is available and we are set to communicate data values
+of arbitrary
+container types. The only prerequisite for the container type is that
+its values are addressable via \lstinline!operator[](size_t index)!.
+This should be safe to assume.
+
+An important feature of our communicators is that we are not only able to
+send one data item per index, but also different numbers of data
+elements (of the same type) for each index. This is
+supported in a generic way by the traits class
+\lstinline!template<class V> struct CommPolicy!
+describing the container type \lstinline!V!. The
+\lstinline!typedef IndexedType! is the atomic type to be communicated and
+\lstinline!typedef IndexedTypeFlag! is either \lstinline!SizeOne! if
+there is only one data item per index or \lstinline!VariableSize! if the
+number of data items per index is variable.
+
+The default implementation works for all
+array-like containers which provide only one data item per index. For all
+other containers the user has to provide its own custom
+specialisation.
+%For the vector classes of ISTL (up to two block levels)
+%those specialisations are already implemented.
+
+The class \lstinline!template<class T> class BufferedCommunicator!
+performs the
+actual communication. The template parameter \lstinline!T! describes
+the type of the parallel index set.
+It uses the information about the communication interface provided by
+an object of class \lstinline!Interface! to set up communication
+buffers for a container containing a specific data type. It is also
+responsible for gathering the data before and scattering the data
+after the communication step. The strict separation of the interface
+description from the actual buffering and communication allows for
+reusing the interface information with various different container and
+data types.
+
+Before the communication can start one has to call the
+\lstinline!build! method with the data source and target containers as
+well as the communication interface as arguments. Assuming
+\lstinline!s! and \lstinline!t! as arrays $s_i$ and $t_i$,
+respectively, then
+\lstinputlisting[linerange=103-106]{poosc08_test.cc}
+demonstrates how to set up the communicator \lstinline!bCommRedist! for the array
+redistribution and \lstinline!bComm! for a parallel calculation on the
+local views $s_i$. The
+\lstinline!build! function
+calculates the size of the messages to send to other processes and
+allocates buffers for the send and receive actions. The
+representatives \lstinline!s! and \lstinline!t! are
+needed to get the number of data values at each index in the case of
+variable numbers of data items per index. Note that, due to the generic
+programming techniques used, the compiler knows if the number of data
+points is constant for each index and will apply a specialised
+algorithm for calculating the message size without querying neither
+\lstinline!s! nor \lstinline!t!. Clean up of allocated
+resources is done either by calling the method \lstinline!free()! or
+automatically in the destructor.
+
+The actual communication takes place if one of the methods
+\lstinline!forward!
+and \lstinline!backward! is called. In our case in
+\lstinline!bCommRedist! the \lstinline!forward! method
+sends data from the local views $s_i$ to the local views $t_i$
+according to the interface information and the \lstinline!backward!
+method in the opposite direction.
+
+The following code snippet first redistributes the local views $s_i$
+of the global array to the local views $t_i$ and
+performs some calculation on this representation. Afterwards the
+result is communicated backwards.
+\lstinputlisting[linerange=110-113]{poosc08_test.cc}
+
+Note that both methods have a different template parameter, either
+\lstinline!CopyData! or \lstinline!AddData!. These are policies for
+gathering and scattering the data items. The former just copies
+the data from and to the location. The latter copies from the source
+location but adds the received data items to the target
+entries. Assuming our data is stored in simple C-arrays
+\lstinline!AddData! could be implemented like this:
+
+\lstinputlisting[linerange=16-27]{poosc08_test.cc}
+
+Note that arbitrary
+manipulations can be applied to the communicated data in both methods.
+
+For containers with multiple data items associated with one index
+the methods \lstinline!gather! and \lstinline!scatter! must have an additional
+integer argument specifying the sub-index.
+
+\section{Collective Communication}
+\label{sec:collective-communication}
+
+While communicating entries of array-like structures is a prominent
+task in scientific computing codes one must not neglect
+collective communication operations, like gathering and scattering data
+ from and to all processes, respectively, or waiting for other processes. An
+abstraction for these operations is crucial for decoupling the
+communication from the parallel programming paradigm used.
+
+Therefore we designed
+\lstinline!template<class T> class CollectiveCommunication! which provides
+information of the underlying parallel programming paradigm as well as
+the collective communication operations as known from MPI. See Table
+\ref{tab:col-comm} for a list of all functions.
+
+\begin{table*}%[b]
+ \centering
+ \begin{tabular}{p{.5\textwidth}|p{.4\textwidth}}
+ Function&Description\\\hline\hline
+ \lstinline!int rank()!&Get the rank of the process\\
+ \lstinline!int size()!&Get the number of processes\\
+ \lstinline!template<typename T> T sum (T& in)!& Compute global
+ sum\\
+ \lstinline!template<typename T> T prod (T& in)!&Compute global
+ product\\
+ \lstinline!template<typename T> T min (T& in)!&Compute global minimum\\
+ \lstinline!template<typename T> T max (T& in)!&Compute global
+ maximum\\
+ \lstinline!void barrier()!& Wait for all processes.\\
+ \lstinline!template<typename T> int broadcast (T* inout, int len, int root)!
+& Broadcast an array from root to all other processes\\
+\lstinline!template<typename T> int gather (T* in, T* out, int len, int root)!&
+Gather arrays at a root process\\
+\lstinline!template<typename BinaryFunction, typename Type> int allreduce(Type* in, Type* out, int len)!&
+Combine values from all processes on all processes. Combine function
+is given with \lstinline!BinaryFunction!
+ \end{tabular}
+ \caption{Collective Communication Functions}
+ \label{tab:col-comm}
+\end{table*}
+
+Currently there is a default implementation for sequential programs
+as well as a specialisation working with MPI. This approach allows for
+running parallel programs sequentially without any parallel overhead
+simply by choosing the sequential specialisation at compile time.
+Note that the interface is far more convenient to use than the C++
+interface of MPI. The latter is a simple wrapper around the C
+implementation without taking advantage of the power of generic programming.
+
+
+The collective communication classes were developed before the release
+of Boost.MPI \cite{boost_mpi}. In contrast to Boost.MPI it was never
+meant as a full generic implementation of all MPI functions. Instead it
+is restricted to the most basic subset of collective operations needed
+to implement finite element methods and iterative solver using the
+previously described components. This lean interface should make it
+possible to easily port this approach to
+thread based parallelisation as well as other parallelisation
+paradigms. This would allow code to easily switch between different paradigms
+
+
+\bibliographystyle{plainnat}
+\bibliography{communication}
+\end{document}
+%%% Local Variables:
+%%% mode: latex
+%%% TeX-master: t
+%%% End:
diff --git a/doc/comm/figures/Makefile.am b/doc/comm/figures/Makefile.am
new file mode 100644
index 000000000..febc84358
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+++ b/doc/comm/figures/Makefile.am
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diff --git a/doc/comm/indexset.cc b/doc/comm/indexset.cc
new file mode 100644
index 000000000..8371b19cb
--- /dev/null
+++ b/doc/comm/indexset.cc
@@ -0,0 +1,55 @@
+// -*- tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 2 -*-
+// vi: set et ts=4 sw=2 sts=2:
+// $Id: indexset.cc 1728 2012-11-06 13:06:44Z christi $
+
+#include "config.h"
+
+#include <dune/common/parallel/indexset.hh>
+#include <dune/common/parallel/plocalindex.hh>
+#include <dune/common/parallel/mpihelper.hh>
+#include <iostream>
+#include "buildindexset.hh"
+#include "reverse.hh"
+
+int main(int argc, char **argv)
+{
+ // This is a parallel programm so we need to
+ // initialize mpi first.
+ Dune::MPIHelper& helper = Dune::MPIHelper::instance(argc, argv);
+
+ // The rank of our process
+ int rank = helper.rank();
+
+ // The type used as the local index
+ typedef Dune::ParallelLocalIndex<Flag> LocalIndex;
+
+ // The type used as the global index
+ typedef int GlobalIndex;
+
+ // The index set we use to identify the local indices with the globally
+ // unique ones
+ typedef Dune::ParallelIndexSet<GlobalIndex,LocalIndex,100> ParallelIndexSet;
+
+ // The index set
+ ParallelIndexSet indexSet;
+
+ build(helper, indexSet);
+
+ // Print the index set
+ std::cout<<indexSet<<std::endl;
+
+
+ reverseLocalIndex(indexSet);
+
+ // Print the index set
+ if(rank==0)
+ std::cout<<"Reordered lcoal indices:"<<std::endl;
+
+ // Wait for all processes
+ helper.getCollectiveCommunication().barrier();
+
+ std::cout<<indexSet<<std::endl;
+ // Assign new local indices
+
+ return 0;
+}
diff --git a/doc/comm/poosc08.cc b/doc/comm/poosc08.cc
new file mode 100644
index 000000000..5f43ffbaa
--- /dev/null
+++ b/doc/comm/poosc08.cc
@@ -0,0 +1,92 @@
+// -*- tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 2 -*-
+// vi: set et ts=4 sw=2 sts=2:
+#ifdef HAVE_CONFIG_H
+# include "config.h"
+#endif
+#include <iostream>
+#include <dune/common/exceptions.hh> // We use exceptions
+#include <dune/common/parallel/mpihelper.hh> // An initializer of MPI
+#include <dune/common/parallel/indexset.hh>
+#include <dune/common/parallel/plocalindex.hh>
+
+enum Flags { owner, ghost };
+
+struct Bla
+{
+
+ /** @brief The local index. */
+ size_t localIndex_;
+
+ /** @brief An attribute for the index. */
+ char attribute_;
+
+ /** @brief True if the index is also known to other processors. */
+ bool public_;
+
+ /**
+ * @brief The state of the index.
+ *
+ * Has to be one of LocalIndexState!
+ * @see LocalIndexState.
+ */
+ char state_;
+};
+
+
+template<typename T1, typename T2>
+void buildBlockedIndexSet(T1& indexset, int N, const T2& comm)
+{
+ int rank=comm.rank();
+ int size=comm.size();
+ int localsize=N/size;
+ int bigger=N%size;
+ int start, end;
+ if(rank<bigger) {
+ start=rank*(localsize+1);
+ end=start+(localsize+1);
+ }else{
+ start=bigger*(localsize+1)+(rank-bigger)*localsize;
+ end=start+localsize;
+ }
+
+ indexset.beginResize();
+ int index=0;
+ int gindex=start;
+ typedef typename T1::LocalIndex LocalIndex;
+
+ std::cout<<sizeof(LocalIndex)<<" "<<sizeof(Bla)<<std::endl;
+
+ if(start>0)
+ indexset.add(gindex-1,LocalIndex(index++,ghost));
+
+ for(int i=start; i<end; i++,index++,gindex++)
+ indexset.add(gindex,LocalIndex(index,owner,true));
+
+ if(end<N)
+ indexset.add(gindex,LocalIndex(index,ghost,true));
+}
+int main(int argc, char** argv)
+{
+ int n=100;
+ try{
+ using namespace Dune;
+
+ //Maybe initialize Mpi
+ MPIHelper& helper = MPIHelper::instance(argc, argv);
+ std::cout << "Hello World! This is poosc08." << std::endl;
+ if(Dune::MPIHelper::isFake)
+ std::cout<< "This is a sequential program." << std::endl;
+ else{
+ typedef ParallelIndexSet<int,ParallelLocalIndex<Flags> > IndexSet;
+ IndexSet blockedSet;
+ buildBlockedIndexSet(blockedSet, n, helper.getCollectiveCommunication());
+ }
+ return 0;
+ }
+ catch (Dune::Exception &e) {
+ std::cerr << "Dune reported error: " << e << std::endl;
+ }
+ catch (...) {
+ std::cerr << "Unknown exception thrown!" << std::endl;
+ }
+}
diff --git a/doc/comm/poosc08_test.cc b/doc/comm/poosc08_test.cc
new file mode 100644
index 000000000..2bef04175
--- /dev/null
+++ b/doc/comm/poosc08_test.cc
@@ -0,0 +1,155 @@
+// -*- tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 2 -*-
+// vi: set et ts=4 sw=2 sts=2:
+#ifdef HAVE_CONFIG_H
+# include "config.h"
+#endif
+#include <iostream>
+#include <dune/common/exceptions.hh> // We use exceptions
+#include <dune/common/parallel/mpihelper.hh> // An initializer of MPI
+#include <dune/common/parallel/indexset.hh>
+#include <dune/common/parallel/remoteindices.hh>
+#include <dune/common/parallel/communicator.hh>
+#include <dune/common/parallel/plocalindex.hh>
+#include <dune/common/parallel/interface.hh>
+#include <dune/common/enumset.hh>
+
+enum Flags { owner, ghost };
+
+template<typename T>
+struct AddData {
+ typedef typename T::value_type IndexedType;
+
+ static const IndexedType& gather(const T& v, int i){
+ return v[i];
+ }
+
+ static void scatter(T& v, const IndexedType& item, int i){
+ v[i]+=item;
+ }
+};
+
+template<typename T>
+struct CopyData {
+ typedef typename T::value_type IndexedType;
+
+ static const IndexedType& gather(const T& v, int i){
+ return v[i];
+ }
+
+ static void scatter(T& v, const IndexedType& item, int i){
+ v[i]=item;
+ }
+};
+
+
+template<class T>
+void doCalculations(T& t){}
+
+#if HAVE_MPI
+void test()
+{
+ int rank;
+ MPI_Comm comm=(MPI_COMM_WORLD);
+ MPI_Comm_rank(MPI_COMM_WORLD, &rank);
+ using namespace Dune;
+ // shortcut for index set type
+ typedef ParallelLocalIndex<Flags> LocalIndex;
+ typedef ParallelIndexSet<int, LocalIndex > PIndexSet;
+ PIndexSet sis;
+ sis.beginResize();
+ if(rank==0) {
+
+ sis.add(11, LocalIndex(0, ghost));
+ for(int i=1; i<=6; i++)
+ sis.add(i-1, LocalIndex(i, owner, i<=1||i>5));
+ sis.add(6, LocalIndex(7, ghost));
+ }else{
+ sis.add(5, LocalIndex(0, ghost));
+ for(int i=1; i<=6; i++)
+ sis.add(5+i, LocalIndex(i, owner, i<=1||i>5));
+ sis.add(0,LocalIndex(7, ghost));
+ }
+ sis.endResize();
+
+ PIndexSet tis;
+ tis.beginResize();
+ int l=0;
+ for(int i=0; i<2; ++i)
+ for(int j=0; j<5; ++j) {
+ int g=rank*3-1+i*6+j;
+ if(g<0||g>11)
+ continue;
+ Flags flag=(j>0&&j<4) ? owner : ghost;
+ tis.add(g, LocalIndex(l++, flag));
+ }
+ tis.endResize();
+ std::cout<<rank<<" isxset: "<<sis<<std::endl;
+
+ RemoteIndices<PIndexSet> riRedist(sis, tis, comm);
+ riRedist.rebuild<true>();
+
+ std::vector<int> v;
+ RemoteIndices<PIndexSet> riS(sis,sis, comm, v, true);
+ riS.rebuild<false>();
+
+ std::cout<<std::endl<<"begin"<<rank<<" riS="<<riS<<" end"<<rank<<std::endl<<std::endl;
+
+ Combine<EnumItem<Flags,ghost>,EnumItem<Flags,owner>,Flags> ghostFlags;
+ EnumItem<Flags,owner> ownerFlags;
+ Combine<EnumItem<Flags,ghost>, EnumItem<Flags,owner> > allFlags;
+
+ Interface infRedist;
+ Interface infS;
+
+ infRedist.build(riRedist, ownerFlags, allFlags);
+ infS.build(riS, ownerFlags, ghostFlags);
+
+ std::cout<<"inf "<<rank<<": "<<infS<<std::endl;
+
+ typedef std::vector<double> Container;
+ Container s(sis.size(),3), t(tis.size());
+
+ s[sis.size()-1]=-1;
+
+ BufferedCommunicator bComm;
+ BufferedCommunicator bCommRedist;
+ bComm.build(s, s, infS);
+ //bCommRedist.build(s, t, infRedist);
+ for(std::size_t i=0; i<sis.size(); i++)
+ std::cout<<s[i]<<" ";
+ std::cout<<std::endl;
+
+ bComm.forward<CopyData<Container> >(s,s);
+
+ for(std::size_t i=0; i<sis.size(); i++)
+ std::cout<<s[i]<<" ";
+ std::cout<<std::endl;
+ //bCommRedist.forward<CopyData<Container> >(s,t);
+ // calculate on the redistributed array
+ doCalculations(t);
+ bCommRedist.backward<AddData<Container> >(s,t);
+}
+#endif // HAVE_MPI
+
+int main(int argc, char** argv)
+{
+ try{
+ using namespace Dune;
+#if HAVE_MPI
+ //Maybe initialize Mpi
+ MPIHelper& helper = MPIHelper::instance(argc, argv);
+ std::cout << "Hello World! This is poosc08. rank=" <<helper.rank()<< std::endl;
+ test();
+ return 0;
+#else
+ std::cout<< "Test poosc08_test disabled because MPI is not available." << std::endl;
+ return 77;
+#endif // HAVE_MPI
+ }
+ catch (Dune::Exception &e) {
+ std::cerr << "Dune reported error: " << e << std::endl;
+ }
+ catch (...) {
+ std::cerr << "Unknown exception thrown!" << std::endl;
+ }
+}
diff --git a/doc/comm/reverse.hh b/doc/comm/reverse.hh
new file mode 100644
index 000000000..371ad2ef1
--- /dev/null
+++ b/doc/comm/reverse.hh
@@ -0,0 +1,39 @@
+// -*- tab-width: 4; indent-tabs-mode: nil; c-basic-offset: 2 -*-
+// vi: set et ts=4 sw=2 sts=2:
+// $Id: reverse.hh 942 2008-09-10 18:21:57Z christi $
+#ifndef REVERSE_HH
+#define REVERSE_HH
+
+#include "buildindexset.hh"
+
+/**
+ * @brief Reverse the local indices of an index set.
+ *
+ * Let the index set have N entries than the index 0 will become N-1,
+ * 1 become N-2, ..., and N-1 will become 0.
+ * @param indexSet The index set to reverse.
+ */
+template<typename TG, typename TL, int N>
+void reverseLocalIndex(Dune::ParallelIndexSet<TG,TL,N>& indexSet)
+{
+ // reverse the local indices
+ typedef typename Dune::ParallelIndexSet<TG,TL,N>::iterator iterator;
+
+ iterator end = indexSet.end();
+ size_t maxLocal = 0;
+
+ // find the maximal local index
+ for(iterator index = indexSet.begin(); index != end; ++index) {
+ // Get the local index
+ LocalIndex& local = index->local();
+ maxLocal = std::max(maxLocal, local.local());
+ }
+
+ for(iterator index = indexSet.begin(); index != end; ++index) {
+ // Get the local index
+ LocalIndex& local = index->local();
+ local = maxLocal--;
+ }
+
+}
+#endif
--
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