119 lines
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HTML
119 lines
7.3 KiB
HTML
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
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<html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en" lang="en">
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<meta name="generator" content="Docutils 0.6: http://docutils.sourceforge.net/" />
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<title>An Overview of the Parallel Boost Graph Library</title>
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<div class="document" id="an-overview-of-the-parallel-boost-graph-library">
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<h1 class="title">An Overview of the Parallel Boost Graph Library</h1>
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<!-- Copyright (C) 2004-2008 The Trustees of Indiana University.
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Use, modification and distribution is subject to the Boost Software
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License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
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http://www.boost.org/LICENSE_1_0.txt) -->
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<img align="right" alt="An example graph" class="align-right" src="../graph.png" style="width: 206px; height: 184px;" />
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<p>The Parallel Boost Graph Library (Parallel BGL) is a C++ library for
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parallel, distributed computation on graphs. The Parallel BGL contains
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distributed graph data structures, distributed graph algorithms,
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abstractions over the communication medium (such as MPI), and
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supporting data structures. A graph (also called a <em>network</em>) consists
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of a set of <em>vertices</em> and a set of relationships between vertices,
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called <em>edges</em>. The edges may be <em>undirected</em>, meaning that the
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relationship between vertices is mutual, e.g., "X is related to Y", or
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they can be <em>directed</em>, meaning that the relationship goes only one
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way, e.g., "X is the child of Y". The following figure illustrates a
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typical directed graph, where <em>a-i</em> are the vertices and the arrows
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represent edges.</p>
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<img align="right" alt="A distributed graph" class="align-right" src="../distributed-graph.png" style="width: 229px; height: 199px;" />
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<p>The Parallel BGL is primarily concerned with <em>distributed</em>
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graphs. Distributed graphs are conceptually graphs, but their storage
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is spread across multiple processors. The following figure
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demonstrates a distributed version of the graph above, where the graph
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has been divided among three processors (represented by the grey
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rectangles). Edges in the graph may be either local (with both
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endpoints stored on the same processor) or remote (the target of the
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edge is stored on a different processor).</p>
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<p>The Parallel BGL is a generic library. At its core are <em>generic</em>
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distributed graph algorithms, which can operate on any distributed
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graph data structure provided that data structure meets certain
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requirements. For instance, the algorithm may need to enumerate the
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set of vertices stored on the current processor, enumerate the set of
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outgoing edges from a particular vertex, and determine on which
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processor the target of each edge resides. The graph algorithms in the
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Parallel BGL are also generic with respect to the <em>properties</em>
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attached to edges and vertices in a graph; for instance, the weight of
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each edge can be stored as part of the graph or allocated in a
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completely separate data structure.</p>
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<p>The genericity available in the algorithms of the Parallel BGL allows
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them to be applied to existing graph data structures. However, most
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users will instead be writing new code that takes advantage of the
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Parallel BGL. The Parallel BGL provides distributed graph data
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structures that meet the requirements of the Parallel BGL
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algorithms. The primary data structure is the <a class="reference external" href="distributed_adjacency_list.html">distributed adjacency
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list</a>, which allows storage and manipulation of a (distributed)
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graph. The vertices in the graph are divided among the various
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processors, and each of the edges outgoing from a vertex are stored on
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the processor that "owns" (stores) that vertex. The following figure
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illustrates the distributed adjacency list representation.</p>
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<div align="center" class="align-center"><img alt="A distributed adjacency list" class="align-center" src="../dist-adjlist.png" style="width: 446px; height: 154px;" /></div>
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<img align="right" alt="A distributed property map" class="align-right" src="../dist-pmap.png" style="width: 271px; height: 175px;" />
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<p>The <a class="reference external" href="distributed_adjacency_list.html">distributed adjacency list</a> distributes the structure of a graph
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over multiple processors. While graph structure is in important part
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of many graph problems, there are typically other properties attached
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to the vertices and edges, such as edge weights or the position of
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vertices within a grid. These properties are stored in <em>property
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maps</em>, which associate a single piece of data with each edge or vertex
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in a graph. Distributed property maps extend this notion to
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distributed computing, where properties are stored on the same
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processor as the vertex or edge. The following figure illustrates the
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distribution of a property map storing colors (white, gray, black) for
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each vertex. In addition to the storage for each vertex, the
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processors store some "ghost cells" that cache values actually stored
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on other processors, represented by the dashed boxes.</p>
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<p>Tying together all of the distributed data structures of the Parallel
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BGL are its process groups and distributed graph algorithms. Process
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groups coordinate the interactions between multiple processes and
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distributed data structures by abstracting the communication
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mechanism. The algorithms are typically written using the SPMD model
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(Single Program, Multiple Data) and interact with both the distributed
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data structures and the process group itself. At various points in the
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algorithm's execution, all processes execute a synchronization point,
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which allows all of the distributed data structures to ensure an
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appropriate degree of consistency across processes. The following
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diagram illustrates the communication patterns within the the
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execution of a distributed algorithm in the Parallel BGL. In
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particular, the diagram illustrates the distributed data structures
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used in a distributed breadth-first search, from the top-left and
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proceeding clockwise:</p>
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<blockquote>
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<ul class="simple">
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<li>a user-defined property map that tracks the distance from the
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source vertex to all other vertices,</li>
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<li>an automatically-generated property map that tracks the "color"
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of vertices in the (distributed) graph, to determine which
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vertices have been seen before,</li>
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<li>a distributed queue, which coordinates the breadth-first search
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and distributes new vertices to search, and</li>
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<li>a distributed graph, on which the breadth-first search is
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operating.</li>
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</ul>
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</blockquote>
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<div align="center" class="align-center"><img alt="Parallel Boost Graph Library architecture" class="align-center" src="../architecture.png" style="width: 485px; height: 410px;" /></div>
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<hr class="docutils" />
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<p>Copyright (C) 2005 The Trustees of Indiana University.</p>
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<p>Authors: Douglas Gregor and Andrew Lumsdaine</p>
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<span class="target" id="process-groups"></span>
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</div>
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<div class="footer">
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<hr class="footer" />
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Generated on: 2009-05-31 00:22 UTC.
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Generated by <a class="reference external" href="http://docutils.sourceforge.net/">Docutils</a> from <a class="reference external" href="http://docutils.sourceforge.net/rst.html">reStructuredText</a> source.
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