Abstract
The Parallel Boost Graph Library (Parallel BGL) is a library of graph algorithms and data structures for distributed-memory computation on large graphs. Developed with the Generic Programming paradigm, the Parallel BGL is highly customizable, supporting various graph data structures, arbitrary vertex and edge properties, and different communication media. In this paper, we describe the implementation of three parallel variants of Dijkstra’s single-source shortest paths algorithm in the Parallel BGL. We also provide an experimental evaluation of these implementations using synthetic and realworld benchmark graphs from the 9th DIMACS Implementation Challenge and present performance results of solving the single-source shortest path problem for graphs with over a billion vertices on a modest size cluster.
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