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ThinkMind // International Journal On Advances in Software, volume 7, numbers 3 and 4, 2014 // View article soft_v7_n34_2014_24


Evaluating Parallel Breadth-First Search Algorithms for Multiprocessor Systems

Authors:
Matthias Makulla
Rudolf Berrendorf

Keywords: parallel breadth-first search, BFS, NUMA, memory bandwidth, data locality

Abstract:
Breadth-First Search is a graph traversal technique used in many applications as a building block, e.g., to systematically explore a search space or to determine single source shortest paths in unweighted graphs. For modern multicore processors and as application graphs get larger, well-performing parallel algorithms are favorable. In this paper, we systematically evaluate an important class of parallel algorithms for this problem and discuss programming optimization techniques for their implementation on parallel systems with shared memory. We concentrate our discussion on level-synchronous algorithms for larger multicore and multiprocessor systems. In our results, we show that for small core counts many of these algorithms show rather similar performance behavior. But, for large core counts and large graphs, there are considerable differences in performance and scalability influenced by several factors, including graph topology. This paper gives advice, which algorithm should be used under which circumstances.

Pages: 740 to 751

Copyright: Copyright (c) to authors, 2014. Used with permission.

Publication date: December 30, 2014

Published in: journal

ISSN: 1942-2628

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