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Evaluating Parallel Breadth-First Search Algorithms for Multiprocessor Systems

  • 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.

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Metadaten
Document Type:Article
Language:English
Parent Title (English):Soft (International Journal on Advances in Software)
Volume:7
Issue:3&4
First Page:740
Last Page:751
ISSN:1942-2628
URL:http://www.thinkmind.org/index.php?view=article&articleid=soft_v7_n34_2014_24
Publisher:ThinkMind
Date of first publication:2014/12/30
Tag:BFS; NUMA; data locality; memory bandwidth; parallel breadth-first search
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):000 Informatik, Informationswissenschaft, allgemeine Werke / 000 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2016/04/22