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ABSTRACT
We study parallel algorithms for a number of graph problems, using the Single Instruction Stream-Multiple Data Stream model. We assume that the processors have access to a common memory and that no memory or data alignment time penalties are incurred. We derive a general time bound for a parallel algorithm that uses K processors for finding the connected components of an undirected graph. In particular, an O(log2 n) time bound can be achieved using only K = n⌈n/log2 n⌉ processors. This result is optimal in the sense that the speedup ratio is linear with the number of processors used. The algorithm can also be modified to solve a whole class of graph problems with the same time bound and fewer processors than previous parallel methods.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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CITED BY 29
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Yi-Jen Chiang , Michael T. Goodrich , Edward F. Grove , Roberto Tamassia , Darren Erik Vengroff , Jeffrey Scott Vitter, External-memory graph algorithms, Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms, p.139-149, January 22-24, 1995, San Francisco, California, United States
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David R. Karger , Noam Nisan , Michal Parnas, Fast connected components algorithms for the EREW PRAM, Proceedings of the fourth annual ACM symposium on Parallel algorithms and architectures, p.373-381, June 29-July 01, 1992, San Diego, California, United States
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Lars Arge , Michael A. Bender , Erik D. Demaine , Bryan Holland-Minkley , J. Ian Munro, Cache-oblivious priority queue and graph algorithm applications, Proceedings of the thiry-fourth annual ACM symposium on Theory of computing, May 19-21, 2002, Montreal, Quebec, Canada
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