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Compression and Sieve: Reducing Communication in Parallel Breadth First Search on Distributed Memory Systems
[article]
2012
arXiv
pre-print
For parallel breadth first search (BFS) algorithm on large-scale distributed memory systems, communication often costs significantly more than arithmetic and limits the scalability of the algorithm. In this paper we sufficiently reduce the communication cost in distributed BFS by compressing and sieving the messages. First, we leverage a bitmap compression algorithm to reduce the size of messages before communication. Second, we propose a novel distributed directory algorithm, cross directory,
arXiv:1208.5542v1
fatcat:qshsx4z3zbgrli3lvtah2ppqza