Characterizing the communication demands of the Graph500 benchmark on a commodity cluster
Document typeConference report
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Rights accessOpen Access
European Commission's projectROMOL - Riding on Moore's Law (EC-FP7-321253)
Big Data applications have gained importance over the last few years. Such applications focus on the analysis of huge amounts of unstructured information and present a series of differences with traditional High Performance Computing (HPC) applications. For illustrating such dissimilarities, this paper analyzes the behavior of the most scalable version of the Graph500 benchmark when run on a state-of-the-art commodity cluster facility. Our work shows that this new computation paradigm stresses the interconnection subsystem. In this work, we provide both analytical and empirical characterizations of the Graph500 benchmark, showing that its communication needs bound the achieved performance on a cluster facility. Up to our knowledge, our evaluation is the first to consider the impact of message aggregation on the communication overhead and explore a tradeoff that diminishes benchmark execution time, increasing system performance.
CitationFuentes, P., Bosque, J., Beivide, R., Valero, M., Minkenberg, C. Characterizing the communication demands of the Graph500 benchmark on a commodity cluster. A: International Symposium on Big Data Computing. "2014 International Symposium on Big Data Computing, BDC 2014: London, United Kingdom 8-11 December 2014: proceedings". Londres: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 83-89.
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