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Performance Analysis of MPI Collective Operations

By Thara Angskun, George Bosilca, Graham E. Fagg, Edgar Gabriel and Jack J. Dongarra

Abstract

Abstract. Previous studies of application usage show that the perfor-mance of collective communications are critical for high-performance computing. Despite active research in the field, both general and fea-sible solution to the optimization of collective communication problem is still missing. In this paper, we analyze and attempt to improve intra-cluster collective communication in the context of the widely deployed MPI programming paradigm by extending accepted models of point-to-point communica-tion, such as Hockney, LogP/LogGP, and PLogP, to collective opera-tions. We compare the predictions from models against the experimen-tally gathered data and using these results, construct optimal decision function for broadcast collective. We quantitatively compare the quality of the model-based decision functions to the experimentally-optimal one. Additionally, in this work, we also introduce a new form of an optimized tree-based broadcast algorithm, splitted-binary. Our results show that all of the models can provide useful insights into various aspects of the different algorithms as well as their relative perfor-mance. Still, based on our findings, we believe that the complete reliance on models would not yield optimal results. In addition, our experimental ⋆ This material is based upon work supported by the Department of Energy under Contract No. DE-FG02-02ER25536. results have identified the gap parameter as being the most critical for accurate modeling of both the classical point-to-point-based pipeline and our extensions to fan-out topologies.

Year: 2005
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.9618
Provided by: CiteSeerX
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