Performance analysis and optimization of MPI collective operations on multi-core clusters |
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Authors: | Email author" target="_blank">Bibo?TuEmail author Jianping?Fan Jianfeng?Zhan Xiaofang?Zhao |
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Affiliation: | (1) Innovative Computing Laboratory, Computer Science Department, University of Tennessee, 1122 Volunteer Blvd., Knoxville, TN 37996-3450, USA;(2) Department of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, Houston, TX 77204-3010, USA |
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Abstract: | Memory hierarchy on multi-core clusters has twofold characteristics: vertical memory hierarchy and horizontal memory hierarchy.
This paper proposes new parallel computation model to unitedly abstract memory hierarchy on multi-core clusters in vertical
and horizontal levels. Experimental results show that new model can predict communication costs for message passing on multi-core
clusters more accurately than previous models, only incorporated vertical memory hierarchy. The new model provides the theoretical
underpinning for the optimal design of MPI collective operations. Aimed at horizontal memory hierarchy, our methodology for
optimizing collective operations on multi-core clusters focuses on hierarchical virtual topology and cache-aware intra-node
communication, incorporated into existing collective algorithms in MPICH2. As a case study, multi-core aware broadcast algorithm
has been implemented and evaluated. The results of performance evaluation show that the above methodology for optimizing collective
operations on multi-core clusters is efficient. |
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Keywords: | |
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