Performance analysis and optimization of MPI collective operations on multi-core clusters.

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Bibliographic Details
Title:	Performance analysis and optimization of MPI collective operations on multi-core clusters.
Authors:	Tu, Bibo¹ tbb@ncic.ac.cn, Fan, Jianping fan@ict.ac.cn, Zhan, Jianfeng¹ jfzhan@ncic.ac.cn, Zhao, Xiaofang¹ zhaoxf@ict.ac.cn
Source:	Journal of Supercomputing. Apr2012, Vol. 60 Issue 1, p141-162. 22p.
Subjects:	Multicore processors, Memory hierarchy (Computer science), Mathematical optimization, Cache memory, Computer networks, Algorithms
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. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
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. [ABSTRACT FROM AUTHOR]
ISSN:	09208542
DOI:	10.1007/s11227-009-0296-3