A Hybrid Hypergraph Partitioning Algorithm for Scientific Computing

Yao Yuan Zeng; Wen Tao Zhao; Zheng Hua Wang

doi:10.4028/www.scientific.net/AMR.753-755.2900

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 753-755A Hybrid Hypergraph Partitioning Algorithm for...

A Hybrid Hypergraph Partitioning Algorithm for Scientific Computing

Abstract:

Hypergraph partitioning is an increasingly important and widely studied research topic in parallel scientific computing. In this paper, we present a multiway hypergraph partitioning algorithm, mixed simulated annealing algorithm for global optimization and tabu search algorithm for local optimization. Experiments on the benchmark suite of several unstructured meshes show that, for 2-, 4-, 8-, 16-and 32-way partitioning, the quality of partition produced by our algorithm are on the average 6% and the maximum 17% better than those produced by partitioning software hMETIS in term of the cutsize metric.

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Periodical:

Advanced Materials Research (Volumes 753-755)

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2900-2903

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.753-755.2900

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Online since:

August 2013

Authors:

Yao Yuan Zeng, Wen Tao Zhao, Zheng Hua Wang

Keywords:

Global Optimization, Local Optimization, Multiway Hypergraph Partitioning, Simulated Annealing (SA), Tabu Search

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References

[1] K.D. Devine, E.G. Boman, R.T. Heaphy, R.H. Bisseling, and U.V. Catalyurek, Parallel hypergraph partitioning for scientific computing, Parallel and Distributed Processing Symposium, 2006. IPDPS 2006. 20th International, IEEE, 2006, p.10.

DOI: 10.1109/ipdps.2006.1639359

Google Scholar

[2] U.V. Catalyurek, E.G. Boman, K.D. Devine, D. Bozdag, R. Heaphy, and L.A. Riesen, Hypergraph-based dynamic load balancing for adaptive scientific computations, Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International, IEEE, 2007, pp.1-11.

DOI: 10.1109/ipdps.2007.370258

Google Scholar

[3] A.J. Pal, B. Ray, N. Zakaria, and S.S. Sarma. Procedia Computer Science 9 (2012), pp.321-327.

Google Scholar

[4] A. Hedar, and A.F. Ali. Applied Intelligence 37 (2012), pp.189-206.

Google Scholar

[5] C.M. Fiduccia, and R.M. Mattheyses, A linear-time heuristic for improving network partitions, Design Automation, 1982. 19th Conference on, IEEE, 1982, pp.175-181.

DOI: 10.1109/dac.1982.1585498

Google Scholar

[6] Information on http: /turbmodels. larc. nasa. gov.

Google Scholar

[7] G. Karypis, and V. Kumar, hMETIS 1. 5: A hypergraph partitioning package, Technical report, Department of Computer Science, University of Minnesota, (1998).

Google Scholar