Replicated partitioning for undirected hypergraphs

Date
2012
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Source Title
Journal of Parallel and Distributed Computing
Print ISSN
0743-7315
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Publisher
Academic Press
Volume
72
Issue
4
Pages
547 - 563
Language
English
Type
Article
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Abstract

Hypergraph partitioning (HP) and replication are diverse but powerful tools that are traditionally applied separately to minimize the costs of parallel and sequential systems that access related data or process related tasks. When combined together, these two techniques have the potential of achieving significant improvements in performance of many applications. In this study, we provide an approach involving a tool that simultaneously performs replication and partitioning of the vertices of an undirected hypergraph whose vertices represent data and nets represent task dependencies among these data. In this approach, we propose an iterative-improvement-based replicated bipartitioning heuristic, which is capable of move, replication, and unreplication of vertices. In order to utilize our replicated bipartitioning heuristic in a recursive bipartitioning framework, we also propose appropriate cut-net removal, cut-net splitting, and pin selection algorithms to correctly encapsulate the two most commonly used cutsize metrics. We embed our replicated bipartitioning scheme into the state-of-the-art multilevel HP tool PaToH to provide an effective and efficient replicated HP tool, rpPaToH. The performance of the techniques proposed and the tools developed is tested over the undirected hypergraphs that model the communication costs of parallel query processing in information retrieval systems. Our experimental analysis indicates that the proposed technique provides significant improvements in the quality of the partitions, especially under low replication ratios. © 2012 Elsevier Inc. All rights reserved.

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Keywords
Hypergraph partitioning, Iterative improvement heuristic, Recursive bipartitioning, Replication, Undirected hypergraphs
Citation
Published Version (Please cite this version)