License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.SEA.2017.21
URN: urn:nbn:de:0030-drops-76226
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2017/7622/
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Heuer, Tobias ; Schlag, Sebastian

Improving Coarsening Schemes for Hypergraph Partitioning by Exploiting Community Structure

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LIPIcs-SEA-2017-21.pdf (7 MB)

Abstract

We present an improved coarsening process for multilevel hypergraph partitioning that incorporates global information about the community structure. Community detection is performed via modularity maximization on a bipartite graph representation. The approach is made suitable for different classes of hypergraphs by defining weights for the graph edges that express structural properties of the hypergraph. We integrate our approach into a leading multilevel hypergraph partitioner with strong local search algorithms and perform extensive experiments on a large benchmark set of hypergraphs stemming from application areas such as VLSI design, SAT solving, and scientific computing. Our results indicate that respecting community structure during coarsening not only significantly improves the solutions found by the initial partitioning algorithm, but also consistently improves overall solution quality.

BibTeX - Entry

@InProceedings{heuer_et_al:LIPIcs:2017:7622,
  author =	{Tobias Heuer and Sebastian Schlag},
  title =	{{Improving Coarsening Schemes for Hypergraph Partitioning by Exploiting Community Structure}},
  booktitle =	{16th International Symposium on Experimental Algorithms (SEA 2017)},
  pages =	{21:1--21:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-036-1},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{75},
  editor =	{Costas S. Iliopoulos and Solon P. Pissis and Simon J. Puglisi and Rajeev Raman},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2017/7622},
  URN =		{urn:nbn:de:0030-drops-76226},
  doi =		{10.4230/LIPIcs.SEA.2017.21},
  annote =	{Keywords: multilevel hypergraph partitioning, coarsening algorithms, community detection}
}

Keywords: multilevel hypergraph partitioning, coarsening algorithms, community detection
Collection: 16th International Symposium on Experimental Algorithms (SEA 2017)
Issue Date: 2017
Date of publication: 07.08.2017

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