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Aggregative Coarsening for Multilevel Hypergraph Partitioning

Authors Ruslan Shaydulin , Ilya Safro



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Ruslan Shaydulin
  • School of Computing, Clemson University, Clemson, SC
Ilya Safro
  • School of Computing, Clemson University, Clemson, SC

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Ruslan Shaydulin and Ilya Safro. Aggregative Coarsening for Multilevel Hypergraph Partitioning. In 17th International Symposium on Experimental Algorithms (SEA 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 103, pp. 2:1-2:15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.SEA.2018.2

Abstract

Algorithms for many hypergraph problems, including partitioning, utilize multilevel frameworks to achieve a good trade-off between the performance and the quality of results. In this paper we introduce two novel aggregative coarsening schemes and incorporate them within state-of-the-art hypergraph partitioner Zoltan. Our coarsening schemes are inspired by the algebraic multigrid and stable matching approaches. We demonstrate the effectiveness of the developed schemes as a part of multilevel hypergraph partitioning framework on a wide range of problems.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Hypergraphs
  • Mathematics of computing → Graph algorithms
  • Mathematics of computing → Matchings and factors
Keywords
  • hypergraph partitioning
  • multilevel algorithms
  • coarsening
  • matching
  • combinatorial scientific computing

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