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Aggregative Coarsening for Multilevel Hypergraph Partitioning

Authors Ruslan Shaydulin , Ilya Safro

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Author Details

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

Funding

This material is based upon work supported by the National Science Foundation under Grant No. 1522751.

Cite AsGet BibTex

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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