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Evaluation of a Flow-Based Hypergraph Bipartitioning Algorithm

Authors Lars Gottesbüren, Michael Hamann, Dorothea Wagner

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Author Details

Lars Gottesbüren
  • Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany
Michael Hamann
  • Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany
Dorothea Wagner
  • Institute of Theoretical Informatics, Karlsruhe Institute of Technology, Germany

Funding

This work was supported by the DFG under grants WA654/19-2 and WA654/22-2. The authors acknowledge support by the state of Baden-Württemberg through bwHPC.

Acknowledgements

We thank Ben Strasser, Tim Zeitz and Lukas Barth for helpful discussions.

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Lars Gottesbüren, Michael Hamann, and Dorothea Wagner. Evaluation of a Flow-Based Hypergraph Bipartitioning Algorithm. In 27th Annual European Symposium on Algorithms (ESA 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 144, pp. 52:1-52:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019) https://doi.org/10.4230/LIPIcs.ESA.2019.52

Abstract

In this paper, we propose HyperFlowCutter, an algorithm for balanced hypergraph bipartitioning that is based on minimum S-T hyperedge cuts and maximum flows. It computes a sequence of bipartitions that optimize cut size and balance in the Pareto sense, being able to trade one for the other. HyperFlowCutter builds on the FlowCutter algorithm for partitioning graphs. We propose additional features, such as handling disconnected hypergraphs, novel methods for obtaining starting S,T pairs as well as an approach to refine a given partition with HyperFlowCutter. Our main contribution is ReBaHFC, a new algorithm which obtains an initial partition with the fast multilevel hypergraph partitioner PaToH and then improves it using HyperFlowCutter as a refinement algorithm. ReBaHFC is able to significantly improve the solution quality of PaToH at little additional running time. The solution quality is only marginally worse than that of the best-performing hypergraph partitioners KaHyPar and hMETIS, while being one order of magnitude faster. Thus ReBaHFC offers a new time-quality trade-off in the current spectrum of hypergraph partitioners. For the special case of perfectly balanced bipartitioning, only the much slower plain HyperFlowCutter yields slightly better solutions than ReBaHFC, while only PaToH is faster than ReBaHFC.

Subject Classification

ACM Subject Classification
  • Mathematics of computing → Graph algorithms
Keywords
  • Hypergraph Partitioning
  • Maximum Flows
  • Algorithm Engineering

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