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European Symposium on Algorithms

ESA 2011: Algorithms – ESA 2011 pp 469–480Cite as

Engineering Multilevel Graph Partitioning Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6942))

Abstract

We present a multi-level graph partitioning algorithm using novel local improvement algorithms and global search strategies transferred from multigrid linear solvers. Local improvement algorithms are based on max-flow min-cut computations and more localized FM searches. By combining these techniques, we obtain an algorithm that is fast on the one hand and on the other hand is able to improve the best known partitioning results for many inputs. For example, in Walshaw’s well known benchmark tables we achieve 317 improvements for the tables at 1%, 3% and 5% imbalance. Moreover, in 118 out of the 295 remaining cases we have been able to reproduce the best cut in this benchmark.

This paper is a short version of the technical report [10].

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References

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Author information

Authors and Affiliations

  1. Karlsruhe Institute of Technology (KIT), 76128, Karlsruhe, Germany

    Peter Sanders & Christian Schulz

Authors
  1. Peter Sanders
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  2. Christian Schulz
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Editor information

Editors and Affiliations

  1. Dipartimento di Informatica e Sistemistica, University of Rome " La Sapienza", via Ariosto 25, 00185, Roma, Italy

    Camil Demetrescu

  2. School of Computer Science, Reykjavik University, Menntavegur 1, 101, Reykjavik, Iceland

    Magnús M. Halldórsson

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© 2011 Springer-Verlag Berlin Heidelberg

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Sanders, P., Schulz, C. (2011). Engineering Multilevel Graph Partitioning Algorithms. In: Demetrescu, C., Halldórsson, M.M. (eds) Algorithms – ESA 2011. ESA 2011. Lecture Notes in Computer Science, vol 6942. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23719-5_40

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  • DOI: https://doi.org/10.1007/978-3-642-23719-5_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23718-8

  • Online ISBN: 978-3-642-23719-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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