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A Parallel Approximation Algorithm for the Weighted Maximum Matching Problem

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 4967)

Abstract

We consider the problem of computing a weighted edge matching in a large graph using a parallel algorithm. This problem has application in several areas of combinatorial scientific computing. Since an exact algorithm for the weighted matching problem is both fairly expensive to compute and hard to parallelise we instead consider fast approximation algorithms.

We analyse a distributed algorithm due to Hoepman [8] and show how this can be turned into a parallel algorithm. Through experiments using both complete as well as sparse graphs we show that our new parallel algorithm scales well using up to 32 processors.

Keywords

  • Parallel Algorithm
  • Sparse Graph
  • Dominant Edge
  • Fast Approximation Algorithm
  • Drop Message

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The authors wish to thank HPC-Europe, the Dutch supercomputing centre SARA, NCF, the BSIK/BRICKS MSV1-2 program, and the NFR funded Parcomb project for financial support.

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References

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Manne, F., Bisseling, R.H. (2008). A Parallel Approximation Algorithm for the Weighted Maximum Matching Problem . In: Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J. (eds) Parallel Processing and Applied Mathematics. PPAM 2007. Lecture Notes in Computer Science, vol 4967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68111-3_74

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  • DOI: https://doi.org/10.1007/978-3-540-68111-3_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-68105-2

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