Graph Repartitioning with both Dynamic Load and Dynamic Processor Allocation

Abstract : Dynamic load balancing is an important step conditioning the performance of parallel programs, like adaptive mesh refinement codes. If the global workload varies drastically over time (such that memory is exceeded), it can be relevant to adjust the number of processors while maintaining the load balanced. We propose two different solutions, that extend classic graph repartitioning approaches to accept a variable number of processors: one based on biased partitioning method and one based on a diffusive method. We call this problem: the MxN graph repartitioning problem. Finally, an experimental study on real-life graphs validates our algorithms against state-of-the-art methods.
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Michael Bader and Arndt Bode and Hans-Joachim Bungartz and Michael Gerndt and Gerhard R. Joubert and Frans J. Peters. International Conference on Parallel Computing - ParCo2013, Sep 2013, München, Germany. IOS Press, 25, pp.243-252, 2013, Advances of Parallel Computing. 〈10.3233/978-1-61499-381-0-243〉
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Soumis le : mercredi 4 septembre 2013 - 17:03:54
Dernière modification le : jeudi 11 janvier 2018 - 06:22:35

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Clément Vuchener, Aurélien Esnard. Graph Repartitioning with both Dynamic Load and Dynamic Processor Allocation. Michael Bader and Arndt Bode and Hans-Joachim Bungartz and Michael Gerndt and Gerhard R. Joubert and Frans J. Peters. International Conference on Parallel Computing - ParCo2013, Sep 2013, München, Germany. IOS Press, 25, pp.243-252, 2013, Advances of Parallel Computing. 〈10.3233/978-1-61499-381-0-243〉. 〈hal-00857881v2〉

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