Coupling-Aware Graph Partitioning Algorithms: Preliminary Study

Abstract : In the field of scientific computing, load balancing is a major issue that determines the performance of parallel applications. Nowadays, simulations of real-life problems are becoming more and more complex, involving numerous coupled codes, representing different models. In this context, reaching high performance can be a great challenge. In this paper, we present graph partitioning techniques, called co-partitioning, that address the problem of load balancing for two coupled codes: the key idea is to perform a "coupling-aware" partitioning, instead of partitioning these codes independently, as it is usually done. Finally, we present a preliminary experimental study which compares our methods against the usual approach.
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Communication dans un congrès
IEEE International Conference on High Performance Computing (HiPC 2014), Dec 2014, Goa, India. 2014, 〈10.1109/HiPC.2014.7116879〉
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Dernière modification le : jeudi 11 janvier 2018 - 06:22:35
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Maria Predari, Aurélien Esnard. Coupling-Aware Graph Partitioning Algorithms: Preliminary Study. IEEE International Conference on High Performance Computing (HiPC 2014), Dec 2014, Goa, India. 2014, 〈10.1109/HiPC.2014.7116879〉. 〈hal-01069578〉

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