Monte-Carlo Simulation on Heterogeneous Distributed Systems: a Computing Framework with Parallel Merging and Checkpointing Strategies

S. Camarasu-Pop 1, 2, * T. Glatard 2 R. Ferreira da Silva 2 P. Gueth 3 D. Sarrut 3 H. Benoit-Cattin 2
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Abstract : This paper introduces an end-to-end framework for efficient computing and merging of Monte Carlo simulations on heterogeneous distributedsystems. Simulations are parallelized using a dynamicload- balancing approach and multiple parallel mergers. Checkpointing is used to improve reliability and to enable incremental results merging from partial results. A model is proposed to analyze the behavior of the proposed framework and help tune its parameters. Experimental results obtained on a production grid infrastructure show that the model fits the realmakes pan with a relative error of maximum 10%, that using multiple parallel mergers reduces the makes pan by 40% on average, that checkpointing enables the completion of very long simulations and that it can be used without penalizing the makespan.
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https://hal.archives-ouvertes.fr/hal-00797962
Contributeur : Béatrice Rayet <>
Soumis le : jeudi 7 mars 2013 - 16:10:42
Dernière modification le : mercredi 20 novembre 2019 - 02:36:15

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HCL | CNRS | INSA-LYON | CREATIS | PRIMES_WP5 | PRIMES | UNIV-LYON1 | UNIV-ST-ETIENNE | INSA-GROUPE | UDL

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S. Camarasu-Pop, T. Glatard, R. Ferreira da Silva, P. Gueth, D. Sarrut, et al.. Monte-Carlo Simulation on Heterogeneous Distributed Systems: a Computing Framework with Parallel Merging and Checkpointing Strategies. Future Generation Computer Systems, Elsevier, 2013, pp.728-738. ⟨10.1016/j.future.2012.09.003⟩. ⟨hal-00797962⟩

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