A decentralized and fault tolerant convergence detection algorithm for asynchronous iterative algorithms

Abstract : This article presents an algorithm that performs a decentralized detection of the global convergence of parallel asynchronous iterative applications. This algorithm is fault tolerant. It runs a decentralized saving procedure which enables this algorithm, after a node's crash, to replace the dead node by a new one which will continue the computing task from the last check point. Combined with the advantages of the asynchronous iteration model, this method allows us to compute very large scale problems using highly volatile parallel architectures like Peer-to-Peer and distributed clusters architectures. We also present the implementation of this algorithm in the JaceP2P platform which is dedicated to designing and executing parallel asynchronous iterative applications in volatile environments. Numerous experiments show the robustness and the efficiency of our algorithm.
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Article dans une revue
Journal of Supercomputing, Springer Verlag, 2010, 53 (2), pp.269-292. 〈10.1007/s11227-009-0293-6〉
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https://hal.inria.fr/hal-00690461
Contributeur : Ist Rennes <>
Soumis le : lundi 23 avril 2012 - 15:42:42
Dernière modification le : jeudi 11 janvier 2018 - 06:16:36

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Jean-Claude Charr, Raphaël Couturier, David Laiymani. A decentralized and fault tolerant convergence detection algorithm for asynchronous iterative algorithms. Journal of Supercomputing, Springer Verlag, 2010, 53 (2), pp.269-292. 〈10.1007/s11227-009-0293-6〉. 〈hal-00690461〉

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