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

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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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Authors and Affiliations

  1. Laboratory of computer science of Franche Comte, University of Franche-Comte, IUT de Belfort-Montbéliard, Rue Engel Gros, BP 527, 90016, Belfort, France

    Jean-Claude Charr, Raphaël Couturier & David Laiymani

Authors
  1. Jean-Claude Charr
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  2. Raphaël Couturier
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  3. David Laiymani
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Correspondence to Raphaël Couturier.

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Charr, JC., Couturier, R. & Laiymani, D. A decentralized and fault tolerant convergence detection algorithm for asynchronous iterative algorithms. J Supercomput 53, 269–292 (2010). https://doi.org/10.1007/s11227-009-0293-6

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  • DOI: https://doi.org/10.1007/s11227-009-0293-6

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