A Discussion on Parallelization Schemes for Stochastic Vector Quantization Algorithms

* Auteur correspondant
Abstract : This paper studies parallelization schemes for stochastic Vector Quantization algorithms in order to obtain time speed-ups using distributed resources. We show that the most intuitive parallelization scheme does not lead to better performances than the sequential algorithm. Another distributed scheme is therefore introduced which obtains the expected speed-ups. Then, it is improved to fit implementation on distributed architectures where communications are slow and inter-machines synchronization too costly. The schemes are tested with simulated distributed architectures and, for the last one, with Microsoft Windows Azure platform obtaining speed-ups up to $32$ Virtual Machines.
Type de document :
Communication dans un congrès
20-th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), Apr 2012, Bruges, Belgium. pp.477-482, 2012
Domaine :
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https://hal.archives-ouvertes.fr/hal-00696072
Contributeur : Fabrice Rossi <>
Soumis le : jeudi 10 mai 2012 - 16:26:12
Dernière modification le : mercredi 21 mars 2018 - 18:56:47
Document(s) archivé(s) le : jeudi 15 décembre 2016 - 06:12:19

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• HAL Id : hal-00696072, version 1
• ARXIV : 1205.2282

Citation

Matthieu Durut, Benoît Patra, Fabrice Rossi. A Discussion on Parallelization Schemes for Stochastic Vector Quantization Algorithms. 20-th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2012), Apr 2012, Bruges, Belgium. pp.477-482, 2012. 〈hal-00696072〉

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