Schwarz waveform relaxation for heterogeneous cluster computing: Application to numerical weather prediction

Laurent Debreu 1, *
* Auteur correspondant
1 MOISE - Modelling, Observations, Identification for Environmental Sciences
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : This presentation deals with the numerical simulation of partial differential equations on highly heterogeneous computing platforms both in terms of computing power and speed of communication. These difficulties are even stronger when the initial problem is not easily decomposable into independent tasks, and when other issues such as fault tolerance come into play. We show that the Schwarz waveform relaxation methods may prove to be the right tool to address all these issues. After explaining the benefits of these methods on a simple 2D advection equation, we present preliminary results of running the weather research and forecasting (WRF) model on the Amazon EC2 computing platform. The main open problems are finally outlined.
Type de document :
Communication dans un congrès
DD22 - 22nd International Conference on Domain Decomposition Methods - 2013, Sep 2013, Lugano, Switzerland. 2013
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https://hal.inria.fr/hal-00932898
Contributeur : Laurent Debreu <>
Soumis le : samedi 18 janvier 2014 - 11:00:26
Dernière modification le : mercredi 11 avril 2018 - 01:59:47

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  • HAL Id : hal-00932898, version 1

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Laurent Debreu. Schwarz waveform relaxation for heterogeneous cluster computing: Application to numerical weather prediction. DD22 - 22nd International Conference on Domain Decomposition Methods - 2013, Sep 2013, Lugano, Switzerland. 2013. 〈hal-00932898〉

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