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Large Scale Experiment and Optimization of a Distributed Stochastic Control Algorithm. Application to Energy Management Problems

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Large Scale Experiment and Optimization of a Distributed Stochastic Control Algorithm. Application to Energy Management Problems

Auteurs : Pascal Vezolle [France] ; Stéphane Vialle [France] ; Xavier Warin [France]

Source :

RBID : Hal:hal-00390290

Abstract

Asset management for the electricity industry leads to very large stochastic optimization problem. We explain in this article how to efficiently distribute the Bellman algorithm used, re-distributing data and computations at each time step, and we examine the parallelization of a simulation algorithm usually used after this optimization part. We focus on distributed architectures with shared memory multi-core nodes, and we design a multiparadigm parallel algorithm, implemented with both MPI and multithreading mechanisms. Then we lay emphasis on the serial optimizations carried out to achieve high performances both on a dual-core PC cluster and a Blue Gene/P IBM supercomputer with quadcore nodes. Finally, we introduce experimental results achieved on two large testbeds, running a 7-stocks and 10-state-variables benchmark, and we show the impact of multithreading and serial optimizations on our distributed application.

Url:

https://hal-supelec.archives-ouvertes.fr/hal-00390290

DOI: 10.1109/IPDPS.2009.5161096

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Le document en format XML

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Large Scale Experiment and Optimization of a Distributed Stochastic Control Algorithm. Application to Energy Management Problems

Large Scale Experiment and Optimization of a Distributed Stochastic Control Algorithm. Application to Energy Management Problems

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