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Large scale experiment and optimization of a distributed stochastic control algorithm. Application to energy management problems

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3 Author(s)
Vezolle, P. ; IBM Deep Comput. Eur., Montpellier, France ; Vialle, S. ; Warin, X.

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 quad-core 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.

Published in:

Parallel & Distributed Processing, 2009. IPDPS 2009. IEEE International Symposium on

Date of Conference:

23-29 May 2009