@InProceedings{Supelec504,
author = {Pascal Vezolle and Stephane Vialle and Xavier Warin},
title = {{Large Scale Experiment and Optimization of a Distributed Stochastic Control Algorithm. Application to Energy Management Problems.}},
year = {2009},
booktitle = {{International workshop on Large-Scale Parallel Processing (LSPP 2009)}},
pages = {8 pages},
month = {May 29},
address = {Rome, Italy},
url = {http://www.metz.supelec.fr/metz/recherche/publis_pdf/Supelec504.pdf},
isbn = {978-1-4244-3750-4},
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.}
}