@misc{10481/77931,
year = {2011},
url = {https://hdl.handle.net/10481/77931},
abstract = {The work presented in this paper consists in an adaptation
of a Genetic Algorithm (GA) to perform variable selection in an heterogeneous
cluster where the nodes are themselves clusters of GPUs. Due
to this heterogeneity, several mechanisms to perform a load balance will
be discussed as well as the optimization of the fitness function to take
advantage of the GPUs available. The algorithm will be compared with
previous parallel implementations analysing the advantages and disadvantages
of the approach, showing that for large data sets, the proposed
approach is the only one that can provide a solution.},
organization = {Spanish CICYT Project TIN2007-60587 and TEC2008-04920},
organization = {Junta Andalucia
Projects P08-TIC-03674 and P08-TIC03928 and PYR-2010-17 of CEI
BioTIC GENIL (CEB09-0010) of the MICINN},
publisher = {Springer},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {Variable Selection in a GPU Cluster Using Delta Test},
author = {Guillén Perales, Alberto and García Arenas, María Isabel and Herrera Maldonado, Luis Javier and Pomares Cintas, Héctor Emilio and Rojas Ruiz, Ignacio},
}