A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm

This paper presents a general model to define, measure and predict the efficiency of applications running on heterogeneous parallel computer systems. Using this framework, it is possible to understand the influence that the heterogeneity of the hardware has on the efficiency of an algorithm. This methodology is used to compare an existing parallel genetic algorithm with a new adaptive parallel model. All the performance measurements were taken in a loosely coupled cluster of processors. © 2004 Elsevier Inc. All rights reserved.Fil: Bazterra, Victor E.. Universidad de Buenos Aires; Argentina. University of Utah; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cuma, Martin. University of Utah; Estados Unidos. Universidad de Buenos Aires; ArgentinaFil: Ferraro, Marta Beatriz. University of Utah; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Facelli, Julio C.. University of Utah; Estados Unidos. Universidad de Buenos Aires; Argentin