info:eu-repo/semantics/article
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm
Fecha
2005-12Registro en:
Bazterra, Victor E.; Cuma, Martin; Ferraro, Marta Beatriz; Facelli, Julio C.; A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm; Academic Press Inc Elsevier Science; Journal Of Parallel And Distributed Computing; 65; 1; 12-2005; 48-57
0743-7315
CONICET Digital
CONICET
Autor
Bazterra, Victor E.
Cuma, Martin
Ferraro, Marta Beatriz
Facelli, Julio C.
Resumen
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.