Artículo

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

Bazterra, Victor E.; Cuma, Martin; Ferraro, Marta BeatrizIcon ; Facelli, Julio C.
Fecha de publicación: 12/2005
Editorial: Academic Press Inc Elsevier Science
Revista: Journal Of Parallel And Distributed Computing
ISSN: 0743-7315
Idioma: Inglés
Tipo de recurso: Artículo publicado
Clasificación temática:

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.
Palabras clave: HETEROGENEOUS PARALLEL ENVIRONMENT , PARALLEL GENETIC ALGORITHMS , PERFORMANCE ANALYSIS
 
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info:eu-repo/semantics/openAccess Excepto donde se diga explícitamente, este item se publica bajo la siguiente descripción: Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Unported (CC BY-NC-SA 2.5)
Identificadores
URI: http://hdl.handle.net/11336/73283
DOI: http://dx.doi.org/10.1016/j.jpdc.2004.09.011
URL: https://www.sciencedirect.com/science/article/abs/pii/S0743731504001741
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Citación
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
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