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dc.contributor.author
Bazterra, Victor E.  
dc.contributor.author
Cuma, Martin  
dc.contributor.author
Ferraro, Marta Beatriz  
dc.contributor.author
Facelli, Julio C.  
dc.date.available
2019-04-05T16:05:16Z  
dc.date.issued
2005-12  
dc.identifier.citation
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  
dc.identifier.issn
0743-7315  
dc.identifier.uri
http://hdl.handle.net/11336/73283  
dc.description.abstract
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.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Academic Press Inc Elsevier Science  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
HETEROGENEOUS PARALLEL ENVIRONMENT  
dc.subject
PARALLEL GENETIC ALGORITHMS  
dc.subject
PERFORMANCE ANALYSIS  
dc.subject.classification
Astronomía  
dc.subject.classification
Ciencias Físicas  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2019-03-27T18:18:08Z  
dc.journal.volume
65  
dc.journal.number
1  
dc.journal.pagination
48-57  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Nueva York  
dc.description.fil
Fil: Bazterra, Victor E.. Universidad de Buenos Aires; Argentina. University of Utah; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Cuma, Martin. University of Utah; Estados Unidos. Universidad de Buenos Aires; Argentina  
dc.description.fil
Fil: 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; Argentina  
dc.description.fil
Fil: Facelli, Julio C.. University of Utah; Estados Unidos. Universidad de Buenos Aires; Argentina  
dc.journal.title
Journal Of Parallel And Distributed Computing  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.jpdc.2004.09.011  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0743731504001741  

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