Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies

Autores
Madera, Julio; Alba Torres, Enrique; Luque, Gabriel
Año de publicación
2006
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This paper proposes two parallel variants of an Estimation of Distribution Algorithm (EDA) that represents the probability distribution by means of a single connected graphical model based on a polytree structure. The main goal is to design a new and more effi cient EDA. Our algorithm is based on the master/slave model that allows to perform the estimation of the probability distribution (the most time-consuming phase in EDAs) in a parallel way. The aim of our experimental studies is manifold. Firstly, we show that our parallel versions achieve a notable reduction of the total execution time with respect to existing algorithms. Secondly, we study the behavior of the algorithm from the numerical point of view, analyzing the different versions. Finally, our methods are evaluated over three interconnection networks (Fast Ethernet, Gigabit Ethernet, and Myrinet) and a study on the infl uence of the parallel platform in the communication is performed.
VII Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
parallel estimation of distribution algorithms
polytree approximation distribution algorithm
Bayesian networks
Algorithms
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22673

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network_name_str SEDICI (UNLP)
spelling Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologiesMadera, JulioAlba Torres, EnriqueLuque, GabrielCiencias Informáticasparallel estimation of distribution algorithmspolytree approximation distribution algorithmBayesian networksAlgorithmsThis paper proposes two parallel variants of an Estimation of Distribution Algorithm (EDA) that represents the probability distribution by means of a single connected graphical model based on a polytree structure. The main goal is to design a new and more effi cient EDA. Our algorithm is based on the master/slave model that allows to perform the estimation of the probability distribution (the most time-consuming phase in EDAs) in a parallel way. The aim of our experimental studies is manifold. Firstly, we show that our parallel versions achieve a notable reduction of the total execution time with respect to existing algorithms. Secondly, we study the behavior of the algorithm from the numerical point of view, analyzing the different versions. Finally, our methods are evaluated over three interconnection networks (Fast Ethernet, Gigabit Ethernet, and Myrinet) and a study on the infl uence of the parallel platform in the communication is performed.VII Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI)2006-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1307-1318http://sedici.unlp.edu.ar/handle/10915/22673enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-11-05T12:35:04Zoai:sedici.unlp.edu.ar:10915/22673Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-11-05 12:35:04.508SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
title Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
spellingShingle Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
Madera, Julio
Ciencias Informáticas
parallel estimation of distribution algorithms
polytree approximation distribution algorithm
Bayesian networks
Algorithms
title_short Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
title_full Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
title_fullStr Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
title_full_unstemmed Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
title_sort Performance evaluation of the parallel polytree approximation distribution algorithm on three network technologies
dc.creator.none.fl_str_mv Madera, Julio
Alba Torres, Enrique
Luque, Gabriel
author Madera, Julio
author_facet Madera, Julio
Alba Torres, Enrique
Luque, Gabriel
author_role author
author2 Alba Torres, Enrique
Luque, Gabriel
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
parallel estimation of distribution algorithms
polytree approximation distribution algorithm
Bayesian networks
Algorithms
topic Ciencias Informáticas
parallel estimation of distribution algorithms
polytree approximation distribution algorithm
Bayesian networks
Algorithms
dc.description.none.fl_txt_mv This paper proposes two parallel variants of an Estimation of Distribution Algorithm (EDA) that represents the probability distribution by means of a single connected graphical model based on a polytree structure. The main goal is to design a new and more effi cient EDA. Our algorithm is based on the master/slave model that allows to perform the estimation of the probability distribution (the most time-consuming phase in EDAs) in a parallel way. The aim of our experimental studies is manifold. Firstly, we show that our parallel versions achieve a notable reduction of the total execution time with respect to existing algorithms. Secondly, we study the behavior of the algorithm from the numerical point of view, analyzing the different versions. Finally, our methods are evaluated over three interconnection networks (Fast Ethernet, Gigabit Ethernet, and Myrinet) and a study on the infl uence of the parallel platform in the communication is performed.
VII Workshop de Agentes y Sistemas Inteligentes (WASI)
Red de Universidades con Carreras en Informática (RedUNCI)
description This paper proposes two parallel variants of an Estimation of Distribution Algorithm (EDA) that represents the probability distribution by means of a single connected graphical model based on a polytree structure. The main goal is to design a new and more effi cient EDA. Our algorithm is based on the master/slave model that allows to perform the estimation of the probability distribution (the most time-consuming phase in EDAs) in a parallel way. The aim of our experimental studies is manifold. Firstly, we show that our parallel versions achieve a notable reduction of the total execution time with respect to existing algorithms. Secondly, we study the behavior of the algorithm from the numerical point of view, analyzing the different versions. Finally, our methods are evaluated over three interconnection networks (Fast Ethernet, Gigabit Ethernet, and Myrinet) and a study on the infl uence of the parallel platform in the communication is performed.
publishDate 2006
dc.date.none.fl_str_mv 2006-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/22673
url http://sedici.unlp.edu.ar/handle/10915/22673
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
1307-1318
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repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
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