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
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/22673
Ver los metadatos del registro completo
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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 |
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info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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eng |
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