Effective Use of Multicore Clusters in Parallel Cellular Automata

Autores
Printista, Alicia Marcela; Saez, Fernando
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. We start from a template designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the template is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this work we discuss and evaluate strategies that will be important in optimizing prototype to run on multicore cluster. The underlying idea in our proposal is the establishment of a relation among parallel processes based on the communication topology that arises in the implementation of task division functions. We propose that this relation can efficiently map on the multicore cluster topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Parallel Programming
Cellular Automata
Multicore Nodes
Mapping Strategy
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/126126

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spelling Effective Use of Multicore Clusters in Parallel Cellular AutomataPrintista, Alicia MarcelaSaez, FernandoCiencias InformáticasParallel ProgrammingCellular AutomataMulticore NodesMapping StrategyCellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. We start from a template designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the template is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this work we discuss and evaluate strategies that will be important in optimizing prototype to run on multicore cluster. The underlying idea in our proposal is the establishment of a relation among parallel processes based on the communication topology that arises in the implementation of task division functions. We propose that this relation can efficiently map on the multicore cluster topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.Sociedad Argentina de Informática e Investigación Operativa2011-08info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf76-88http://sedici.unlp.edu.ar/handle/10915/126126enginfo:eu-repo/semantics/altIdentifier/url/https://40jaiio.sadio.org.ar/sites/default/files/T2011/HPC/927.pdfinfo:eu-repo/semantics/altIdentifier/issn/1851-9326info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:30:27Zoai:sedici.unlp.edu.ar:10915/126126Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:30:28.132SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Effective Use of Multicore Clusters in Parallel Cellular Automata
title Effective Use of Multicore Clusters in Parallel Cellular Automata
spellingShingle Effective Use of Multicore Clusters in Parallel Cellular Automata
Printista, Alicia Marcela
Ciencias Informáticas
Parallel Programming
Cellular Automata
Multicore Nodes
Mapping Strategy
title_short Effective Use of Multicore Clusters in Parallel Cellular Automata
title_full Effective Use of Multicore Clusters in Parallel Cellular Automata
title_fullStr Effective Use of Multicore Clusters in Parallel Cellular Automata
title_full_unstemmed Effective Use of Multicore Clusters in Parallel Cellular Automata
title_sort Effective Use of Multicore Clusters in Parallel Cellular Automata
dc.creator.none.fl_str_mv Printista, Alicia Marcela
Saez, Fernando
author Printista, Alicia Marcela
author_facet Printista, Alicia Marcela
Saez, Fernando
author_role author
author2 Saez, Fernando
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Parallel Programming
Cellular Automata
Multicore Nodes
Mapping Strategy
topic Ciencias Informáticas
Parallel Programming
Cellular Automata
Multicore Nodes
Mapping Strategy
dc.description.none.fl_txt_mv Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. We start from a template designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the template is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this work we discuss and evaluate strategies that will be important in optimizing prototype to run on multicore cluster. The underlying idea in our proposal is the establishment of a relation among parallel processes based on the communication topology that arises in the implementation of task division functions. We propose that this relation can efficiently map on the multicore cluster topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.
Sociedad Argentina de Informática e Investigación Operativa
description Cellular automata provide an abstract model of parallel computation that can be effectively used for modeling and simulation of complex phenomena and systems. We start from a template designed to facilitate faster D-dimensional cellular automata application development. The key for the use of the template is to achieve an efficient implementation, irrespective of the application specific details. In the parallel implementation on a cluster was important to consider issues such as task and data decomposition. With multicore clusters, new problems have emerged. The increasing numbers of cores per node, caches and shared memory inside the nodes, has led to the formation of a new hierarchy of access to processors. In this work we discuss and evaluate strategies that will be important in optimizing prototype to run on multicore cluster. The underlying idea in our proposal is the establishment of a relation among parallel processes based on the communication topology that arises in the implementation of task division functions. We propose that this relation can efficiently map on the multicore cluster topology. We introduce a new mapping strategy that can obtain benefit in the performance by adapting its communication pattern to the hardware affinities among processes allocated in different cores. We apply our approach to a two-dimensional application achieving sensible execution time reduction.
publishDate 2011
dc.date.none.fl_str_mv 2011-08
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dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1851-9326
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http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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