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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/126126
Ver los metadatos del registro completo
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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 |
dc.type.none.fl_str_mv |
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 |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/126126 |
url |
http://sedici.unlp.edu.ar/handle/10915/126126 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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openAccess |
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