Methodology for efficient Execution of SPMD applications on Multicore Clusters

Autores
Muresano, Ronal
Año de publicación
2011
Idioma
inglés
Tipo de recurso
reseña artículo
Estado
versión publicada
Descripción
Nowadays, the scientific applications are developed with more complexity and accuracy and these precisions need high computational resources to be executed. Also, the current trend in high performance computing (HPC) is to find clusters composed of Multicore nodes, and these nodes include heterogeneity levels which have to be handled carefully if we want to improve the performance metrics. The integration of these Multicore nodes in HPC (High Performance Computing) has allowed the inclusion of more parallelism within nodes, but this parallelism generates challenges that have to be managed considering some troubles present in these environments that affect the application efficiency and speedup. Aspects associated to number of cores, data locality, shared cache, communications link inside the node, etc are considered relevant when our goal is to improve the performance.
Facultad de Informática
Materia
Ciencias Informáticas
Parallel
multicore
high performance computing
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/9704
Acceder
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network_name_str SEDICI (UNLP)
spelling Methodology for efficient Execution of SPMD applications on Multicore ClustersMuresano, RonalCiencias InformáticasParallelmulticorehigh performance computingNowadays, the scientific applications are developed with more complexity and accuracy and these precisions need high computational resources to be executed. Also, the current trend in high performance computing (HPC) is to find clusters composed of Multicore nodes, and these nodes include heterogeneity levels which have to be handled carefully if we want to improve the performance metrics. The integration of these Multicore nodes in HPC (High Performance Computing) has allowed the inclusion of more parallelism within nodes, but this parallelism generates challenges that have to be managed considering some troubles present in these environments that affect the application efficiency and speedup. Aspects associated to number of cores, data locality, shared cache, communications link inside the node, etc are considered relevant when our goal is to improve the performance.Facultad de Informática2011-10info:eu-repo/semantics/reviewinfo:eu-repo/semantics/publishedVersionRevisionhttp://purl.org/coar/resource_type/c_dcae04bcinfo:ar-repo/semantics/resenaArticuloapplication/pdf111-112http://sedici.unlp.edu.ar/handle/10915/9704enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct11-TO2.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:50:48Zoai:sedici.unlp.edu.ar:10915/9704Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:49.028SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Methodology for efficient Execution of SPMD applications on Multicore Clusters
title Methodology for efficient Execution of SPMD applications on Multicore Clusters
spellingShingle Methodology for efficient Execution of SPMD applications on Multicore Clusters
Muresano, Ronal
Ciencias Informáticas
Parallel
multicore
high performance computing
title_short Methodology for efficient Execution of SPMD applications on Multicore Clusters
title_full Methodology for efficient Execution of SPMD applications on Multicore Clusters
title_fullStr Methodology for efficient Execution of SPMD applications on Multicore Clusters
title_full_unstemmed Methodology for efficient Execution of SPMD applications on Multicore Clusters
title_sort Methodology for efficient Execution of SPMD applications on Multicore Clusters
dc.creator.none.fl_str_mv Muresano, Ronal
author Muresano, Ronal
author_facet Muresano, Ronal
author_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
Parallel
multicore
high performance computing
topic Ciencias Informáticas
Parallel
multicore
high performance computing
dc.description.none.fl_txt_mv Nowadays, the scientific applications are developed with more complexity and accuracy and these precisions need high computational resources to be executed. Also, the current trend in high performance computing (HPC) is to find clusters composed of Multicore nodes, and these nodes include heterogeneity levels which have to be handled carefully if we want to improve the performance metrics. The integration of these Multicore nodes in HPC (High Performance Computing) has allowed the inclusion of more parallelism within nodes, but this parallelism generates challenges that have to be managed considering some troubles present in these environments that affect the application efficiency and speedup. Aspects associated to number of cores, data locality, shared cache, communications link inside the node, etc are considered relevant when our goal is to improve the performance.
Facultad de Informática
description Nowadays, the scientific applications are developed with more complexity and accuracy and these precisions need high computational resources to be executed. Also, the current trend in high performance computing (HPC) is to find clusters composed of Multicore nodes, and these nodes include heterogeneity levels which have to be handled carefully if we want to improve the performance metrics. The integration of these Multicore nodes in HPC (High Performance Computing) has allowed the inclusion of more parallelism within nodes, but this parallelism generates challenges that have to be managed considering some troubles present in these environments that affect the application efficiency and speedup. Aspects associated to number of cores, data locality, shared cache, communications link inside the node, etc are considered relevant when our goal is to improve the performance.
publishDate 2011
dc.date.none.fl_str_mv 2011-10
dc.type.none.fl_str_mv info:eu-repo/semantics/review
info:eu-repo/semantics/publishedVersion
Revision
http://purl.org/coar/resource_type/c_dcae04bc
info:ar-repo/semantics/resenaArticulo
format review
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/9704
url http://sedici.unlp.edu.ar/handle/10915/9704
dc.language.none.fl_str_mv eng
language eng
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info:eu-repo/semantics/altIdentifier/issn/1666-6038
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/3.0/
Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)
dc.format.none.fl_str_mv application/pdf
111-112
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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