Performance comparison of parallel programming paradigms on a multicore cluster

Autores
Rucci, Enzo; Chichizola, Franco; Naiouf, Marcelo; De Giusti, Armando Eduardo
Año de publicación
2012
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Currently, most supercomputers are multicore clusters. This type of architectures is said to be hybrid, because they combine distributed memory with shared memory. Traditional parallel programming paradigms (message passing and shared memory) cannot be naturally adapted to the hardware features offered by these architectures. A parallel paradigm that combines message passing with shared memory is expected to better exploit them. Therefore, in this paper the performance of two parallel programming paradigms (message passing and combination of message passing with shared memory) is analyzed for multicore clusters. The study case used is the construction of phylogenetic trees by means of the Neighbor-Joining method. Finally, conclusions and future research lines are presented.
Facultad de Informática
Materia
Ciencias Informáticas
Parallel programming languages
Parallel computing methodologies
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/80059
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/80059
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Performance comparison of parallel programming paradigms on a multicore clusterRucci, EnzoChichizola, FrancoNaiouf, MarceloDe Giusti, Armando EduardoCiencias InformáticasParallel programming languagesParallel computing methodologiesCurrently, most supercomputers are multicore clusters. This type of architectures is said to be hybrid, because they combine distributed memory with shared memory. Traditional parallel programming paradigms (message passing and shared memory) cannot be naturally adapted to the hardware features offered by these architectures. A parallel paradigm that combines message passing with shared memory is expected to better exploit them. Therefore, in this paper the performance of two parallel programming paradigms (message passing and combination of message passing with shared memory) is analyzed for multicore clusters. The study case used is the construction of phylogenetic trees by means of the Neighbor-Joining method. Finally, conclusions and future research lines are presented.Facultad de Informática2012info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/80059enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/4.0/Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-15T11:06:33Zoai:sedici.unlp.edu.ar:10915/80059Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-15 11:06:34.125SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Performance comparison of parallel programming paradigms on a multicore cluster
title Performance comparison of parallel programming paradigms on a multicore cluster
spellingShingle Performance comparison of parallel programming paradigms on a multicore cluster
Rucci, Enzo
Ciencias Informáticas
Parallel programming languages
Parallel computing methodologies
title_short Performance comparison of parallel programming paradigms on a multicore cluster
title_full Performance comparison of parallel programming paradigms on a multicore cluster
title_fullStr Performance comparison of parallel programming paradigms on a multicore cluster
title_full_unstemmed Performance comparison of parallel programming paradigms on a multicore cluster
title_sort Performance comparison of parallel programming paradigms on a multicore cluster
dc.creator.none.fl_str_mv Rucci, Enzo
Chichizola, Franco
Naiouf, Marcelo
De Giusti, Armando Eduardo
author Rucci, Enzo
author_facet Rucci, Enzo
Chichizola, Franco
Naiouf, Marcelo
De Giusti, Armando Eduardo
author_role author
author2 Chichizola, Franco
Naiouf, Marcelo
De Giusti, Armando Eduardo
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Parallel programming languages
Parallel computing methodologies
topic Ciencias Informáticas
Parallel programming languages
Parallel computing methodologies
dc.description.none.fl_txt_mv Currently, most supercomputers are multicore clusters. This type of architectures is said to be hybrid, because they combine distributed memory with shared memory. Traditional parallel programming paradigms (message passing and shared memory) cannot be naturally adapted to the hardware features offered by these architectures. A parallel paradigm that combines message passing with shared memory is expected to better exploit them. Therefore, in this paper the performance of two parallel programming paradigms (message passing and combination of message passing with shared memory) is analyzed for multicore clusters. The study case used is the construction of phylogenetic trees by means of the Neighbor-Joining method. Finally, conclusions and future research lines are presented.
Facultad de Informática
description Currently, most supercomputers are multicore clusters. This type of architectures is said to be hybrid, because they combine distributed memory with shared memory. Traditional parallel programming paradigms (message passing and shared memory) cannot be naturally adapted to the hardware features offered by these architectures. A parallel paradigm that combines message passing with shared memory is expected to better exploit them. Therefore, in this paper the performance of two parallel programming paradigms (message passing and combination of message passing with shared memory) is analyzed for multicore clusters. The study case used is the construction of phylogenetic trees by means of the Neighbor-Joining method. Finally, conclusions and future research lines are presented.
publishDate 2012
dc.date.none.fl_str_mv 2012
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/80059
url http://sedici.unlp.edu.ar/handle/10915/80059
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/4.0/
Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc/4.0/
Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
dc.format.none.fl_str_mv application/pdf
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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score 13.22299

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