The collective computing model

Autores
Gonzalez, Jesús Alberto; León, Coromoto; Piccoli, María Fabiana; Printista, Alicia Marcela; Roda García, José Luis; Rodríguez, Casiano; Sande, Francisco de
Año de publicación
2000
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the well-known Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and Normal supersteps. The structure of divisions produced by the Division Functions and the partnership relation among processors give place to communication patterns among processors that are topologically similar to a hypercube. We have named the resulting structures Dynamic Polytopes To illustrate these concepts, the Fast Fourier Transform Algorithm is used. Computational results prove the accuracy of the model in four different parallel computers: a Parsytec Power PC, a Cray T3E, a Silicon Graphics Origin 2000 and a Digital Alpha Server.
Facultad de Informática
Materia
Ciencias Informáticas
parallelism; bulk synchronous parallel model; supersteps; performance prediction; parallel computer
Parallel programming
Parallel processors
Algorithms
Simulation
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:10915/9396

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network_name_str SEDICI (UNLP)
spelling The collective computing modelGonzalez, Jesús AlbertoLeón, CoromotoPiccoli, María FabianaPrintista, Alicia MarcelaRoda García, José LuisRodríguez, CasianoSande, Francisco deCiencias Informáticasparallelism; bulk synchronous parallel model; supersteps; performance prediction; parallel computerParallel programmingParallel processorsAlgorithmsSimulationThe parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the well-known Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and Normal supersteps. The structure of divisions produced by the Division Functions and the partnership relation among processors give place to communication patterns among processors that are topologically similar to a hypercube. We have named the resulting structures Dynamic Polytopes To illustrate these concepts, the Fast Fourier Transform Algorithm is used. Computational results prove the accuracy of the model in four different parallel computers: a Parsytec Power PC, a Cray T3E, a Silicon Graphics Origin 2000 and a Digital Alpha Server.Facultad de Informática2000info: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/10915/9396enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/pap2.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:UNLP2025-09-29T10:50:40Zoai:sedici.unlp.edu.ar:10915/9396Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:40.253SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv The collective computing model
title The collective computing model
spellingShingle The collective computing model
Gonzalez, Jesús Alberto
Ciencias Informáticas
parallelism; bulk synchronous parallel model; supersteps; performance prediction; parallel computer
Parallel programming
Parallel processors
Algorithms
Simulation
title_short The collective computing model
title_full The collective computing model
title_fullStr The collective computing model
title_full_unstemmed The collective computing model
title_sort The collective computing model
dc.creator.none.fl_str_mv Gonzalez, Jesús Alberto
León, Coromoto
Piccoli, María Fabiana
Printista, Alicia Marcela
Roda García, José Luis
Rodríguez, Casiano
Sande, Francisco de
author Gonzalez, Jesús Alberto
author_facet Gonzalez, Jesús Alberto
León, Coromoto
Piccoli, María Fabiana
Printista, Alicia Marcela
Roda García, José Luis
Rodríguez, Casiano
Sande, Francisco de
author_role author
author2 León, Coromoto
Piccoli, María Fabiana
Printista, Alicia Marcela
Roda García, José Luis
Rodríguez, Casiano
Sande, Francisco de
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
parallelism; bulk synchronous parallel model; supersteps; performance prediction; parallel computer
Parallel programming
Parallel processors
Algorithms
Simulation
topic Ciencias Informáticas
parallelism; bulk synchronous parallel model; supersteps; performance prediction; parallel computer
Parallel programming
Parallel processors
Algorithms
Simulation
dc.description.none.fl_txt_mv The parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the well-known Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and Normal supersteps. The structure of divisions produced by the Division Functions and the partnership relation among processors give place to communication patterns among processors that are topologically similar to a hypercube. We have named the resulting structures Dynamic Polytopes To illustrate these concepts, the Fast Fourier Transform Algorithm is used. Computational results prove the accuracy of the model in four different parallel computers: a Parsytec Power PC, a Cray T3E, a Silicon Graphics Origin 2000 and a Digital Alpha Server.
Facultad de Informática
description The parallel computing model used in this paper, the Collective Computing Model (CCM), is a variant of the well-known Bulk Synchronous Parallel (BSP) model. The synchronicity imposed by the BSP model restricts the set of available algorithms and prevents the overlapping of computation and communication. Other models, like the LogP model, allow asynchronous computing and overlapping but depend on the use of specific libraries. The CCM describes a system exploited through a standard software platform providing facilities for group creation, collective operations and remote memory operations. Based in the BSP model, two kinds of supersteps are considered: Division supersteps and Normal supersteps. The structure of divisions produced by the Division Functions and the partnership relation among processors give place to communication patterns among processors that are topologically similar to a hypercube. We have named the resulting structures Dynamic Polytopes To illustrate these concepts, the Fast Fourier Transform Algorithm is used. Computational results prove the accuracy of the model in four different parallel computers: a Parsytec Power PC, a Cray T3E, a Silicon Graphics Origin 2000 and a Digital Alpha Server.
publishDate 2000
dc.date.none.fl_str_mv 2000
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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info:ar-repo/semantics/articulo
format article
status_str publishedVersion
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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)
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instname:Universidad Nacional de La Plata
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instname_str Universidad Nacional de La Plata
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