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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/9396
Ver los metadatos del registro completo
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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 http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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http://sedici.unlp.edu.ar/handle/10915/9396 |
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http://sedici.unlp.edu.ar/handle/10915/9396 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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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) |
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openAccess |
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http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
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application/pdf |
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