A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures

Autores
de Giusti, Laura Cristina; Chichizola, Franco; Naiouf, Ricardo Marcelo; Ripoll, Ana; de Giusti, Armando Eduardo
Año de publicación
2007
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper discusses automatic mapping methods for concurrent tasks to processors applying graph analysis for the relation among tasks, in which processing and communicating times are incorporated.Starting by an analysis in which processors are homogeneous and data transmission times do not depend on the processors that are communicating (a typical case in homogeneous clusters), we progress to extend the model to heterogeneous processors having the possibility of different communication levels, applicable to a multicluster.Some results obtained with the model and future work lines are presented, particularly, the possibility of obtaining the required optimal number of processors, keeping a constant efficiency level.
Fil: de Giusti, Laura Cristina. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina
Fil: Chichizola, Franco. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Naiouf, Ricardo Marcelo. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina
Fil: Ripoll, Ana. Universidad de Barcelona; España
Fil: de Giusti, Armando Eduardo. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina
Materia
Parallel Systems
Cluster and Multi-Cluster Architectures
Performance Prediction Models
Mapping of Tasks to Processors
Homogeneous and Heterogeneous Processors
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/241894
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/241894
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architecturesde Giusti, Laura CristinaChichizola, FrancoNaiouf, Ricardo MarceloRipoll, Anade Giusti, Armando EduardoParallel SystemsCluster and Multi-Cluster ArchitecturesPerformance Prediction ModelsMapping of Tasks to ProcessorsHomogeneous and Heterogeneous Processorshttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2This paper discusses automatic mapping methods for concurrent tasks to processors applying graph analysis for the relation among tasks, in which processing and communicating times are incorporated.Starting by an analysis in which processors are homogeneous and data transmission times do not depend on the processors that are communicating (a typical case in homogeneous clusters), we progress to extend the model to heterogeneous processors having the possibility of different communication levels, applicable to a multicluster.Some results obtained with the model and future work lines are presented, particularly, the possibility of obtaining the required optimal number of processors, keeping a constant efficiency level.Fil: de Giusti, Laura Cristina. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; ArgentinaFil: Chichizola, Franco. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Naiouf, Ricardo Marcelo. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; ArgentinaFil: Ripoll, Ana. Universidad de Barcelona; EspañaFil: de Giusti, Armando Eduardo. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; ArgentinaUniversidad Nacional de La Plata. Facultad de Informática2007-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/241894de Giusti, Laura Cristina; Chichizola, Franco; Naiouf, Ricardo Marcelo; Ripoll, Ana; de Giusti, Armando Eduardo; A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures; Universidad Nacional de La Plata. Facultad de Informática; Journal of Computer Science and Technology; 7; 1; 12-2007; 39-441666-6046CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.redalyc.org/articulo.oa?id=638067340019info:eu-repo/semantics/altIdentifier/url/https://journal.info.unlp.edu.ar/JCST/article/view/801info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:11:32Zoai:ri.conicet.gov.ar:11336/241894instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-10 13:11:33.086CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
title A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
spellingShingle A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
de Giusti, Laura Cristina
Parallel Systems
Cluster and Multi-Cluster Architectures
Performance Prediction Models
Mapping of Tasks to Processors
Homogeneous and Heterogeneous Processors
title_short A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
title_full A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
title_fullStr A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
title_full_unstemmed A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
title_sort A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures
dc.creator.none.fl_str_mv de Giusti, Laura Cristina
Chichizola, Franco
Naiouf, Ricardo Marcelo
Ripoll, Ana
de Giusti, Armando Eduardo
author de Giusti, Laura Cristina
author_facet de Giusti, Laura Cristina
Chichizola, Franco
Naiouf, Ricardo Marcelo
Ripoll, Ana
de Giusti, Armando Eduardo
author_role author
author2 Chichizola, Franco
Naiouf, Ricardo Marcelo
Ripoll, Ana
de Giusti, Armando Eduardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Parallel Systems
Cluster and Multi-Cluster Architectures
Performance Prediction Models
Mapping of Tasks to Processors
Homogeneous and Heterogeneous Processors
topic Parallel Systems
Cluster and Multi-Cluster Architectures
Performance Prediction Models
Mapping of Tasks to Processors
Homogeneous and Heterogeneous Processors
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper discusses automatic mapping methods for concurrent tasks to processors applying graph analysis for the relation among tasks, in which processing and communicating times are incorporated.Starting by an analysis in which processors are homogeneous and data transmission times do not depend on the processors that are communicating (a typical case in homogeneous clusters), we progress to extend the model to heterogeneous processors having the possibility of different communication levels, applicable to a multicluster.Some results obtained with the model and future work lines are presented, particularly, the possibility of obtaining the required optimal number of processors, keeping a constant efficiency level.
Fil: de Giusti, Laura Cristina. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina
Fil: Chichizola, Franco. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; Argentina
Fil: Naiouf, Ricardo Marcelo. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina
Fil: Ripoll, Ana. Universidad de Barcelona; España
Fil: de Giusti, Armando Eduardo. Universidad Nacional de La Plata. Facultad de Informática. Instituto de Investigación en Informática Lidi; Argentina
description This paper discusses automatic mapping methods for concurrent tasks to processors applying graph analysis for the relation among tasks, in which processing and communicating times are incorporated.Starting by an analysis in which processors are homogeneous and data transmission times do not depend on the processors that are communicating (a typical case in homogeneous clusters), we progress to extend the model to heterogeneous processors having the possibility of different communication levels, applicable to a multicluster.Some results obtained with the model and future work lines are presented, particularly, the possibility of obtaining the required optimal number of processors, keeping a constant efficiency level.
publishDate 2007
dc.date.none.fl_str_mv 2007-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/241894
de Giusti, Laura Cristina; Chichizola, Franco; Naiouf, Ricardo Marcelo; Ripoll, Ana; de Giusti, Armando Eduardo; A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures; Universidad Nacional de La Plata. Facultad de Informática; Journal of Computer Science and Technology; 7; 1; 12-2007; 39-44
1666-6046
CONICET Digital
CONICET
url http://hdl.handle.net/11336/241894
identifier_str_mv de Giusti, Laura Cristina; Chichizola, Franco; Naiouf, Ricardo Marcelo; Ripoll, Ana; de Giusti, Armando Eduardo; A model for the automatic mapping of tasks to processors in heterogeneous multi-cluster architectures; Universidad Nacional de La Plata. Facultad de Informática; Journal of Computer Science and Technology; 7; 1; 12-2007; 39-44
1666-6046
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.redalyc.org/articulo.oa?id=638067340019
info:eu-repo/semantics/altIdentifier/url/https://journal.info.unlp.edu.ar/JCST/article/view/801
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Universidad Nacional de La Plata. Facultad de Informática
publisher.none.fl_str_mv Universidad Nacional de La Plata. Facultad de Informática
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 12.993085

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