Robustness analysis for the method of assignment MATEHa

Autores
De Giusti, Laura Cristina; Chichizola, Franco; Naiouf, Marcelo; De Giusti, Armando Eduardo
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The TTIGHa model has been developed to model and predict the performance of parallel applications run over heterogeneous architectures. In addition, the task assignment algorithm was implemented to MATEHa processors based on the TTIGHa model. This paper analyzes the assignment algorithm robustness before different variations which the model parameters may undergo (basically, communication and processing times).
Facultad de Informática
Materia
Ciencias Informáticas
cluster and multicluster architectures
heterogeneous processor
Parallel processing
Modeling and prediction
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:10915/9616
Acceder
id SEDICI_2bb47a06a8667d3137fe46bc02cc52e6
oai_identifier_str oai:sedici.unlp.edu.ar:10915/9616
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Robustness analysis for the method of assignment MATEHaDe Giusti, Laura CristinaChichizola, FrancoNaiouf, MarceloDe Giusti, Armando EduardoCiencias Informáticascluster and multicluster architecturesheterogeneous processorParallel processingModeling and predictionThe TTIGHa model has been developed to model and predict the performance of parallel applications run over heterogeneous architectures. In addition, the task assignment algorithm was implemented to MATEHa processors based on the TTIGHa model. This paper analyzes the assignment algorithm robustness before different variations which the model parameters may undergo (basically, communication and processing times).Facultad de Informática2008-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf1-7http://sedici.unlp.edu.ar/handle/10915/9616enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr08-1.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:UNLP2025-09-29T10:50:44Zoai:sedici.unlp.edu.ar:10915/9616Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:50:45.115SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Robustness analysis for the method of assignment MATEHa
title Robustness analysis for the method of assignment MATEHa
spellingShingle Robustness analysis for the method of assignment MATEHa
De Giusti, Laura Cristina
Ciencias Informáticas
cluster and multicluster architectures
heterogeneous processor
Parallel processing
Modeling and prediction
title_short Robustness analysis for the method of assignment MATEHa
title_full Robustness analysis for the method of assignment MATEHa
title_fullStr Robustness analysis for the method of assignment MATEHa
title_full_unstemmed Robustness analysis for the method of assignment MATEHa
title_sort Robustness analysis for the method of assignment MATEHa
dc.creator.none.fl_str_mv De Giusti, Laura Cristina
Chichizola, Franco
Naiouf, Marcelo
De Giusti, Armando Eduardo
author De Giusti, Laura Cristina
author_facet De Giusti, Laura Cristina
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
cluster and multicluster architectures
heterogeneous processor
Parallel processing
Modeling and prediction
topic Ciencias Informáticas
cluster and multicluster architectures
heterogeneous processor
Parallel processing
Modeling and prediction
dc.description.none.fl_txt_mv The TTIGHa model has been developed to model and predict the performance of parallel applications run over heterogeneous architectures. In addition, the task assignment algorithm was implemented to MATEHa processors based on the TTIGHa model. This paper analyzes the assignment algorithm robustness before different variations which the model parameters may undergo (basically, communication and processing times).
Facultad de Informática
description The TTIGHa model has been developed to model and predict the performance of parallel applications run over heterogeneous architectures. In addition, the task assignment algorithm was implemented to MATEHa processors based on the TTIGHa model. This paper analyzes the assignment algorithm robustness before different variations which the model parameters may undergo (basically, communication and processing times).
publishDate 2008
dc.date.none.fl_str_mv 2008-04
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/10915/9616
url http://sedici.unlp.edu.ar/handle/10915/9616
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Apr08-1.pdf
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
1-7
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 13.070432

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