Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis

Autores
De Giusti, Laura Cristina; Naiouf, Marcelo; Chichizola, Franco; Luque Fadón, Emilio; De Giusti, Armando Eduardo
Año de publicación
2009
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
A MPAHA (Model for Parallel Algorithms on Heterogeneous Architectures) model that allows predicting parallel application performance running over heterogeneous architectures is presented. MPAHA considers the heterogeneity of processors and communications. From the results obtained with the MPAHA model, the AMTHA (Automatic Mapping Task on Heterogeneous Architectures) algorithm for task-to-processors assignment is presented and its implementation is analyzed. DCS_AMTHA, a dynamic scheduling strategy for multiple applications on heterogeneous multiprocessor architectures, is defined and experimental results focusing on global efficiency are presented. Finally, current lines of research related with model extensions for clusters of multicores are mentioned.
Presentado en el IX Workshop Procesamiento Distribuido y Paralelo (WPDP).
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Scheduling
Parallel algorithms
Distributed architectures
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/20904
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/20904
network_acronym_str SEDICI
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network_name_str SEDICI (UNLP)
spelling Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysisDe Giusti, Laura CristinaNaiouf, MarceloChichizola, FrancoLuque Fadón, EmilioDe Giusti, Armando EduardoCiencias InformáticasSchedulingParallel algorithmsDistributed architecturesA MPAHA (Model for Parallel Algorithms on Heterogeneous Architectures) model that allows predicting parallel application performance running over heterogeneous architectures is presented. MPAHA considers the heterogeneity of processors and communications. From the results obtained with the MPAHA model, the AMTHA (Automatic Mapping Task on Heterogeneous Architectures) algorithm for task-to-processors assignment is presented and its implementation is analyzed. DCS_AMTHA, a dynamic scheduling strategy for multiple applications on heterogeneous multiprocessor architectures, is defined and experimental results focusing on global efficiency are presented. Finally, current lines of research related with model extensions for clusters of multicores are mentioned.Presentado en el IX Workshop Procesamiento Distribuido y Paralelo (WPDP).Red de Universidades con Carreras en Informática (RedUNCI)2009-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf221-230http://sedici.unlp.edu.ar/handle/10915/20904enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:27:14Zoai:sedici.unlp.edu.ar:10915/20904Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:27:15.218SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
title Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
spellingShingle Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
De Giusti, Laura Cristina
Ciencias Informáticas
Scheduling
Parallel algorithms
Distributed architectures
title_short Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
title_full Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
title_fullStr Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
title_full_unstemmed Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
title_sort Dynamic scheduling in heterogeneous multiprocessor architectures : Efficiency analysis
dc.creator.none.fl_str_mv De Giusti, Laura Cristina
Naiouf, Marcelo
Chichizola, Franco
Luque Fadón, Emilio
De Giusti, Armando Eduardo
author De Giusti, Laura Cristina
author_facet De Giusti, Laura Cristina
Naiouf, Marcelo
Chichizola, Franco
Luque Fadón, Emilio
De Giusti, Armando Eduardo
author_role author
author2 Naiouf, Marcelo
Chichizola, Franco
Luque Fadón, Emilio
De Giusti, Armando Eduardo
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Scheduling
Parallel algorithms
Distributed architectures
topic Ciencias Informáticas
Scheduling
Parallel algorithms
Distributed architectures
dc.description.none.fl_txt_mv A MPAHA (Model for Parallel Algorithms on Heterogeneous Architectures) model that allows predicting parallel application performance running over heterogeneous architectures is presented. MPAHA considers the heterogeneity of processors and communications. From the results obtained with the MPAHA model, the AMTHA (Automatic Mapping Task on Heterogeneous Architectures) algorithm for task-to-processors assignment is presented and its implementation is analyzed. DCS_AMTHA, a dynamic scheduling strategy for multiple applications on heterogeneous multiprocessor architectures, is defined and experimental results focusing on global efficiency are presented. Finally, current lines of research related with model extensions for clusters of multicores are mentioned.
Presentado en el IX Workshop Procesamiento Distribuido y Paralelo (WPDP).
Red de Universidades con Carreras en Informática (RedUNCI)
description A MPAHA (Model for Parallel Algorithms on Heterogeneous Architectures) model that allows predicting parallel application performance running over heterogeneous architectures is presented. MPAHA considers the heterogeneity of processors and communications. From the results obtained with the MPAHA model, the AMTHA (Automatic Mapping Task on Heterogeneous Architectures) algorithm for task-to-processors assignment is presented and its implementation is analyzed. DCS_AMTHA, a dynamic scheduling strategy for multiple applications on heterogeneous multiprocessor architectures, is defined and experimental results focusing on global efficiency are presented. Finally, current lines of research related with model extensions for clusters of multicores are mentioned.
publishDate 2009
dc.date.none.fl_str_mv 2009-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/20904
url http://sedici.unlp.edu.ar/handle/10915/20904
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-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
dc.format.none.fl_str_mv application/pdf
221-230
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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