GPU implementations of scheduling heuristics for heterogeneous computing environments

Autores
Nesmachnow, Sergio; Canabé, Mauro
Año de publicación
2011
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
This work presents the application of parallel computing techniques using Graphic Processing Units to improve the effciency of scheduling heuristics for heterogeneous computing systems. The experimental evaluation of the proposed methods demonstrates that a signiffcant reduction on the computing times can be attained, allowing to tackle large scheduling scenarios in reasonable execution times.
Presentado en el XI Workshop Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
GPU computing; heterogeneous computing
Scheduling
Graphics processors
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:10915/18652

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spelling GPU implementations of scheduling heuristics for heterogeneous computing environmentsNesmachnow, SergioCanabé, MauroCiencias InformáticasGPU computing; heterogeneous computingSchedulingGraphics processorsThis work presents the application of parallel computing techniques using Graphic Processing Units to improve the effciency of scheduling heuristics for heterogeneous computing systems. The experimental evaluation of the proposed methods demonstrates that a signiffcant reduction on the computing times can be attained, allowing to tackle large scheduling scenarios in reasonable execution times.Presentado en el XI Workshop Procesamiento Distribuido y Paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI)2011-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf292-301http://sedici.unlp.edu.ar/handle/10915/18652enginfo: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:UNLP2025-09-10T11:56:58Zoai:sedici.unlp.edu.ar:10915/18652Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-10 11:56:58.768SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv GPU implementations of scheduling heuristics for heterogeneous computing environments
title GPU implementations of scheduling heuristics for heterogeneous computing environments
spellingShingle GPU implementations of scheduling heuristics for heterogeneous computing environments
Nesmachnow, Sergio
Ciencias Informáticas
GPU computing; heterogeneous computing
Scheduling
Graphics processors
title_short GPU implementations of scheduling heuristics for heterogeneous computing environments
title_full GPU implementations of scheduling heuristics for heterogeneous computing environments
title_fullStr GPU implementations of scheduling heuristics for heterogeneous computing environments
title_full_unstemmed GPU implementations of scheduling heuristics for heterogeneous computing environments
title_sort GPU implementations of scheduling heuristics for heterogeneous computing environments
dc.creator.none.fl_str_mv Nesmachnow, Sergio
Canabé, Mauro
author Nesmachnow, Sergio
author_facet Nesmachnow, Sergio
Canabé, Mauro
author_role author
author2 Canabé, Mauro
author2_role author
dc.subject.none.fl_str_mv Ciencias Informáticas
GPU computing; heterogeneous computing
Scheduling
Graphics processors
topic Ciencias Informáticas
GPU computing; heterogeneous computing
Scheduling
Graphics processors
dc.description.none.fl_txt_mv This work presents the application of parallel computing techniques using Graphic Processing Units to improve the effciency of scheduling heuristics for heterogeneous computing systems. The experimental evaluation of the proposed methods demonstrates that a signiffcant reduction on the computing times can be attained, allowing to tackle large scheduling scenarios in reasonable execution times.
Presentado en el XI Workshop Procesamiento Distribuido y Paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
description This work presents the application of parallel computing techniques using Graphic Processing Units to improve the effciency of scheduling heuristics for heterogeneous computing systems. The experimental evaluation of the proposed methods demonstrates that a signiffcant reduction on the computing times can be attained, allowing to tackle large scheduling scenarios in reasonable execution times.
publishDate 2011
dc.date.none.fl_str_mv 2011-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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http://purl.org/coar/resource_type/c_5794
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status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/18652
url http://sedici.unlp.edu.ar/handle/10915/18652
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
292-301
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