Power characterisation of shared-memory hpc systems

Autores
Balladini, Javier; Rucci, Enzo; De Giusti, Armando Eduardo; Naiouf, Marcelo; Suppi, Remo; Rexachs del Rosario, Dolores; Luque Fadón, Emilio
Año de publicación
2012
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Energy consumption has become one of the greatest challenges in the eld of High Performance Computing (HPC). Besides its impact on the environment, energy is a limiting factor for the HPC. Keeping the power consumption of a system below a threshold is one of the great problems; and power prediction can help to solve it. The power characterisation can be used to know the power behaviour of the system under study, and to be a support to reach the power prediction. Furthermore, it could be used to design power-aware application programs. In this article we propose a methodology to characterise the power consumption of shared-memory HPC systems. Our proposed methodology involves the nding of in uence factors on power consumed by the systems. It is similar to previous works, but we propose an in-deep approach that can help us to get a better power characterisation of the system. We apply our methodology to characterise an Intel server platform and the results show that we can nd a more extended set of in uence factors on power consumption.
Eje: Workshop Procesamiento distribuido y paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Power Characterisation
Shared-Memory
HPC Systems
Distributed
Parallel
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:10915/23630
Acceder
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spelling Power characterisation of shared-memory hpc systemsBalladini, JavierRucci, EnzoDe Giusti, Armando EduardoNaiouf, MarceloSuppi, RemoRexachs del Rosario, DoloresLuque Fadón, EmilioCiencias InformáticasPower CharacterisationShared-MemoryHPC SystemsDistributedParallelEnergy consumption has become one of the greatest challenges in the eld of High Performance Computing (HPC). Besides its impact on the environment, energy is a limiting factor for the HPC. Keeping the power consumption of a system below a threshold is one of the great problems; and power prediction can help to solve it. The power characterisation can be used to know the power behaviour of the system under study, and to be a support to reach the power prediction. Furthermore, it could be used to design power-aware application programs. In this article we propose a methodology to characterise the power consumption of shared-memory HPC systems. Our proposed methodology involves the nding of in uence factors on power consumed by the systems. It is similar to previous works, but we propose an in-deep approach that can help us to get a better power characterisation of the system. We apply our methodology to characterise an Intel server platform and the results show that we can nd a more extended set of in uence factors on power consumption.Eje: Workshop Procesamiento distribuido y paralelo (WPDP)Red de Universidades con Carreras en Informática (RedUNCI)2012-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23630enginfo: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:UNLP2025-09-29T10:55:31Zoai:sedici.unlp.edu.ar:10915/23630Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:31.751SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Power characterisation of shared-memory hpc systems
title Power characterisation of shared-memory hpc systems
spellingShingle Power characterisation of shared-memory hpc systems
Balladini, Javier
Ciencias Informáticas
Power Characterisation
Shared-Memory
HPC Systems
Distributed
Parallel
title_short Power characterisation of shared-memory hpc systems
title_full Power characterisation of shared-memory hpc systems
title_fullStr Power characterisation of shared-memory hpc systems
title_full_unstemmed Power characterisation of shared-memory hpc systems
title_sort Power characterisation of shared-memory hpc systems
dc.creator.none.fl_str_mv Balladini, Javier
Rucci, Enzo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Suppi, Remo
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author Balladini, Javier
author_facet Balladini, Javier
Rucci, Enzo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Suppi, Remo
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author_role author
author2 Rucci, Enzo
De Giusti, Armando Eduardo
Naiouf, Marcelo
Suppi, Remo
Rexachs del Rosario, Dolores
Luque Fadón, Emilio
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Power Characterisation
Shared-Memory
HPC Systems
Distributed
Parallel
topic Ciencias Informáticas
Power Characterisation
Shared-Memory
HPC Systems
Distributed
Parallel
dc.description.none.fl_txt_mv Energy consumption has become one of the greatest challenges in the eld of High Performance Computing (HPC). Besides its impact on the environment, energy is a limiting factor for the HPC. Keeping the power consumption of a system below a threshold is one of the great problems; and power prediction can help to solve it. The power characterisation can be used to know the power behaviour of the system under study, and to be a support to reach the power prediction. Furthermore, it could be used to design power-aware application programs. In this article we propose a methodology to characterise the power consumption of shared-memory HPC systems. Our proposed methodology involves the nding of in uence factors on power consumed by the systems. It is similar to previous works, but we propose an in-deep approach that can help us to get a better power characterisation of the system. We apply our methodology to characterise an Intel server platform and the results show that we can nd a more extended set of in uence factors on power consumption.
Eje: Workshop Procesamiento distribuido y paralelo (WPDP)
Red de Universidades con Carreras en Informática (RedUNCI)
description Energy consumption has become one of the greatest challenges in the eld of High Performance Computing (HPC). Besides its impact on the environment, energy is a limiting factor for the HPC. Keeping the power consumption of a system below a threshold is one of the great problems; and power prediction can help to solve it. The power characterisation can be used to know the power behaviour of the system under study, and to be a support to reach the power prediction. Furthermore, it could be used to design power-aware application programs. In this article we propose a methodology to characterise the power consumption of shared-memory HPC systems. Our proposed methodology involves the nding of in uence factors on power consumed by the systems. It is similar to previous works, but we propose an in-deep approach that can help us to get a better power characterisation of the system. We apply our methodology to characterise an Intel server platform and the results show that we can nd a more extended set of in uence factors on power consumption.
publishDate 2012
dc.date.none.fl_str_mv 2012-10
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/10915/23630
url http://sedici.unlp.edu.ar/handle/10915/23630
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
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
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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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