A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling

Autores
Pi Puig, Martín; De Giusti, Laura Cristina; Naiouf, Marcelo; De Giusti, Armando Eduardo
Año de publicación
2019
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
In the exascale race where huge corporations are spending billions of dollars on designing highly efficient heterogeneous supercomputers, the real need to reduce power envelopes forces current technologies to face crucial challenges as well as it demands the scientific community to evaluate and optimize the performance-power ratio. While energy consumption continues to climb up, the viability of these massive systems becomes a growing concern. In this context, the relevance of specific power-related research works turns into a priority. So we here develop an exhaustive step-by-step process for selecting a comprehensive set of hardware performance counters to serve as an input in an eventual GPU cross-architectural power consumption model. Our experiments show a high power-performance correlation between shared GPU events. Also, we present a set of events that delivers exclusive performance information in order to predict accurately GPU power fluctuations.
XX Workshop Procesamiento Distribuido y Paralelo.
Red de Universidades con Carreras en Informática
Materia
Ciencias Informáticas
GPU
Architectures
Performance Counters
Power Consumption
Correlation
Prediction
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/90904
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power ModelingPi Puig, MartínDe Giusti, Laura CristinaNaiouf, MarceloDe Giusti, Armando EduardoCiencias InformáticasGPUArchitecturesPerformance CountersPower ConsumptionCorrelationPredictionIn the exascale race where huge corporations are spending billions of dollars on designing highly efficient heterogeneous supercomputers, the real need to reduce power envelopes forces current technologies to face crucial challenges as well as it demands the scientific community to evaluate and optimize the performance-power ratio. While energy consumption continues to climb up, the viability of these massive systems becomes a growing concern. In this context, the relevance of specific power-related research works turns into a priority. So we here develop an exhaustive step-by-step process for selecting a comprehensive set of hardware performance counters to serve as an input in an eventual GPU cross-architectural power consumption model. Our experiments show a high power-performance correlation between shared GPU events. Also, we present a set of events that delivers exclusive performance information in order to predict accurately GPU power fluctuations.XX Workshop Procesamiento Distribuido y Paralelo.Red de Universidades con Carreras en Informática2019-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf126-139http://sedici.unlp.edu.ar/handle/10915/90904enginfo:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1info:eu-repo/semantics/reference/hdl/10915/90359info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:59:53Zoai:sedici.unlp.edu.ar:10915/90904Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:59:53.297SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
title A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
spellingShingle A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
Pi Puig, Martín
Ciencias Informáticas
GPU
Architectures
Performance Counters
Power Consumption
Correlation
Prediction
title_short A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
title_full A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
title_fullStr A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
title_full_unstemmed A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
title_sort A Study of Hardware Performance Counters Selection for Cross Architectural GPU Power Modeling
dc.creator.none.fl_str_mv Pi Puig, Martín
De Giusti, Laura Cristina
Naiouf, Marcelo
De Giusti, Armando Eduardo
author Pi Puig, Martín
author_facet Pi Puig, Martín
De Giusti, Laura Cristina
Naiouf, Marcelo
De Giusti, Armando Eduardo
author_role author
author2 De Giusti, Laura Cristina
Naiouf, Marcelo
De Giusti, Armando Eduardo
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
GPU
Architectures
Performance Counters
Power Consumption
Correlation
Prediction
topic Ciencias Informáticas
GPU
Architectures
Performance Counters
Power Consumption
Correlation
Prediction
dc.description.none.fl_txt_mv In the exascale race where huge corporations are spending billions of dollars on designing highly efficient heterogeneous supercomputers, the real need to reduce power envelopes forces current technologies to face crucial challenges as well as it demands the scientific community to evaluate and optimize the performance-power ratio. While energy consumption continues to climb up, the viability of these massive systems becomes a growing concern. In this context, the relevance of specific power-related research works turns into a priority. So we here develop an exhaustive step-by-step process for selecting a comprehensive set of hardware performance counters to serve as an input in an eventual GPU cross-architectural power consumption model. Our experiments show a high power-performance correlation between shared GPU events. Also, we present a set of events that delivers exclusive performance information in order to predict accurately GPU power fluctuations.
XX Workshop Procesamiento Distribuido y Paralelo.
Red de Universidades con Carreras en Informática
description In the exascale race where huge corporations are spending billions of dollars on designing highly efficient heterogeneous supercomputers, the real need to reduce power envelopes forces current technologies to face crucial challenges as well as it demands the scientific community to evaluate and optimize the performance-power ratio. While energy consumption continues to climb up, the viability of these massive systems becomes a growing concern. In this context, the relevance of specific power-related research works turns into a priority. So we here develop an exhaustive step-by-step process for selecting a comprehensive set of hardware performance counters to serve as an input in an eventual GPU cross-architectural power consumption model. Our experiments show a high power-performance correlation between shared GPU events. Also, we present a set of events that delivers exclusive performance information in order to predict accurately GPU power fluctuations.
publishDate 2019
dc.date.none.fl_str_mv 2019-10
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/10915/90904
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dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-987-688-377-1
info:eu-repo/semantics/reference/hdl/10915/90359
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
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126-139
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