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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/90904
Ver los metadatos del registro completo
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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:UNLP2025-09-29T11:19:03Zoai: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:13292025-09-29 11:19:03.342SEDICI (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 |
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conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/90904 |
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http://sedici.unlp.edu.ar/handle/10915/90904 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
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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) |
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openAccess |
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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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application/pdf 126-139 |
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