Methodology for predicting the energy consumption of SPMD application on virtualized environments
- Autores
- Balladini, Javier; Muresano, Ronal; Suppi, Remo; Rexachs del Rosario, Dolores; Luque Fadón, Emilio
- Año de publicación
- 2013
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Over the last decade, the computing clusters have been updated in order to satisfy the increasing demand of greater computational power for running applications. However, this increasing is transformed in more system en- ergy consumption, which results in financial, environmental and in some cases with social consequences. Hence, the ideal is to achieve an scenario that allows the system admin- istrator to find a trade-off between time and energy-efficiency for parallel algorithms on virtualized environments. The main objective of this work is based on developing an analytical model to predict the energy consumption and energy delay product (EDP) for SPMD applications on virtual environments. The SPMD applications selected are designed through a message passing interface (MPI) library with high communication volumes, which can generate im- balance issues that affect seriously the execution time and also the energy-efficiency. Our method is composed by four phases (characterization, tile distribution model, mapping and scheduling). This method has been validated using scientific applications and we observe that the minimum Energy and EDP values are located close to the values calculated with our analytical model with an error rate between 4% and 9%.
Facultad de Informática - Materia
-
Ciencias Informáticas
performance
energy
EDP
prediction
virtualization - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc/3.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/34507
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Methodology for predicting the energy consumption of SPMD application on virtualized environmentsBalladini, JavierMuresano, RonalSuppi, RemoRexachs del Rosario, DoloresLuque Fadón, EmilioCiencias InformáticasperformanceenergyEDPpredictionvirtualizationOver the last decade, the computing clusters have been updated in order to satisfy the increasing demand of greater computational power for running applications. However, this increasing is transformed in more system en- ergy consumption, which results in financial, environmental and in some cases with social consequences. Hence, the ideal is to achieve an scenario that allows the system admin- istrator to find a trade-off between time and energy-efficiency for parallel algorithms on virtualized environments. The main objective of this work is based on developing an analytical model to predict the energy consumption and energy delay product (EDP) for SPMD applications on virtual environments. The SPMD applications selected are designed through a message passing interface (MPI) library with high communication volumes, which can generate im- balance issues that affect seriously the execution time and also the energy-efficiency. Our method is composed by four phases (characterization, tile distribution model, mapping and scheduling). This method has been validated using scientific applications and we observe that the minimum Energy and EDP values are located close to the values calculated with our analytical model with an error rate between 4% and 9%.Facultad de Informática2013-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf130-136http://sedici.unlp.edu.ar/handle/10915/34507enginfo:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec13-4.pdfinfo:eu-repo/semantics/altIdentifier/issn/1666-6038info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc/3.0/Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:59:01Zoai:sedici.unlp.edu.ar:10915/34507Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:59:01.757SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Methodology for predicting the energy consumption of SPMD application on virtualized environments |
title |
Methodology for predicting the energy consumption of SPMD application on virtualized environments |
spellingShingle |
Methodology for predicting the energy consumption of SPMD application on virtualized environments Balladini, Javier Ciencias Informáticas performance energy EDP prediction virtualization |
title_short |
Methodology for predicting the energy consumption of SPMD application on virtualized environments |
title_full |
Methodology for predicting the energy consumption of SPMD application on virtualized environments |
title_fullStr |
Methodology for predicting the energy consumption of SPMD application on virtualized environments |
title_full_unstemmed |
Methodology for predicting the energy consumption of SPMD application on virtualized environments |
title_sort |
Methodology for predicting the energy consumption of SPMD application on virtualized environments |
dc.creator.none.fl_str_mv |
Balladini, Javier Muresano, Ronal Suppi, Remo Rexachs del Rosario, Dolores Luque Fadón, Emilio |
author |
Balladini, Javier |
author_facet |
Balladini, Javier Muresano, Ronal Suppi, Remo Rexachs del Rosario, Dolores Luque Fadón, Emilio |
author_role |
author |
author2 |
Muresano, Ronal Suppi, Remo Rexachs del Rosario, Dolores Luque Fadón, Emilio |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas performance energy EDP prediction virtualization |
topic |
Ciencias Informáticas performance energy EDP prediction virtualization |
dc.description.none.fl_txt_mv |
Over the last decade, the computing clusters have been updated in order to satisfy the increasing demand of greater computational power for running applications. However, this increasing is transformed in more system en- ergy consumption, which results in financial, environmental and in some cases with social consequences. Hence, the ideal is to achieve an scenario that allows the system admin- istrator to find a trade-off between time and energy-efficiency for parallel algorithms on virtualized environments. The main objective of this work is based on developing an analytical model to predict the energy consumption and energy delay product (EDP) for SPMD applications on virtual environments. The SPMD applications selected are designed through a message passing interface (MPI) library with high communication volumes, which can generate im- balance issues that affect seriously the execution time and also the energy-efficiency. Our method is composed by four phases (characterization, tile distribution model, mapping and scheduling). This method has been validated using scientific applications and we observe that the minimum Energy and EDP values are located close to the values calculated with our analytical model with an error rate between 4% and 9%. Facultad de Informática |
description |
Over the last decade, the computing clusters have been updated in order to satisfy the increasing demand of greater computational power for running applications. However, this increasing is transformed in more system en- ergy consumption, which results in financial, environmental and in some cases with social consequences. Hence, the ideal is to achieve an scenario that allows the system admin- istrator to find a trade-off between time and energy-efficiency for parallel algorithms on virtualized environments. The main objective of this work is based on developing an analytical model to predict the energy consumption and energy delay product (EDP) for SPMD applications on virtual environments. The SPMD applications selected are designed through a message passing interface (MPI) library with high communication volumes, which can generate im- balance issues that affect seriously the execution time and also the energy-efficiency. Our method is composed by four phases (characterization, tile distribution model, mapping and scheduling). This method has been validated using scientific applications and we observe that the minimum Energy and EDP values are located close to the values calculated with our analytical model with an error rate between 4% and 9%. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-12 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/34507 |
url |
http://sedici.unlp.edu.ar/handle/10915/34507 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/url/http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Dec13-4.pdf info:eu-repo/semantics/altIdentifier/issn/1666-6038 |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nc/3.0/ Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) |
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application/pdf 130-136 |
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SEDICI (UNLP) - Universidad Nacional de La Plata |
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