Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings

Autores
Longo, Mathias; Rodriguez, Ana Virginia; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio
Año de publicación
2019
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In-silico research has grown considerably. Today's scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.
Fil: Longo, Mathias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. University of Southern California; Estados Unidos
Fil: Rodriguez, Ana Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Materia
Energy
Scientific applications
Java
Micro-benchmarks
Code refactoring
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/121006
Acceder
id CONICETDig_1ed6f289ca5316d837f13ba77fda2738
oai_identifier_str oai:ri.conicet.gov.ar:11336/121006
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactoringsLongo, MathiasRodriguez, Ana VirginiaMateos Diaz, Cristian MaximilianoZunino Suarez, Alejandro OctavioEnergyScientific applicationsJavaMicro-benchmarksCode refactoringhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1In-silico research has grown considerably. Today's scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.Fil: Longo, Mathias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. University of Southern California; Estados UnidosFil: Rodriguez, Ana Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaFil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; ArgentinaComsis Consortium2019-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/121006Longo, Mathias; Rodriguez, Ana Virginia; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings; Comsis Consortium; Computer Science And Information Systems; 16; 2; 6-2019; 541-5641820-0214CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.comsis.org/archive.php?show=ppr675-1806info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:23:59Zoai:ri.conicet.gov.ar:11336/121006instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:23:59.599CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
title Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
spellingShingle Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
Longo, Mathias
Energy
Scientific applications
Java
Micro-benchmarks
Code refactoring
title_short Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
title_full Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
title_fullStr Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
title_full_unstemmed Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
title_sort Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings
dc.creator.none.fl_str_mv Longo, Mathias
Rodriguez, Ana Virginia
Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
author Longo, Mathias
author_facet Longo, Mathias
Rodriguez, Ana Virginia
Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
author_role author
author2 Rodriguez, Ana Virginia
Mateos Diaz, Cristian Maximiliano
Zunino Suarez, Alejandro Octavio
author2_role author
author
author
dc.subject.none.fl_str_mv Energy
Scientific applications
Java
Micro-benchmarks
Code refactoring
topic Energy
Scientific applications
Java
Micro-benchmarks
Code refactoring
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv In-silico research has grown considerably. Today's scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.
Fil: Longo, Mathias. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina. University of Southern California; Estados Unidos
Fil: Rodriguez, Ana Virginia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Mateos Diaz, Cristian Maximiliano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
Fil: Zunino Suarez, Alejandro Octavio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina
description In-silico research has grown considerably. Today's scientific code involves long-running computer simulations and hence powerful computing infrastructures are needed. Traditionally, research in high-performance computing has focused on executing code as fast as possible, while energy has been recently recognized as another goal to consider. Yet, energy-driven research has mostly focused on the hardware and middleware layers, but few efforts target the application level, where many energy-aware optimizations are possible. We revisit a catalog of Java primitives commonly used in OO scientific programming, or micro-benchmarks, to identify energy-friendly versions of the same primitive. We then apply the micro-benchmarks to classical scientific application kernels and machine learning algorithms for both single-thread and multi-thread implementations on a server. Energy usage reductions at the micro-benchmark level are substantial, while for applications obtained reductions range from 3.90% to 99.18%.
publishDate 2019
dc.date.none.fl_str_mv 2019-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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://hdl.handle.net/11336/121006
Longo, Mathias; Rodriguez, Ana Virginia; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings; Comsis Consortium; Computer Science And Information Systems; 16; 2; 6-2019; 541-564
1820-0214
CONICET Digital
CONICET
url http://hdl.handle.net/11336/121006
identifier_str_mv Longo, Mathias; Rodriguez, Ana Virginia; Mateos Diaz, Cristian Maximiliano; Zunino Suarez, Alejandro Octavio; Reducing energy usage in resource-intensive Java-based scientific applications via micro-benchmark based code refactorings; Comsis Consortium; Computer Science And Information Systems; 16; 2; 6-2019; 541-564
1820-0214
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.comsis.org/archive.php?show=ppr675-1806
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Comsis Consortium
publisher.none.fl_str_mv Comsis Consortium
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846082656298598400
score 13.22299

Publicaciones similares