Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster

Autores
Tinetti, Fernando Gustavo; Rios, Leopoldo Jose
Año de publicación
2016
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
We introduce a tool for automating (or aiding) performance evaluation of HPC (High Performance Computing) applications by combining both, Round Robin Databases (also referred to as RRD) and performance data collected at runtime. RRD monitoring is at the base of several well-known and popoular tools for cluster monitoring. We use take advantage of already existing RRD tools for collecting, processing, and presenting runtime data for scientific processing users. Scientific application (and even the hardware used by those scientific applications) are assumed to be performance optimized, but it is not always the case. Thus, collecting and analyzing runtime information will help scientific users to decide new optimizations and/or runtime strategies. The primary focus will be on parallel applications running in clusters, i.e. distributed hardware, since they are the most complex to optimize given their different and varying computing and communications patterns.
Fil: Tinetti, Fernando Gustavo. Universidad Nacional de La Plata. Facultad de Informática; Argentina
Fil: Rios, Leopoldo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Modelado e Innovación Tecnológica. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Modelado e Innovación Tecnológica; Argentina
2016 International Conference on Grid, Cloud, and Cluster Computing
Las Vegas
Estados Unidos
University of Georgia
Materia
HPC
RRD TOOLS
PERFORMANCE EVALUATION
OPEN SOFTWARE TOOLS
ROUND ROBIN DATABASES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/199995
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Round Robin Data Bases for Performance Evaluation of High Performance Applications and ClusterTinetti, Fernando GustavoRios, Leopoldo JoseHPCRRD TOOLSPERFORMANCE EVALUATIONOPEN SOFTWARE TOOLSROUND ROBIN DATABASEShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1We introduce a tool for automating (or aiding) performance evaluation of HPC (High Performance Computing) applications by combining both, Round Robin Databases (also referred to as RRD) and performance data collected at runtime. RRD monitoring is at the base of several well-known and popoular tools for cluster monitoring. We use take advantage of already existing RRD tools for collecting, processing, and presenting runtime data for scientific processing users. Scientific application (and even the hardware used by those scientific applications) are assumed to be performance optimized, but it is not always the case. Thus, collecting and analyzing runtime information will help scientific users to decide new optimizations and/or runtime strategies. The primary focus will be on parallel applications running in clusters, i.e. distributed hardware, since they are the most complex to optimize given their different and varying computing and communications patterns.Fil: Tinetti, Fernando Gustavo. Universidad Nacional de La Plata. Facultad de Informática; ArgentinaFil: Rios, Leopoldo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Modelado e Innovación Tecnológica. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Modelado e Innovación Tecnológica; Argentina2016 International Conference on Grid, Cloud, and Cluster ComputingLas VegasEstados UnidosUniversity of GeorgiaComputer Science Research, Education, and Applications Press2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectConferenciaBookhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/199995Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster; 2016 International Conference on Grid, Cloud, and Cluster Computing; Las Vegas; Estados Unidos; 20161-60132-436-7CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://worldcomp-proceedings.com/proc/p2016/GCC16_Contents.htmlInternacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-11-05T10:13:51Zoai:ri.conicet.gov.ar:11336/199995instacron: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:34982025-11-05 10:13:51.633CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
title Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
spellingShingle Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
Tinetti, Fernando Gustavo
HPC
RRD TOOLS
PERFORMANCE EVALUATION
OPEN SOFTWARE TOOLS
ROUND ROBIN DATABASES
title_short Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
title_full Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
title_fullStr Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
title_full_unstemmed Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
title_sort Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster
dc.creator.none.fl_str_mv Tinetti, Fernando Gustavo
Rios, Leopoldo Jose
author Tinetti, Fernando Gustavo
author_facet Tinetti, Fernando Gustavo
Rios, Leopoldo Jose
author_role author
author2 Rios, Leopoldo Jose
author2_role author
dc.subject.none.fl_str_mv HPC
RRD TOOLS
PERFORMANCE EVALUATION
OPEN SOFTWARE TOOLS
ROUND ROBIN DATABASES
topic HPC
RRD TOOLS
PERFORMANCE EVALUATION
OPEN SOFTWARE TOOLS
ROUND ROBIN DATABASES
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv We introduce a tool for automating (or aiding) performance evaluation of HPC (High Performance Computing) applications by combining both, Round Robin Databases (also referred to as RRD) and performance data collected at runtime. RRD monitoring is at the base of several well-known and popoular tools for cluster monitoring. We use take advantage of already existing RRD tools for collecting, processing, and presenting runtime data for scientific processing users. Scientific application (and even the hardware used by those scientific applications) are assumed to be performance optimized, but it is not always the case. Thus, collecting and analyzing runtime information will help scientific users to decide new optimizations and/or runtime strategies. The primary focus will be on parallel applications running in clusters, i.e. distributed hardware, since they are the most complex to optimize given their different and varying computing and communications patterns.
Fil: Tinetti, Fernando Gustavo. Universidad Nacional de La Plata. Facultad de Informática; Argentina
Fil: Rios, Leopoldo Jose. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Modelado e Innovación Tecnológica. Universidad Nacional del Nordeste. Facultad de Ciencias Exactas Naturales y Agrimensura. Instituto de Modelado e Innovación Tecnológica; Argentina
2016 International Conference on Grid, Cloud, and Cluster Computing
Las Vegas
Estados Unidos
University of Georgia
description We introduce a tool for automating (or aiding) performance evaluation of HPC (High Performance Computing) applications by combining both, Round Robin Databases (also referred to as RRD) and performance data collected at runtime. RRD monitoring is at the base of several well-known and popoular tools for cluster monitoring. We use take advantage of already existing RRD tools for collecting, processing, and presenting runtime data for scientific processing users. Scientific application (and even the hardware used by those scientific applications) are assumed to be performance optimized, but it is not always the case. Thus, collecting and analyzing runtime information will help scientific users to decide new optimizations and/or runtime strategies. The primary focus will be on parallel applications running in clusters, i.e. distributed hardware, since they are the most complex to optimize given their different and varying computing and communications patterns.
publishDate 2016
dc.date.none.fl_str_mv 2016
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Conferencia
Book
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/199995
Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster; 2016 International Conference on Grid, Cloud, and Cluster Computing; Las Vegas; Estados Unidos; 2016
1-60132-436-7
CONICET Digital
CONICET
url http://hdl.handle.net/11336/199995
identifier_str_mv Round Robin Data Bases for Performance Evaluation of High Performance Applications and Cluster; 2016 International Conference on Grid, Cloud, and Cluster Computing; Las Vegas; Estados Unidos; 2016
1-60132-436-7
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://worldcomp-proceedings.com/proc/p2016/GCC16_Contents.html
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.coverage.none.fl_str_mv Internacional
dc.publisher.none.fl_str_mv Computer Science Research, Education, and Applications Press
publisher.none.fl_str_mv Computer Science Research, Education, and Applications Press
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
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score 13.087074

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