Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications

Autores
Caymes Scutari, Paola Guadalupe; Morajko, Anna; Margalef, Tomàs; Luque, Emilio
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Parallel/distributed systems are continuously growing. This allows and enables the scalability of the applications, either by considering bigger problems in the same period of time or by solving the problem in a shorter time. In consequence, the methodologies, approaches and tools related to parallel paradigm should be brought up to date to support the increasing requirements of the applications and the users. MATE (Monitoring, Analysis and Tuning Environment) provides automatic and dynamic tuning for parallel/distributed applications. The tuning decisions are made according to performance models, which provide a fast means to decide what to improve in the execution. However, MATE presents some bottlenecks as the application grows, due to the fact that the analysis process is made in a full centralized manner. In this work, we propose a new approach to make MATE scalable. In addition, we present the experimental results and the analysis to validate the proposed approach against the original one.
Fil: Caymes Scutari, Paola Guadalupe. Universidad Tecnologica Nacional. Facultad Reg.mendoza. Departamento de Ingeniería Química.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Morajko, Anna. Universitat Autònoma de Barcelona; España
Fil: Margalef, Tomàs. Universitat Autònoma de Barcelona; España
Fil: Luque, Emilio. Universitat Autònoma de Barcelona; España
Materia
DYNAMIC TUNING
PERFORMANCE EVALUATION
SCALABILITY
PARALLEL APPLICATIONS
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:11336/242483
Acceder
id CONICETDig_200330395d50754559a58afe53588ca1
oai_identifier_str oai:ri.conicet.gov.ar:11336/242483
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applicationsCaymes Scutari, Paola GuadalupeMorajko, AnnaMargalef, TomàsLuque, EmilioDYNAMIC TUNINGPERFORMANCE EVALUATIONSCALABILITYPARALLEL APPLICATIONShttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Parallel/distributed systems are continuously growing. This allows and enables the scalability of the applications, either by considering bigger problems in the same period of time or by solving the problem in a shorter time. In consequence, the methodologies, approaches and tools related to parallel paradigm should be brought up to date to support the increasing requirements of the applications and the users. MATE (Monitoring, Analysis and Tuning Environment) provides automatic and dynamic tuning for parallel/distributed applications. The tuning decisions are made according to performance models, which provide a fast means to decide what to improve in the execution. However, MATE presents some bottlenecks as the application grows, due to the fact that the analysis process is made in a full centralized manner. In this work, we propose a new approach to make MATE scalable. In addition, we present the experimental results and the analysis to validate the proposed approach against the original one.Fil: Caymes Scutari, Paola Guadalupe. Universidad Tecnologica Nacional. Facultad Reg.mendoza. Departamento de Ingeniería Química.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Morajko, Anna. Universitat Autònoma de Barcelona; EspañaFil: Margalef, Tomàs. Universitat Autònoma de Barcelona; EspañaFil: Luque, Emilio. Universitat Autònoma de Barcelona; EspañaAcademic Press Inc Elsevier Science2010-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/242483Caymes Scutari, Paola Guadalupe; Morajko, Anna; Margalef, Tomàs; Luque, Emilio; Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications; Academic Press Inc Elsevier Science; Journal Of Parallel And Distributed Computing; 70; 4; 4-2010; 330-3370743-7315CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0743731509001518info:eu-repo/semantics/altIdentifier/doi//10.1016/j.jpdc.2009.08.008info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:21:37Zoai:ri.conicet.gov.ar:11336/242483instacron: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:34982025-09-29 10:21:37.34CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
title Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
spellingShingle Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
Caymes Scutari, Paola Guadalupe
DYNAMIC TUNING
PERFORMANCE EVALUATION
SCALABILITY
PARALLEL APPLICATIONS
title_short Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
title_full Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
title_fullStr Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
title_full_unstemmed Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
title_sort Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications
dc.creator.none.fl_str_mv Caymes Scutari, Paola Guadalupe
Morajko, Anna
Margalef, Tomàs
Luque, Emilio
author Caymes Scutari, Paola Guadalupe
author_facet Caymes Scutari, Paola Guadalupe
Morajko, Anna
Margalef, Tomàs
Luque, Emilio
author_role author
author2 Morajko, Anna
Margalef, Tomàs
Luque, Emilio
author2_role author
author
author
dc.subject.none.fl_str_mv DYNAMIC TUNING
PERFORMANCE EVALUATION
SCALABILITY
PARALLEL APPLICATIONS
topic DYNAMIC TUNING
PERFORMANCE EVALUATION
SCALABILITY
PARALLEL APPLICATIONS
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Parallel/distributed systems are continuously growing. This allows and enables the scalability of the applications, either by considering bigger problems in the same period of time or by solving the problem in a shorter time. In consequence, the methodologies, approaches and tools related to parallel paradigm should be brought up to date to support the increasing requirements of the applications and the users. MATE (Monitoring, Analysis and Tuning Environment) provides automatic and dynamic tuning for parallel/distributed applications. The tuning decisions are made according to performance models, which provide a fast means to decide what to improve in the execution. However, MATE presents some bottlenecks as the application grows, due to the fact that the analysis process is made in a full centralized manner. In this work, we propose a new approach to make MATE scalable. In addition, we present the experimental results and the analysis to validate the proposed approach against the original one.
Fil: Caymes Scutari, Paola Guadalupe. Universidad Tecnologica Nacional. Facultad Reg.mendoza. Departamento de Ingeniería Química.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Morajko, Anna. Universitat Autònoma de Barcelona; España
Fil: Margalef, Tomàs. Universitat Autònoma de Barcelona; España
Fil: Luque, Emilio. Universitat Autònoma de Barcelona; España
description Parallel/distributed systems are continuously growing. This allows and enables the scalability of the applications, either by considering bigger problems in the same period of time or by solving the problem in a shorter time. In consequence, the methodologies, approaches and tools related to parallel paradigm should be brought up to date to support the increasing requirements of the applications and the users. MATE (Monitoring, Analysis and Tuning Environment) provides automatic and dynamic tuning for parallel/distributed applications. The tuning decisions are made according to performance models, which provide a fast means to decide what to improve in the execution. However, MATE presents some bottlenecks as the application grows, due to the fact that the analysis process is made in a full centralized manner. In this work, we propose a new approach to make MATE scalable. In addition, we present the experimental results and the analysis to validate the proposed approach against the original one.
publishDate 2010
dc.date.none.fl_str_mv 2010-04
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/11336/242483
Caymes Scutari, Paola Guadalupe; Morajko, Anna; Margalef, Tomàs; Luque, Emilio; Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications; Academic Press Inc Elsevier Science; Journal Of Parallel And Distributed Computing; 70; 4; 4-2010; 330-337
0743-7315
CONICET Digital
CONICET
url http://hdl.handle.net/11336/242483
identifier_str_mv Caymes Scutari, Paola Guadalupe; Morajko, Anna; Margalef, Tomàs; Luque, Emilio; Scalable dynamic Monitoring, Analysis and Tuning Environment for parallel applications; Academic Press Inc Elsevier Science; Journal Of Parallel And Distributed Computing; 70; 4; 4-2010; 330-337
0743-7315
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/abs/pii/S0743731509001518
info:eu-repo/semantics/altIdentifier/doi//10.1016/j.jpdc.2009.08.008
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
application/pdf
dc.publisher.none.fl_str_mv Academic Press Inc Elsevier Science
publisher.none.fl_str_mv Academic Press Inc Elsevier Science
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_ 1844614205092659200
score 13.069144

Publicaciones similares