A Performance Prediction Module for Workflow Scheduling

Through the years, scientific applications have demanded more powerful and sophisticated computing environments and management techniques. Workflows facilitated the design and management of scientific applications. The complexity of to day's workflows demand a high amount of resources and mecha...

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Detalles Bibliográficos
Autores principales: Monge, David A., Bělohradský, Jiří, García Garino, Carlos, Železný, Filip
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2011
Materias:
Ciencias Informáticas
Workflow
Scheduling
Performance Prediction
Nonparametric Regression
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/126141
https://40jaiio.sadio.org.ar/sites/default/files/T2011/HPC/1102.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-126141
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Workflow
Scheduling
Performance Prediction
Nonparametric Regression
spellingShingle Ciencias Informáticas
Workflow
Scheduling
Performance Prediction
Nonparametric Regression
Monge, David A.
Bělohradský, Jiří
García Garino, Carlos
Železný, Filip
A Performance Prediction Module for Workflow Scheduling
topic_facet Ciencias Informáticas
Workflow
Scheduling
Performance Prediction
Nonparametric Regression
description Through the years, scientific applications have demanded more powerful and sophisticated computing environments and management techniques. Workflows facilitated the design and management of scientific applications. The complexity of to day's workflows demand a high amount of resources and mechanisms for provisioning them. The execution of scientific workflow applications is a complex task and depends on how the resources are assigned. Scheduling is the name given to the process that assigns computing resources to the tasks comprised in a workflow. This work presents a scheduling algorithm (PPSA) for workflows tightly coupled to a performance prediction module (PEM). A set of experiments was developed for measuring the performance of the algorithm using the information provided by the proposed performance module. The proposed algorithm is compared with an algorithm included in the well-known workflow middlewares Condor DAGMan and ASKALON.
format Objeto de conferencia
Objeto de conferencia
author Monge, David A.
Bělohradský, Jiří
García Garino, Carlos
Železný, Filip
author_facet Monge, David A.
Bělohradský, Jiří
García Garino, Carlos
Železný, Filip
author_sort Monge, David A.
title A Performance Prediction Module for Workflow Scheduling
title_short A Performance Prediction Module for Workflow Scheduling
title_full A Performance Prediction Module for Workflow Scheduling
title_fullStr A Performance Prediction Module for Workflow Scheduling
title_full_unstemmed A Performance Prediction Module for Workflow Scheduling
title_sort performance prediction module for workflow scheduling
publishDate 2011
url http://sedici.unlp.edu.ar/handle/10915/126141
https://40jaiio.sadio.org.ar/sites/default/files/T2011/HPC/1102.pdf
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