Parallel Application Signature for Performance Prediction : Ph. D. Thesis in High Perfomance Computing

In order to measure the performance of a parallel machine, a set of application kernels as benchmarks have often been used. However, it is not always possible to characterize the performance using only benchmarks, given the fact that each one usually reflects a narrow set of kernel applications at be...

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Autor principal: Wong, Alvaro
Formato: Articulo Revision
Lenguaje:Inglés
Publicado: 2010
Materias:
Ciencias Informáticas
Parallel
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/9686
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct10-TO3.pdf
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-9686
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
Parallel
spellingShingle Ciencias Informáticas
Parallel
Wong, Alvaro
Parallel Application Signature for Performance Prediction : Ph. D. Thesis in High Perfomance Computing
topic_facet Ciencias Informáticas
Parallel
description In order to measure the performance of a parallel machine, a set of application kernels as benchmarks have often been used. However, it is not always possible to characterize the performance using only benchmarks, given the fact that each one usually reflects a narrow set of kernel applications at best. Computers show different performance indices for different applications as they run them. Accurate prediction of parallel applications’ performance is becoming increasingly complex and the time required to run it thoroughly is an onerous requirement; especially if we want to predict for different systems. In production clusters, where throughput and efficiency of use are fundamental, it is important to be able to predict which system is more appropriate for an application, or how long a scheduled application will take to run, in order to have the foresight that will allow us to make better use of the resources available.
format Articulo
Revision
author Wong, Alvaro
author_facet Wong, Alvaro
author_sort Wong, Alvaro
title Parallel Application Signature for Performance Prediction : Ph. D. Thesis in High Perfomance Computing
title_short Parallel Application Signature for Performance Prediction : Ph. D. Thesis in High Perfomance Computing
title_full Parallel Application Signature for Performance Prediction : Ph. D. Thesis in High Perfomance Computing
title_fullStr Parallel Application Signature for Performance Prediction : Ph. D. Thesis in High Perfomance Computing
title_full_unstemmed Parallel Application Signature for Performance Prediction : Ph. D. Thesis in High Perfomance Computing
title_sort parallel application signature for performance prediction : ph. d. thesis in high perfomance computing
publishDate 2010
url http://sedici.unlp.edu.ar/handle/10915/9686
http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Oct10-TO3.pdf
work_keys_str_mv AT wongalvaro parallelapplicationsignatureforperformancepredictionphdthesisinhighperfomancecomputing
bdutipo_str Repositorios
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