A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm
This paper presents a general model to define, measure and predict the efficiency of applications running on heterogeneous parallel computer systems. Using this framework, it is possible to understand the influence that the heterogeneity of the hardware has on the efficiency of an algorithm. This me...
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todo:paper_07437315_v65_n1_p48_Bazterra2023-10-03T15:38:29Z A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm Bazterra, V.E. Cuma, M. Ferraro, M.B. Facelli, J.C. Heterogeneous parallel environment Parallel genetic algorithms Performance analysis Heterogeneous parallel environment Parallel genetic algorithm Performance analysis Adaptive algorithms Genetic algorithms Mathematical models Parallel algorithms Probability Set theory Synchronization Theorem proving Parallel processing systems This paper presents a general model to define, measure and predict the efficiency of applications running on heterogeneous parallel computer systems. Using this framework, it is possible to understand the influence that the heterogeneity of the hardware has on the efficiency of an algorithm. This methodology is used to compare an existing parallel genetic algorithm with a new adaptive parallel model. All the performance measurements were taken in a loosely coupled cluster of processors. © 2004 Elsevier Inc. All rights reserved. Fil:Bazterra, V.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Ferraro, M.B. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Facelli, J.C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_07437315_v65_n1_p48_Bazterra |
institution |
Universidad de Buenos Aires |
institution_str |
I-28 |
repository_str |
R-134 |
collection |
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) |
topic |
Heterogeneous parallel environment Parallel genetic algorithms Performance analysis Heterogeneous parallel environment Parallel genetic algorithm Performance analysis Adaptive algorithms Genetic algorithms Mathematical models Parallel algorithms Probability Set theory Synchronization Theorem proving Parallel processing systems |
spellingShingle |
Heterogeneous parallel environment Parallel genetic algorithms Performance analysis Heterogeneous parallel environment Parallel genetic algorithm Performance analysis Adaptive algorithms Genetic algorithms Mathematical models Parallel algorithms Probability Set theory Synchronization Theorem proving Parallel processing systems Bazterra, V.E. Cuma, M. Ferraro, M.B. Facelli, J.C. A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm |
topic_facet |
Heterogeneous parallel environment Parallel genetic algorithms Performance analysis Heterogeneous parallel environment Parallel genetic algorithm Performance analysis Adaptive algorithms Genetic algorithms Mathematical models Parallel algorithms Probability Set theory Synchronization Theorem proving Parallel processing systems |
description |
This paper presents a general model to define, measure and predict the efficiency of applications running on heterogeneous parallel computer systems. Using this framework, it is possible to understand the influence that the heterogeneity of the hardware has on the efficiency of an algorithm. This methodology is used to compare an existing parallel genetic algorithm with a new adaptive parallel model. All the performance measurements were taken in a loosely coupled cluster of processors. © 2004 Elsevier Inc. All rights reserved. |
format |
JOUR |
author |
Bazterra, V.E. Cuma, M. Ferraro, M.B. Facelli, J.C. |
author_facet |
Bazterra, V.E. Cuma, M. Ferraro, M.B. Facelli, J.C. |
author_sort |
Bazterra, V.E. |
title |
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm |
title_short |
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm |
title_full |
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm |
title_fullStr |
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm |
title_full_unstemmed |
A general framework to understand parallel performance in heterogeneous clusters: Analysis of a new adaptive parallel genetic algorithm |
title_sort |
general framework to understand parallel performance in heterogeneous clusters: analysis of a new adaptive parallel genetic algorithm |
url |
http://hdl.handle.net/20.500.12110/paper_07437315_v65_n1_p48_Bazterra |
work_keys_str_mv |
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1807321990849101824 |