Sparse Equation Systems in Heterogeneous Clusters of Computers
- Autores
- Tinetti, Fernando Gustavo; Aróztegui, Walter; Quijano, Antonio A.
- Año de publicación
- 2005
- Idioma
- inglés
- Tipo de recurso
- informe técnico
- Estado
- versión enviada
- Descripción
- This paper presents a parallelization strategy in heterogeneous clusters of the Gauss-Seidel’s method applied for the solution of sparse equation systems. From the point of view of the numerical solution for matrices of coefficients with low density of non null-elements, the standard lines of thought are followed, that is, only non-null elements are stored and iterative solution-search methods are used. Two basic guidelines are defined for the parallel algorithm: one-dimensional data distribution and broadcast messages for all data communications. One-dimensional data distribution eases the processing workload balance on heterogeneous clusters. The use of broadcast messages for every data communication is directly oriented to optimize performance on the the most common cluster interconnection: Ethernet. Experimental results obtained in a local network of heterogeneous computers are presented.
- Materia
-
Ingeniería Eléctrica y Electrónica
heterogeneous clusters
Gauss-Seidel’s method
sparse equation systems - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/6514
Ver los metadatos del registro completo
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spelling |
Sparse Equation Systems in Heterogeneous Clusters of ComputersTinetti, Fernando GustavoAróztegui, WalterQuijano, Antonio A.Ingeniería Eléctrica y Electrónicaheterogeneous clustersGauss-Seidel’s methodsparse equation systemsThis paper presents a parallelization strategy in heterogeneous clusters of the Gauss-Seidel’s method applied for the solution of sparse equation systems. From the point of view of the numerical solution for matrices of coefficients with low density of non null-elements, the standard lines of thought are followed, that is, only non-null elements are stored and iterative solution-search methods are used. Two basic guidelines are defined for the parallel algorithm: one-dimensional data distribution and broadcast messages for all data communications. One-dimensional data distribution eases the processing workload balance on heterogeneous clusters. The use of broadcast messages for every data communication is directly oriented to optimize performance on the the most common cluster interconnection: Ethernet. Experimental results obtained in a local network of heterogeneous computers are presented.2005info:eu-repo/semantics/reportinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/resource_type/c_18ghinfo:ar-repo/semantics/informeTecnicoapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/6514enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:40:22Zoai:digital.cic.gba.gob.ar:11746/6514Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:40:22.328CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
Sparse Equation Systems in Heterogeneous Clusters of Computers |
title |
Sparse Equation Systems in Heterogeneous Clusters of Computers |
spellingShingle |
Sparse Equation Systems in Heterogeneous Clusters of Computers Tinetti, Fernando Gustavo Ingeniería Eléctrica y Electrónica heterogeneous clusters Gauss-Seidel’s method sparse equation systems |
title_short |
Sparse Equation Systems in Heterogeneous Clusters of Computers |
title_full |
Sparse Equation Systems in Heterogeneous Clusters of Computers |
title_fullStr |
Sparse Equation Systems in Heterogeneous Clusters of Computers |
title_full_unstemmed |
Sparse Equation Systems in Heterogeneous Clusters of Computers |
title_sort |
Sparse Equation Systems in Heterogeneous Clusters of Computers |
dc.creator.none.fl_str_mv |
Tinetti, Fernando Gustavo Aróztegui, Walter Quijano, Antonio A. |
author |
Tinetti, Fernando Gustavo |
author_facet |
Tinetti, Fernando Gustavo Aróztegui, Walter Quijano, Antonio A. |
author_role |
author |
author2 |
Aróztegui, Walter Quijano, Antonio A. |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ingeniería Eléctrica y Electrónica heterogeneous clusters Gauss-Seidel’s method sparse equation systems |
topic |
Ingeniería Eléctrica y Electrónica heterogeneous clusters Gauss-Seidel’s method sparse equation systems |
dc.description.none.fl_txt_mv |
This paper presents a parallelization strategy in heterogeneous clusters of the Gauss-Seidel’s method applied for the solution of sparse equation systems. From the point of view of the numerical solution for matrices of coefficients with low density of non null-elements, the standard lines of thought are followed, that is, only non-null elements are stored and iterative solution-search methods are used. Two basic guidelines are defined for the parallel algorithm: one-dimensional data distribution and broadcast messages for all data communications. One-dimensional data distribution eases the processing workload balance on heterogeneous clusters. The use of broadcast messages for every data communication is directly oriented to optimize performance on the the most common cluster interconnection: Ethernet. Experimental results obtained in a local network of heterogeneous computers are presented. |
description |
This paper presents a parallelization strategy in heterogeneous clusters of the Gauss-Seidel’s method applied for the solution of sparse equation systems. From the point of view of the numerical solution for matrices of coefficients with low density of non null-elements, the standard lines of thought are followed, that is, only non-null elements are stored and iterative solution-search methods are used. Two basic guidelines are defined for the parallel algorithm: one-dimensional data distribution and broadcast messages for all data communications. One-dimensional data distribution eases the processing workload balance on heterogeneous clusters. The use of broadcast messages for every data communication is directly oriented to optimize performance on the the most common cluster interconnection: Ethernet. Experimental results obtained in a local network of heterogeneous computers are presented. |
publishDate |
2005 |
dc.date.none.fl_str_mv |
2005 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/report info:eu-repo/semantics/submittedVersion http://purl.org/coar/resource_type/c_18gh info:ar-repo/semantics/informeTecnico |
format |
report |
status_str |
submittedVersion |
dc.identifier.none.fl_str_mv |
https://digital.cic.gba.gob.ar/handle/11746/6514 |
url |
https://digital.cic.gba.gob.ar/handle/11746/6514 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:CIC Digital (CICBA) instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
reponame_str |
CIC Digital (CICBA) |
collection |
CIC Digital (CICBA) |
instname_str |
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
instacron_str |
CICBA |
institution |
CICBA |
repository.name.fl_str_mv |
CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
repository.mail.fl_str_mv |
marisa.degiusti@sedici.unlp.edu.ar |
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1844618619630125056 |
score |
12.891075 |