Performance of scientific processing in networks of workstations
- Autores
- Tinetti, Fernando Gustavo
- Año de publicación
- 2000
- Idioma
- español castellano
- Tipo de recurso
- documento de conferencia
- Estado
- versión enviada
- Descripción
- The growing processing power of standard workstations, along with the relatively easy way in which they can be available for parallel processing, have both contributed to their increasing use in computation intensive application areas. Usually, computation intensive areas have been referred to as scientific processing; one of them being linear algebra, where a great effort has been made to optimize solution methods for serial as well as for parallel computing.\nSince the appearance of software libraries for parallel environments such as PVM (Parallel Virtual Machine) [4] and implementations of MPI (Message Passing Interface) [5], the distributed processing power of networks of workstations has been available for parallel processing as well.\nAlso, a strong emphasis has been made on the heterogeneous computing facility provided by these libraries over networks of workstations. However, there is a lack of published results on the performance obtained on this kind of parallel (more specifically distributed) processing architectures.\nFrom the whole area of linear algebra applications, the most challenging (in terms of performance) operations to be solved are the so called Level 3 BLAS (Basic Linear Algebra Subprograms). In Level 3 BLAS, all of the processing can be expressed (and solved) in terms of matrix-matrix operations. Even more specifically, the most studied operation has been matrix multiplication, which is in fact a benchmark in this application area.
Eje: Procesamiento Concurrente, paralelo y distribuido. Redes - Materia
-
Ciencias Informáticas
Parallel processing
Distributed
Performance of Scientific Processing
Networks of Workstations - 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:11746/3635
Ver los metadatos del registro completo
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Performance of scientific processing in networks of workstationsTinetti, Fernando GustavoCiencias InformáticasParallel processingDistributedPerformance of Scientific ProcessingNetworks of WorkstationsThe growing processing power of standard workstations, along with the relatively easy way in which they can be available for parallel processing, have both contributed to their increasing use in computation intensive application areas. Usually, computation intensive areas have been referred to as scientific processing; one of them being linear algebra, where a great effort has been made to optimize solution methods for serial as well as for parallel computing.\nSince the appearance of software libraries for parallel environments such as PVM (Parallel Virtual Machine) [4] and implementations of MPI (Message Passing Interface) [5], the distributed processing power of networks of workstations has been available for parallel processing as well.\nAlso, a strong emphasis has been made on the heterogeneous computing facility provided by these libraries over networks of workstations. However, there is a lack of published results on the performance obtained on this kind of parallel (more specifically distributed) processing architectures.\nFrom the whole area of linear algebra applications, the most challenging (in terms of performance) operations to be solved are the so called Level 3 BLAS (Basic Linear Algebra Subprograms). In Level 3 BLAS, all of the processing can be expressed (and solved) in terms of matrix-matrix operations. Even more specifically, the most studied operation has been matrix multiplication, which is in fact a benchmark in this application area.Eje: Procesamiento Concurrente, paralelo y distribuido. Redes2000-05info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/3635spainfo: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:CICBA2025-09-29T13:40:16Zoai:digital.cic.gba.gob.ar:11746/3635Institucionalhttp://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 13:40:16.313CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
Performance of scientific processing in networks of workstations |
title |
Performance of scientific processing in networks of workstations |
spellingShingle |
Performance of scientific processing in networks of workstations Tinetti, Fernando Gustavo Ciencias Informáticas Parallel processing Distributed Performance of Scientific Processing Networks of Workstations |
title_short |
Performance of scientific processing in networks of workstations |
title_full |
Performance of scientific processing in networks of workstations |
title_fullStr |
Performance of scientific processing in networks of workstations |
title_full_unstemmed |
Performance of scientific processing in networks of workstations |
title_sort |
Performance of scientific processing in networks of workstations |
dc.creator.none.fl_str_mv |
Tinetti, Fernando Gustavo |
author |
Tinetti, Fernando Gustavo |
author_facet |
Tinetti, Fernando Gustavo |
author_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Parallel processing Distributed Performance of Scientific Processing Networks of Workstations |
topic |
Ciencias Informáticas Parallel processing Distributed Performance of Scientific Processing Networks of Workstations |
dc.description.none.fl_txt_mv |
The growing processing power of standard workstations, along with the relatively easy way in which they can be available for parallel processing, have both contributed to their increasing use in computation intensive application areas. Usually, computation intensive areas have been referred to as scientific processing; one of them being linear algebra, where a great effort has been made to optimize solution methods for serial as well as for parallel computing.\nSince the appearance of software libraries for parallel environments such as PVM (Parallel Virtual Machine) [4] and implementations of MPI (Message Passing Interface) [5], the distributed processing power of networks of workstations has been available for parallel processing as well.\nAlso, a strong emphasis has been made on the heterogeneous computing facility provided by these libraries over networks of workstations. However, there is a lack of published results on the performance obtained on this kind of parallel (more specifically distributed) processing architectures.\nFrom the whole area of linear algebra applications, the most challenging (in terms of performance) operations to be solved are the so called Level 3 BLAS (Basic Linear Algebra Subprograms). In Level 3 BLAS, all of the processing can be expressed (and solved) in terms of matrix-matrix operations. Even more specifically, the most studied operation has been matrix multiplication, which is in fact a benchmark in this application area. Eje: Procesamiento Concurrente, paralelo y distribuido. Redes |
description |
The growing processing power of standard workstations, along with the relatively easy way in which they can be available for parallel processing, have both contributed to their increasing use in computation intensive application areas. Usually, computation intensive areas have been referred to as scientific processing; one of them being linear algebra, where a great effort has been made to optimize solution methods for serial as well as for parallel computing.\nSince the appearance of software libraries for parallel environments such as PVM (Parallel Virtual Machine) [4] and implementations of MPI (Message Passing Interface) [5], the distributed processing power of networks of workstations has been available for parallel processing as well.\nAlso, a strong emphasis has been made on the heterogeneous computing facility provided by these libraries over networks of workstations. However, there is a lack of published results on the performance obtained on this kind of parallel (more specifically distributed) processing architectures.\nFrom the whole area of linear algebra applications, the most challenging (in terms of performance) operations to be solved are the so called Level 3 BLAS (Basic Linear Algebra Subprograms). In Level 3 BLAS, all of the processing can be expressed (and solved) in terms of matrix-matrix operations. Even more specifically, the most studied operation has been matrix multiplication, which is in fact a benchmark in this application area. |
publishDate |
2000 |
dc.date.none.fl_str_mv |
2000-05 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/submittedVersion http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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submittedVersion |
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https://digital.cic.gba.gob.ar/handle/11746/3635 |
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https://digital.cic.gba.gob.ar/handle/11746/3635 |
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spa |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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http://creativecommons.org/licenses/by/4.0/ |
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application/pdf |
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CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
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