Performance of scientific processing in networks of workstations

Autores
Tinetti, Fernando Gustavo
Año de publicación
2000
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
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. Since 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. Also, 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. From 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
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Parallel processing
Performance of Scientific Processing
Networks of Workstations
Distributed
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/22090

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spelling Performance of scientific processing in networks of workstationsTinetti, Fernando GustavoCiencias InformáticasParallel processingPerformance of Scientific ProcessingNetworks of WorkstationsDistributedThe 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. Since 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. Also, 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. From 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. RedesRed de Universidades con Carreras en Informática (RedUNCI)2000-05info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf10-12http://sedici.unlp.edu.ar/handle/10915/22090enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:54:52Zoai:sedici.unlp.edu.ar:10915/22090Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:54:53.294SEDICI (UNLP) - Universidad Nacional de La Platafalse
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
Performance of Scientific Processing
Networks of Workstations
Distributed
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
Performance of Scientific Processing
Networks of Workstations
Distributed
topic Ciencias Informáticas
Parallel processing
Performance of Scientific Processing
Networks of Workstations
Distributed
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. Since 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. Also, 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. From 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
Red de Universidades con Carreras en Informática (RedUNCI)
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. Since 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. Also, 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. From 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
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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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