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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/22090
Ver los metadatos del registro completo
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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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info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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http://sedici.unlp.edu.ar/handle/10915/22090 |
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eng |
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eng |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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