Performance Evaluation of Network based Distributed Supercomputing Environment

Detalhes bibliográficos
Autor(a) principal: Gupta, OP
Data de Publicação: 2007
Outros Autores: Kahlon, Karanjeet Singh
Tipo de documento: Artigo
Idioma: eng
Título da fonte: INFOCOMP: Jornal de Ciência da Computação
Texto Completo: https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/181
Resumo: In the past decade, supercomputing has witnessed a paradigm shift from massively parallel supercomputers to network computers. Though dedicated high end supercomputers still have their place in the market yet combined unused CPU cycles of desktop PCs available in the campus network can form comparable virtual supercomputers. Consequently, Parallel Processing in a network of PCs are attracted a boost of attention and becoming one of the most promising areas of large scale scientific computing. In this paper, we are presenting Grid-enabled PC Cluster (GPCC), exhibiting low latency and bandwidth scalable sub-communication system. The design of the GPCC is such that it keeps in view the socket buffer size of local and non-local nodes in the network environment. The design is relatively easy to use, inexpensive to apply and extremely accurate. The highly accurate results provided by TCP/IP ping-pong were coupled with parallel matrix multiplication benchmark. ParallelMatrix Multiplication (PMM) performance benchmark is used to test the GPCC for node-to-node network performance and parallel floating point performance of all involved processor in a local and non-local cluster environment. PMM benchmark is developed on the basis of master-slave model using dynamic distribution scheme.
id UFLA-5_08b04d1cee54a6bd226e26e0189ead1f
oai_identifier_str oai:infocomp.dcc.ufla.br:article/181
network_acronym_str UFLA-5
network_name_str INFOCOMP: Jornal de Ciência da Computação
repository_id_str
spelling Performance Evaluation of Network based Distributed Supercomputing EnvironmentDistributed ComputingParallel ComputingGrid ComputingLocal Area NetworkIn the past decade, supercomputing has witnessed a paradigm shift from massively parallel supercomputers to network computers. Though dedicated high end supercomputers still have their place in the market yet combined unused CPU cycles of desktop PCs available in the campus network can form comparable virtual supercomputers. Consequently, Parallel Processing in a network of PCs are attracted a boost of attention and becoming one of the most promising areas of large scale scientific computing. In this paper, we are presenting Grid-enabled PC Cluster (GPCC), exhibiting low latency and bandwidth scalable sub-communication system. The design of the GPCC is such that it keeps in view the socket buffer size of local and non-local nodes in the network environment. The design is relatively easy to use, inexpensive to apply and extremely accurate. The highly accurate results provided by TCP/IP ping-pong were coupled with parallel matrix multiplication benchmark. ParallelMatrix Multiplication (PMM) performance benchmark is used to test the GPCC for node-to-node network performance and parallel floating point performance of all involved processor in a local and non-local cluster environment. PMM benchmark is developed on the basis of master-slave model using dynamic distribution scheme.Editora da UFLA2007-09-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/181INFOCOMP Journal of Computer Science; Vol. 6 No. 3 (2007): September, 2007; 15-181982-33631807-4545reponame:INFOCOMP: Jornal de Ciência da Computaçãoinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://infocomp.dcc.ufla.br/index.php/infocomp/article/view/181/166Copyright (c) 2016 INFOCOMP Journal of Computer Scienceinfo:eu-repo/semantics/openAccessGupta, OPKahlon, Karanjeet Singh2015-06-27T23:27:21Zoai:infocomp.dcc.ufla.br:article/181Revistahttps://infocomp.dcc.ufla.br/index.php/infocompPUBhttps://infocomp.dcc.ufla.br/index.php/infocomp/oaiinfocomp@dcc.ufla.br||apfreire@dcc.ufla.br1982-33631807-4545opendoar:2024-05-21T19:54:22.617861INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv Performance Evaluation of Network based Distributed Supercomputing Environment
title Performance Evaluation of Network based Distributed Supercomputing Environment
spellingShingle Performance Evaluation of Network based Distributed Supercomputing Environment
Gupta, OP
Distributed Computing
Parallel Computing
Grid Computing
Local Area Network
title_short Performance Evaluation of Network based Distributed Supercomputing Environment
title_full Performance Evaluation of Network based Distributed Supercomputing Environment
title_fullStr Performance Evaluation of Network based Distributed Supercomputing Environment
title_full_unstemmed Performance Evaluation of Network based Distributed Supercomputing Environment
title_sort Performance Evaluation of Network based Distributed Supercomputing Environment
author Gupta, OP
author_facet Gupta, OP
Kahlon, Karanjeet Singh
author_role author
author2 Kahlon, Karanjeet Singh
author2_role author
dc.contributor.author.fl_str_mv Gupta, OP
Kahlon, Karanjeet Singh
dc.subject.por.fl_str_mv Distributed Computing
Parallel Computing
Grid Computing
Local Area Network
topic Distributed Computing
Parallel Computing
Grid Computing
Local Area Network
description In the past decade, supercomputing has witnessed a paradigm shift from massively parallel supercomputers to network computers. Though dedicated high end supercomputers still have their place in the market yet combined unused CPU cycles of desktop PCs available in the campus network can form comparable virtual supercomputers. Consequently, Parallel Processing in a network of PCs are attracted a boost of attention and becoming one of the most promising areas of large scale scientific computing. In this paper, we are presenting Grid-enabled PC Cluster (GPCC), exhibiting low latency and bandwidth scalable sub-communication system. The design of the GPCC is such that it keeps in view the socket buffer size of local and non-local nodes in the network environment. The design is relatively easy to use, inexpensive to apply and extremely accurate. The highly accurate results provided by TCP/IP ping-pong were coupled with parallel matrix multiplication benchmark. ParallelMatrix Multiplication (PMM) performance benchmark is used to test the GPCC for node-to-node network performance and parallel floating point performance of all involved processor in a local and non-local cluster environment. PMM benchmark is developed on the basis of master-slave model using dynamic distribution scheme.
publishDate 2007
dc.date.none.fl_str_mv 2007-09-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/181
url https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/181
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/181/166
dc.rights.driver.fl_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2016 INFOCOMP Journal of Computer Science
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Editora da UFLA
publisher.none.fl_str_mv Editora da UFLA
dc.source.none.fl_str_mv INFOCOMP Journal of Computer Science; Vol. 6 No. 3 (2007): September, 2007; 15-18
1982-3363
1807-4545
reponame:INFOCOMP: Jornal de Ciência da Computação
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str INFOCOMP: Jornal de Ciência da Computação
collection INFOCOMP: Jornal de Ciência da Computação
repository.name.fl_str_mv INFOCOMP: Jornal de Ciência da Computação - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv infocomp@dcc.ufla.br||apfreire@dcc.ufla.br
_version_ 1799874740443152384