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Article: Node placement optimization in ShuffleNets

TitleNode placement optimization in ShuffleNets
Authors
KeywordsGradient Algorithm
Node Placement Problem
Shufflenet
Topological Design
Issue Date1998
PublisherI E E E. The Journal's web site is located at http://www.comsoc.org/livepubs/net
Citation
Ieee/Acm Transactions On Networking, 1998, v. 6 n. 3, p. 319-324 How to Cite?
AbstractNode placement problem in ShuffleNets is a combinatorial optimization problem. In this paper an efficient node placement algorithm, called the gradient algorithm, is proposed. A communication cost function between a node pair is defined and the gradient algorithm places the node pairs one by one, based on the gradient of the cost function. Then two lower bounds on the traffic weighted mean internodal distance h are proposed. The performance of the gradient algorithm is compared to the lower bounds as well as to some algorithms in the literature. Significant reduction of h̄ is obtained with the use of the gradient algorithm, especially for highly skewed traffic distributions. For a ShuffleNet with N = 64 nodes, the h̄ found is only 22% above the lower bound for the uniform random traffic distribution, and 14.7% for a highly skewed traffic distribution with skew factor γ = 100. © 1998 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/155072
ISSN
2015 Impact Factor: 2.186
2015 SCImago Journal Rankings: 1.795
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYeung, KLen_US
dc.contributor.authorYum, TSPen_US
dc.date.accessioned2012-08-08T08:31:45Z-
dc.date.available2012-08-08T08:31:45Z-
dc.date.issued1998en_US
dc.identifier.citationIeee/Acm Transactions On Networking, 1998, v. 6 n. 3, p. 319-324en_US
dc.identifier.issn1063-6692en_US
dc.identifier.urihttp://hdl.handle.net/10722/155072-
dc.description.abstractNode placement problem in ShuffleNets is a combinatorial optimization problem. In this paper an efficient node placement algorithm, called the gradient algorithm, is proposed. A communication cost function between a node pair is defined and the gradient algorithm places the node pairs one by one, based on the gradient of the cost function. Then two lower bounds on the traffic weighted mean internodal distance h are proposed. The performance of the gradient algorithm is compared to the lower bounds as well as to some algorithms in the literature. Significant reduction of h̄ is obtained with the use of the gradient algorithm, especially for highly skewed traffic distributions. For a ShuffleNet with N = 64 nodes, the h̄ found is only 22% above the lower bound for the uniform random traffic distribution, and 14.7% for a highly skewed traffic distribution with skew factor γ = 100. © 1998 IEEE.en_US
dc.languageengen_US
dc.publisherI E E E. The Journal's web site is located at http://www.comsoc.org/livepubs/neten_US
dc.relation.ispartofIEEE/ACM Transactions on Networkingen_US
dc.subjectGradient Algorithmen_US
dc.subjectNode Placement Problemen_US
dc.subjectShuffleneten_US
dc.subjectTopological Designen_US
dc.titleNode placement optimization in ShuffleNetsen_US
dc.typeArticleen_US
dc.identifier.emailYeung, KL:kyeung@eee.hku.hken_US
dc.identifier.authorityYeung, KL=rp00204en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/90.700895en_US
dc.identifier.scopuseid_2-s2.0-0032097104en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0032097104&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume6en_US
dc.identifier.issue3en_US
dc.identifier.spage319en_US
dc.identifier.epage324en_US
dc.identifier.isiWOS:000074218500008-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridYeung, KL=7202424908en_US
dc.identifier.scopusauthoridYum, TSP=36949354100en_US

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