Partitioning of unstructured grid meshes using Boltzmann machine neural networks

Theodoridis, J; Giannakoglou, KC; Stafylopatis, A

dc.contributor.author	Theodoridis, J	en
dc.contributor.author	Giannakoglou, KC	en
dc.contributor.author	Stafylopatis, A	en
dc.date.accessioned	2014-03-01T01:15:46Z
dc.date.available	2014-03-01T01:15:46Z
dc.date.issued	2000	en
dc.identifier.issn	0965-9978	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/13731
dc.subject	neural networks	en
dc.subject	Boltzmann machine	en
dc.subject	graph partitioning	en
dc.subject.classification	Computer Science, Interdisciplinary Applications	en
dc.subject.classification	Computer Science, Software Engineering	en
dc.title	Partitioning of unstructured grid meshes using Boltzmann machine neural networks	en
heal.type	journalArticle	en
heal.identifier.primary	10.1016/S0965-9978(00)00051-X	en
heal.identifier.secondary	http://dx.doi.org/10.1016/S0965-9978(00)00051-X	en
heal.language	English	en
heal.publicationDate	2000	en
heal.abstract	Properly adapted Boltzmann machine neural networks are used to devise effective unstructured grid partitioners that are capable of providing equally loaded grid subsets with minimum interface, for concurrent data-handling on parallel computers. The partitioning scheme is based on recursive bisections so that the outcome always consists of 2(n) partitions. Two different techniques are introduced to speed up the-otherwise costly-partitioning process and several variants are considered. In particular, a transformation of bipolar Hopfield-type neural networks is developed providing an effective multi-scale approach. Results on a number of test cases are presented in order to assess the performance of the proposed techniques. (C) 2000 Elsevier Science Ltd. All rights reserved.	en
heal.publisher	ELSEVIER SCI LTD	en
heal.journalName	ADVANCES IN ENGINEERING SOFTWARE	en
dc.identifier.doi	10.1016/S0965-9978(00)00051-X	en
dc.identifier.isi	ISI:000087628100002	en
dc.identifier.volume	31	en
dc.identifier.issue	7	en
dc.identifier.spage	445	en
dc.identifier.epage	451	en