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dc.contributor.authorSimiakakis, G.
dc.contributor.authorTheoharis, Theoharis
dc.contributor.authorDay, A. M.
dc.contributor.editorSkala, Václav
dc.date.accessioned2015-09-18T11:39:30Z
dc.date.available2015-09-18T11:39:30Z
dc.date.issued2001
dc.identifier.citationJournal of WSCG. 2001, vol. 9, no. 1-3.en
dc.identifier.issn1213-6972 (print)
dc.identifier.issn1213-6980 (CD-ROM)
dc.identifier.issn1213-6964 (online)
dc.identifier.urihttp://hdl.handle.net/11025/15752
dc.identifier.urihttp://wscg.zcu.cz/wscg2001/WSCG2001_Program.htm
dc.format3 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencycs
dc.relation.ispartofseriesJournal of WSCGen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectsledování paprskucs
dc.subjectsměrové dělenícs
dc.subjectparalelní zpracovánícs
dc.subjectdistribuované zpracovánícs
dc.titleParallel ray tracing with 5D adaptive subdivisonen
dc.typečlánekcs
dc.typearticleen
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.description.abstract-translatedWe present strategies for parallelising ray tracing based on 5D adaptive subdivision. Our goals are to obtain good speed-up and to efficiently balance the load between the processors while minimising the required memory per processor inherently large in 5D subdivision. First, loosely coupled strategies are presented, which are ideal for implementation on clusters of workstations, the most commonly used form of parallel processing nowadays. Then we consider a tightly coupled algorithm ideal for multiprocessors with fast interconnection network or shared memory. Finally, results on a cluster of workstations are presented and discussed.en
dc.subject.translatedray tracingen
dc.subject.translateddirectional subdivisionen
dc.subject.translatedparallel processingen
dc.subject.translateddistributed processingen
dc.type.statusPeer-revieweden
Appears in Collections:Volume 9, number 1-3 (2001)

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