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Parallel execution of kNN-queries on in-memory K-D trees

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dc.contributor.authorHering, Tim
dc.contributor.editorSaake, Gunter
dc.contributor.editorHenrich, Andreas
dc.contributor.editorLehner, Wolfgang
dc.contributor.editorNeumann, Thomas
dc.contributor.editorKöppen, Veit
dc.date.accessioned2018-10-24T10:44:46Z
dc.date.available2018-10-24T10:44:46Z
dc.date.issued2013
dc.description.abstractParallel algorithms for main memory databases become an increasingly interesting topic as the amount of main memory and the number of CPU cores in computer systems increase. This paper suggests a method for parallelizing the k-d tree and its kNN search algorithm as well as suggesting optimizations. In empirical tests, the resulting modified k-d tree outperforms both the k-d tree and a parallelized sequential search for medium dimensionality data (6-13 dimensions).en
dc.identifier.isbn978-3-88579-610-7
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/17440
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW) 2013 - Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-216
dc.titleParallel execution of kNN-queries on in-memory K-D treesen
dc.typeText/Conference Paper
gi.citation.endPage266
gi.citation.publisherPlaceBonn
gi.citation.startPage257
gi.conference.date11.-12. März 2013
gi.conference.locationMagdeburg
gi.conference.sessiontitleRegular Research Papers

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P216 - BTW2013 - Datenbanksysteme für Business, Technologie und Web – Workshopband