A Versatile and Efficient GPU Data Structure for Spatial Indexing

Handle URI:
http://hdl.handle.net/10754/620933
Title:
A Versatile and Efficient GPU Data Structure for Spatial Indexing
Authors:
Schneider, Jens; Rautek, Peter
Abstract:
In this paper we present a novel GPU-based data structure for spatial indexing. Based on Fenwick trees—a special type of binary indexed trees—our data structure allows construction in linear time. Updates and prefixes can be computed in logarithmic time, whereas point queries require only constant time on average. Unlike competing data structures such as summed-area tables and spatial hashing, our data structure requires a constant amount of bits for each data element, and it offers unconstrained point queries. This property makes our data structure ideally suited for applications requiring unconstrained indexing of large data, such as block-storage of large and block-sparse volumes. Finally, we provide asymptotic bounds on both run-time and memory requirements, and we show applications for which our new data structure is useful.
KAUST Department:
Visual Computing Center (VCC)
Citation:
Schneider J, Rautek P (2016) A Versatile and Efficient GPU Data Structure for Spatial Indexing. IEEE Transactions on Visualization and Computer Graphics: 1–1. Available: http://dx.doi.org/10.1109/TVCG.2016.2599043.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Transactions on Visualization and Computer Graphics
Issue Date:
10-Aug-2016
DOI:
10.1109/TVCG.2016.2599043
Type:
Article
ISSN:
1077-2626
Sponsors:
The authors’ work is funded by the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Volume data sets were obtained from VolVis.org, TU Wien, and Digi-Morph. The vessel data set was provided by John Keyser, TAMU.
Additional Links:
http://ieeexplore.ieee.org/document/7539577/
Appears in Collections:
Articles

Full metadata record

DC FieldValue Language
dc.contributor.authorSchneider, Jensen
dc.contributor.authorRautek, Peteren
dc.date.accessioned2016-10-12T08:26:17Z-
dc.date.available2016-10-12T07:39:40Z-
dc.date.available2016-10-12T08:26:17Z-
dc.date.issued2016-08-10-
dc.identifier.citationSchneider J, Rautek P (2016) A Versatile and Efficient GPU Data Structure for Spatial Indexing. IEEE Transactions on Visualization and Computer Graphics: 1–1. Available: http://dx.doi.org/10.1109/TVCG.2016.2599043.en
dc.identifier.issn1077-2626-
dc.identifier.doi10.1109/TVCG.2016.2599043-
dc.identifier.urihttp://hdl.handle.net/10754/620933-
dc.description.abstractIn this paper we present a novel GPU-based data structure for spatial indexing. Based on Fenwick trees—a special type of binary indexed trees—our data structure allows construction in linear time. Updates and prefixes can be computed in logarithmic time, whereas point queries require only constant time on average. Unlike competing data structures such as summed-area tables and spatial hashing, our data structure requires a constant amount of bits for each data element, and it offers unconstrained point queries. This property makes our data structure ideally suited for applications requiring unconstrained indexing of large data, such as block-storage of large and block-sparse volumes. Finally, we provide asymptotic bounds on both run-time and memory requirements, and we show applications for which our new data structure is useful.en
dc.description.sponsorshipThe authors’ work is funded by the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Volume data sets were obtained from VolVis.org, TU Wien, and Digi-Morph. The vessel data set was provided by John Keyser, TAMU.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urlhttp://ieeexplore.ieee.org/document/7539577/en
dc.rightsThis article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI 10.1109/TVCG.2016.2599043, IEEE Transactions on Visualization and Computer Graphicsen
dc.titleA Versatile and Efficient GPU Data Structure for Spatial Indexingen
dc.typeArticleen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journalIEEE Transactions on Visualization and Computer Graphicsen
dc.eprint.versionPost-printen
kaust.authorSchneider, Jensen
kaust.authorRautek, Peteren

Version History

VersionItem Editor Date Summary
2 10754/620933mastore2016-10-12 09:23:07.0Adding metadata and file
1 10754/620933.1grenzdm2016-10-12 08:39:40.0null
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