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rdf:type
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Description
| - A triangulation of points in E^2, or a tetrahedronization of points in E^3, is used in many applications. It is not necessary to fulfill the Delaunay criteria in all cases. For large data (more then 5? 10^7 points), parallel methods are used for the purpose of decreasing time complexity. A new approach for fast and effective parallel CPU and GPU triangulation, or tetrahedronization, of large data sets in E^2 or E^3, is proposed in this paper. Experimental results show that the triangulation/tetrahedralization, is close to the Delaunay triangulation/tetrahedralization. It also demonstrates the applicability of the method presented in applications.
- A triangulation of points in E^2, or a tetrahedronization of points in E^3, is used in many applications. It is not necessary to fulfill the Delaunay criteria in all cases. For large data (more then 5? 10^7 points), parallel methods are used for the purpose of decreasing time complexity. A new approach for fast and effective parallel CPU and GPU triangulation, or tetrahedronization, of large data sets in E^2 or E^3, is proposed in this paper. Experimental results show that the triangulation/tetrahedralization, is close to the Delaunay triangulation/tetrahedralization. It also demonstrates the applicability of the method presented in applications. (en)
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Title
| - Fast Parallel Triangulation Algorithm of Large Data Sets in E2 and E3 for In-Core and Out-Core Memory Processing
- Fast Parallel Triangulation Algorithm of Large Data Sets in E2 and E3 for In-Core and Out-Core Memory Processing (en)
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skos:prefLabel
| - Fast Parallel Triangulation Algorithm of Large Data Sets in E2 and E3 for In-Core and Out-Core Memory Processing
- Fast Parallel Triangulation Algorithm of Large Data Sets in E2 and E3 for In-Core and Out-Core Memory Processing (en)
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skos:notation
| - RIV/49777513:23520/14:43922550!RIV15-MSM-23520___
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http://linked.open...avai/riv/aktivita
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http://linked.open...avai/riv/aktivity
| - P(LG13047), P(LH12181), S
|
http://linked.open...vai/riv/dodaniDat
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http://linked.open...aciTvurceVysledku
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http://linked.open.../riv/druhVysledku
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http://linked.open...iv/duvernostUdaju
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http://linked.open...titaPredkladatele
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http://linked.open...dnocenehoVysledku
| |
http://linked.open...ai/riv/idVysledku
| - RIV/49777513:23520/14:43922550
|
http://linked.open...riv/jazykVysledku
| |
http://linked.open.../riv/klicovaSlova
| - Large data; CPU & GPU; Parallel computing; Triangulation (en)
|
http://linked.open.../riv/klicoveSlovo
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http://linked.open...ontrolniKodProRIV
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http://linked.open...v/mistoKonaniAkce
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http://linked.open...i/riv/mistoVydani
| |
http://linked.open...i/riv/nazevZdroje
| - Computational Science and Its Applications - ICCSA 2014
|
http://linked.open...in/vavai/riv/obor
| |
http://linked.open...ichTvurcuVysledku
| |
http://linked.open...cetTvurcuVysledku
| |
http://linked.open...vavai/riv/projekt
| |
http://linked.open...UplatneniVysledku
| |
http://linked.open...iv/tvurceVysledku
| - Skala, Václav
- Šmolík, Michal
|
http://linked.open...vavai/riv/typAkce
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http://linked.open.../riv/zahajeniAkce
| |
issn
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number of pages
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http://bibframe.org/vocab/doi
| - 10.1007/978-3-319-09129-7_23
|
http://purl.org/ne...btex#hasPublisher
| |
https://schema.org/isbn
| |
http://localhost/t...ganizacniJednotka
| |