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Fast Parallel Triangulation Algorithm of Large Data Sets in E2 and E3 for In-Core and Out-Core Memory Processing

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Computational Science and Its Applications – ICCSA 2014 (ICCSA 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8580))

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Abstract

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 5.107 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.

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Author information

Authors and Affiliations

  1. Faculty of Applied Sciences, University of West Bohemia, Univerzitni 22, CZ 30614, Plzen, Czech Republic

    Michal Smolik & Vaclav Skala

Authors
  1. Michal Smolik
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  2. Vaclav Skala
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Editor information

Editors and Affiliations

  1. School of Engineering, University of Basilicata, 85100, Potenza, Italy

    Beniamino Murgante

  2. Department of Computer and Information Sciences, Covenant University, Ota, Nigeria

    Sanjay Misra

  3. Department of Production and Systems, University of Minho, 4710-057, Braga, Portugal

    Ana Maria A. C. Rocha

  4. DICAR, Polytecnico di Bari, 70125, Bari, Italy

    Carmelo Torre

  5. University of Minho, Braga, Portugal

    Jorge Gustavo Rocha  & Maria Irene Falcão  & 

  6. Monash University, 3800, Clayton, VIC, Australia

    David Taniar

  7. Department of Intelligent Informatics, Kyushu Sangyo University, 2-3-1 Matsukadai, 813-8503, Higashi-ku, Fukuoka, Japan

    Bernady O. Apduhan

  8. Department of Mathematics and Computer Science, University of Perugia, Via Vanvitelli, 1, 06123, Perugia, Italy

    Osvaldo Gervasi

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© 2014 Springer International Publishing Switzerland

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Smolik, M., Skala, V. (2014). Fast Parallel Triangulation Algorithm of Large Data Sets in E2 and E3 for In-Core and Out-Core Memory Processing. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2014. ICCSA 2014. Lecture Notes in Computer Science, vol 8580. Springer, Cham. https://doi.org/10.1007/978-3-319-09129-7_23

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  • DOI: https://doi.org/10.1007/978-3-319-09129-7_23

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09128-0

  • Online ISBN: 978-3-319-09129-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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