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2017
Journal Article
Title

Ternary sparse matrix representation for volumetric mesh subdivision and processing on GPUs

Abstract
In this paper, we present a novel volumetric mesh representation suited for parallel computing on modern GPU architectures. The data structure is based on a compact, ternary sparse matrix storage of boundary operators. Boundary operators correspond to the first-order top-down relations of k-faces to their (k-1)-face facets. The compact, ternary matrix storage format is based on compressed sparse row matrices with signed indices and allows for efficient parallel computation of indirect and bottom-up relations. This representation is then used in the implementation of several parallel volumetric mesh algorithms including Laplacian smoothing and volumetric Catmull-Clark subdivision. We compare these algorithms with their counterparts based on OpenVolumeMesh and achieve speedups from 3x to 531x, for sufficiently large meshes, while reducing memory consumption by up to 36%.
Author(s)
Mueller-Roemer, Johannes  orcid-logo
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Altenhofen, Christian  
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Stork, André
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Journal
Computer graphics forum  
Project(s)
CAxMan  
Funder
European Commission EC  
Conference
Symposium on Geometry Processing (SGP) 2017  
Open Access
DOI
10.24406/publica-r-249113
10.1111/cgf.13245
File(s)
Download (4.63 MB)
Rights
Under Copyright
Language
English
Fraunhofer-Institut für Graphische Datenverarbeitung IGD  
Keyword(s)
  • concurrent programming

  • parallel programming

  • computational geometry

  • object modeling

  • object representation

  • Lead Topic: Digitized Work

  • Research Line: Computer graphics (CG)

  • Research Line: (Interactive) simulation (SIM)

  • Research Line: Modeling (MOD)

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