HexaShrink, an exact scalable framework for hexahedral meshes with attributes and discontinuities: multiresolution rendering and storage of geoscience models

Computational Geosciences, May 2019

With huge data acquisition progresses realized in the past decades and acquisition systems now able to produce high resolution grids and point clouds, the digitization of physical terrains becomes increasingly more precise. Such extreme quantities of generated and modeled data greatly impact computational performances on many levels of high-performance computing (HPC): storage media, memory requirements, transfer capability, and finally simulation interactivity, necessary to exploit this instance of big data. Efficient representations and storage are thus becoming “enabling technologies” in HPC experimental and simulation science. We propose HexaShrink, an original decomposition scheme for structured hexahedral volume meshes. The latter are used for instance in biomedical engineering, materials science, or geosciences. HexaShrink provides a comprehensive framework allowing efficient mesh visualization and storage. Its exactly reversible multiresolution decomposition yields a hierarchy of meshes of increasing levels of details, in terms of either geometry, continuous or categorical properties of cells. Starting with an overview of volume meshes compression techniques, our contribution blends coherently different multiresolution wavelet schemes in different dimensions. It results in a global framework preserving discontinuities (faults) across scales, implemented as a fully reversible upscaling at different resolutions. Experimental results are provided on meshes of varying size and complexity. They emphasize the consistency of the proposed representation, in terms of visualization, attribute downsampling and distribution at different resolutions. Finally, HexaShrink yields gains in storage space when combined to lossless compression techniques.

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HexaShrink, an exact scalable framework for hexahedral meshes with attributes and discontinuities: multiresolution rendering and storage of geoscience models

Computational Geosciences pp 1–21 | Cite as HexaShrink, an exact scalable framework for hexahedral meshes with attributes and discontinuities: multiresolution rendering and storage of geoscience models AuthorsAuthors and affiliations Jean-Luc PeyrotLaurent DuvalFrédéric PayanLauriane BouardLénaïc ChizatSébastien SchneiderMarc Antonini Open Access Original Paper First Online: 03 May 2019 2 Shares 68 Downloads Abstract With huge data acquisition progresses realized in the past decades and acquisition systems now able to produce high resolution grids and point clouds, the digitization of physical terrains becomes increasingly more precise. Such extreme quantities of generated and modeled data greatly impact computational performances on many levels of high-performance computing (HPC): storage media, memory requirements, transfer capability, and finally simulation interactivity, necessary to exploit this instance of big data. Efficient representations and storage are thus becoming “enabling technologies” in HPC experimental and simulation science. We propose HexaShrink, an original decomposition scheme for structured hexahedral volume meshes. The latter are used for instance in biomedical engineering, materials science, or geosciences. HexaShrink provides a comprehensive framework allowing efficient mesh visualization and storage. Its exactly reversible multiresolution decomposition yields a hierarchy of meshes of increasing levels of details, in terms of either geometry, continuous or categorical properties of cells. Starting with an overview of volume meshes compression techniques, our contribution blends coherently different multiresolution wavelet schemes in different dimensions. It results in a global framework preserving discontinuities (faults) across scales, implemented as a fully reversible upscaling at different resolutions. Experimental results are provided on meshes of varying size and complexity. They emphasize the consistency of the proposed representation, in terms of visualization, attribute downsampling and distribution at different resolutions. Finally, HexaShrink yields gains in storage space when combined to lossless compression techniques. KeywordsCompression Corner point grid Discrete wavelet transform Geometrical discontinuities Hexahedral volume meshes High-performance computing Multiscale methods Simulation Upscaling  This work was partly presented in [1]. Download to read the full article text Notes Acknowledgments The authors would like to thank C. Dawson and M. F. Wheeler for their help, as well as the reviewers whose comments helped improve the compression performance assessment and comparison. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. 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Authors and Affiliations Jean-Luc Peyrot1Laurent Duval23Email authorView author's OrcID profileFrédéric Payan4Lauriane Bouard1Lénaïc Chizat25Sébastien Schneider16Marc Antonini41.IFP Energies nouvellesSolaizeFrance2.IFP Energies nouvellesRueil-MalmaisonFrance3.ESIEE ParisUniversity Paris-Est, LIGMNoisy-le-GrandFrance4.CNRS, I3SUniversité Côte d’AzurSophia AntipolisFrance5.INRIA, ENSPSL Research University ParisParisFrance6.HoloMakeMeudonFrance


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Jean-Luc Peyrot, Laurent Duval, Frédéric Payan, Lauriane Bouard, Lénaïc Chizat, Sébastien Schneider, Marc Antonini. HexaShrink, an exact scalable framework for hexahedral meshes with attributes and discontinuities: multiresolution rendering and storage of geoscience models, Computational Geosciences, 2019, 1-21, DOI: 10.1007/s10596-019-9816-2