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    Memory Efficient GPU-Based Ray Casting for Unstructured Volume Rendering

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    Date
    2008
    Author
    Maximo, A.
    Ribeiro, S.
    Bentes, C.
    Oliveira, A.
    Farias, R.
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    Abstract
    Volume ray casting algorithms benefit greatly with recent increase of GPU capabilities and power. In this paper, we present a novel memory efficient ray casting algorithm for unstructured grids completely implemented on GPU using a recent off-the-shelf nVidia graphics card. Our approach is built upon a recent CPU ray casting algorithm, called VF-Ray, that considerably reduces the memory footprint while keeping good performance. In addition to the implementation of VF-Ray in the graphics hardware, we also propose a restructuring in its data structures. As a result, our algorithm is much faster than the original software version, while using significantly less memory, it needed only one-half of its previous memory usage. Comparing our GPU implementation to other hardware-based ray casting algorithms, our approach used between three to ten times less memory. These results made it possible for our GPU implementation to handle larger datasets on GPU than previous approaches.
    BibTeX
    @inproceedings {10.2312:VG:VG-PBG08:155-162,
    booktitle = {IEEE/ EG Symposium on Volume and Point-Based Graphics},
    editor = {Hans-Christian Hege and David Laidlaw and Renato Pajarola and Oliver Staadt},
    title = {{Memory Efficient GPU-Based Ray Casting for Unstructured Volume Rendering}},
    author = {Maximo, A. and Ribeiro, S. and Bentes, C. and Oliveira, A. and Farias, R.},
    year = {2008},
    publisher = {The Eurographics Association},
    ISSN = {1727-8376},
    ISBN = {978-3-905674-12-5},
    DOI = {10.2312/VG/VG-PBG08/155-162}
    }
    URI
    http://dx.doi.org/10.2312/VG/VG-PBG08/155-162
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    • VG-PBG08: Eurographics/IEEE VGTC on Volume and Point-Based Graphics
    • VG-PBG08: Eurographics/IEEE VGTC on Volume and Point-Based Graphics

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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA