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    Fast Flow-based Distance Quantification and Interpolation for High-Resolution Density Distributions

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    Date
    2017
    Author
    Frey, Steffen
    Ertl, Thomas ORCID
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    Abstract
    We present a GPU-targeted algorithm for the efficient direct computation of distances and interpolates between high-resolution density distributions without requiring any kind of intermediate representation like features. It is based on a previously published multi-core approach, and substantially improves its performance already on the same CPU hardware due to algorithmic improvements. As we explicitly target a manycore-friendly algorithm design, we further achieve significant speedups by running on a GPU. This paper quickly reviews the previous approach, and explicitly discusses the analysis of algorithmic characteristics as well as hardware architectural considerations on which our redesign was based. We demonstrate the performance and results of our technique by means of several transitions between volume data sets.
    BibTeX
    @inproceedings {10.2312:egsh.20171009,
    booktitle = {EG 2017 - Short Papers},
    editor = {Adrien Peytavie and Carles Bosch},
    title = {{Fast Flow-based Distance Quantification and Interpolation for High-Resolution Density Distributions}},
    author = {Frey, Steffen and Ertl, Thomas},
    year = {2017},
    publisher = {The Eurographics Association},
    ISSN = {1017-4656},
    DOI = {10.2312/egsh.20171009}
    }
    URI
    http://dx.doi.org/10.2312/egsh.20171009
    https://diglib.eg.org:443/handle/10.2312/egsh20171009
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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