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    Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives

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    Date
    2017
    Author
    Li, Shaomeng
    Marsaglia, Nicole
    Chen, Vincent
    Sewell, Christopher
    Clyne, John
    Childs, Hank ORCID
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    Abstract
    We consider the problem of wavelet compression in the context of portable performance over multiple architectures. We contribute a new implementation of the wavelet transform algorithm that uses data parallel primitives from the VTK-m library. Because of the data parallel primitives approach, our algorithm is hardware-agnostic and yet can run on many-core architectures. We also study the efficacy of this implementation over multiple architectures against hardware-specific comparators. Results show that our performance is portable, scales well, and is comparable to native implementations. Finally, we argue that compression times for large data sets are likely fast enough to fit within in situ constraints, adding to the evidence that wavelet transformation could be an effective in situ compression operator.
    BibTeX
    @inproceedings {10.2312:pgv.20171095,
    booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
    editor = {Alexandru Telea and Janine Bennett},
    title = {{Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives}},
    author = {Li, Shaomeng and Marsaglia, Nicole and Chen, Vincent and Sewell, Christopher and Clyne, John and Childs, Hank},
    year = {2017},
    publisher = {The Eurographics Association},
    ISSN = {1727-348X},
    ISBN = {978-3-03868-034-5},
    DOI = {10.2312/pgv.20171095}
    }
    URI
    http://dx.doi.org/10.2312/pgv.20171095
    https://diglib.eg.org:443/handle/10.2312/pgv20171095
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    Eurographics Association copyright © 2013 - 2022 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
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