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    • 38-Issue 3
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    Scalable Ray Tracing Using the Distributed FrameBuffer

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    Date
    2019
    Author
    Usher, Will
    Wald, Ingo ORCID
    Amstutz, Jefferson
    Günther, Johannes
    Brownlee, Carson
    Pascucci, Valerio ORCID
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    Abstract
    Image- and data-parallel rendering across multiple nodes on high-performance computing systems is widely used in visualization to provide higher frame rates, support large data sets, and render data in situ. Specifically for in situ visualization, reducing bottlenecks incurred by the visualization and compositing is of key concern to reduce the overall simulation runtime. Moreover, prior algorithms have been designed to support either image- or data-parallel rendering and impose restrictions on the data distribution, requiring different implementations for each configuration. In this paper, we introduce the Distributed FrameBuffer, an asynchronous image-processing framework for multi-node rendering. We demonstrate that our approach achieves performance superior to the state of the art for common use cases, while providing the flexibility to support a wide range of parallel rendering algorithms and data distributions. By building on this framework, we extend the open-source ray tracing library OSPRay with a data-distributed API, enabling its use in data-distributed and in situ visualization applications.
    BibTeX
    @article {10.1111:cgf.13702,
    journal = {Computer Graphics Forum},
    title = {{Scalable Ray Tracing Using the Distributed FrameBuffer}},
    author = {Usher, Will and Wald, Ingo and Amstutz, Jefferson and Günther, Johannes and Brownlee, Carson and Pascucci, Valerio},
    year = {2019},
    publisher = {The Eurographics Association and John Wiley & Sons Ltd.},
    ISSN = {1467-8659},
    DOI = {10.1111/cgf.13702}
    }
    URI
    https://doi.org/10.1111/cgf.13702
    https://diglib.eg.org:443/handle/10.1111/cgf13702
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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.
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