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OSPRay - A CPU Ray Tracing Framework for Scientific Visualization

Published: 01 January 2017 Publication History

Abstract

Scientific data is continually increasing in complexity, variety and size, making efficient visualization and specifically rendering an ongoing challenge. Traditional rasterization-based visualization approaches encounter performance and quality limitations, particularly in HPC environments without dedicated rendering hardware. In this paper, we present OSPRay, a turn-key CPU ray tracing framework oriented towards production-use scientific visualization which can utilize varying SIMD widths and multiple device backends found across diverse HPC resources. This framework provides a high-quality, efficient CPU-based solution for typical visualization workloads, which has already been integrated into several prevalent visualization packages. We show that this system delivers the performance, high-level API simplicity, and modular device support needed to provide a compelling new rendering framework for implementing efficient scientific visualization workflows.

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  • (2024)Progressive Tree-Based Compression of Large-Scale Particle DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.326062830:7(4321-4338)Online publication date: 1-Jul-2024
  • (2023)Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEIProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624159(862-867)Online publication date: 12-Nov-2023
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  1. OSPRay - A CPU Ray Tracing Framework for Scientific Visualization

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    cover image IEEE Transactions on Visualization and Computer Graphics
    IEEE Transactions on Visualization and Computer Graphics  Volume 23, Issue 1
    January 2017
    999 pages

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    IEEE Educational Activities Department

    United States

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    Published: 01 January 2017

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    • (2024)Analysis Towards Energy-Aware Image-based In Situ Visualization on the FugakuProceedings of the International Conference on High Performance Computing in Asia-Pacific Region10.1145/3635035.3635048(154-163)Online publication date: 18-Jan-2024
    • (2024)Progressive Tree-Based Compression of Large-Scale Particle DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2023.326062830:7(4321-4338)Online publication date: 1-Jul-2024
    • (2023)Scaling Computational Fluid Dynamics: In Situ Visualization of NekRS using SENSEIProceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis10.1145/3624062.3624159(862-867)Online publication date: 12-Nov-2023
    • (2023)Immersive OSPRay: Enabling VR Experiences with OSPRayPractice and Experience in Advanced Research Computing 2023: Computing for the Common Good10.1145/3569951.3597579(226-230)Online publication date: 23-Jul-2023
    • (2023)GPU-based adaptive data reconstruction for large-scale statistical visualizationJournal of Visualization10.1007/s12650-022-00892-126:4(899-915)Online publication date: 6-Mar-2023
    • (2023)GuideRender: large-scale scene navigation based on multi-modal view frustum movement predictionThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-023-02922-x39:8(3597-3607)Online publication date: 26-Jun-2023
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    • (2022)AMM: Adaptive Multilinear MeshesIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2022.316539228:6(2350-2363)Online publication date: 1-Jun-2022
    • (2022)Probabilistic Occlusion Culling using Confidence Maps for High-Quality Rendering of Large Particle DataIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2021.311478828:1(573-582)Online publication date: 1-Jan-2022
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