Center for Computing Research (CCR)

Center for Computing Research

The Center for Computing Research (CCR) at Sandia creates technology and solutions for many of our nation's most demanding national security challenges. The Center's portfolio spans the spectrum from fundamental research to state‑of‑the‑art applications. Our work includes computer system architecture (both hardware and software); enabling technology for modeling physical and engineering systems; and research in discrete mathematics, data analytics, cognitive modeling, and decision support materials.

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  • Sandia and Kitware Partner to Improve Performance of Volume Rendering for HPC Applications

    In collaboration with researchers at Sandia, Kitware developers have made significant performance improvements to volume rendering for large-scale applications. First, Kitware significantly improved unstructured-grid volume rendering....

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    Sandia and Kitware Partner to Improve Performance of Volume Rendering for HPC Applications

    In collaboration with researchers at Sandia, Kitware developers have made significant performance improvements to volume rendering for large-scale applications. First, Kitware significantly improved unstructured-grid volume rendering.  In a volume-rendering example for turbulent flow with 100 million cells on 320 ranks on a Sandia cluster, the volume rendered in 8 seconds using the new method, 122 seconds for the old method, making unstructured-grid visualization a viable in-situ option for applications.  Second, Kitware created a new "resample-to-image" filter that uses adaptive-mesh refinement to calculate and resample the image to the smaller mesh with minimal visualization artifacts.  The new filter reduces the amount of data required for visualization and provides a potential performance improvement (more testing is needed).  These improvements were driven by Sandia researchers for the NNSA Advanced Simulation and Computing program in support of the P&EM, V&V, and ATDM ASC sub-elements as part of a Large-Scale Calculation Initiative (LSCI) project. Kitware funding was provided through a contract with the ASC/CSSE sub-element.  Contacts for this work are Stefan Paul Domino (spdomin@sandia.gov), W. Alan Scott (wascott@sandia.gov), and Ron A. Oldfield (raoldfi@sandia.gov).

    The image shows an unstructured volume-rendered Q-criterion field for a Reynolds # ~10,000 turbulent impinging jet. The performance improvements enabled rendering (for the first time) of the full unstructured dataset (nearly 2 billion Hexahedral elements). The rendering of this image was supported by the ASC LSCI portfolio.

    Contact: Oldfield, Ron A.
    November 2020
    2020-12237 S

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