• DocumentCode
    3759279
  • Title

    CPU ray tracing large particle data with balanced P-k-d trees

  • Author

    Ingo Wald;Aaron Knoll;Gregory P. Johnson;Will Usher;Valerio Pascucci;Michael E. Papka

  • Author_Institution
    Intel Corporation
  • fYear
    2015
  • fDate
    10/1/2015 12:00:00 AM
  • Firstpage
    57
  • Lastpage
    64
  • Abstract
    We present a novel approach to rendering large particle data sets from molecular dynamics, astrophysics and other sources. We employ a new data structure adapted from the original balanced k-d tree, which allows for representation of data with trivial or no overhead. In the OSPRay visualization framework, we have developed an efficient CPU algorithm for traversing, classifying and ray tracing these data. Our approach is able to render up to billions of particles on a typical workstation, purely on the CPU, without any approximations or level-of-detail techniques, and optionally with attribute-based color mapping, dynamic range query, and advanced lighting models such as ambient occlusion and path tracing.
  • Keywords
    "Ray tracing","Rendering (computer graphics)","Data visualization","Graphics processing units","Data models","Acceleration","Memory management"
  • Publisher
    ieee
  • Conference_Titel
    Scientific Visualization Conference (SciVis), 2015 IEEE
  • Type

    conf

  • DOI
    10.1109/SciVis.2015.7429492
  • Filename
    7429492