Micropolygon Rendering on the GPU

Information

• Publication Type: Master Thesis
• Workgroup(s)/Project(s):
  • Rendering and Modeling
• Date: January 2015
• Date (Start): 1. January 2013
• Date (End): 13. January 2015
• Diploma Examination: 13. January 2015
• First Supervisor: Michael Wimmer

Abstract

Recent advances in graphics hardware have made it a desirable goal to implement the Reyes algorithm commonly used in production rendering to run on current graphics cards. One key component in this algorithm is the bound-and-split phase, where surface patches are recursively split until they are smaller than a given screen-space bound. While this operation has been successfully parallelized for execution on the GPU using a breadth-first traversal, the resulting implementations are limited by their unpredictable worst-case memory consumption and high global memory bandwidth utilization. In this paper, we propose an alternate strategy that allows limiting the amount of necessary memory by controlling the number of assigned worker threads. The result is an implementation that scales to the performance of the breadth-first approach while offering three advantages: significantly decreased memory usage, a smooth and predictable tradeoff between memory usage and performance, and increased locality for surface processing. This allows us to render scenes that would require too much memory to be processed by the breadth-first method.

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BibTeX

@mastersthesis{WEBER-2015-PRA1,
  title =      "Micropolygon Rendering on the GPU",
  author =     "Thomas Weber",
  year =       "2015",
  abstract =   "Recent advances in graphics hardware have made it a
               desirable goal to implement the Reyes algorithm commonly
               used in production rendering to run on current graphics
               cards. One key component in this algorithm is the
               bound-and-split phase, where surface patches are recursively
               split until they are smaller than a given screen-space
               bound. While this operation has been successfully
               parallelized for execution on the GPU using a breadth-first
               traversal, the resulting implementations are limited by
               their unpredictable worst-case memory consumption and high
               global memory bandwidth utilization. In this paper, we
               propose an alternate strategy that allows limiting the
               amount of necessary memory by controlling the number of
               assigned worker threads. The result is an implementation
               that scales to the performance of the breadth-first approach
               while offering three advantages: significantly decreased
               memory usage, a smooth and predictable tradeoff between
               memory usage and performance, and increased locality for
               surface processing. This allows us to render scenes that
               would require too much memory to be processed by the
               breadth-first method.",
  month =      jan,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2015/WEBER-2015-PRA1/",
}