Markus Schütz, Bernhard Kerbl, Michael Wimmer
Software Rasterization of 2 Billion Points in Real Time
Proc. ACM Comput. Graph. Interact. Tech., 5:1-16, July 2022. [paper]

Information

  • Publication Type: Journal Paper with Conference Talk
  • Workgroup(s)/Project(s):
  • Date: July 2022
  • Call for Papers: Call for Paper
  • Date (from): 11. July 2022
  • Date (to): 14. July 2022
  • Event: High Performance Graphics 2022
  • Journal: Proc. ACM Comput. Graph. Interact. Tech.
  • Lecturer: Markus Schütz
  • Location: Vancouver
  • Pages (from): 1
  • Pages (to): 16
  • Volume: 5

Abstract

We propose a software rasterization pipeline for point clouds that is capable of brute-force rendering up to two billion points in real time (60fps). Improvements over the state of the art are achieved by batching points in a way that a number of batch-level optimizations can be computed before rasterizing the points within the same rendering pass. These optimizations include frustum culling, level-of-detail rendering, and choosing the appropriate coordinate precision for a given batch of points directly within a compute workgroup. Adaptive coordinate precision, in conjunction with visibility buffers, reduces the number of loaded bytes for the majority of points down to 4, thus making our approach several times faster than the bandwidth-limited state of the art. Furthermore, support for LOD rendering makes our software-rasterization approach suitable for rendering arbitrarily large point clouds, and to meet the increased performance demands of virtual reality rendering.

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BibTeX

@article{SCHUETZ-2022-PCC,
  title =      "Software Rasterization of 2 Billion Points in Real Time",
  author =     "Markus Sch\"{u}tz and Bernhard Kerbl and Michael Wimmer",
  year =       "2022",
  abstract =   "We propose a software rasterization pipeline for point
               clouds that is capable of brute-force rendering up to two
               billion points in real time (60fps). Improvements over the
               state of the art are achieved by batching points in a way
               that a number of batch-level optimizations can be computed
               before rasterizing the points within the same rendering
               pass. These optimizations include frustum culling,
               level-of-detail rendering, and choosing the appropriate
               coordinate precision for a given batch of points directly
               within a compute workgroup. Adaptive coordinate precision,
               in conjunction with visibility buffers, reduces the number
               of loaded bytes for the majority of points down to 4, thus
               making our approach several times faster than the
               bandwidth-limited state of the art. Furthermore, support for
               LOD rendering makes our software-rasterization approach
               suitable for rendering arbitrarily large point clouds, and
               to meet the increased performance demands of virtual reality
               rendering.  ",
  month =      jul,
  journal =    "Proc. ACM Comput. Graph. Interact. Tech.",
  volume =     "5",
  pages =      "1--16",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2022/SCHUETZ-2022-PCC/",
}