Autostereoscopic display of large-scale scientific visualization

Tom Peterka, Robert Ross, Hongfeng Yu, Kwan Liu Ma, Robert Kooima, Javier Girado

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


Modern computational science poses two challenges for scientific visualization: managing the size of resulting datasets and extracting maximum knowledge from them. While our team attacks the first problem by implementing parallel visualization algorithms on supercomputing architectures at vast scale, we are experimenting with autostereoscopic display technology to aid scientists in the second challenge. We are building a visualization framework connecting parallel visualization algorithms running on one of the world's most powerful supercomputers with high-quality autostereo display systems. This paper is a case study of the development of an end-to-end solution that couples scalable volume rendering on thousands of supercomputer cores to the scientists' interaction with autostereo volume rendering at their desktops and larger display spaces. We discuss modifications to our volume rendering algorithm to produce perspective stereo images, their transport from supercomputer to display system, and the scientists' 3D interactions. A lightweight display client software architecture supports a variety of monoscopic and autostereoscopic display technologies through a flexible configuration framework. This case study provides a foundation that future research can build upon in order to examine how autostereo immersion in scientific data can improve understanding and perhaps enable new discoveries.

Original languageEnglish (US)
Article number723706
JournalProceedings of SPIE - The International Society for Optical Engineering
StatePublished - 2009
Externally publishedYes
EventStereoscopic Displays and Applications XX - San Jose, CA, United States
Duration: Jan 19 2009Jan 21 2009


  • Autostereoscopic 3D displays
  • Large scale visualization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


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