Distance visualization of ultrascale data with explorable images

Kwan-Liu Ma, Anna Tikhonova, Carlos D. Correa

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This talk presents a new approach to distance visualization of very large data sets output from scientific supercomputing. The processing power of massively parallel supercomputers increases at a rather fast rate, about an order of magnitude faster every three years, enabling scientists to model complex physical phenomena and chemical processes at unprecedented fidelity. Several petascale computers are already in operation (http://www.top500.org) and exascale computing is around the corner. Each run of a petascale simulation typically outputs several hundred terabytes of data to disk. Transferring data at this scale over wide-area networks to the scientist's laboratory for post-processing analysis is not an option. Even the data files may be transferred, existing desktop data analysis and visualization tools cannot effectively handle such large-scale data. If the scientists may use the same supercomputing facility for data analysis and visualization, there are three viable solutions: in situ visualization, where visualization is computed during the simulation on the same supercomputer co-processing visualization, where visualization is computed during the simulation on a separate computer, and post-processing visualization, where visualization is computed after simulation is over.

Original languageEnglish (US)
Title of host publicationACM SIGGRAPH 2010 Talks, SIGGRAPH '10
StatePublished - Sep 10 2010
EventACM SIGGRAPH 2010 Talks, SIGGRAPH '10 - Los Angeles, CA, United States
Duration: Jul 26 2010Jul 30 2010


OtherACM SIGGRAPH 2010 Talks, SIGGRAPH '10
Country/TerritoryUnited States
CityLos Angeles, CA

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition
  • Software


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