Visualizing extreme-scale data

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

Abstract

The ability to extract meaning from the huge amounts of data obtained from simulations, experiments, sensors, or the world wide web gives one tremendous advantage over others in the respective area of business or study. Visualization becomes a hot topic because it enables that ability. As data size is growing from terascale to petascale and exascale, new visualization techniques must be developed and integrated into data analysis tools and problem solving environments so the collected data can be fully exploited. In this talk, I will point out a few important directions for advancing the visualization technology, which include parallel visualization, knowledge-assisted visualization, intelligent visualization, and in situ visualization. I will use some of the projects we have done at UC Davis in my discussion.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2008
Volume6809
DOIs
StatePublished - May 15 2008
EventVisualization and Data Analysis 2008 - San Jose, CA, United States
Duration: Jan 28 2008Jan 29 2008

Other

OtherVisualization and Data Analysis 2008
CountryUnited States
CitySan Jose, CA
Period1/28/081/29/08

Keywords

  • Data analysis
  • Data compression
  • Feature extraction and tracking
  • Machine learning
  • Parallel computing
  • 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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  • Cite this

    Ma, K-L. (2008). Visualizing extreme-scale data. In Proceedings of SPIE-IS and T Electronic Imaging - Visualization and Data Analysis 2008 (Vol. 6809). [680902] https://doi.org/10.1117/12.786401