28 January 2008 Visualizing extreme-scale data
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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.
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Kwan-Liu Ma, Kwan-Liu Ma, } "Visualizing extreme-scale data", Proc. SPIE 6809, Visualization and Data Analysis 2008, 680902 (28 January 2008); doi: 10.1117/12.786401; https://doi.org/10.1117/12.786401
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