Sunday, September 24

Higher Performance Visualization

8:30 AM-9:15 AM
New Hampshire Ballroom
Chair:Linda R. Petzold, University of California, Santa Barbara, USA

Data analysis in the computational sciences is typically made difficult by the large amount of information that must be correlated to make sense of measurements or simulations of many physical phenomena. Visualization has become a critical tool in understanding these relationships among large volumes of data. Visualization techniques are most effective if they are interrogative, that is, as long as they allow scientists to query and manipulate the visualized data at interactive rates.

We are engaged in a long term project the goal of which is to develop a comprehensive framework for multiscale visualization and simulation for terascale problems, with a tight coupling among modeling, simulation and visualization. In this talk, I will discuss recent work on multiresolution data organization, compression and parallel out-of-core algorithms which deals strictly with progressive interrogative visualization of terascale data.

Chandrajit Bajaj
Department of Computer Sciences and Texas Institute for Computational and Applied Mathematics
University of Texas at Austin, USA
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