Query-driven visualization of time-varying adaptive mesh refinement data.
The visualization and analysis of AMR-based simulations is integral to the process of obtaining new insight in scientific research. We present a new method for performing query-driven visualization and analysis on AMR data, with specific emphasis on time-varying AMR data. Our work introduces a new method that directly addresses the dynamic spatial and temporal properties of AMR grids that challenge many existing visualization techniques. Further, we present the first implementation of query-driven visualization on the GPU that uses a GPU-based indexing structure to both answer queries and efficiently utilize GPU memory. We apply our method to two different science domains to demonstrate its broad applicability.
Gosink
Luke J
LJ
Institute for Data Analysis and Visualization, University of California, Davis, CA, USA. ljgosink@ucdavis.edu
Anderson
John C
JC
Bethel
E Wes
EW
Joy
Kenneth I
KI