Adaptive, multiresolution visualization of large data sets using parallel octrees [electronic resource].
- Washington, D.C. : United States. Dept. of Energy, 1999. and Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy.
- Physical Description:
- 12 pages : digital, PDF file
- Additional Creators:
- Argonne National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
- Restrictions on Access:
- Free-to-read Unrestricted online access
- The interactive visualization and exploration of large scientific data sets is a challenging and difficult task; their size often far exceeds the performance and memory capacity of even the most powerful graphics work-stations. To address this problem, we have created a technique that combines hierarchical data reduction methods with parallel computing to allow interactive exploration of large data sets while retaining full-resolution capability. The hierarchical representation is built in parallel by strategically inserting field data into an octree data structure. We provide functionality that allows the user to interactively adapt the resolution of the reduced data sets so that resolution is increased in regions of interest without sacrificing local graphics performance. We describe the creation of the reduced data sets using a parallel octree, the software architecture of the system, and the performance of this system on the data from a Rayleigh-Taylor instability simulation.
- Published through SciTech Connect., 06/10/1999., "anl/mcs/cp-99211", SC99: High Performance Networking and Computing Conference, Portland, OR (US), 11/13/1999--11/19/1999., and Freitag, L. A.; Loy, R. M.
- Funding Information:
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