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Proceedings Paper

Parallel visualization of large data sets
Author(s): Robert O. Rosenberg; Marco O. Lanzagorta; Almadena Chtchelkanova; Alexei Khokhlov
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Paper Abstract

In this paper we describe our efforts towards the parallel visualization of large data sets. We describe the fully threaded tree (FTT) structure developed at NRL to tackle the problem of massive parallel calculations using adaptive mesh refinement methods. All operations with FTT are performed in parallel and require only a small memory overhead. The FTT can be viewed as a data compression scheme that dramatically improves the performance of standard finite difference algorithms by performing calculations on the compressed data in situ. Because of the tremendous benefits of this type of data structure, it is of great interest to develop visualization algorithms that are native to the FTT. Using the FTT library, we convert the FTT data structure to an unstructured data set and discuss applications to both scatter dot visualization and parallel ray-tracing. The latter technique gives a good indication of the performance and scalability of the FTT algorithm for ray-tracking. We then discuss conversion of the FTT data structure for virtual reality visualization in an immersive room. Our results are presented using an example of a numerical calculation of a detonation in a rectangular cavity using from 1 to 2 million cells.

Paper Details

Date Published: 28 February 2000
PDF: 9 pages
Proc. SPIE 3960, Visual Data Exploration and Analysis VII, (28 February 2000); doi: 10.1117/12.378889
Show Author Affiliations
Robert O. Rosenberg, Naval Research Lab. (United States)
Marco O. Lanzagorta, Naval Research Lab. (United States)
Almadena Chtchelkanova, Naval Research Lab. (United States)
Alexei Khokhlov, Naval Research Lab. (United States)

Published in SPIE Proceedings Vol. 3960:
Visual Data Exploration and Analysis VII
Robert F. Erbacher; Philip C. Chen; Jonathan C. Roberts; Craig M. Wittenbrink, Editor(s)

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