Topological Analysis and CinemaDB Enable Richer Exploration of In Situ Visualization Results
Scientific Achievement
New topological analysis method [1] stores images of
individual features in a Cinema database to enable richer post hoc exploration
of in situ simulation visualization results.
Significance and Impact
The widening gap between compute power and I/O bandwidth requires computing
visualizations in situ, i.e., while simulation is running. Our new method makes
it possible to automatically save individual images of most relevant features,
increase flexibility during post hoc exploration and gain more insight in
simulation results.
Research Details
Isosurface extraction is one of the most common visualization techniques
New approach for shared-memory parallel simplification of contour trees
enables automatic selection of contours, benefiting a wide range of
application domains; the developed techniques can also serve as basis for
high-level feature detection and analysis methods
New approach to saving images of individual topological features in Cinema
database reduces storage requirements while still facilitating greater
degree of explorative analysis
Contact
Gunther H. Weber
Bibliography
P. Hristov, G. H. Weber, H. A. Carr, O. Rübel, and J. P. Ahrens, “Data Parallel Hypersweeps for In Situ Topological Analysis,” in Proceedings of the 10th IEEE Symposium on Large Data Analysis and Visualization (LDAV), pp. 12–21, Oct. 2020.
@inproceedings{Hristov:2020:DPH,
author = {Hristov, Petar and Weber, Gunther H. and Carr, Hamish A. and R{\"u}bel, Oliver and Ahrens, James P.},
title = {Data Parallel Hypersweeps for In Situ Topological Analysis},
booktitle = {Proceedings of the 10th IEEE Symposium on Large Data Analysis and Visualization (LDAV)},
year = {2020},
month = oct,
pages = {12--21},
doi = {10.1109/LDAV51489.2020.00008}
}