Contour Tree Depth Images For Large Data Visualization

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Date
2015
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
High-fidelity simulation models on large-scale parallel computer systems can produce data at high computational throughput, but modern architectural trade-offs make full persistent storage to the slow I/O subsystem prohibitively costly with respect to time. We demonstrate the feasibility and potential of combining in situ topological contour tree analysis and compact image-based data representation to address this problem. Our experiments show significant reductions in storage requirements using topology-guided layered depth imaging, while preserving flexibility for explorative visualization and analysis. Our approach represents an effective and easy-to-control trade-off between storage overhead and visualization fidelity for large data visualization.
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@inproceedings{
10.2312:pgv.20151158
, booktitle = {
Eurographics Symposium on Parallel Graphics and Visualization
}, editor = {
C. Dachsbacher and P. Navrátil
}, title = {{
Contour Tree Depth Images For Large Data Visualization
}}, author = {
Biedert, Tim
and
Garth, Christoph
}, year = {
2015
}, publisher = {
The Eurographics Association
}, ISBN = {}, DOI = {
10.2312/pgv.20151158
} }
Citation