A Space-Efficient Method for Navigable Ensemble Analysis and Visualization (Unknown language)

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Scientists increasingly rely on simulation runs of complex models in lieu of cost-prohibitive or infeasible experimentation. The data output of many controlled simulation runs, the ensemble, is used to verify correctness and quantify uncertainty. However, due to their size and complexity, ensembles are difficult to visually analyze because the working set often exceeds strict memory limitations.We present a navigable ensemble analysis tool, NEA, for interactive exploration of ensembles. NEA's pre-processing component takes advantage of the data similarity characteristics of ensembles to represent the data in a new, spatially-efficient data structure which does not require fully reconstructing the original data at visualization time. This data structure allows a fine degree of control in working set management, which enables interactive ensemble exploration while fitting within memory limitations. Scientists can also gain new insights from the data-similarity analysis in the pre-processing component.

Table of contents conference proceedings

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PaViz: A Power-Adaptive Framework for Optimizing Visualization Performance
Labasan, Stephanie / Larsen, Matthew / Childs, Hank / Rountree, Barry | 2017
Prediction of Distributed Volume Visualization Performance to Support Render Hardware Acquisition
Tkachev, Gleb / Frey, Steffen / Müller, Christoph / Bruder, Valentin / Ertl, Thomas | 2017
Progressive CPU Volume Rendering with Sample Accumulation
Usher, Will / Amstutz, Jefferson / Brownlee, Carson / Knoll, Aaron / Wald, Ingo | 2017
Photo-Guided Exploration of Volume Data Features
Raji, Mohammad / Hota, Alok / Sisneros, Robert / Messmer, Peter / Huang, Jian | 2017
A Space-Efficient Method for Navigable Ensemble Analysis and Visualization
Hota, Alok / Raji, Mohammad / Hobson, Tanner / Huang, Jian | 2017
Interactive Exploration of Dissipation Element Geometry
Vierjahn, Tom / Schnorr, Andrea / Weyers, Benjamin / Denker, Dominik / Wald, Ingo / Garth, Christoph / Kuhlen, Torsten W. / Hentschel, Bernd | 2017
A Task-Based Parallel Rendering Component For Large-Scale Visualization Applications
Biedert, Tim / Werner, Kilian / Hentschel, Bernd / Garth, Christoph | 2017
Achieving Portable Performance For Wavelet Compression Using Data Parallel Primitives
Li, Shaomeng / Marsaglia, Nicole / Chen, Vincent / Sewell, Christopher / Clyne, John / Childs, Hank | 2017