A Space-Efficient Method for Navigable Ensemble Analysis and Visualization
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
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.
Description
@inproceedings{10.2312:pgv.20171092,
booktitle = {Eurographics Symposium on Parallel Graphics and Visualization},
editor = {Alexandru Telea and Janine Bennett},
title = {{A Space-Efficient Method for Navigable Ensemble Analysis and Visualization}},
author = {Hota, Alok and Raji, Mohammad and Hobson, Tanner and Huang, Jian},
year = {2017},
publisher = {The Eurographics Association},
ISSN = {1727-348X},
ISBN = {978-3-03868-034-5},
DOI = {10.2312/pgv.20171092}
}