@inproceedings{7b78bb9311df435c97c426359c8380e5,
title = "Enabling Explorative Visualization with Full Temporal Resolution via In Situ Calculation of Temporal Intervals",
abstract = "We explore a technique for saving full spatiotemporal simulation data for visualization and analysis. While such data is typically prohibitively large to store, we consider an in situ reduction approach that takes advantage of temporal coherence to make storage sizes tractable in some cases. Rather than limiting our data reduction to individual time slices or time windows, our algorithms act on individual locations and save data to disk as temporal intervals. Our results show that the efficacy of piecewise approximations varies based on the desired error bound guarantee and tumultuousness of the time-varying data. We ran our in situ algorithms for one simulation and experienced promising results compared to the traditional paradigm. We also compared the results to two data reduction operators: wavelets and SZ.",
author = "Nicole Marsaglia and Shaomeng Li and Hank Childs",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.; International Conference on High Performance Computing, ISC High Performance 2018 ; Conference date: 28-06-2018 Through 28-06-2018",
year = "2018",
doi = "10.1007/978-3-030-02465-9\_19",
language = "English",
isbn = "9783030024642",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "273--293",
editor = "Mich{\`e}le Weiland and Sadaf Alam and Rio Yokota and John Shalf",
booktitle = "High Performance Computing - ISC High Performance 2018 International Workshops, Revised Selected Papers",
address = "Germany",
}