@inproceedings{d0a849a6d9884302bbe99cfe12c0e83d,
title = "Extreme event analysis in next generation simulation architectures",
abstract = "Numerical simulations present challenges because they generate petabyte-scale data that must be extracted and reduced during the simulation. We demonstrate a seamless integration of feature extraction for a simulation of turbulent fluid dynamics. The simulation produces on the order of 6 TB per timestep. In order to analyze and store this data, we extract velocity data from a dilated volume of the strong vortical regions and also store a lossy compressed representation of the data. Both reduce data by one or more orders of magnitude. We extract data from user checkpoints in transit while they reside on temporary burst buffer SSD stores. In this way, analysis and compression algorithms are designed to meet specific time constraints so they do not interfere with simulation computations. Our results demonstrate that we can perform feature extraction on a world-class direct numerical simulation of turbulence while it is running and gather meaningful scientific data for archival and post analysis.",
author = "Stephen Hamilton and Randal Burns and Charles Meneveau and Perry Johnson and Peter Lindstrom and John Patchett and Szalay, {Alexander S.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG 2017; 32nd International Conference, ISC High Performance, 2017 ; Conference date: 18-06-2017 Through 22-06-2017",
year = "2017",
doi = "10.1007/978-3-319-58667-0_15",
language = "English (US)",
isbn = "9783319586663",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "277--293",
editor = "Kunkel, {Julian M.} and Pavan Balaji and David Keyes and Rio Yokota",
booktitle = "High Performance Computing - 32nd International Conference, ISC High Performance 2017, Proceedings",
}