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Erschienen in:
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2017 | OriginalPaper | Buchkapitel

Extreme Event Analysis in Next Generation Simulation Architectures

verfasst von : Stephen Hamilton, Randal Burns, Charles Meneveau, Perry Johnson, Peter Lindstrom, John Patchett, Alexander S. Szalay

Erschienen in: High Performance Computing

Verlag: Springer International Publishing

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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.

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Vorheriges Kapitel A New Parallel Research Kernel to Expand Research on Dynamic Load-Balancing Capabilities
Nächstes Kapitel An Analysis of Core- and Chip-Level Architectural Features in Four Generations of Intel Server Processors
Fußnoten
1
Thresholds are easy to choose because turbulence has threshold values with physical meaning derived from the inverse Kolmogorov scale that describes the near absence of, medium, and high vorticity [11].
 
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Metadaten
Titel
Extreme Event Analysis in Next Generation Simulation Architectures
verfasst von
Stephen Hamilton
Randal Burns
Charles Meneveau
Perry Johnson
Peter Lindstrom
John Patchett
Alexander S. Szalay
Copyright-Jahr
2017
Buch
High Performance Computing

Print ISBN: 978-3-319-58666-3

Electronic ISBN: 978-3-319-58667-0

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-58667-0_15

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