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Activity Number: 18 - Uncertainty Quantification Across the Boundaries
Type: Topic-Contributed
Date/Time: Sunday, August 8, 2021 : 1:30 PM to 3:20 PM
Sponsor: Uncertainty Quantification in Complex Systems Interest Group
Abstract #317336
Title: In Situ Uncertainty Quantification
Author(s): Natalie Klein* and Earl Lawrence and Arthur Lui and Mary Frances Dorn and Yu Wang
Companies: Los Alamos National Laboratory and Los Alamos National Laboratory and Los Alamos National Laboratory and Los Alamos National Laboratory and University of Michigan
Keywords: in situ; uncertainty quantification; climate; space weather; simulations

Communication and storage will not keep pace with computational power in the next generation of supercomputers. As a result, most of the data generated during large-scale simulations will need to be discarded and will not be available for post hoc analysis. In this talk, we will discuss in situ analysis for building statistical models inside simulations as they run to make use of the full simulation data. We will demonstrate in situ modeling in climate and space weather simulations. In both cases, the simulations produce large amounts of spatiotemporal data that is typically not saved out at full resolution, complicating efforts to address scientific questions of interest such as characterization of extreme events and their precursors. Our approach addresses challenges that arise because the data are distributed across compute nodes and most of the computational power is reserved for the physics simulations.

Authors who are presenting talks have a * after their name.

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