Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for In-Situ Use Case

Biswas, Ayan; Ahrens, James P.; Dutta, Soumya; Musser, Jordan M.; Almgren, Ann S.; Turton, Terece L.

doi:10.1109/mcse.2020.3016927

Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for In-Situ Use Case

Journal Article · 14 August 2021 · Computing in Science and Engineering

DOI:https://doi.org/10.1109/mcse.2020.3016927· OSTI ID:1841161

^[1]; Ahrens, James P. ^[1]; ^[1]; ^[2]; Almgren, Ann S. ^[3]; ^[1]

Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
National Energy Technology Lab. (NETL), Morgantown, WV (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

As we enter the exascale computing regime, powerful supercomputers continue to produce much higher amounts of data than what can be stored for offline data processing. To utilize such high compute capabilities on these machines, much of the data processing needs to happen in situ, when the full high-resolution data is available at the supercomputer memory. In this article, we discuss our MFiX-Exa simulation, which models multiphase flow by tracking a very large number of particles through the simulation domain. In one of the use cases, the carbon particles interact with air to produce carbon dioxide bubbles from the reactor. These bubbles are of primary interest to the domain experts for these simulations. For this particle-based simulation, we propose a streaming technique that can be deployed in situ to efficiently identify the bubbles, track them over time, and use them to down-sample the data with minimal loss in these features.

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1841161

Journal Information:: Computing in Science and Engineering, Journal Name: Computing in Science and Engineering Journal Issue: 1 Vol. 23; ISSN 1521-9615

Publisher:: IEEE Computer SocietyCopyright Statement

Country of Publication:: United States

Language:: English

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