期刊
COMPUTING IN SCIENCE & ENGINEERING
卷 23, 期 1, 页码 75-82出版社
IEEE COMPUTER SOC
DOI: 10.1109/MCSE.2020.3016927
关键词
-
资金
- Department of Energy
- U.S. Department of Energy Office of Science [17-SC-20-SC]
- National Nuclear Security Administration [17-SC-20-SC]
- Los Alamos National Laboratory
The article discusses a method to simulate multiphase flow by tracking a large number of particles and utilizing streaming technique for efficient real-time data processing, particularly in identifying, tracking, and downsampling bubbles generated from particle interactions in a reactor.
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.
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