Name
Title | ||
|---|---|---|
Feature Analysis, Tracking, and Data Reduction: An Application to Multiphase Reactor Simulation MFiX-Exa for <italic>In-Situ</italic> Use Case |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MCSE.2020.3016927 | Computing in Science & Engineering |
Keywords | DocType | Volume |
feature analysis,data reduction,reactor simulation MFiX-Exa,exascale computing regime,powerful supercomputers,offline data processing,high compute capabilities,high-resolution data,supercomputer memory,MFiX-Exa simulation,simulation domain,carbon particles,carbon dioxide bubbles,particle-based simulation,multiphase flow,streaming technique,CO2 | Journal | 23 |
Issue | ISSN | Citations |
1 | 1521-9615 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ayan Biswas | 1 | 21 | 3.83 |
| James Ahrens | 2 | 233 | 35.07 |
| Soumya Dutta | 3 | 100 | 10.26 |
| Jordan Musser | 4 | 0 | 0.34 |
| Ann S. Almgren | 5 | 82 | 22.33 |
| Terece L. Turton | 6 | 16 | 5.16 |