Abstract
With the growing computational complexity of science and the complexity of new and emerging hardware, it is time to re-evaluate the traditional monolithic design of computational codes. One new paradigm is constructing larger scientific computational experiments from the coupling of multiple individual scientific applications, each targeting their own physics, characteristic lengths, and/or scales. We present a framework constructed by leveraging capabilities such as in-memory communications, workflow scheduling on HPC resources, and continuous performance monitoring. This code coupling capability is demonstrated by a fusion science scenario, where differences between the plasma at the edges and at the core of a device have different physical descriptions. This infrastructure not only enables the coupling of the physics components, but it also connects in situ or online analysis, compression, and visualization that accelerate the time between a run and the analysis of the science content. Results from runs on Titan and Cori are presented as a demonstration.
Original language | English (US) |
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Title of host publication | Proceedings - IEEE 14th International Conference on eScience, e-Science 2018 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 442-452 |
Number of pages | 11 |
ISBN (Electronic) | 9781538691564 |
DOIs | |
State | Published - Dec 24 2018 |
Event | 14th IEEE International Conference on eScience, e-Science 2018 - Amsterdam, Netherlands Duration: Oct 29 2018 → Nov 1 2018 |
Publication series
Name | Proceedings - IEEE 14th International Conference on eScience, e-Science 2018 |
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Conference
Conference | 14th IEEE International Conference on eScience, e-Science 2018 |
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Country/Territory | Netherlands |
City | Amsterdam |
Period | 10/29/18 → 11/1/18 |
All Science Journal Classification (ASJC) codes
- Computer Science Applications
- Software
- Ecological Modeling
- Modeling and Simulation
Keywords
- Coupling
- In situ analysis
- Staging