Automatic Between-Pulse Analysis of DIII-D Experimental Data Performed Remotely on a Supercomputer at Argonne Leadership Computing Facility

Journal Article · 01 February 2018 · Fusion Science and Technology

DOI: https://doi.org/10.1080/15361055.2017.1390388 · OSTI ID:1437987

Kostuk, M. ^[1]; Uram, T. D. ^[2]; Evans, T. ^[1]; Orlov, D. M. ^[3]; Papka, M. E. ^[4]; Schissel, D. ^[1]

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1. General Atomics, San Diego, CA (United States)
2. Argonne National Lab. (ANL), Lemont, IL (United States)
3. Univ. of California, San Diego, CA (United States)
4. Argonne National Lab. (ANL), Lemont, IL (United States); Northern Illinois Univ., DeKalb, IL (United States)

For the first time, an automatically triggered, between-pulse fusion science analysis code was run on-demand at a remotely located supercomputer at Argonne Leadership Computing Facility (ALCF, Lemont, IL) in support of in-process experiments being performed at DIII-D (San Diego, CA). This represents a new paradigm for combining geographically distant experimental and high performance computing (HPC) facilities to provide enhanced data analysis that is quickly available to researchers. Enhanced analysis improves the understanding of the current pulse, translating into a more efficient use of experimental resources, and to the quality of the resultant science. The analysis code used here, called SURFMN, calculates the magnetic structure of the plasma using Fourier transform. Increasing the number of Fourier components provides a more accurate determination of the stochastic boundary layer near the plasma edge by better resolving magnetic islands, but requires 26 minutes to complete using local DIII-D resources, putting it well outside the useful time range for between pulse analysis. These islands relate to confinement and edge localized mode (ELM) suppression, and may be controlled by adjusting coil currents for the next pulse. Argonne has ensured on-demand execution of SURFMN by providing a reserved queue, a specialized service that launches the code after receiving an automatic trigger, and with network access from the worker nodes for data transfer. Runs are executed on 252 cores of ALCF’s Cooley cluster and the data is available locally at DIII-D within three minutes of triggering. The original SURFMN design limits additional improvements with more cores, however our work shows a path forward where codes that benefit from thousands of processors can run between pulses.

• Research Organization: General Atomics, San Diego, CA (United States); Argonne National Laboratory (ANL), Argonne, IL (United States)
• Sponsoring Organization: USDOE Office of Nuclear Energy (NE); USDOE Office of Science (SC), Fusion Energy Sciences (FES)
• Grant/Contract Number: FC02-04ER54698; AC02-06CH11357
• OSTI ID: 1437987
• Alternate ID(s): OSTI ID: 1475553
• Journal Information: Fusion Science and Technology, Vol. 74, Issue 1-2; ISSN 1536-1055
• Publisher: American Nuclear SocietyCopyright Statement
• Country of Publication: United States
• Language: English