Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers

Eric Suchyta; Jong Youl Choi; Seung Hoe Ku; David Pugmire; Ana Gainaru; Kevin Huck; Ralph Kube; Aaron Scheinberg; Frederic Suter; Choongseock Chang; Todd Munson; Norbert Podhorszki; Scott Klasky

doi:10.1109/CLUSTER51413.2022.00035

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers

Eric Suchyta, Jong Youl Choi, Seung Hoe Ku, David Pugmire, Ana Gainaru, Kevin Huck, Ralph Kube, Aaron Scheinberg, Frederic Suter, Choongseock Chang, Todd Munson, Norbert Podhorszki, Scott Klasky

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

Abstract

The current practice for fusion scientists running first principle simulations on high performance computing plat-forms is to either run their simulations and output their data for post-hoc analysis, or to place in situ analytics into their code. In this paper we examine a complex workflow using XGC fusions simulation run on the Oak Ridge Leadership Computing Facility's supercomputer Summit, which also involve three anal-yses as part of the results necessary for scientific discovery. We discuss the challenges faced when implementing these algorithms and present an original hybrid staging technique to help enable the physicists to make discoveries during the execution of the simulation. By creating this infrastructure, we can examine complicated physics results, which may not have been possible without the infrastructure. For example, our work enables the online visualization of turbulent homoclinic tangle around the magnetic X-point, breaking the last confinement surface. This visualization could help fusion scientists to better understand and improve the turbulence spread of plasma exhaust heat, which is crucial toward realizing plasmas beyond the currently accessible physics regimes of present-day tokamak reactors. The physics of turbulent homoclinic tangle will be reported in a future physics publication, by utilizing the original online analysis/visualization framework presented in this paper.

Original language	English
Title of host publication	Proceedings - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	218-229
Number of pages	12
ISBN (Electronic)	9781665498562
DOIs	https://doi.org/10.1109/CLUSTER51413.2022.00035
State	Published - 2022
Event	2022 IEEE International Conference on Cluster Computing, CLUSTER 2022 - Heidelberg, Germany Duration: Sep 6 2022 → Sep 9 2022

Publication series

Name	Proceedings - IEEE International Conference on Cluster Computing, ICCC
Volume	2022-September
ISSN (Print)	1552-5244

Conference

Conference	2022 IEEE International Conference on Cluster Computing, CLUSTER 2022
Country/Territory	Germany
City	Heidelberg
Period	09/6/22 → 09/9/22

Funding

This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations—the Office of Science and the National Nuclear Security Administration— responsible for the planning and preparation of a capable ex-ascale ecosystem—including software, applications, hardware, advanced system engineering, and early testbed platforms—to support the nation’s exascale computing imperative. This research was supported by the Exascale Computing Project (ECP), Project Number: 17-SC-20-SC, a collaborative effort of two DOE organizations-the Office of Science and the National Nuclear Security Administration-responsible for the planning and preparation of a capable exascale ecosystem-including software, applications, hardware, advanced system engineering, and early testbed platforms-to support the nation’s exascale computing imperative This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-00OR22725.

Keywords

Extreme Scale
Fusion Science
Online Analysis and Visualization
Workflows

Access to Document

10.1109/CLUSTER51413.2022.00035

Cite this

Suchyta, E., Choi, J. Y., Ku, S. H., Pugmire, D., Gainaru, A., Huck, K., Kube, R., Scheinberg, A., Suter, F., Chang, C., Munson, T., Podhorszki, N., & Klasky, S. (2022). Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers. In Proceedings - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022 (pp. 218-229). (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2022-September). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CLUSTER51413.2022.00035

Suchyta, Eric ; Choi, Jong Youl ; Ku, Seung Hoe et al. / Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers. Proceedings - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 218-229 (Proceedings - IEEE International Conference on Cluster Computing, ICCC).

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title = "Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers",

abstract = "The current practice for fusion scientists running first principle simulations on high performance computing plat-forms is to either run their simulations and output their data for post-hoc analysis, or to place in situ analytics into their code. In this paper we examine a complex workflow using XGC fusions simulation run on the Oak Ridge Leadership Computing Facility's supercomputer Summit, which also involve three anal-yses as part of the results necessary for scientific discovery. We discuss the challenges faced when implementing these algorithms and present an original hybrid staging technique to help enable the physicists to make discoveries during the execution of the simulation. By creating this infrastructure, we can examine complicated physics results, which may not have been possible without the infrastructure. For example, our work enables the online visualization of turbulent homoclinic tangle around the magnetic X-point, breaking the last confinement surface. This visualization could help fusion scientists to better understand and improve the turbulence spread of plasma exhaust heat, which is crucial toward realizing plasmas beyond the currently accessible physics regimes of present-day tokamak reactors. The physics of turbulent homoclinic tangle will be reported in a future physics publication, by utilizing the original online analysis/visualization framework presented in this paper.",

keywords = "Extreme Scale, Fusion Science, Online Analysis and Visualization, Workflows",

author = "Eric Suchyta and Choi, {Jong Youl} and Ku, {Seung Hoe} and David Pugmire and Ana Gainaru and Kevin Huck and Ralph Kube and Aaron Scheinberg and Frederic Suter and Choongseock Chang and Todd Munson and Norbert Podhorszki and Scott Klasky",

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language = "English",

series = "Proceedings - IEEE International Conference on Cluster Computing, ICCC",

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Suchyta, E , Choi, JY, Ku, SH, Pugmire, D, Gainaru, A, Huck, K, Kube, R, Scheinberg, A, Suter, F, Chang, C, Munson, T, Podhorszki, N & Klasky, S 2022, Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers. in Proceedings - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022. Proceedings - IEEE International Conference on Cluster Computing, ICCC, vol. 2022-September, Institute of Electrical and Electronics Engineers Inc., pp. 218-229, 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022, Heidelberg, Germany, 09/6/22. https://doi.org/10.1109/CLUSTER51413.2022.00035

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers. / Suchyta, Eric ; Choi, Jong Youl; Ku, Seung Hoe et al.
Proceedings - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022. Institute of Electrical and Electronics Engineers Inc., 2022. p. 218-229 (Proceedings - IEEE International Conference on Cluster Computing, ICCC; Vol. 2022-September).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Suchyta, Eric

AU - Choi, Jong Youl

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AU - Pugmire, David

AU - Gainaru, Ana

AU - Huck, Kevin

AU - Kube, Ralph

AU - Scheinberg, Aaron

AU - Suter, Frederic

AU - Chang, Choongseock

AU - Munson, Todd

AU - Podhorszki, Norbert

AU - Klasky, Scott

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AB - The current practice for fusion scientists running first principle simulations on high performance computing plat-forms is to either run their simulations and output their data for post-hoc analysis, or to place in situ analytics into their code. In this paper we examine a complex workflow using XGC fusions simulation run on the Oak Ridge Leadership Computing Facility's supercomputer Summit, which also involve three anal-yses as part of the results necessary for scientific discovery. We discuss the challenges faced when implementing these algorithms and present an original hybrid staging technique to help enable the physicists to make discoveries during the execution of the simulation. By creating this infrastructure, we can examine complicated physics results, which may not have been possible without the infrastructure. For example, our work enables the online visualization of turbulent homoclinic tangle around the magnetic X-point, breaking the last confinement surface. This visualization could help fusion scientists to better understand and improve the turbulence spread of plasma exhaust heat, which is crucial toward realizing plasmas beyond the currently accessible physics regimes of present-day tokamak reactors. The physics of turbulent homoclinic tangle will be reported in a future physics publication, by utilizing the original online analysis/visualization framework presented in this paper.

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KW - Workflows

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T3 - Proceedings - IEEE International Conference on Cluster Computing, ICCC

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Suchyta E , Choi JY, Ku SH, Pugmire D, Gainaru A, Huck K et al. Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers. In Proceedings - 2022 IEEE International Conference on Cluster Computing, CLUSTER 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 218-229. (Proceedings - IEEE International Conference on Cluster Computing, ICCC). doi: 10.1109/CLUSTER51413.2022.00035

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers

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