학술논문

Hybrid Analysis of Fusion Data for Online Understanding of Complex Science on Extreme Scale Computers
Document Type
Conference
Source
2022 IEEE International Conference on Cluster Computing (CLUSTER) CLUSTER Cluster Computing (CLUSTER), 2022 IEEE International Conference on. :218-229 Sep, 2022
Subject
Computing and Processing
Heating systems
Analytical models
Codes
Computational modeling
Data models
Tokamak devices
Supercomputers
Fusion Science
Online Analysis and Visualization
Workflows
Extreme Scale
Language
ISSN
2168-9253
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.