Understanding Large-Scale Plasma Simulation Challenges for Fusion Energy on Supercomputers
Jeremy J. Williams, Ashish Bhole, Dylan Kierans, Matthias Hoelzl, Ihor, Holod, Weikang Tang, David Tskhakaya, Stefan Costea, Leon Kos, Ales Podolnik,, Jakub Hromadka, JOREK Team, Erwin Laure, Stefano Markidis

TL;DR
This paper analyzes the computational challenges of large-scale plasma simulations for fusion energy on supercomputers, focusing on improving the efficiency and scalability of codes like JOREK to better predict plasma behavior.
Contribution
It provides a comprehensive HPC analysis of JOREK, optimizing its performance for simulating non-linear MHD phenomena in tokamak fusion devices, building on prior work with BIT1.
Findings
Enhanced JOREK's computational efficiency and scalability.
Identified key bottlenecks in plasma simulation codes.
Improved predictability of plasma behavior in fusion devices.
Abstract
Understanding plasma instabilities is essential for achieving sustainable fusion energy, with large-scale plasma simulations playing a crucial role in both the design and development of next-generation fusion energy devices and the modelling of industrial plasmas. To achieve sustainable fusion energy, it is essential to accurately model and predict plasma behavior under extreme conditions, requiring sophisticated simulation codes capable of capturing the complex interaction between plasma dynamics, magnetic fields, and material surfaces. In this work, we conduct a comprehensive HPC analysis of two prominent plasma simulation codes, BIT1 and JOREK, to advance understanding of plasma behavior in fusion energy applications. Our focus is on evaluating JOREK's computational efficiency and scalability for simulating non-linear MHD phenomena in tokamak fusion devices. The motivation behind…
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Taxonomy
TopicsMagnetic confinement fusion research · Advanced Data Storage Technologies
