  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 this work stems from
the urgent need to advance our understanding of plasma instabilities in
magnetically confined fusion devices. Enhancing JOREK's performance on
supercomputers improves fusion plasma code predictability, enabling more
accurate modelling and faster optimization of fusion designs, thereby
contributing to sustainable fusion energy. In prior studies, we analysed BIT1,
a massively parallel Particle-in-Cell (PIC) code for studying plasma-material
interactions in fusion devices. Our investigations into BIT1's computational
requirements and scalability on advanced supercomputing architectures yielded
valuable insights. Through detailed profiling and performance analysis, we have
identified the primary bottlenecks and implemented optimization strategies,
significantly enhancing parallel performance. This previous work serves as a
foundation for our present endeavours.
