Understanding Large-Scale Plasma Simulation Challenges for Fusion Energy on Supercomputers
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| Autores principales: | , , , , , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866916339077087232 |
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| author | Williams, Jeremy J. Bhole, Ashish Kierans, Dylan Hoelzl, Matthias Holod, Ihor Tang, Weikang Tskhakaya, David Costea, Stefan Kos, Leon Podolnik, Ales Hromadka, Jakub Team, JOREK Laure, Erwin Markidis, Stefano |
| author_facet | Williams, Jeremy J. Bhole, Ashish Kierans, Dylan Hoelzl, Matthias Holod, Ihor Tang, Weikang Tskhakaya, David Costea, Stefan Kos, Leon Podolnik, Ales Hromadka, Jakub Team, JOREK Laure, Erwin Markidis, Stefano |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_00394 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding Large-Scale Plasma Simulation Challenges for Fusion Energy on Supercomputers Williams, Jeremy J. Bhole, Ashish Kierans, Dylan Hoelzl, Matthias Holod, Ihor Tang, Weikang Tskhakaya, David Costea, Stefan Kos, Leon Podolnik, Ales Hromadka, Jakub Team, JOREK Laure, Erwin Markidis, Stefano Plasma Physics Distributed, Parallel, and Cluster Computing Performance Computational Physics 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. |
| title | Understanding Large-Scale Plasma Simulation Challenges for Fusion Energy on Supercomputers |
| topic | Plasma Physics Distributed, Parallel, and Cluster Computing Performance Computational Physics |
| url | https://arxiv.org/abs/2407.00394 |