Evaluation of NVIDIA Xavier NX Platform for Real-Time Image Processing for Plasma Diagnostics

Bartłomiej Jabłoński, Dariusz Makowski, Piotr Perek, Patryk Nowak vel Nowakowski, Aleix Puig Sitjes, Marcin Jakubowski, Yu Gao, Axel Winter and The W-X Team
Additional contact information
Bartłomiej Jabłoński: Department of Microelectronics and Computer Science, Lodz University of Technology, 90-924 Łódź, Poland
Dariusz Makowski: Department of Microelectronics and Computer Science, Lodz University of Technology, 90-924 Łódź, Poland
Piotr Perek: Department of Microelectronics and Computer Science, Lodz University of Technology, 90-924 Łódź, Poland
Patryk Nowak vel Nowakowski: Department of Microelectronics and Computer Science, Lodz University of Technology, 90-924 Łódź, Poland
Aleix Puig Sitjes: Stellarator Edge and Divertor Physics Division, Max Planck Institute for Plasma Physics, 17491 Greifswald, Germany
Marcin Jakubowski: Stellarator Edge and Divertor Physics Division, Max Planck Institute for Plasma Physics, 17491 Greifswald, Germany
Yu Gao: Stellarator Edge and Divertor Physics Division, Max Planck Institute for Plasma Physics, 17491 Greifswald, Germany
Axel Winter: Wendelstein 7-X Operations Division, Max Planck Institute for Plasma Physics, 17491 Greifswald, Germany
The W-X Team: W7-X Team are listed in acknowledgments.

Energies, 2022, vol. 15, issue 6, 1-19

Abstract: Machine protection is a core task of real-time image diagnostics aiming for steady-state operation in nuclear fusion devices. The paper evaluates the applicability of the newest low-power NVIDIA Jetson Xavier NX platform for image plasma diagnostics. This embedded NVIDIA Tegra System-on-a-Chip (SoC) integrates a Graphics Processing Unit (GPU) and Central Processing Unit (CPU) on a single chip. The hardware differences and features compared to the previous NVIDIA Jetson TX2 are signified. Implemented algorithms detect thermal events in real-time, utilising the high parallelism provided by the embedded General-Purpose computing on Graphics Processing Units (GPGPU). The performance and accuracy are evaluated on the experimental data from the Wendelstein 7-X (W7-X) stellarator. Strike-line and reflection events are primarily investigated, yet benchmarks for overload hotspots, surface layers and visualisation algorithms are also included. Their detection might allow for automating real-time risk evaluation incorporated in the divertor protection system in W7-X. For the first time, the paper demonstrates the feasibility of complex real-time image processing in nuclear fusion applications on low-power embedded devices. Moreover, GPU-accelerated reference processing pipelines yielding higher accuracy compared to the literature results are proposed, and remarkable performance improvement resulting from the upgrade to the Xavier NX platform is attained.

Keywords: graphics processing unit; general-purpose computing on graphics processing units; image processing; plasma diagnostics; embedded system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/6/2088/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/6/2088/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:6:p:2088-:d:770000

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().