GPU4S: Embedded GPUs in Space -- Latest Project Updates
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Abstract (arXiv)
Following the trend of other safety-critical industries like automotive and avionics, the space domain is witnessing an increase in the on-board computing performance demands. This raise in performance needs comes from both control and payload parts of the spacecraft and calls for advanced electronics systems able to provide high computational power under the constraints of the harsh space environment. On the non-technical side, for strategic reasons it is mandatory to get European independence on the used computing technology. In this project, we study the applicability of embedded GPUs in space, which have shown a dramatic improvement of their performance per-watt ratio coming from their proliferation in consumer markets based on competitive European technology. To that end, we perform an analysis of the existing space application domains to identify which software domains can benefit from their use. Moreover, we survey the embedded GPU domain in order to assess whether embedded GPUs can provide the required computational power and identify the challenges which need to be addressed for their adoption in space. In this paper, we describe the steps followed in the project, as well as a summary of results obtained from our analyses so far in the project.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Sep 2021.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 2; 2025: 2.
6 papers.
- 2023A Survey on Deep Learning-Based Monocular Spacecraft Pose Estimation: Current State, Limitations and Prospectscited by 30
- 2022AstroVision: Towards Autonomous Feature Detection and Description for Missions to Small Bodies Using Deep Learningcited by 10
- 2024Satellite Federated Edge Learning: Architecture Design and Convergence Analysiscited by 10
- 2025Satellite Edge Artificial Intelligence with Large Models: Architectures and Technologiescited by 4
- 2025Efficient Adaptation of Deep Neural Networks for Semantic Segmentation in Space Applicationscited by 1
- 2024Accelerating AI and Computer Vision for Satellite Pose Estimation on the Intel Myriad X Embedded SoCcited by 0
- 2025Efficient Adaptation of Deep Neural Networks for Semantic Segmentation in Space Applications22 Apr 2025
- 2025Satellite Edge Artificial Intelligence with Large Models: Architectures and Technologies2 Apr 2025
- 2024Accelerating AI and Computer Vision for Satellite Pose Estimation on the Intel Myriad X Embedded SoC19 Sep 2024
- 2024Satellite Federated Edge Learning: Architecture Design and Convergence Analysis2 Apr 2024
- 2023A Survey on Deep Learning-Based Monocular Spacecraft Pose Estimation: Current State, Limitations and Prospects12 May 2023
- 2022AstroVision: Towards Autonomous Feature Detection and Description for Missions to Small Bodies Using Deep Learning3 Aug 2022