Work

On-Board Deep Learning for Payload Data Processing: Hardware Performance Comparison

Year: 2025
Type: conference-paper
Abstract: The path towards a multi-planetary species passes through the implementation of disruptive technological innovation. Artificial Intelligence and autonomy on spacecraft will be a fundamental part of this future. Hence, leveraging on-the-edge AI accelerators, such as FPGAs, GPUs, VPUs, ASICs, will constitute an essential component of the spacecraft hardware of tomorrow. This work presents a comparative work, specifically targeted to the use of on-board satellites. The tested platforms are Intel Myriad X, Nvidia Jetson Nano, and CPU (x64 architecture)
Language: English
Open Access status: green
OpenAlex ID: W3183379946
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