Session
Technical Poster Session 2: Command & Data Handling
Location
Utah State University, Logan, UT
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)
On-Board Deep Learning for Payload Data Processing: Hardware Performance Comparison
Utah State University, Logan, UT
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)
