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A Comparative Study Of High-Level And Low-Level Implementations Of Deep Learning Models For Spacecraft

Programme Reference

21-D-S-OPS-02-e

Status

Closed

Country

Canada

Start Date

2022

End Date

2022

Programme: Discovery Prime Contractor: Mission Control Space Services

Description

In this activity, Mission Control Space Services deployed a low-level implementation of the OPS-SAT SmartCam model using a Field Programmable Gate Array (FPGA), comparing against a high-level CPU model using Tensorflow Lite. Experiments showed that the FPGA implementation reproduced the precision and accuracy of the high-level model, while running at a slower speed. Further optimisations of the FPGA are expected to close the gap in timing and unlock new methods for deploying deep learning on spacecraft.

Application domain: Generic Technologies

Technology Domain:
01 - On-board Data Subsystems
09 - Mission Operation and Ground Data Systems
Competence Domain:
03 - Avionic Architecture / DHS / OnBoard S/W / FDIR / GNC / AOCS / TT&C (E2E)
08 - Ground Data Systems / Mission Operations
Initial TRL: TRL N/A Target TRL: TRL N/A Achieved TRL: TRL N/A

Public Document:

Executive Summary
PDF
Final Presentation
PDF

A Comparative Study Of High-Level And Low-Level Implementations Of Deep Learning Models For Spacecraft