Modern space applications impose significant challenges to the design of hardware and software platforms. Beyond traditional applications such as avionics, Attitude Orbit Control, and signal/telemetry processing, new developments increasingly leverage Machine Learning models to enhance the autonomy of spacecraft. Such AI-based functional-ities promise significant advantages, but require computing power beyond what can be provided by current on-board platforms. At the same time, the challenge of technological sovereignty requires a move towards open hardware and software. To achieve these objectives, within the KDT ISOLDE project started in 2023, we propose the development of a new family of processors for AI-based applications to be deployed on board of satellites. In this paper, we showcase some examples of space applications with their requirements, and highlight the possible solutions as well as the corresponding work that will be carried out in ISOLDE, and the expected results.

RISC-V Processor Technologies for Aerospace Applications in the ISOLDE Project / Fornaciari, W.; Reghenzani, F.; Agosta, G.; Zoni, D.; Galimberti, A.; Conti, F.; Tortorella, Y.; Parisi, E.; Barchi, F.; Bartolini, A.; Acquaviva, A.; Gregori, D.; Cognetta, S.; Ciancarelli, C.; Leboffe, A.; Serri, P.; Burrello, A.; Jahier Pagliari, D.; Urgese, G.; Martina, M.; Masera, G.; Di Carlo, R.; Sciarappa, A.. - 14385:(2023), pp. 363-378. (Intervento presentato al convegno 23rd International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2023 tenutosi a Samos (GRC) nel July 2–6, 2023) [10.1007/978-3-031-46077-7_24].

RISC-V Processor Technologies for Aerospace Applications in the ISOLDE Project

Burrello A.;Jahier Pagliari D.;Urgese G.;Martina M.;Masera G.;Sciarappa A.
2023

Abstract

Modern space applications impose significant challenges to the design of hardware and software platforms. Beyond traditional applications such as avionics, Attitude Orbit Control, and signal/telemetry processing, new developments increasingly leverage Machine Learning models to enhance the autonomy of spacecraft. Such AI-based functional-ities promise significant advantages, but require computing power beyond what can be provided by current on-board platforms. At the same time, the challenge of technological sovereignty requires a move towards open hardware and software. To achieve these objectives, within the KDT ISOLDE project started in 2023, we propose the development of a new family of processors for AI-based applications to be deployed on board of satellites. In this paper, we showcase some examples of space applications with their requirements, and highlight the possible solutions as well as the corresponding work that will be carried out in ISOLDE, and the expected results.
2023
9783031460760
9783031460777
File in questo prodotto:
File Dimensione Formato  
SAMOS+2023+paper+ISOLDEpdf.pdf

non disponibili

Descrizione: Versione Editoriale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 774.89 kB
Formato Adobe PDF
774.89 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2991610