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UID:pretalx-eu-summit-2026-XXQJQF@cfp.riscv-europe.org
DTSTART;TZID=CET:20260610T105000
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DESCRIPTION:Integrating AI-based capabilities into satellites improves spac
 ecraft autonomy\, but poses considerable obstacles in designing the hardwa
 re and software ecosystem. \nThe orbit-dependent generation of power with 
 solar cells\, the limited thermal dissipation and weight present significa
 nt challenges in designing a compute platform capable of edge inference\, 
 forcing the trade-off between high-performance for complex AI models and s
 trict power/area budget. \nMoreover\, AI models must share the same resour
 ces of traditional algorithm that are executed onboard concurrently with t
 he inference\, such as avionics\, attitude orbit control\, data handling a
 nd signal processing. \nHowever\, benefits of onboard processing comprise 
 secure and private computation\, decreased data uplink/downlink demands\, 
 autonomous detection and resolution of anomalies\, enabling autonomous spa
 cecraft operation.\nTherefore\, it is necessary to adapt a hardware-aware 
 codesign approach in designing software components to implement energy-eff
 icient and secure edge inference without decreasing the performance of tra
 ditional applications. \nThe ISOLDE space demonstrator comprises several R
 ISC-V cores and accelerators\, and its hardware architecture and software 
 ecosystem are presented\, with a particular focus on the interactions of s
 everal open-source and open-hardware IPs developed by various academic and
  industry European partners.
DTSTAMP:20260522T163243Z
LOCATION:Poster Island C
SUMMARY:The ISOLDE Space Demonstrator: a RISC-V Ecosystem for Low-Power On-
 board Inference - Emanuele Valpreda\, Davide Di Ienno\, Mattia Paladino
URL:https://cfp.riscv-europe.org/eu-summit-2026/talk/XXQJQF/
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