Hapka, RobinRobinHapkaChristmann, AnikaAnikaChristmannErnst, RolfRolfErnstKuzolap, AlexanderAlexanderKuzolapHecker, PeterPeterHeckerRockschies, MariusMariusRockschiesHalle, MartinMartinHalleThielecke, FrankFrankThielecke2023-12-142023-12-14202342nd IEEE/AIAA Digital Avionics Systems Conference (DASC 2023)https://hdl.handle.net/11420/44618While the European Union Aviation Safety Agency pushes towards artificial intelligence and neural networks, their introduction is still prevented by a lack of reliable high-performance platforms. This paper addresses this gap by adopting the novel Timing Diversity approach from the real-time community and adapting it to the avionics domain to achieve a reliable and safe timing behavior on system-level. Timing Diversity provides a safety net to handle unexpected timing outliers of multi-core processors by exploiting existing modular redundancy. The system design is illustrated using a neural network-based runway detection, deploying different multi-core hardware and diverse software algorithms. Furthermore, error handling and compliance to current acceptable means according to AMC 20-193 are discussed.enmodular redundancymulti-core processorsneural networkreal-timetiming diversityMLE@TUHHCivil Engineering, Environmental EngineeringSafe usage of multi-cores in neural network avionics applicationsConference Paper10.1109/DASC58513.2023.10311131Conference Paper