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The next-generation of partially and fully autonomous cars will be powered by embedded many-core platforms. Technologies for Advanced Driver Assistance Systems (ADAS) need to process an unprecedented amount of data within tight power budgets, making those platform the ideal candidate architecture. Integrating tens-to-hundreds of computing elements that run at lower frequencies allows obtaining impressive performance capabilities at a reduced power consumption, that meets the size, weight and power (SWaP) budget of automotive systems. Unfortunately, the inherent architectural complexity of many-core platforms makes it almost impossible to derive real-time guarantees using “traditional” state-of-the-art techniques, ultimately preventing their adoption in real industrial settings. Having impressive average performances with no guaranteed bounds on the response times of the critical computing activities …