In this paper we characterise two embedded GPU devices from the NVIDIA Xavier family System-on-Chip (SoC) using a proton beam. We compare the NVIDIA Xavier NX and Industrial devices, that respectively target commercial and automotive applications. We evaluate the Single-Event Effect (SEE) rate of both modules and their sub-components, both the CPU and GPU, using different power modes, and we try for the first time to identify their exact sources using the on-line testing facilities included in their ARM based system. Our conclusion is that the most sensitive part of the CPU complex of the SoC is the tag array of the various cache structures, while no errors were observed in the GPU, probably because of its fast execution compared to the CPU part of the application during the radiation campaign.
Embedded systems in critical domains, such as automotive, aviation, space domains, are often required to guarantee both functional and temporal correctness. Considering transient faults, fault analysis and mitigation approaches are implemented at various levels of the system design, in order to maintain the functional correctness. However, transient faults and their mitigation methods have a timing impact, which can affect the temporal correctness of the system. In this work, we expose the functional and the timing implications of transient faults for critical systems. More precisely, we initially highlight the timing effect of transient faults occurring in the combinational and sequential logic of a processor. Furthermore, we propose a full stack vulnerability analysis that drives the design of selective hardware-based mitigation for real-time applications. Last, we study the timing impact of software-based reliability mitigation methods applied in a COTS GPU, using a fault tolerant middleware.
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