Abstract
This article investigates 14-MeV neutron radiation soft-error effects on two contrasting hardware architectures for edge computing systems, one based on an 8-bit processor and another on a 64-bit processor, both processing three frequently used types of tiny machine learning (ML) algorithms. Experimental results of 14-MeV neutron radiation tests in the different case-study ML algorithms running on the 64-bit processor show that the artificial neural network version using floating point failed more than the other versions, although most failure situations caused no misclassification in the ML inference. Furthermore, considering tiny ML applications demanding the investigated 8-bit and 64-bit computing systems for the same amount of ML inferences, the overall results suggest a preliminary trend that both case-study systems would have similar tolerance to 14-MeV neutron radiation soft errors.
Published Version
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