On the robustness of stochastic bayesian machines

Abstract

This work revisits the stochastic computing paradigm as a way to implement architectures dedicated to probabilistic inference. In general, it is assumed the operation over stochastic bit streams is robust with respect to radiation transient events effects. Moreover, it can be expected that leveraging the stochastic computing paradigm to implement probabilistic computations such as Bayesian inference implemented in hardware, could yield an increased resilience to radiation effects comparatively to deterministic procedures. However, the practical assessment of the robustness against radiation is mandatory before considering Stochastic Bayesian Machines (SBMs) in hazardous environments. Results of fault injection campaigns at RTL level provide the first evidences of the intrinsic robustness of SBMs with respect to SEUs and SETs.