On the Robustness of Stochastic Bayesian Machines

Coelho, Alexandre; Laurent, Raphael; Solinas, Miguel; Fraire, Juan; Mazer, Emmanuel; Zergainoh, Nacer-Eddine; Karaoui, Said; Velazco, Raoul

Abstract

This paper 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 register transfer level provide the first evidences of the intrinsic robustness of SBMs with respect to single event upsets and single event transients.

Más información

Título según WOS: ID WOS:000411034700035 Not found in local WOS DB
Título de la Revista: IEEE TRANSACTIONS ON NUCLEAR SCIENCE
Volumen: 64
Número: 8
Editorial: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Fecha de publicación: 2017
Página de inicio: 2276
Página final: 2283
DOI:

10.1109/TNS.2017.2678204

Notas: ISI