Behavior of stochastic circuits under severe error conditions

Abstract

Abstract Stochastic computing is an old and unconventional computing technique that is finding promising new applications in image processing and the handling of complex error-correcting codes. Stochastic circuits offer an alternative to conventional digital circuits because of their extremely small size and inherent noise tolerance. They are also well-suited to meeting the requirements of emerging nanoscale technologies where non-deterministic behavior due to manufacturing defects and soft errors cannot be ignored. Error analysis of stochastic circuits, however, has received little attention and remains a largely open problem, especially when multiple errors affecting both the data sources and the stochastic circuits can occur in the course of a computation. This paper attempts to analyze stochastic circuits under various error conditions, and to compare their behavior to that of conventional circuits under similar error conditions. We use probabilistic transfer matrices for this analysis, complemented by circuit simulation. Our results indicate that stochastic circuits provide significantly better error tolerance under severe error conditions.