Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization

Abstract

Providing efficient and scalable specialized hardware for stochastic neural networks remains a challenge. Here, the authors propose a fast, energy-efficient and scalable stochastic dot-product circuit that may use either of two types of memory devices – metal-oxide memristors and floating-gate memories.