An unconventional computing technique for ultra-fast and ultra-low power data mining

Abstract

In this work we review the basic principles of stochastic logic and propose its application to probabilistic-based pattern-recognition analysis. The proposed technique is the implementation of a parallel comparison of data with respect to various pre-stored categories. We design smart pulse-based stochastic-logic blocks to provide an efficient pattern recognition analysis. The proposed architecture can speed-up the screening process of huge databases by two orders of magnitude with respect classical software-based solutions, thus implying a great improvement in terms of total performance (speed and power dissipation).