Probability‐Distribution‐Configurable True Random Number Generators Based on Spin‐Orbit Torque Magnetic Tunnel Junctions

Abstract

Abstract The incorporation of randomness into stochastic computing can provide ample opportunities for applications such as simulated annealing, non‐polynomial hard problem solving, and Bayesian neuron networks. In these cases, a considerable number of random numbers with an accurate and configurable probability distribution function (PDF) are indispensable. Preferably, these random numbers are provided at the hardware level to improve speed, efficiency, and parallelism. In this paper, how spin‐orbit torque magnetic tunnel junctions (SOT‐MTJs) with high barriers are suitable candidates for the desired true random number generators is demonstrated. Not only do these SOT‐MTJs perform excellently in speed and endurance, but their randomness can also be conveniently and precisely controlled by a writing voltage, which makes them a well‐performed Bernoulli bit. By utilizing these SOT‐MTJ‐based Bernoulli bits, any PDF, including Gaussian, uniform, exponential, Chi‐square, and even arbitrarily defined distributions can be realized. These PDF‐configurable true random number generators can then promise to advance the development of stochastic computing and broaden the applications of the SOT‐MTJs.

Keywords

• bayesian network
• magnetic tunnel junctions
• spin‐orbit torque
• true random number generator