We introduce a new method for hardware nonuniform random number generation based on the transfer characteristics of graphene field-effect transistors (GFETs) which requires as few as two transistors and a resistor. We implement the method by fabricating multiple GFETs and experimentally validating that their transfer characteristics exhibit the nonlinearity on which our method depends. We use characterisation data in simulations of a proposed architecture for generating samples from dynamically selectable non-uniform probability distributions. The method we present has the potential for Gb/s sample rates, is reconfigurable for arbitrary target distributions, and has a wide range of possible applications. Using a combination of experimental measurements of GFETs under a range of biasing conditions and simulation of the GFET-based non-uniform random variate generator, we demonstrate a speedup of Monte Carlo integration by up to 2×. This speedup assumes the analogue-to-digital converters reading the outputs from the circuit can produce samples in the same amount of time that it takes to perform memory accesses.
N. J. Tye, J. T. Meech, B. A. Bilgin and P. Stanley-Marbell, "A System for Generating Non-Uniform Random Variates using Graphene Field-Effect Transistors," 2020 IEEE 31st International Conference on Application-specific Systems, Architectures and Processors (ASAP), Manchester, United Kingdom, 2020, pp. 101-108, doi: 10.1109/ASAP49362.2020.00026.