Time Division Multiplexing Ising Computer Using Single Tunable True Random Number Generator Based on Spin Torque Nano-Oscillator

TL;DR

This paper introduces a novel TDM Ising computer utilizing a single spin torque nano-oscillator-based true random number generator to efficiently solve NP-hard optimization problems with high accuracy.

Contribution

It presents the first TDM Ising computer using a single tunable STNO-based TRNG as a P-Bit, enabling efficient combinational optimization with a simplified hardware design.

Findings

Achieved 87% accuracy in integer factorization.

Demonstrated high-fidelity logic gates (NOT, XOR) using the proposed P-Bit.

Reused the TRNG as a P-Bit array via time division multiplexing.

Abstract

Ising computer is a powerful computation scheme to deal with NP-hard optimization problems that cannot be efficiently addressed by conventional computers. A robust probabilistic bit (P-Bit) which is realized by a hardware entity fluctuating in time between -1 and 1 plays a key role in the success of Ising computer. Spintronics technology, such as stochastic nanomagnet, is recently proposed as a good platform for the hardware emulation of P-Bit. Here, we report, for the first time, a Time Division Multiplexing (TDM) Ising computer using single tunable true random number generator which is comprised of a Spin Torque Nano-Oscillator (STNO). First, the intrinsic frequency fluctuation of the STNO is utilized to design a simple digital true random number generator (TRNG). The true random number generator is further evolved into a tunable random number generator to act as a P-Bit. Second, in order to accomplish combinational optimization with our proposed P-Bit under Ising model, a novel incremental coupling rule is proposed. With such coupling rule between P-Bit array, high fidelity NOT and XOR logic gate is demonstrated. Third, it is proposed that our digital TRNG can be simply reused acting as a P-Bit array by time division multiplexing. The whole Ising computer can be implemented by one single STNO, and integer factorization of as high as 87% accuracy rate is achieved.