A 1,968-node coupled ring oscillator circuit for combinatorial optimization problem solving

Computational architectures that are optimized to solve non-deterministic polynomial-time hard or complete problems are of use in the development of machine learning, logistical planning and pathfinding. A range of quantum-, optical- and spintronic-based approaches have been explored for solving such combinatorial optimization problems, but they remain complicated to build and to scale. Here we report a scalable ring-oscillator-based integrated circuit for optimization problem solving. Our 1,968-node King's graph ring oscillator array has five levels of coupling strengths and can achieve up to 95% accuracy for randomly generated combinatorial optimization problems. The measured average power consumption of the Ising chip is 0.042 W and it takes less than 50 oscillation cycles to resolve to the ground state. Our device is resilient to environmental and variation effects. By using a multi-phase phase measurement circuit, we also capture the true phase behaviour within a coupled-oscillator integrated circuit. A coupled ring-oscillator-based integrated circuit with 1,968 nodes can be used to efficiently solve combinatorial optimization problems with an accuracy of up to 95%.

Automated summary

This article presents a scalable ring-oscillator-based integrated circuit that can be used to solve optimization problems with high accuracy. The device is resilient to environmental and variation effects.