Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 310-317 |
| Number of pages | 8 |
| Journal | Nature Electronics |
| Volume | 5 |
| Issue number | 5 |
| DOIs | |
| State | Published - May 2022 |
Bibliographical note
Funding Information:I.A. and C.H.K. acknowledges the initial support of the project from the National Science Foundation under ECCS 1739635 and the Semiconductor Research Corporation (SRC) under 2759.007. For the chip testing and data analysis works, W.M. and C.H.K. have been supported in part by the SRC under 3024.001. We would like to thank SRC’s industry liaisons for their technical feedback.
Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature Limited.