Zhang Yi, Deng Yi, Lin Yinan, Jiang Yang, Dong Yujiao, Chen Xi, Wang Guangyi, Shang Dashan, Wang Qing, Yu Hongyu, Wang Zhongrui
Faculty of Engineering, The University of Hong Kong, Hong Kong 999077, China.
School of Microelectronics, Southern University of Science and Technology, Shenzhen 518055, China.
Micromachines (Basel). 2022 Jun 27;13(7):1016. doi: 10.3390/mi13071016.
With the slowdown of Moore's law, many emerging electronic devices and computing architectures have been proposed to sustain the performance advancement of computing. Among them, the Ising machine is a non-von-Neumann solver that has received wide attention in recent years. It is capable of solving intractable combinatorial optimization (CO) problems, which are difficult to be solve using conventional digital computers. In fact, many CO problems can be mapped to finding the corresponding ground states of Ising model. At present, Ising machine prototypes based on different physical principles, such as emerging memristive oscillators, have been demonstrated, among which the Ising Hamiltonian solver based on the coupled oscillator network simultaneously holds the advantages of room-temperature operation, compact footprint, low power consumption, and fast speed to solution. This paper comprehensively surveys the recent developments in this important field, including the types of oscillators, the implementation principle of the Ising model, and the solver's performance. Finally, methods to further improve the performance have also been suggested.
随着摩尔定律的放缓,人们提出了许多新兴电子设备和计算架构,以维持计算性能的提升。其中,伊辛机是一种非冯·诺依曼求解器,近年来受到了广泛关注。它能够解决传统数字计算机难以解决的棘手组合优化(CO)问题。事实上,许多CO问题都可以映射到寻找伊辛模型的相应基态。目前,基于不同物理原理的伊辛机原型已经得到了验证,比如新兴的忆阻振荡器,其中基于耦合振荡器网络的伊辛哈密顿量求解器同时具备室温运行、占地面积小、功耗低和求解速度快等优点。本文全面综述了这一重要领域的最新进展,包括振荡器的类型、伊辛模型的实现原理以及求解器的性能。最后,还提出了进一步提高性能的方法。