English

CBM-Dual: A 65-nm Fully Connected Chaotic Boltzmann Machine Processor for Dual Function Simulated Annealing and Reservoir Computing

Hardware Architecture 2026-04-09 v1 Machine Learning

Abstract

This paper presents CBM-Dual, the first silicon-proven digital chaotic dynamics processor (CDP) supporting both simulated annealing (SA) and reservoir computing (RC). CBM-Dual enables real-time decision-making and lightweight adaptation for autonomous Edge AI, employing the largest-scale fully connected 1024-neuron chaotic Boltzmann machine (CBM). To address the high computational and area costs of digital CDPs, we propose: 1) a CBM-specific scheduler that exploits an inherently low neuron flip rate to reduce multiply-accumulate operations by 99%, and 2) an efficient multiply splitting scheme that reduces the area by 59%. Fabricated in 65nm (12mm2^2), CBM-Dual achieves simultaneous heterogeneous task execution and state-of-the-art energy efficiency, delivering ×\times25-54 and ×\times4.5 improvements in the SA and RC fields, respectively.

Keywords

Cite

@article{arxiv.2604.06808,
  title  = {CBM-Dual: A 65-nm Fully Connected Chaotic Boltzmann Machine Processor for Dual Function Simulated Annealing and Reservoir Computing},
  author = {Kanta Yoshioka and Soshi Hirayae and Yuichiro Tanaka and Yuichi Katori and Takashi Morie and Hakaru Tamukoh},
  journal= {arXiv preprint arXiv:2604.06808},
  year   = {2026}
}

Comments

3 pages, 9 figures