CBM-Dual: A 65-nm Fully Connected Chaotic Boltzmann Machine Processor for Dual Function Simulated Annealing and Reservoir Computing
Kanta Yoshioka, Soshi Hirayae, Yuichiro Tanaka, Yuichi Katori, Takashi Morie, Hakaru Tamukoh

TL;DR
CBM-Dual is a 65nm silicon processor supporting chaotic Boltzmann machine-based simulated annealing and reservoir computing, enabling efficient real-time autonomous Edge AI with significant computational and area savings.
Contribution
First silicon-proven digital chaotic processor supporting both SA and RC with innovative scheduling and area reduction schemes.
Findings
Reduces multiply-accumulate operations by 99%
Decreases area by 59%
Achieves 25-54x energy efficiency improvements
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 (12mm), CBM-Dual achieves simultaneous heterogeneous task execution and state-of-the-art energy efficiency, delivering 25-54 and 4.5 improvements in the SA and RC fields, respectively.
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