E-NPU: A 34~126nJ/Class Event-Driven Adaptive Neural SoC with Signal-Dynamics-Aware Feature Clustering and Multi-Model In-Memory Inference/Training for Personalized Medical Wearables

Fengshi Tian, Jinbo Chen, Kunming Shao, Zilu Liu, Jiakun Zheng, Hui Wu, Chaoming Fang, Xiaomeng Wang, Ziyang Shen, Pingcheng Dong, Yuan Yao, Xuliang Wang, Jie Yang, Mohamad Sawan, Chi-Ying Tsui, Kwang-Ting Cheng

CICC 2025IEEE Custom Integrated Circuits Conference (CICC)Co-first author

Paper

This paper presents an event-driven adaptive neural SoC with signal-dynamics-aware feature clustering and multi-model in-memory inference/training for personalized medical wearables.

Citation

Fengshi Tian, Jinbo Chen, Kunming Shao, Zilu Liu, Jiakun Zheng, Hui Wu, Chaoming Fang, Xiaomeng Wang, Ziyang Shen, Pingcheng Dong, Yuan Yao, Xuliang Wang, Jie Yang, Mohamad Sawan, Chi-Ying Tsui, and Kwang-Ting Cheng. E-NPU: A 34~126nJ/Class Event-Driven Adaptive Neural SoC with Signal-Dynamics-Aware Feature Clustering and Multi-Model In-Memory Inference/Training for Personalized Medical Wearables. In 2025 IEEE Custom Integrated Circuits Conference (CICC), pages 1-3. IEEE, 2025.