133 citations · 247 across the 6 of their papers we have counts for
6 papers
ASCH-PUF: A "Zero" Bit Error Rate CMOS Physically Unclonable Function with Dual-Mode Low-Cost Stabilization
Yan He, Dai Li, Zhanghao Yu +1
Physically unclonable functions (PUFs) are increasingly adopted for low-cost and secure secret key and chip ID generations for embedded and IoT devices. Achieving 100% reproducible…
MeNTT: A Compact and Efficient Processing-in-Memory Number Theoretic Transform (NTT) Accelerator
Dai Li, Akhil Pakala, Kaiyuan Yang
Lattice-based cryptography (LBC) exploiting Learning with Errors (LWE) problems is a promising candidate for post-quantum cryptography. Number theoretic transform (NTT) is the late…
Training BatchNorm Only in Neural Architecture Search and Beyond
Yichen Zhu, Jie Du, Yuqin Zhu +4
This work investigates the usage of batch normalization in neural architecture search (NAS). Specifically, Frankle et al. find that training BatchNorm only can achieve nontrivial p…
A Self-Regulated and Reconfigurable CMOS Physically Unclonable Function Featuring Zero-Overhead Stabilization
Dai Li, Kaiyuan Yang
This article presents a reconfigurable physically unclonable function (PUF) design fabricated using 65-nm CMOS technology. A subthreshold-inverter-based static PUF cell achieves 0.…
A Dual-Port 8-T CAM-Based Network Intrusion Detection Engine for IoT
Dai Li, Kaiyuan Yang
This letter presents an energy- and memory-efficient pattern-matching engine for a network intrusion detection system (NIDS) in the Internet of Things. Tightly coupled architecture…
CAP-RAM: A Charge-Domain In-Memory Computing 6T-SRAM for Accurate and Precision-Programmable CNN Inference
Zhiyu Chen, Zhanghao Yu, Qing Jin +6
A compact, accurate, and bitwidth-programmable in-memory computing (IMC) static random-access memory (SRAM) macro, named CAP-RAM, is presented for energy-efficient convolutional ne…