← 返回 JSSC 论文列表JSSC 2023第7期Memory180-nm
Dual-Mode Operations of Self-Rectifying Ferroelectric Tunnel Junction Crosspoint Array for High-Density Integration of IoT Devices
提出自整流铁电隧道结交叉阵列,实现双模式操作(TCAM/BCAM/PUF),具有超高密度和低能耗。
2.05 fJ/search/bit, Hamming weight of 0.5000, >84.2% area reduction
自整流铁电隧道结交叉阵列双模式操作内容可寻址存储器物理不可克隆函数
▸自整流铁电隧道结(SR-FTJ)交叉阵列设计
▸双模式操作(TCAM/BCAM/PUF)
▸超高密度和低搜索能耗
Abstract
This study proposes a self-rectifying ferroelectric tunnel junction (SR-FTJ) crosspoint array to satisfy the stringent size requirements of the Internet-of-Things devices. Each cell in the SR-FTJ crosspoint array consists of two SR-FTJs stacked vertically, resulting in ultrahigh density. The SR-FTJ crosspoint array can operate as: 1) ternary content-addressable memory (TCAM) or 2) binary content addressable memory (BCAM) or physically unclonable function (PUF) in the dual-mode operation. In the dual-mode operation, the amount of the current flowing through the SR-FTJs remains the same, resulting in a stable PUF response regardless of the BCAM data. The dual-mode operation of the SR-FTJ crosspoint array is experimentally verified by 4-in wafer-level demonstrations. HSPICE simulation results using the industrial-compatible 180-nm technology with the SR-FTJ model reflecting measured characteristics show that the SR-FTJ crosspoint array achieves the lowest search energy (2.05 fJ/search/bit) and the highest randomness (Hamming weight of 0.5000) among the previous content addressable memories (CAMs) and PUFs. In addition, the SR-FTJ crosspoint array reduces area by >84.2% compared to the previous structures that implement individual CAM and PUF.