SEE-MCAM: Scalable Multi-Bit FeFET Content Addressable Memories for Energy Efficient Associative Search

Author:

Shou Shengxi1,Liu Che-Kai2,Yun Sanggeon3,Wan Zishen2,Ni Kai4,Imani Mohsen3,Hu X. Sharon5,Yang Jianyi6,Zhuo Cheng6,Yin Xunzhao1

Affiliation:

1. College of Information Science and Electronic Engineering, Zhejiang University,China

2. School of Electrical and Computer Engineering, Georgia Institute of Technology,USA

3. University of California Irvine,Department of Information and Computer Science,USA

4. Rochester Institute of Technology,Department of Electrical and Microelectronic Engineering,USA

5. University of Notre Dame,Department of Computer Science and Engineering,USA

6. School of Micro-Nano Electronics. Zhejiang University,China

Publisher

IEEE

Reference41 articles.

1. 1mb 0.41µm22t2r cell nonvolatile team with two-bit encoding and clocked self-referenced sensing;li;IEEE JSSC,2013

2. Achieving software-equivalent accuracy for hyperdimensional computing with ferroelectric-based in-memory computing;kazemi;Scientific Reports,2022

3. A 3T1R Nonvolatile TCAM Using MLC ReRAM for Frequent-Off Instant-On Filters in IoT and Big-Data Processing

4. An ultra-dense 2fefet team design based on a multi -domain fefet model;yin;IEEE Transactions on Circuits and Systems II Express Briefs,2018

5. Analog content-addressable memories with memristors

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