An Ultracompact Single‐Ferroelectric Field‐Effect Transistor Binary and Multibit Associative Search Engine

Author:

Yin Xunzhao1ORCID,Müller Franz2,Huang Qingrong1,Li Chao1,Imani Mohsen3,Yang Zeyu1,Cai Jiahao1,Lederer Maximilian2,Olivo Ricardo2,Laleni Nellie2,Deng Shan4,Zhao Zijian4,Shi Zhiguo1,Shi Yiyu5,Zhuo Cheng6,Kämpfe Thomas2,Ni Kai4

Affiliation:

1. College of Information Science and Electronic Engineering Zhejiang University Hangzhou 310027 China

2. IPMS Fraunhofer Center Nanoelectronic Technologies 01109 Dresden Germany

3. Department of Computer Science University of California Irvine Irvine 92697 USA

4. Department of Electrical and Microelectronic Engineering Rochester Institute of Technology Rochester 14623 USA

5. Department of Computer Science and Engineering University of Notre Dame Notre Dame 46556 USA

6. School of Micro‐Nano Electronics Zhejiang University ZJU‐Hangzhou Global Scientific and Technological Innovation Center Hangzhou 311200 China

Abstract

Content addressable memory (CAM) is widely used in associative search tasks due to its parallel pattern matching capability. As more complex and data‐intensive tasks emerge, it is becoming increasingly important to enhance CAM density for improved performance and better area efficiency. To reduce the area overheads, various nonvolatile memory (NVM) devices, such as ferroelectric field‐effect transistors (FeFETs), are used in CAM design. Herein, a novel ultracompact 1FeFET CAM design that enables parallel associative search and in‐memory hamming distance calculation is used, as well as a multibit CAM for exact search using the same CAM cell. The proposed CAM design leverages the 1FeFET1R structure, and compact device designs that integrate the series resistor current limiter into the intrinsic FeFET structure are demonstrated to turn the 1FeFET1R structure into an effective 1FeFET cell. A two‐step search operation of the proposed binary and multibit 1FeFET CAM array through both experiments and simulations is proposed, showing a sufficient sensing margin despite unoptimized FeFET device variation. In genome pattern matching applications, using the hyperdimensional computing paradigm, the design results in a 89.9× speedup and 66.5× improvement in energy efficiency over the state‐of‐the‐art alignment tools on GPU.

Publisher

Wiley

Subject

General Medicine

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