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  4. A FeFET-based Time-Domain Associative Memory for Multi-bit Similarity Computation
 
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2024
Conference Paper
Title

A FeFET-based Time-Domain Associative Memory for Multi-bit Similarity Computation

Abstract
The exponential growth of data across various domains of human society necessitates the rapid and efficient data processing. In many contemporary data-intensive applications, similarity computation (SC) is one of the most fundamental and indispensable operations. In recent years, In-memory computing (IMC) architectures have been designed to accelerate SC by reducing data movement costs, however, they encounter challenges with signal domain conversion, variation sensitivity, and limited precision. This paper proposes a ferroelectric FET (FeFET) based time-domain (TD) associative memory (AM) for energy efficient SC. Such TD design can convert its output (i.e., time interval) to digits with relatively simple sensing circuitry thus saves large amount of area and energy compared with conventional IMC designs that process analog voltage/current signals. The variable-capacitance (VC) delay chain structure in our design supports quantitative SC and enhances robustness against variations. Furthermore, by exploiting multi-domain ferroelctric FET (FeFET), our design is capable of performing SC on vectors with multi-bit element, enabling support for higher-precision algorithms. Simulation results show that the proposed TD-AM achieves 13.8x/1.47x energy saving of our design compared to CMOS/NVM based TD-IMC designs. Additionally, our design exhibits good robustness in monte carlo simulation with variation extracted from experimental measurements. Investigation on precision of hyperdimensional computing (HDC) show that higher element precision reduces the size of HDC model when considering to achieve same accuracy, indicating an improved efficiency. Benchmarkings against GPU demonstrate in general 2/3 orders of magnitude speedup/energy efficiency improvement of our design. Our proposed multi-bit TD-AM promises energy-efficient quantitative SC for diverse intensive data processing application, especially in energy-constrained scenarios.
Author(s)
Huang, Qingrong
Zhejiang University
Errahmouni Barkam, Hamza
University of California, Irvine
Yang, Zeyu
Zhejiang University
Yang, Jianyi
Zhejiang University
Kämpfe, Thomas  orcid-logo
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
Ni, Kai
University of Notre Dame
Zhang, Grace Li
Technische Universität Darmstadt
Li, Bing
Technische Universität München
Schlichtmann, Ulf
Technische Universität München
Imani, Mohsen
University of California, Irvine
Zhuo, Cheng
Zhejiang University
Yin, Xunzhao
Zhejiang University
Mainwork
Proceedings Design Automation and Test in Europe Date
Funder
National Natural Science Foundation of China  
Conference
2024 Design, Automation and Test in Europe Conference and Exhibition, DATE 2024
Language
English
Fraunhofer-Institut für Photonische Mikrosysteme IPMS  
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