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An Ultra-Compact Single FeFET Binary and Multi-Bit Associative Search Engine

Authors :
Yin, Xunzhao
Müller, Franz
Huang, Qingrong
Li, Chao
Imani, Mohsen
Yang, Zeyu
Cai, Jiahao
Lederer, Maximilian
Olivo, Ricardo
Laleni, Nellie
Deng, Shan
Zhao, Zijian
Zhuo, Cheng
Kämpfe, Thomas
Ni, Kai
Publication Year :
2022
Publisher :
arXiv, 2022.

Abstract

Content addressable memory (CAM) is widely used in associative search tasks for its highly parallel pattern matching capability. To accommodate the increasingly complex and data-intensive pattern matching tasks, it is critical to keep improving the CAM density to enhance the performance and area efficiency. In this work, we demonstrate: i) a novel ultra-compact 1FeFET CAM design that enables parallel associative search and in-memory hamming distance calculation; ii) a multi-bit CAM for exact search using the same CAM cell; iii) compact device designs that integrate the series resistor current limiter into the intrinsic FeFET structure to turn the 1FeFET1R into an effective 1FeFET cell; iv) a successful 2-step search operation and a sufficient sensing margin of the proposed binary and multi-bit 1FeFET1R CAM array with sizes of practical interests in both experiments and simulations, given the existing unoptimized FeFET device variation; v) 89.9x speedup and 66.5x energy efficiency improvement over the state-of-the art alignment tools on GPU in accelerating genome pattern matching applications through the hyperdimensional computing paradigm.<br />Comment: 20 pages, 14 figures

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....8ca77df66999737d2439bb54df2695fe
Full Text :
https://doi.org/10.48550/arxiv.2203.07948