1. An Ultra-Compact Single FeFET Binary and Multi-Bit Associative Search Engine
- Author
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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, and Ni, Kai
- Subjects
Signal Processing (eess.SP) ,FOS: Computer and information sciences ,Emerging Technologies (cs.ET) ,FOS: Electrical engineering, electronic engineering, information engineering ,Computer Science - Emerging Technologies ,Electrical Engineering and Systems Science - Signal Processing - 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., Comment: 20 pages, 14 figures
- Published
- 2022
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