A technical paper titled “SEE-MCAM: Scalable Multi-bit FeFET Content Addressable Memories for Energy Efficient Associative Search” was published by researchers at Zhejiang University, China, Georgia Institute of Technology, University of California Irvine, Rochester Institute of Technology, University of Notre Dame, and Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province.
“In this work, we propose SEE-MCAM, scalable and compact multi-bit CAM (MCAM) designs that utilize the three-terminal ferroelectric FET (FeFET) as the proxy. By exploiting the multi-level-cell characteristics of FeFETs, our proposed SEE-MCAM designs enable multi-bit associative search functions and achieve better energy efficiency and performance than existing FeFET-based CAM designs. We validated the functionality of our proposed designs by achieving 3 bits per cell CAM functionality, resulting in 3x improvement in storage density. The area per bit of the proposed SEE-MCAM cell is 8% of the conventional CMOS CAM. We thoroughly investigated the scalability and robustness of the proposed design. Evaluation results suggest that the proposed 2FeFET-1T SEE-MCAM achieves 9.8x more energy efficiency and 1.6x less search latency compared to the CMOS CAM, respectively. When compared to existing MCAM designs, the proposed SEE-MCAM can achieve 8.7x and 4.9x more energy efficiency than ReRAM-based and FeFET-based MCAMs, respectively. Benchmarking results show that our approach provides up to 3 orders of magnitude improvement in speedup and energy efficiency over a GPU implementation in accelerating a novel quantized hyperdimensional computing (HDC) application.”
Find the technical paper here. Published October 2023 (preprint).
Shou, Shengxi, Che-Kai Liu, Sanggeon Yun, Zishen Wan, Kai Ni, Mohsen Imani, X. Sharon Hu, Jianyi Yang, Cheng Zhuo, and Xunzhao Yin. “SEE-MCAM: Scalable Multi-bit FeFET Content Addressable Memories for Energy Efficient Associative Search.” arXiv preprint arXiv:2310.04940 (2023).
Related Reading
Ferroelectric Memories Answer Call For Non-Volatile Alternatives
Researchers target NVMs that are compatible with CMOS logic.
ReRAM Seeks To Replace NOR
There is increased interest in ReRAM for embedded computing, especially in automotive applications, as more of its known issues are solved. Nevertheless, there is no one-size-fits-all NVM.
Leave a Reply