A 2-Transistor-2-Capacitor Ferroelectric Edge Compute-in-Memory Scheme with Disturb-Free Inference and High Endurance

Xiaoyang Ma, Shan Deng, Juejian Wu, Zijian Zhao, David Lehninger, Tarek Ali, Konrad Seidel, Sourav De, Xiyu He, Yiming Chen, Huazhong Yang, Vijaykrishnan Narayanan, Suman Datta, Thomas Kampfe, Qing Luo, Kai Ni, Xueqing Li

Research output: Contribution to journalArticlepeer-review

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Abstract

This letter proposes C2FeRAM, a 2T2C/cell ferroelectric compute-in-memory (CiM) scheme for energy-efficient and high-reliability edge inference and transfer learning. With certain area overhead, C2FeRAM achieves the following highlights: (i) compared with FeFET/FeMFET, it achieves disturb-free CiM and much higher write endurance (equal to FeRAM), leading to 100× inference time with < 1% accuracy drop for VGG8 in CIFAR-10 dataset, along with the enhanced endurance for weight updates, e.g., CiM-based transfer learning; (ii) compared with 1T1C FeRAM inference cache, the achieved disturb-free feature and CiM capability in C2FeRAM lead to improvements of 4× energy, 200× speed, and 3.2e 5× life cycles. Such benefits highlight an intriguing solution for future intelligent edge AI.

Original languageEnglish (US)
Pages (from-to)1088-1091
Number of pages4
JournalIEEE Electron Device Letters
Volume44
Issue number7
DOIs
StatePublished - Jul 1 2023

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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