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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

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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