Computing-in-Memory with Ferroelectric Materials and Beyond

研究成果: Conference contribution

摘要

Recent discovery of hafnium-based ferroelectric (FE) materials opens up numerous CMOS-compatible memory device opportunities: FE capacitors, FE-FETs, and FE tunnel junctions. These devices offer significant advantages in endurance, write speed, and power compared to today's flash. In this paper, we give a brief overview of FE materials/devices fundamentals, and its applicability towards computing-in-memory (CIM). We discuss CIM realized using FE-FinFET arrays with various possible configurations. Alternatively, FE capacitors in CMOS backend may be used in non-volatile SRAM cells to store contents of CIM-SRAM before powering off. We also present CIMulator, a simulation platform to account for device, circuit, and neural network aspects CIM macros with deep machine learning applications.

原文English
主出版物標題2023 International VLSI Symposium on Technology, Systems and Applications, VLSI-TSA/VLSI-DAT 2023 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9798350334166
DOIs
出版狀態Published - 2023
事件2023 International VLSI Symposium on Technology, Systems and Applications, VLSI-TSA/VLSI-DAT 2023 - Hsinchu, Taiwan
持續時間: 2023 4月 172023 4月 20

出版系列

名字2023 International VLSI Symposium on Technology, Systems and Applications, VLSI-TSA/VLSI-DAT 2023 - Proceedings

Conference

Conference2023 International VLSI Symposium on Technology, Systems and Applications, VLSI-TSA/VLSI-DAT 2023
國家/地區Taiwan
城市Hsinchu
期間23-04-1723-04-20

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 電腦科學應用
  • 硬體和架構
  • 資訊系統
  • 電氣與電子工程

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