TY - GEN
T1 - ICCAD Tutorial Session Paper Ferroelectric FET Technology and Applications
T2 - 40th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2021
AU - Amrouch, Hussam
AU - Gao, Di
AU - Hu, Xiaobo Sharon
AU - Kazemi, Arman
AU - Laguna, Ann Franchesca
AU - Ni, Kai
AU - Niemier, Michael
AU - Sharifi, Mohammad Mehdi
AU - Thomann, Simon
AU - Yin, Xunzhao
AU - Zhuo, Cheng
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - The rapidly increasing volume and complexity of data is demanding the relentless scaling of computing power. With transistor feature size approaching physical limits, the benefits that CMOS technology can provide is diminishing. For future energy efficient computing systems, researchers aim to exploit various emerging nanotechnologies to replace conventional CMOS technology. In particular, ferroelectric FETs (FeFETs) appear to be a promising candidate to continue improving energy efficiency for data-intensive applications. Advances in FeFET scalability and FeFET compatibility with CMOS have sparked growing interest in device, circuit, and system communities. While FeFET is still evolving, many researchers and developers are already cautiously optimistic about its future. This paper provides a review on FeFET’s recent technology advances, challenges, and opportunities, with a particular emphasis upon device modeling and circuit design of FeFET content addressable memory, as well as their applications in machine learning.
AB - The rapidly increasing volume and complexity of data is demanding the relentless scaling of computing power. With transistor feature size approaching physical limits, the benefits that CMOS technology can provide is diminishing. For future energy efficient computing systems, researchers aim to exploit various emerging nanotechnologies to replace conventional CMOS technology. In particular, ferroelectric FETs (FeFETs) appear to be a promising candidate to continue improving energy efficiency for data-intensive applications. Advances in FeFET scalability and FeFET compatibility with CMOS have sparked growing interest in device, circuit, and system communities. While FeFET is still evolving, many researchers and developers are already cautiously optimistic about its future. This paper provides a review on FeFET’s recent technology advances, challenges, and opportunities, with a particular emphasis upon device modeling and circuit design of FeFET content addressable memory, as well as their applications in machine learning.
UR - http://www.scopus.com/inward/record.url?scp=85124154846&partnerID=8YFLogxK
U2 - 10.1109/ICCAD51958.2021.9643578
DO - 10.1109/ICCAD51958.2021.9643578
M3 - Conference contribution
AN - SCOPUS:85124154846
T3 - IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
BT - 2021 40th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2021 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 1 November 2021 through 4 November 2021
ER -
