TY - GEN
T1 - On the reliability of in-memory computing
T2 - 39th IEEE VLSI Test Symposium, VTS 2021
AU - Thomann, Simon
AU - Li, Chao
AU - Zhuo, Cheng
AU - Prakash, Om
AU - Yin, Xunzhao
AU - Hu, Xiaobo Sharon
AU - Amrouch, Hussam
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/4/25
Y1 - 2021/4/25
N2 - With the rapid development of emerging technologies, especially the ferroelectric field-effect transistors (FeFETs), the density and energy efficiency of ternary content addressable memory (TCAM) have been increasingly improved. TCAM plays a major role in realizing In-Memory Computing and other brain-inspired computing concepts. Recently, the parallel search functionality of a FeFET based ultra-dense TCAM design is also enhanced with a Hamming distance-based approximate search scheme. However, in order to realize the highly-promising TCAM design, in which the approximate search function based on Hamming distance is implemented, it is inevitable to investigate the impact of temperature on the reliability of FeFET-based TCAM cells as well as all involved peripheral circuits. In this paper, the temperature impact on the FeFET at the device level and the approximate TCAM design at the circuit level is investigated for the first time. The demonstrated example of a FeFET-based TCAM array shows that the unique temperature dependency of a FeFET device can help mitigate the temperature impact on the FeFET TCAM array. Based on the observation, we showcase, evaluate, and discuss in detail one strategy to eliminate the temperature impact on the approximate TCAM design. Understanding and mitigating the deleterious impact of temperature on the reliability of FeFET-based TCAM circuits is essential to ensure reliable In-Memory Computing.
AB - With the rapid development of emerging technologies, especially the ferroelectric field-effect transistors (FeFETs), the density and energy efficiency of ternary content addressable memory (TCAM) have been increasingly improved. TCAM plays a major role in realizing In-Memory Computing and other brain-inspired computing concepts. Recently, the parallel search functionality of a FeFET based ultra-dense TCAM design is also enhanced with a Hamming distance-based approximate search scheme. However, in order to realize the highly-promising TCAM design, in which the approximate search function based on Hamming distance is implemented, it is inevitable to investigate the impact of temperature on the reliability of FeFET-based TCAM cells as well as all involved peripheral circuits. In this paper, the temperature impact on the FeFET at the device level and the approximate TCAM design at the circuit level is investigated for the first time. The demonstrated example of a FeFET-based TCAM array shows that the unique temperature dependency of a FeFET device can help mitigate the temperature impact on the FeFET TCAM array. Based on the observation, we showcase, evaluate, and discuss in detail one strategy to eliminate the temperature impact on the approximate TCAM design. Understanding and mitigating the deleterious impact of temperature on the reliability of FeFET-based TCAM circuits is essential to ensure reliable In-Memory Computing.
KW - Emerging Technology
KW - FeFET
KW - In-Memory Computing
KW - Reliability
KW - TCAM
KW - Temperature
UR - http://www.scopus.com/inward/record.url?scp=85107497573&partnerID=8YFLogxK
U2 - 10.1109/VTS50974.2021.9441038
DO - 10.1109/VTS50974.2021.9441038
M3 - Conference contribution
AN - SCOPUS:85107497573
T3 - Proceedings of the IEEE VLSI Test Symposium
BT - Proceedings - 2021 IEEE 39th VLSI Test Symposium, VTS 2021
PB - IEEE Computer Society
Y2 - 26 April 2021 through 28 April 2021
ER -
