TY - GEN
T1 - GNN-Based INC and IVC Co-Optimization for Aging Mitigation
AU - Chen, Yu Guang
AU - Yang, Hsiu Yi
AU - Lin, Ing Chao
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - As semiconductor processes advance, circuit aging becomes prominent. One of the most severe aging effects is Negative Bias Temperature Instability (NBTI), which increases the threshold voltage and the propagation delay of PMOS transistors. To mitigate NBTI, aging mitigation methods such as Internal Node Control (INC) and Input Vector Control (IVC) have been proposed. INC applies designed logic gates, while IVC uses appropriate input patterns during circuit idle. However, INC leads to extra area overhead and power consumption, and the circuit structure limits the controllability of IVC. Although various approaches have proposed aging tolerance methods with INC or IVC, only a few of them consider co-optimization. In this paper, we introduce a GNN-based INC and IVC co-optimization framework to minimize aging-induced delay. The key concept of our framework is using GNN to identify serious-aged gates in a circuit, and then using INC and IVC to mitigate the aging effect under an area overhead constraint. The experimental results indicate that our method reduces aging-induced delay and area by 2.16 times and 29.5%, respectively, compared to previous work.
AB - As semiconductor processes advance, circuit aging becomes prominent. One of the most severe aging effects is Negative Bias Temperature Instability (NBTI), which increases the threshold voltage and the propagation delay of PMOS transistors. To mitigate NBTI, aging mitigation methods such as Internal Node Control (INC) and Input Vector Control (IVC) have been proposed. INC applies designed logic gates, while IVC uses appropriate input patterns during circuit idle. However, INC leads to extra area overhead and power consumption, and the circuit structure limits the controllability of IVC. Although various approaches have proposed aging tolerance methods with INC or IVC, only a few of them consider co-optimization. In this paper, we introduce a GNN-based INC and IVC co-optimization framework to minimize aging-induced delay. The key concept of our framework is using GNN to identify serious-aged gates in a circuit, and then using INC and IVC to mitigate the aging effect under an area overhead constraint. The experimental results indicate that our method reduces aging-induced delay and area by 2.16 times and 29.5%, respectively, compared to previous work.
KW - aging mitigation
KW - gate replacement
KW - Graph Neural Network (GNN)
KW - Input Vector Control (IVC)
KW - Internal Node Control (INC)
KW - lifetime enhancement
KW - Negative Bias Temperature Instability (NBTI)
UR - http://www.scopus.com/inward/record.url?scp=85197544916&partnerID=8YFLogxK
U2 - 10.1109/ETS61313.2024.10567322
DO - 10.1109/ETS61313.2024.10567322
M3 - 會議論文篇章
AN - SCOPUS:85197544916
T3 - Proceedings of the European Test Workshop
BT - Proceedings - 2024 29th IEEE European Test Symposium, ETS 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 29th IEEE European Test Symposium, ETS 2024
Y2 - 20 May 2024 through 24 May 2024
ER -