TY - GEN
T1 - A2-ILT
T2 - 59th ACM/IEEE Design Automation Conference, DAC 2022
AU - Wang, Qijing
AU - Jiang, Bentian
AU - Wong, Martin D.F.
AU - Young, Evangeline F.Y.
N1 - The work described in this paper was partially supported by a grant from the Research Grants Council of the Hong Kong Special Administrative Region, China (Project No. CUHK 14209320).
PY - 2022/7/10
Y1 - 2022/7/10
N2 - Inverse lithography technology (ILT) is one of the promising resolution enhancement techniques (RETs) in modern design-for-manufacturing closure, however, it suffers from huge computational overhead and unaffordable mask writing time. In this paper, we propose A2-ILT, a GPU-accelerated ILT framework with spatial attention mechanism. Based on the previous GPU-accelerated ILT flow, we significantly improve the ILT quality by introducing spatial attention map and on-the-fly mask rectilinearization, and strengthen the robustness by Reinforcement-Learning deployment. Experimental results show that, comparing to the state-of-the-art solutions, A2-ILT achieves 5.06% and 11.60% reduction in printing error and process variation band with a lower mask complexity and superior runtime performance.
AB - Inverse lithography technology (ILT) is one of the promising resolution enhancement techniques (RETs) in modern design-for-manufacturing closure, however, it suffers from huge computational overhead and unaffordable mask writing time. In this paper, we propose A2-ILT, a GPU-accelerated ILT framework with spatial attention mechanism. Based on the previous GPU-accelerated ILT flow, we significantly improve the ILT quality by introducing spatial attention map and on-the-fly mask rectilinearization, and strengthen the robustness by Reinforcement-Learning deployment. Experimental results show that, comparing to the state-of-the-art solutions, A2-ILT achieves 5.06% and 11.60% reduction in printing error and process variation band with a lower mask complexity and superior runtime performance.
UR - http://www.scopus.com/inward/record.url?scp=85134669235&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85134669235&partnerID=8YFLogxK
U2 - 10.1145/3489517.3530579
DO - 10.1145/3489517.3530579
M3 - Conference contribution
AN - SCOPUS:85134669235
T3 - Proceedings - Design Automation Conference
SP - 967
EP - 972
BT - Proceedings of the 59th ACM/IEEE Design Automation Conference, DAC 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 July 2022 through 14 July 2022
ER -