A2-ILT: GPU Accelerated ILT with Spatial Attention Mechanism

Qijing Wang; Bentian Jiang; Martin D. F. Wong; Evangeline F. Y. Young

doi:10.1145/3489517.3530579

A2-ILT: GPU Accelerated ILT with Spatial Attention Mechanism

Qijing Wang, Bentian Jiang, Martin D. F. Wong, Evangeline F. Y. Young

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Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

23 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	59th ACM/IEEE Design Automation Conference - Proceedings 2022
Publisher	Association for Computing Machinery (ACM)
Pages	967-972
Number of pages	6
ISBN (Print)	9781450391429
DOIs	https://doi.org/10.1145/3489517.3530579
Publication status	Published - 14 Jul 2022
Event	59th ACM/IEEE Design Automation Conference, DAC 2022 - San Francisco, United States Duration: 10 Jul 2022 → 14 Jul 2022 https://www.dac.com/About/Conference-Archive/59th-DAC-2022 (Conference website) https://www.dac.com/Portals/0/DAC%2059/59DAC%20Onsite%20Guide_v3.pdf?ver=GbBS5sBuhmEVJWVEz9CNIg%3d%3d (Conference programme) https://dl.acm.org/doi/proceedings/10.1145/3489517 (Conference proceedings)

Publication series

Name	ACM/IEEE Design Automation Conference - Proceedings
ISSN (Print)	0738-100X

Conference

Conference	59th ACM/IEEE Design Automation Conference, DAC 2022
Country/Territory	United States
City	San Francisco
Period	10/07/22 → 14/07/22
Internet address	https://www.dac.com/About/Conference-Archive/59th-DAC-2022 (Conference website) https://www.dac.com/Portals/0/DAC%2059/59DAC%20Onsite%20Guide_v3.pdf?ver=GbBS5sBuhmEVJWVEz9CNIg%3d%3d (Conference programme) https://dl.acm.org/doi/proceedings/10.1145/3489517 (Conference proceedings)

Access to Document

10.1145/3489517.3530579

Cite this

@inproceedings{3f8806e7d4c9484d90d1bd18146b9f64,

title = "A2-ILT: GPU Accelerated ILT with Spatial Attention Mechanism",

abstract = "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.",

author = "Qijing Wang and Bentian Jiang and Wong, {Martin D. F.} and Young, {Evangeline F. Y.}",

note = "Funding Information: 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). Publisher Copyright: {\textcopyright} 2022 ACM.; 59th ACM/IEEE Design Automation Conference, DAC 2022 ; Conference date: 10-07-2022 Through 14-07-2022",

year = "2022",

month = jul,

day = "14",

doi = "10.1145/3489517.3530579",

language = "English",

isbn = "9781450391429",

series = "ACM/IEEE Design Automation Conference - Proceedings",

publisher = "Association for Computing Machinery (ACM)",

pages = "967--972",

booktitle = "59th ACM/IEEE Design Automation Conference - Proceedings 2022",

address = "United States",

url = "https://www.dac.com/About/Conference-Archive/59th-DAC-2022, https://www.dac.com/Portals/0/DAC%2059/59DAC%20Onsite%20Guide_v3.pdf?ver=GbBS5sBuhmEVJWVEz9CNIg%3d%3d, https://dl.acm.org/doi/proceedings/10.1145/3489517",

}

Wang, Q, Jiang, B, Wong, MDF & Young, EFY 2022, A2-ILT: GPU Accelerated ILT with Spatial Attention Mechanism. in 59th ACM/IEEE Design Automation Conference - Proceedings 2022. ACM/IEEE Design Automation Conference - Proceedings, Association for Computing Machinery (ACM), pp. 967-972, 59th ACM/IEEE Design Automation Conference, DAC 2022, San Francisco, California, United States, 10/07/22. https://doi.org/10.1145/3489517.3530579

A2-ILT: GPU Accelerated ILT with Spatial Attention Mechanism. / Wang, Qijing; Jiang, Bentian; Wong, Martin D. F. et al.
59th ACM/IEEE Design Automation Conference - Proceedings 2022. Association for Computing Machinery (ACM), 2022. p. 967-972 (ACM/IEEE Design Automation Conference - Proceedings).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

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 - Funding Information: 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). Publisher Copyright: © 2022 ACM.

PY - 2022/7/14

Y1 - 2022/7/14

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.

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M3 - Conference proceeding

AN - SCOPUS:85134669235

SN - 9781450391429

T3 - ACM/IEEE Design Automation Conference - Proceedings

SP - 967

EP - 972

BT - 59th ACM/IEEE Design Automation Conference - Proceedings 2022

PB - Association for Computing Machinery (ACM)

Y2 - 10 July 2022 through 14 July 2022

ER -

A2-ILT: GPU Accelerated ILT with Spatial Attention Mechanism

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