Article

Process variation aware OPC with variational lithography modeling

Authors:

David Z. PanAuthors Info & Claims

DAC '06: Proceedings of the 43rd annual Design Automation Conference

Pages 785 - 790

https://doi.org/10.1145/1146909.1147108

Published: 24 July 2006 Publication History

Abstract

Optical proximity correction (OPC) is one of the most widely used resolution enhancement techniques (RET) in nanometer designs to improve subwavelength printability. Conventional model-based OPC assumes nominal process parameters without considering process variations, due to prohibitive runtimes of lithography simulations across process windows. This is the first paper to propose a true process-variation aware OPC (PV-OPC) framework. It is enabled by the variational lithography modeling and guided by the variational edge placement error (V-EPE) metrics. Due to the analytical nature of our models, our PV-OPC is only about 2-3x slower than the conventional OPC, but it explicitly considers the two main sources of process variations (dosage and focus) during OPC. Thus our post PV-OPC results are much more robust than the conventional OPC ones, in terms of both geometric printability and electrical characterization under process variations.

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Cited By

Yang HLin YYu B(2022)Machine Learning for Mask Synthesis and VerificationMachine Learning Applications in Electronic Design Automation10.1007/978-3-031-13074-8_15(425-470)Online publication date: 10-Aug-2022
https://doi.org/10.1007/978-3-031-13074-8_15
Zhang WChen KLi XMa YZhu CChen BGao XKim K(2021)A Workflow of Hotspot Prediction based on Semi-Supervised Machine Learning Methodology2021 International Workshop on Advanced Patterning Solutions (IWAPS)10.1109/IWAPS54037.2021.9671068(1-3)Online publication date: 12-Dec-2021
https://doi.org/10.1109/IWAPS54037.2021.9671068
Yang HLi SDeng ZMa YYu BYoung E(2020)GAN-OPC: Mask Optimization With Lithography-Guided Generative Adversarial NetsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2019.293932939:10(2822-2834)Online publication date: Oct-2020
https://doi.org/10.1109/TCAD.2019.2939329
Show More Cited By

Index Terms

Process variation aware OPC with variational lithography modeling
1. Applied computing
  1. Arts and humanities
    1. Architecture (buildings)
      1. Computer-aided design
  2. Physical sciences and engineering
    1. Engineering
      1. Computer-aided design
2. Hardware
  1. Electronic design automation
    1. Physical design (EDA)

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Published In

cover image ACM Conferences

DAC '06: Proceedings of the 43rd annual Design Automation Conference

July 2006

1166 pages

ISBN:1595933816

DOI:10.1145/1146909

General Chair:
Ellen M. Sentovich
Cadence Berkeley Labs, Berkeley, CA

Copyright © 2006 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 July 2006

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DAC06

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DAC06: The 43rd Annual Design Automation Conference 2006

July 24 - 28, 2006

CA, San Francisco, USA

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Overall Acceptance Rate 1,770 of 5,499 submissions, 32%

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Citations

Cited By

Yang HLin YYu B(2022)Machine Learning for Mask Synthesis and VerificationMachine Learning Applications in Electronic Design Automation10.1007/978-3-031-13074-8_15(425-470)Online publication date: 10-Aug-2022
https://doi.org/10.1007/978-3-031-13074-8_15
Zhang WChen KLi XMa YZhu CChen BGao XKim K(2021)A Workflow of Hotspot Prediction based on Semi-Supervised Machine Learning Methodology2021 International Workshop on Advanced Patterning Solutions (IWAPS)10.1109/IWAPS54037.2021.9671068(1-3)Online publication date: 12-Dec-2021
https://doi.org/10.1109/IWAPS54037.2021.9671068
Yang HLi SDeng ZMa YYu BYoung E(2020)GAN-OPC: Mask Optimization With Lithography-Guided Generative Adversarial NetsIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2019.293932939:10(2822-2834)Online publication date: Oct-2020
https://doi.org/10.1109/TCAD.2019.2939329
Awad ATakahashi AKodaman C(2018)Optical Proximity Correction (OPC) Under Immersion LithographyMicro/Nanolithography - A Heuristic Aspect on the Enduring Technology10.5772/intechopen.72699Online publication date: 2-May-2018
https://doi.org/10.5772/intechopen.72699
Dong XZhang L(2017)Process-Variation-Aware Rule-Based Optical Proximity Correction for Analog Layout MigrationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2016.262643736:8(1395-1405)Online publication date: Aug-2017
https://doi.org/10.1109/TCAD.2016.2626437
Evans AHamdioui SKaczer B(2017)Manufacturing SolutionsDependable Multicore Architectures at Nanoscale10.1007/978-3-319-54422-9_4(107-153)Online publication date: 30-Aug-2017
https://doi.org/10.1007/978-3-319-54422-9_4
AWAD ATAKAHASHI AKODAMA C(2016)A Fast Mask Manufacturability and Process Variation Aware OPC Algorithm with Exploiting a Novel Intensity Estimation ModelIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences10.1587/transfun.E99.A.2363E99.A:12(2363-2374)Online publication date: 2016
https://doi.org/10.1587/transfun.E99.A.2363
Su YHuang YTsai LChang YBanerjee S(2016)Fast Lithographic Mask Optimization Considering Process VariationIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems10.1109/TCAD.2015.251408235:8(1345-1357)Online publication date: 1-Aug-2016
https://dl.acm.org/doi/10.1109/TCAD.2015.2514082
Geng ZShi ZYan XLuo KPan W(2015)Fast Level-Set-Based Inverse Lithography Algorithm for Process Robustness Improvement and Its ApplicationJournal of Computer Science and Technology10.1007/s11390-015-1549-730:3(629-638)Online publication date: 1-May-2015
https://doi.org/10.1007/s11390-015-1549-7
Awad ATakahashi ATanaka SKodama CChang Y(2014)A fast process variation and pattern fidelity aware mask optimization algorithmProceedings of the 2014 IEEE/ACM International Conference on Computer-Aided Design10.5555/2691365.2691414(238-245)Online publication date: 3-Nov-2014
https://dl.acm.org/doi/10.5555/2691365.2691414
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