ControLayout: Conditional Diffusion for Style-Controllable and Violation-Fixable Layout Pattern Generation: Conditional Diffusion for Style-Controllable and Violation-Fixable Layout Pattern Generation

Qijing Wang, Xiaopeng Zhang, Martin D.F. Wong, Evangeline F.Y. Young

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

Abstract

Due to the lengthy design cycle, generating legal, diverse and valid layout patterns artificially to expand VLSI layout pattern libraries has become an important problem to solve in order to facilitate modern design-for-manufacturability (DFM) studies. Considering the more realistic demands and to enhance functionality, this work proposes a style-controllable and violation-fixable layout pattern generation framework based on conditional diffusion models named ControLayout, which treats pattern category and complexity as conditions to control the style of generated patterns, and leverages the idea of image masking-inpainting to fix violations adaptively. Experiments reveal its promising performance in controllability and different metrics compared with the state-of-the-art methods.

Original languageEnglish
Title of host publicationGLSVLSI 2024 - Proceedings of the Great Lakes Symposium on VLSI 2024
EditorsInna Partin-Vaisband, Srinivas Katkoori, Lu Peng, Boris Vaisband, Tooraj Nikoubin
PublisherAssociation for Computing Machinery (ACM)
Pages511-515
Number of pages5
ISBN (Print)9798400706059
DOIs
Publication statusPublished - 12 Jun 2024
Event34th Great Lakes Symposium on VLSI 2024, GLSVLSI 2024 - Clearwater, United States
Duration: 12 Jun 202414 Jun 2024
https://dl.acm.org/doi/proceedings/10.1145/3649476

Publication series

NameProceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI

Conference

Conference34th Great Lakes Symposium on VLSI 2024, GLSVLSI 2024
Country/TerritoryUnited States
CityClearwater
Period12/06/2414/06/24
Internet address

Scopus Subject Areas

  • General Engineering

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