Invited: Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants

Vidya A. Chhabria; Bing Yue Wu; Utsav Sharma; Kishor Kunal; Austin Rovinski; Sachin S. Sapatnekar

doi:10.1145/3676536.3697122

Invited: Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants

Vidya A. Chhabria, Bing Yue Wu, Utsav Sharma, Kishor Kunal, Austin Rovinski, Sachin S. Sapatnekar

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The electronic design automation (EDA) community has recently begun recognizing the potential of generative artificial intelligence (AI) in chip design. However, its full potential is not fully exploited due to the limited availability of publicly accessible datasets crucial for advancing research in EDA. This paper highlights the dual role of generative AI; in particular, it showcases (i) BeGAN, the use of a generative AI strategy to create thousands of realistic benchmarks for power grid synthesis and analysis to advance power-related research, and (ii) EDA Corpus—an expert-curated and generative AI-enhanced dataset to serve research and development of EDA tool assistants. These two case studies emphasize the ability of generative methods to create and utilize datasets to advance research and lower the barriers to entry in EDA.

Original language	English (US)
Title of host publication	Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2024
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798400710773
DOIs	https://doi.org/10.1145/3676536.3697122
State	Published - Apr 9 2025
Event	43rd International Conference on Computer-Aided Design, ICCAD 2024 - New York, United States Duration: Oct 27 2024 → Oct 31 2024

Publication series

Name	IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
ISSN (Print)	1092-3152

Conference

Conference	43rd International Conference on Computer-Aided Design, ICCAD 2024
Country/Territory	United States
City	New York
Period	10/27/24 → 10/31/24

ASJC Scopus subject areas

Software
Computer Science Applications
Computer Graphics and Computer-Aided Design

Access to Document

10.1145/3676536.3697122

Cite this

Chhabria, V. A., Wu, B. Y., Sharma, U., Kunal, K., Rovinski, A., & Sapatnekar, S. S. (2025). Invited: Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants. In Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2024 Article 57 (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1145/3676536.3697122

Invited: Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants. / Chhabria, Vidya A.; Wu, Bing Yue; Sharma, Utsav et al.
Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2024. Institute of Electrical and Electronics Engineers Inc., 2025. 57 (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Chhabria, VA, Wu, BY, Sharma, U, Kunal, K, Rovinski, A & Sapatnekar, SS 2025, Invited: Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants. in Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2024., 57, IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD, Institute of Electrical and Electronics Engineers Inc., 43rd International Conference on Computer-Aided Design, ICCAD 2024, New York, United States, 10/27/24. https://doi.org/10.1145/3676536.3697122

Chhabria VA, Wu BY, Sharma U, Kunal K, Rovinski A, Sapatnekar SS. Invited: Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants. In Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2024. Institute of Electrical and Electronics Engineers Inc. 2025. 57. (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD). doi: 10.1145/3676536.3697122

Chhabria, Vidya A. ; Wu, Bing Yue ; Sharma, Utsav et al. / Invited : Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants. Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2024. Institute of Electrical and Electronics Engineers Inc., 2025. (IEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD).

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abstract = "The electronic design automation (EDA) community has recently begun recognizing the potential of generative artificial intelligence (AI) in chip design. However, its full potential is not fully exploited due to the limited availability of publicly accessible datasets crucial for advancing research in EDA. This paper highlights the dual role of generative AI; in particular, it showcases (i) BeGAN, the use of a generative AI strategy to create thousands of realistic benchmarks for power grid synthesis and analysis to advance power-related research, and (ii) EDA Corpus—an expert-curated and generative AI-enhanced dataset to serve research and development of EDA tool assistants. These two case studies emphasize the ability of generative methods to create and utilize datasets to advance research and lower the barriers to entry in EDA.",

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Invited: Generative Methods in EDA: Innovations in Dataset Generation and EDA Tool Assistants

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