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) |
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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 | |
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 |
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ISSN (Print) | 1092-3152 |
Conference
Conference | 43rd International Conference on Computer-Aided Design, ICCAD 2024 |
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Country/Territory | United States |
City | New York |
Period | 10/27/24 → 10/31/24 |
Bibliographical note
Publisher Copyright:© 2024 Copyright is held by the owner/author(s).