The electronic design automation (EDA) community has been actively exploring machine learning (ML) for very large-scale integrated computer-aided design (VLSI CAD). Many studies explored learning-based techniques for cross-stage prediction tasks in the design flow to achieve faster design convergence. Although building ML models usually requires a large amount of data, most studies can only generate small internal datasets for validation because of the lack of large public datasets. In this essay, we present the first open-source dataset called CircuitNet for ML tasks in VLSI CAD.
@article{arxiv.2208.01040,
title = {CircuitNet: An Open-Source Dataset for Machine Learning Applications in Electronic Design Automation (EDA)},
author = {Zhuomin Chai and Yuxiang Zhao and Yibo Lin and Wei Liu and Runsheng Wang and Ru Huang},
journal= {arXiv preprint arXiv:2208.01040},
year = {2022}
}