  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.
