Efficient Design Rule Checking Script Generation via Key Information Extraction

Design rule checking (DRC) is a critical step in integrated circuit design. DRC requires formatted scripts as the input to the design rule checker. However, these scripts are always generated manually in the foundry, and such a generation process is extremely inefficient, especially when encountering a large number of design rules. To mitigate this issue, we first propose a deep learning-based key information extractor to automatically identify the essential arguments of the scripts from rules. Then, a script translator is designed to organize the extracted arguments into executable DRC scripts. In addition, we incorporate three specific design rule generation techniques to improve the performance of our extractor. Experimental results demonstrate that our proposed method can significantly reduce the cost of script generation and show remarkable superiority over other baselines.