Can I read DRC-Coder: Automated DRC Checker Code Generation Using LLM Autonomous Agent on EtoBox?

DRC-Coder: Automated DRC Checker Code Generation Using LLM Autonomous Agent by Chang, Chen-Chia; Ho, Chia-Tung; Li, Yaguang; Chen, Yiran; Ren, Haoxing is a scholarly article available to read on EtoBox.

What is DRC-Coder: Automated DRC Checker Code Generation Using LLM Autonomous Agent about?

In the advanced technology nodes, the integrated design rule checker (DRC) is often utilized in place and route tools for fast optimization loops for power-performance-area. Implementing integrated DRC checkers to meet the standard of commercial DRC tools demands extensive human expertise to interpret foundry specifications, analyze layouts, and debug code iteratively. However, this labor-intensive process, requiring to be repeated by every update of technology nodes, prolongs the turnaround time of designing circuits. In this paper, we present DRC-Coder, a multi-agent framework with vision capabilities for automated DRC code generation. By incorporating vision language models and large language models (LLM), DRC-Coder can effectively process textual, visual, and layout information to perform rule interpretation and coding by two specialized LLMs. We also design an auto-evaluation function for LLMs to enable DRC code debugging. Experimental results show that targeting on a sub-3nm technology node for a state-of-the-art standard cell layout tool, DRC-Coder achieves perfect F1 score 1.000 in generating DRC codes for meeting the standard of a commercial DRC tool, highly outperforming

Author

Chang, Chen-Chia; Ho, Chia-Tung; Li, Yaguang; Chen, Yiran; Ren, Haoxing

Published

2024

Language

EN