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The integration of a complex set of Electronic Design Automation (EDA) toolsto enhance interoperability is a critical concern for circuit designers. Recentadvancements in large language models (LLMs) have showcased their exceptionalcapabilities in natural language processing and comprehension, offering a novelapproach to interfacing with EDA tools. This research paper introduces ChatEDA,an autonomous agent for EDA empowered by a large language model, AutoMage,complemented by EDA tools serving as executors. ChatEDA streamlines the designflow from the Register-Transfer Level (RTL) to the Graphic Data System VersionII (GDSII) by effectively managing task planning, script generation, and taskexecution. Through comprehensive experimental evaluations, ChatEDA hasdemonstrated its proficiency in handling diverse requirements, and ourfine-tuned AutoMage model has exhibited superior performance compared to GPT-4and other similar LLMs.

ChatEDA: A Large Language Model Powered Autonomous Agent for EDA