AI-driven design automation

AI-driven design automation is the use of artificial intelligence (AI) to automate and improve different parts of the electronic design automation (EDA) process. It is particularly important in the design of integrated circuits (chips) and complex electronic systems, where it can potentially increase productivity, decrease costs, and speed up design cycles. AI Driven Design Automation uses several methods, including machine learning, expert systems, and reinforcement learning. These are used for many tasks, from planning a chip's architecture and logic synthesis to its physical design and final verification.

This figure explains how can we train large circuit models by making use of the front-end (depicted in blue) and back-end (depicted in yellow) of the EDA flow in order to either enhance existing EDA tools or to create novel EDA applications.[1]
  1. ^ Chen, Lei; Chen, Yiqi; Chu, Zhufei; Fang, Wenji; Ho, Tsung-Yi; Huang, Ru; Huang, Yu; Khan, Sadaf; Li, Min (1 May 2024), "Large circuit models: Opportunities and challenges", Science China Information Sciences, 67 (10), arXiv:2403.07257, doi:10.1007/s11432-024-4155-7

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