Chip Design

Chip design is undergoing a transformation driven by the need for faster, more energy-efficient, and complex integrated circuits. Current research focuses heavily on leveraging machine learning, particularly deep learning models like Graph Neural Networks and diffusion models, to optimize various stages of the design process, from placement and routing to power management and verification. These advancements aim to significantly reduce design time and improve chip performance, impacting both the efficiency of the EDA workflow and the capabilities of resulting hardware.