Cell Layout

Cell layout optimization focuses on arranging cells within a design to minimize area, power consumption, and interconnect delays, ultimately improving circuit performance. Current research emphasizes leveraging machine learning, including Bayesian methods and large language models, to guide placement algorithms and predict optimal cell densities, often incorporating topological information for improved routability and design rule check compliance. These advancements are crucial for creating efficient and reliable integrated circuits, particularly in advanced process nodes where design complexity and density are increasing, and for generating realistic synthetic cell layouts for applications in digital pathology.