How Google is Applying Machine Learning to Macro Placement

CHIPS Alliance’s latest Deep Dive Cafe featured an outstanding talk by a Google physical design engineer, Young-Joon Lee, who has a PhD from Georgia Tech, and has been working on machine learning physical design projects for the past two years. The chip placement problem is a notoriously challenging design problem, and has been explored in the electronic design automation research and development community for years. For those unfamiliar with the problem, it involves finding the optimal placement of physical cells implementing the logical function on a chip image to minimize performance,…