RollPlace: Improving Macro Placement via Monte Carlo Rollout Search

Excerpt

arXiv:2610.06316v1 Announce Type: new Abstract: The application of Reinforcement Learning (RL) in Electronic Design Automation (EDA), particularly for chip placement, has attracted considerable attention in recent years. While existing machine learning (ML)-based approaches have achieved notable progress, they predominantly focus on generating optimal layouts in a single attempt, often producing solutions that require subsequent refinement. To address this limitation, we propose RollPlace, a nov