Preprint Open access
GPlaceRL: An Open-Source Graph Reinforcement Learning Framework for Detailed Placement
Reinforcement learning (RL) has emerged as a promising approach for placement optimization, particularly when combined with graph neural networks (GNNs) that capture circuit connectivity. However, most learning-based placement approaches focus on floorplanning, macro placement, or global placement, while detailed place …