A Learning-Based Algorithm for Early Floorplan With Flexible Blocks

This paper presents a learning-based algorithm using graph neural network (GNN) and deconvolution network to predict the placement of the locations and the aspect ratios for the design blocks with flexible rectangles. With several hours of training on 4 GPUs, the proposed method, targeting at minimizing the cost of wirelength, can generate the placements in early stage of floorplan which is superior to that from the manual placements which requires several days’ efforts for physical design experts.