MaskPlace: Fast Chip Placement via Reinforced Visual Representation Learning Y ao Lai Y ao Mu Ping Luo Department of Computer Science The University of Hong Kong {ylai,ymu,pluo }@cs.hku.hk

Firstly, MaskPlace recasts placement as a problem of learning pixel-level visual representation to comprehensively describe millions of modules on a chip, enabling placement in a high-resolution canvas and a large action space. It outperforms recent methods that represent a chip as a hypergraph.