FlowPlace: Flow Matching for Chip Placement 事件

FlowPlace: Flow Matching for Chip Placement arXiv:2604.23658v2 Announce Type: replace-cross Abstract: Chip placement plays an important role in physical design. While generative models like diffusion models offer promising learning-based solutions, current methods have the following limitations: they use random synthetic data for pre-training, require long sampling times, and often result in overlaps due to their dependence on gradient-based solvers during the sampling process. To overcome thes