LAUSR

One of the most important issues in physical design is coupling capacitance. However, the issue is typically addressed during the routing stage, which necessitates the execution of a time-consuming algorithm. Based on the generative adversarial networks (GAN) model, we propose a coupling-free global placement (CFGP) model with different orders of ordinary differential equations (ODE) solver. Experiments on the ISPD’11/DAC’12 contest benchmark revealed that using the ODE-GAN architecture, our coupling effect estimator (CEE) model can achieve 0.91X similarity to the ground-truth image and a 50X speedup over traditional global routers such as NCTUgr. Compared to the original framework without the CEE model, the CFGP implemented using DREAMPlace results in a 41% reduction in coupling effect.