Afsara Khan

Routing Dense Layouts with History-Aware Offline Reinforcement Learning using LSTM

A history-aware offline RL policy which predicts iterative cost weights in these dense regimes to improve convergence across placement densities by utilizing readily available features from the router and which reduces design rule violations (DRVs) by an average of 92% over the top public baseline while simultaneously...