MISP-Net: Significantly Reducing Transient Backward Steppings via Novel Multi-step Irregular Sequence Prediction

In the post-layout simulation for large-scale integrated circuits, Transient Analysis (TA), determining the time-domain response over a specified time interval, is essential and time-consuming. Especially, a mass of backward steppings and low simulation efficiency occur without proper settings of Newton-Raphson (NR) initial solution and accurate Local Truncation Error (LTE) estimation. In this work, a novel multi-step irregular sequence prediction model (MISP-Net) is proposed to predict multiple NR initial solutions and precise LTE estimations by just one inference step. This model is constructed by an Irregular Multiple Timesteps Prediction Module (IMTP) and a Irregular Multi-step Solution Prediction Module (IMSP). In IMSP, to improve the irregular prediction performance, a Dual-branch Irregular Feature Pyramid (DIFP) equipped with lightweight Multi-Channel Irregular Time Attention (MITA) are designed. We assess the proposed MISP-Net in the real large-scale industrial circuits on a commercial SPICE simulator. Compared with the commercial SPICE and the SOTA ISPT-Net model, significant backward stepping reductions are achieved: up to 78.57% for NR nonconvergence case and 76.62% for LTE overlimit case, respectively. And the prediction time for NR initial solution in our model is remarkably reduced by up to 5.58× compared to the SOTA ISPT-Net model.