Machine Learning-Based Verilog-A Modeling for Power Distribution Network of On-Die Regulator

The paper introduces a Verilog-A model with the skill of vector fitting and neural network for the efficient methodology to analyze the power distribution network of on-chip linear dropout regulator (LDO). A practical methodology demonstrates the effectiveness and the efficiency of the Verilog-A model in the time domain and is derived that takes into account LDO-PDN system impedance response. The goal is to provide adequate performance for cost-effective and system solution and achieving on system-level success.