Unified Dynamic Library: Neural Network-Based Compact Modeling for Enhanced Efficiency

This study introduces the new concept of Unified Dynamic Library(UDL) to overcome existing limitations and proposes a novel method for ANN-based compact modeling. Using this method, it becomes possible to adopt the computational framework of neural networks, achieving high simulation speeds. In addition, it offers the advantage of incorporating the physical phenomenon of components into the device modeling process, such as negative differential resistance. To validate this concept, our model's accuracy and simulation speed have been compared with the direct implementation of ANN model in Verilog-A as well as the Look-Up Table model. In the transient Ring Oscillator circuit simulations, the UDL calculation achieved a speed 43 times faster than the Verilog-A-based neural network model and 389 times faster than the Look-Up Table model while sufficiently guaranteeing model accuracy.