A statistical model of logic gates for Monte Carlo simulation including on-chip variation

Process variations are becoming a paramount design problem in nano-scale VLSI. We present a framework for the statistical model of logic gates that describes both inter-die and intra-die variations of performance parameters such as propagation delay and leakage currents. This allows fast but accurate behavioral-level Monte-Carlo simulations, that could be useful for full-custom digital design optimization and yield prediction, and enables the development of a yield-aware digital design flow. The model can incorporate correlation between mismatch parameters and dependence on distance and position, and can be extracted by fitting of Monte-Carlo transistor level simulations. An example implementation using Verilog-A hardware description language in Cadence environment is presented.