Scalable trajectory methods for on-demand analog macromodel extraction

Trajectory methods sample the state trajectory of a circuit as it simulates in the time domain, and build macromodels by reducing and interpolating among the linearizations created at a suitably spaced subset of the time points visited during training simulations. Unfortunately, moving from simple to industrial circuits requires more extensive training, which creates models too large to interpolate efficiently. To make trajectory methods practical, we describe a scalable interpolation architecture, and the first implementation of a complete trajectory "infrastructure" inside a full SPICE engine. The approach supports arbitrarily large training runs, automatically prunes redundant trajectory samples, supports limited hierarchy, enables incremental macromodel updates, and gives 3-10X speedups for larger circuits. Categories and Subject Descriptors I.6.5 [Simulation and Modeling]: Model Development General Terms Algorithms, Design Keywords Circuit, trajectory method, analog, ma...

• Type: Conference
• Year: 2005
• Where: DAC
• Authors: Saurabh K. Tiwary, Rob A. Rutenbar
• Keywords: Complete Trajectory, DAC 2005, Design Automation, Redundant Trajectory Samples, Trajectory Methods