Linearized reduced-order models for subsurface flow simulation
Journal of Computational Physics
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Automated compact dynamical modeling: an enabling tool for analog designers
Proceedings of the 47th Design Automation Conference
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Proceedings of the 16th Asia and South Pacific Design Automation Conference
A Framework for Reduced Order Modeling with Mixed Moment Matching and Peak Error Objectives
SIAM Journal on Scientific Computing
Efficient analytical macromodeling of large analog circuits by transfer function trajectories
Proceedings of the International Conference on Computer-Aided Design
Model order reduction of fully parameterized systems by recursive least square optimization
Proceedings of the International Conference on Computer-Aided Design
Proceedings of the Conference on Design, Automation and Test in Europe
Towards improving simulation of analog circuits using model order reduction
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
Journal of Electronic Testing: Theory and Applications
Mathematics and Computers in Simulation
Hi-index | 0.04 |
We present algorithms for automated macromodeling of nonlinear mixed-signal system blocks. A key feature of our methods is that they automate the generation of general-purpose macromodels that are suitable for a wide range of time- and frequency-domain analyses important in mixed-signal design flows. In our approach, a nonlinear circuit or system is approximated using piecewise-polynomial (PWP) representations. Each polynomial system is reduced to a smaller one via weakly nonlinear polynomial model-reduction methods. Our approach, dubbed PWP, generalizes recent trajectory-based piecewise-linear approaches and ties them with polynomial-based model-order reduction, which inherently captures stronger nonlinearities within each region. PWP-generated macromodels not only reproduce small-signal distortion and intermodulation properties well but also retain fidelity in large-signal transient analyses. The reduced models can be used as drop-in replacements for large subsystems to achieve fast system-level simulation using a variety of time- and frequency-domain analyses (such as dc, ac, transient, harmonic balance, etc.). For the polynomial reduction step within PWP, we also present a novel technique [dubbed multiple pseudoinput (MPI)] that combines concepts from proper orthogonal decomposition with Krylov-subspace projection. We illustrate the use of PWP and MPI with several examples (including op-amps and I/O buffers) and provide important implementation details. Our experiments indicate that it is easy to obtain speedups of about an order of magnitude with push-button nonlinear macromodel-generation algorithms.