TurboMOR: an Efficient Model Order Reduction Technique for RC Networks with Many Ports

TL;DR

TurboMOR is a new model order reduction method for RC networks with many ports, offering improved efficiency, scalability, and interpretability over existing techniques through moment-matching and block-diagonal reduced models.

Contribution

It introduces TurboMOR, a novel MOR technique that produces sparse, block-diagonal reduced models for passive RC networks, enhancing scalability and interpretability.

Findings

TurboMOR reduces reduction time significantly.

TurboMOR decreases simulation time and memory usage.

TurboMOR scales better than existing methods.

Abstract

Model order reduction (MOR) techniques play a crucial role in the computer-aided design of modern integrated circuits, where they are used to reduce the size of parasitic networks. Unfortunately, the efficient reduction of passive networks with many ports is still an open problem. Existing techniques do not scale well with the number of ports, and lead to dense reduced models that burden subsequent simulations. In this paper, we propose TurboMOR, a novel MOR technique for the efficient reduction of passive RC networks. TurboMOR is based on moment-matching, achieved through efficient congruence transformations based on Householder reflections. A novel feature of TurboMOR is the block-diagonal structure of the reduced models, that makes them more efficient than the dense models produced by existing techniques. Moreover, the model structure allows for an insightful interpretation of the reduction process in terms of system theory. Numerical results show that TurboMOR scales more favourably than existing techniques in terms of reduction time, simulation time and memory consumption.