Exploiting input information in a model reduction algorithm for massively coupled parasitic networks

ABSTRACT

In this paper we present a model reduction algorithm that circumvents some of the issues encountered for parasitic networks with large numbers of input/output "ports". Our approach is based on the premise that for such networks, there are typically strong dependencies between the input waveforms at different network "ports". We present an approximate truncated balanced realizations procedure that, by exploiting such correlation information, produces much more compact models compared to standard algorithms such as PRIMA.

REFERENCES

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INDEX TERMS

Primary Classification:
  B. Hardware
  B.7 INTEGRATED CIRCUITS
      B.7.2 Design Aids
          Subjects: Simulation

General Terms:
Algorithms

Keywords:
interconnect, model order reduction, parasitic