Parametric Structure-Preserving Model Order Reduction

Part of the IFIP International Federation for Information Processing book series (IFIPAICT, volume 291)

Analysis and verification environments for next-generation nano-scale RFIC designs must be able to cope with increasing design complexity and to account for new effects, such as process variations and Electromagnetic (EM) couplings. Designed-in passives, substrate, interconnect and devices can no longer be treated in isolation as the interactions between them are becoming more relevant to the behavior of the complete system. At the same time variations in process parameters lead to small changes in the device characteristics that may directly affect system performance. These two effects, however, cannot be treated separately as the process variations that modify the physical parameters of the devices also affect those same EM couplings. Accurately capturing the effects of process variations as well as the relevant EM coupling effects requires detailed models that become very expensive to simulate. Reduction techniques able to handle parametric descriptions of linear systems are necessary in order to obtain better simulation performance. In this work we discuss parametric Model Order Reduction techniques based on Structure-Preserving formulations that are able to exploit the hierarchical system representation of designed-in blocks, substrate and interconnect, in order to obtain more efficient simulation models.


Singular Value Decomposition Model Order Reduction Krylov Subspace Moment Match Congruence Transformation 
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Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  1. 1.INESC ID / IST - TechUniversity of LisbonLisbonPortugal
  2. 2.NXPSemiconductors ResearchAE Eindhoven
  3. 3.Cadence Research LabsRua Alves Redol 9Portugal

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