Parametric structure-preserving model order reduction

J. Fernández Villena, W.H.A. Schilders, L.M. Silveira

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

3 Citations (Scopus)


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.
Original languageEnglish
Title of host publicationVLSI-SoC: Advanced Topics on Systems on a Chip (A Selection of Extended Versions of the Best Papers of the Fourteenth International Conference on Very Large Scale Integration of System on Chip, VLSI-SoC2007, Atlanta USA, October 15-17, 2007)
EditorsR. Reis, V. Nooney, P. Hasler
ISBN (Print)978-0-387-89557-4
Publication statusPublished - 2009

Publication series

NameIFIP Advances in Information and Communication Technology
ISSN (Print)1868-4238


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