This paper addresses the behavioral modeling of digital drivers for Signal and Power Integrity co-simulations. State-of-the-art two-piece model representations are combined with a compact description of the device static characteristics. The latter are considered as multivariate mappings that are functions of the device electrical variables, and of additional parameters defining process corners and device settings. Overall model complexity is reduced through a compressed tensor representation obtained via a high-order singular value decomposition. Several application examples demonstrate the feasibility and the advantages of the proposed approach

Behavioral macromodeling of high-speed drivers via compressed tensor representations / Siviero, Claudio; GRIVET TALOCIA, Stefano; Stievano, IGOR SIMONE; Signorini, Gianni. - ELETTRONICO. - (2015), pp. 1-3. (Intervento presentato al convegno 2015 IEEE MTT-S International Conference on Numerical Electromagnetic and Multiphysics Modeling and Optimization (NEMO) tenutosi a Ottawa, Canada nel 11-14 Aug. 2015) [10.1109/NEMO.2015.7415004].

Behavioral macromodeling of high-speed drivers via compressed tensor representations

SIVIERO, CLAUDIO;GRIVET TALOCIA, STEFANO;STIEVANO, IGOR SIMONE;SIGNORINI, GIANNI
2015

Abstract

This paper addresses the behavioral modeling of digital drivers for Signal and Power Integrity co-simulations. State-of-the-art two-piece model representations are combined with a compact description of the device static characteristics. The latter are considered as multivariate mappings that are functions of the device electrical variables, and of additional parameters defining process corners and device settings. Overall model complexity is reduced through a compressed tensor representation obtained via a high-order singular value decomposition. Several application examples demonstrate the feasibility and the advantages of the proposed approach
2015
978-1-4799-6811-4
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2637830
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