This paper presents an alternative modeling strategy for the stochastic analysis of high-speed interconnects. The proposed approach takes advantage of the polynomial chaos framework and a fully SPICE-compatible formulation to avoid repeated circuit simulations, thereby alleviating the computational burden associated with traditional sampling-based methods such as Monte Carlo. Nonetheless, the technique offers very good accuracy and the opportunity to easily simulate complex interconnect topologies which include lossy and dispersive transmission lines, thus overcoming the limitations of previous formulations. Application examples involving the stochastic analysis of on-chip and on-board interconnects validate the methodology proposed.

Uncertainty Assessment of Lossy and Dispersive Lines in SPICE-Type Environments / Manfredi, Paolo; Vande Ginste, D.; De Zutter, D.; Canavero, Flavio. - In: IEEE TRANSACTIONS ON COMPONENTS, PACKAGING, AND MANUFACTURING TECHNOLOGY. - ISSN 2156-3950. - STAMPA. - 3:7(2013), pp. 1252-1258. [10.1109/TCPMT.2013.2259295]

Uncertainty Assessment of Lossy and Dispersive Lines in SPICE-Type Environments

MANFREDI, PAOLO;CANAVERO, Flavio
2013

Abstract

This paper presents an alternative modeling strategy for the stochastic analysis of high-speed interconnects. The proposed approach takes advantage of the polynomial chaos framework and a fully SPICE-compatible formulation to avoid repeated circuit simulations, thereby alleviating the computational burden associated with traditional sampling-based methods such as Monte Carlo. Nonetheless, the technique offers very good accuracy and the opportunity to easily simulate complex interconnect topologies which include lossy and dispersive transmission lines, thus overcoming the limitations of previous formulations. Application examples involving the stochastic analysis of on-chip and on-board interconnects validate the methodology proposed.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2514679
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