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The major concerns in state-of-the-art model reduction algorithms are: achieving accurate models of sufficiently small size, numerically stable and efficient generation of the models, and preservation of system properties such as passivity. Algorithms such as PRIMA generate guaranteed-passive models, for systems with special internal structure, using(More)
In this paper, we describe an approach for generating accurate geometrically parameterized integrated circuit interconnect models that are efficient enough for use in interconnect synthesis. The model-generation approach presented is automatic, and is based on a multiparameter moment matching model-reduction algorithm. A moment-matching theorem proof for(More)
In this paper an optimization based model order reduction (MOR) framework is proposed. The method involves setting up a quasiconvex program that explicitly minimizes a relaxation of the optimal <i>H</i>&#8734; norm MOR problem. The method generates guaranteed stable and passive reduced models and it is very flexible in imposing additional constraints. The(More)
In this paper we present a parameterized reduction technique for non-linear systems. Our approach combines an existing non-parameterized trajectory piecewise linear method for non-linear systems, with an existing moment matching parameterized technique for linear systems. Results and comparisons are presented for two examples: an analog non-linear circuit,(More)
Abstract— In this paper we describe an approach for generating geometrically-parameterized integrated-circuit interconnect models that are efficient enough for use in interconnect synthesis. The model generation approach presented is automatic, and is based on a multi-parameter modelreduction algorithm. The effectiveness of the technique is tested using a(More)
Simulation and Modeling Techniques for Signal Integrity and Electromagnetic Interference on High Frequency Electronic Systems. by Luca Daniel Doctor of Philosophy in Engineering Electrical Engineering and Computer Sciences University of California at Berkeley Professor Alberto L Sangiovanni-Vincentelli, Chair Many future electronic systems will consist of(More)
Uncertainties have become a major concern in integrated circuit design. In order to avoid the huge number of repeated simulations in conventional Monte Carlo flows, this paper presents an intrusive spectral simulator for statistical circuit analysis. Our simulator employs the recently developed generalized polynomial chaos expansion to perform uncertainty(More)
In this paper, we present an efficient method to model the interior of the conductors in a quasi-static or full-wave integral equation solver. We show how interconnect cross-sectional current distributions can be modeled using a small number of conduction modes as basis functions for the discretization of the Mixed Potential Integral Equation (MPIE). Two(More)
In this paper we present an efficient algorithm for extracting the complete statistical distribution of the input impedance of interconnect structures in the presence of a large number of random geometrical variations. The main contribution in this paper is the development of a new algorithm, which combines both Neumann expansion and Hermite expansion, to(More)
In this paper we describe the acceleration algorithm implemented in FastMaxwell, a program for wideband electromagnetic extraction of complicated 3D conductor structures over substrate. FastMaxwell is based on the integral domain mixed potential integral equation (MPIE) formulation, with 3-D full-wave substrate dyadic Green's function kernel. Two dyadic(More)