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Since the rst papers on asymptotic waveform evaluation (AWE), reduced order models have become standard for improving interconnect simulation eciency, and very recent w ork has demonstrated that bi-orthogonalization algorithms can be used to robustly generate AWE-style macromodels. In this paper we describe using block Arnoldi-based orthogonalization methods to generate reduced order models from FastHenry, a m ultipole-accelerated three dimensional inductance extraction program. Examples are analyzed to demonstrate the eciency and accuracy of the block Arnoldi algorithm.
Silveira et al. (Sun,) studied this question.
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