A Multiparameter Moment-Matching Model-Reduction Approach for Generating Geometrically Parameterized Interconnect Performance Models

L. Daniel, O.C. Siong, L.S. Chay, K.H. Lee, J. White
2004 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems  
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 the algorithm is derived, as well as a complexity analysis for the model-order growth. The effectiveness of the technique is tested using a
more » ... s tested using a capacitance extraction example, where the plate spacing is considered as the geometric parameter, and a multiline bus example, where both wire spacing and wire width are considered as geometric parameters. Experimental results demonstrate that the generated models accurately predict capacitance values for the capacitor example, and both delay and cross-talk effects over a reasonably wide range of spacing and width variation for the multiline bus example. Index Terms-Interconnect synthesis, integrated circuits interconnections, modeling, parameterized reduced-order systems, reduced-order systems. I. INTRODUCTION D EVELOPERS of routing tools for mixed-signal applications could make productive use of more accurate performance models for interconnect, but the cost of extracting even a modestly accurate model for a candidate route is far beyond the computational budget of the inner loop of a router. If it were possible to extract geometrically parameterized, but inexpensive to evaluate, models for the interconnect performance, then such models could be used for detailed interconnect synthesis in performance critical digital or analog applications. The idea of generating parameterized reduced-order interconnect models is not new. Recent approaches have been developed that focus on statistical performance evaluation [1], [2] Manuscript
doi:10.1109/tcad.2004.826583 fatcat:ngi2wclndjcz3bumvu74wgfcvm