Title :
Model order reduction techniques for linear systems with large numbers of terminals
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
Abstract :
This paper addresses the well known difficulty of applying model order reduction (MOR) to linear circuits with a large number of input-output terminals. Traditional MOR techniques substitute the original large but sparse matrices used in the mathematical modeling of linear circuits by models that approximate the behavior of the circuit at its terminals, and use significantly smaller matrices. Unfortunately these small MOR matrices become dense as the number of terminals increases, thus canceling the benefits of size reduction. The paper introduces a model reduction technique suitable for circuits with numerous terminals. The technique exploits the correlation that almost always exists between circuit responses at different terminals. The correlation is rendered explicit through an SVD-based algorithm and the result is a substantial sparsification of the MOR matrices. The proposed sparsification technique is applicable to a large class of problems encountered in the analysis and design of interconnect in VLSI circuits. Relevant examples are used to analyze and validate the method.
Keywords :
linear systems; reduced order systems; singular value decomposition; sparse matrices; SVD based algorithm; VLSI circuits; circuit responses; input-output terminals; linear circuits; linear systems; mathematical modeling; model order reduction techniques; singular value decomposition; sparse matrices; sparsification technique; very large scale integration circuits; Degradation; Information analysis; Integrated circuit interconnections; Linear circuits; Linear systems; Mathematical model; Reduced order systems; Sparse matrices; Transfer functions; Wires;
Conference_Titel :
Design, Automation and Test in Europe Conference and Exhibition, 2004. Proceedings
Print_ISBN :
0-7695-2085-5
DOI :
10.1109/DATE.2004.1269013