Sparse Matrix Methods for Circuit Simulation Problems

Differential algebraic equations used for circuit simulation give rise to sequences of sparse linear systems. The matrices have very peculiar characteristics as compared to sparse matrices arising in other scientific applications. The matrices are extremely sparse and remain so when factorized. They are permutable to block triangular form, which breaks the sparse LU factorization problem into many smaller subproblems. Sparse methods based on operations on dense submatrices (supernodal and multifrontal methods) are not effective because of the extreme sparsity. KLU is a software package specifically written to exploit the properties of sparse circuit matrices. It relies on a permutation to block triangular form (BTF), several methods for finding a fill-reducing ordering (variants of approximate minimum degree and nested dissection), and Gilbert/Peierls’ sparse left-looking LU factorization algorithm to factorize each block. The package is written in C and includes a MATLAB interface. Performance results comparing KLU with SuperLU, Sparse 1.3, and UMFPACK on circuit simulation matrices are presented. KLU is the default sparse direct solver in the Xyce

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circuit simulation package developed by Sandia National Laboratories.