Abstract
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 XyceTMcircuit simulation package developed by Sandia National Laboratories.
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Acknowledgements
We would like to thank Mike Heroux for coining the name “KLU” and suggesting that we tackle this project in support of the Xyce circuit simulation package developed at Sandia National Laboratories [19, 25]. Portions of this work were supported by the Department of Energy, and by National Science Foundation grants 0203270, 0620286, and 0619080.
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Davis, T.A., Natarajan, E.P. (2012). Sparse Matrix Methods for Circuit Simulation Problems. In: Michielsen, B., Poirier, JR. (eds) Scientific Computing in Electrical Engineering SCEE 2010. Mathematics in Industry(), vol 16. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-22453-9_1
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