Parallel Solution Techniques for Sparse Linear Systems in Circuit Simulation
For solving sparse linear systems from circuit simulation whose coefficient matrices include a few dense rows and columns, a parallel Bi-CGSTAB algorithm with distributed Schur complement (DSC) preconditioning is presented. The parallel efficiency of the solver is increased by transforming the equation system into a problem without dense rows and columns as well as by exploitation of parallel graph partitioning methods. The costs of local, incomplete LU decompositions are decreased by fill-in reducing reordering methods of the matrix and a threshold strategy for the factorization. The efficiency of the parallel solver is demonstrated with real circuit simulation problems on a PC cluster.
KeywordsOuter Iteration Circuit Simulation Direct Solver Sparsity Pattern Sparse Linear System
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