Efficient sparse matrix factorization for circuit simulation on vector supercomputers

An efficient approach to sparse matrix factorization on vector supercomputers is described. The approach is suitable for application domains like circuit simulation that require the repeated direct solution of sparse linear systems of equations with identical zero-nonzero structures. An overlap-scatter data structure is used to represent the sparse matrix, enabling the use of multiple operand access modes to achieve higher performance than earlier proposed approaches. The superior performance of the new solver is demonstrated using a number of matrices derived from circuit simulation runs.<
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