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In this paper, a method via sparse-sparse iteration for computing a sparseincomplete factorization of the inverse of a symmetric positive definite matrixis proposed. The resulting factorized sparse approximate inverse is used as apreconditioner for solving symmetric positive definite linear systems ofequations by using the preconditioned conjugate gradient algorithm. Somenumerical experiments on test matrices from the Harwell-Boeing collection forcomparing the numerical performance of the presented method with one availablewell-known algorithm are also given.

A Sparse-Sparse Iteration for Computing a Sparse Incomplete Factorization of the Inverse of an SPD Matrix