Two level parallel preconditioning derived from an approximate inverse based on the Sherman--Morrison formula

Linjie Zhang, Kentaro Moriya, Takashi Nodera


The AISM (Approximate Inverse based on the Sherman--Morrison Formula) method is one of the existing effective methods for computing an approximate inverse. This algorithm was proposed by Bru et al. [SIAM J. Sci. Comput., 25, pp.701--715 (2003)]. Although it has been showed that the aism is generally a stable option for large linear systems of equations, its computation cost can be prohibitively high. Complications also arise when an attempt is made to parallelize the algorithm, since a sequential process is necessary. This article proposes a two level AISM in which the coefficient matrix is rearranged to a block form, which is more suitable for parallel computation. This technique can also significantly speed-up computations on a single processor. We implemented this technique on an Origin 2400 system with an MPI to illustrate its efficiency through numerical experiments.

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sparse linear system of equation, GMRES(m), approximate inverse, Sherman-Morrison formula, Two level parallel computation

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