Solutions t o systems of linear equations and specif-ically, the LU factorization of matrices form the computational core of many scientific and engineering applications. In this paper, we present the parallelization of blocked algorithms for LU factorization. W e isolate problems inherent t o sequential blocked algorithms and provide approaches to overcome them on distributed memory architectures. The performance of the parallelized versions of three blocked algorithms suited t o column oriented Fortran is compared. Experiments are performed on the iPSC/SSO Hypercube. Our study shows that it is not intuitively clear which algorithm might perform best on a given architecture, but is dependent on the problem site and the number of available processors.
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