Abstract
This paper presents a column-oriented distributed algorithm for factoring a large sparse symmetric positive definite matrix on a local-memory parallel processor. Processors cooperate in computing each column of the Cholesky factor by calculating independent updates to the corresponding column of the original matrix. These updates are sent in a fan-in manner to the processor assigned to the column, which then completes the computation. Experimental results on an Intel iPSC/2 hypercube demonstrate that the method is effective and achieves good speedups.
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