Abstract
A practical out-of-core Cholesky factorization scheme is introduced that is based on reorganizations of the matrix data structure during the factorization. It is applicable to the factorization of both dense and sparse matrices. The scheme can be regarded as a simple extension of the conventional in-core sparse factorization method. It is highly adaptive in the sense that it will run successfully in a range of storage sizes. Experimental results on some large sparse practical problems are provided; they show significant reduction in storage requirement for Cholesky factors with little increase (and sometimes decrease) in execution time.
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