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SVDPACK comprises four numerical (iterative) methods for computing the singular value decomposition (SVD) of large sparse matrices using double precision ANSI Fortran-77. A compatible ANSI-C version (SVDPACKC) is also available. This software package implements Lanczos and subspace iteration-based methods for determining several of the largest singular triplets (singular values and corresponding left- and right-singular vectors) for large sparse matrices. The package has been ported to a variety of machines ranging from supercomputers to workstations: CRAY Y-MP, CRAY-2S, Alliant FX/80, SPARCstation 10, IBM RS/6000-550, DEC 5000-100, and HP 9000-750. The development of SVDPACK wa motivated by the need to compute large rank approximations to sparse term-document matrices from information retrieval applications. Future updates to SVDPACK(C), will include out-of-core updating strategies, which can be used, for example, to handle extremely large sparse matrices (on the order of a million rows or columns) associated with extremely large databases in query-based information retrieval applications.

around 1993-5, no copyright info I could find in a hurry

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Martin Spernau
© 1994-2003

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