[SciPy-dev] Sparse SVD in SciPy -- SVDPACK[C] made available
Fri Apr 24 01:13:24 CDT 2009
> 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.
> He asked that we let him know whether we'd like to use the Fortran or
> the C version. Which would best suit SciPy? I have a tendency to
> prefer SVDPACKC, since we can reach it easily via Cython.
Is there a speed difference between the two? If it's significantly
faster using Fortran, some would prefer it.
More information about the Scipy-dev