A Toolbox for Computing the Singular Value Decomposition on Distributed Memory Computers a Toolbox for Computing the Singular Value Decomposition on Distributed Memory Computers
نویسنده
چکیده
We present a parallel software implementation for computing the singular value decomposition (SVD) of general, banded or bidiagonal matrices. First, the matrix is reduced to bidiagonal form. This reduction can be rearranged in a way that allows heavy use of matrix-matrix operations. Then the singular values are computed in an iterative process. Finally the singular vectors are computed independently. The methods are compared to the ScaLAPACK library with respect to accuracy, stability and performance on parallel computers.
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