Hello,
there is no driver for the banded SVD problem in LAPACK. Basically if
you want to solve the banded SVD problem what the documentation is
saying is that you need to do it yourself.
There is one driver for general matrix SVD problem (xGESVD), it calls
xGEBRD (reduction of a general matrix to bidiagonal form) and then
xBDSQR (compute the singular values of a bidiagonal matrix using QR
algorithm).
To make your own driver for the banded matrix SVD problem, you first
call xGBBRD (reduction of a banded matrix to bidiagonal form) and then
xBDSQR (compute the singular values of a bidiagonal matrix using QR
algorithm).
If you want both singular vector basis as well, you can call xGBBRD
with option VECT='B' (or 'Q' if only left or 'P' if only right), and
give those vectors to xBDSQR with NCVT and NRU correctly set.
I have never tried it personnally but that's what I understand from the
documentation.
Best wishes,
Julien Langou.
-------- Original Message --------
Subject: LAPACK documentation doubt
Date: Mon, 20 Feb 2006 09:27:38 -0500 (EST)
From: srajaman@Domain.Removed
Hi
In LAPACK's documentation of the singular value decomposition driver,
it mentions that xGBBRD will be called if input matrix is banded. But
when I look at the actual source of SVD driver routine, I don't see
any calls to DGBBRD. Is there any reason why it wasn't called. I am
using the documentation at http://www.netlib.org/lapack/lug/node53.html
Thanks
Siva Rajamanickam.
w
_______________________________________________
Lapack mailing list
Lapack@Domain.Removed
http://lists.cs.utk.edu/listinfo/lapack