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
