Hi,
You were right, Matlab gets dramatically slower with nonsymmetric
nononlydiagonal matrix.
for (signed i=0; i<n; i++) {
A(i,i) = 1.0;
if( (i+1)<=(n1) && (i1)>=0 ){
A(i,i+1) = 2.0;
A(i,i1) = 1.0;
}
b(i) = i+1.0;
}
Actually matlab gets far slower compared to
vnl_lsqr but on the test system (above) I have:
vnl_lsqr.cxx : The equations A*x = b are probably compatible. Norm(A*x
 b) is as small as seems reasonable on this machine.
vnl solves this (n=3000) very quickly while matlab chews it much
longer.
n=10,000 is solved by vnl in 1.5 min on my machine, matlab after a
longer while crashes screaming for memory.

I have all optimisations on. I am using solaris with gcc2.95.
No things like netscape running in bg, or two calculations running at
the same time.

I still will try svd today, just to compare.
thank you for feedback
dominique
