From: <domi@vi...>  20020328 15:46:46

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 