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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 
From: Ian Scott <ian.scott@st...>  20020328 11:01:15

Dominique wrote: > Well my feeling is that 2*n is enough. I get a good solution for > n=10,000 for 20,000 iterations. Isn't the useful termination condition really Repeat ... Until ( answer isn't moving very much  error is small  error stops moving very much ) The iterations limit is an upper bound, to stop the algorithm running forever ( which would make it a nonalgorithm.) I think Peter's mod to have an upper limit of 4*n is sensible. It is ofcourse trivial to change the value in your code using set_max_iterations() > But it takes very long. Just to check  Do you have all the optimisations turned on? Which platform/compiler are you using? Ian. 
From: Andrew Fitzgibbon <awf@ro...>  20020328 10:50:55

MATLAB will be fast for that matrix as it checks for symmetry (at the very least). Try A(i,i) = 1; A(i,i+1) = 2; A(i,i+2) = 1; > Original Message > From: vxlusersadmin@... > [mailto:vxlusersadmin@...] On Behalf Of > domi@... > Sent: 28 March 2002 10:44 > To: Vxlusers@... > Subject: Re: [Vxlusers] vnl_lsqr doesnt solve Ax=b > > > Well my feeling is that 2*n is enough. I get a good solution for > n=10,000 for 20,000 iterations. But it takes very long. Do you think I > could try using svd in my case to gain speed? > > > > > whereas for 30 equations it goes banana (wrong solution): > > > vnl_lsqr.cxx : The iteration limit ITNLIM was reached. > > > vnl_lsqr.cxx : iterations = 30 > > > > Could you try changing the # iterations to 120 in this case? > > > 60 already gave good results in my case. > > *I DONT KNOW IF THIS DOESNT DEPEND ON THE MATRIX* I used pretty naive > one: > > for (unsigned i=0; i<n; i++) { > A(i,i) = i+1.0; > b(i) = i+10.0; > } > > so the solution can be check by head. > > Domi > > > _______________________________________________ > Vxlusers mailing list > Vxlusers@... > https://lists.sourceforge.net/lists/listinfo/vxlusers > 
From: <domi@vi...>  20020328 10:44:05

Well my feeling is that 2*n is enough. I get a good solution for n=10,000 for 20,000 iterations. But it takes very long. Do you think I could try using svd in my case to gain speed? > > whereas for 30 equations it goes banana (wrong solution): > > vnl_lsqr.cxx : The iteration limit ITNLIM was reached. > > vnl_lsqr.cxx : iterations = 30 > > Could you try changing the # iterations to 120 in this case? 60 already gave good results in my case. *I DONT KNOW IF THIS DOESNT DEPEND ON THE MATRIX* I used pretty naive one: for (unsigned i=0; i<n; i++) { A(i,i) = i+1.0; b(i) = i+10.0; } so the solution can be check by head. Domi 