Hi Ellen, It looks like you’re using the old unconstrained CG code. This will be deprecated in the near future in favor of the newer bound-constrained CG algorithm (TAOBNCG) that can also solve unconstrained problems when the user does not specify any bounds on the problem.
The newer TAOBNCG algorithm implements a preconditioner that significantly improves the scaling of the search direction and helps the line search accept the unit step length most of the time. I would recommend making sure that you’re on PETSc version 3.11 or newer, and then switching to this with “-tao_type bncg”. You will not need to change any of your code to do this. If you still fail to converge, please send a new log with the new algorithm and we can evaluate the next steps. — Alp Dener Postdoctoral Researcher Argonne National Laboratory https://www.anl.gov/profile/alp-dener On February 26, 2020 at 6:01:34 PM, Ellen Price ([email protected]<mailto:[email protected]>) wrote: Hi Jed, Thanks for getting back to me! Here's the output for my CG config. Sorry it's kind of a lot. Ellen On Wed, Feb 26, 2020 at 12:43 PM Jed Brown <[email protected]<mailto:[email protected]>> wrote: Could you share output for your current configuration with -tao_monitor -tao_ls_monitor -tao_view? "Ellen M. Price" <[email protected]<mailto:[email protected]>> writes: > Hello PETSc users! > > I am using Tao for an unconstrained minimization problem. I have found > that CG works better than the other types for this application. After > about 85 iterations, I get an error about line search failure. I'm not > clear on what this means, or how I could mitigate the problem, and > neither the manual nor FAQ give any guidance. Can anyone suggest things > I could try to help the method converge? I have function and gradient > info, but no Hessian. > > Thanks, > Ellen Price
