[petsc-users] [petsc-3.2] LSQR new convergence test

[Barry Smith]

On Sep 21, 2011, at 2:39 AM, Alexander Grayver wrote:

> Hong, Barry,
> 
> Thanks! Sorry for not to be clear, but Barry right, my question was how to get back to DefaultConvergenceTest in case of LSQR solver.
> 
> Barry, yes, both versions give the same two norms.
> 
> Can you clarify please how to implement that in Fortran:
> void *cctx;
> KSPDefaultConvergedCreate(&cctx);
> KSPSetConvergenceTest(ksp,KSPDefaultConverged,cctx);

   It should be almost the same

    PetscFortranAddr cctx

    call KSPDefaultConvergedCreate(cctx,ierr)
    call KSPSetConvergenceTest(ksp,KSPDefaultConverged,cctx,PETSC_NULL_FUNCTION,ierr)

   Barry


> 
> I'm a little bit confused about cctx parameter.
> 
> Regards,
> Alexander
> 
> 
> On 21.09.2011 01:10, Barry Smith wrote:
>> It has its own monitor that provides additional information  -ksp_monitor_lsqr
>> 
>> You can also remove the new convergence test and get back the old one with code like
>> 
>> void *cctx;
>> KSPDefaultConvergedCreate(&cctx);
>> KSPSetConvergenceTest(ksp,KSPDefaultConverged,cctx);
>> 
>> after the KSPType is set to LSQR. So if you are happy with the old test.
>> 
>> 
>>   Do both versions give the same first two norms?
>> 
>>> 0 KSP Residual norm 9.386670021557e-17
>>>  1 KSP Residual norm 8.258308650175e-17
>>   Barry
>> 
>> 
>> On Sep 20, 2011, at 4:40 AM, Alexander Grayver wrote:
>> 
>>> Hello,
>>> 
>>> In comparison with petsc-3.1-p7 in the latest petsc LSQR solver behaves differently.
>>> 
>>> In petsc31 I had:
>>> 
>>>  0 KSP Residual norm 9.386670021557e-17
>>> ...
>>> 95 KSP Residual norm 9.341367317075e-18
>>> Linear solve converged due to CONVERGED_RTOL iterations 95
>>> KSP Object:
>>>  type: lsqr
>>>  maximum iterations=200, initial guess is zero
>>>  tolerances:  relative=0.1, absolute=1e-50, divergence=10000
>>>  left preconditioning
>>>  using PRECONDITIONED norm type for convergence test
>>> PC Object:
>>>  type: none
>>>  linear system matrix = precond matrix:
>>>  Matrix Object:
>>>    type=shell, rows=19584, cols=19584
>>> 
>>> relative residual norm =    0.9951737192872134E-01
>>> 
>>> Now, with petsc32 I have:
>>> 
>>>  0 KSP Residual norm 9.386670021557e-17
>>>  1 KSP Residual norm 8.258308650175e-17
>>> Linear solve converged due to CONVERGED_RTOL_NORMAL iterations 1
>>> KSP Object: 12 MPI processes
>>>  type: lsqr
>>>  maximum iterations=200, initial guess is zero
>>>  tolerances:  relative=0.1, absolute=1e-50, divergence=10000
>>>  left preconditioning
>>>  using UNPRECONDITIONED norm type for convergence test
>>> PC Object: 12 MPI processes
>>>  type: none
>>>  linear system matrix = precond matrix:
>>>  Matrix Object:   12 MPI processes
>>>    type: shell
>>>    rows=19584, cols=19584
>>> relative residual norm =    0.8797910900468064E+00
>>> 
>>> So I found new convergence test here which sets CONVERGED_RTOL_NORMAL:
>>> http://www.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-current/docs/manualpages/KSP/KSPLSQRDefaultConverged.html
>>> 
>>> The question is, how to interpret this new test and make it works properly for me?
>>> Thanks in advance.
>>> 
>>> Regards,
>>> Alexander
>