[petsc-users] Tao iterations
Justin Chang
jchang27 at uh.edu
Tue Apr 28 22:19:28 CDT 2015
Jason (or anyone),
I am noticing that the iteration numbers reported by TaoGetSolutionStatus()
for blmvm differ whenever I change the number of processes. The solution
seems to remain the same though. Is there a reason why this could be
happening?
Thanks,
On Tue, Apr 21, 2015 at 10:40 AM, Jason Sarich <jason.sarich at gmail.com>
wrote:
> Justin,
>
> 1) The big difference between TRON and BLMVM is that TRON requires hessian
> information, BLMVM only uses gradient information. Thus TRON will usually
> converge faster, but requires more information, memory, and a KSP solver.
> GPCG (gradient projected conjugate gradient) is another gradient-only
> option, but usually performs worse than BLMVM.
>
> 2) TaoGetLinearSolveIterations() will get the total number of KSP
> iterations per solve
>
> Jason
>
>
> On Tue, Apr 21, 2015 at 10:33 AM, Justin Chang <jychang48 at gmail.com>
> wrote:
>
>> Jason,
>>
>> Tightening the tolerances did the trick. Thanks. Though I do have a
>> couple more related questions:
>>
>> 1) Is there a general guideline for choosing tron over blmvm or vice
>> versa? Also is there another tao type that is also suitable given only
>> bounded constraints?
>>
>> 2) Is it possible to obtain the total number of KSP and/or PG iterations
>> from tron?
>>
>> Thanks,
>> Justin
>>
>> On Tue, Apr 21, 2015 at 9:52 AM, Jason Sarich <jason.sarich at gmail.com>
>> wrote:
>>
>>> Hi Justin,
>>>
>>> blmvm believes that it is already sufficiently close to a minimum, so it
>>> doesn't do anything. You may need to tighten some of the tolerance to force
>>> an iteration.
>>>
>>> Jason
>>>
>>>
>>> On Tue, Apr 21, 2015 at 9:48 AM, Justin Chang <jychang48 at gmail.com>
>>> wrote:
>>>
>>>> Time step 1:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0663148
>>>> Objective value=-55.5945
>>>> total number of iterations=35, (max: 2000)
>>>> total number of function/gradient evaluations=37, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 2:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0682307
>>>> Objective value=-66.9675
>>>> total number of iterations=23, (max: 2000)
>>>> total number of function/gradient evaluations=25, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 3:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0680522
>>>> Objective value=-71.8211
>>>> total number of iterations=19, (max: 2000)
>>>> total number of function/gradient evaluations=22, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 4:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0551556
>>>> Objective value=-75.1252
>>>> total number of iterations=18, (max: 2000)
>>>> total number of function/gradient evaluations=20, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 5:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0675667
>>>> Objective value=-77.4414
>>>> total number of iterations=6, (max: 2000)
>>>> total number of function/gradient evaluations=8, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 6:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.059143
>>>> Objective value=-79.5007
>>>> total number of iterations=3, (max: 2000)
>>>> total number of function/gradient evaluations=5, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 7:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0433683
>>>> Objective value=-81.3546
>>>> total number of iterations=5, (max: 2000)
>>>> total number of function/gradient evaluations=8, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 8:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0840676
>>>> Objective value=-82.9382
>>>> total number of iterations=0, (max: 2000)
>>>> total number of function/gradient evaluations=1, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 9:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0840676
>>>> Objective value=-82.9382
>>>> total number of iterations=0, (max: 2000)
>>>> total number of function/gradient evaluations=1, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>> Time step 10:
>>>>
>>>> Tao Object: 1 MPI processes
>>>> type: blmvm
>>>> Gradient steps: 0
>>>> TaoLineSearch Object: 1 MPI processes
>>>> type: more-thuente
>>>> Active Set subset type: subvec
>>>> convergence tolerances: fatol=0.0001, frtol=0.0001
>>>> convergence tolerances: gatol=0, steptol=0, gttol=0
>>>> Residual in Function/Gradient:=0.0840676
>>>> Objective value=-82.9382
>>>> total number of iterations=0, (max: 2000)
>>>> total number of function/gradient evaluations=1, (max: 4000)
>>>> Solution converged: estimated |f(x)-f(X*)|/|f(X*)| <= frtol
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> On Tue, Apr 21, 2015 at 9:28 AM, Jason Sarich <jason.sarich at gmail.com>
>>>> wrote:
>>>>
>>>>> Hi Justin,
>>>>>
>>>>> what reason is blmvm giving for stopping the solve? (you can use
>>>>> -tao_view or -tao_converged_reason to get this)
>>>>>
>>>>> Jason
>>>>>
>>>>> On Mon, Apr 20, 2015 at 6:32 PM, Justin Chang <jychang48 at gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Jason,
>>>>>>
>>>>>> I am using TaoGetSolutionStatus(tao,&its, ...) and it gives me
>>>>>> exactly what I want. However, I seem to be having an issue with blmvm
>>>>>>
>>>>>> I wrote my own backward euler code for a transient linear diffusion
>>>>>> problem with lower bounds >= 0 and upper bounds <= 1. For the first several
>>>>>> time steps I am getting its > 0, and it decreases over time due to the
>>>>>> nature of the discrete maximum principles. However, at some point my its
>>>>>> become 0 and the solution does not "update", which seems to me that
>>>>>> TaoSolve is not doing anything after that. This doesn't happen if I were to
>>>>>> use tron (my KSP and PC are cg and jacobi respectively).
>>>>>>
>>>>>> Do you know why this behavior may occur?
>>>>>>
>>>>>> Thanks,
>>>>>>
>>>>>> On Tue, Apr 14, 2015 at 9:35 AM, Jason Sarich <jason.sarich at gmail.com
>>>>>> > wrote:
>>>>>>
>>>>>>> Hi Justin,
>>>>>>>
>>>>>>> I have pushed these changes to the "next" branch, your code
>>>>>>> snippet should work fine there.
>>>>>>>
>>>>>>> Note that there is also available (since version 3.5.0) the
>>>>>>> routine TaoGetSolutionStatus(tao,&its,NULL,NULL,NULL,NULL,NULL) which will
>>>>>>> provide the
>>>>>>> same information
>>>>>>>
>>>>>>> Jason
>>>>>>>
>>>>>>> On Fri, Apr 10, 2015 at 6:28 PM, Justin Chang <jychang48 at gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>> Whatever is convenient and/or follow the "PETSc" standards.
>>>>>>>> Something similar to SNESGetIterationNumber() or KSPGetIterationNumber()
>>>>>>>> would be nice. Ideally I want my code to look like this:
>>>>>>>>
>>>>>>>> ierr = TaoGetIterationNumber(tao,&its);CHKERRQ(ierr);
>>>>>>>> ierr = PetscPrintf(PETSC_COMM_WORLD, "Number of Tao iterations =
>>>>>>>> %D\n", its);
>>>>>>>>
>>>>>>>> Thanks :)
>>>>>>>>
>>>>>>>> On Fri, Apr 10, 2015 at 5:53 PM, Jason Sarich <
>>>>>>>> jason.sarich at gmail.com> wrote:
>>>>>>>>
>>>>>>>>> Hi Justin, I'll get this in. I assume that displaying the number
>>>>>>>>> of iterations with tao_converged_reason is what you are asking for in
>>>>>>>>> particular? Or did you have something else in mind?
>>>>>>>>>
>>>>>>>>> Jason
>>>>>>>>> On Apr 10, 2015 16:42, "Smith, Barry F." <bsmith at mcs.anl.gov>
>>>>>>>>> wrote:
>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> Justin,
>>>>>>>>>>
>>>>>>>>>> Sorry TAO simply doesn't even collect this information
>>>>>>>>>> currently. But yes we should definitely make it available!
>>>>>>>>>>
>>>>>>>>>> Jason,
>>>>>>>>>>
>>>>>>>>>> Could you please add this; almost all the TaoSolve_xxx()
>>>>>>>>>> have a local variable iter; change that to tao->niter (I'm guess this is
>>>>>>>>>> suppose to capture this information) and add a TaoGetIterationNumber() and
>>>>>>>>>> the uses can access this. Also modify at the end of TaoSolve()
>>>>>>>>>> -tao_converged_reason to also print the iteration count. At the same time
>>>>>>>>>> since you add this you can add a tao->totalits which would accumulate all
>>>>>>>>>> iterations over all the solves for that Tao object and the routine
>>>>>>>>>> TaoGetTotalIterations() to access this. Note that TaoSolve() would
>>>>>>>>>> initialize tao->niter = 0 at the top.
>>>>>>>>>>
>>>>>>>>>> Thanks
>>>>>>>>>>
>>>>>>>>>> Barry
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>> > On Apr 10, 2015, at 4:16 PM, Justin Chang <jchang27 at uh.edu>
>>>>>>>>>> wrote:
>>>>>>>>>> >
>>>>>>>>>> > Hi all,
>>>>>>>>>> >
>>>>>>>>>> > Is there a way to generically obtain the number of Tao
>>>>>>>>>> iterations? I am looking through the -help options for Tao and I don't see
>>>>>>>>>> any metric where you can output this quantity in the manner that you could
>>>>>>>>>> for SNES or KSP solves. I am currently using blmvm and tron, and the only
>>>>>>>>>> way I can see getting this metric is by outputting -tao_view and/or
>>>>>>>>>> -tao_monitor and manually finding this number. I find this cumbersome
>>>>>>>>>> especially for transient problems where I would like to simply have this
>>>>>>>>>> number printed for each step instead of ending up with unnecessary info.
>>>>>>>>>> >
>>>>>>>>>> > Thanks,
>>>>>>>>>> >
>>>>>>>>>> >
>>>>>>>>>> > --
>>>>>>>>>> > Justin Chang
>>>>>>>>>> > PhD Candidate, Civil Engineering - Computational Sciences
>>>>>>>>>> > University of Houston, Department of Civil and Environmental
>>>>>>>>>> Engineering
>>>>>>>>>> > Houston, TX 77004
>>>>>>>>>> > (512) 963-3262
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
--
Justin Chang
PhD Candidate, Civil Engineering - Computational Sciences
University of Houston, Department of Civil and Environmental Engineering
Houston, TX 77004
(512) 963-3262
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