[petsc-users] Tao iterations
Jason Sarich
jason.sarich at gmail.com
Tue Apr 21 10:40:55 CDT 2015
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
>>>>>>>>>
>>>>>>>>>
>>>>>>>
>>>>>>
>>>>>
>>>>
>>>
>>
>
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