[petsc-users] Using -ts_type sundials with -snes-fd

[Geoff Oxberry]

Peter,

You are correct. Here is the output (now with petsc-dev changeset: 23668:a876ee8e66fd):

goxberry$ ./ex8 -problem_type rober -ts_type sundials -ts_view
TS Object: 1 MPI processes
  type: sundials
  maximum steps=1000
  maximum time=1e+11
  total number of nonlinear solver iterations=3739
  total number of nonlinear solve failures=0
  total number of linear solver iterations=3739
  total number of rejected steps=0
  Sundials integrater does not use SNES!
  Sundials integrater type BDF: backward differentiation formula
  Sundials abs tol 1e-06 rel tol 1e-06
  Sundials linear solver tolerance factor 0.05
  Sundials max dimension of Krylov subspace 5
  Sundials using unmodified (classical) Gram-Schmidt for orthogonalization in GMRES
  Sundials suggested factor for tolerance scaling 1
  Sundials cumulative number of internal steps 1000
  Sundials no. of calls to rhs function 1931
  Sundials no. of calls to linear solver setup function 0
  Sundials no. of error test failures 16
  Sundials no. of nonlinear solver iterations 1930
  Sundials no. of nonlinear convergence failure 204
  Sundials no. of linear iterations 3739
  Sundials no. of linear convergence failures 0
  PC Object:   1 MPI processes
    type: none
  Sundials no. of preconditioner evaluations 0
  Sundials no. of preconditioner solves 0
  Sundials no. of Jacobian-vector product evaluations 3739
  Sundials no. of rhs calls for finite diff. Jacobian-vector evals 3739
steps 1000 (0 rejected, 0 SNES fails), ftime 744.845, nonlinits 3739, linits 3739

I use Sundials mostly with finite difference Jacobians, but I also provide Jacobian matrices where I can (which would be another helpful feature).

Cheers,

Geoff

On Jun 21, 2012, at 10:52 AM, Peter Brune wrote:

> I asked my question because it might be happening automatically.  His output looked like the equation was solved.  A brief google search on this makes it look like they do this anyways.  In addition: 
> 
> http://www.mcs.anl.gov/petsc/petsc-dev/src/ts/impls/implicit/sundials/sundials.c.html#TSView_Sundials
> 
> directly refers to "Sundials no. of rhs calls for finite diff. Jacobian-vector evals."
> 
> - Peter
> 
> On Thu, Jun 21, 2012 at 9:48 AM, Matthew Knepley <knepley at gmail.com> wrote:
> On Thu, Jun 21, 2012 at 8:45 AM, Peter Brune <prbrune at gmail.com> wrote:
> What do you see when you run with -ts_view?
> 
> - Peter
> 
> 
> On Thu, Jun 21, 2012 at 9:40 AM, Geoff Oxberry <goxberry at gmail.com> wrote:
> Peter,
> 
> Just wanted to make sure there wasn't some Sundials-specific option for finite difference Jacobians that I was missing; despite reading the manual, it's a large package, and it's easy to miss things. If that's the case, I'd like to make a feature request for such an option.
> 
> If I understand correctly, you want a MF Jacobian with Sundials. We can't do that because Sundials is completely
> closed package, which we cannot pry apart to insert something like this. The alternative is to use the stuff solvers
> we currently have in TS. I thought that you had used the Rosenbrock-W stuff. Is this sufficient?
> 
>   Thanks,
> 
>       Matt
>  
> Geoff
> 
> On Jun 21, 2012, at 9:53 AM, Peter Brune wrote:
> 
>> Note that in the code in ts/impls/implicit/sundials it says:
>> 
>> This uses its own nonlinear solver and krylov method so PETSc SNES and KSP options do not apply...
>> 
>> - Peter
>> 
>> On Jun 21, 2012 7:59 AM, "Geoff Oxberry" <goxberry at gmail.com> wrote:
>> Running the following example from PETSC 3.3.0-dev (changeset: 23631:0e86ac5e4170)
>> 
>> /path/to/petsc-dev/src/ts/examples/tutorials/ex8 -problem_type rober -snes_fd -ts_type sundials
>> 
>> gives the following output
>> 
>> steps 1000 (0 rejected, 0 SNES fails), ftime 744.845, nonlinits 3739, linits 3739
>> WARNING! There are options you set that were not used!
>> WARNING! could be spelling mistake, etc!
>> Option left: name:-snes_fd no value
>> 
>> Just to confirm, is it currently impossible to use a finite difference Jacobian matrix in concert with CVODE? If so, could this feature be implemented in a future release? I currently rely on Sundials to integrate stiff systems of ODEs, and for my application, it is impractical to derive an analytical Jacobian matrix. (It is an issue I've discussed both with Jed and Matt on another forum.)
>> 
>> Cheers,
>> 
>> Geoff
> 
> 
> 
> 
> 
> -- 
> What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead.
> -- Norbert Wiener
> 

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