[petsc-users] sources of floating point randomness in JFNK in serial

[Mark Adams]

If you are using MG what is the coarse grid solver?
-snes_view might give you that.

On Thu, May 4, 2023 at 8:25 AM Matthew Knepley <knepley at gmail.com> wrote:

> On Thu, May 4, 2023 at 8:21 AM Mark Lohry <mlohry at gmail.com> wrote:
>
>> Do they start very similarly and then slowly drift further apart?
>>
>>
>> Yes, this. I take it this sounds familiar?
>>
>> See these two examples with 20 fixed iterations pasted at the end. The
>> difference for one solve is slight (final SNES norm is identical to 5
>> digits), but in the context I'm using it in (repeated applications to solve
>> a steady state multigrid problem, though here just one level) the
>> differences add up such that I might reach global convergence in 35
>> iterations or 38. It's not the end of the world, but I was expecting that
>> with -np 1 these would be identical and I'm not sure where the root cause
>> would be.
>>
>
> The initial KSP residual is different, so its the PC. Please send the
> output of -snes_view. If your ASM is using direct factorization, then it
> could be randomness in whatever LU you are using.
>
>   Thanks,
>
>     Matt
>
>
>>   0 SNES Function norm 2.801842107848e+04
>>     0 KSP Residual norm 4.045639499595e+01
>>     1 KSP Residual norm 1.917999809040e+01
>>     2 KSP Residual norm 1.616048521958e+01
>> [...]
>>    19 KSP Residual norm 8.788043518111e-01
>>    20 KSP Residual norm 6.570851270214e-01
>>   Linear solve converged due to CONVERGED_ITS iterations 20
>>   1 SNES Function norm 1.801309983345e+03
>> Nonlinear solve converged due to CONVERGED_ITS iterations 1
>>
>>
>> Same system, identical initial 0 SNES norm, 0 KSP is slightly different
>>
>>   0 SNES Function norm 2.801842107848e+04
>>     0 KSP Residual norm 4.045639473002e+01
>>     1 KSP Residual norm 1.917999883034e+01
>>     2 KSP Residual norm 1.616048572016e+01
>> [...]
>>    19 KSP Residual norm 8.788046348957e-01
>>    20 KSP Residual norm 6.570859588610e-01
>>   Linear solve converged due to CONVERGED_ITS iterations 20
>>   1 SNES Function norm 1.801311320322e+03
>> Nonlinear solve converged due to CONVERGED_ITS iterations 1
>>
>> On Wed, May 3, 2023 at 11:05 PM Barry Smith <bsmith at petsc.dev> wrote:
>>
>>>
>>>   Do they start very similarly and then slowly drift further apart? That
>>> is the first couple of KSP iterations they are almost identical but then
>>> for each iteration get a bit further. Similar for the SNES iterations,
>>> starting close and then for more iterations and more solves they start
>>> moving apart. Or do they suddenly jump to be very different? You can run
>>> with -snes_monitor -ksp_monitor
>>>
>>> On May 3, 2023, at 9:07 PM, Mark Lohry <mlohry at gmail.com> wrote:
>>>
>>> This is on a single MPI rank. I haven't checked the coloring, was just
>>> guessing there. But the solutions/residuals are slightly different from run
>>> to run.
>>>
>>> Fair to say that for serial JFNK/asm ilu0/gmres we should expect bitwise
>>> identical results?
>>>
>>>
>>> On Wed, May 3, 2023, 8:50 PM Barry Smith <bsmith at petsc.dev> wrote:
>>>
>>>>
>>>>   No, the coloring should be identical every time. Do you see
>>>> differences with 1 MPI rank? (Or much smaller ones?).
>>>>
>>>>
>>>>
>>>> > On May 3, 2023, at 8:42 PM, Mark Lohry <mlohry at gmail.com> wrote:
>>>> >
>>>> > I'm running multiple iterations of newtonls with an MFFD/JFNK
>>>> nonlinear solver where I give it the sparsity. PC asm, KSP gmres, with
>>>> SNESSetLagJacobian -2 (compute once and then frozen jacobian).
>>>> >
>>>> > I'm seeing slight (<1%) but nonzero differences in residuals from run
>>>> to run. I'm wondering where randomness might enter here -- does the
>>>> jacobian coloring use a random seed?
>>>>
>>>>
>>>
>
> --
> 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
>
> https://www.cse.buffalo.edu/~knepley/
> <http://www.cse.buffalo.edu/~knepley/>
>
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