So just keep the "full" variable set.
Note that without the full set the true residual is not tracking the
preconditioned residual
0 KSP unpreconditioned resid norm 1.250000000000e+03 true resid norm
1.250000000000e+03 ||r(i)||/||b|| 1.000000000000e+00
1 KSP unpreconditioned resid norm 1.250000000000e+03 true resid norm
1.250000000000e+03 ||r(i)||/||b|| 1.000000000000e+00
2 KSP unpreconditioned resid norm 2.182679427760e+02 true resid norm
7.819529716916e+08 ||r(i)||/||b|| 6.255623773533e+05
3 KSP unpreconditioned resid norm 1.011652745364e+02 true resid norm
4.461678857470e+01 ||r(i)||/||b|| 3.569343085976e-02
4 KSP unpreconditioned resid norm 8.125623676015e+00 true resid norm
8.053940519499e+08 ||r(i)||/||b|| 6.443152415599e+05
5 KSP unpreconditioned resid norm 5.805247155944e+00 true resid norm
8.054105876447e+08 ||r(i)||/||b|| 6.443284701157e+05
6 KSP unpreconditioned resid norm 4.756488143441e+00 true resid norm
8.054162537433e+08 ||r(i)||/||b|| 6.443330029946e+05
7 KSP unpreconditioned resid norm 4.126450902175e+00 true resid norm
8.054191165808e+08 ||r(i)||/||b|| 6.443352932646e+05
8 KSP unpreconditioned resid norm 3.694696196953e+00 true resid norm
8.054208439360e+08 ||r(i)||/||b|| 6.443366751488e+05
9 KSP unpreconditioned resid norm 3.375152117403e+00 true resid norm
8.054219995564e+08 ||r(i)||/||b|| 6.443375996451e+05
10 KSP unpreconditioned resid norm 3.126354693526e+00 true resid norm
8.054228269923e+08 ||r(i)||/||b|| 6.443382615939e+05
meaning that the linear solver is not making any progress. With the full set
the as the preconditioned residual gets smaller the true one does as well, to
some degree
0 KSP unpreconditioned resid norm 1.250000000000e+03 true resid norm
1.250000000000e+03 ||r(i)||/||b|| 1.000000000000e+00
1 KSP unpreconditioned resid norm 1.247314056942e+03 true resid norm
1.247314056942e+03 ||r(i)||/||b|| 9.978512455538e-01
2 KSP unpreconditioned resid norm 4.860927105197e-02 true resid norm
4.776005315904e-02 ||r(i)||/||b|| 3.820804252723e-05
3 KSP unpreconditioned resid norm 4.787844580540e-02 true resid norm
4.752835483387e-02 ||r(i)||/||b|| 3.802268386709e-05
4 KSP unpreconditioned resid norm 4.437366678888e-02 true resid norm
2.756372625290e-01 ||r(i)||/||b|| 2.205098100232e-04
5 KSP unpreconditioned resid norm 1.696908986557e-05 true resid norm
5.105761919450e+00 ||r(i)||/||b|| 4.084609535560e-03
Try using right preconditioning where the preconditioned residual does not
appear -ksp_pc_side right what happens in both cases?
Barry
> On Nov 23, 2015, at 2:44 PM, Alex Lindsay <[email protected]> wrote:
>
> I've found that with a "full" variable set, I can get convergence. However,
> if I remove two of my variables (the other variables have no dependence on
> the variables that I remove; the coupling is one-way), then I no longer get
> convergence. I've attached logs of one time-step for both the converged and
> non-converged cases.
>
> On 11/23/2015 01:29 PM, Alex Lindsay wrote:
>> On 11/20/2015 02:33 PM, Jed Brown wrote:
>>> Alex Lindsay <[email protected]> writes:
>>>> I'm almost ashamed to share my condition number because I'm sure it must
>>>> be absurdly high. Without applying -ksp_diagonal_scale and
>>>> -ksp_diagonal_scale_fix, the condition number is around 1e25. When I do
>>>> apply those two parameters, the condition number is reduced to 1e17.
>>>> Even after scaling all my variable residuals so that they were all on
>>>> the order of unity (a suggestion on the Moose list), I still have a
>>>> condition number of 1e12.
>>> Double precision provides 16 digits of accuracy in the best case. When
>>> you finite difference, the accuracy is reduced to 8 digits if the
>>> differencing parameter is chosen optimally. With the condition numbers
>>> you're reporting, your matrix is singular up to available precision.
>>>
>>>> I have no experience with condition numbers, but knowing that perfect
>>>> condition number is unity, 1e12 seems unacceptable. What's an
>>>> acceptable upper limit on the condition number? Is it problem
>>>> dependent? Having already tried scaling the individual variable
>>>> residuals, I'm not exactly sure what my next method would be for
>>>> trying to reduce the condition number.
>>> Singular operators are often caused by incorrect boundary conditions.
>>> You should try a small and simple version of your problem and find out
>>> why it's producing a singular (or so close to singular we can't tell)
>>> operator.
>> Could large variable values also create singular operators? I'm essentially
>> solving an advection-diffusion-reaction problem for several species where
>> the advection is driven by an electric field. The species concentrations are
>> in a logarithmic form such that the true concentration is given by exp(u).
>> With my current units (# of particles / m^3) exp(u) is anywhere from 1e13 to
>> 1e20, and thus the initial residuals are probably on the same order of
>> magnitude. After I've assembled the total residual for each variable and
>> before the residual is passed to the solver, I apply scaling to the
>> residuals such that the sum of the variable residuals is around 1e3. But
>> perhaps I lose some accuracy during the residual assembly process?
>>
>> I'm equating "incorrect" boundary conditions to "unphysical" or
>> "unrealistic" boundary conditions. Hopefully that's fair.
>
> <logFailedSnippet.txt><logGoldSnippet.txt>
