Hi Justin,
since you're talking about possible issues with optimised/non-optimised
Firedrake, I checked if this had something to do with COFFEE, but it really
seems it doesn't, so I'm not sure what's going on. Maybe the others can
help.
-- Fabio
2016-06-01 9:44 GMT+02:00 Justin Chang <jychang48(a)gmail.com>:
> Hi all,
>
> So we have been attempting to convert a FEniCS implementation of a
> semi-linear diffusion code into Firedrake. Mainly because we want to employ
> PETSc/TAO's optimization routines, which FEniCS does not let us do.
> However, the Firedrake implementation is not working, namely our consistent
> Newton-Raphson approach.
>
> Attached is the FEniCS code (P3_Galerkin_NR.py) and the firedrake code
> (NR_Nonlinear_poisson.py). For FEniCS you may just run the code as "python
> P3_Galerkin_NR.py" but for the firedrake code you must run as:
>
> python NR_Nonlinear_poisson.py 50 50 0
>
> For the FEniCS code, this is my solver output:
>
> >> python P3_Galerkin_NR.py
> Calling FFC just-in-time (JIT) compiler, this may take some time.
> Calling FFC just-in-time (JIT) compiler, this may take some time.
> Solving linear variational problem.
> iter=1: norm=1
> Solving linear variational problem.
> iter=2: norm=0.0731224
> Solving linear variational problem.
> iter=3: norm=0.00217701
> Solving linear variational problem.
> iter=4: norm=1.64398e-06
> Solving linear variational problem.
> iter=5: norm=8.89289e-13
>
> but for Firedrake, i have this:
>
> >> python NR_Nonlinear_poisson.py 50 50 0
> COFFEE finished in 0.00142097 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00103188 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00173187 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00173306 seconds (flops: 0 -> 0)
> COFFEE finished in 0.0015831 seconds (flops: 0 -> 0)
> COFFEE finished in 0.000972033 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00118279 seconds (flops: 2 -> 2)
> COFFEE finished in 0.000946999 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00165105 seconds (flops: 1 -> 1)
> Error norm: 2.193e-01
> Error norm: 4.697e-02
> Error norm: 4.830e-02
> Error norm: 8.437e-02
> Error norm: 2.740e-01
> Error norm: 2.872e+00
> Error norm: 8.993e+02
> Error norm: 1.912e+10
> Error norm: 1.919e+32
> Error norm: 1.981e+98
> Traceback (most recent call last):
> File "NR_Nonlinear_poisson.py", line 119, in <module>
> solver.solve(u_k1,b)
> File
> "/home/justin/Software/firedrake/src/firedrake/firedrake/linear_solver.py",
> line 153, in solve
> raise RuntimeError("LinearSolver failed to converge after %d
> iterations with reason: %s", self.ksp.getIterationNumber(),
> solving_utils.KSPReasons[r])
> RuntimeError: ('LinearSolver failed to converge after %d iterations with
> reason: %s', 0, 'DIVERGED_NANORINF')
>
>
> I strongly believe there are no inconsistencies between our FEniCS and
> Firedrake codes (in terms of what we want to solve) but for some reason the
> latter blows up. However, if I run the optimization version of the
> Firedrake code, my solver converges quadratically as expected:
>
> >> python NR_Nonlinear_poisson.py 50 50 1
> COFFEE finished in 0.00143099 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00164199 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00169611 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00169706 seconds (flops: 0 -> 0)
> COFFEE finished in 0.00153899 seconds (flops: 0 -> 0)
> COFFEE finished in 0.000952005 seconds (flops: 0 -> 0)
> COFFEE finished in 0.000900984 seconds (flops: 1 -> 1)
> COFFEE finished in 0.000989914 seconds (flops: 0 -> 0)
> Error norm: 2.193e-01
> Error norm: 1.626e-02
> Error norm: 4.870e-04
> Error norm: 9.332e-07
> Error norm: 0.000e+00
>
> When I compare the pvd plots between the FEniCS and Firedrake (with
> optimization), Firedrake seems correct qualitatively (i.e., the negative
> concentrations are gone). But I am confused why the non-optimization
> implementation of firedrake does not converge whereas the FEniCS one does.
>
> Any thoughts?
>
> Thanks!
> Justin
>