> I tried
> to use the same trick as in step-22, where an InnerPreconditioner was
> defined to switch between SparseDirectUMFPACK in 2D and SparseILU in 3D.
> However I found that SparseILU won't work even when in small 2D cases. To
> verify this I tried to replace the SparseDirectUMFPACK in step-57 with
> SparseILU, same thing happened. Without additional off-diagonals the GMRES
> solver won't converge; with additional off-diagonals, the program runs
> unbearably slow. Why is the performance of SparseILU so much worse than
> SparseDirectUMFPACK? Am I using it the right way?

Do you have an inner inner solve or do you just use a single SparseILU
application?

ILU is not great in 3d. This is even true if you consider the velocity
block of the Stokes problem (which is Laplace-like). See the tables in
https://urldefense.proofpoint.com/v2/url?u=https-3A__www.dealii.org_8.5.0_doxygen_deal.II_step-5F56.html-23Results&d=DwIBaQ&c=Ngd-ta5yRYsqeUsEDgxhcqsYYY1Xs5ogLxWPA_2Wlc4&r=4k7iKXbjGC8LfYxVJJXiaYVu6FRWmEjX38S7JmlS9Vw&m=--nG2SHIoX884s0M9k-XskKi6u9iVsUaE8GaIsVH_Yw&s=PXVWQ3PvRgczuV6a0GPJS7sH7uTPr9z0O-LNq7vuRtA&e=
  for
example. You can clearly see that ILU is h-dependent. So ILU should
"work" but I am not surprised that it degrades for larger problem
sizes. Your system is even harder to solve because of Grad-Div and the
non-symmetric convective term.

> At this point I totally understand parallelization is necessary for larger
> problems. But I still want to enable my toy program to run problems slightly
> out the scope of SparseDirectUMFPACK. After that I will try parallelize it.

I am afraid this will be difficult. While not easy to do, step-56
allows you to solve larger problems using geometric multigrid.
Extending this to Navier-Stokes is not easy either (and we are getting
close to state-of-the-art research).

Best,
Timo

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