[Nek5000-users] Proper setup for AMG solver

[nek5000-users at lists.mcs.anl.gov]

Hi Steffen,


Thanks for the note.


I would recommend fixed dt at a value near your target CFL.


There are several reasons -


  1.  I doubt you gain that much with variable dt
  2.  I personally don't like Nek's auto-dt selection scheme
  3.  You have to reorthogonalize the projection basis every time dt changes (expensive)

Paul


________________________________
From: Nek5000-users <nek5000-users-bounces at lists.mcs.anl.gov> on behalf of nek5000-users at lists.mcs.anl.gov <nek5000-users at lists.mcs.anl.gov>
Sent: Monday, September 10, 2018 9:19:00 AM
To: nek5000-users at lists.mcs.anl.gov
Subject: Re: [Nek5000-users] Proper setup for AMG solver

Dear Nek experts,


I wanted to add some remarks on my performance tests conducted last week
mostly for the turbulent pipe flow at Re_b=5300

- The bad performance of the AMG solver was indeed due to an old version
of amg_hypre, as Stefan mentioned already.
For Re_b=5300 XXT and AMG showed the same performance.

- Additionally, I could increase the performance by about 20% using the
following settings:
-- lxd=10 (instead of 12, for lx1=8)
-- lx2=lx1-0 (PN-PN)
-- lower tolerances for p=1e-5 (instead of 1e-8) and 1e-6 for velocity
and passive scalars
-- turning of projection except for the fields of low Prandtl number

- Going from BDF3/EXT3 with a variable DT and targetCFL=0.5 to BDF2/OIFS
with variable DT and targetCFL=0.5 resulted in a longer time / timestep
(3x) but a also a larger average DT (6x).
Assuming the collected statistics require a similar averaging time in
wash-outs, BDF2/OIFS is advantageous (even for 10 passive scalars).
Before this discussion, I was running at constant DT and collected
statistics every 10th step. Now with a larger DT using characteristics,
should I collect statistics for each step?

- Regarding the filterWeight and filterCutoffRatio, I found out (with
Stefan's help) that the divergence error in L2 norm (when using PN-PN)
is affected by filterWeight.
For the setup at Re_b=5300 a filterWeight of 27 seemed to be OK
considering a divergence error in L2 norm of L2=3e-2, whereas a weight
of 54 resulted in L2=1e-1.


How these settings will affect the statistics, I am testing now.

Thank you all for your help and suggestions.


Cheers,
Steffen

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