Add preference to disable LoopVectorization

[vchuravy]

Enzyme struggles with differentiation through the code that LoopVectorization
generates.

https://docs.sciml.ai/SciMLSensitivity/stable/faq/#How-do-I-isolate-potential-gradient-issues-and-improve-performance?

Is a good way to check if an Elixir's rhs is differentiable.
I ran into this when playing around with https://github.com/trixi-framework/Trixi.jl/blob/31e3c8fee15d9955af8c7c6a64e3bfcfea1c3e94/examples/p4est_2d_dgsem/elixir_navierstokes_NACA0012airfoil_mach08.jl and SciMLSensitivity.jl

[github-actions]

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Created with ❤️ by the Trixi.jl community.

[codecov]

Codecov Report

Attention: Patch coverage is 16.66667% with 10 lines in your changes missing coverage. Please review.

Project coverage is 96.93%. Comparing base (8c4cd80) to head (3887269).
Report is 2 commits behind head on main.

Files with missing lines	Patch %	Lines
src/auxiliary/mock_turbo.jl	0.00%	6 Missing ⚠️
src/auxiliary/math.jl	0.00%	3 Missing ⚠️
src/callbacks_step/summary.jl	50.00%	1 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##             main    #2295      +/-   ##
==========================================
- Coverage   96.95%   96.93%   -0.02%     
==========================================
  Files         504      505       +1     
  Lines       41721    41732      +11     
==========================================
+ Hits        40448    40449       +1     
- Misses       1273     1283      +10     

Flag	Coverage Δ
unittests	96.93% <16.67%> (-0.02%)	⬇️

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[sloede]

Very nice! Just a small naming suggestion...

[ranocha]

Why is LinearMap not defined in CI?

https://github.com/trixi-framework/Trixi.jl/actions/runs/13454713957/job/37596143655?pr=2295#step:7:4635

[vchuravy]

I believe @turbo also implies @inbounds. Right now this slows down simulations quite a bit.

[ranocha]

Yes, it does.

[ranocha]

Shall we go ahead with this PR as it is or would you like to change something?

[ranocha]

What kind of simulations do you look at to observe the significant slowdown?

[vchuravy]

I was running https://github.com/trixi-framework/Trixi.jl/blob/31e3c8fee15d9955af8c7c6a64e3bfcfea1c3e94/examples/p4est_2d_dgsem/elixir_navierstokes_NACA0012airfoil_mach08.jl

[vchuravy]

@ranocha this is ready from my side.

[ranocha]

Thanks! Did you test this locally?

[vchuravy]

Did you test this locally?

Only for my implicit example I mentioned earlier today.

[huiyuxie]

┌ Warning: #= C:\Users\huiyu\.julia\packages\Trixi\kIdT5\src\solvers\dgsem\interpolation.jl:118 =#:
│ `LoopVectorization.check_args` on your inputs failed; running fallback `@inbounds @fastmath` loop instead.
│ Use `warn_check_args=false`, e.g. `@turbo warn_check_args=false ...`, to disable this warning.
└ @ Trixi C:\Users\huiyu\.julia\packages\LoopVectorization\tIJUA\src\condense_loopset.jl:1166

Does this often happen when running examples from Trixi.jl or is it just a rare warning?

[ranocha]

This is a rare warning that you may get if you use "unusual types" (like rational numbers or types from Measurements jl) or array types that are not supported by LoopVectorization.jl (like GPU arrays).

[ranocha]

Thanks

[ranocha]

Do you have an idea why the threaded CI tests fail?