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Mpi + Openmp Results in Seg Fault Couple Mins Into Run


Hi WRF team,

We've been running WRF successfully using pure mpi (dmpar) and want to explore potential gains when switching over to the hybrid mpi + openmp (dm+sm). Unfortunately, we get a seg fault about 2 mins into a model run. Any advice / pointer? I know it is usually advised to go with either a pure mpi or openmp solution, but I'd really like to find out what is causing crash.

We are using:
- Intel OneAPI 2022.2.1
- Intel MPI 2021.7.1

Namelist is attached which runs fine with mpi but crashes with mpi+opnemp. Test run script is also attached where stuff like the stack size is set to unlimited.

Let me know if I can provide any more info.

Thanks in advance for any help,



  • configure.wrf.txt
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  • rsl.error.0000
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  • namelist.input
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  • rsl.out.0000
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With OpenMP, you may need to increase the size of OMP_STACKSIZE. This is separate from the shell stacksize. Default value is usually 4M (MB). I would expect the seg fault to happen on the first time step, however, if this were the problem. You can try setting it larger, e.g.,


On the other hand, the sudden decrease in adaptive dt could mean that it has become unstable. You might try with a constant, smaller dt to see if that is the problem.
Thanks for your reply, inside the run script ( we do set the stack size - we even tried crazy high ones - e.g. export OMP_STACKSIZE="30G"

The fact it gets to running suggests to me that I'm not dealing with any fundamental missing libraries etc.

Running with a single mpi task also results in the same issue.

Any other suggestions would be appreciated
There was another suggestion there: Did you try a fixed, smaller dt? Instabilities can cause out-of-bounds errors in physics (seg fault).
We're using adaptive time step and have successfully run an identical case without openMP. With no CFL errors being reported I'm not expecting this to be a physical instability.
It is generally not recommended to run WRF in dm+sm mode. This is because the OpenMP parallelization is not well implemented in WRF. Furthermore, with WRF being in maintenance status now, it is no longer our top priority to improve the openMP parallelization in WRF.