How to specify serial computation

[Ating24]

I am using MOOSE's polynomial chaos for training on a cluster, calculating 256 deterministic samples. Using more kernels will keep initializing the equation, while using fewer kernels will exceed memory or cause the following errors：
srun:First task exited 60s ago
srun:StepId=128229.0 task 3:running
srun :StepId=128229.0 tasks 0-2:exited
srun:launch/slurm:step signal:Terminating StepId=128229.0
srun :srun: Job step aborted: Waiting up to 32 seconds for job step to finish.130131
srun: error: ion171:task 3:Killed
when calculating the second step. Running the main input file alone can run it. Is there a way to abandon multiple apps and execute it in serial order? Or how to group the training sampler and specify the number of kernels for a single example

[GiudGiud]

Hello

You can limit the number of concurrent apps using the min/max procs per app parameters.

If you still want only one processor to run with several assigned, then use a singleRankPartitioner in the Paritioning block to force it back to one processor

Guillaume

[GiudGiud]

The parameters we mentioned will let you specify this for each child application.
You can specify however many processor on the main application with

mpirun -n <number of procs> <executable_name-opt> -i <input_file.i>

but then the limitation of the number of processors in each child app can only be done with these parameters

[Ating24]

This only sets the number of processors used by the entire main program, but for each sub application, there is only one processor. I want to divide each processor into 80 processors, and then each sub application will use these 80 processes for calculation in sequence.

[GiudGiud]

Still, this can be done with the new parameters min_procs_per...

[Ating24]

What does it mean? Can the old version use this parameter?

[GiudGiud]

no. You have seen that this parameter is not used in the old version already

[grmnptr]

Also, make sure you use the batch-reset mode in combination with your min/max procs per app settings. Here is a short description on the gains:
https://mooseframework.inl.gov/modules/stochastic_tools/batch_mode.html

The number of kernels would not influence your memory consumption too much unless you take it to the extreme.

[Ating24]

I can run a single example in 1 hour with 80 kernels now. I want to run all 256 examples in series using 80 kernels. Do I set mode=batch - reset in the mutiapps module and then set min/max procs per app parameters in the samplers module

[Ating24]

This version does not have the reprotters module, how to use min/max procs per app parameters

[Ating24]

I took a look at the version of SamplerFullSolveMultiApp being used C did not mention min/max_ Procs_ Per_ App and min/max_ Procs_ Per_ Row