问题
Background
I need to run a blocks simulation. I've used OMEdit to create the system and I call omc to run the simulation using OMPython with zmq for messaging. The simulation works fine but now I need to move it to a server to simulate the system for long times.
Since the server is shared among a team of people, it uses slurm to queue the jobs. The server has 32 cores but they asked me to use only 8 while I tune my script and then 24 when I want to run my final simulation.
I've configured slurm to call my script in the following manner:
#!/bin/bash
#
#SBATCH --job-name=simulation_Test_ADC2_pipe_4096s
#SBATCH --output=simulation_Test_ADC2_pipe_4096s.txt
#
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8
#SBATCH --time=10:00
#SBATCH --mem-per-cpu=10000
source activate /home/jabozzo/conda_envs/py27
#which python
python ./Test_ADC2_pipe_4096s.py
Then I execute the slurm file using sbatch.
Problem
The omc compilation works fine. When it starts to simulate all the 32 cores of the server become loaded, even if it was configured to only use 8.
I've tried
There are compilation and simulation flags that can be passed to omc. I've tried to use --numProcs (a compilation flag) but this only seem to apply during the compilation process and does not affect the final executable. I've scanned the page of simulation flags looking for something related but it seems there is no option to change the cpu usage.
回答1:
The only thing that we add when doing our OpenModelica testing in parallel is to add the GC_MARKERS=1 environment variable and --numProcs=1; this makes our nightly library testing of 10000 tests all run in serial. But GC_MARKERS shouldn't affect simulations unless they are allocating extreme amounts of memory. Other than that, OpenModelica simulations are serial unless perhaps you use a parallel blas/lapack/sundials library which might use more cores without OpenModelica knowing anything about it; in that case you would need to read the documentation for the library that's consuming all your resources.
What's a bit surprising is also how slurm allows your process to consume more CPUs than you set; it could use the taskset command to make the kernel force the process to only use certain CPUs.
回答2:
My server administrator was unsure if taskset would interfere with slurm internals. So we found another option. If omc uses openMP for compilation we can also limit the number of cores replacing the last line of the slurm file with:
OMP_NUM_THREADS=8 python ./Test_ADC2_pipe_4096s.py
I'm leaving this anwser here to complement sjoelund.se anwser
来源：https://stackoverflow.com/questions/48119762/limit-number-of-cores-used-by-ompython