slurm-emission 0.1.0

Submit jobs to SLURM seamlessly

SLURM emission

For those of you who make heavy use of High Performance Computing (HPC) clusters that depend on SLURM, you might have noticed that submitting jobs to the cluster can be a bit of a hassle. This is especially true when you have to submit multiple jobs with similar scripts but different parameters. Fortunately, slurm_emission comes for the rescue. In fact,

• it automates the creation of the sh file
• and it simplifies the submission of jobs to the cluster when the scripts to reuse are similar, and only the parameters change

You can install it with

pip install slurm-emission

I use it constantly so I thought it might be useful for you as well.

Example

Here we go in detail through what you can find in the example_1 script. Let's define the parameters of the jobs, the number of gpus, cpus and memory we'll need. Also, we want to repeat the experiments for several settings, in this case, we have two datasets, two models, and four seeds. Remember to adapt the script.py code to be able to receive those arguments as argparse arguments. We define also the script location and the name of the script to run.

from slurm_emission import run_experiments

script_path = 'path/to/your/script'
script_name = 'script.py'

sbatch_args = {
    'job-name': 'example_1',
    'partition': 'gpu',
    'gres': 'gpu:1',
    'cpus-per-task': 4,
    'mem': '40G',
    'account': '1230e98kal',
    'time': '23:00:00',
}

id = 'llms'

experiments = []

datasets = ['cifar', 'mnist']
models = ['transformer', 'lstm']

experiment = {
    'seed': list(range(4)),
    'epochs': [300], 'model': models, 'dataset': datasets
}
experiments.append(experiment)

Finally, we define the bash lines that will go in the sh, which are the lines that will be executed before the script, and will ask the system to load the necessary modules and activate the conda environment. Then we submit the jobs with run_experiments function, which will create the sh file and submit the jobs to the cluster.

load_modules = 'module load conda'
activate_env = 'conda activate llms'
py_location = f'cd {script_path}'
bash_prelines = f'{load_modules}\n{activate_env}\n{py_location}'

run_experiments(
    experiments,
    init_command=f'python {script_name} ',
    sbatch_args=sbatch_args,
    bash_prelines=bash_prelines,
    id=id,
)

The output of this script will be a .sh file with the following inside

#!/bin/bash
#SBATCH --job-name=example_1
#SBATCH --partition=gpu
#SBATCH --gres=gpu:1
#SBATCH --cpus-per-task=4
#SBATCH --mem=40G
#SBATCH --account=1230e98kal
#SBATCH --time=23:00:00

module load conda
conda activate llms
cd path/to/your/script
$1

that will be used by all the jobs that will be submitted:

Number jobs: 16/16
1/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=2 --epochs=300 --model=lstm --dataset=cifar '
2/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=3 --epochs=300 --model=lstm --dataset=cifar '
3/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=1 --epochs=300 --model=transformer --dataset=mnist '
4/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=0 --epochs=300 --model=transformer --dataset=mnist '
5/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=2 --epochs=300 --model=transformer --dataset=mnist '
6/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=0 --epochs=300 --model=lstm --dataset=cifar '
7/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=0 --epochs=300 --model=lstm --dataset=mnist '
8/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=2 --epochs=300 --model=lstm --dataset=mnist '
9/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=3 --epochs=300 --model=transformer --dataset=mnist '
10/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=1 --epochs=300 --model=lstm --dataset=mnist '
11/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=2 --epochs=300 --model=transformer --dataset=cifar '
12/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=1 --epochs=300 --model=transformer --dataset=cifar '
13/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=0 --epochs=300 --model=transformer --dataset=cifar '
14/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=1 --epochs=300 --model=lstm --dataset=cifar '
15/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=3 --epochs=300 --model=lstm --dataset=mnist '
16/16 sbatch cdir\sh\llms--2024-06-07_11-49-47OukHy.sh 'python script.py --seed=3 --epochs=300 --model=transformer --dataset=cifar '
Number jobs: 16/16

Hope it helps!