Minimal Slurm FAQ

What is Slurm?

Slurm (Simple Linux Utility for Resource Management) is a job scheduler that manages computational resources in a cluster. It allocates resources to jobs, dispatches them, monitors their execution, and cleans up after job completion.

Why use Slurm?

Resource allocation: Once resources are allocated to your job, they're exclusively yours for the duration of execution, regardless of system load.
Detached execution: No need to keep an open terminal session.
Efficient resource use: Jobs start as soon as requested resources are available, even outside working hours.
Fair scheduling: Jobs are prioritized based on requested resources, user's system share, and queue time.

Slurm Concepts

Before diving into Slurm usage, it's important to understand some key concepts:

Node : A computer in the cluster.

Partition: A group of nodes with specific characteristics.

Job : A resource allocation request for a specific program or task.

Task : An instance of a running program within a job.

Which Partition can I use?

You have 3 partitions on the Cluster

normal_prio: 1 day max runnig time, priority 100

normal_prio_long: 15 days max running time, priority 50

high_prio: 1 day max running time, priority 1000

Basic Usage

Loading Software as modules

To use a software that's not part of the system you can load it as a module

module avail

list all available modules

module load R/4.4.0

load R version 4.40

module list

list loaded modules

module unload module_name

unload loaded module module_name

module purge

unload all loaded modules

Simple Job Submission

Prefix your command with

srun myprogram

Run an interactive bash session

srun --pty bash

Note: This uses default settings, which may not always be suitable.

Specifying a Partition

Use the -p option with srun:

srun -p partition_name myprogram

Running Detached Jobs (Batch Mode)

Create a shell script (batch script) containing:
- Slurm directives (lines starting with #SBATCH)
- Any necessary preparatory steps (e.g., loading modules)
- Your srun command
Submit the script using sbatch:
```
sbatch myscript.sh
```

Using Conda

You can use conda inside your Batch script

# Load Conda


                module load anaconda3 
                
               # Activate your environment 
                conda activate myenv 
                
                # Run your Python script 
                python my_script.py

Monitoring Jobs

Checking Job Status

Use squeue to see which jobs are running or queued:

squeue

To see only your jobs:

squeue -u yourusername

Viewing Job Details

Use scontrol:

scontrol show job <jobid>

Checking Job Output

Slurm captures console output to a file named slurm-<jobid>.out in the submission directory. You can examine this file while the job is running or after it finishes.

Resource Requests

CPUs

To request multiple CPU threads:

#SBATCH --cpus-per-task=X
srun --cpus-per-task=X myprogram

Note: This argument must be given to both sbatch (via #SBATCH) and srun. The first one for the job allocation, the second for the task e

Other Resources

Specify in your batch script using #SBATCH directives:


            #SBATCH --mem=8G
            #SBATCH --time=02:00:00 
            #SBATCH --gres=gpu:1

Here you have the options for Memory, Time Limit and GPUs

Example batch script

#!/bin/bash #SBATCH --job-name=conda_job #SBATCH --output=output_%j.log #SBATCH --error=error_%j.log #SBATCH --time=01:00:00 #SBATCH --ntasks=1 #SBATCH --cpus-per-task=1 #SBATCH --mem=4G # Load Conda module load anaconda3 # Activate your environment conda activate myenv # Run your Python script python my_script.py

An example script with conda, launch it with:

sbatch conda_job.sh

Useful Slurm Commands

squeue: Show job queue information
sinfo: Display node and partition information
scancel <jobid>: Delete a job
sacct: View accounting data for jobs
scontrol: Detailed info