gpu_job_1gpu.sh

#!/usr/bin/zsh
############################################################
### Slurm flags
############################################################

#SBATCH --partition=c23g            # request partition with GPU nodes
#SBATCH --nodes=1                   # request desired number of nodes
#SBATCH --ntasks-per-node=1         # request desired number of processes (or MPI tasks)

#SBATCH --cpus-per-task=24          # request desired number of CPU cores or threads per process (default: 1)
                                    # Note: available main memory is also scaling with
                                    #       number of cores if not specified otherwise
                                    # Note: On CLAIX-2023 each GPU can be used with 24 cores

#SBATCH --gres=gpu:1                # specify desired number of GPUs per node
#SBATCH --time=00:15:00             # max. run time of the job
#SBATCH --job-name=example_1gpus    # set the job name
#SBATCH --output=stdout_%j.txt      # redirects stdout and stderr to stdout.txt
#SBATCH --account=<project-id>      # insert your project-id or delete this line

############################################################
### Parameters and Settings
############################################################

# print some information about current system
echo "Job nodes: ${SLURM_JOB_NODELIST}"
echo "Current machine: $(hostname)"
nvidia-smi

############################################################
### Execution / Commands
############################################################

# Example: Only a single GPU is used. However, due to billing
#          settings, 24 CPU cores can be requested and used
#          in conjunction with that GPU. That also enables
#          multi-threaded preprocessing on the CPU side.