SGE vs SLURM comparison

A guide comparing common commands in slurm and sge

Some common commands and flags in slurm and sge:

sge	slurm
qstat qstat -u username qstat -f	squeue squeue -u username squeue -al
qsub qsub -N jobname qsub -m beas qsub -M user@host qsub -l h_rt=24:00:00 qsub -pe dmp4 16 qsub -l mem=4G qsub -P projectname qsub -o filename qsub -e filename qsub -l scratch_free=20G	sbatch sbatch -J jobname sbatch --mail-type=ALL sbatch --mail-user=user@host sbatch -t 24:00:00 sbatch -p node -n 16 # Do not use mem specifications! sbatch -A projectname sbatch -o filename sbatch -e filename sbatch --tmp=20480
# Interactive run, one core	# Interactive run, one core
qrsh -l h_rt=8:00:00	salloc -t 8:00:00 interactive -p core -n 1 -t 8:00:00
qdel	scancel

A comparison between job scripts in slurm and sge

sge for an MPI application	slurm for an MPI application
#!/bin/bash # # #$ -N test #$ -j y #$ -o test.output #$ -cwd #$ -M username@domain.tld #$ -m bea # Request 5 hours run time #$ -l h_rt=5:0:0 #$ -P your_project_id_here #$ -R y # for Isis with 4 cores/node: #$ -pe dmp4 16 # (for grad, with 8 cores, use dmp8) #$ -l mem=2G # memory is counted per process on node # (dmp4 and mem=2G requires 8GB per node) module load pgi openmpi mpirun <put your app here>	#!/bin/bash -l # NOTE the -l flag! # #SBATCH -J test #SBATCH -o test.output #SBATCH -e test.output # Default in slurm #SBATCH --mail-user username@domain.tld #SBATCH --mail-type=ALL # Request 5 hours run time #SBATCH -t 5:0:0 #SBATCH -A your_project_id_here # #SBATCH -p node -n 16 # NOTE Each Kalkyl node has eight cores # module load pgi openmpi mpirun <put your app here>

sge for an MPI application

slurm for an MPI application

#!/bin/bash
#
#
#$ -N test
#$ -j y
#$ -o test.output
#$ -cwd
#$ -M username@domain.tld
#$ -m bea
# Request 5 hours run time
#$ -l h_rt=5:0:0
#$ -P your_project_id_here
#$ -R y
# for Isis with 4 cores/node:
#$ -pe dmp4 16
# (for grad, with 8 cores, use dmp8)
#$ -l mem=2G
# memory is counted per process on node
# (dmp4 and mem=2G requires 8GB per node)
 
module load pgi openmpi
 
mpirun <put your app here>

#!/bin/bash -l
# NOTE the -l flag!
#
#SBATCH -J test
#SBATCH -o test.output
#SBATCH -e test.output
# Default in slurm
#SBATCH --mail-user username@domain.tld
#SBATCH --mail-type=ALL
# Request 5 hours run time
#SBATCH -t 5:0:0
#SBATCH -A your_project_id_here
#
#SBATCH -p node -n 16
# NOTE Each Kalkyl node has eight cores
#
 
module load pgi openmpi
 
mpirun <put your app here>

sge for a single-core application	slurm for a single-core application
#!/bin/bash # # #$ -N test #$ -j y #$ -o test.output #$ -cwd #$ -M username@domain.tld #$ -m bea # Request 5 hours run time #$ -l h_rt=5:0:0 #$ -P your_project_id_here # #$ -l mem=4G # <call your app here>	#!/bin/bash -l # NOTE the -l flag! # #SBATCH -J test #SBATCH -o test.output #SBATCH -e test.output # Default in slurm #SBATCH --mail-user username@domain.tld #SBATCH --mail-type=ALL # Request 5 hours run time #SBATCH -t 5:0:0 #SBATCH -A your_project_id_here # #SBATCH -p core -n 1 # NOTE: You must not use more than 3GB of memory <call your app here>

sge for a single-core application

slurm for a single-core application

#!/bin/bash
#
#
#$ -N test
#$ -j y
#$ -o test.output
#$ -cwd
#$ -M username@domain.tld
#$ -m bea
# Request 5 hours run time
#$ -l h_rt=5:0:0
#$ -P your_project_id_here
#
#$ -l mem=4G
#
 
<call your app here>

#!/bin/bash -l
# NOTE the -l flag!
#
#SBATCH -J test
#SBATCH -o test.output
#SBATCH -e test.output
# Default in slurm
#SBATCH --mail-user username@domain.tld
#SBATCH --mail-type=ALL
# Request 5 hours run time
#SBATCH -t 5:0:0
#SBATCH -A your_project_id_here
#
#SBATCH -p core -n 1
# NOTE: You must not use more than 3GB of memory
 
<call your app here>

Comparison of some parallel environments set by sge and slurm

sge	slurm
$JOB_ID	$SLURM_JOB_ID
$NSLOTS	$SLURM_NPROCS