Job Settings
 Mail Type

 Cluster

MOGON 2 Cluster choosen
MOGON NHR-SW Cluster choosen

 Memory


 Job Duration


 Parallelization Paradigms

Deeplearning: max 8 GPUs
M2_GPU: max 6 GPUs
MI250: max 4 GPUs
SmallGPU: max 8 GPUs
A100DL: max 4 GPUs
A100AI: max 8 GPUs

 Partitions

Max Walltime for : (d-hh:mm:ss)
For GPU-Jobs, only Broadwell CPU Architecture is available. mogondoks
GPUs are only useable, when your Project requested them.
Billing Weights: CPU=1.5*Num Mem=0.25*GB GPU=6*Num
For GPU-Jobs, only Broadwell CPU Architecture is available. mogondoks
GPUs are only useable, when your Project requested them.
Billing Weights: CPU=1.5*Num Mem=0.25*GB GPU=10*Num
SMP is only available when 1 Node is choosen. mogondoks
SMP is the common queue for most users on MOGON 2, lowest bill overall.
Billing Weights: CPU=1.0*Num Mem=0.25*GB
smallcpu is only available when 1 Node is choosen. mogondoks
smallcpu is the common queue for most users on MOGON NHR, lowest bill overall.
Billing Weights: CPU=1.0*Num Mem=1*GB
Devel is only available when max 320 CPUs are used, with max 128 GB RAM.
Skylake CPUs are only available up to 96 GB RAM. mogondoks
Devel is a high priority queue, u bill for higher priority.
Billing Weights: CPU=2.0*Num Mem=0.5*GB
Parallel is an exclusive queue,
you must pay for all the resources of your allocated node,
even if you do not use them. mogondoks
Over 576 Nodes just Broadwell is available.
Billing Weights: Skylake: CPU=64 Mem=0.25*96/192
Broadwell: CPU=40 Mem=0.25*64/128/256
Parallel is an exclusive queue,
you must pay for all the resources of your allocated node,
even if you do not use them. mogondoks
Over 173 Nodes omly 256GB per Node is available.
Billing Weights: Skylake: CPU=128 Mem=1*256/512
Longtime is a special queue for jobs,
that exceed the 5-day walltime limit of the other CPU partitions.
If your Job has less than 5 Days Walltime,
Slurm will not schedule your Job or accept your Script. mogondoks
Billing Weights: CPU=2.0*Num Mem=1.0*GB
Longtime is a special queue for jobs,
that exceed the 6-day walltime limit of the other CPU partitions.
If your Job has less than 6 Days Walltime,
Slurm will not schedule your Job or accept your Script. mogondoks
Billing Weights: CPU=1.25*Num Mem=1.0*GB
Bigmem is a high memory queue,
for jobs that exceed the standard node's 256GB mem limit.
If your Job need more then 1TB RAM,
only Skylake is available. mogondoks
If your Job requires less than 256GB,
Slurm will not schedule your Job or accept your Script.
Billing Weights: CPU=2.0*Num Mem=1.0*GB
Largemem is a high memory queue,
for jobs that exceed the standard node's 512GB mem limit.
If your Job need more then 1TB RAM,
only Hugemem is available. mogondoks
If your Job requires less than 512GB,
Slurm will not schedule your Job or accept your Script.
Billing Weights: CPU=1.0*Num Mem=1.6*GB
Hugemem is a high memory queue, for jobs that
exceed the 1TB mem limit of Largemem. mogondoks
If your Job requires less than 1TB,
Slurm will not schedule your Job or accept your Script.
Billing Weights: CPU=1.0*Num Mem=2.8*GB
For the MI250 Queue, you must compile your Application with SYCL/HIP/OpenCL
on the System with ROCm, not CUDA. mogondoks
GPUs are only useable, when your Project requested them.
The MI250 are Dual-GPUs, for best Performace often 2 MPI-Prozesses per GPU is best.
Billing Weights: CPU=1.0*Num Mem=1.5*GB GPU=9*Num
For the SmallGPU Queue with A40, load CUDA-Modules. mogondoks
GPUs are only useable, when your Project requested them.
Billing Weights: CPU=1.0*Num Mem=1.5*GB GPU=7*Num
For the A100DL Queue, load CUDA-Modules. mogondoks
GPUs are only useable, when your Project requested them.
Billing Weights: CPU=1.0*Num Mem=1.5*GB GPU=9*Num
For the A100AI Queue, load CUDA-Modules. mogondoks
GPUs are only useable, when your Project requested them.
Billing Weights: CPU=1.0*Num Mem=3.0*GB GPU=17*Num
#!/bin/bash
#========[ + + + + MOGON Script Engine v2.25.01 + + + + ]========#
#
#  Documentation:  https://docs.hpc.uni-mainz.de
#   Chat Support:  https://mattermost.gitlab.rlp.net/hpc-support
# Ticket Support:  hpc@uni-mainz.de

#========[ + + + + Job Information + + + + ]========#
#SBATCH --mail-user=
#SBATCH --account=
#SBATCH --mail-type=
#SBATCH --job-name=
#SBATCH --comment=
#SBATCH --output=stdout_%x_%j.out
#SBATCH --output=_%x_%j.out
#SBATCH --error=stderr_%x_%j.err
#SBATCH --error=_%x_%j.err

#========[ + + + + Job Description + + + + ]========#
#SBATCH --partition=
#SBATCH --constrain=
#SBATCH --gres=gpu:
#SBATCH --time=:00
#SBATCH --signal=B:SIGUSR2@600
#SBATCH --ramdisk=
M
#SBATCH --mem=
#SBATCH --mem-per-cpu=
#SBATCH --nodes=
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=
#SBATCH --array=1-
export OMP_NUM_THREADS=
export MKL_NUM_THREADS=

#========[ + + + + Localscratch & Ramdisk + + + + ]========#
SAVEDPWD=$(pwd)
JOBDIR=/localscratch/$SLURM_JOB_ID
RAMDISK=$JOBDIR/ramdisk
cleanup(){
    cp /localscratch/${SLURM_JOB_ID}/output_file ${SAVEDPWD}/ &
    cp /localscratch/${SLURM_JOB_ID}/restart_file ${SAVEDPWD}/ &
    wait
    exit 0
}
trap 'cleanup' SIGUSR2
cp ${SAVEDPWD}/input_file /localscratch/${SLURM_JOB_ID}
cp ${SAVEDPWD}/restart_file /localscratch/${SLURM_JOB_ID}
cd /localscratch/${SLURM_JOB_ID}
${SAVEDPWD}/my_program
cleanup
######
cp *file in parallel file system* $RAMDISK/.

#========[ + + + + Modules + + + + ]========#
module purge
module load

#========[ + + + + Execution + + + + ]========#
srun mpirun --hint=nomultithread
Get your share: "sshare -A <account_name>" mogondoks
   Total Resource Consumption
Total CPUs:
Total GPUs:
Total Memory: MB
Total CPU hours: h
Max Energy Consumption: up to for the Job
Billing: Your share costs