For HCLM

Introduction and general information

We have our own computational cluster (10 nodes, 96 CPU cores and ~1Tb RAM each) located at:

hclm.ifp.tuwien.ac.at

To monitor the usage of resources see this page.

SSH setup

For an easier access one might want to set up ssh-config file, ~/.ssh/config:

Host hclm                                                                       
  User username                                                                   
  Hostname hclmbck.ifp.tuwien.ac.at

And use the following command to login:

ssh hclm

For more info about ssh config file see this page.

To keep the ssh session open for prolonged time, use the following keyword:

ServerAliveInterval 60

SLURM

The slurm system is used to manage the queue with computational jobs. Use sinfo  to see the information on the current setup and available computational resources.

Here is a template for your run.sh  file:

#!/bin/bash

#SBATCH -J JOB_NAME
#SBATCH -N 1
#SBATCH --tasks-per-node=96
#SBATCH --partition=compute
#SBATCH -t 3-0:00:00 # 3 days walltime, the format is MM:SS, or HH:MM:SS, or D-HH:MM:SS

#environment variables to set
export OMP_NUM_THREADS=1

# modules to load
module purge
module load --auto w2dynamics/1.1.4-gcc-11.4.0-4e7xlay

# commands to run
mpirun -n $SLURM_TASKS_PER_NODE DMFT.py input_file.in

It will ask for one node, request 96 tasks/threads to be available and see that it does not run more than three days (walltime limit).

To submit your job use:

sbatch run.sh

To check the status of your jobs:

squeue -u $USER

To cancel the job:

scancel job_id

Julia

Please install julia and setup the proper environment yourself following the instructions from the official page.
If you're new to julia and want to get introduced to the current workflow, check this link.

Table of contents