...

• login via ssh,
• file systems, and
• Slurm usage.

Program build and execution

• Each node of the GPU A100 system is a combination of a host CPU and their four attached device GPUs. There is a wide range of software to support this hardware.
• We recommend to use the GPU A100 login nodes for program build. If a program build needs for the presence of CUDA drivers, compilation is possible on a compute node within a slurm job session, too.
• We restrict our presentation to examples. For that, please visit our manual on
  • OpenMP for GPU A100,
  • CUDA.

Job monitoring

A running job can be monitored interactively, directly on each of the compute nodes. Once you know the names of the job nodes you can login and monitor the host CPU as well as the GPUs.

bgnlogin1 $ squeue -u myaccount
  JOBID PARTITION     NAME      USER ST TIME  NODES NODELIST(REASON)
7748370  gpu-a100 a100_mpi myaccount  R 1:23      2 bgn[1007,1017]
bgnlogin1 $ ssh bgn1007
bgn1007 $ top
bgn1007 $ nvidia-smi
bgn1007 $ module load nvtop
bgn1007 $ nvtop

Software and environment modules

• Login and compute nodes of the A100 GPU partition are running under Rocky Linux (currently version 8.6).
• Software for the A100 GPU partition provided by NHR@ZIB can be found using the module command, see Quickstart.
• Please note the presence of the sw.a100 environment module. It controls the software selection for the GPU A100 partition.

bgnlogin1 $ module avail
...
bgnlogin1 $ module load gcc
...
bgnlogin1 $ module list
Currently Loaded Modulefiles:
 1) HLRNenv   2) sw.a100   3) slurm   4) gcc/11.3.0(default)

Using the slurm batch system

The GPU A100 shares the same slurm batch system with all partitions of System Lise.

...

#!/bin/bash
#SBATCH --partition=gpu-a100
#SBATCH --nodes=2
#SBATCH --ntasks=8 
#SBATCH --gres=gpu:4

module load openmpi/gcc.11/4.1.4
mpirun ./mycode.bin

Container

Apptainer is provided as a module and can be used to download, build and run e.g. Nvidia containers:

...