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Access to VASP executables is restricted to users satisfying who satisfy the following criteria. :

• The user must

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• be a member of a research group owning a VASP license,.
• The user must employ VASP only for work on projects of this research group,.
• The user must be registered in Vienna as a VASP user of this research group. This task must be done by logging into the VASP Portal at https://www.vasp.at/vasp-portal/, and registering the user's institutional email address.

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VASP Version	User Group	VASP Modulefile	Compute Partitions	MPI Requirement	CPU/GPU	Lise/Emmy	Supported Features
5.4.4 with patch 16052018	vasp5_2	vasp/5.4.4.p1	CentOS 7	impi/2019.5	/	/
6.4.1	vasp6	vasp/6.4.1	CentOS 7	impi/2021.7.1	/	/	OpenMP, HDF5, Wannier90, Libxc
6.4.2	vasp6	vasp/6.4.2	CentOS 7	impi/2021.7.1	/	/	OpenMP, HDF5, Wannier90, Libxc, DFTD4 van-der-Waals functional
6.4.	3	vasp6	vasp/6.4.	nvhpc-hpcx/23.1	3	Rocky Linux 9	impi/2021.13	/	/

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Executables

Our installations of VASP comprise the regular executables (vasp_std, vasp_gam, vasp_ncl) and, optionally, community driven modifications to VASP as shown in the table below. They are available in the directory added to the PATH environment variable by one of the vasp environment modules.

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Example Jobscripts

#!/bin/bash
#SBATCH --time 12:00:00
#SBATCH --nodes 2
#SBATCH --tasks-per-node 40

export SLURM_CPU_BIND=none

module load impi/2019.5
module load vasp/5.4.4.p1

mpirun vasp_std

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#!/bin/bash
#SBATCH --time 12:00:00
#SBATCH --nodes 2
#SBATCH --tasks-per-node 96

export SLURM_CPU_BIND=none

module load impi/2019.5
module load vasp/5.4.4.p1

mpirun vasp_std

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#!/bin/bash
#SBATCH --time=12:00:00
#SBATCH --nodes=2
#SBATCH --tasks-per-node=48
#SBATCH --cpus-per-task=2
#SBATCH --partition=cpu-clx

export SLURM_CPU_BIND=none

# Set the number of OpenMP threads as given by the SLURM parameter "cpus-per-task"
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK

# Adjust the maximum stack size of OpenMP threads
export OMP_STACKSIZE=512m

# Binding OpenMP threads
export OMP_PLACES=cores
export OMP_PROC_BIND=close

# Binding MPI tasks
export I_MPI_PIN=yes
export I_MPI_PIN_DOMAIN=omp
export I_MPI_PIN_CELL=core

module load impi/2021.13
module load vasp/6.4.3

# This is to avoid the (harmless) warning message "MPI strtup(): warning I_MPI_PMI_LIBRARY will be ignored since the hydra process manager was found"
unset I_MPI_PMI_LIBRARY

# Our tests have shown that vasp has better performance with psm2 as libfabric provider
# Check if this also apply to your system
# To stick to the default provider, comment out the following line
export FI_PROVIDER=psm2

mpirun vasp_std

Here is the same example, but for the compute nodes with CentOS7

#!/bin/bash
#SBATCH --time=12:00:00
#SBATCH --nodes=2
#SBATCH --tasks-per-node=48
#SBATCH --cpus-per-task=2
#SBATCH --partition=standard96

export SLURM_CPU_BIND=none

# Set the number of OpenMP threads as given by the SLURM parameter "cpus-per-task"
export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK

# Adjust the maximum stack size of OpenMP threads
export OMP_STACKSIZE=512m

# Binding OpenMP threads
export OMP_PLACES=cores
export OMP_PROC_BIND=close

# Binding MPI tasks
export I_MPI_PIN=yes
export I_MPI_PIN_DOMAIN=omp
export I_MPI_PIN_CELL=core

module load impi/2021.7.1
module load vasp/6.4.1  

mpirun vasp_std

In the The following example , we show shows a job script that will run on the Nvidia A100 GPU nodes (Berlin). Per default, VASP will use one GPU per MPI task. If you plan to use 4 GPUs per node, you need to set 4 MPI tasks per node. Then, set the number of OpenMP threads to 18 (because 4x18=72 which is the number of CPU cores on GPU A100 partition) to speed up your calculation. This, however, also requires proper process pinning.

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