The Vienna Ab initio Simulation Package (VASP) is a computer program for atomic scale materials modelling, e.g. electronic structure calculations and quantum-mechanical molecular dynamics, from first principles.
Official website : https://www.vasp.at/
updated : 20 Feb 2023
Available version
VASP version 6.3.2 is available on Lanta. For running VASP on CPU node, please use VASP modules that has text cpu in its name. On the other hand, please use VASP modules that has text gpu in its name to run on GPU node. For VASP that implemented VTST code (https://theory.cm.utexas.edu/vtsttools/index.html ), these VASP modules have suffix vtst in modules name.
Version | Processing unit | Module name |
|---|---|---|
| CPU | VASP/6.3.2-GNU-cpu VASP/6.3.2-GNU-cpu_vtst |
GPU | VASP/6.3.2-NVHPC-gpu VASP/6.3.2-NVHPC-gpu_vtst |
1. Input file
The basic input files for running VASP on Lanta are VASP inputs and job submission script.
2. Job submission script
create a script using vi submit.sh command and specify the following details depending on computational resources you want to use.
2.1 Run VASP on CPU node
VASP on Lanta has OpenMP support, so users can use a combination of OpenMP threading and parallelization over MPI ranks. However, only some cases can get benefit from using multiple OpenMP threads per MPI rank. For further information, please visit Combining OpenMP + MPI in VASP. Here, both job submission scripts with Pure MPI and Hybrid OpenMP+MPI are shown.
2.1.1 Pure MPI
#!/bin/bash -l #SBATCH -p compute #specify partition #SBATCH -N 1 #specify number of nodes #SBATCH --ntasks-per-node=64 #specify number of tasks per node #SBATCH -t 2:00:00 #job time limit <hr:min:sec> #SBATCH -A ltXXXXXX #project name #SBATCH -J VASP-run #job name ##Module Load## module load VASP/6.3.2-GNU-cpu ##Extra Modules load due to MPI issue module load craype-network-ucx module swap cray-mpich cray-mpich-ucx module load libfabric/1.15.0.0 #set the maximum stacksize to unlimited ulimit -s unlimited # Extra setting due to MPI issue export UCX_TLS=all export UCX_WARN_UNUSED_ENV_VARS=n #disable OpenMP export OMP_NUM_THREADS=1 ##Run VASP### srun vasp_std
The script above using compute partition (-p compute), 1 node (-N 1) with 64 tasks per node (--ntasks-per-node=64), so the total CPUs core for this job is 64 (the number of tasks) x 1 (default CPU per task) = 64 cores. The account is set to ltXXXXXX (-A ltXXXXXX) that is subjected to change to your own account.
2.1.2 Hybrid MPI + OpenMP
#!/bin/bash -l
#SBATCH -p compute #specify partition
#SBATCH -N 1 #specify number of nodes
#SBATCH --ntasks-per-node=16 #specify number of tasks per node
#SBATCH --cpus-per-task=4 #specify number of openmp thread per task
#SBATCH -t 2:00:00 #job time limit <hr:min:sec>
#SBATCH -A ltXXXXXX #project name
#SBATCH -J VASP-run #job name
##Module Load##
module load VASP/6.3.2-GNU-cpu
##Extra Modules load due to MPI issue
module load craype-network-ucx
module swap cray-mpich cray-mpich-ucx
module load libfabric/1.15.0.0
#set the maximum stacksize to unlimited
ulimit -s unlimited
# Extra setting due to MPI issue
export UCX_TLS=all
export UCX_WARN_UNUSED_ENV_VARS=n
# Set OpenMP variables
export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}
export OMP_PLACES=cores
export OMP_PROC_BIND=close
export OMP_STACKSIZE=512m
##Run VASP###
srun vasp_std
The script above using compute partition (-p compute), 1 node (-N 1) with 16 tasks per node (--ntasks-per-node=16) and 4 CPU cores per task (--cpus-per-node=4), so the total CPUs core for this job is 16 (the number of tasks) x 4 (no. of CPU per task) = 64 cores.
The total number of MPI ranks (ntasks) × OMP_NUM_THREADS must not exceed the total number of physical cores (128 cores per Compute node on Lanta)
Please note that more CPU cores is not always mean better performance. It is a good idea to do a test with your own system for the optimum CPU cores.
2.2 Run VASP on GPU node
#!/bin/bash -l
#SBATCH -p gpu #specify partition
#SBATCH -N 1 #specify number of nodes
#SBATCH --ntasks-per-node=4 #specify number of tasks per node
#SBATCH --gpus-per-task=1 #specify number of gpus per task
#SBATCH --cpus-per-task=16 #specify number of openmp thread per task
#SBATCH -t 2:00:00 #job time limit <hr:min:sec>
#SBATCH -A ltXXXXXX #project name
#SBATCH -J VASP-run #job name
##Module Load##
module load VASP/6.3.2-NVHPC-gpu
##Extra Modules load due to MPI issue
module load craype-network-ucx
module swap cray-mpich cray-mpich-ucx
module load libfabric/1.15.0.0
#set the maximum stacksize to unlimited
ulimit -s unlimited
# Extra setting due to MPI issue
export UCX_TLS=all
export UCX_WARN_UNUSED_ENV_VARS=n
# Set OpenMP variables
export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}
export OMP_PLACES=cores
export OMP_PROC_BIND=close
export OMP_STACKSIZE=512m
##Run VASP###
srun vasp_std
The script above using gpu partition (-p gpu), 1 node (-N 1) with 4 tasks per node (--ntasks-per-node=4), 1 GPU card per task (--gpus-per-task=1) and each task uses 16 CPUs core (--cpus-per-task=16), so the total CPU cores for this job is 4 (the number of tasks) x 16 (no. of CPUs per task) = 64 cores. The total GPUs used in this job is 4 (one gpu node on Lanta has 4 GPUs of A100).
Total cores per LANTA GPU node is 64
the number of MPI ranks (ntasks) should less than or equal to the number of GPUs (--ntasks-per-node should not exceed 4 for a single gpu node)
3. Job submission
using sbatch submit.sh command to submit the job to the queuing system.