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 6 June 2023
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There are two modules of VASP VASP version 6.3.2 is available on Lanta. One is for For running VASP on CPU node, and the another is for running on GPU 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. All VASP modules has implemented VTST code (https://theory.cm.utexas.edu/vtsttools/index.html ).
Version | Processing unit | Module name |
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| CPU | VASP/6.3.2-GNU-cpu_vtst VASP/6.3.2-Intel-cpu_vtst |
GPU | VASP/6.3.2-NVHPC-gpu_vtst |
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The basic input files for running VASP on Lanta are VASP inputs and job submission script.
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create a script using vi submit.sh command and specify the following details depending on computational resources you want to use.
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Compute 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.
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#!/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 thaiscltXXXXXX #project name #SBATCH -J VASP-run #job name ##Module Load## #module purge 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 _vtst #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.
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#!/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 thaiscltXXXXXX #project name #SBATCH -J VASP-run #job name ##Module Load## #module purge 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 _vtst #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=${SLURM_CPUS_PER_TASK} export OMP_PLACES=cores export OMP_PROC_BIND=close export OMP_STACKSIZE=512m ##Run VASP### srun --cpus-per-task=${SLURM_CPUS_PER_TASK} 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.
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The total number of MPI ranks (ntasks) × |
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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. |
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#!/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-tasknode=14 #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 thaiscltXXXXXX #project name #SBATCH -J VASP-run #job name ##Module Load## #module purge 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 NVHPC-gpu_vtst #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=${SLURM_CPUS_PER_TASK} export OMP_PLACES=cores export OMP_PROC_BIND=close export OMP_STACKSIZE=512m ##Run VASP### srun --cpus-per-task=${SLURM_CPUS_PER_TASK} vasp_std |
The script above using gpu partition (-p gpu), 1 node (-N 1) with 4 tasks per node (--ntasks-per-node=4), 1 4 GPU card per task node (--gpus-per-tasknode=14) 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 GPU GPUs of A100).
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Total cores per LANTA GPU node is 64 |
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the number of MPI ranks (ntasks) should less than or equal to the number of GPUs ( |
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using sbatch submit.sh command to submit the job to the queuing system.
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