Description
Quantum ESPRESSO is an integrated suite of computer codes for electronic-structure calculations and materials modeling at the nanoscale. It is based on density-functional theory, plane waves, and pseudopotentials (both norm-conserving and ultrasoft).
More information
- Homepage: https://www.quantum-espresso.org
Available Versions of QuantumESPRESSO
This table is generated automatically. If you need other versions please click pc2-support@uni-paderborn.de.
Usage Hints for QuantumESPRESSO
If you need support in using this software or example job scipts please contact pc2-support@uni-paderborn.de.
SLURM Jobscript for Using the QuantumESPRESSO Module Built with EasyBuild
The following is an example SLURM jobscript for using the QuantumESPRESSO module built by EasyBuild (see the table above). The AUSURF112 benchmark is used for demonstration.
#!/usr/bin/env bash
#SBATCH --job-name=qe_ausurf112
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=16
#SBATCH --cpus-per-task=8
#SBATCH --time=00:10:00
#SBATCH --partition=normal
#
# parallelization
#
# | parallelization | value |
# |----------------------------------|----------|
# | number of allocated node | 1 |
# | number of MPI ranks per node | 16 |
# | number of CPU cores per MPI rank | 8 |
#
# thus total number of CPU cores used is 1 x 16 x 8 = 128
#
# load your required QuantumESPRESSO module
#
module reset
module load chem/QuantumESPRESSO/7.0-foss-2021a
#
# download the input files of AUSURF112
#
wget https://raw.githubusercontent.com/QEF/benchmarks/master/AUSURF112/ausurf.in
wget https://raw.githubusercontent.com/QEF/benchmarks/master/AUSURF112/Au.pbe-nd-van.UPF
#
# run the AUSURF112 benchmark
#
export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}
srun pw.x -ni 1 -nk 2 -nt 1 -nd 1 -input ausurf.in > benchmark.out 2> benchmark.err
Please note that this example may not guarantee the best computation performance, because the computation performance of QuantumESPRESSO depends on many factors, e.g. the version of QuantumESPRESSO, the compilers, the MPI library and involved math libraries, as well as the configuration for parallelization.