Description

CP2K is a package for atomistic simulations of solid state, liquid, molecular, and biological systems offering a wide range of computational methods with the mixed Gaussian and plane waves approaches.

More information about CP2K and the documentation are found on https://www.cp2k.org/

Availability

CP2K is freely available for all users under the GNU General Public License (GPL).

Modules

CP2K is an MPI-parallel application. You can use either mpirun or srun as the job starter for CP2K. If you opt for mpirun, then, apart from loading the corresponding impi or openmpi modules, CPU and/or GPU pinning should be carefully carried out.

CP2K Version Modulefile Requirement Support CPU/GPU Lise/Emmy

2022.2

cp2k/2022.2

intel/2021.2 (Lise)

intel/2022.2 (Emmy)

libint, fftw3, libxc, elpa, scalapack, cosma, xsmm, spglib, mkl, sirius, libvori and libbqb

/

2023.1

cp2k/2023.1

intel/2021.2 (Lise)

intel/2022.2 (Emmy)

Lise: libint, fftw3, libxc, elpa, scalapack, cosma, xsmm, spglib, mkl, sirius, libvori and libbqb.

Emmy: libint, fftw3, libxc, elpa, scalapack, cosma, xsmm, spglib, mkl and sirius.

/

2023.1

cp2k/2023.1

openmpi/gcc.11/4.1.4

libint, fftw3, libxc, elpa, elpa_nvidia_gpu, scalapack, cosma, xsmm, dbcsr_acc, spglib,

mkl, sirius, offload_cuda, spla_gemm, m_offloading, libvdwxc

/

Example Jobscripts

Lise (using srun)

#!/bin/bash 
#SBATCH --time 12:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=24
#SBATCH --cpus-per-task=4
#SBATCH --time=06:00:00
#SBATCH --job-name=cp2k

export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}

module load intel/2021.2 impi/2021.7.1 cp2k/2023.1
srun cp2k.psmp input > output

Lise (using mpirun)

#!/bin/bash 
#SBATCH --time 12:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=24
#SBATCH --cpus-per-task=4
#SBATCH --time=06:00:00
#SBATCH --job-name=cp2k

export SLURM_CPU_BIND=none
export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}  

# 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 intel/2021.2 impi/2021.7.1 cp2k/2023.1
mpirun cp2k.psmp input > output

Lise (using mpirun): on Nvidia A100 GPU nodes

#!/bin/bash 
#SBATCH --partition=gpu-a100  
#SBATCH --time 12:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=4
#SBATCH --cpus-per-task=18
#SBATCH --time=06:00:00
#SBATCH --job-name=cp2k

export SLURM_CPU_BIND=none
export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}    
export OMP_PLACES=cores
export OMP_PROC_BIND=close

export OMPI_MCA_coll="^hcoll"
export OMPI_MCA_btl="smcuda,tcp,vader,self"  

module load gcc/11.3.0 openmpi/gcc.11/4.1.4 cp2k/2023.1

mpirun --bind-to core --map-by numa:PE=${SLURM_CPUS_PER_TASK} ./gpu_bind.sh cp2k.psmp input > output

Emmy (using srun)

#!/bin/bash
#SBATCH --time 12:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=24
#SBATCH --cpus-per-task=4
#SBATCH --time=06:00:00
#SBATCH --job-name=cp2k

export OMP_NUM_THREADS=${SLURM_CPUS_PER_TASK}

module load intel/2022.2 impi/2021.6 cp2k/2023.1
srun cp2k.psmp input > output

Depending on the problem size, it may happen that the code stops with a segmentation fault due to insufficient stack size or due to threads exceeding their stack space. To circumvent this, we recommend inserting in the jobscript:

export OMP_STACKSIZE=512M
ulimit -s unlimited