LAMMPS¶

LAMMPS is a large scale classical molecular dynamics code, and stands for Large-scale Atomic/Molecular Massively Parallel Simulator. LAMMPS has potentials for soft materials (biomolecules, polymers), solid-state materials (metals, semiconductors) and coarse-grained or mesoscopic systems. It can be used to model atoms or, more generically, as a parallel particle simulator at the atomic, meso, or continuum scale.

Availability and Supported Architectures¶

LAMMPS is available at NERSC as a provided support level package. LAMMPS runs at NERSC are currently supported on CPU and GPU nodes.

Application Information, Documentation and Support¶

The official LAMMPS is available at LAMMPS Online Manual. LAMMPS has a large user base and good user support. Question related to using LAMMPS can be posted to the LAMMPS User forum. The forum also contains an archive of all past mailing list messages, which can be useful to help resolve some of the common user issues.

Using LAMMPS at NERSC¶

Lammps is now supported on Perlmutter machines using containers. Please note that lammps modules are deprecated and will not be updated.

There are two different containers of LAMMPS available on Perlmutter:

perlmutter$ shifterimg images | grep 'nersc/lammps'
perlmutter docker     READY    78c9bbb876   2023-10-11T15:35:48 nersc/lammps_all:23.08
perlmutter docker     READY    1265e04cff   2023-12-05T12:20:10 nersc/lammps_allegro:23.08
perlmutter docker     READY    a546b186a4   2023-09-19T12:14:13 nersc/lammps_lite:23.08

The lammps lite container should be sufficient for simulations utilizing most popularly used potentials. This a lighter build and does not contain user packages except SNAP-ML and ReaxFF. For most other mainstream packages available from LAMMPS, users should instead use lammps all container in their batch submission scripts.

Users running pair allegro should use image lammps allegro.

Using LAMMPS on Perlmutter¶

LAMMPS can be run on both, CPU and GPU nodes of Perlmutter. The following are the two example scripts that can be used to submit a batch job to either of the nodes.

#!/bin/bash
#SBATCH --image docker:nersc/lammps_lite:23.08
#SBATCH -C cpu
#SBATCH -t 00:20:00
#SBATCH -J LAMMPS_CPU
#SBATCH -o LAMMPS_CPU.o%j
#SBATCH -A mXXXX
#SBATCH -N 1
#SBATCH --cpus-per-task=1
#SBATCH -q regular

input="<please change this section to what is needed to run your simulation>"

export OMP_NUM_THREADS=64
export OMP_PROC_BIND=spread
export OMP_PLACES=threads

command="srun --cpu-bind=cores --module mpich shifter lmp $input" 
echo $command
$command

The above script launches a 1 CPU node job running with 128 tasks (equal to the number of cores available on 1 CPU node).

#!/bin/bash
#SBATCH --image docker:nersc/lammps_lite:23.08
#SBATCH -C gpu
#SBATCH -t 00:20:00
#SBATCH -J LAMMPS_GPU
#SBATCH -o LAMMPS_GPU.o%j
#SBATCH -A mXXXX
#SBATCH -N 1
#SBATCH -c 32
#SBATCH --ntasks-per-node=4
#SBATCH --gpus-per-task=1
#SBATCH --gpu-bind=none
#SBATCH -q regular

input="-k on g 4 -sf kk -pk kokkos newton on neigh half -in in.snap.test -var nsteps 20 -var nx 10 -var ny 10 -var nz 80 -var snapdir 2J14_InflatedFrom_2J10/"

export OMP_NUM_THREADS=64
export OMP_PROC_BIND=spread
export OMP_PLACES=threads

command="srun --cpu-bind=cores --gpu-bind=none --module mpich,gpu shifter lmp $input"
echo $command
$command

Please change the project number to number assigned to your project where it says mXXXX. The example above uses 1 GPU node on PM, which has 4 GPUs each. When changing the number of nodes, please modify the line SBATCH -N 1 to whatever number of nodes you want to run your problem with. Additionally, please change the line 'command="srun -n 4 lmp $input"' to -n as number of nodes times 4. Please change line 'input=' in accordance to LAMMPS GPU use guide as suitable for your problem.

If running LAMMPS with Kokkos package, please review the Kokkos package page to add appropriate flags to the job submission line as well as modify the input script.

Further details on using docker containers at NERSC with shifter can be found at shifter

Building LAMMPS from source¶

Some users may be interested in building LAMMPS from source to enable more specific LAMMPS packages. The source files for LAMMPS can be downloaded as either a tar file or from the LAMMPS Github repository.

module load cudatoolkit
module load craype-accel-nvidia80

git clone https://github.com/lammps/lammps.git
cd lammps
mkdir build
cd build

cmake -DCMAKE_INSTALL_PREFIX=$PWD/../install_pm -D CMAKE_BUILD_TYPE=Release \
            -D CMAKE_Fortran_COMPILER=ftn -D CMAKE_C_COMPILER=cc -D CMAKE_CXX_COMPILER=CC \
            -D MPI_C_COMPILER=cc -D MPI_CXX_COMPILER=CC -D LAMMPS_EXCEPTIONS=ON \
            -D BUILD_SHARED_LIBS=ON -D PKG_KOKKOS=yes -D Kokkos_ARCH_AMPERE80=ON -D Kokkos_ENABLE_CUDA=yes \
            -D PKG_MANYBODY=ON -D PKG_MOLECULE=ON -D PKG_KSPACE=ON -D PKG_REPLICA=ON -D PKG_ASPHERE=ON \
            -D PKG_RIGID=ON -D PKG_MPIIO=ON \
            -D CMAKE_POSITION_INDEPENDENT_CODE=ON -D CMAKE_EXE_FLAGS="-dynamic" ../cmake
make -j16
make install

Related Applications¶

• NAMD

User Contributed Information¶