LAMMPS on Jean Zay

LAMMPS is a classical molecular dynamics simulator code specialised in materials modeling.

• Web site
• Documentation

• A deadlock problem was identified with version 2023.08.02 CPU. An alternate version is available with:

module load gcc/12.2.0 openmpi/4.1.1                                                                                                                                                                              
module load lammps/20230802-mpi

lammps.in

#!/bin/bash
#SBATCH --nodes=1               # Number of Nodes
#SBATCH --ntasks-per-node=40    # Number of MPI tasks per node
#SBATCH --cpus-per-task=1       # Number of OpenMP threads
#SBATCH --hint=nomultithread    # Disable hyperthreading
#SBATCH --job-name=rhodo        # Jobname
#SBATCH --output=%x.o%j         # Output file %x is the jobname, %j the jobid
#SBATCH --error=%x.o%j          # Error file
#SBATCH --time=10:00:00         # Expected runtime HH:MM:SS (max 100h)
##
## Please, refer to comments below for
## more information about these 4 last options.
##SBATCH --account=<account>@cpu       # To specify cpu accounting: <account> = echo $IDRPROJ
##SBATCH --partition=<partition>       # To specify partition (see IDRIS web site for more info)
##SBATCH --qos=qos_cpu-dev      # Uncomment for job requiring less than 2 hours
##SBATCH --qos=qos_cpu-t4      # Uncomment for job requiring more than 20h (up to 4 nodes)
 
# Cleans out the modules loaded in interactive and inherited by default
module purge
 
# Load the module
module load lammps/20200721-mpi intel-mkl/2020.1
 
# Execute commands
srun lmp -i rhodo.in

lammps_gpu.slurm

#!/bin/bash
#SBATCH --nodes=1               # Number of Nodes
#SBATCH --ntasks-per-node=40    # Number of MPI tasks per node
#SBATCH --cpus-per-task=1       # Number of OpenMP threads
#SBATCH --gres=gpu:4                # Allocate 4 GPUs/node
#SBATCH --hint=nomultithread    # Disable hyperthreading
#SBATCH --job-name=rhodo        # Jobname
#SBATCH --output=%x.o%j         # Output file %x is the jobname, %j the jobid
#SBATCH --error=%x.o%j          # Error file
#SBATCH --time=10:00:00         # Expected runtime HH:MM:SS (max 100h for V100, 20h for A100)
##
## Please, refer to comments below for
## more information about these 4 last options.
##SBATCH --account=<account>@v100      # To specify gpu accounting: <account> = echo $IDRPROJ
##SBATCH --partition=<partition>       # To specify partition (see IDRIS web site for more info)
##SBATCH --qos=qos_gpu-dev      # Uncomment for job requiring less than 2 hours
##SBATCH --qos=qos_gpu-t4      # Uncomment for job requiring more than 20h (up to 16 GPU, V100 only)
 
# Cleans out the modules loaded in interactive and inherited by default
module purge
 
# Load the module
module load lammps/20200630-mpi-cuda-kokkos intel-mkl/2020.1 cuda/10.2
 
# Execute commands
srun lmp -i rhodo.in

• All jobs have resources defined in Slurm per partition and per QoS (Quality of Service) by default. You can modify the limits by specifying another partition and / or QoS as shown in our documentation detailing the partitions and Qos.
• For multi-project users and those having both CPU and GPU hours, it is necessary to specify the project accounting (hours allocation for the project) for which to count the job's computing hours as indicated in our documentation detailing the project hours management.