Gromacs is a very efficient engine to perform molecular dynamics simulations and energy minimizations particularly for proteins. However, it can also be used to model polymers, membranes and e.g. coarse grained systems. It also comes with plenty of analysis scripts.
- Notes about performance
- Example parallel batch script for Puhti
- Example serial batch script for Puhti
- Example GPU script for Puhti
- Example mpi-only parallel batch script for Mahti
- Example mixed parallel batch script for Mahti
- High-throughput computing with Gromacs
- Visualizing trajectories and graphs
- More information
- Puhti: 2020-2022 releases with regularly updated minor versions, one with plumed, four with CUDA
- Mahti: 2020-2022 releases with regularly updated minor versions, two with plumed, two with CP2K, three with CUDA
- Check recommended version(s) with
module avail gromacs-env
- If you want to use command-line plumed tools, load the plumed module.
We only provide the parallel version
gmx_mpi, but it can
be used for grompp, editconf etc. similarly to the serial version.
gmx grompp ... give
CP2K 9.1 has been linked to Gromacs 2022.1 for QM/MM in the module
on Mahti. This option was previously available under the CP2K module
which has now been deprecated. Please use
gromacs-env/2022-cp2k for QM/MM simulations
from now on. See the official documentation for more
Gromacs is a free software available under LGPL, version 2.1.
Initialize recommended version of Gromacs on Puhti like this:
module purge module load gromacs-env
module spider to locate other versions. To load these modules, you
need to first load its dependencies, which are shown with
module spider gromacs/<version>.
Notes about performance
It is important to set up the simulations properly to use resources efficiently. The most important aspects to consider are:
- If you run in parallel, make a scaling test for each system - don't use more cores than is efficient. Scaling depends on many aspects of your system and used algorithms, not just size.
- Use a recent version - there has been significant speedup over the years
- Minimize unnecessary disk I/O - never run batch jobs with -v (the verbose flag) for mdrun
- For large jobs, use full nodes (multiples of 40 cores on Puhti or multiples of 128 cores on Mahti), see example below.
For a more complete description, consult the mdrun performance checklist on the Gromacs page.
We recommend using the latest versions as they have most bugs fixed and tend to be faster. If you switch the major version, check that the results are comparable.
A scaling test with a very large system (1M+ particles) may take a while to load balance optimally. Rather than running very long scaling tests in advance, it is better to increase the number of nodes in your production simulation IF you see better performance than in the scaling test at the scaling limit.
Example parallel batch script for Puhti
#!/bin/bash #SBATCH --time=00:15:00 #SBATCH --partition=large #SBATCH --ntasks-per-node=40 #SBATCH --nodes=2 #SBATCH --account=<project> ##SBATCH --mail-type=END #uncomment to get mail # this script runs a 80 core (2 full nodes) gromacs job, requesting 15 minutes time module purge module load gromacs-env export OMP_NUM_THREADS=1 srun gmx_mpi mdrun -s topol -maxh 0.2 -dlb yes
To avoid multi node parallel jobs to spread over more nodes
than necessary, don't use the
--ntasks flag, but specify
--ntasks-per-node=40 to get full nodes. This minimizes communication
overhead and fragmentation of node reservations. Don't use the large
partition for jobs with less than 40 cores.
Example serial batch script for Puhti
#!/bin/bash #SBATCH --time=00:15:00 #SBATCH --partition=small #SBATCH --ntasks=1 #SBATCH --account=<project> ##SBATCH --mail-type=END #uncomment to get mail # this script runs a 1 core gromacs job, requesting 15 minutes time module purge module load gromacs-env export OMP_NUM_THREADS=1 srun gmx_mpi mdrun -s topol -maxh 0.2
Example GPU script for Puhti
#!/bin/bash #SBATCH --ntasks=1 #SBATCH --cpus-per-task=10 #SBATCH --gres=gpu:v100:1 #SBATCH --time=00:10:00 #SBATCH --partition=gpu #SBATCH --account=<project> ##SBATCH --mail-type=END #uncomment to get mail module purge module load gromacs-env/2022-gpu export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK srun gmx_mpi mdrun -s verlet -dlb yes # additional flags, like these, may be useful - test! # srun gmx_mpi mdrun -pin on -pme gpu -pmefft gpu -nb gpu -bonded gpu -update gpu -nstlist 200 -s verlet -dlb yes
Please make sure that using one GPU (and upto 10 cores) is faster than using one full node of CPU cores according to the Usage policy page under Computing. Otherwise, don't use GPUs.
Submit the script with
Example mpi-only parallel batch script for Mahti
#!/bin/bash #SBATCH --time=00:15:00 #SBATCH --partition=medium #SBATCH --ntasks-per-node=128 #SBATCH --nodes=2 #SBATCH --account=<project> ##SBATCH --mail-type=END #uncomment to get mail # this script runs a 256 core (2 full nodes, no hyperthreading) gromacs job, # requesting 15 minutes time module purge module load gromacs-env export OMP_NUM_THREADS=1 srun gmx_mpi mdrun -s topol -maxh 0.2 -dlb yes
Example mixed parallel batch script for Mahti
#!/bin/bash #SBATCH --time=00:15:00 #SBATCH --partition=medium #SBATCH --ntasks-per-node=64 #SBATCH --cpus-per-task=2 #SBATCH --nodes=2 #SBATCH --account=<project> ##SBATCH --mail-type=END #uncomment to get mail # this script runs a 256 core (2 full nodes, no hyperthreading) gromacs job, # requesting 15 minutes time and 64 tasks per node, each with 2 OpenMP threads module purge module load gromacs-env export OMP_NUM_THREADS=$SLURM_CPUS_PER_TASK srun gmx_mpi mdrun -s topol -maxh 0.2 -dlb yes
High-throughput computing with Gromacs
Gromacs comes with a built-in
multidir functionality, which allows users to run
multiple concurrent simulations within one Slurm allocation. This is an excellent
option for high-throughput use cases, where the aim is to run several similar, but
independent, jobs. Notably, multiple calls of
srun are not needed,
which decreases the load on the batch queue system. Please consider this option if
you're running high-throughput workflows or jobs such as replica exchange, umbrella
sampling or adaptive weight histogram (AWH) free energy simulations using Gromacs.
multidir.sh batch script for running a
multidir Gromacs job is
provided below. This example adapts the production part of the
lysozyme tutorial by considering 8
similar copies of the system that have been equilibrated with different velocity
initializations. Inputs corresponding to each copy are named identically
and placed in subdirectories
run* as illustrated below by the output of the
$ tree . ├── multidir.sh ├── run1 │ └── md_0_1.tpr ├── run2 │ └── md_0_1.tpr ├── run3 │ └── md_0_1.tpr ├── run4 │ └── md_0_1.tpr ├── run5 │ └── md_0_1.tpr ├── run6 │ └── md_0_1.tpr ├── run7 │ └── md_0_1.tpr └── run8 └── md_0_1.tpr
#!/bin/bash #SBATCH --time=00:30:00 #SBATCH --partition=medium #SBATCH --ntasks-per-node=128 #SBATCH --nodes=1 #SBATCH --account=<project> # this script runs a 128 core gromacs multidir job (8 simulations, 16 cores per simulation) module purge module load gromacs-env export OMP_NUM_THREADS=1 srun gmx_mpi mdrun -multidir run* -s md_0_1.tpr -dlb yes
sbatch multidir.sh in the parent directory, all simulations are run concurrently
using one full Mahti node without hyperthreading so that each system is allocated 16 cores.
As the systems were initialized with different velocities, we obtain 8 distinct trajectories
and an improved sampling of the phase space (see RMSD analysis below). This is a great option
for enhanced sampling when your system does not scale beyond a certain core count.
For further details on running Gromacs multi-simulations, see the official Gromacs documentation.
Visualizing trajectories and graphs
In addition to the
view tool of Gromacs (not available at CSC),
trajectory files can be visualized with the following programs:
- VMD visualizing program for large biomolecular systems
- Grace plotting graphs produced with Gromacs tools
- PyMOL molecular modeling system (not available at CSC)
Please don't run visualization or heavy Gromacs tool scripts in
the login node (see usage policy for details).
You can run the tools in the interactive partition
by prepending your
gmx_mpi command with
orterun -n 1, e.g.
orterun -n 1 gmx_mpi msd -n index -s topol -f traj).
Cite your work with the following references:
- GROMACS 4: Algorithms for Highly Efficient, Load-Balanced, and Scalable Molecular Simulation. Hess, B., Kutzner, C., van der Spoel, D. and Lindahl, E. J. Chem. Theory Comput., 4, 435-447 (2008).
- GROMACS: Fast, Flexible and Free. D. van der Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Mark and H. J. C.Berendsen, J. Comp. Chem. 26 (2005) pp. 1701-1719
- GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers M. J. Abraham, T. Murtola, R. Schulz, S. Páll, J. C. Smith, B. Hess, E. Lindahl SoftwareX 1 (2015) pp. 19-25
- Tackling Exascale Software Challenges in Molecular Dynamics Simulations with GROMACS In S. Markidis & E. Laure (Eds.), Solving Software Challenges for Exascale S. Páll, M. J. Abraham, C. Kutzner, B. Hess, E. Lindahl 8759 (2015) pp. 3-27
- GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit S. Pronk, S. Páll, R. Schulz, P. Larsson, P. Bjelkmar, R. Apostolov, M. R. Shirts, J. C. Smith, P. M. Kasson, D. van der Spoel, B. Hess, and E. Lindahl Bioinformatics 29 (2013) pp. 845-54
See your simulation log file for more detailed references for methods applied in your setup.
- Gromacs home page: http://www.gromacs.org/
- Hands-on tutorials by Justin A. Lemkul, on GROMACS tutorial home and by Bert de Groot group
- Lots of material at BioExcel EU project
- HOW-TO section on the Gromacs pages
- Gromacs documentation and mdrun performance checklist
- The PRODRG Server for online creation of small molecule topology
- 2021 Advanced Gromacs Workshop materials