GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles.
It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers.
This is a Docker image of GROMACS, which - if used with nvidia-docker - can provide hardware acceleration using NVIDIA GPUs.
Docker image tags correspond to the official Gromacs releases. Note that the tags without a minor version number (e.g. 2019) are not updated for new minor versions (e.g. 2019.1), as 2019 and 2019.1 are distinct GROMACS versions (2019 ~= 2019.0).
Feel free to raise a pull request to add a new release by updating GROMACS_VERSION and GROMACS_MD5.
Docker requires binding of any directory that the container should have access to. The flag -it is also recommended for any interactive steps. All GROMACS commands are executed as gmx MODULE, each module provides their own help:
docker run gromacs/gromacs gmx help commands
docker run gromacs/gromacs gmx help pdb2gmx
The below highlights this using an example of using pdb2gmx from the tutorial KALP15 in DPPC:
mkdir $HOME/data ; cd $HOME/data
wget http://www.mdtutorials.com/gmx/membrane_protein/Files/KALP-15_princ.pdb
docker run -v $HOME/data:/data -w /data -it gromacs/gromacs gmx pdb2gmx -f KALP-15_princ.pdb -o KALP-15_processed.gro -ignh -ter -water spc
If you get a permissions error when trying to run this command it is likely that SELINUX is blocking it and the permissions need to be set by adding :Z to the end of the volume bind as so:
mkdir $HOME/data ; cd $HOME/data
wget http://www.mdtutorials.com/gmx/membrane_protein/Files/KALP-15_princ.pdb
docker run -v $HOME/data:/data:Z -w /data -it gromacs/gromacs gmx pdb2gmx -f KALP-15_princ.pdb -o KALP-15_processed.gro -ignh -ter -water spc
It is beyond the scope of this README file to document GROMACS usage. For further information see:
The command gmx in this container image will attempt to detect your CPU's AVX/SSE flags to use the corresponding optimized gmx binary.
If you have an NVIDIA GPU, some GROMACS modules (in particular mdrun) can benefit hugely from hardware acceleration by using nvidia-docker which takes care of mapping the GPU device files. Simply replace docker above with nvidia-docker in the commands above.
A pre-compiled latest GROMACS distribution optionally using CUDA or OpenCL acceleration is available from conda-forge. Older versions of GROMACS using (only) OpenCL acceleration are available from BioConda.
The corresponding BioContainers Docker image can be used instead of this image, but that will not be able to provide GPU acceleration without additional binding of OpenCL folders.
Debian/Ubuntu include GROMACS with variants for different hardware, but these may not be the latest version.
In many cases compiling GROMACS from source code for your particular OS/hardware will provide additional performance gains. See the installation guide for details.
GROMACS is free software, distributed under the GNU Lesser General Public License (LGPL) Version 2.1 or (at your option) any later version. See COPYING for details.
This Docker image is based on the image nvidia/cuda that includes the CUDA runtime by NVIDIA. By downloading these images, you agree to the terms of the license agreements for the included NVIDIA software.
Other open source dependencies include:
Contributions welcome! Please fork this repository and submit a pull request to the dev branch.
The source code for GROMACS is available from http://manual.gromacs.org/current/download and is maintained at https://github.com/gromacs/gromacs
All of the containers are built by GitHub actions. This is done in a three part process.
- Build a container with optimised FFTW in.
- Build containers with emacs optimised for each SIMD type and/or gromacs version
- Build a container for each gromacs version that includes all containers built
in the previous step
This will require you to have an account on Dockerhub, and to have setup a PAT that you have then told Github about. The main part that then needs changing is the dockerhub repository in the workflow file: .github/workflow/main.yml
To change the version of gromacs or CUDA, you just need to change the variables in the workflow file: .github/workflow/main.yml
At the start of this file there is a list of parameters that can be changed such as GROMACS version, CUDA version and SIMD types.
To change the SIMD types you need to change the variable "simd_types". This should be a space separted list of SIMD types. This will be used to create the workflow matrix to build each of the SIMD specifc containers.
generate_specifications_file.py will build all containers needed to create the final docker conatiner. It is provided from gromacs-hpccm-recipes-mult-stages.
Firstly, generate_specifications_file.py takes many options. It is first called to generate an FFTW container that is optimised for all the SIMD types in simd_types.
Next, generate_specifications_file.py is called in a job matrix to build an optimised version of GROMACS for each SIMD type. Each of these is then registered to DockerHub with the name gmx-GROMACS_version-cuda-CUDA_version-SIMD_type.
Finally, a new Docker container is created which copies the optimised GROMACS versions from the containers built into a single container and publishes this to DockerHub
Subscribe to the GROMACS mailing list for any questions.