Linux / arm64
Linux / amd64
VMD is designed for modeling, visualization, and analysis of biomolecular systems such as proteins, nucleic acids, lipid membranes, carbohydrate structures, etc. VMD provides a wide variety of graphical representations for visualizing and coloring molecular structures: molecular surfaces, space-filling CPK spheres and cylinders, licorice bonds, backbone tubes, and ribbons, secondary structure cartoons, and others.
VMD can be used to animate and analyze the trajectory of a molecular dynamics (MD) simulation. In particular, VMD can act as a graphical front end for an external MD program by displaying and animating a molecule undergoing simulation on a local or remote computer.
While VMD is typically used interactively in a desktop graphical environment, it can also be used to perform non-interactive (batch mode) analytical calculations and visualization tasks run on both workstations (or single cluster nodes) and in parallel on distributed memory clusters and supercomputers using MPI.
VMD, tutorials, and documentation are available at http://www.ks.uiuc.edu/Research/vmd/
See here for a document describing prerequisites and setup steps for all HPC containers.
See here for a document describing the steps to pull NGC containers.
Before running the NGC RELION container please ensure your system meets the following requirements.
There are two options to run the VMD container.
In this example,
To run the VMD container from the CLI, issue the following command, which runs VMD and makes the current working directory accessible within the container as "/workspace":
docker run -ti --gpus all --rm -v $(pwd):/workspace nvcr.io/hpc/vmd:1.9.4a44 vmd
Note you could also point the CLI command to launch VMD on a script located in your working directory instead. The script below starts the VMD container and runs the xxx.vmd script from your workspace directory.
docker run -ti --gpus all --rm -v $(pwd):/workspace nvcr.io/hpc/vmd:1.9.4a44 vmd -dispdev openglpbuffer -e /workspace/xxx.vmd
In this example, we will run VMD interactively and reproduce an H1N1 test scene included within the container. Running interactively is useful when using VMD for visualization and analysis tasks that may involve external scripting of VMD runs, significant file management within complex directory hierarchies, or when running multiple VMD instances run within the same container and OS image.
To run the VMD container interactively, issue the following command which starts the container and also mounts your current directory to /workspace so it is available inside the container. (see the -v options on the command below to set the mapping of your local data directory to the one inside the container).
docker run -ti --gpus all --rm -v $(pwd):/workspace nvcr.io/hpc/vmd:1.9.4a44
After the container starts you will be in the / directory and, you can then change to /workspace and run VMD manually
vmd -dispdev openglpbuffer -e xxxx.vmd
This image was verified on Singularity version 3.X.Y. To check the currently installed Singularity version, use:
$ singularity --version
Before running with
singularity, configure NGC container registry authentication credentials via these environment variables:
$ export SINGULARITY_DOCKER_USERNAME='$oauthtoken' $ export SINGULARITY_DOCKER_PASSWORD=
More information about obtaining and using an NVIDIA NGC Cloud Services API key can be found here.
To build a singularity image run this:
$ singularity build vmd:1.9.4a44.sif nvcr.io/hpc/vmd:1.9.4a44
Run VMD with the image:
$ singularity exec --nv -B : vmd:1.9.4a44.sif vmd
Upon success, you will see the VMD command-line interface:
Info) VMD for LINUXARM64, version 1.9.4a44 (June 25, 2020) Info) http://www.ks.uiuc.edu/Research/vmd/ Info) Email questions and bug reports to firstname.lastname@example.org Info) Please include this reference in published work using VMD: Info) Humphrey, W., Dalke, A. and Schulten, K., `VMD - Visual Info) Molecular Dynamics', J. Molec. Graphics 1996, 14.1, 33-38. Info) ------------------------------------------------------------- Info) Multithreading available, 56 CPUs detected. Info) Free system memory: 249GB (97%) Info) Creating CUDA device pool and initializing hardware... Info) Detected 2 available CUDA accelerators: Info) [0-1] Tesla V100-PCIE-32GB 80 SM_7.0 1.4 GHz, 32GB RAM AE7 ZC vmd >
or run it in non-interactive mode:
$ singularity exec --nv -B : vmd:1.9.4a44.sif sh -c "vmd -dispdev openglpbuffer -e /workspace/xxx.vmd"