Container Usage¶
A pre-built container image is published to the GitHub Container Registry at
ghcr.io/abramsgroup/htpolynet:latest. It bundles Gromacs, AmberTools,
OpenBabel, and htpolynet itself, so no local installation of any of these
tools is required.
Desktop Users (Docker)¶
Docker Desktop (Windows and Mac) or Docker Engine (Linux) is required.
The recommended way to use the image is with Docker Compose. Save the
following as compose.yml in your working directory:
services:
htpolynet:
image: ghcr.io/abramsgroup/htpolynet:latest
volumes:
- .:/work
working_dir: /work
user: "${UID:-0}:${GID:-0}"
Then run htpolynet subcommands via:
$ docker compose run --rm htpolynet run config.yaml
All htpolynet subcommands work the same way:
$ docker compose run --rm htpolynet fetch-example 4
$ docker compose run --rm htpolynet info
$ docker compose run --rm htpolynet postsim -proj proj-0 -cfg postsim.yaml
The compose.yml file mounts the current directory into the container as
/work and runs the process as your host user, so all output files are
written with your own ownership.
Note
On Windows the user: field in compose.yml has no effect (Docker
Desktop on Windows always runs as the current user). Output files will be
owned correctly without any changes.
GPU support¶
If you have an NVIDIA GPU and the
NVIDIA Container Toolkit
installed, add a deploy block to your local copy of compose.yml:
services:
htpolynet:
image: ghcr.io/abramsgroup/htpolynet:latest
volumes:
- .:/work
working_dir: /work
user: "${UID:-0}:${GID:-0}"
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
htpolynet will detect the available GPU(s) automatically at startup.
HPC Users (Singularity/Apptainer)¶
Most HPC clusters provide Singularity or Apptainer rather than Docker. Both can pull the image directly from the container registry.
Pull the image once (store it somewhere on shared storage so cluster members can share it):
$ singularity pull htpolynet.sif docker://ghcr.io/abramsgroup/htpolynet:latest
Then run it, binding your working directory:
$ singularity run --bind $(pwd):/work --pwd /work htpolynet.sif run config.yaml
For GPU nodes, add the --nv flag:
$ singularity run --nv --bind $(pwd):/work --pwd /work htpolynet.sif run config.yaml
A typical SLURM job script might look like:
#!/bin/bash
#SBATCH --job-name=htpolynet
#SBATCH --nodes=1
#SBATCH --ntasks=8
#SBATCH --gres=gpu:1 # remove if no GPU partition
#SBATCH --output=slurm-%j.out
SIF=/shared/containers/htpolynet.sif
singularity run --nv \
--bind $SLURM_SUBMIT_DIR:/work \
--pwd /work \
$SIF run config.yaml -proj next