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https://github.com/deepmodeling/dpdispatcher

generate HPC scheduler systems jobs input scripts and submit these scripts to HPC systems and poke until they finish
https://github.com/deepmodeling/dpdispatcher

hpc job-scheduler lsf pbs python slurm

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generate HPC scheduler systems jobs input scripts and submit these scripts to HPC systems and poke until they finish

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# DPDispatcher

[![conda-forge](https://img.shields.io/conda/dn/conda-forge/dpdispatcher?color=red&label=conda-forge&logo=conda-forge)](https://anaconda.org/conda-forge/dpdispatcher)
[![pip install](https://img.shields.io/pypi/dm/dpdispatcher?label=pip%20install&logo=pypi)](https://pypi.org/project/dpdispatcher)
[![docker pull](https://img.shields.io/docker/pulls/dptechnology/dpdispatcher?logo=docker)](https://hub.docker.com/r/dptechnology/dpdispatcher)
[![Documentation Status](https://readthedocs.org/projects/dpdispatcher/badge/)](https://dpdispatcher.readthedocs.io/)

DPDispatcher is a Python package used to generate HPC (High-Performance Computing) scheduler systems (Slurm/PBS/LSF/Bohrium) jobs input scripts, submit them to HPC systems, and poke until they finish.

DPDispatcher will monitor (poke) until these jobs finish and download the results files (if these jobs are running on remote systems connected by SSH).

For more information, check the [documentation](https://dpdispatcher.readthedocs.io/).

## Installation

DPDispatcher can be installed by `pip`:

```bash
pip install dpdispatcher
```

To add [Bohrium](https://bohrium.dp.tech/) support, execute

```bash
pip install dpdispatcher[bohrium]
```

## Usage

See [Getting Started](https://dpdispatcher.readthedocs.io/en/latest/getting-started.html) for usage.

## Contributing

DPDispatcher is maintained by Deep Modeling's developers and welcomes other people.
See [Contributing Guide](CONTRIBUTING.md) to become a contributor! 🤓

## References

DPDispatcher is derived from the [DP-GEN](https://github.com/deepmodeling/dpgen) package. To mention DPDispatcher in a scholarly publication, please read Section 3.3 in the [DP-GEN paper](https://doi.org/10.1016/j.cpc.2020.107206).