Description

pbs4py is a Python module for automating submission of compute jobs on High Performance Computing clusters, such as those that use the Portable Batch System (PBS). It includes pre-configured launchers for common NASA HPC systems: the Langley K cluster and NASA Advanced Supercomputing (NAS) systems.

Examples uses are uncertainty quantification where many jobs are submitted simultaneously or optimization where sequences of jobs need to scripted.

pbs4py also includes scripts for performing tasks associated with PBS jobs such as a script when given a job number will print the directory from which it was launched and a script that can delete multiple jobs based on filters.

Documentation

Documentation is hosted using Github Pages

The pbs4py documentation is generated from the source code with Sphinx. Once you have installed pbs4py, the documentation is built by running make html in the docs directory. The generated documentation will be in docs/build/html.

Installation

pbs4py can be installed with

pip install pbs4py

Quick Start

After installation,

On the K cluster:

from pbs4py import PBS
pbs = PBS.k4()
pbs.requested_number_of_nodes = 1
pbs.launch(job_name='example_job',job_body=['echo "Hello World"'])

On NAS:

from pbs4py import PBS
group = 'a1111' # your project ID to charge here
pbs = PBS.nas(group, proc_type='san', queue='devel', time=1)
pbs.launch(job_name='example_job',job_body=['echo "Hello World"'])

License Notices and Disclaimers

Notices: Copyright 2022 United States Government as represented by the Administrator of the National Aeronautics and Space Administration. No copyright is claimed in the United States under Title 17, U.S. Code. All Other Rights Reserved.

Third Party Software:

This software calls the following third party software, which is subject to the terms and conditions of its licensor, as applicable at the time of licensing. Third party software is not bundled with this software, but may be available from the licensor. License hyperlinks are provided here for information purposes only: numpy, BSD 3-Clause "New" or "Revised" License, https://github.com/numpy/numpy/blob/main/LICENSE.txt.

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