p3-analysis-library
A library simplifying the collection and interpretation of P3 data.
Science Score: 67.0%
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
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✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 3 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
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○Scientific vocabulary similarity
Low similarity (11.2%) to scientific vocabulary
Keywords
Repository
A library simplifying the collection and interpretation of P3 data.
Basic Info
- Host: GitHub
- Owner: P3HPC
- License: mit
- Language: Python
- Default Branch: main
- Homepage: https://p3hpc.github.io/p3-analysis-library/
- Size: 2.14 MB
Statistics
- Stars: 8
- Watchers: 4
- Forks: 9
- Open Issues: 5
- Releases: 1
Topics
Metadata Files
README.md
Performance, Portability and Productivity Analysis Library
The Performance, Portability, and Productivity Analysis Library (P3 Analysis Library) enables a simpler workflow for the collection and interpretation of P3 data.
Table of Contents
Dependencies
- jsonschema
- numpy
- matplotlib >= 3.6.3
- pandas
- Python >= 3.8
Installation
To install, run pip install . or python setup.py install.
Getting Started
Demonstrations of library functionality can be found in examples and case-studies.
Contribute
Contributions to the P3 Analysis Library are welcome in the form of issues and pull requests.
See CONTRIBUTING for more information.
License
Distributed under the MIT license. See LICENSE for more information.
Security
See SECURITY for more information.
The master branch of the P3 Analysis Library is the development branch, and should not be used in production.
Citations
If your use of the P3 Analysis Library results in a research publication, please consider citing the software and/or the papers that inspired its functionality (as appropriate). See CITATION for more information.
Owner
- Name: P3HPC
- Login: P3HPC
- Kind: organization
- Repositories: 1
- Profile: https://github.com/P3HPC
Citation (CITATION.md)
# Citing the P3 Analysis Library
To cite the library itself, please use:
```bibtex
@software{p3-analysis-library,
author = {Pennycook, S. John and
Sewall, Jason and
Jacobsen, Douglas and
Deakin, Tom and
Zamora, Yuliana and
Lee, Kin Long Kelvin},
title = {{Performance, Portability and Productivity Analysis
Library}},
month = mar,
year = 2023,
publisher = {Zenodo},
doi = {10.5281/zenodo.7733678},
url = {https://doi.org/10.5281/zenodo.7733678}
}
```
Additional DOIs are generated for each [release][1].
[1]: https://github.com/P3HPC/p3-analysis-library/releases
## Citing Specific Functionality
Some of the functionality implemented by the P3 Analysis Library
was first introduced in academic papers, as detailed below.
### Performance Portability Metric
The performance portability metric is discussed in the following papers:
- S.J. Pennycook, J.D. Sewall and V.W. Lee, "[A Metric for Performance Portability](https://arxiv.org/abs/1611.07409)", in Proceedings of the 7th International Workshop in Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS), 2016
- S.J. Pennycook, J.D. Sewall and V.W. Lee, "[Implications of a Metric for Performance Portability](https://doi.org/10.1016/j.future.2017.08.007)", in Future Generation Computer Systems, Volume 92, March 2019, Pages 947-958
- S.J. Pennycook and J.D. Sewall, "[Revisiting a Metric for Performance Portability](https://doi.org/10.1109/P3HPC54578.2021.00004)", in Proceedings of the IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), 2020
### Code Divergence Metric
The code divergence metric is based on the one proposed in the following paper:
- S.L. Harrell, J. Kitson, et al., "[Effective Performance Portability](https://doi.org/10.1109/P3HPC.2018.00006)", in Proceedings of the IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), 2018
### Cascade Plots
Cascade plots were first introduced in the following paper:
- J.D. Sewall, S.J. Pennycook, D. Jacobsen, T. Deakin and S. McIntosh-Smith, "[Interpreting and Visualizing Performance Portability Metrics](https://doi.org/10.1109/P3HPC51967.2020.00007)", in Proceedings of the IEEE/ACM International Workshop on Performance, Portability and Productivity in HPC (P3HPC), 2020
### P3 Analysis Methodology
The end-to-end P3 analysis workflow was first described in the following
article:
- S.J. Pennycook, J.D. Sewall, D. Jacobsen, T. Deakin and S. McIntosh-Smith, "[Navigating Performance Portability](https://doi.org/10.1109/MCSE.2021.3097276)", in Computing in Science & Engineering, Volume: 23, Issue: 5, 01 Sept.-Oct. 2021
GitHub Events
Total
- Delete event: 3
- Issue comment event: 5
- Push event: 3
- Pull request review event: 4
- Pull request review comment event: 2
- Pull request event: 9
- Create event: 1
Last Year
- Delete event: 3
- Issue comment event: 5
- Push event: 3
- Pull request review event: 4
- Pull request review comment event: 2
- Pull request event: 9
- Create event: 1
Dependencies
- actions/checkout v3 composite
- actions/setup-python v5 composite
- pre-commit/action v3.0.1 composite
- actions/checkout v3 composite
- actions/setup-python v3 composite
- gsactions/commit-message-checker v2 composite
- jsonschema *
- matplotlib >=3.6.3
- numpy *
- pandas *