9a15f37960
Signed-off-by: Cole Ramos <colramos@amd.com>
62 行
2.3 KiB
Markdown
62 行
2.3 KiB
Markdown
[](https://github.com/AMDResearch/omniperf/actions/workflows/ubuntu-focal.yml)
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[](https://github.com/AMDResearch/omniperf/actions/workflows/opensuse.yml)
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[](https://amdresearch.github.io/omniperf/)
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[](https://zenodo.org/badge/latestdoi/561919887)
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# Omniperf
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## General
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Omniperf is a system performance profiling tool for machine
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learning/HPC workloads running on AMD MI GPUs. The tool presently
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targets usage on MI100 and MI200 accelerators.
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* For more information on available features, installation steps, and
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workload profiling and analysis, please refer to the online
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[documentation](https://amdresearch.github.io/omniperf).
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* Omniperf is an AMD open source research project and is not supported
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as part of the ROCm software stack. We welcome contributions and
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feedback from the community. Please see the
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[CONTRIBUTING.md](CONTRIBUTING.md) file for additional details on our
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contribution process.
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* Licensing information can be found in the [LICENSE](LICENSE) file.
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## Development
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Omniperf follows a
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[main-dev](https://nvie.com/posts/a-successful-git-branching-model/)
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branching model. As a result, our latest stable release is shipped
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from the `main` branch, while new features are developed in our
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`dev` branch.
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Users may checkout `dev` to preview upcoming features.
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## How to Cite
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This software can be cited using a Zenodo
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[DOI](https://doi.org/10.5281/zenodo.7314631) reference. A BibTex
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style reference is provided below for convenience:
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```
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@software{xiaomin_lu_2022_7314631
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author = {Xiaomin Lu and
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Cole Ramos and
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Fei Zheng and
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Karl W. Schulz and
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Jose Santos and
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Keith Lowery and
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Nicholas Curtis and
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Cristian Di Pietrantonio},
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title = {AMDResearch/omniperf: v1.0.9 (17 Aug 2023)},
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month = aug,
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year = 2023,
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publisher = {Zenodo},
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version = {v1.0.9},
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doi = {10.5281/zenodo.7314631},
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url = {https://doi.org/10.5281/zenodo.7314631}
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}
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```
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