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Common Metadata eXchange framework (CMX) and Collective Mind automation framework (CM)

Project description

PyPI version Python Version License Downloads arXiv

Collective Mind workflow automation framework (MLCommons CM)

This Python package contains 2 front-ends:

License

Apache 2.0

Copyright

Copyright (c) 2021-2025 MLCommons

Grigori Fursin, the cTuning foundation and OctoML donated this project to MLCommons to benefit everyone.

Copyright (c) 2014-2021 cTuning foundation

Author

Maintainers

Concepts

To learn more about the concepts and motivation behind this project, please explore the following articles and presentations:

  • HPCA'25 article "MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI": [ Arxiv ], [ tutorial to reproduce results using CM/CMX ]
  • NeuralMagic's vLLM MLPerf inference 4.1 submission automated by CM: [README]
  • SDXL MLPerf inference 4.1 submission automated by CM: [README]
  • "Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments": [ ArXiv ]
  • ACM REP'23 keynote about the MLCommons CM automation framework: [ slides ]
  • ACM TechTalk'21 about Collective Knowledge project: [ YouTube ] [ slides ]
  • Journal of Royal Society'20: [ paper ]

Citation

If you found the CM, CMX and MLPerf automations helpful, kindly reference this article: [ ArXiv ], [ BibTex ].

You are welcome to contact the author to discuss long-term plans and potential collaboration.

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