This Python package contains 2 front-ends:
- Collective Mind eXtension or Common Metadata eXchange (CMX, 2024+)
- Legacy Collective Mind (CM, 2021-2024)
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
- CM, CM4MLOps and MLPerf automations: MLCommons infra WG
- CMX (the next generation of CM): Grigori Fursin
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 ]
- "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 ]
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.