Metadata-Version: 2.1
Name: cmind
Version: 0.5.3
Summary: cmind
Home-page: https://github.com/mlcommons/ck/tree/master/ck2
Author: Grigori Fursin
Author-email: grigori@octoml.ai
License: Apache 2.0
Description: # Collective Mind toolkit
        
        The Collective Mind toolkit (CM or CK2) transforms Git repositories, Docker containers, Jupyter notebooks and zip/tar files
        into a collective database of reusable artifacts and automation scripts with a unified interface and extensible meta descriptions.
        
        It is motivated by our tedious experience reproducing [150+ ML and Systems papers](https://www.youtube.com/watch?v=7zpeIVwICa4)
        when our colleagues have spent many months analyzing the structure of ad-hoc projects, reproducing results
        and [validating them in the real world](https://cKnowledge.org/partners.html) 
        with different and continuously changing software, hardware, environments, data sets and settings.
        
        That is why we have decided to develop a simple toolkit to help you share your artifacts, knowledge, 
        experience and best practices with the world in a more reusable, automated, portable and reproducible way.
        
        The CM toolkit is based on the [Collective Knowledge concept]( https://arxiv.org/abs/2011.01149 )
        that was successfully validated in the past few years to 
        [enable collaborative ML and Systems R&D](https://cKnowledge.org/partners.html),
        modularize the [MLPerf inference benchmark](https://github.com/mlcommons/ck/tree/master/docs/mlperf-automation),
        and [automate the development and deployment of Pareto-efficient ML Systems](https://www.youtube.com/watch?v=1ldgVZ64hEI).
        
        See a few [related slides](docs/motivation.md) and a related article 
        about ["MLOps Is a Mess But That's to be Expected"](https://www.mihaileric.com/posts/mlops-is-a-mess/) (March 2022).
        
        
        
        # License
        
        Apache 2.0
        
        
        
        # How it works
        
        * Check this [getting started tutorial](docs/getting-started.md) 
          to undestand the Collective Mind concepts and try this toolkit.
        
        
        # Community meetings
        
        * TBA: Regular conf-calls
        * TBD: Public notes 
          
        
        # News
        
        * **2022 April 20:** Join us at the public MLCommons community meeting. Register [here](https://docs.google.com/spreadsheets/d/1bb7qWgWM-6gop1Mwjm4u8LZtC7uqbee8C30DHipkkms/edit#gid=533252977).
        
        * **2022 April 3:** We presented our approach to bridge the growing gap between ML Systems research and production 
          at the HPCA'22 workshop on [benchmarking deep learning systems](https://sites.google.com/g.harvard.edu/mlperf-bench-hpca22/home).
        
        * **2022 March:** We presented our concept to [enable collaborative and reproducible ML Systems R&D](https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=73126) 
          at the SIAM'22 workshop on "Research Challenges and Opportunities within Software Productivity, Sustainability, and Reproducibility"
        
        * **2022 March:** we've released the first prototype of [our toolkit ](https://github.com/mlcommons/ck/tree/master/ck2)
          based on your feedback and our practical experience [reproducing 150+ ML and Systems papers and validating them in the real world](https://www.youtube.com/watch?v=7zpeIVwICa4).
        ! 
        
        
        # Research and development
        
        ## CM core enhancements
        
        We use [GitHub tickets](https://github.com/mlcommons/ck/issues) 
        to improve and enhance the CM core based on the feedback from our users!
        Please don't hesitate to share your ideas and report encountered issues!
        
        ## CM-based automation scripts
        
        * We work with the community to transform R&D projects [from ML and Systems papers](https://cTuning.org/ae) 
          into [reusable CM artifacts and automation scripts](docs/reusable-components.md). 
          Feel free to suggest your own automation recipes to be reused by the community.
        
        ## CM-based projects
        
        * [Universal benchmarking of computational systems](docs/projects/universal-benchmarking.md).
        * [Towards modular MLPerf benchmark](docs/projects/modular-mlperf.md).
        * [MLPerf design space exploration](docs/projects/mlperf-dse.md).
        * [Automated deployment of Pareto-efficient ML Systems](docs/projects/production-deployment.md).
        
        
        # Resources
        
        * [MLOps projects](docs/KB/MLOps.md)
        
        
        # Acknowledgments
        
        We thank the [users and partners of the original CK framework](https://cKnowledge.org/partners.html), 
        [OctoML](https://octoml.ai), [MLCommons](https://mlcommons.org) 
        and all our colleagues for their valuable feedback and support!
        
        
        # Contacts
        
        * [Grigori Fursin](https://cKnowledge.io/@gfursin) - author and coordinator
        * [Arjun Suresh](https://www.linkedin.com/in/arjunsuresh) - coordinator and maintainer
        
Keywords: collective mind,cmind,cdatabase,cmeta,automation,reusability,meta,JSON,YAML,python
Platform: UNKNOWN
Description-Content-Type: text/markdown
