clean up

.travis.yml

@@ -44,7 +44,7 @@ install:
 
 script: 
     - ${PYTHON_EXE} -m pip install --ignore-installed --verbose pip setuptools
-    - cd ck2
+    - cd cm
     - ${PYTHON_EXE} setup.py install
     - ${PYTHON_EXE} -m cmind
     - cm

README.md

@@ -1,7 +1,4 @@
-***April 2022: We've started prototyping the new [CK2 toolkit](https://github.com/mlcommons/ck/tree/master/ck2) 
-   based on your feedback and combined with our practical experience 
-   [reproducing 150+ ML and Systems papers and validating them in the real world](https://www.youtube.com/watch?v=7zpeIVwICa4).
-   Please [get in touch](https://github.com/mlcommons/ck/tree/master/ck2#contacts) if you are interested to participate in this community effort!***
+***We are developing the new [CM toolkit aka CK2](https://github.com/mlcommons/ck/tree/master/cm) based on the community feedback.***
 
 # Collective Knowledge framework (CK)
 

appveyor.yml

@@ -21,7 +21,7 @@ install:
 build: false
 
 test_script:
-  - cd ck2
+  - cd cm
   - "%PYTHON%\\python.exe setup.py install"
   - "%PYTHON%\\python.exe -m cmind"
   - "cm"

ck2/README.md

@@ -1,119 +1 @@
-# Collective Mind toolkit
-
-[![PyPI version](https://badge.fury.io/py/cmind.svg)](https://pepy.tech/project/cmind)
-[![Downloads](https://pepy.tech/badge/cmind)](https://pepy.tech/project/cmind)
-[![Python Version](https://img.shields.io/badge/python-3+-blue.svg)](https://github.com/mlcommons/ck/tree/master/ck2)
-[![License](https://img.shields.io/badge/License-Apache%202.0-green)](https://github.com/mlcommons/ck/tree/master/ck2)
-
-
-The Collective Mind toolkit (CM) transforms Git repositories, Docker containers, Jupyter notebooks, zip/tar files
-and any local directory into a collective database of reusable artifacts 
-and automation scripts with a unified interface and extensible meta descriptions.
-
-Our goal is to help researchers and engineers exchange their artifacts, knowledge, 
-experience and best practices in a more automated, reusable, portable and unified way
-across rapidly evolving software and hardware.
-
-CM is motivated by our tedious experience reproducing [150+ ML and Systems papers](https://www.youtube.com/watch?v=7zpeIVwICa4)
-when [our colleagues](https://ctuning.org/ae/committee.html) have spent many frustrating months communicating with each other 
-and trying to understand numerous technical reports, README files, specifications, dependencies, 
-ad-hoc scripts, tools, APIs, models and data sets of all shared projects 
-to be able to [validate experimental results](https://cknowledge.io/?q=%22reproduced-papers%22) 
-and adapt ad-hoc projects to the real world with very diverse 
-and continuously changing software, hardware, user environments, settings and data.
-
-The Collective Mind toolkit is based on the [Collective Knowledge concept (CK)]( https://arxiv.org/abs/2011.01149 )
-that was successfully validated in the past few years to provide a simple, common and extensible format 
-and API for shared projects and make it easier for researchers and engineers to communicate, collaborate and innovate.
-The CK prototype was used to [enable collaborative ML and Systems R&D](https://cKnowledge.org/partners.html),
-[connect MLOps and DevOps](https://github.com/mlcommons/ck-mlops) by treating models, datasets and other artifacts as "code" packages,
-[automate 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 in the real world](https://www.youtube.com/watch?v=1ldgVZ64hEI).
-We are desiging the CM toolkit based on all the feedback we have received from these projects.
-
-See related slides [about our motivation](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
-
-
-
-# Documentation
-
-* [Online docs](https://cknowledge.org/docs/cm)
-
-# Tutorials
-
-* [Converting ad-hoc scripts into intelligent CM components](https://cknowledge.org/docs/cm/tutorial-ic.html)
-* [CM concepts](https://cknowledge.org/docs/cm/tutorial-concept.html)
-
-# Community meetings
-
-* [Public notes](meetings/)
-* [Regular conf-calls](meetings/conf-calls.md)
-
-
-# News
-
-* **2022 May 20:** Brainstorming session for CM-powered ["intelligent components"](https://cknowledge.org/docs/cm/tutorial-ic.html) in Seattle, WA.
-
-* **2022 April 20:** MLCommons virutal community meeting.
-
-* **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 [the Collective Mind toolkit (CK2)](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).
-
-
-
-
-# Development
-
-## CM database
-
-We use [GitHub tickets](https://github.com/mlcommons/ck/issues) 
-to improve and enhance the CM core that manages shared projects
-as a collective database of reusable artifacts and automations.
-Please don't hesitate to share your ideas and report encountered issues!
-
-
-
-## CM-based projects
-
-### Automating development, optimization and deployment of efficient ML Systems
-
-CM provides a common playground and a common language to help researchers and engineers
-discuss and learn how to make benchmarking, optimization, co-design and deployment
-of complex ML Systems more deterministic, portable and reproducible across
-continusly changing software and hardware stacks.
-
-* Common CM repository to bridge [the growing gap](https://www.mihaileric.com/posts/mlops-is-a-mess) 
-  between ML research and production: [GitHub](https://github.com/mlcommons/ck/tree/master/ck2-repo-mlops)
-
-
-
-
-# Related resources
-
-* [MLOps](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)
-* [Arjun Suresh](https://www.linkedin.com/in/arjunsuresh)
+*Moved [here](../cm)*

ck2/CONTRIBUTING.md → cm/CONTRIBUTING.md

@@ -1,6 +1,6 @@
-# Contributing to CM (CK2)
+# Contributing to CM (aka CK2)
 
-* Development website: https://github.com/mlcommons/ck/tree/master/ck2
+* Development website: https://github.com/mlcommons/ck/tree/master/cm
 * Issues: https://github.com/mlcommons/ck/issues (use [CM] prefix)
 * Mailing list: https://groups.google.com/g/collective-knowledge (use [CM] prefix)
 * Discord channel: TBA

cm/README.md

@@ -0,0 +1,119 @@
+# Collective Mind toolkit
+
+[![PyPI version](https://badge.fury.io/py/cmind.svg)](https://pepy.tech/project/cmind)
+[![Downloads](https://pepy.tech/badge/cmind)](https://pepy.tech/project/cmind)
+[![Python Version](https://img.shields.io/badge/python-3+-blue.svg)](https://github.com/mlcommons/ck/tree/master/cm)
+[![License](https://img.shields.io/badge/License-Apache%202.0-green)](https://github.com/mlcommons/ck/tree/master/cm)
+
+
+The Collective Mind toolkit (CM) transforms Git repositories, Docker containers, Jupyter notebooks, zip/tar files
+and any local directory into a collective database of reusable artifacts 
+and automation scripts with a unified interface and extensible meta descriptions.
+
+Our goal is to help researchers and engineers exchange their artifacts, knowledge, 
+experience and best practices in a more automated, reusable, portable and unified way
+across rapidly evolving software and hardware.
+
+CM is motivated by our tedious experience reproducing [150+ ML and Systems papers](https://www.youtube.com/watch?v=7zpeIVwICa4)
+when [our colleagues](https://ctuning.org/ae/committee.html) have spent many frustrating months communicating with each other 
+and trying to understand numerous technical reports, README files, specifications, dependencies, 
+ad-hoc scripts, tools, APIs, models and data sets of all shared projects 
+to be able to [validate experimental results](https://cknowledge.io/?q=%22reproduced-papers%22) 
+and adapt ad-hoc projects to the real world with very diverse 
+and continuously changing software, hardware, user environments, settings and data.
+
+The Collective Mind toolkit is based on the [Collective Knowledge concept (CK)]( https://arxiv.org/abs/2011.01149 )
+that was successfully validated in the past few years to provide a simple, common and extensible format 
+and API for shared projects and make it easier for researchers and engineers to communicate, collaborate and innovate.
+The CK prototype was used to [enable collaborative ML and Systems R&D](https://cKnowledge.org/partners.html),
+[connect MLOps and DevOps](https://github.com/mlcommons/ck-mlops) by treating models, datasets and other artifacts as "code" packages,
+[automate 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 in the real world](https://www.youtube.com/watch?v=1ldgVZ64hEI).
+We are desiging the CM toolkit based on all the feedback we have received from these projects.
+
+See related slides [about our motivation](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
+
+
+
+# Documentation
+
+* [Online docs](https://cknowledge.org/docs/cm)
+
+# Tutorials
+
+* [Converting ad-hoc scripts into intelligent CM components](https://cknowledge.org/docs/cm/tutorial-ic.html)
+* [CM concepts](https://cknowledge.org/docs/cm/tutorial-concept.html)
+
+# Community meetings
+
+* [Public notes](meetings/)
+* [Regular conf-calls](meetings/conf-calls.md)
+
+
+# News
+
+* **2022 May 20:** Brainstorming session for CM-powered ["intelligent components"](https://cknowledge.org/docs/cm/tutorial-ic.html) in Seattle, WA.
+
+* **2022 April 20:** MLCommons virutal community meeting.
+
+* **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 [the Collective Mind toolkit (aka CK2)](https://github.com/mlcommons/ck/tree/master/cm)
+  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).
+
+
+
+
+# Development
+
+## CM database
+
+We use [GitHub tickets](https://github.com/mlcommons/ck/issues) 
+to improve and enhance the CM core that manages shared projects
+as a collective database of reusable artifacts and automations.
+Please don't hesitate to share your ideas and report encountered issues!
+
+
+
+## CM-based projects
+
+### Automating development, optimization and deployment of efficient ML Systems
+
+CM provides a common playground and a common language to help researchers and engineers
+discuss and learn how to make benchmarking, optimization, co-design and deployment
+of complex ML Systems more deterministic, portable and reproducible across
+continusly changing software and hardware stacks.
+
+* Common CM repository to bridge [the growing gap](https://www.mihaileric.com/posts/mlops-is-a-mess) 
+  between ML research and production: [GitHub](https://github.com/mlcommons/ck/tree/master/cm-devops)
+
+
+
+
+# Related resources
+
+* [MLOps](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)
+* [Arjun Suresh](https://www.linkedin.com/in/arjunsuresh)

ck2/cmind/automation.py → cm/cmind/automation.py

@@ -119,7 +119,7 @@ def test(self, i):
         print ('Path to CM repositories:    {}'.format(self.cmind.repos_path))
 
         print ('')
-        print ('GitHub for CM development:  https://github.com/mlcommons/ck/tree/master/ck2')
+        print ('GitHub for CM development:  https://github.com/mlcommons/ck/tree/master/cm')
         print ('Reporting issues and ideas: https://github.com/mlcommons/ck/issues')
 
         return {'return':0}

ck2/cmind/repo/README.md → cm/cmind/repo/README.md

@@ -1,7 +1,7 @@
 # Internal Collective Mind repository
 
-[![CM artifact](https://img.shields.io/badge/Artifact-automated%20and%20reusable-blue)](https://github.com/mlcommons/ck/tree/master/ck2)
-[![CM repository](https://img.shields.io/badge/Collective%20Mind-compatible-blue)](https://github.com/mlcommons/ck/tree/master/ck2)
+[![CM artifact](https://img.shields.io/badge/Artifact-automated%20and%20reusable-blue)](https://github.com/mlcommons/ck/tree/master/cm)
+[![CM repository](https://img.shields.io/badge/Collective%20Mind-compatible-blue)](https://github.com/mlcommons/ck/tree/master/cm)
 
 This internal repository contains CM-compatible artifacts and automations 
 that were moved to the CM core to ensure their stability 

ck2/docs/KB/MLOps.md → cm/docs/KB/MLOps.md

@@ -69,4 +69,4 @@ Here we collect related notes about MLPerf, MLOps, DevOps, inference engines, co
 
 # ML artifact management
 
-- [CM toolkit](https://github.com/mlcommons/ck/tree/master/ck2)
+- [CM toolkit](https://github.com/mlcommons/ck/tree/master/cm)

ck2/docs/conf.py → cm/docs/conf.py

@@ -31,7 +31,7 @@
 release=version
 
 edit_on_github_url='https://github.com'
-edit_on_github_project = 'mlcommons/ck/tree/master/ck2/docs/'
+edit_on_github_project = 'mlcommons/ck/tree/master/cm/docs/'
 
 kernel_file=os.path.join('..', 'cmind', '__init__.py')
 
@@ -135,7 +135,7 @@
     "display_github": True,
     "github_user": "mlcommons",
     "github_repo": "ck",
-    "github_version": "master/ck2/docs/",
+    "github_version": "master/cm/docs/",
 }
 
 html_logo = 'auto/static/logo.png'

ck2/docs/enhancements.md → cm/docs/enhancements.md

@@ -12,7 +12,7 @@ In the CK1, we used explicit indexing of all entries using .cm directories.
 Such mechanism provided a very fast search but it was not very user friendly:
 if a user forgot to add .cm to Git or Zip, the search function was broken.
 
-In the CK2 (CM), we decided to simplify the overall architecture and removed
+In the CM (aka CK2), we decided to simplify the overall architecture and removed
 explicit indexing by default. Now, CM will be searching recursively for entries
 based on UID and alias in their meta description (_cm.yaml | _cm.json).
 

ck2/docs/installation.md → cm/docs/installation.md

@@ -3,7 +3,7 @@
 
 ## Prerequisites
 
-The CM toolkit (CK2 framework) requires minimal dependencies: Python 3.x, PIP and Git. 
+The CM framework (aka CK2) requires minimal dependencies: Python 3.x, PIP and Git. 
 
 ### Linux
 
@@ -85,7 +85,7 @@ Path to CM internal repo:   C:\!Progs\Python39\lib\site-packages\cmind\repo
 
 Path to CM repositories:    D:\Work1\CM\cm-repos
 
-GitHub for CM development:  https://github.com/mlcommons/ck/tree/master/ck2
+GitHub for CM development:  https://github.com/mlcommons/ck/tree/master/cm
 Reporting issues and ideas: https://github.com/mlcommons/ck/issues
 ```
 
@@ -101,7 +101,7 @@ You can use the following environment variables to customize CM installation:
   * *%USERPROFILE%\CM* directory on Windows
 
 * 'CM_CONFIG' - provide full path to a JSON or YAML file with the CM configuration.
-  The content of this file will be merged with the ["cfg" dictionary](https://github.com/mlcommons/ck/blob/master/ck2/cmind/config.py#L23)
+  The content of this file will be merged with the ["cfg" dictionary](https://github.com/mlcommons/ck/blob/master/cm/cmind/config.py#L23)
   from the *config.py*.
 
 * 'CM_DEBUG' - if set to 'yes', turn on internal CM debugging and raise errors