diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index c8465de35..41100cf26 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -1,3 +1,5 @@ # These owners will be the default owners for everything in the repo. # Unless a later match takes precedence,they will be requested for review when someone opens a pull request. * @mlcommons/wg-ck + +/CODEOWNERS @mlcommons/staff diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 3e1dbddb2..eee843d40 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -14,9 +14,9 @@ Modify the project in your own fork and issue a pull request once you want other to take a look at what you have done and discuss the proposed changes. Ensure that cla-bot and other checks pass for your Pull requests. -## CM project coordinator +## CM framework author -* Grigori Fursin (cTuning.org and cKnowledge.org) +* Grigori Fursin ([cKnowledge.org](https://cKnowledge.org) and [cTuning.org](https://cTuning.org)) ## CM contributors in alphabetical order (suggestions, feedback, scripts) diff --git a/README.md b/README.md index 02100df16..430b18db5 100755 --- a/README.md +++ b/README.md @@ -43,9 +43,9 @@ CK consists of several ongoing sub-projects: * [Modular Python harness for MLPerf loadgen](https://github.com/mlcommons/cm4mlops/tree/main/script/app-mlperf-inference-mlcommons-python) -* [Collective Knowledge Playground](https://access.cKnowledge.org) - an open-source platform to list CM scripts similar to PYPI, - aggregate AI/ML Systems benchmarking results with CM workflows, and organize - [public optimization challenges and reproducibility initiatives](https://access.cknowledge.org/playground/?action=challenges) +* [Collective Knowledge Playground](https://access.cKnowledge.org) - an external platform being developed by [cKnowledge](https://cKnowledge.org) + to list CM scripts similar to PYPI, aggregate AI/ML Systems benchmarking results in a reproducible format with CM workflows, + and organize [public optimization challenges and reproducibility initiatives](https://access.cknowledge.org/playground/?action=challenges) to find the most performance and cost-effective AI/ML Systems. * [CK GUI to run modular benchmarks](https://access.cknowledge.org/playground/?action=howtorun) - such benchmarks @@ -56,18 +56,11 @@ CK consists of several ongoing sub-projects: [Apache 2.0](LICENSE.md) -### Copyright -2022-2024 [MLCommons](https://mlcommons.org) - -### Motivation behind CK and CM projects - -* ACM REP'23 keynote about the MLCommons CM automation framework: [ [slides](https://doi.org/10.5281/zenodo.8105339) ] -* ACM TechTalk'21 about automating research projects: [ [YouTube](https://www.youtube.com/watch?v=7zpeIVwICa4) ] [ [slides](https://learning.acm.org/binaries/content/assets/leaning-center/webinar-slides/2021/grigorifursin_techtalk_slides.pdf) ] ### Documentation -**We plan to rewrite and simplify the CM documentation and tutorials based on user feedback in Q2 2024 - please stay tuned for more details**. +**MLCommons is updating the CM documentation based on user feedback - please stay tuned for more details**. * [CM Getting Started Guide and FAQ](docs/getting-started.md) * [Common CM interface to run MLPerf inference benchmarks](docs/mlperf/inference) @@ -79,14 +72,20 @@ CK consists of several ongoing sub-projects: * [CM and CK history](docs/history.md) +### Citing this project + +Please use this [BibTex file](citation.bib). ### Acknowledgments -This open-source technology is being developed by the [MLCommons Task Force on Automation and Reproducibility](https://github.com/mlcommons/ck/blob/master/docs/taskforce.md) -as a community effort based on user feedback. +The open-source Collective Knowledge (CK v1,v2) and Collective Mind automation frameworks (CM) were developed by [Grigori Fursin](https://cKnowledge.org/gfursin) +and donated to MLCommons to benefit everyone. You can learn more about the motivation behind this project from the following presentations: -We would like to thank all [volunteers, collaborators and contributors](https://github.com/mlcommons/ck/blob/master/CONTRIBUTING.md) -for their support, fruitful discussions, and useful feedback! +* ACM REP'23 keynote about the MLCommons CM automation framework: [ [slides](https://doi.org/10.5281/zenodo.8105339) ] +* ACM TechTalk'21 about automating research projects: [ [YouTube](https://www.youtube.com/watch?v=7zpeIVwICa4) ] [ [slides](https://learning.acm.org/binaries/content/assets/leaning-center/webinar-slides/2021/grigorifursin_techtalk_slides.pdf) ] +We would like to thank all +[volunteers, collaborators and contributors](https://github.com/mlcommons/ck/blob/master/CONTRIBUTING.md) +for their support, fruitful discussions, and useful feedback! We thank the [cTuning foundation](https://cTuning.org), [cKnowledge.org](https://cKnowledge.org) and [MLCommons](https://mlcommons.org) for sponsoring this project! diff --git a/citation.bib b/citation.bib new file mode 100644 index 000000000..08638c3e5 --- /dev/null +++ b/citation.bib @@ -0,0 +1,21 @@ +@article{doi:10.1098/rsta.2020.0211, + author = {Fursin, Grigori}, + title = {Collective knowledge: organizing research projects as a database of reusable components and portable workflows with common interfaces}, + journal = {Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences}, + volume = {379}, + number = {2197}, + pages = {20200211}, + year = {2021}, + doi = {10.1098/rsta.2020.0211}, + URL = {https://royalsocietypublishing.org/doi/abs/10.1098/rsta.2020.0211}, + eprint = {https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2020.0211}, + howpublished = {https://doi.org/10.1098/rsta.2020.0211} +} + +@misc{acm_rep_23_cm_keynote, + author = {Fursin, Grigori}, + year = "2023", + booktitle = "{Keynote at the 1st ACM conference on reproducibility and replicability (ACM REP'23)}", + title = "Collective Mind: toward a common language to facilitate reproducible research and technology transfer", + howpublished = {https://doi.org/10.5281/zenodo.8105339} +} diff --git a/cm/README.md b/cm/README.md index 6027892f1..7a1822d58 100644 --- a/cm/README.md +++ b/cm/README.md @@ -214,7 +214,7 @@ and how to implement and share new automations in your public or private project ### Documentation -**We plan to rewrite and simplify the CM documentation and tutorials based on user feedback in Q2 2024 - please stay tuned for more details**. +**MLCommons is updating the CM documentation based on user feedback - please stay tuned for more details**. * [News](../docs/news.md) * [Getting Started Guide and FAQ](../docs/getting-started.md) @@ -228,18 +228,20 @@ and how to implement and share new automations in your public or private project [Apache 2.0](LICENSE.md) -### Copyright +### Citing this project -2022-2024 [MLCommons](https://mlcommons.org) +Please use this [BibTex file](https://github.com/mlcommons/ck/blob/master/citation.bib). -### Get in touch +### Acknowledgments -Collective Mind workflow automation framework and Collective Knowledge Playground are being developed -by the [MLCommons Task Force on Automation and Reproducibility](https://github.com/mlcommons/ck/blob/master/docs/taskforce.md) -as a community effort. Volunteers are very welcome to help with this community project! +The open-source Collective Knowledge (CK v1,v2) and Collective Mind automation frameworks (CM) were developed by [Grigori Fursin](https://cKnowledge.org/gfursin) +and donated to MLCommons to benefit everyone. You can learn more about the motivation behind this project from the following presentations: -### Acknowledgments +* ACM REP'23 keynote about the MLCommons CM automation framework: [ [slides](https://doi.org/10.5281/zenodo.8105339) ] +* ACM TechTalk'21 about automating research projects: [ [YouTube](https://www.youtube.com/watch?v=7zpeIVwICa4) ] [ [slides](https://learning.acm.org/binaries/content/assets/leaning-center/webinar-slides/2021/grigorifursin_techtalk_slides.pdf) ] -CK and CM are community projects based on the feedback from our users and MLCommons members. -We would like to thank all [collaborators and contributors](https://github.com/mlcommons/ck/blob/master/CONTRIBUTING.md) +We would like to thank all +[volunteers, collaborators and contributors](https://github.com/mlcommons/ck/blob/master/CONTRIBUTING.md) for their support, fruitful discussions, and useful feedback! +We thank the [cTuning foundation](https://cTuning.org), [cKnowledge.org](https://cKnowledge.org) +and [MLCommons](https://mlcommons.org) for sponsoring this project!