Collective Knowledge (software)

The Collective Knowledge (CK) project is an open-source framework and repository to enable collaborative, reproducible and sustainable research and development of complex computational systems.[1][2] CK is a small, portable, customizable and decentralized infrastructure helping researchers and practitioners:

Collective Knowledge (CK)
Developer(s)Grigori Fursin and the cTuning foundation
Initial release2014 (2014)
Stable release
1.55.0 / November 17, 2020 (2020-11-17)
Written inPython
Operating systemLinux, Mac OS X, Microsoft Windows, Android
TypeKnowledge management, Data management, Artifact Evaluation, Package management system, Scientific workflow system, DevOps, Continuous integration, Reproducibility
LicenseBSD License 3-clause
Websitegithub.com/ctuning/ck, cknowledge.io

Notable usages

Portable package manager for portable workflows

CK has an integrated cross-platform package manager with Python scripts, JSON API and JSON meta-description to automatically rebuild software environment on a user machine required to run a given research workflow.[17]

Reproducibility of experiments

CK enables reproducibility of experimental results via community involvement similar to Wikipedia and physics. Whenever a new workflow with all components is shared via GitHub, anyone can try it on a different machine, with different environment and using slightly different choices (compilers, libraries, data sets). Whenever an unexpected or wrong behavior is encountered, the community explains it, fixes components and shares them back as described in.[4]

References

  1. Fursin, Grigori (October 2020). Collective Knowledge: organizing research projects as a database of reusable components and portable workflows with common APIs (PDF). Philosophical Transactions of the Royal_Society. Retrieved 22 October 2020.
  2. Fursin, Grigori; Anton Lokhmotov; Ed Plowman (January 2016). Collective Knowledge: Towards R&D Sustainability. Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition (DATE). Retrieved 14 September 2016.
  3. reusable CK components and actions to automate common research tasks
  4. Grigori Fursin, Anton Lokhmotov, Dmitry Savenko, Eben Upton. A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques, arXiv:1801.08024, January 2018 (arXiv link, interactive report with reproducible experiments)
  5. Online repository with reproduced results
  6. Index of reproduced papers
  7. HiPEAC info (page 17) (PDF), January 2016
  8. Ed Plowman; Grigori Fursin, ARM TechCon'16 presentation "Know Your Workloads: Design more efficient systems!"
  9. Reproducibility of Results in the ACM Digital Library
  10. Artifact Evaluation for systems and machine learning conferences
  11. EU TETRACOM project to combine CK and CLSmith (PDF), archived from the original (PDF) on 2017-03-05, retrieved 2016-09-15
  12. Artifact Evaluation Reproduction for "Software Prefetching for Indirect Memory Accesses", CGO 2017, using CK
  13. GitHub development website for CK-powered Caffe
  14. Open-source Android application to let the community participate in collaborative benchmarking and optimization of various DNN libraries and models
  15. Reproducing Quantum results from Nature – how hard could it be?
  16. MLPerf crowd-benchmarking
  17. List of shared CK packages
  • Development site:
  • Documentation:
  • Public repository with crowdsourced experiments:
  • International Workshop on Adaptive Self-tuning Computing System (ADAPT) uses CK to enable public reviewing of publications and artifacts via Reddit:
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