CTuning foundation

The cTuning Foundation is a global non-profit organization developing open-source tools and a common methodology to enable sustainable, collaborative and reproducible research in Computer science,[1] perform collaborative optimization of realistic workloads across devices provided by volunteers, enable self-optimizing computer systems,[2][3] and automate artifact evaluation at machine learning and systems conferences and journals.

The cTuning Foundation
Founded2014 (2014)
FounderGrigori Fursin
TypeNon-profit research and development organization, Engineering organization
Registration no.W943003814
FocusCollaborative software, Open Science, Open Source Software, Reproducibility, Computer Science, Machine learning, Artifact Evaluation, Performance tuning, Knowledge management
Location
OriginsCollective Tuning Initiative & Milepost GCC
Area served
Worldwide
MethodDevelop open-source tools, a public repository of knowledge, and a common methodology for collaborative and reproducible experimentation
Websitectuning.org

Notable projects
  • Collective Knowledge - an open-source framework to organize software projects as a database of reusable components with common automation actions and extensible meta descriptions based on FAIR principles, implement portable research workflows, and crowdsource experiments across diverse platforms provided by volunteers.
  • ACM ReQuEST - Reproducible Quality-Efficient Systems Tournaments to co-design efficient software/hardware stacks for deep learning algorithms in terms of speed, accuracy and costs across diverse platforms, environments, libraries, models and data sets[4]
  • MILEPOST GCC - open-source technology to build machine learning based self-optimizing compilers.
  • CK crowd-tuner - universal, customizable and multi-objective autotuner.[2]
  • CK package and environment manager - python CK API to detect, install and rebuild code and data dependencies for CK workflows.
  • Artifact Evaluation - validation of experimental results from published papers at the computer systems and machine learning conferences.
  • Reproducible Papers - a public index of reproducible papers with portable workflows and reusable research components.

History

Grigori Fursin developed cTuning.org at the end of the Milepost project in 2009 to continue his research on machine learning based program and architecture optimization as a community effort.[5][6]

In 2014, cTuning Foundation was registered in France as a non-profit research and development organization. It received funding from the EU TETRACOM project and ARM to develop the Collective Knowledge Framework and prepare reproducible research methodology for ACM and IEEE conferences.[7]

In 2020, cTuning Foundation joined MLCommons as a founding member to accelerate innovation in ML.[8]

Funding

Current funding comes from the European Union research and development funding programme, Microsoft, and other organizations.[9]

References
  1. 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.
  2. 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)
  3. Fursin, Grigori; Abdul Memon; Christophe Guillon; Anton Lokhmotov (January 2015). Collective Mind, Part II: Towards Performance- and Cost-Aware Software Engineering as a Natural Science. Proceedings of the CPC 2016. arXiv:1506.06256. Bibcode:2015arXiv150606256F.
  4. ACM ReQuEST'18 front matters and report (PDF)
  5. World's First Intelligent, Open Source Compiler Provides Automated Advice on Software Code Optimization, IBM press-release, June 2009 (link)
  6. Grigori Fursin. Collective Tuning Initiative: automating and accelerating development and optimization of computing systems. Proceedings of the GCC Summit'09, Montreal, Canada, June 2009 (link)
  7. Article on TTP project "COLLECTIVE KNOWLEDGE: A FRAMEWORK FOR SYSTEMATIC PERFORMANCE ANALYSIS AND OPTIMIZATION", HiPEACinfo, July 2015 (link)
  8. MLCommons press-release: "MLCommons Launches and Unites 50+ Global Technology and Academic Leaders in AI and Machine Learning to Accelerate Innovation in ML" (link)
  9. cTuning foundation partners


This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.