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We help General Motors with AI/SW/HW co-design. We use CK to crowd-benchmark and crowd-tune AI across the whole SW/HW/model/data set stack. See GM's presentation from the Embedded Vision Summit about CK-powered CNN/SW/HW benchmarking here:

CK-powered AI ] [ CK repository of reusable AI artifacts ]
We help ARM use our Collective Knowledge Technology to design more efficient computer systems for emerging workloads such as deep learning across the whole SW/HW stack from IoT to HPC. See ARM's video from the Embedded Vision Summit about CK-powered collaborative DNN co-design, HiPEAC info (page 17) for more details about ARM and the cTuning foundation using CK to accelerate computer engineering, and a demo about connecting CK and ARM's workload automation, and building a representative set of applications and data sets from ARM TechCon'16.

Open optimization repository ]
We collaborate with Raspberry Pi foundation for a new educational initiative to teach students and researchers how to automatically optimize and test (autotuning, crowd-tuning and crowd-fuzzing) realistic workloads in terms of speed, size, energy usage, accuracy and costs across diverse software and hardware stack using CK workflow framework and open optimization repository.
Association for Computing Machinery (ACM) evaluates Collective Knowledge technology to share artifacts and experimental workflows as reusable and customizable components along with reproducible publications as a part of Artifact Evaluation initiative.

ACM CK video ]
TETRACOM project provided initial funding for our non-profit organization in 2014-2015 to prototype Collective Knowledge Technology. CK later won HiPEAC technology transfer award.

The non-profit cTuning foundation and dividiti regularly help various international projects (MILEPOST, CARP, PAMELA) and assist scientists in crowdsourcing and reproducing experiments, and developing customizable and sustainable research software powered by CK which can now survive in a Cambrian AI/SW/HW chaos or when leading researchers leave!

We collaborative with colleagues from the University of Edinburgh and Glasgow use CK to automate and crowdsource optimization of mathematical libraries and compilers.

Michel Steuwer blog about CK ]
We help colleagues from ENS Paris to automate and crowdsource polyhedral optimization using CK.
We assist colleagues from Hartree SuperComputing Center to use CK for customizable and sustainable experimental workflows and collaboratively optimize realistic workloads across various HPC systems.
University of Cambridge colleagues use Collective Knowledge framework to develop sustainable software, accelerate research, automate experimentation and reuse artifacts. For example, portable and reproducible experimental workflow from the "Software Prefetching for Indirect Memory Accesses" article by Sam Ainsworth and Timothy M. Jones received a distinguished artifact award at CGO'17.

GitHub artifacts ] [ Paper with AE appendix and CK workflow ] [PDF snapshot of the interactive CK dashboard ]
Alastair Donaldson's group uses CK to automate and crowdsource detection of compiler bugs (crowd-fuzzing of traditional, OpenCL and OpenGL compilers). TETRACOM project "CLmith in Collective Knowledge" won HiPEAC technology transfer award in 2016.

CK-CLsmith GitHub repo ]
We have a successful and productive partnership with Xored to develop various open-source CK extensions since 2016 including DNN engine optimization front-end and Android app to crowdsource DNN benchmarking.

Non-profit cTuning foundation is the main coordinator and sponsor of all CK developments and CK-powered educational initiatives such as Artifact Evaluation. It also partnered with dividiti to facilitate technology transfer from academia to industry while boosting innovation in science and technology!
We would like to thank all CK contributors and participants in public discussions via Collective Knowledge mailing list and our LinkedIn group.
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