About Partners Achievements Activities Education Contact
Contact us if you need help with sharing research artifacts and developing sustainable research software!
We would like to thank the following organizations for supporting our open-source technology, international open science initiative and open challenges
Raspberry Pi foundation supports our educational initiative since 2017 to teach students and researchers how to develop sustainable research software, share artifacts, and 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) supports our artifact evaluation initiave for the leading computer systems conferences and evaluates our Collective Knowledge technology to share artifacts and experimental workflows as reusable and sustainable components along with reproducible publications. We are also a part of the ACM workgroup on reproducibility preparing a common policy on artifact review and badging.

We partnered with ARM to enchance open-source tools, public optimization repository and scientific methodology to design more efficient computer systems for emerging workloads such as deep learning across the whole SW/HW stack from IoT to HPC based on Collective Knowledge technology and ARM's workload automation. See 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.
TETRACOM project provided initial funding for our non-profit organization in 2014-2015 to develop Collective Knowledge Technology. We successfully completed the project, released open-source framework, and won HiPEAC technology transfer award.

We 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!

Nvidia regularly sponsors awards for the highest ranked artifacts at our artifact evaluation events since 2014.
We jointly organize Artifact Evaluation at CGO, PPoPP, PACT and other computer systems conferences since 2015. We also collaborate on a common methodology for reproducible articles.
We help several groups in the University of Cambridge to use Collective Knowledge framework and develop sustainable research software, automate and accelerate 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 (see GitHub artifacts, Paper with AE appendix and CK workflow and a PDF snapshot of the interactive CK dashboard).
We help Alastair Donaldson's group to automate and crowdsource detection of compiler bugs (crowd-fuzzing of traditional, OpenCL and OpenGL compilers) using combination of CK, CLSmith and other tools.
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.
We collaborated with IBM and other partners in 2006-2009 to develop the world's first open-source, machine learning based, self-optimizing compiler based on cTuning technology (see IBM press-release, project page, journal paper, long-term vision paper). More importantly, we developed CK-based workflows to continue this research with the community even after the end of this project.
dividiti sponsors development of the open-source research SDK (CK), public repository of optimization knowledge, scientific methodology for computer engineering, and organization of Artifact Evaluation at the leading computer systems conferences since 2015.
We would like to thank all cTuning supporters as well as CK contributors and participants in public discussions via Collective Knowledge and cTuning mailing lists and LinkedIn group.
          
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