News: the cTuning foundation and OctoML donated CK and MLOps components to MLCommons in September 2021 to continue further developments within a new working group to automate design space exploration of ML Systems - more details to come soon!
We collaborate with the Association for Computing Machinery (ACM), the Raspberry Pi foundation, and ML&systems conferences to share digital artifacts along with published papers in the form of portable CK workflows, automation actions, and reusable components. The goal is to make it easier for researchers and practitioners to reproduce and compare research techniques, build upon them, and participate in collaborative ML&systems benchmarking and optimization.
cKnowledge.io is an open platform developed by Grigori Fursin (CK author) to automate software/hardware co-design for the realistic AI/ML tasks from end-users based on their requirements and constraints. This platform aggregates portable CK workflows and components from the community for diverse ML models, data sets, frameworks and platforms from the cloud to the edge. It is then possible to perform automated design space exploration of AI/ML/SW/HW stacks and find the most optimal ones on a Pareto frontier in terms of accuracy, latency, throughput, energy, costs and other characteristics that satisfy user constraints. This platform was acquired by OctoML.ai in 2021.
Arm is one of the first and main users of the Collective Knowledge Technology to automate the design of the more efficient computer systems for emerging workloads such as deep learning across the whole SW/HW stack from IoT to HPC. See the HiPEAC info (page 17) and the Arm TechCon'16 demo for more details about Arm and the cTuning foundation using CK to accelerate computer engineering.
We collaborate with colleagues from TomTom on a model-driven approach for a new generation of adaptive libraries, while automating and crowdsourcing experiments and ML-based modeling using the Collective Knowledge framework.
We collaborate with the colleagues from the University of Edinburgh and Glasgow use CK to automate and crowdsource optimization of mathematical libraries and compilers.
We collaborate with the colleagues from ENS Paris to automate and crowdsource polyhedral optimization using CK.
We collaborate with the 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.
KRAI is an engineering company that develops open-source CK workflows to automate MLPerf™ submissions and provides optimization services to co-design efficient SW/HW stacks for robotics.