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.
The non-profit cTuning foundation
and dividiti regularly help various
international projects (MILEPOST,
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 help colleagues from the University of Edinburgh and Glasgow
use CK to automate and crowdsource optimization of mathematical libraries
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.
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!