Software and hardware optimization and co-design of HPC systems becomes
intolerably complex, ad-hoc, time consuming and error prone due to enormous
number of available design and optimization choices, complex interactions
between all software and hardware components, and multiple strict
requirements placed on performance, power consumption, size, reliability
and cost.

We present our novel long-term holistic and practical solution to this
problem based on customizable, plugin-based, open-source Collective Mind
repository and infrastructure with unified web interfaces. This
collaborative framework distributes multi-objective auto-tuning among many
participants while utilizing any available smart phone, tablet, laptop,
cluster or data center, and continuously observing, classifying and
modeling realistic their behavior. Any unexpected behavior is analyzed
using shared data mining and predictive modeling plugins or exposed to the
community at cTuning.org for collaborative explanation. Gradually
increasing optimization knowledge helps to continuously improve
optimization heuristics of any compiler, predict optimizations for new
programs or suggest efficient run-time adaptation strategies depending on
end-user requirements. Already available public repository with thousands
of shared codelets, numerical applications, data sets, models, universal
experimental pipelines, and unified tools enables systematic, reproducible
and collaborative R&D with a new publication model where experiments and
techniques are validated and improved by the community.