Designing, porting and optimizing applications for rapidly evolving computing systems is often complex, ad-hoc, repetitive, costly and error prone process due to an enormous number of available design and optimization choices combined with the complex interactions between all components.
I will present a possible solution to this fundamental problem based on collective participation of users combined with empirical tuning and predictive modeling. I will describe public Collective Tuning Repository and new projects for collaborative application characterization and optimization. With continuously increasing and systematized knowledge about behavior of computer systems, users should be able to obtain scientifically motivated advices about anomalies in the behavior of their applications and possible solutions to effectively balance performance and power consumption. I believe that such approach will be vital for developing efficient Exascale computing systems.