Efficiently utilizing the resources provided on current petascale and future exascale systems will be a challenging task, potentially causing a large amount of underutilized resources and wasted energy. A promising potential to improve efficiency of HPC applications stems from the significant degree of dynamic behavior, e.g., run-time alternation in application resource requirements in HPC workloads. Manually detecting and leveraging this dynamism to improve performance and energy-efficiency is a tedious task that is commonly neglected by developers. However, using an automatic optimization approach, application dynamism can be analyzed at design-time and used to optimize system configurations at run-time. The European Union Horizon 2020 READEX project will develop a tools-aided scenario based auto-tuning methodology to exploit the dynamic behavior of HPC applications to achieve improved energy-efficiency and performance. Driven by a consortium of European experts from academia, HPC resource providers, and industry, the READEX project aims at developing the first of its kind generic framework for split design-time run-time automatic tuning for heterogeneous system at the exascale level.