Energy efficiency and consumption are currently the challenging issues in current Petascale and in designing future Exascale systems. The European Union Horizon 2020 project READEX (Runtime Exploitation of Application Dynamism for Energy-efficient Exascale computing) develops a tools-aided online approach to analyze and auto-tune HPC applications for energy efficiency on Exascale systems. It exploits dynamism that occurs due to the variation in the application behavior between iterations of the time loop as well as changing control flow within the time loop. This paper describes the readex_interphase tuning plugin, which analyzes the inter-loop dynamism. The plugin performs clustering using DBSCAN for normalized PAPI metrics, and computes the best tuning parameter settings for each cluster. It verifies the cluster analysis results, and finally computes static and dynamic savings. The inter-phase tuning strategy was evaluated for miniMD and INDEED, and the energy savings obtained validate the effectiveness of this methodology.