@article{SchuchartGerndtKjeldsbergetal., author = {Schuchart, Joseph and Gerndt, Michael and Kjeldsberg, Per Gunnar and Diethelm, Kai and Lysaght, Michael and Hor{\´a}k, David and Ř{\´i}ha, Lubom{\´i}r and Gocht, Andreas and Sourouri, Mohammed and Kumaraswamy, Madhura and Chowdhury, Anamika and Jahre, Magnus and Bouizi, Othman and Sabir Mian, Umbreen and Kruž{\´i}k, Jakub and Sojka, Radim and Beseda, Martin and Kannan, Venkatesh and Bendifallah, Zakaria and Hackenberg, Daniel and Nagel, Wolfgang E.}, title = {The READEX formalism for automatic tuning for energy efficiency}, series = {Computing}, volume = {99}, journal = {Computing}, doi = {10.1007/s00607-016-0532-7}, pages = {727 -- 745}, abstract = {Energy efficiency is an important aspect of future exascale systems, mainly due to rising energy cost. Although High performance computing (HPC) applications are compute centric, they still exhibit varying computational characteristics in different regions of the program, such as compute-, memory-, and I/O-bound code regions. Some of today's clusters already offer mechanisms to adjust the system to the resource requirements of an application, e.g., by controlling the CPU frequency. However, manually tuning for improved energy efficiency is a tedious and painstaking task that is often neglected by application developers. The European Union's Horizon 2020 project READEX (Runtime Exploitation of Application Dynamism for Energy-efficient eXascale computing) aims at developing a tools-aided approach for improved energy efficiency of current and future HPC applications. To reach this goal, the READEX project combines technologies from two ends of the compute spectrum, embedded systems and HPC, constituting a split design-time/runtime methodology. From the HPC domain, the Periscope Tuning Framework (PTF) is extended to perform dynamic auto-tuning of fine-grained application regions using the systems scenario methodology, which was originally developed for improving the energy efficiency in embedded systems. This paper introduces the concepts of the READEX project, its envisioned implementation, and preliminary results that demonstrate the feasibility of this approach.}, language = {en} } @incollection{KjeldsbergSchoeneGerndtetal., author = {Kjeldsberg, Per Gunnar and Sch{\"o}ne, Robert and Gerndt, Michael and Diethelm, Kai and Ř{\´i}ha, Lubom{\´i}r and Kannan, Venkatesh and Sawley, Marie-Christine and Zapletal, Jan and Gocht, Andreas and Reissmann, Nico and Vysocky, Ondrei and Kumaraswamy, Madhura and Nagel, Wolfgang E.}, title = {Run-Time Exploitation of Application Dynamism for Energy-Efficient Exascale Computing}, series = {System-Scenario-based Design Principles and Applications}, booktitle = {System-Scenario-based Design Principles and Applications}, editor = {Catthoor, Francky and Basten, Twan and Zompakis, Nikolaos and Geilen, Marc and Kjeldsberg, Per Gunnar}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-20342-9}, doi = {10.1007/978-3-030-20343-6_6}, pages = {113 -- 126}, abstract = {As in the embedded systems domain, energy efficiency has recently become one of the main design criteria in high performance computing. The European Union Horizon 2020 project READEX (Run-time Exploitation of Application Dynamism for Energy-efficient eXascale computing) has developed a tools-aided auto-tuning methodology inspired by system scenario based design. Applying similar concepts as those presented in earlier chapters of this book, the dynamic behavior of HPC applications is exploited to achieve improved energy efficiency and performance. Driven by a consortium of European experts from academia, HPC resource providers, and industry, the READEX project has developed the first generic framework of its kind for split design-time and run-time tuning while targeting heterogeneous systems at the Exascale level. Using a real-life boundary element application, energy savings of more than 30\% can be shown.}, language = {en} }