TY - JOUR A1 - Schuchart, Joseph A1 - Gerndt, Michael A1 - Kjeldsberg, Per Gunnar A1 - Diethelm, Kai A1 - Lysaght, Michael A1 - Horák, David A1 - Říha, Lubomír A1 - Gocht, Andreas A1 - Sourouri, Mohammed A1 - Kumaraswamy, Madhura A1 - Chowdhury, Anamika A1 - Jahre, Magnus A1 - Bouizi, Othman A1 - Sabir Mian, Umbreen A1 - Kružík, Jakub A1 - Sojka, Radim A1 - Beseda, Martin A1 - Kannan, Venkatesh A1 - Bendifallah, Zakaria A1 - Hackenberg, Daniel A1 - Nagel, Wolfgang E. T1 - The READEX formalism for automatic tuning for energy efficiency JF - Computing N2 - 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. Y1 - 2017 U6 - https://doi.org/10.1007/s00607-016-0532-7 VL - 99 SP - 727 EP - 745 ER - TY - CHAP A1 - Kjeldsberg, Per Gunnar A1 - Schöne, Robert A1 - Gerndt, Michael A1 - Diethelm, Kai A1 - Říha, Lubomír A1 - Kannan, Venkatesh A1 - Sawley, Marie-Christine A1 - Zapletal, Jan A1 - Gocht, Andreas A1 - Reissmann, Nico A1 - Vysocky, Ondrei A1 - Kumaraswamy, Madhura A1 - Nagel, Wolfgang E. ED - Catthoor, Francky ED - Basten, Twan ED - Zompakis, Nikolaos ED - Geilen, Marc ED - Kjeldsberg, Per Gunnar T1 - Run-Time Exploitation of Application Dynamism for Energy-Efficient Exascale Computing T2 - System-Scenario-based Design Principles and Applications N2 - 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. Y1 - 2020 SN - 978-3-030-20342-9 SN - 978-3-030-20343-6 U6 - https://doi.org/10.1007/978-3-030-20343-6_6 SP - 113 EP - 126 PB - Springer CY - Cham ER -