@inproceedings{8d59e3384b63400488c1b13d23089a78,
title = "The READEX project for dynamic energy efficiency tuning",
abstract = "High Performance Computing (HPC) systems consume a lot of energy. The overall energy consumption is one of the biggest challenges on the way towards exascale computers. Therefore, energy reduction techniques have to be applied on all levels from the basic chip technology up to the data center infrastructure. The READEX project explores the potential of dynamically switching application and system parameters, such as the clock frequency of the cores, to reduce the overall energy consumption of applications. An analysis is performed during application design time to precompute a tuning model that is then input to the runtime tuning library. This library switches the application and system configuration at runtime to adapt to varying application characteristics.",
keywords = "Autotuning, Energy efficiency, High Performance Computing",
author = "Michael Gerndt",
year = "2016",
month = may,
day = "31",
doi = "10.1145/2916026.2916033",
language = "English",
series = "SEM4HPC 2016 - Proceedings of the ACM Workshop on Software Engineering Methods for Parallel and High Performance Applications, Co-located with HPDC 2016",
publisher = "Association for Computing Machinery, Inc",
pages = "11--12",
booktitle = "SEM4HPC 2016 - Proceedings of the ACM Workshop on Software Engineering Methods for Parallel and High Performance Applications, Co-located with HPDC 2016",
note = "ACM Workshop on Software Engineering Methods for Parallel and High Performance Applications, SEM4HPC 2016 ; Conference date: 31-05-2016",
}
