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Energy efficiency and energy conservation are one of the most crucialconstraints for meeting the 20MW power envelope desired for exascale systems.Towards this, most of the research in this area has been focused on theutilization of user-controllable hardware switches such as per-core dynamicvoltage frequency scaling (DVFS) and software controlled clock modulation atthe application level. In this paper, we present a tuning plugin for thePeriscope Tuning Framework which integrates fine-grained autotuning at theregion level with DVFS and uncore frequency scaling (UFS). The tuning is basedon a feed-forward neural network which is formulated using PerformanceMonitoring Counters (PMC) supported by x86 systems and trained usingstandardized benchmarks. Experiments on five standardized hybrid benchmarksshow an energy improvement of 16.1% on average when the applications are tunedaccording to our methodology as compared to 7.8% for static tuning.

Modelling DVFS and UFS for Region-Based Energy Aware Tuning of HPC Applications