Abstract
Since the demand for computing power increases, new architectures emerged to obtain better performance. Reducing the power and energy consumption of these architectures is one of the main challenges to achieving high-performance computing. Current research trends aim at developing new software and hardware techniques to achieve the best performance and energy trade-offs. In this work, we investigate the impact of different CPU frequency scaling techniques such as ondemand, performance, and powersave on the power and energy consumption of multi-core based computer infrastructure. We apply these techniques in PAMPAR, a parallel benchmark suite implemented in PThreads, OpenMP, MPI-1, and MPI-2 (spawn). We measure the energy and execution time of 10 benchmarks, varying the number of threads. Our results show that although powersave consumes up to 43.1% less power than performance and ondemand governors, it consumes the triple of energy due to the high execution time. Our experiments also show that the performance governor consumes up to 9.8% more energy than ondemand for CPU-bound benchmarks. Finally, our results show that PThreads has the lowest power consumption, consuming less than the sequential version for memory-bound benchmarks. Regarding performance, the performance governor achieved 3% of performance over the ondemand.
This research received funding from Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior - Brasil (CAPES) - Finance Code 001, FAPERGS 01/2017-ARD project ParaElastic (N\(^{\text {o}}\) 17/2551-0000871-5), FAPERGS 05/2019-PQG project ParAS (N\(^{\text {o}}\) 19/2551-0001895-9), and Universal MCTIC/CNPq N\(^{\text {o}}\) 28/2018 project SParCloud (No. 437693/2018-0). It has also been supported by National Council for Scientific and Technological Development (CNPq) and Green Cloud project (2016/2551-0000 488-9), from FAPERGS and CNPq Brazil, program PRONEX 12/2014.
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Garcia, A.M., Serpa, M., Griebler, D., Schepke, C., Fernandes, L.G.L., Navaux, P.O.A. (2020). The Impact of CPU Frequency Scaling on Power Consumption of Computing Infrastructures. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12254. Springer, Cham. https://doi.org/10.1007/978-3-030-58817-5_12
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