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15 \emph{ \begin{center} \Large Energy Consumption Optimization of Parallel Iterative Applications using CPU Frequency Scaling\end{center}}
16 %\emph{ \begin{center} \large By \end{center}}
17 \emph{ \begin{center} \large Ahmed Badri Muslim Fanfakh \\ University of Franche-Comt\'e, 2016 \end{center}}
18 %\emph{ \begin{center} \large The University of Franche-Comt\'e, 2015 \end{center}}
19 \emph{ \begin{center} \large Supervisors: Raphaël Couturier, Jean-Claude Charr and Arnaud Giersch \end{center}}
22 In recent years, green computing has become an important topic in the supercomputing
23 research domain. However, the computing platforms are still consuming more and more energy due to the increasing number of nodes composing them.
24 To minimize the operating costs of these platforms many techniques have
25 been used. Dynamic voltage and frequency scaling (DVFS) is one of them. It
26 can be used to reduce the power consumption of the CPU while computing, by
27 lowering its frequency. However, lowering the frequency of a CPU may increase
28 the execution time of an application running on that processor. Therefore, the
29 frequency that gives the best trade-off between the energy consumption and the
30 performance of an application must be selected.
31 In this thesis, a set of works are presented to optimize the energy consumption
32 and the performance of the synchronous and asynchronous message passing iterative applications running over clusters and grids. The energy consumption and performance models for each type of iterative application
33 are well modelled and defined according to the characteristics of both the application itself and the parallel architecture executing this application.
35 Firstly, we propose a frequency scaling factors selection algorithm for synchronous iterative applications running over a homogeneous platform. It is applied to the NAS parallel benchmarks and stimulated by SimGrid simulator.
36 Secondly, we develop two frequency scaling factors selection algorithms for synchronous iterative applications running over a heterogeneous cluster and grid. Both algorithms are implemented to the NAS parallel benchmarks and conducted over SimGrid simulator and Grid'5000 testbed.
37 Thirdly, we propose a frequency scaling factors selection algorithm for an asynchronous and a hybrid iterative applications running over a grid. The algorithm is evaluated over SimGrid simulator and Grid'5000 testbed while running a multi-splitting application that solves 3D problem.
38 All the proposed algorithms are compared to an existing methods, which are the Rauber and Rünger and the energy and delay products (EDP) methods. The comparison results show that all the proposed algorithms give better energy consumption and performance trade-off results. The proposed algorithms have a very small overhead on the execution time of the applications and they work online without training and profiling.
40 \textbf{KEY WORDS:} Dynamic voltage and frequency scaling, Grid computing, Energy optimization, iterative applications and frequency scaling online algorithm.