Energy saving of cluster computing by CPU frequency Tuning using genetic algorithm
Zainab A. Abdulazeez1,*, Nihad Abduljalil2, Ahmed B. M. Fanfakh3, Ali Kadhum M. Al-Qurabat4, Esraa H. Alwan5
1 College of Education for Human Sciences, University of Karbala, 56001, Iraq
2 Department of Air Conditioning and Refrigeration, University of Warith Al-Anbiyaa, Karbala 56001, Iraq
3 Department of Computer Science, College of science for women, University of Babylon, Babylon, 51002, Iraq
4 Department of Cyber Security, College of Sciences, Al-Mustaqbal university, 51001, Babylon, Iraq
5 Department of Computer Science, College of science for women, University of Babylon, Babylon, 51002, Iraq
Emails: zainab.abdulhameed@uokerbala.edu.iq, nihad.ab@uowa.edu.iq, ahmed.fanfakh@uobabylon.edu.iq, ali.kadhum.mohammed@uomus.edu.iq, esras.hadi@uobabylon.edu.iq
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Abstract
Dynamic voltage and frequency scaling (DVFS) is a tool used primarily to decrease computer processor energy consumption by lowering its operational frequency. Their only downside is that they distract from the efficiency of parallel applications while operating on parallel platforms. In a heterogeneous cluster architecture, however, a genetic algorithm is being implemented and applied to model the best trade-off between energy-saving and parallel application performance degradation. The proposed algorithm selects the best frequency vector in order to accomplish these objectives by providing the same compromise. So, the objective function of the genetic algorithm at the same time gives limited energy consumption and minimum decreases in performance. The SimGrid simulator will be used for all experiments. The suggested algorithm saves the average energy by (20 %) and the application performance degrades to the limit (0.15 %).
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Keywords: Genetic algorithm; heterogeneous cluster; frequency scaling; energy consumption