COMPARISON OF SORTING ALGORITHMS BASED ON ENERGY CONSUMPTION
Creators
- 1. Department of Computer Science and Engineering, APS College of Engineering, Bangalore, Karnataka
Description
Use of computers, mobile phones and various hand held electronic devices are increasing rapidly in recent years. Several applications run simultaneously in these devices and some of the devices like mobile phones and laptops are battery powered. Desktop computers and servers running several applications starting from simple word processing to complex big data analytics, also consume a large amount of energy. Energy consumed mostly by hardware of the devices such as by CPU, memory units, networking interfaces and so on have become area of serious concern and the subject of Green Software Engineering have emerged to study ways for reducing energy consumption. Computer scientists and engineers are seriously looking at reducing energy consumption by various means including redesigning the algorithms. In the area of Green Software Engineering, accurate measurement of energy consumption is very important and various tools have been suggested for the purpose. In this paper, we have measured the energy consumption of various sorting algorithms using open source library jRAPL [6]. The energy consumed in joules was measured on six sorting algorithms and the values compared for different data sets. Comparison of the results is given in the paper.
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References
- 1. C. Calero and M. Piattini, "Introduction to Green in Software Engineering"Springer International Publishing Switzerland, 2015. 2. Smart 2020: Enabling the Low Carbon Economy in the Information Age, tech. report, Climate Group, 2008; www.smart2020.org/_assets/fi les/02_Smart2020Report.pdf. 3. N. Rajovic et al., "Supercomputing with Commodity CPUs:Are Mobile SoCs Ready for HPC?," Proc. Int'l Conf. High PerformanceComputing, Networking, Storage, and Analysis (SC13), 2013, article no. 40. 4. EfraimRotem et al., "H-EARtH: Heterogeneous Multicore Platform Energy Management", IEEE Computer, Volume: 49, Issue: 10, Oct. 2016, pp. 47-55. 5. Ryan E. Grant et al., "Standardizing Power Monitoring and Control at Exascale" IEEE Computer, Volume: 49, Issue: 10, Oct. 2016, pp. 38-46. 6. Kenan Liu, "Data-Oriented Characterization of Application-Level Energy Optimization" , Springer Link LNCS, 2015, volume 9033, pp 316-331. 7. https://en.wikipedia.org/wiki/