Experience and Guidelines for Sorting Algorithm Choices and Their Energy Efficiency

Abstract

Energy efficiency has become a major concern in the IT sector as the energy demand for data centers is projected to reach 1PWh per year by 2030. While hardware designers improve the energy efficiency of their products, software developers often do not consider or are unaware of the impact their design choices can make on the energy consumption caused by the execution of their applications. Energy efficiency improvements in applications can, to a certain extent, be achieved through compiler optimizations. Nonetheless, software developers should still make reasonable design choices to improve energy efficiency further. In this paper, we present the energy efficiency of common sorting algorithms under different pre-sorted conditions. Previous work in this field considered only randomized data. We expand on this previous work and measure the sorting algorithms' energy efficiency when the data is already partially sorted to 20% and 50%. Our presented experience is a case study intended to demonstrate the effect simple design choices, such as the selection of algorithm as well as its implementation, can make on energy efficiency. It is intended for industry practitioners to aid them in selecting a more energy-efficient algorithm for their problems at hand through helpful guidelines. Our results also can function as an incentive to make energy efficiency a non-functional requirement for tenders, and as a motivation for researchers to include energy efficiency as an additional quality criterion when studying the properties of algorithms.