Ranking programming languages by energy efficiency

Abstract

This paper compares a large set of programming languages regarding their efficiency, including from an energetic point-of-view. Indeed, we seek to establish and analyze different rankings for programming languages based on their energy efficiency. The goal of being able to rank languages with energy in mind is a recent one, and certainly deserves further studies. We have taken 19 solutions to well defined programming problems, expressed in (up to) 27 programming languages, from well know repositories such as the Computer Language Benchmark Game and Rosetta Code. We have also built a framework to automatically, and systematically, run, measure and compare the efficiency of such solutions. Ultimately, it is based on such comparison that we propose a serious of efficiency rankings, based on multiple criteria. Our results show interesting findings, such as, slower/faster languages consuming less/more energy, and how memory usage influences energy consumption. We also show how to use our results to provide software engineers support to decide which language to use when energy efficiency is a concern.