A study led by researchers from three universities in Portugal tested 27 programming languages for energy efficiency, speed, and memory usage. The research aimed to explore whether energy consumption can reveal insights into the quality of programming languages.
By running 10 algorithmic problems through the Computer Language Benchmarks Game, the researchers found that compiled languages like C, C++, and Rust were the most energy-efficient and fastest, often outperforming interpreted languages. However, the results varied depending on the specific task. For instance, while C was the most energy-efficient overall, Rust excelled in specific tasks like DNA sequence scanning. These results highlighted that the fastest language is not always the most energy-efficient, contradicting the common belief that faster execution directly correlates with lower energy consumption.
The study also found significant differences between compiled, interpreted, and virtual machine languages. On average, compiled languages consumed much less energy than interpreted languages, with compiled languages requiring 120 joules to run benchmark problems, while interpreted languages used 2,365 joules.
In addition to energy usage, the researchers analyzed the impact of different programming paradigms on efficiency. They discovered that imperative programming languages often outperformed object-oriented, functional, and scripting paradigms in both speed and energy efficiency.
Ultimately, the study revealed that no single programming language is universally superior in terms of energy efficiency, with the best choice depending on the specific requirements of the task at hand. This research provides valuable insights for developers, particularly those working with power-constrained applications like mobile devices or IoT systems, where energy efficiency is critical.
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