The video analyzes a 2021 study revealing that Python is 71 times slower and uses 76 times more energy than C, highlighting concerns about the efficiency of higher-level programming languages. It emphasizes the importance of choosing more efficient languages like C or Rust for compute-intensive applications to reduce energy consumption and improve performance.
https://www.sciencedirect.com/science/article/abs/pii/S0167642321000022.
The video discusses a study from 2021 that compares the performance and energy efficiency of various programming languages, highlighting that Python is significantly slower and consumes more energy than C. The study found that Python is 71 times slower and uses 76 times more energy than C when performing the same tasks. This finding is particularly striking given Python’s widespread use in many applications, especially in Linux environments, where many scripts and tools are written in Python.
The benchmarks used in the study included a range of programming languages and focused on ten well-defined problems. The researchers aimed to measure execution time, energy consumption, and memory usage across 27 different languages. The results revealed a clear hierarchy in performance, with C being the fastest and most energy-efficient language, followed closely by Rust. Other languages, such as JavaScript, Ruby, and Perl, ranked much lower in terms of efficiency, with Python standing out as one of the slowest and most energy-intensive options.
In terms of energy consumption, the study noted that Perl was the most energy-intensive language, using 79.5 times more energy than C, followed by Ruby at 69 times more. The correlation between execution time and energy usage became evident, indicating that slower languages inherently consume more energy due to prolonged execution. The study emphasized that if programmers are genuinely concerned about energy efficiency and environmental impact, they should prioritize using languages like C instead of higher-level languages like Python, Ruby, or Swift.
The analysis of memory usage showed that Pascal outperformed C in terms of memory efficiency, while C still maintained a low memory footprint compared to many other languages. Various languages, including Java and Rust, also demonstrated higher memory usage rates, with some languages consuming up to 20 times more memory than Pascal for similar tasks. The video stresses the importance of considering these metrics when choosing a programming language, especially for compute-intensive applications.
The presenter questions the trend of newer programming languages consistently being slower and less efficient than their predecessors, suggesting a lack of focus on optimizing compilers and languages for performance. The video concludes by urging developers to consider the implications of using energy-intensive languages like Python and advocating for a return to more efficient options like C, Rust, and Java for applications where speed and energy consumption are critical factors.