Haven’t decided which language you want to program in yet? Find out which one is the fastest.
The world is changing rapidly, and technology is at the very center of it. Technology is affecting our present. Technology drives and shapes our future. What better way to be part of that driving force than to learn the beating heart of all these computers and application? Coding.
In 2017, Portuguese researchers conducted a series of experiments to find out which language is the fastest, most energy efficient, and also the least memory intensive.
The experiments were carried out with 27 languages, in which several of the same tasks were performed. For example, first they tried to carry out calculations in all languages, then – to draw something, and so on. Later, the data was entered into a table, on the basis of which we compiled the top.
Fastest programming languages
Assembler could come first, but it was not considered in research. Therefore, the top looks like this (after the dash, the time in seconds is indicated):
- C – 1.00.
- Rust – 1.04.
- C ++ – 1.56.
- Ada – 1.85.
- Java – 1.89.
- Chapel – 2.14.
- Go – 2.83.
- Pascal – 3.02.
- Ocaml – 3.09.
- C # – 3.14.
Some popular languages, like Python, did not make it into the top ten at all, showing a result of 71.90 seconds.
However, you shouldn’t rush to learn C by giving up programming in C #, because these languages are used for different purposes. The former is popular for software and driver development, while the latter is actively used to create games on Unity.
All these languages are used for different purposes, so it is not entirely correct to compare them. In addition, slower languages may have advantages. For example, where C # will need 2.85 MB of memory, Java will need 6.01 MB, and Python, despite its slowness, will require only 2.8 MB.
Also, do not forget that some languages, like Pascal, are used for educational purposes only, so it is not suitable for serious projects.
We advise you to go from the opposite and learn one of the worst programming languages - Python. Although it is not as fast as other languages, it can be accelerated using special libraries. It is also widely used in many fields and is included in the list of languages suitable for working with machine learning.
A new edition of a textbook that provides students with a deep, working understanding of the essential concepts of programming languages, completely revised, with significant new material.
This book provides students with a deep, working understanding of the essential concepts of programming languages. Most of these essentials relate to the semantics, or meaning, of program elements, and the text uses interpreters (short programs that directly analyze an abstract representation of the program text) to express the semantics of many essential language elements in a way that is both clear and executable. The approach is both analytical and hands-on. The book provides views of programming languages using widely varying levels of abstraction, maintaining a clear connection between the high-level and low-level views. Exercises are a vital part of the text and are scattered throughout; the text explains the key concepts, and the exercises explore alternative designs and other issues. The complete Scheme code for all the interpreters and analyzers in the book can be found online through The MIT Press web site. For this new edition, each chapter has been revised and many new exercises have been added. Significant additions have been made to the text, including completely new chapters on modules and continuation-passing style. Essentials of Programming Languages can be used for both graduate and undergraduate courses, and for continuing education courses for programmers.