Programming Languages for Scientific Computing

TL;DR

This paper reviews various programming languages used in scientific computing, analyzing their features, strengths, and weaknesses through examples from widely used scientific codes, to guide better language choice for complex simulations.

Contribution

It provides a comprehensive comparison of programming languages for scientific computing, highlighting their suitability for different computational science applications.

Findings

Different languages excel in specific scientific computing tasks.

Trade-offs exist between ease of use, performance, and flexibility.

Examples illustrate practical strengths and weaknesses of each language.

Abstract

Scientific computation is a discipline that combines numerical analysis, physical understanding, algorithm development, and structured programming. Several yottacycles per year on the world's largest computers are spent simulating problems as diverse as weather prediction, the properties of material composites, the behavior of biomolecules in solution, and the quantum nature of chemical compounds. This article is intended to review specfic languages features and their use in computational science. We will review the strengths and weaknesses of different programming styles, with examples taken from widely used scientific codes.