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Introduction to Fortran


Fortran, "Formula Translation" is still used today as one of the oldest programming languages. Created during the 1950s by IBM engineer John Backus, Fortran was aimed at performing numerical and scientific mathematics, which means that in the field it initiated high-performance computing today and deserves pride of place there.

Naming History

The name "Fortran" comes from the words formula translation. IBM engineers including John Backus develops the tools in order to make a more efficient and understandable programming language for scientific and engineering applications.


Numeric Computing
Fortran has solid capabilities in both numeric and scientific computing. It provides built-in support for complicated arithmetic, arrays and numerical algorithms.

Fortran is widely known for its efficiency and strength in performing math, which makes it ideal for routine settings like weather forecasting after being translated into equivalent hardware algorithms by a compiler or middleware knowledgeable in that area of application.

Legacy Compatibility
Fortran has a long history and extensive codebase. Consequently, it is suitable for modernization or the continuing maintenance of existing scientific computing programs that rely on this language.

Fortran is well-defined standards. The latest edition is the 2018 Fortran, which covers all types of computers and operating systems.

Modern versions of Fortran, such as 2008 and 2018, offer parallel programming facilities like coarrays and parallel loop constructs. These enable the programmer to take advantage of multiple core processors besides products with distributed memory designs.

Area of Applications

Scientific Computing
Fortran is employed in the numerical analysis, simulation and modeling efforts of science and engineering. Its efficiency as well as rich library support make it an invaluable tool for researchers and engineers alike.

High-performance computing
As a language suitable for batch-oriented computing, Fortran still remains as a common language used in the field of high performance computing (HPC) power supercomputers and cluster systems used for large-scale simulation or data analysis.

Weather Forecasting
In weather forecasting and climate modeling, as well as forecasting trends from The weather, the use of sophisticated numerical algorithms to predict a number of weather patterns and how they change over time has relied on FORTRAN to play such a vital role.

Aerospace and Defense
Many in the aerospace defense sector are familiar with Fortran programming. Typical uses include trajectory analysis and structural mechanics as well as simulations using computational fluid dynamics techniques to model objects' flight patterns or weapons impacts at impact points before they ever occur.

Quantum Chemistry
FORTRAN is favorite of computational chemists everywhere. It is widely used in this field to simulate basic molecular structures and predict what happens when two chemicals react together. For example, spectroscopy data can be handled by the program extremely well without input from other sources or modification.


Fortran is faster and more accurate
Each year's designers strive to keep those goals in sight even with computationally demanding applications where speed not only saves time but reduces the endless patience of end users.

Legacy compatibility
Fortran has a huge knowledge base from the 70's and 80's, making it well-situated for existing scientific computing apps to maintain operation when they need upgrading.

The definition of "For All" is standard, so regardless which compiler is used on what platform there will be no compatibility problems between them

Library support
Fortran has a rich tradition in libraries tailored to scientific computing tasks. The toolset for developers have an abundant supply of resources with which they can do numerical analysis, simulations, and modeling.

Modern Fortran versions offer all sorts of parallel programming features. Thanks to them, developers may exploit multi-core processors and distributed memory systems for better performance.


Learning Curve
Fortran's old-fashioned syntax, as well as its programming model, are both hard to learn for a new-comer with habits from newer programming languages.

Limited areas where it with a high success rate
Although Fortran is most successful in scientific computing and doing numerical analyses, there are not that many scenario outside of these instances from which it would be on even ground; making the language less fit to various other ordinary tasks.

Poor tooling
Compared to newer languages, Fortran programming often suffers from software and environment support. This can hit a developer's productivity and workflow.

Language complexity
While Fortran's syntax is relatively simple, its feature set and programming model may be complex for developers unfamiliar with scientific computing concepts and algorithms.