Fortran
Fortran
Fortran (FORMula TRANslator) is a high-level, general-purpose programming language widely used in scientific computing, especially for numerical simulations and data analysis. Its primary use cases revolve around mathematical, statistical, and scientific calculations.
What does Fortran mean?
Fortran (FORmula TRANslation) is a high-level Programming Language specifically designed for scientific and numerical computing. It was developed in the mid-1950s by a team led by John Backus at IBM. Fortran is characterized by its strong support for arrays, powerful mathematical functions, and efficient Memory Management. It is widely used in various scientific and engineering disciplines, such as physics, chemistry, engineering, and finance.
Fortran is known for its speed, accuracy, and ability to handle large datasets effectively. It offers a range of data types, including integer, real, complex, and double precision, to support precise and complex calculations. Fortran’s syntax is relatively straightforward, emphasizing readability and maintainability. Additionally, it provides a rich set of built-in functions for mathematical operations, linear algebra, and data manipulation.
Applications
Fortran is primarily used in scientific and technical computing where high performance and accuracy are critical. Key applications include:
- Scientific simulations: Fortran is widely used in scientific simulations, such as weather forecasting, fluid dynamics, and quantum mechanics. Its ability to handle large datasets and perform complex calculations makes it suitable for modeling complex physical systems.
- Numerical analysis: Fortran is extensively used in numerical analysis, which involves solving complex mathematical problems using numerical methods. It is particularly effective for solving systems of linear equations, finding eigenvalues, and performing data analysis.
- High-performance computing: Fortran is a popular choice for high-performance computing, where speed and efficiency are essential. It is used in applications that require massive parallel processing, such as climate modeling, molecular simulations, and financial modeling.
- Data science and machine learning: Fortran is increasingly used in data science and machine learning for tasks such as data preprocessing, feature engineering, and training machine learning algorithms. Its efficient memory management and ability to handle large datasets make it a suitable language for data-intensive applications.
History
The development of Fortran began in the mid-1950s at IBM. John Backus led a team of researchers to create a programming language specifically designed for scientific and engineering applications. The first version of Fortran, known as Fortran I, was released in 1957.
Over the years, Fortran has undergone several revisions and updates to enhance its capabilities and address evolving computing needs. Key milestones include:
- Fortran II: Released in 1958, it introduced support for arrays and a range of built-in mathematical functions.
- Fortran IV: Released in 1962, it became the widely adopted standard and introduced features such as DO loops, format statements, and subprograms.
- Fortran 77: Released in 1977, it established a common standard for Fortran across different platforms and compilers.
- Fortran 90: Released in 1990, it introduced significant enhancements, including support for dynamic memory allocation, user-defined data types, and Array sections.
- Fortran 2003: Released in 2004, it further extended Fortran’s capabilities with support for object-oriented programming, Interoperability with other languages, and advanced data structures.
- Fortran 2008: Released in 2010, it added new features for concurrency and parallel programming.
- Fortran 2018: The latest version, released in 2018, introduced support for coarrays, allowing for better handling of parallel data structures.
Throughout its history, Fortran has remained a widely used and respected programming language in the scientific and engineering community due to its reliability, performance, and precision.