May 1, 2024
Updated June 18, 2025
16 minute read
Fortran: A Foundational Pillar of Scientific Computing
Fortran, a name derived from "Formula Translation," stands as one of the pioneering high-level programming languages. Its creation in the 1950s marked a significant leap in computing, enabling scientists and engineers to express complex mathematical formulas and procedures in a more human-readable format than the assembly languages or machine code that preceded it. This innovation dramatically accelerated the pace of scientific discovery and engineering advancements by making computers more accessible for complex numerical computations.
Working with Fortran can be an engaging experience, particularly for those passionate about high-performance computing and solving complex scientific puzzles. The language's design is optimized for numerical accuracy and speed, making it a thrill to see massive datasets processed efficiently. Furthermore, Fortran's long history means that developers often work with, and contribute to, codebases that have powered significant research for decades, offering a unique connection to the legacy and future of scientific endeavor. The strong sense of community and the specialized nature of its applications also provide a distinct and rewarding career path for those who master its intricacies.
The Enduring Legacy: Introduction and History of Fortran
Fortran's story is deeply intertwined with the evolution of computing itself. Its continued relevance in specific, demanding fields is a testament to its robust design and the critical problems it helps solve. Understanding its origins and development provides valuable context for anyone considering delving into this powerful language.
Origins and Early Development
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Find a path to becoming a Fortran. Learn more at:
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Reading list
We've selected 12 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Fortran.
This three-volume set provides a comprehensive guide to numerical recipes in Fortran 77. It covers a wide range of topics, from basic numerical methods to advanced topics such as partial differential equations.
Provides a comprehensive introduction to deep learning. It covers a wide range of topics, from basic concepts to advanced techniques such as convolutional neural networks and recurrent neural networks.
Gentle introduction to Fortran 95, with a focus on scientific and engineering applications. It includes coverage of HPF and OpenMP, two parallel programming models that are commonly used in Fortran.
Provides a comprehensive introduction to high-performance parallel programming using MPI, OpenMP, and CUDA. It covers a wide range of topics, from basic concepts to advanced techniques such as collective communication and load balancing.
Provides a comprehensive introduction to machine learning. It covers a wide range of topics, from basic concepts to advanced techniques such as deep learning and reinforcement learning.
Provides a comprehensive introduction to parallel programming using Fortran. It covers a wide range of topics, from basic concepts to advanced techniques such as message passing and shared memory programming.
An essential reference for programmers making the transition to a new version of Fortran, this book includes syntax changes, compiler enhancements, and advanced programming techniques. does not teach Fortran, and thus fits into the 'Advanced' category of difficulty.
Provides a comprehensive introduction to scientific computing using Python. It covers a wide range of topics, from basic concepts to advanced techniques such as numerical methods and data visualization.
Provides a comprehensive introduction to data science from scratch. It covers a wide range of topics, from basic concepts to advanced techniques such as machine learning and deep learning.
Provides a comprehensive introduction to computational science using Python. It covers a wide range of topics, from basic concepts to advanced techniques such as numerical methods and data visualization.
Provides a comprehensive introduction to Python for data analysis. It covers a wide range of topics, from basic concepts to advanced techniques such as data cleaning and machine learning.
Comprehensive introduction to Fortran 90. It provides a step-by-step guide to the language's features, with a focus on scientific and engineering applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/z0yzzf/fortra