The face of scientific computing has changed. Computational scientists are no longer writing their programs in Fortran and competing for time on supercomputers. Scientists are now streamlining their research by choosing more expressive programming languages, parallel processing on desktop machines and exploiting the wealth of scientific information distributed across the internet.
The landscape of programming languages saw a punctuation in its evolution at the end of the 20th century, marked by the advent of a new breed of languages. These new languages incorporate a multitude of features that are all designed to serve a single purpose: to make life easier. Modern programming languages offer so much more expressive power than traditional languages that they even open up new avenues of scientific research that were simply intractable before.
The next few years will usher in a new era of computing, where parallelism becomes ubiquitous. Few approaches to programming will survive this transition, and functional programming is one of them.
Seamlessly interoperating with computers across the world is of pivotal importance not only because of the breadth of information now available on-line but also because this is the only practicable way to interrogate the enormous amount of data available. The amount of genomic and proteinomic data published every year continues to grow exponentially, as each generation of technology fuels the next.
Only one mainstream programming language combines awesome expressive power, interoperability and performance: F#. This book introduces all of the aspects of the F# programming language needed by a working scientist, emphasizing aspects not covered by existing literature. Consequently, this book is the ideal complement to a detailed overview of the language itself, such as the F# manual or the book Expert F#[25].
Chapters 1–5 cover the most important aspects of F# programming needed to start developing useful F# programs. Chapter 6 ossifies this knowledge with a variety of enlightening and yet simple examples. Chapters 7–11 cover advanced topics including real-time visualization, interoperability and parallel computing. Chapter 12 concludes the book with a suite of complete working programs relevant to scientific computing.
The source code from this book is available from the following website:
http://www.ffconsultancy.com/products/fsharp_for_scientists/
J. D. Harrop
Cambridge, UK
June, 2008