Introduction to the Tools of Scientific Computing

 
 
Springer (Verlag)
  • erscheint ca. am 11. November 2020
 
  • Buch
  • |
  • Hardcover
  • |
  • XII, 344 Seiten
978-3-030-60807-1 (ISBN)
 

The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. Unlike widely used standard approaches, it does not focus on any particular language but aims to explain the key underlying concepts.

In general, new concepts are first introduced in the particularly user-friendly Python language and then transferred and expanded in various scientific programming environments from C / C ++, Julia and MATLAB to Maple. This includes different approaches to distributed computing.

The fact that different languages are studied and compared also makes the book useful for mathematicians and practitioners trying to decide which programming language to use for which purposes.


1st ed. 2020
  • Englisch
  • Cham
  • |
  • Schweiz
Springer International Publishing
  • Für Beruf und Forschung
XII, 344 p.
  • Höhe: 23.5 cm
  • |
  • Breite: 15.5 cm
978-3-030-60807-1 (9783030608071)
10.1007/978-3-030-60808-8
weitere Ausgaben werden ermittelt
Einar Smith holds academic degrees in Mathematics from the Unversity of Bonn, in Economics from the University of Oslo, and in Computer Science from the University of Hamburg. He has published a textbook on Mathematical Computability Theory, and a biography of the German computer scientist C.A. Petri. Both books have been published by Springer. In recent years he has mainly been concerned with the teaching of numerical methods at the University of Bonn, with an emphasis on computer programming.

Introduction.- Part I, Background.- Part II, Core Languages.- Part III, Commercial Computing Environments.- Part IV, Distributed Computing.- Part V, Specialized Programming Environments.- References.- Index.

The book provides an introduction to common programming tools and methods in numerical mathematics and scientific computing. In contrast to widespread standard approaches, it does not focus on a specific language, but rather aims to explain the central underlying concepts.

Generally, concepts are first introduced in the particularly user-friendly language Python, and then transferred to various scientific programming environments, from C/C++, Julia, and MATLAB to Maple and expanded in these. This includes different approaches to distributed computing.



The fact that it surveys and compares many different languages also makes the book helpful for mathematicians and practitioners who are trying to decide which programming language to use for which purposes.

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