Guide to Scientific Computing in C++ Guide to Scientific Computing in C++

Guide to Scientific Computing in C+‪+‬

    • $39.99
    • $39.99

Publisher Description

This simple-to-follow textbook/reference provides an invaluable guide to object-oriented C++ programming for scientific computing. Through a series of clear and concise discussions, the key features most useful to the novice programmer are explored, enabling the reader to quickly master the basics and build the confidence to investigate less well-used features when needed. The text presents a hands-on approach that emphasizes the benefits of learning by example, stressing the importance of a clear programming style to minimise the introduction of errors into the code, and offering an extensive selection of practice exercises.

This updated and enhanced new edition includes additional material on software testing, and on some new features introduced in modern C++ standards such as C++11.

Topics and features:

Presents a practical treatment of the C++ programming language for applications in scientific computingReviews the essentials of procedural programming in C++, covering variables, flow of control, input and output, pointers, functions and reference variablesIntroduces the concept of classes, showcasing the main features of object-orientation, and discusses such advanced C++ features as templates and exceptionsExamines the development of a collection of classes for linear algebra calculations, and presents an introduction to parallel computing using MPIDescribes how to construct an object-oriented library for solving second order differential equationsContains appendices reviewing linear algebra and useful programming constructs, together with solutions to selected exercisesProvides exercises and programming tips at the end of every chapter, and supporting code at an associated website
This accessible textbook is a “must-read” for programmers of all levels of expertise. Basic familiarity with concepts such as operations between vectors and matrices, and the Newton-Raphson method for finding the roots of non-linear equations, would be an advantage, but extensive knowledge of the underlying mathematics is not assumed.

Dr. Joe Pitt-Francis is a Departmental Lecturer at the Department of Computer Science and teaches Computer Science at Exeter College, the University of Oxford, UK. Prof. Jonathan Whiteley is Associate Professor at the Department of Computer Science and Governing Body Fellow of Linacre College, the University of Oxford, UK.

GENRE
Computers & Internet
RELEASED
2018
March 26
LANGUAGE
EN
English
LENGTH
301
Pages
PUBLISHER
Springer International Publishing
SELLER
Springer Nature B.V.
SIZE
5.4
MB
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