C++ for Scientific Computing: 2019-2020


Timetable - Trinity 2020

Prior to Spring 2020 lockdown conditions in the UK this course was due to run for Week 1 of Trinity term 2020 as a special topic module on an MSc program.

Under new MSc regulations the course will not be lectured and is not available for credit on the MSc. However keen students are welcome to download lecture slides, exercises and any other resources that they find here. If you use things you find here for self-study and you struggle to understand any concepts in the lectures or exercises then you should drop me email with joe.pitt-francis@cs... (preferably in the first few weeks of Trinity Term).


Basic coding of numerical methods in Matlab, Python or another high-level language.
Basic linear algebra such as matrix-vector multiplication.
C++ level
No previous knowledge of C++ is expected. (The course is intended for programmers/mathematicians who are beginner or novice C++ programmers.)
C++ level
A more precise idea of the content of the course can be gauged from the syllabus below or from contents of the recommended text book. Note that there are differences: in particular, the material in Chapter 11 (MPI) is not covered in this course.


Producing almost any numerical software requires writing codes that manipulate matrices and vectors, making Matlab a natural choice as an introductory programming language for scientific computing. However, the ease of programming in Matlab comes at a cost: the codes take a relatively long time to execute; and the software is commercial. While the use of procedural languages such as Fortran and C will overcome these limitations, they do not allow the straightforward coding of operations between matrices and vectors permitted by Matlab. An alternative approach is to use an object-oriented language such as C++ , where vectors and matrices can be represented as classes. Writing subroutines for these classes that have the same syntax as employed by Matlab allows code developed in Matlab to be translated with minimal effort into C++ code. Such an approach combines the ease of development in the Matlab environment without the associated drawbacks.


C++ programming fundamentals.
  1. Variables and expressions
  2. Input and output
  3. Flow of control: if, switch, while, for
  4. Pointers and references
  5. Arrays
  6. Functions
Object orientation in C++
  1. Concept of a class
  2. Private, public and protected class members
  3. Constructors
  4. Operator overloading
  5. Function overloading - templates
  6. Defining functions that may take default values
  7. Exceptions

Lecture Slides

Practical Assignments

Previous assessments

Supplementary Materials