FYSS5120 Efficient Numerical Programming (4 cr)
Learning outcomes
At the end of the course, students will be able to combine coding with python and C++ and write C++ code that uses libraries for solving problems. Students will be able to understand the layout and inner workings of a C++ code, keep C++ code and the underlying mathematics in close unison as well as hide uninteresting or already well-tested programming details from daily view.
Study methods
Programming assignments.
Content
Efficient C++ programming for practical numerical applications; calling C++ from Python; using program libraries e.g. GSL and Boost libraries; numerically efficient data structures; benefits and caveats of operator overloading; debugging code, finding memory leaks.
Further information
Given on autumn semester 1st period, every two years starting in autumn 2017.
Assessment criteria
Accepted solutions to programming assignments.
Prerequisites
Programming experience with Python, C++ or some other programming language.