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Software for Numerical Linear Algebra
Last Updated: 2026-02-05 15:29:34
Abstract
The aim of this course is to show how numerical algorithms are implemented correctly and efficiently.We follow this agenda by discussing various important algorithms of numerical linear algebra.
Objective
The aim of this course is to show how numerical algorithms are implemented correctly and efficiently. We follow this agenda by discussing various important algorithms of numerical linear algebra.
Content
Examples, mainly from numerical linear algebra are used to show how algorithms are implemented correctly and efficiently in floating-point arithmetic. In the first part, the exact computation of eigenvalues and eigenvectors, as well as singular values and singular vectors of dense matrices is discussed. In the second part, sparse matrices are treated first. Then we present an introduction to iterative methods for large sparse matrix eigenvalue problems and systems of linear equations. In particular the eigensolver package ARPACK amd the implementation of the well-known methods CG, MinRes, and GMRes is discussed. Finally, in the third part, parallel algorithms are treated. The course is given in German unless there are requests to use English.
Resources
Lecture Notes
Scripts or notes on the various parts will be provided.
Literature
See homepage.
General Information
- Language
- German
- Levels
- BSC , DS , MSC
- Frequency
- Yearly recurring
Examination
- Type
- end-of-semester examination
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture | Software for Numerical Linear Algebra |
|
2 h weekly |
| exercise | Software for Numerical Linear Algebra |
|
2 h weekly |