Personal tools

Algorithms of Scientific Computing II - Winter 11

From Sccswiki

Jump to: navigation, search
Winter 11/12
Prof. Dr. Michael Bader
Time and Place
Lecture: Wednesday, 10:30 - 12:00 Uhr, room MI 02.07.023, started Oct 26
Tutorial: Monday, 16:00 -18:00, every second week, room MI 02.07.023, started Nov 7
Elective topic in Informatik Bachelor/Master/Diplom subject area Algorithms and Scientific Computing
Wirtschaftsinformatik Bachelor (Modul IN2002)
Mathematik, Natur- und Ingenieurwissenschaften students are also welcome!
Daniel Butnaru, M.Sc, Christoph Kowitz, M.Sc.
details t.b.a.
Semesterwochenstunden / ECTS Credits
3 SWS (2V + 1Ü) / 4 Credits



  • In winter term 2011/12, this lecture will be held by Michael Bader with a focus on algorithms in high performance computing (and scientific computing).
  • The lecture on Wednesday, Nov 2, was skipped due to the student's general assembly


The lecture will have a focus on parallel algorithms and implementation techniques in the field of numerical simulation and high performance computing, such as:

  • linear algebra problems on dense and sparse matrices
  • simulation on structured and unstructured meshes
  • particle-based simulations (with long-range and short-range interactions)
  • spectral methods (parallel FFT and related algorithms)
  • Monte Carlo and statistical methods

(a.k.a. the seven dwarfs of HPC).

Lecture Material

Lecture slides will be published here after the lessons:


Roughly every second week a two hour tutorial will take place (details at page top; days and time will be announced here and in the lectures). The assignments and their solutions will be gradually posted here.

Date Slides Files
07.11.2011 Slides - Introduction to Cuda, README-1.txt
21.11.2011 Slides - Further Details on Dense Linear Algebra
05.12.2011 Slides - Shallow Water Equation; Worksheet Code framework
23.01.2012 Slides - SpMV Kernels & Worksheet Code framework


  • R. H. Bisseling: Parallel Scientific Computing - A structured approach using BSP and MPI, Oxford University Press, 2004.


Lecture IN0019 Numerical Programming or similar basic knowledge in numerical methods. Basic knowledge in parallel programming (lecture Parallel Programming, Parallele Algorithmen und Höchstleistungsrechnen, or similar) is helpful (as is a certain interest in problems from scientific computing and numerical simulation).