Difference between revisions of "Algorithms of Scientific Computing II - Winter 11"

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* Oct 26: [http://www5.in.tum.de/lehre/vorlesungen/algowiss2/WS11/intro.pdf Intro]
* Oct 26: [http://www5.in.tum.de/lehre/vorlesungen/algowiss2/WS11/intro.pdf Intro]
* Oct 26, Nov 9: [http://www5.in.tum.de/lehre/vorlesungen/algowiss2/WS11/fundamentals.pdf Fundamentals - Parallel Architectures, Models, and Languages]
* Oct 26, Nov 9: [http://www5.in.tum.de/lehre/vorlesungen/algowiss2/WS11/fundamentals.pdf Fundamentals - Parallel Architectures, Models, and Languages]
* Nov 16: Dwarf no. 1 - Dense Linear Algebra
* Nov 16: Dwarf no. 1 - [http://www5.in.tum.de/lehre/vorlesungen/algowiss2/WS11/denseLA.pdf Dense Linear Algebra];<br>additional material: [http://epubs.siam.org/sirev/resource/1/siread/v46/i1/p3_s1 article by Elmroth et al.] in [http://epubs.siam.org/sirev/ SIAM Review]

Revision as of 18:23, 18 November 2011

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


  • The next tutorial will be on 21.11.2010 (15:30).
  • 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 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 cuda_mmult.cu, README-1.txt


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).