Difference between revisions of "Algorithms of Scientific Computing II - Winter 11"
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Revision as of 13:34, 26 January 2012
- 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 slides will be published here after the lessons:
- Oct 26: Intro
- Oct 26, Nov 9: Fundamentals - Parallel Architectures, Models, and Languages
- Nov 16, Nov 23: Dwarf no. 1 - Dense Linear Algebra;
- Nov 30: Dwarf no. 5 - Structured Grids
- Dec 7, Dec 14: Structured Grids and Space-filling Curves
- Maple worksheets: hilbert_adap.mws (also as PDF);
- additional material: article by Frigo/Strumpen: The memory behavior of cache oblivious stencil computations
- Dec 14, Dec 21: Dwarf no. 6 - Unstructured Grids and Partitioning
- Jan 11: Dwarf no. 2 - Sparse Linear Algebra: Application example (page rank) and data structures
- Jan 18, Jan 25: Parallel Sparse Matrix-Vector Multiplication
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.
|07.11.2011||Slides - Introduction to Cuda||cuda_mmult.cu, 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).