Difference between revisions of "HPC - Algorithms and Applications - Winter 13"

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| Nov 6th || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/cuda.pdf Introduction to CUDA] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/worksheet1.pdf Worksheet 1] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Exercise1.zip Exercise 1] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Solution1.zip Solution 1]
 
| Nov 6th || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/cuda.pdf Introduction to CUDA] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/worksheet1.pdf Worksheet 1] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Exercise1.zip Exercise 1] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Solution1.zip Solution 1]
 
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| Nov 13th || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/cuda_2.pdf Further details on Dense LA in CUDA] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/worksheet2.pdf Worksheet 2] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Exercise2.zip Exercise 2] ||
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| Nov 13th || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/cuda_2.pdf Further details on Dense LA in CUDA] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/worksheet2.pdf Worksheet 2] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Exercise2.zip Exercise 2] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Solution2.zip Solution 2]
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| Nov 27th || || || ||
 
 
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| Nov 27th || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/sparse_la_01.pdf Sparse LA in CUDA] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/worksheet3.pdf Worksheet 3] || [http://www5.in.tum.de/lehre/vorlesungen/hpc/WS13/uebung/Exercise3.zip Exercise 3] ||
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| Dec 11th || || || ||
 
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Revision as of 15:08, 27 November 2013

Term
Winter 13/14
Lecturer
Prof. Dr. Michael Bader
Time and Place
Lecture: Monday, 14.00-15.30, MI 02.07.023 (starts Oct 21);
Tutorial: Wednesday, 10-12, MI 02.07.023 (starts Oct 23, roughly bi-weekly)
Audience
Elective topic in Informatics Bachelor/Master: students in mathematics or in any science or engineering discipline are welcome!
Tutorials
Oliver Meister
Exam
written or oral exam at end of semester
Semesterwochenstunden / ECTS Credits
3 SWS (2V + 1Ü) / 4 ECTS
TUMonline
https://campus.tum.de/tumonline/lv.detail?clvnr=950111465 (lecture)
https://campus.tum.de/tumonline/wbStpModHB.detailPage?&pKnotenNr=705979 (module description)



Annonuncements

  • From Nov 18, the lecture on Monday will start at 14.00 (instead of 14.15)

Content

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).

The accompanying tutorials will include practical assignments, and will concentrate on the programming of GPU and accelerator platforms.

Lecture Material

Slides and exercise sheets/solutions will be made available during the lecture.

Lecture slides will be published here after the lessons: See also the lecture from winter term 2012/13.

Tutorials

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

Date Slides Worksheet Source Source (solution)
Oct 23rd Organizational remarks - - -
Nov 6th Introduction to CUDA Worksheet 1 Exercise 1 Solution 1
Nov 13th Further details on Dense LA in CUDA Worksheet 2 Exercise 2 Solution 2
Nov 27th Sparse LA in CUDA Worksheet 3 Exercise 3

Literature and Online Material

Prerequisites

Helpful, but not strictly required is knowledge in:

  • basics of numerical methods (e.g.: lecture IN0019 Numerical Programming or similar)
  • basics of parallel programming (lecture Parallel Programming, HPC - Programming Paradigms and Scalability, or similar)

Most important is a certain interest in problems from scientific computing and numerical simulation!