Matlab course 2, "advanced"

Nov 2016
Heikki.Apiola'at', Juha.Kuortti'at'
"Advanced" means: Some experience, like Matlab 1 is expected.

Matlab 1 frontpage

Matlab/Octave guides:
- Introduction to Octave, Univ. of Cambridge
- YAGTOM, Yet Another Guide to Matlab

In Finnish
- Matlab miniopas
- Lyhyt Matlab opas
- "YAGTOM" muokattu ja osin suometettu

- MATLAB Tutorials
- Matlab Central: Blogs
- find-exercise, find, min/max
- Data Fitting with MATLAB
- Global minimization

Open courseware
- MIT material
- Berkeley

- D.J. Higham- N.J. Higham: Matlab Guide, Siam 2005
- m-files for the book
- W.J. Palm: Intro to MATLAB for Engineers, Mc Graw Hill, 2011

- Moler:Experiments with MATLAB
- Numerical Computing with MATLAB

Indexing tricks
Indexing, repmat

Dates, times
  Mo 21.11 12-15
  Wed 23.11 12-15   Problems
  Wed 30.11 12-15
NOTE: There is no session on Monday 28.11, the total number of sessions will be reduced to 3.

Topics touched:
  • Efficient use of Matlab.
    • Vectorization, preallocation, logical indexing, cell arrays, timing, profiling, sparce matrices, file handling, etc. (some more, some less)
    • Parallel computing with Matlab's toolbox. Participants will get access to
      Parallel toolbox can be practiced on laptops, Triton-cluster has a larger number of "workers", ie. Matlab servers running in parallel.
        Examples vary from very basic for understanding toolbox usage possiblities to "interesting".
  • Some, hopefully interesting examples enlightening the techniques taught and
    motivating their learning.
  • Time permitting, some other Matlab tools, like symbolic toolbox, optimization etc.

Course news [16.11.], extended: 12.4.2017

  • Condor-question m-file
  • For repeating and widening your knowledge, have a look at the YAGTOM-guide up left. Includes among other things also useful efficiency aspects as preparation for the first lectures.

Parallel computing references

#1. Efficient uses of Matlab, getting started with Parallel Toolbox [21-23.11.16]

Juha's materials
Problems [23.11.]

Slides/Live documents/Links:
Run Code on Parallel Pools | Compare... | spmd | spmd example:numerical integration | spmd_numint mfile | spmd examples | VanTemplate.m (tiny little exercise)

Some references to motivate further studies

#3. Examples on passing parameters, "paramsweep", Batch, tasks, nsection/Newton run in parallel, GPU-computing [30.11.16]

GPU-computing demos (directory) [Juha] | GPU-computing demos (.zip) [7.12.16]