Rank: 205 based on 464 downloads (last 30 days) and 5 files submitted
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Markus Buehren

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Professional Interests:
signal processing

 

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Files Posted by Markus View all
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(last 30 days)
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09 Sep 2014 Differential Evolution Optimization using the evolutionary algorithm of Differential Evolution. Author: Markus Buehren optimization, evolutionary algorith..., differential evolutio... 204 29
  • 4.95833
5.0 | 25 ratings
21 Jul 2014 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren distributed processin..., parallel computing, parallel processing, distributed computing, multiple core, multicore processing 143 66
  • 4.74138
4.7 | 68 ratings
17 Mar 2014 Functions for the rectangular assignment problem This package provides m- and mex-functions for solving the rectangular assignment problem. Author: Markus Buehren optimization, munkres algorithm, hungarian algorithm, assignment problem, data association 86 23
  • 4.78261
4.8 | 25 ratings
11 Apr 2011 Screenshot Precise Figure Placing This contribution provides functions for precisely placing a figure to a given screen location. Author: Markus Buehren annotation, customization, figure, window, placing, border 25 2
  • 4.5
4.5 | 2 ratings
06 Nov 2009 Faster grade function for Color Bridge Matlab Contest Here I provide a speedup for the grade function of the Color Bridge Matlab Contest. Author: Markus Buehren flooding, color bridge, matlab contest 6 0
Comments and Ratings by Markus View all
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27 Sep 2014 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren

Hi Theo,

the different Matlab processes communicate via the file system in the multicore package. All function input and output arguments are saved to/read from the file system. In your example, the multicore master process will save 100 files of about 8 MB (1 million doubles) to the disk which are read by the slaves. The overhead is in this case clearly larger than the benefit of the parallel processing.

For further dicussion, please use the Yahoo group: http://groups.yahoo.com/group/multicore_for_matlab

Yours
Markus

14 Mar 2014 Munkres Assignment Algorithm An efficient implementation of the Munkres algorithm for the assignment problem. Author: Yi Cao

There is another version of this package here: http://www.mathworks.com/matlabcentral/fileexchange/20652-hungarian-algorithm-for-linear-assignment-problems-v2-3

22 Jun 2009 Structure display simple recursive display of a structure content in Matlab Author: Thomas Deneux

08 Apr 2009 UDFactor Performs the U-D factorization of a symmetric matrix. Author: Dmitry Savransky

10 Feb 2009 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren

I have opened a discussion group for the Multicore package on Yahoo. Please join and discuss with other users!

http://groups.yahoo.com/group/multicore_for_matlab/

Comments and Ratings on Markus' Files View all
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13 Oct 2014 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren Hiroyuki

09 Oct 2014 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren Harrison, Charles

Scratch my first suggestion on my last post. I just read David's post below and was not aware of the -nodisplay flag.

03 Oct 2014 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren Rami

Excellent function. It was really helpful for me in the case of multi-objective optimization

27 Sep 2014 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren Buehren, Markus

Hi Theo,

the different Matlab processes communicate via the file system in the multicore package. All function input and output arguments are saved to/read from the file system. In your example, the multicore master process will save 100 files of about 8 MB (1 million doubles) to the disk which are read by the slaves. The overhead is in this case clearly larger than the benefit of the parallel processing.

For further dicussion, please use the Yahoo group: http://groups.yahoo.com/group/multicore_for_matlab

Yours
Markus

25 Sep 2014 Multicore - Parallel processing on multiple cores This package provides parallel processing on multiple cores/machines. Author: Markus Buehren Theo

When I try to run the following piece of code:

clear all;
for ii=1:100
heavy_cell{ii}=rand(1000,1000);
end
myfun=@inv;
resultCell = cell(size(heavy_cell));
tic
for k=1:numel(heavy_cell)
resultCell{k} = myfun(heavy_cell{k});
end
toc
clear resultCell;
tic
resultCell = startmulticoremaster(@inv, heavy_cell);
toc

I end up with :

Elapsed time is 26.412324 seconds.
Elapsed time is 111.729816 seconds.

The later being the result of the parallel processing. I take I must be missing something here. Could someone elaborate please?

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