RE: matlab/octave performance hit

[Bhaskar Mehta]

My most recent experience with slow loops etc in Octave is that writing oct
files ( c++ code ) and then compiling then as functions inside octave with
mkoctfile speedups octave performance significantly ( I saw a speed up of
1000 times). This is esp true if you need to do anything requiring an
iteration over the entire matrix.

If you can analyze which code is slow, writing oct files is the easiest way
(INHO). Matlab uses Java JIT can thus is much better now with loop
optimization. 

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Bhaskar Mehta,
Researcher, L3S Forschungszentrum
Appelstrasse 4 Hannover, Germany
Phone: +49 511 762 17761
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________________________________________
From: Victor Zhorin [mailto:address@hidden 
Sent: Thursday, October 18, 2007 10:34 PM
To: address@hidden
Subject: matlab/octave performance hit

Hello,

We tried to see whether we could make existing matlab code to run using
octave on parallel cluster.
Unfortunately we found that performance hit is too strong.

It seems that slowness is most likely due to some instrinsic system/octave 
issues.

Here is a quick example:

tic; test = 1:200; nc = cumsum(test);toc

octave (linux based box, latest release compiled)
Elapsed time is 0.023521 seconds.
matlab (mac, powerpc)
Elapsed time is 0.000064 seconds.
octave (same mac, latest binary package for Mac X installed as-is)
Elapsed time is 0.050179 seconds.

That's a very significant difference in performing the most basic
operations.
Is there a way we can speed it up or could we possibly miss something in
installation?

Thank you.

Victor V. Zhorin
University of Chicago
Computational Institute