From help-request at octave dot org Sat Feb  5 00:50:07 2005
Subject: Re: octave-speed
From: "Paul Thomas" <paulthomas2 at wanadoo dot fr>
To: =?iso-8859-1?Q?Rafael_Rodr=EDguez_Velilla?= <rrv66 at tid dot es>,         <help@octave.org>
Date: Sat, 5 Feb 2005 07:54:53 +0100

As Paul Kienzle has said, there is a performance hit of ~10 for loop 
operations in octave, relative to Matlab 5.  This is, in particular due to 
index operations.  Most of this time is absorbed by the function subsref and 
the difference in timing between octave and Matlab is reflected in their 
manifestations of this function.  There was lengthy correspondence on the 
lists about this during the first half of last year.

For a variety of reasons, I am coming to think that the difference in 
performance is due to the exploitation of C++'s virtual functions in the 
octave classes.  I have a TODO on demonstrating that this is the case.

In the mean time, to get back to Rafael's original question:

(i) Performance improvement in octave and Matlab is very often effected by 
vectorization.  See the following, which is a must for users of either 
product:
http://www.mathworks.com/access/helpdesk/help/techdoc/ref/filter.html

(ii) Your sample programme can be rewritten as:

tic;
Ns=1e5;
m=[1:Ns-1];
T=sqrt(m.*(m+1));
n=zeros(1,Ns);
n(1)=8;
for i=m
  n(i+1)=sqrt(T(i)*n(i));
end
printf("time=%g\n",toc);
printf("n=%g\n",n(1,Ns));

which exposes the core iteration - n(i+1) = function ( weight(i) * n(i) ). 
If this were linear, you could use the trick with filter, given in (i).  As 
it is, as Paul Kienzle advised you, you will have to write a C++ function to 
do the job.

Try: http://perso.wanadoo.fr/prthomas/intro.html for a relatively painless 
how-to-do.

Regards

Paul T 




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