Re: Octave interpreter slowness

[John Swensen]

Keith Goodman wrote:
> On 3/15/06, John Swensen <address@hidden> wrote:
>   
>> In some recent work, I wasn't able to get our companies' only Matlab
>> Statistics toolbox license, so I switched to octave for a week or two.
>> I noticed that the poisson random function in octave took orders of
>> magnitude longer than Matlab's implementation.  This led me to do a
>> simple experiment.  I ran the following script on the same computer with
>> both Matlab and Octave (WinXP with Cygwin Octave release vs. Matlab
>> 7.something), with very interesting results.
>> -------------------------------
>> tic
>> size = 1000000;
>> var = zeros(1,size);
>> for i = 1:size
>>   var(i) = rand();
>> end
>> sum(var)
>> ElapsedTime = toc
>> -------------------------------
>>
>> Matlab (10 runs) - Ave = 2.0818 seconds
>> Octave (10 runs) - Ave = 19.911 seconds
>>
>> Since this is a fairly simple script with a lot of iterations, does this
>> indicate that the discrepency is caused somewhere in the parsing
>> portions of Octave?  I tried the test again with the rand() call
>> eliminated with similar differences in execution times.  I then tried
>> the script in Octave on a faster PC running Ubuntu with some
>> improvements (15 seconds per).
>>     
>
> For loops are slow in Octave.
>
> When most of the time of a single for loop iteration is spent in
> matrix operations, the slowness of the for looping is not noticeable.
> But when most of the time is spent in looping, it is very noticeable.
>
> For example
>
> a = randn(N);
> tic
> for i = 1:1000
>    x = a*a';
> end
> toc
>
> As you increase N, the ratio of the slowness decreases.
>
> If N is small, the trick is either to vectorize or compile your
> function with mkoctfile.
>
>
>   
I guess my question pertains as to the source of the slowness.  Is it
the parser, or is Matlab doing some sort of look-ahead optimization of m
files?  Do they compile to byte-code or something similar prior to
execution?

-John Swensen



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