Re: Octave versus matlab performances on linux platform 64 bits

[Peter Cloetens]

Sergei Steshenko wrote:
> --- On Wed, 10/29/08, Jaroslav Hajek <address@hidden> wrote:
>
> > From: Jaroslav Hajek <address@hidden>
> > Subject: Re: Octave versus matlab performances on linux platform 64 bits
> > To: "Luca Tagliacozzo" <address@hidden>
> > Cc: address@hidden
> > Date: Wednesday, October 29, 2008, 11:47 PM
> > On Thu, Oct 30, 2008 at 7:01 AM, Luca Tagliacozzo
> > <address@hidden> wrote:
> > > Hello, I was wondering what  I am doing wrong:
> > >
> > > I was planning to pass some matlab programs to octave
> > but as I will have to
> > > do real simulation I was planning to write them in
> > C++.
> > > Before starting the project I decided to make a simple
> > test.
> > > I took the DaCoda example of the matpow.m file, did
> > the esteatical changes
> > > such that it can be run on matlab,
> > >
> > > and I run it on matlab via the following script:
> > test.m
> > > a=matpow(rand(1000),10);
> > >
> > >
> > > That is it mutliplies log_2(10) times  a 1000x1000
> > matrix
> > > By running
> > > time matlab -nodisplay <test.m
> > >
> > >
> > > I get     0m4.076s as a user time
> > >
> > > we see that it take 4.076s to execute on my already
> > fully loaded machine.
> > > Now always with the matpow.m file i did the following
> > test:
> > > time octave test.m: user    0m21.189s
> > > where we see that Octave took 21.189 seconds  (like 7
> > times matlab)
> > > Till here nothing strange since I was exectuing the
> > matpow.m file.
> > > Now I compile the matpow.cc and I crosscheck that
> > octave sees it:
> > > octave:1> help matpow
> > > Return b = a^n for square matrix a, and non-negative,
> > integral
> > > n./home/luca/Desktop/testing_perf/matpow.oct
> > > ......
> > >
> > > where we see that indeed it does see it in
> > > /home/luca/Desktop/testing_perf/matpow.oct
> > >
> > > So now I run again the test: and we see that the the
> > time is now 20.161s
> > > very slight variation with respect to the non compiled
> > case.
> > > I thought it could be a matter of overload taken by
> > octave to startup so I
> > > decided to increase the matrix size to 3000x3000 where
> > we would expect that
> > > this should run for around 10 minutes so that the
> > starting overhead should
> > > be negligible
> > >
> > >
> > >
> > >
> > > By running the .m file with matlab I get: 1m3.564s
> > >
> > > By running the .oct file with octave I get: a user
> > time 8m59.474s
> > > By running the .m file with octave I get: 8m58.702s
> > >
> > >
> > >
> > > So I do not get any increase of performance by
> > compiling the matlab
> > > matpow.cc .
> > >
> > >
> > > What am I missing?
> >
> > What Octave version do you use? How is it configured?
> > The speed of large matrix multiplication is basically all
> > about what
> > BLAS library you use. If Octave doesn't find a suitable
> > BLAS library,
> > it will compile a simplistic one for you, but depending on
> > what
> > Fortran compiler you use, the compiled thing's speed
> > may range from "a
> > little slow" to "really slow". Also, chances
> > are that your Matlab's
> > BLAS is exploiting multiple cores, if you have a multi-core
> > machine.
> >
> > --
> > RNDr. Jaroslav Hajek
> > computing expert
> > Aeronautical Research and Test Institute (VZLU)
> > Prague, Czech Republic
> > url: www.highegg.matfyz.cz
> > _______________________________________________
> > Help-octave mailing list
> > address@hidden
> > https://www-old.cae.wisc.edu/mailman/listinfo/help-octave
>
> I've tested that http://wiki.octave.org/wiki.pl?CodaTutorial matpow.cc
> example on my self-built (including self-built ATLAS) 'octave' - the
> machine runs 32 bit OS.
>
> Here is the benchmark:
>
> "
> octave:8> tic;a=matpow(rand(1000),10);toc;
> Elapsed time is 3.52261 seconds.
> "
>
> - not bad.
>
> The CPU is AMD X2 (AM2) 5000+.
>
> Regards,
>   Sergei.
>
>
>       
> _______________________________________________
> Help-octave mailing list
> address@hidden
> https://www-old.cae.wisc.edu/mailman/listinfo/help-octave
This seems indeed very dependent on the BLAS library:
On 3.0.1 with standard blas and lapack we get (with the m-code):
tic;a=matpow(rand(1000),10);toc
Elapsed time is 20.3305 seconds.

and for the large problem
tic;a=matpow(rand(3000),10);toc
Elapsed time is 547.43 seconds.

On 2.1.73 where we had mkl from intel (with the m-code and using 1 cpu):
tic;a=matpow(rand(1000),10);toc
ans = 3.7134

and for the large problem
tic;a=matpow(rand(3000),10);toc
ans = 89.689

This makes a factor of 6 for the same code.
Peter