On Mon, Feb 8, 2010 at 2:51 AM, Muthiah Annamalai <[email protected]> wrote:
> Hello Luca Favatella, and friends,
>
> Octave can be used in ways Matlab cannot be, for example
> in problems which have data-parallelism ( same problem solved
> for different initial conditions/ data ) Octave gives a large speedup
> factors.
>
> A master Octave can spawn several Octave processess whose parameters
> are written in a disk and then wait for all of them to end, and pickup
> the resulting data
> from known saved files. So this would easily allow throwing
> multicore resources at a problem which allows data parallelism, which 
> otherwise
> would run as just a single Octave serial process.
>
> In a GA toolbox we evaluate same function/program for different
> data and this can make use of the data parallelism.
>
> Under the assumptions of having a  Fitness functions (f(x))  to be
> specified as a string, and
> [ncores] has to be the number of cores to be used in the GA fitness 
> evaluation,
> specified as an attribute to GA problem structure, we can do this by creating
> replacing __ga_scores__.m script with the following pair of scripts,
>
> __ga_multicore_scores__.m
> __ga_multicore_helper__.m
>
> You can test these scripts by, running test_multicore.m .
>
> (please see attachments. )
>
> We need fitness functions as a string,  since child processess donot share
> memory with the parent/master process.
>

If you're working in UNIX-based environment (Linux, FreeBSD etc), an
alternative is to install the general package and do
results = parcellfun (number_of_cores, @my_function, pop, arg1,...).

-- 
RNDr. Jaroslav Hajek, PhD
computing expert & GNU Octave developer
Aeronautical Research and Test Institute (VZLU)
Prague, Czech Republic
url: www.highegg.matfyz.cz

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