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Subject: Re: [ublas] uBLAS parallelization
From: Riccardo Rossi (rrossi_at_[hidden])
Date: 2009-04-02 03:50:40


Hi,

we spent some effort in the parallelization of matrix vector product and
other of such things.

in doing so we partially took advantage of the "omptl" library which is
a library freely available

i attach here the wrapper we use for "parallel ublas". It appears to
work fine over itanium (however we only did 1 test as we do not have it
"at home") but does not scale at all due to hardware limitation over
multicore cpus (neither intel nor AMDs)

i hope it can be helpful

greetings
Riccardo

-
________________________________________________________________
Riccardo Rossi, Ph.D, Civil Engineer
member of the Kratos Group: kratos.cimne.upc.es
Centro Internacional de Métodos Numéricos en Ingeniería (CIMNE)
Universidad Politécnica de Cataluña (UPC)
Edificio C-1, campus Norte UPC
Gran Capitan, s/n
08034 Barcelona, España
Tel. (+34) 93 401 73 99
________________________________________________________________

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On Thu, 2009-04-02 at 08:29 +0200, Jörn Ungermann wrote:
> Hi all,
>
> I am currently looking into uBLAS to replace gsl/ATLAS as our linear
> algebra solution, as it supports sparse matrices, which our increasing
> problems (going towards 100000x100000) start to require.
> We use 8 core 64GB machines for our calculations and would like to use
> 'em as efficiently as possible, i.e. ideally use all cores all the time,
> even if a single problem requires all 64GB of memory. For dense
> matrices, ATLAS does this automatically with its threaded implementation
> (ptcblas).
> With the nice ATLAS bindings, this seems to work like a charm with
> uBLAS' dense matrices.
> But I have not seen anything (helpful) about speeding sparse matrix
> operations up with a threaded implementation (shared memory
> parallelization).
> I assume that it is possible to do so at least for some sparse matrix
> implementations, as certain specialized packages offer it (e.g. PetSC).
> So:
> 1) Is there some ready-to-use solution for parallelizing uBLAS sparse
> matrix operations?
> 2) If not, is there some ongoing development effort, I could tap
> into/get involved?
> 3) If not, could someone comment on how difficult it would be to
> implement such a thing for selected operations/matrix types from both a
> mathematical and a uBLAS-implementaion-constraints point of view (we
> already use OpenMP to parallelize the non-linear-algebra part of our
> program)?
>
> Thanks and kind regards,
> Jörn
>
> PS: uBLAS and the numerical bindings are really marvelous. The migration
> of our software package from GSL worked like a charm given all the
> helpful hints in the wiki and the test cases as working examples.
>
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