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Message #20948
Re: [Bug 706909] [NEW] [python] matrix multiplication fails in parallel
On Monday January 24 2011 09:43:45 Johan Hake wrote:
> On Monday January 24 2011 09:33:12 Garth N. Wells wrote:
> > On 24/01/11 17:17, Johan Hake wrote:
> > > Isn't there a way to initialize a paralell vector with arbitrary
> > > distribution pattern?
> > >
> > > There is a way to general a local range from a given entity size using
> > > MPI.local_range. One should be able to generate a distributed Vector
> > > with this information.
> >
> > This isn't guaranteed to work since using MPI.local_range may produce a
> > vector with a layout that is inconsistent with the matrix layout.
>
> Ok.
>
> > A Vector could be created using the local range data from the Matrix.
>
> Is this possible to do using the GenericMatrix inteface?
GenericVector that should be.
Johan
> Johan
>
> > Garth
> >
> > > Johan
> > >
> > > On Monday January 24 2011 05:17:21 Joachim Haga wrote:
> > >> Public bug reported:
> > >>
> > >> The python code for __mul__() assumes an empty vector suitable for
> > >>
> > >> mult() can be created from just the dimensions of the matrix:
> > >> if type(other) == Vector:
> > >> ret = Vector(self.size(0))
> > >>
> > >> This is not true in parallel. And it won't help to copy the input
> > >> vector, as that only works for square matrices.
> > >>
> > >> How to create a vector which is compatible with a given matrix at this
> > >> point (only the matrix available, not the sparsity pattern)? Would it
> > >> perhaps be acceptable to add methods create_rhs_vector(),
> > >> create_lhs_vector() to GenericMatrix?
> > >>
> > >> ** Affects: dolfin
> > >>
> > >> Importance: Undecided
> > >>
> > >> Status: New
> > >
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