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Re: [Bug 706909] [NEW] [python] matrix multiplication fails in parallel

 

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?

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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