dolfin team mailing list archive

["Garth N. Wells" <gnw20@xxxxxxxxx>]

Johan Hake wrote:
> On Wednesday 19 August 2009 19:11:42 Garth N. Wells wrote:
> > Johan Hake wrote:
> > > On Wednesday 19 August 2009 18:50:13 Garth N. Wells wrote:
> > > > Johan Hake wrote:
> > > > > On Wednesday 19 August 2009 17:29:52 Garth N. Wells wrote:
> > > > > > What's going on behind the scene when I copy one vector to another in
> > > > > > PyDOLFIN using
> > > > > >
> > > > > >      u0.vector()[:] = u.vector()[:]
> > > > > When I add:
> > > > >
> > > > > u2 = Function(V)
> > > > > u2.vector()[:] = u.vector()[:]
> > > > >
> > > > > # Plot solution
> > > > > plot(u2)
> > > > >
> > > > > In a the Poisson demo it works fine.
> > > > In parallel?
> > > Yupp!
> > >
> > > > > This type of slice only uses the assignment operator.
> > > > The GenericVector assignment operator?
> > > Yes. This is done in __setslice__/__getslice__ in the extended python
> > > class.
> > I don't see then why the we end up inside
> >
> >    _compare_vector_with_vector
> >
> > for the Cahn-Hilliard demo when running in parallel?
>
> Are you sure it is in 
>
>   _compare_vector_with_vector
>
> this should only kick in if you used '==' or some other comparison operator. 

Yep, I put a print statement in there.

Garth


> When I run this demo in parallel, I get passed the assignment line but it 
> stops when calling the solve function with the following message:
>
> Traceback (most recent call last):
>   File "demo.py", line 86, in <module>
>     Traceback (most recent call last):
> solver.solve(problem, u.vector())
> RuntimeError: *** Error: MUMPS is required for parallel symbolic LU.
>  
>
> > > > I delved into the problem and the program ends up in the function
> > > > _compare_vector_with_vector from dolfin_la_get_set_items.i. It uses
> > > > GenericVector::get and GenericVector::set. These need to be used with
> > > > caution in parallel.
> > > Yes, when other type of slices are used we need to find a way to do that
> > > in parallel. I have just started digging in the parallel code, and need
> > > to look into all the changes to get familiar with it before I try to
> > > solve this.
> > This shouldn't be too hard.
> >
> >     set(const double* block, uint m, const uint* rows)
> >
> > works in parallel but
> >
> >     get(double* block, uint m, const uint* rows)
> >
> > doesn't yet (not too hard to fix though). The really evil functions are
> >
> >    set(const double*)
> >
> > and
> >
> >    get(double*)
>
> I think I am only using
>
>    set(const double* block, uint m, const uint* rows)
>    get(double* block, uint m, const uint* rows)
>
> However GenericVector.array is using the get(double*) function, and returns 
> some fishy numbers in the numpy.array.
>
> Johan
>
> > Garth
> >
> > > The best solution would be to have a full fledge VectotView in place ;)
> > >
> > > Johan
> > >
> > > > Garth
> > > >
> > > > Other slices might not
> > > >
> > > > > work. Have not checked.
> > > > >
> > > > > Johan
> > > > >
> > > > > > ? The issue is that it doesn't work in parallel.
> > > > > >
> > > > > > Garth
> > > > > > _______________________________________________
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