ffc team mailing list archive

[Kristian Oelgaard <k.b.oelgaard@xxxxxxxxx>]

2010/1/22 Anders Logg <logg@xxxxxxxxx>:
> On Thu, Jan 21, 2010 at 11:26:47PM +0100, Anders Logg wrote:
> > The MetaData.ufl example is failing in the quadrature representation.
> >
> > Kristian, could you have a look and see what goes wrong. Then I can
> > continue to make the incremental/combined integral stuff work.
>
> On second thought, maybe we should skip the whole thing with having
> different representations inside the same tabulate_tensor function
> for the following reasons:
>
> 1. It leads to complications in the code generation.

Very true.

> 2. It probably doesn't make much difference since if quadrature is
> required for one part of an integral, then it is likely the cost is
> low for including the other terms inside the existing quadrature loop.

True.

> 3. The situation will not arise often since UFL will anyway group
> terms with the same dx inside the same integral and then all will have
> the same representation.

I'm not sure this is correct, if the metadata is different the integrals will not be grouped.

> So the cases where this is useful are rare (because of the UFL
> grouping), it won't give any speedup and it's complicated to
> implement...
>
> We will still have the possibility of different representations for
> integrals on different subdomains and for cell, interior and exterior
> facet integrals.

Yes, and this is probably the case where one will use it the most anyway.

> If this sounds ok, I can add some checks in analysis.py that force all
> UFL integrals that will be grouped as part of the same UFC integral to
> use the same representation.

Yes, such that if any quadrature is present they will all be quadrature.

> Btw, does quadrature handle different quadrature degree for different
> integrals that become part of the same tabulate_tensor? If not, we can
> force metadata to be the same for all integrals that belong together.

I don't know how the meta data is set up now, but it used to be able to do:

a = v*u*dx + inner(grad(v), grad(u))*dx -->

loop ip range(4):
 ....

loop ip range(9):
 ....

Inside one tabulate_tensor() funtion.

Kristian

> --
> Anders
>
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