[petsc-dev] Non-scalable matrix operations

[Matthew Knepley]

We need ISGlobalToLocalMappingApply(). This could be done with an STL map :)

   Matt

On Fri, Dec 23, 2011 at 1:01 AM, Jed Brown <jedbrown at mcs.anl.gov> wrote:

> Can we enumerate the matrix operations that are known to be non-scalable
> currently?
>
> 1. MatPermute() does ISAllGather() on the row indices and requires the
> user to ISAllGather() the column indices before calling (I consider this to
> be an interface bug similar to the MatGetSubMatrix() one we fixed before
> petsc-3.1). The problem is that we have to determine the new row and column
> or each locally visible row and column. This would be equivalent to having
> a scalable ISInvertPermutation(), which is not difficult to implement, and
> a way to retrieve data from off-process (new column indices for the "B"
> part). The latter can be done with a "VecScatter for integers", or
> trivially with PetscBG (name subject to change).
>
> 2. MatGetSubMatrix(), also called by MatPermute(). For this, it is
> sufficient to determine where each currently owned entry should go (or be
> skipped). We could do this by making a parallel int-vector for the entire
> column space, setting it all to -1, then pushing the "new" column index
> (location in the IS) over the IS. This gives a parallel vector that is -1
> for all column indices we don't want and the non-negative new column index
> for those that we do want. Now we retrieve from the parallel vector
> everything we need for the local column space.
>
> 3. MatIncreaseOverlap_MPISBAIJ(), I haven't looked carefully.
>
> I'm writing MatConvert_Nest_AIJ() which needs a similar feature. Mark
> wants parallel MIS and MOOSE wants parallel coloring, both of which involve
> moving integer data over the scatter context.
>
> What other implementations are currently non-scalable? Do we need other
> primitives, or would two-way integer operations over the MPIXAIJ scatter
> and via an IS be sufficient?
>



-- 
What most experimenters take for granted before they begin their
experiments is infinitely more interesting than any results to which their
experiments lead.
-- Norbert Wiener
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