In place ILU(0) factorization

[Hong Zhang]

Laslo,
> The point I was trying to make is that performing and ILU(0) does not
> change the sparsity pattern, no matter what reordering is used, since by
> definition there is no fill and hence no change in sparsity pattern from
> the original matrix.

The space required remains the same, but
the row-compressed matrix format
for the factor will be changed with the
reordering.
To store the new format over the
existing memory, temp space has to be allocated during
implementation. Thus replacing the original memory with
newly allocated space would make implementation easier.

> The reordering in this case simply changes the order of operations to
> perform the ILU(0) but not the memory requirements. In this case
> reordering is performed not to reduce fill but to achieve a "better" ILU
> factorization.

Yes.
>
> Hence it should be possible to perform and ILU(0) in place with
> different reorderings. This is what I was hoping to get support for.
>
We'll try to provide this support.

Hong
>
>
> On Thu, 3 Aug 2006, Hong Zhang wrote:
>
> >
> > Laslo,
> >
> > An reordering of matrix changes matrix sparse pattern,
> > then the factored matrix cannot be stored in the original matrix.
> > Here is the notes from petsc MatILUFactor():
> >
> > Notes:
> >   Probably really in-place only when level of fill is zero, otherwise
> > allocates
> >   new space to store factored matrix and deletes previous memory.
> >
> > i.e., except ilu(0) without reordering, petsc inplace ilu()
> > virtually computes a new factor, and deletes the previous memory.
> > You may use petsc out-place ilu, and call MatDestroy()
> > to delete your original matrix.
> >
> >> In otherwords, Petsc only supports in place ILU(0) without reordering.
> >>
> >> The idea behind doing an in place factorization is so that I don't use
> >> twice as much memory to store my matrix (ie the original matrix and the
> >> ILU factored matrix).
> >>
> >>
> >> Is in place ILU factorization with reordering going to be supported by
> >> Petsc anytime in the near future or is there an easy work around so I can
> >> get this to work?
> >
> > We can add this support. As mentioned above, the factored matrix
> > will be newly allocated with the original memory deleted.
> >
> > Hong
> >
> >
>
>