[petsc-users] question about MatMatMultTranspose

[Hong Zhang]

Bin :
We do not have plan for supporting parallel (mpiaij format)
C = A*B^T
because sparse inner product is too expensive, and we have parallel C =
A^T*B.

For sequential C = A*B^T, currently we only support
C_seqaij = A_seqaij*B_seqaij^T

Do you want
C_seqdense = A_seqaij*B_seqaij^T
or
C_seqdense = A_seqaij*B_seqdense^T?

Hong

>
> Good to know it is simpler ;-) I am switching to the developed version and
> try it. Again, thank you very much.
>
> P.S., Moreover, I notice that some functions is not for MATMPIDENSE. May I
> ask if they are too difficult to implement (for instance, C=A*B^T and
> C=A^T*B for MATMPIDENSE)? Thank you.
>
> Cheers
>
> Gao
>  ------------------------------
> *From:* petsc-users-bounces at mcs.anl.gov [petsc-users-bounces at mcs.anl.gov]
> on behalf of Jed Brown [jedbrown at mcs.anl.gov]
> *Sent:* Thursday, April 05, 2012 2:32 PM
> *To:* PETSc users list; Hong Zhang
>
> *Subject:* Re: [petsc-users] question about MatMatMultTranspose
>
>   On Thu, Apr 5, 2012 at 05:16, Gao Bin <bin.gao at uit.no> wrote:
>
>> Thank you for your quick reply. But as pointed out at
>> http://www.mcs.anl.gov/petsc/petsc-dev/docs/manualpages/Mat/MatMatTransposeMult.html
>> :
>>
>> This routine is currently only implemented for pairs of SeqAIJ matrices.
>> C will be of type MATSEQAIJ.
>>
>> Therefore I can not use it for dense matrix, am I right? If so, will
>> MatMatTransposeMult be extended for other types of matrix later on? Thank
>> you very much.
>>
>
> This is much simpler than the sparse case. Hong, did you intend to get
> around to this?
>
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