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? > -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20120405/fe0af8aa/attachment.htm>
