OK. I have a MPI sparse matrix. I'll find a way to convert it to MPI dense. Thanks Jose.
Franck ----- Mail original ----- > De: "Jose E. Roman" <[email protected]> > À: "Franck Houssen" <[email protected]> > Cc: "For users of the development version of PETSc" <[email protected]> > Envoyé: Vendredi 15 Décembre 2017 11:58:41 > Objet: Re: [petsc-dev] QR factorization of dense matrix > > It also works with MPIDense matrices. Use PETSC_COMM_WORLD only for bv and Z. > R should still be sequential. > Jose > > > El 15 dic 2017, a las 11:47, Franck Houssen <[email protected]> > > escribió: > > > > Coming back on that question: does BVOrthogonalize works also with > > distributed matrices ? Or only sequential ones ? > > > > This works fine with sequential matrices : > > > > Mat Z; MatCreateSeqDense(PETSC_COMM_SELF, n, m, NULL, &Z); > > ... // MatSetValues(Z, ...) > > BVCreate(PETSC_COMM_SELF, &bv); > > BVCreateFromMat(Z, &bv); // Z is tall-skinny > > Mat R; MatCreateSeqDense(PETSC_COMM_SELF, m, m, NULL, &R); > > BVOrthogonalize(bv, R); > > > > If it could be possible to got this to work with distributed matrices, do I > > need to replace PETSC_COMM_SELF with PETSC_COMM_WORLD all over the place, > > or, only for Z and bv ? (the doc says R must be sequential dense) > > > > Franck > > > > ----- Mail original ----- > >> De: "Franck Houssen" <[email protected]> > >> À: "Jose E. Roman" <[email protected]> > >> Cc: "For users of the development version of PETSc" > >> <[email protected]> > >> Envoyé: Mardi 31 Octobre 2017 16:17:28 > >> Objet: Re: [petsc-dev] QR factorization of dense matrix > >> > >> OK, got it. Thanks. > >> > >> Franck > >> > >> ----- Mail original ----- > >>> De: "Jose E. Roman" <[email protected]> > >>> À: "Franck Houssen" <[email protected]> > >>> Cc: "For users of the development version of PETSc" > >>> <[email protected]> > >>> Envoyé: Lundi 30 Octobre 2017 17:37:52 > >>> Objet: Re: [petsc-dev] QR factorization of dense matrix > >>> > >>> Any BV type will do. The default BVSVEC is generally best. > >>> Jose > >>> > >>> > >>>> El 30 oct 2017, a las 17:18, Franck Houssen <[email protected]> > >>>> escribió: > >>>> > >>>> It was not clear to me when I read the doc. That's OK now: got it to > >>>> work, > >>>> thanks Jose ! > >>>> Just to make sure, to make it work, I had to set a BV type: I chose > >>>> BVMAT > >>>> as I use BVCreateFromMat. Is that the good type ? (BVVECS works too) > >>>> > >>>> Franck > >>>> > >>>> ----- Mail original ----- > >>>>> De: "Jose E. Roman" <[email protected]> > >>>>> À: "Franck Houssen" <[email protected]> > >>>>> Cc: "For users of the development version of PETSc" > >>>>> <[email protected]> > >>>>> Envoyé: Samedi 28 Octobre 2017 16:56:22 > >>>>> Objet: Re: [petsc-dev] QR factorization of dense matrix > >>>>> > >>>>> Matrix R must be mxm. > >>>>> BVOrthogonalize computes Z=Q*R, where Q overwrites Z. > >>>>> Jose > >>>>> > >>>>>> El 28 oct 2017, a las 13:11, Franck Houssen <[email protected]> > >>>>>> escribió: > >>>>>> > >>>>>> I've seen that !... But can't get BVOrthogonalize to work. > >>>>>> > >>>>>> I tried: > >>>>>> Mat Z; MatCreateSeqDense(PETSC_COMM_SELF, n, m, NULL, &Z); > >>>>>> ...; // MatSetValues(Z, ...) > >>>>>> BVCreate(PETSC_COMM_SELF, &bv); > >>>>>> BVCreateFromMat(Z, &bv); // Z is tall-skinny > >>>>>> Mat R; MatCreateSeqDense(PETSC_COMM_SELF, n, m, NULL, &R); // Same n, > >>>>>> m > >>>>>> than Z. > >>>>>> BVOrthogonalize(bv, R); > >>>>>> > >>>>>> But BVOrthogonalize fails with : > >>>>>>> [0]PETSC ERROR: Nonconforming object sizes > >>>>>>> [0]PETSC ERROR: Mat argument is not square, it has 1 rows and 3 > >>>>>>> columns > >>>>>> > >>>>>> So, as I didn't get what's wrong, I was looking for another way to do > >>>>>> this. > >>>>>> > >>>>>> Franck > >>>>>> > >>>>>> ----- Mail original ----- > >>>>>>> De: "Jose E. Roman" <[email protected]> > >>>>>>> À: "Franck Houssen" <[email protected]> > >>>>>>> Cc: "For users of the development version of PETSc" > >>>>>>> <[email protected]> > >>>>>>> Envoyé: Vendredi 27 Octobre 2017 19:03:37 > >>>>>>> Objet: Re: [petsc-dev] QR factorization of dense matrix > >>>>>>> > >>>>>>> Franck, > >>>>>>> > >>>>>>> SLEPc has some support for this, but it is intended only for > >>>>>>> tall-skinny > >>>>>>> matrices, that is, when the number of columns is much smaller than > >>>>>>> rows. > >>>>>>> For > >>>>>>> an almost square matrix you should not use it. > >>>>>>> > >>>>>>> Have a look at this > >>>>>>> http://slepc.upv.es/documentation/current/docs/manualpages/BV/BVOrthogonalize.html > >>>>>>> http://slepc.upv.es/documentation/current/docs/manualpages/BV/BVOrthogBlockType.html > >>>>>>> > >>>>>>> You can see there are three methods. All of them have drawbacks: > >>>>>>> GS: This is a Gram-Schmidt QR, computed column by column, so it is > >>>>>>> slower > >>>>>>> than the other two. However, it is robust. > >>>>>>> CHOL: Cholesky QR, it is not numerically stable. In the future we > >>>>>>> will > >>>>>>> add > >>>>>>> Cholesky QR2. > >>>>>>> TSQR: Unfortunately this is not implemented in parallel. I wanted to > >>>>>>> add > >>>>>>> the > >>>>>>> parallel version for 3.8, but didn't have time. It will be added > >>>>>>> soon. > >>>>>>> > >>>>>>> You can use BVCreateFromMat() to create a BV object from a Mat. > >>>>>>> > >>>>>>> Jose > >>>>>>> > >>>>>>> > >>>>>>>> El 27 oct 2017, a las 18:39, Franck Houssen > >>>>>>>> <[email protected]> > >>>>>>>> escribió: > >>>>>>>> > >>>>>>>> I am looking for QR factorization of (sequential) dense matrix: is > >>>>>>>> this > >>>>>>>> available in PETSc ? I "just" need the diagonal of R (I do not need > >>>>>>>> neither the full content of R, nor Q) > >>>>>>>> > >>>>>>>> I found that (old !) thread > >>>>>>>> https://lists.mcs.anl.gov/pipermail/petsc-users/2013-November/019577.html > >>>>>>>> that says it could be implemented: has it been done ? > >>>>>>>> As for a direct solve, the way to go is "KSPSetType(ksp, > >>>>>>>> KSPPREONLY); > >>>>>>>> PCSetType(pc, PCLU);", I was expecting something like > >>>>>>>> "KSPSetType(ksp, > >>>>>>>> KSPPREONLY); PCSetType(pc, PCQR);"... But it seems there is no PCQR > >>>>>>>> available. Or is it possible to do that using "an iterative way" > >>>>>>>> with > >>>>>>>> a > >>>>>>>> specific kind of KSP that triggers a Gram Schmidt orthogonalization > >>>>>>>> in > >>>>>>>> back-end ? (I have seen a KSPLSQR but could I get Q and R back ? As > >>>>>>>> I > >>>>>>>> understand this, I would say no: I would say the user can only get > >>>>>>>> the > >>>>>>>> solution) > >>>>>>>> > >>>>>>>> Is it possible to QR a (sequential) dense matrix in PETSc ? If yes, > >>>>>>>> what > >>>>>>>> are the steps to follow ? > >>>>>>>> > >>>>>>>> Franck > >>>>>>>> > >>>>>>>> My understanding is that DGEQRF from lapack can do "more" than what > >>>>>>>> I > >>>>>>>> need, > >>>>>>>> but, no sure to get if I can use it from PETSc through a KSP: > >>>>>>>>>> git grep DGEQRF > >>>>>>>> include/petscblaslapack_stdcall.h:# define LAPACKgeqrf_ DGEQRF > >>>>>>>>>> git grep LAPACKgeqrf_ > >>>>>>>> include/petscblaslapack.h:PETSC_EXTERN void > >>>>>>>> LAPACKgeqrf_(PetscBLASInt*,PetscBLASInt*,PetscScalar*,PetscBLASInt*,PetscScalar*,PetscScalar*,PetscBLASInt*,PetscBLASInt*); > >>>>>>>> include/petscblaslapack_mangle.h:#define LAPACKgeqrf_ > >>>>>>>> PETSCBLAS(geqrf,GEQRF) > >>>>>>>> include/petscblaslapack_stdcall.h:# define LAPACKgeqrf_ SGEQRF > >>>>>>>> include/petscblaslapack_stdcall.h:# define LAPACKgeqrf_ DGEQRF > >>>>>>>> include/petscblaslapack_stdcall.h:# define LAPACKgeqrf_ CGEQRF > >>>>>>>> include/petscblaslapack_stdcall.h:# define LAPACKgeqrf_ ZGEQRF > >>>>>>>> include/petscblaslapack_stdcall.h:PETSC_EXTERN void PETSC_STDCALL > >>>>>>>> LAPACKgeqrf_(PetscBLASInt*,PetscBLASInt*,PetscScalar*,PetscBLASInt*,PetscScalar*,PetscScalar*,PetscBLASInt*,PetscBLASInt*); > >>>>>>>> src/dm/dt/interface/dt.c: > >>>>>>>> PetscStackCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&M,&N,A,&lda,tau,work,&ldwork,&info)); > >>>>>>>> src/dm/dt/interface/dtfv.c: > >>>>>>>> LAPACKgeqrf_(&M,&N,A,&lda,tau,work,&ldwork,&info); > >>>>>>>> src/ksp/ksp/impls/gmres/agmres/agmres.c: > >>>>>>>> PetscStackCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&lC, &KspSize, > >>>>>>>> agmres->hh_origin, &ldH, agmres->tau, agmres->work, &lwork, &info)); > >>>>>>>> src/ksp/pc/impls/bddc/bddcprivate.c: > >>>>>>>> PetscStackCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&Blas_M,&Blas_N,qr_basis,&Blas_LDA,qr_tau,&lqr_work_t,&lqr_work,&lierr)); > >>>>>>>> src/ksp/pc/impls/bddc/bddcprivate.c: > >>>>>>>> PetscStackCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&Blas_M,&Blas_N,qr_basis,&Blas_LDA,qr_tau,qr_work,&lqr_work,&lierr)); > >>>>>>>> src/ksp/pc/impls/gamg/agg.c: > >>>>>>>> PetscStackCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&Mdata, &N, qqc, &LDA, > >>>>>>>> TAU, WORK, &LWORK, &INFO)); > >>>>>>>> src/tao/leastsquares/impls/pounders/pounders.c: > >>>>>>>> PetscStackCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&blasnp,&blasnplus1,mfqP->Q_tmp,&blasnpmax,mfqP->tau_tmp,mfqP->mwork,&blasmaxmn,&info)); > >>>>>>>> src/tao/leastsquares/impls/pounders/pounders.c: > >>>>>>>> PetscStackCallBLAS("LAPACKgeqrf",LAPACKgeqrf_(&blasn,&blask,mfqP->Q,&blasnpmax,mfqP->tau,mfqP->mwork,&blasmaxmn,&info)); > >>>>>>> > >>>>>>> > >>>>> > >>>>> > >>> > >>> > >> > >
