Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[晓峰 何]

Hi Barry,

A00 is formed from elliptic operator.

I tried GAMG with A00, but it was extremely slow to solve the system with 
field-split preconditioner(I’m not sure I did it with the right way).

Thanks,
Xiaofeng

On Sep 26, 2022, at 23:11, Barry Smith 
mailto:bsm...@petsc.dev>> wrote:


  What is your A00 operator? ILU is almost never a good choice for large scale 
problems. If it is an elliptic operator that using a PC of gamg may work well 
for the A00 preconditioner instead of ILU.

  Barry

  For moderate size problems you can use a PC type LU for AOO to help you 
understand the best preconditioner to use for the A11 (the Schur complement 
block), once you have a good preconditioner for the A11 block you would then go 
back and determine a good preconditioner for the A00 block.

On Sep 26, 2022, at 10:08 AM, 晓峰 何 
mailto:tlan...@hotmail.com>> wrote:

Hello Jed,

The saddle point is due to Lagrange multipliers, thus the size of A11 is much 
smaller than A00.



Best Regards,

Xiaofeng


On Sep 26, 2022, at 21:03, Jed Brown 
mailto:j...@jedbrown.org>> wrote:

Lagrange multipliers

Re: [petsc-users] Strange mpi timing and CPU load when -np > 2

[Barry Smith]

  It is important to check out 
https://petsc.org/main/faq/?highlight=faq#why-is-my-parallel-solver-slower-than-my-sequential-solver-or-i-have-poor-speed-up
 


  In particular you will need to set appropriate binding for the mpiexec and 
should run the streams benchmark (make mpistreams) using the binding to find 
the potential performance of the system.

  If you are using a thread enabled BLAS/LAPACK that utilizes all the cores 
then you can get oversubscription and thus slow performance during BLAS/LAPACK 
calls. We try not to link with thread enabled BLAS/LAPACK by default. See 
https://petsc.org/main/docs/manual/blas-lapack/?highlight=thread%20blas

   Barry



> On Sep 26, 2022, at 12:39 PM, Duan Junming via petsc-users 
>  wrote:
> 
> Dear all,
> 
> I am using PETSc 3.17.4 on a Linux server, compiling with --download-exodus 
> --download-hdf5 --download-openmpi --download-triangle --with-fc=0 
> --with-debugging=0 PETSC_ARCH=arch-linux-c-opt COPTFLAGS="-g -O3" 
> CXXOPTFLAGS="-g -O3".
> The strange thing is when I run my code with mpirun -np 1 ./main, the CPU 
> time is 30s.
> When I use mpirun -np 2 ./main, the CPU time is 16s. It's OK.
> But when I use more than 2 CPUs, like mpirun -np 3 ./main, the CPU time is 
> 30s.
> The output of command time is: real 0m30.189s, user 9m3.133s, sys 10m55.715s.
> I can also see that the CPU load is about 100% for each process when np = 2, 
> but the CPU load goes to 2000%, 1000%, 1000% for each process (the server has 
> 40 CPUs).
> Do you have any idea about this?
> 
> Thanks in advance!

Re: [petsc-users] Strange mpi timing and CPU load when -np > 2

[Matthew Knepley]

On Mon, Sep 26, 2022 at 12:40 PM Duan Junming via petsc-users <
petsc-users@mcs.anl.gov> wrote:

> Dear all,
>
> I am using PETSc 3.17.4 on a Linux server, compiling
> with --download-exodus --download-hdf5 --download-openmpi
> --download-triangle --with-fc=0 --with-debugging=0
> PETSC_ARCH=arch-linux-c-opt COPTFLAGS="-g -O3" CXXOPTFLAGS="-g -O3".
> The strange thing is when I run my code with mpirun -np 1 ./main, the CPU
> time is 30s.
> When I use mpirun -np 2 ./main, the CPU time is 16s. It's OK.
> But when I use more than 2 CPUs, like mpirun -np 3 ./main, the CPU time is
> 30s.
> The output of command time is: real 0m30.189s, user 9m3.133s, sys
> 10m55.715s.
> I can also see that the CPU load is about 100% for each process when np =
> 2, but the CPU load goes to 2000%, 1000%, 1000% for each process (the
> server has 40 CPUs).
> Do you have any idea about this?
>

I believe this is an MPI implementation problem, in which there is a large
penalty for oversubscription. I think you can try

  --download-mpich --download-mpich-pm=gforker

which should be good for oversubscription.

  Thanks,

  Matt



> Thanks in advance!
>
-- 
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

https://www.cse.buffalo.edu/~knepley/ 

[petsc-users] Strange mpi timing and CPU load when -np > 2

[Duan Junming via petsc-users]

Dear all,

I am using PETSc 3.17.4 on a Linux server, compiling with --download-exodus 
--download-hdf5 --download-openmpi --download-triangle --with-fc=0 
--with-debugging=0 PETSC_ARCH=arch-linux-c-opt COPTFLAGS="-g -O3" 
CXXOPTFLAGS="-g -O3".
The strange thing is when I run my code with mpirun -np 1 ./main, the CPU time 
is 30s.
When I use mpirun -np 2 ./main, the CPU time is 16s. It's OK.
But when I use more than 2 CPUs, like mpirun -np 3 ./main, the CPU time is 30s.
The output of command time is: real 0m30.189s, user 9m3.133s, sys 10m55.715s.
I can also see that the CPU load is about 100% for each process when np = 2, 
but the CPU load goes to 2000%, 1000%, 1000% for each process (the server has 
40 CPUs).
Do you have any idea about this?

Thanks in advance!

Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[Barry Smith]

  
  What is your A00 operator? ILU is almost never a good choice for large scale 
problems. If it is an elliptic operator that using a PC of gamg may work well 
for the A00 preconditioner instead of ILU.

  Barry

  For moderate size problems you can use a PC type LU for AOO to help you 
understand the best preconditioner to use for the A11 (the Schur complement 
block), once you have a good preconditioner for the A11 block you would then go 
back and determine a good preconditioner for the A00 block.

> On Sep 26, 2022, at 10:08 AM, 晓峰 何  wrote:
> 
> Hello Jed,
> 
> The saddle point is due to Lagrange multipliers, thus the size of A11 is much 
> smaller than A00.
> 
> 
> 
> Best Regards,
> 
> Xiaofeng
> 
> 
>> On Sep 26, 2022, at 21:03, Jed Brown > > wrote:
>> 
>> Lagrange multipliers
> 

Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[晓峰 何]

Hello Matt,

Many thanks for your suggestion.


BR,
Xiaofeng


On Sep 26, 2022, at 20:29, Matthew Knepley 
mailto:knep...@gmail.com>> wrote:

Another option are the PCPATCH solvers for multigrid, as shown in this paper: 
https://arxiv.org/abs/1912.08516
which I believe solves incompressible elasticity. There is an example in PETSc 
for Stokes I believe.

  Thanks,

 Matt

On Mon, Sep 26, 2022 at 5:20 AM 晓峰 何 
mailto:tlan...@hotmail.com>> wrote:
Are there other approaches to solve this kind of systems in PETSc except for 
field-split methods?

Thanks,
Xiaofeng

On Sep 26, 2022, at 14:13, Jed Brown 
mailto:j...@jedbrown.org>> wrote:

This is the joy of factorization field-split methods. The actual Schur 
complement is dense, so we represent it implicitly. A common strategy is to 
assemble the mass matrix and drop it in the 11 block of the Pmat. You can check 
out some examples in the repository for incompressible flow (Stokes problems). 
The LSC (least squares commutator) is another option. You'll likely find that 
lumping diag(A00)^{-1} works poorly because the resulting operator behaves like 
a Laplacian rather than like a mass matrix.

晓峰 何 mailto:tlan...@hotmail.com>> writes:

If assigned a preconditioner to A11 with this cmd options:

  -fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu -fieldsplit_1_ksp_type 
gmres -fieldsplit_1_pc_type ilu

Then I got this error:

"Could not locate a solver type for factorization type ILU and matrix type 
schurcomplement"

How could I specify a preconditioner for A11?

BR,
Xiaofeng


On Sep 26, 2022, at 11:02, 晓峰 何 
mailto:tlan...@hotmail.com>> 
wrote:

-fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu -fieldsplit_1_ksp_type 
gmres -fieldsplit_1_pc_type none



--
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

https://www.cse.buffalo.edu/~knepley/

Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[晓峰 何]

Hello Jed,

The saddle point is due to Lagrange multipliers, thus the size of A11 is much 
smaller than A00.



Best Regards,

Xiaofeng


On Sep 26, 2022, at 21:03, Jed Brown 
mailto:j...@jedbrown.org>> wrote:

Lagrange multipliers

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[Pierre Jolivet]

> On 26 Sep 2022, at 2:52 PM, fujisan  wrote:
> 
> Ok, Thank you.
> I didn't know about MatCreateNormal.
> 
> In terms of computer performance, what is best to solve Ax=b with A 
> rectangular?
> Is it to keep A rectangular and use KSPLSQR along with PCNONE or 
> to convert to normal equations using MatCreateNormal and use another ksp type 
> with another pc type? 

It’s extremely cheap to call MatCreateNormal().
It’s just an object that behaves like A^T A, but it’s actually not assembled.

> In the future, our A will be very sparse and will be something like up to 100 
> millions lines and 10 millions columns in size.

Following-up on Matt’s answer, the good news is that if A is indeed very sparse 
and if A^T A is sparse as well, then you have a couple of options.
I’d be happy helping you out benchmark those.
Some of the largest problems I have been investigating thus far are 
https://sparse.tamu.edu/Hardesty/Hardesty3 
 and 
https://sparse.tamu.edu/Mittelmann/cont11_l 

To this day, PETSc has no Mat partitioner for rectangular systems (like PaToH), 
so whenever you need to redistribute such systems, the normal equations must be 
formed explicitly.
This can get quite costly, but if you already have an application with the 
proper partitioning, then the sky is the limit, I guess.

Thanks,
Pierre

> I will study all that.
> 
> Fuji
> 
> On Mon, Sep 26, 2022 at 11:45 AM Pierre Jolivet  > wrote:
> I’m sorry, solving overdetermined systems, alongside (overlapping) domain 
> decomposition preconditioners and solving systems with multiple right-hand 
> sides, is one of the topic for which I need to stop pushing new features and 
> update the users manual instead…
> The very basic documentation of PCQR is here: 
> https://petsc.org/main/docs/manualpages/PC/PCQR 
>  (I’m guessing you are using 
> the release documentation in which it’s indeed not present).
> Some comments about your problem of solving Ax=b with a rectangular matrix A.
> 1) if you switch to KSPLSQR, it is wrong to use KSPSetOperators(ksp, A, A).
> You can get away with murder if your PCType is PCNONE, but otherwise, you 
> should always supply the normal equations as the Pmat (you will get runtime 
> errors otherwise).
> To get the normal equations, you can use 
> https://petsc.org/main/docs/manualpages/Mat/MatCreateNormal/ 
> 
> The following two points only applies if your Pmat is sparse (or sparse with 
> some dense rows).
> 2) there are a couple of PC that handle MATNORMAL: PCNONE, PCQR, PCJACOBI, 
> PCBJACOBI, PCASM, PCHPDDM
> Currently, PCQR needs SuiteSparse, and thus runs only if the Pmat is 
> distributed on a single MPI process (if your Pmat is distributed on multiple 
> processes, you should first use PCREDUNDANT).
> 3) if you intend to make your problem scale in sizes, most of these 
> preconditioners will not be very robust.
> In that case, if your problem does not have any dense rows, you should either 
> use PCHPDDM or MatConvert(Pmat, MATAIJ, PmatAIJ) and then use PCCHOLESKY, 
> PCHYPRE or PCGAMG (you can have a look at 
> https://epubs.siam.org/doi/abs/10.1137/21M1434891 
>  for a comparison)
> If your problem has dense rows, I have somewhere the code to recast it into 
> an augmented system then solved using PCFIELDSPLIT (see 
> https://link.springer.com/article/10.1007/s11075-018-0478-2 
> ). I can send it 
> to you if needed.
> Let me know if I can be of further assistance or if something is not clear to 
> you.
> 
> Thanks,
> Pierre
> 
>> On 26 Sep 2022, at 10:56 AM, fujisan > > wrote:
>> 
>> OK thank you.
>> 
>> On Mon, Sep 26, 2022 at 10:53 AM Jose E. Roman > > wrote:
>> The QR factorization from SuiteSparse is sequential only, cannot be used in 
>> parallel.
>> In parallel you can try PCBJACOBI with a PCQR local preconditioner.
>> Pierre may have additional suggestions.
>> 
>> Jose
>> 
>> 
>> > El 26 sept 2022, a las 10:47, fujisan > > > escribió:
>> > 
>> > I did configure Petsc with the option --download-suitesparse.
>> > 
>> > The error is more like this:
>> > PETSC ERROR: Could not locate a solver type for factorization type QR and 
>> > matrix type mpiaij.
>> > 
>> > Fuji
>> > 
>> > On Mon, Sep 26, 2022 at 10:25 AM Jose E. Roman > > > wrote:
>> > If the error message is "Could not locate a solver type for factorization 
>> > type QR" then you should configure PETSc with --download-suitesparse
>> > 
>> > Jose
>> > 
>> > 
>> > > El 26 sept 2022, a las 9:06, fujisan > > > > escribió:
>> > > 
>> > > Thank you Pierre,
>> > > 
>> > > I used PCNONE along with 

Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[Jed Brown]

Xiaofeng, is your saddle point due to incompressibility or other constraints 
(like Lagrange multipliers for contact or multi-point constraints)? If 
incompressibility, are you working on structured or unstructured/non-nested 
meshes?

Matthew Knepley  writes:

> Another option are the PCPATCH solvers for multigrid, as shown in this
> paper: https://arxiv.org/abs/1912.08516
> which I believe solves incompressible elasticity. There is an example in
> PETSc for Stokes I believe.
>
>   Thanks,
>
>  Matt
>
> On Mon, Sep 26, 2022 at 5:20 AM 晓峰 何  wrote:
>
>> Are there other approaches to solve this kind of systems in PETSc except
>> for field-split methods?
>>
>> Thanks,
>> Xiaofeng
>>
>> On Sep 26, 2022, at 14:13, Jed Brown  wrote:
>>
>> This is the joy of factorization field-split methods. The actual Schur
>> complement is dense, so we represent it implicitly. A common strategy is to
>> assemble the mass matrix and drop it in the 11 block of the Pmat. You can
>> check out some examples in the repository for incompressible flow (Stokes
>> problems). The LSC (least squares commutator) is another option. You'll
>> likely find that lumping diag(A00)^{-1} works poorly because the resulting
>> operator behaves like a Laplacian rather than like a mass matrix.
>>
>> 晓峰 何  writes:
>>
>> If assigned a preconditioner to A11 with this cmd options:
>>
>>   -fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu
>> -fieldsplit_1_ksp_type gmres -fieldsplit_1_pc_type ilu
>>
>> Then I got this error:
>>
>> "Could not locate a solver type for factorization type ILU and matrix type
>> schurcomplement"
>>
>> How could I specify a preconditioner for A11?
>>
>> BR,
>> Xiaofeng
>>
>>
>> On Sep 26, 2022, at 11:02, 晓峰 何 > mailto:tlan...@hotmail.com >> wrote:
>>
>> -fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu
>> -fieldsplit_1_ksp_type gmres -fieldsplit_1_pc_type none
>>
>>
>>
>
> -- 
> 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
>
> https://www.cse.buffalo.edu/~knepley/ 

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[Matthew Knepley]

On Mon, Sep 26, 2022 at 8:52 AM fujisan  wrote:

> Ok, Thank you.
> I didn't know about MatCreateNormal.
>
> In terms of computer performance, what is best to solve Ax=b with A
> rectangular?
> Is it to keep A rectangular and use KSPLSQR along with PCNONE or
> to convert to normal equations using MatCreateNormal and use another ksp
> type with another pc type?
>

It depends on the spectral characteristics of the normal equations.

  Thanks,

 Matt


> In the future, our A will be very sparse and will be something like up to
> 100 millions lines and 10 millions columns in size.
>
> I will study all that.
>
> Fuji
>
> On Mon, Sep 26, 2022 at 11:45 AM Pierre Jolivet  wrote:
>
>> I’m sorry, solving overdetermined systems, alongside (overlapping) domain
>> decomposition preconditioners and solving systems with multiple right-hand
>> sides, is one of the topic for which I need to stop pushing new features
>> and update the users manual instead…
>> The very basic documentation of PCQR is here:
>> https://petsc.org/main/docs/manualpages/PC/PCQR (I’m guessing you are
>> using the release documentation in which it’s indeed not present).
>> Some comments about your problem of solving Ax=b with a rectangular
>> matrix A.
>> 1) if you switch to KSPLSQR, it is wrong to use KSPSetOperators(ksp, A,
>> A).
>> You can get away with murder if your PCType is PCNONE, but otherwise, you
>> should always supply the normal equations as the Pmat (you will get runtime
>> errors otherwise).
>> To get the normal equations, you can use
>> https://petsc.org/main/docs/manualpages/Mat/MatCreateNormal/
>> The following two points only applies if your Pmat is sparse (or sparse
>> with some dense rows).
>> 2) there are a couple of PC that handle MATNORMAL: PCNONE, PCQR,
>> PCJACOBI, PCBJACOBI, PCASM, PCHPDDM
>> Currently, PCQR needs SuiteSparse, and thus runs only if the Pmat is
>> distributed on a single MPI process (if your Pmat is distributed on
>> multiple processes, you should first use PCREDUNDANT).
>> 3) if you intend to make your problem scale in sizes, most of these
>> preconditioners will not be very robust.
>> In that case, if your problem does not have any dense rows, you should
>> either use PCHPDDM or MatConvert(Pmat, MATAIJ, PmatAIJ) and then use
>> PCCHOLESKY, PCHYPRE or PCGAMG (you can have a look at
>> https://epubs.siam.org/doi/abs/10.1137/21M1434891 for a comparison)
>> If your problem has dense rows, I have somewhere the code to recast it
>> into an augmented system then solved using PCFIELDSPLIT (see
>> https://link.springer.com/article/10.1007/s11075-018-0478-2). I can send
>> it to you if needed.
>> Let me know if I can be of further assistance or if something is not
>> clear to you.
>>
>> Thanks,
>> Pierre
>>
>> On 26 Sep 2022, at 10:56 AM, fujisan  wrote:
>>
>> OK thank you.
>>
>> On Mon, Sep 26, 2022 at 10:53 AM Jose E. Roman 
>> wrote:
>>
>>> The QR factorization from SuiteSparse is sequential only, cannot be used
>>> in parallel.
>>> In parallel you can try PCBJACOBI with a PCQR local preconditioner.
>>> Pierre may have additional suggestions.
>>>
>>> Jose
>>>
>>>
>>> > El 26 sept 2022, a las 10:47, fujisan  escribió:
>>> >
>>> > I did configure Petsc with the option --download-suitesparse.
>>> >
>>> > The error is more like this:
>>> > PETSC ERROR: Could not locate a solver type for factorization type QR
>>> and matrix type mpiaij.
>>> >
>>> > Fuji
>>> >
>>> > On Mon, Sep 26, 2022 at 10:25 AM Jose E. Roman 
>>> wrote:
>>> > If the error message is "Could not locate a solver type for
>>> factorization type QR" then you should configure PETSc with
>>> --download-suitesparse
>>> >
>>> > Jose
>>> >
>>> >
>>> > > El 26 sept 2022, a las 9:06, fujisan  escribió:
>>> > >
>>> > > Thank you Pierre,
>>> > >
>>> > > I used PCNONE along with KSPLSQR and it worked.
>>> > > But as for PCQR, it cannot be found. There is nothing about it in
>>> the documentation as well.
>>> > >
>>> > > Fuji
>>> > >
>>> > > On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet 
>>> wrote:
>>> > > Yes, but you need to use a KSP that handles rectangular Mat, such as
>>> KSPLSQR (-ksp_type lsqr).
>>> > > PCLU does not handle rectangular Pmat. The only PC that handle
>>> rectangular Pmat are PCQR, PCNONE.
>>> > > If you supply the normal equations as the Pmat for LSQR, then you
>>> can use “standard” PC.
>>> > > You can have a look at
>>> https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html that covers
>>> most of these cases.
>>> > >
>>> > > Thanks,
>>> > > Pierre
>>> > >
>>> > > (sorry for the earlier answer sent wrongfully to petsc-maint, please
>>> discard the previous email)
>>> > >
>>> > >> On 21 Sep 2022, at 10:03 AM, fujisan  wrote:
>>> > >>
>>> > >> I'm trying to solve Ax=b with a sparse rectangular matrix A (of
>>> size 33x17 in my test) using
>>> > >> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
>>> > >>
>>> > >> And I always get an error saying "Incompatible vector local
>>> lengths" (see below).
>>> > >>
>>> > >> Here is the 

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[fujisan]

Ok, Thank you.
I didn't know about MatCreateNormal.

In terms of computer performance, what is best to solve Ax=b with A
rectangular?
Is it to keep A rectangular and use KSPLSQR along with PCNONE or
to convert to normal equations using MatCreateNormal and use another ksp
type with another pc type?

In the future, our A will be very sparse and will be something like up to
100 millions lines and 10 millions columns in size.

I will study all that.

Fuji

On Mon, Sep 26, 2022 at 11:45 AM Pierre Jolivet  wrote:

> I’m sorry, solving overdetermined systems, alongside (overlapping) domain
> decomposition preconditioners and solving systems with multiple right-hand
> sides, is one of the topic for which I need to stop pushing new features
> and update the users manual instead…
> The very basic documentation of PCQR is here:
> https://petsc.org/main/docs/manualpages/PC/PCQR (I’m guessing you are
> using the release documentation in which it’s indeed not present).
> Some comments about your problem of solving Ax=b with a rectangular matrix
> A.
> 1) if you switch to KSPLSQR, it is wrong to use KSPSetOperators(ksp, A, A).
> You can get away with murder if your PCType is PCNONE, but otherwise, you
> should always supply the normal equations as the Pmat (you will get runtime
> errors otherwise).
> To get the normal equations, you can use
> https://petsc.org/main/docs/manualpages/Mat/MatCreateNormal/
> The following two points only applies if your Pmat is sparse (or sparse
> with some dense rows).
> 2) there are a couple of PC that handle MATNORMAL: PCNONE, PCQR, PCJACOBI,
> PCBJACOBI, PCASM, PCHPDDM
> Currently, PCQR needs SuiteSparse, and thus runs only if the Pmat is
> distributed on a single MPI process (if your Pmat is distributed on
> multiple processes, you should first use PCREDUNDANT).
> 3) if you intend to make your problem scale in sizes, most of these
> preconditioners will not be very robust.
> In that case, if your problem does not have any dense rows, you should
> either use PCHPDDM or MatConvert(Pmat, MATAIJ, PmatAIJ) and then use
> PCCHOLESKY, PCHYPRE or PCGAMG (you can have a look at
> https://epubs.siam.org/doi/abs/10.1137/21M1434891 for a comparison)
> If your problem has dense rows, I have somewhere the code to recast it
> into an augmented system then solved using PCFIELDSPLIT (see
> https://link.springer.com/article/10.1007/s11075-018-0478-2). I can send
> it to you if needed.
> Let me know if I can be of further assistance or if something is not clear
> to you.
>
> Thanks,
> Pierre
>
> On 26 Sep 2022, at 10:56 AM, fujisan  wrote:
>
> OK thank you.
>
> On Mon, Sep 26, 2022 at 10:53 AM Jose E. Roman  wrote:
>
>> The QR factorization from SuiteSparse is sequential only, cannot be used
>> in parallel.
>> In parallel you can try PCBJACOBI with a PCQR local preconditioner.
>> Pierre may have additional suggestions.
>>
>> Jose
>>
>>
>> > El 26 sept 2022, a las 10:47, fujisan  escribió:
>> >
>> > I did configure Petsc with the option --download-suitesparse.
>> >
>> > The error is more like this:
>> > PETSC ERROR: Could not locate a solver type for factorization type QR
>> and matrix type mpiaij.
>> >
>> > Fuji
>> >
>> > On Mon, Sep 26, 2022 at 10:25 AM Jose E. Roman 
>> wrote:
>> > If the error message is "Could not locate a solver type for
>> factorization type QR" then you should configure PETSc with
>> --download-suitesparse
>> >
>> > Jose
>> >
>> >
>> > > El 26 sept 2022, a las 9:06, fujisan  escribió:
>> > >
>> > > Thank you Pierre,
>> > >
>> > > I used PCNONE along with KSPLSQR and it worked.
>> > > But as for PCQR, it cannot be found. There is nothing about it in the
>> documentation as well.
>> > >
>> > > Fuji
>> > >
>> > > On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet 
>> wrote:
>> > > Yes, but you need to use a KSP that handles rectangular Mat, such as
>> KSPLSQR (-ksp_type lsqr).
>> > > PCLU does not handle rectangular Pmat. The only PC that handle
>> rectangular Pmat are PCQR, PCNONE.
>> > > If you supply the normal equations as the Pmat for LSQR, then you can
>> use “standard” PC.
>> > > You can have a look at
>> https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html that covers
>> most of these cases.
>> > >
>> > > Thanks,
>> > > Pierre
>> > >
>> > > (sorry for the earlier answer sent wrongfully to petsc-maint, please
>> discard the previous email)
>> > >
>> > >> On 21 Sep 2022, at 10:03 AM, fujisan  wrote:
>> > >>
>> > >> I'm trying to solve Ax=b with a sparse rectangular matrix A (of size
>> 33x17 in my test) using
>> > >> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
>> > >>
>> > >> And I always get an error saying "Incompatible vector local lengths"
>> (see below).
>> > >>
>> > >> Here is the relevant lines of my code:
>> > >>
>> > >> program test
>> > >> ...
>> > >> ! Variable declarations
>> > >>
>> > >> PetscCallA(PetscInitialize(PETSC_NULL_CHARACTER,ierr))
>> > >>
>> > >> PetscCall(MatCreate(PETSC_COMM_WORLD,A,ierr))
>> > >> 

Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[Matthew Knepley]

Another option are the PCPATCH solvers for multigrid, as shown in this
paper: https://arxiv.org/abs/1912.08516
which I believe solves incompressible elasticity. There is an example in
PETSc for Stokes I believe.

  Thanks,

 Matt

On Mon, Sep 26, 2022 at 5:20 AM 晓峰 何  wrote:

> Are there other approaches to solve this kind of systems in PETSc except
> for field-split methods?
>
> Thanks,
> Xiaofeng
>
> On Sep 26, 2022, at 14:13, Jed Brown  wrote:
>
> This is the joy of factorization field-split methods. The actual Schur
> complement is dense, so we represent it implicitly. A common strategy is to
> assemble the mass matrix and drop it in the 11 block of the Pmat. You can
> check out some examples in the repository for incompressible flow (Stokes
> problems). The LSC (least squares commutator) is another option. You'll
> likely find that lumping diag(A00)^{-1} works poorly because the resulting
> operator behaves like a Laplacian rather than like a mass matrix.
>
> 晓峰 何  writes:
>
> If assigned a preconditioner to A11 with this cmd options:
>
>   -fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu
> -fieldsplit_1_ksp_type gmres -fieldsplit_1_pc_type ilu
>
> Then I got this error:
>
> "Could not locate a solver type for factorization type ILU and matrix type
> schurcomplement"
>
> How could I specify a preconditioner for A11?
>
> BR,
> Xiaofeng
>
>
> On Sep 26, 2022, at 11:02, 晓峰 何  mailto:tlan...@hotmail.com >> wrote:
>
> -fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu
> -fieldsplit_1_ksp_type gmres -fieldsplit_1_pc_type none
>
>
>

-- 
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

https://www.cse.buffalo.edu/~knepley/ 

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[Pierre Jolivet]

I’m sorry, solving overdetermined systems, alongside (overlapping) domain 
decomposition preconditioners and solving systems with multiple right-hand 
sides, is one of the topic for which I need to stop pushing new features and 
update the users manual instead…
The very basic documentation of PCQR is here: 
https://petsc.org/main/docs/manualpages/PC/PCQR 
 (I’m guessing you are using 
the release documentation in which it’s indeed not present).
Some comments about your problem of solving Ax=b with a rectangular matrix A.
1) if you switch to KSPLSQR, it is wrong to use KSPSetOperators(ksp, A, A).
You can get away with murder if your PCType is PCNONE, but otherwise, you 
should always supply the normal equations as the Pmat (you will get runtime 
errors otherwise).
To get the normal equations, you can use 
https://petsc.org/main/docs/manualpages/Mat/MatCreateNormal/ 

The following two points only applies if your Pmat is sparse (or sparse with 
some dense rows).
2) there are a couple of PC that handle MATNORMAL: PCNONE, PCQR, PCJACOBI, 
PCBJACOBI, PCASM, PCHPDDM
Currently, PCQR needs SuiteSparse, and thus runs only if the Pmat is 
distributed on a single MPI process (if your Pmat is distributed on multiple 
processes, you should first use PCREDUNDANT).
3) if you intend to make your problem scale in sizes, most of these 
preconditioners will not be very robust.
In that case, if your problem does not have any dense rows, you should either 
use PCHPDDM or MatConvert(Pmat, MATAIJ, PmatAIJ) and then use PCCHOLESKY, 
PCHYPRE or PCGAMG (you can have a look at 
https://epubs.siam.org/doi/abs/10.1137/21M1434891 
 for a comparison)
If your problem has dense rows, I have somewhere the code to recast it into an 
augmented system then solved using PCFIELDSPLIT (see 
https://link.springer.com/article/10.1007/s11075-018-0478-2 
). I can send it 
to you if needed.
Let me know if I can be of further assistance or if something is not clear to 
you.

Thanks,
Pierre

> On 26 Sep 2022, at 10:56 AM, fujisan  wrote:
> 
> OK thank you.
> 
> On Mon, Sep 26, 2022 at 10:53 AM Jose E. Roman  > wrote:
> The QR factorization from SuiteSparse is sequential only, cannot be used in 
> parallel.
> In parallel you can try PCBJACOBI with a PCQR local preconditioner.
> Pierre may have additional suggestions.
> 
> Jose
> 
> 
> > El 26 sept 2022, a las 10:47, fujisan  > > escribió:
> > 
> > I did configure Petsc with the option --download-suitesparse.
> > 
> > The error is more like this:
> > PETSC ERROR: Could not locate a solver type for factorization type QR and 
> > matrix type mpiaij.
> > 
> > Fuji
> > 
> > On Mon, Sep 26, 2022 at 10:25 AM Jose E. Roman  > > wrote:
> > If the error message is "Could not locate a solver type for factorization 
> > type QR" then you should configure PETSc with --download-suitesparse
> > 
> > Jose
> > 
> > 
> > > El 26 sept 2022, a las 9:06, fujisan  > > > escribió:
> > > 
> > > Thank you Pierre,
> > > 
> > > I used PCNONE along with KSPLSQR and it worked.
> > > But as for PCQR, it cannot be found. There is nothing about it in the 
> > > documentation as well.
> > > 
> > > Fuji
> > > 
> > > On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet  > > > wrote:
> > > Yes, but you need to use a KSP that handles rectangular Mat, such as 
> > > KSPLSQR (-ksp_type lsqr).
> > > PCLU does not handle rectangular Pmat. The only PC that handle 
> > > rectangular Pmat are PCQR, PCNONE.
> > > If you supply the normal equations as the Pmat for LSQR, then you can use 
> > > “standard” PC.
> > > You can have a look at 
> > > https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html 
> > >  that covers 
> > > most of these cases.
> > > 
> > > Thanks,
> > > Pierre
> > > 
> > > (sorry for the earlier answer sent wrongfully to petsc-maint, please 
> > > discard the previous email)
> > > 
> > >> On 21 Sep 2022, at 10:03 AM, fujisan  > >> > wrote:
> > >> 
> > >> I'm trying to solve Ax=b with a sparse rectangular matrix A (of size 
> > >> 33x17 in my test) using
> > >> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
> > >> 
> > >> And I always get an error saying "Incompatible vector local lengths" 
> > >> (see below).
> > >> 
> > >> Here is the relevant lines of my code:
> > >> 
> > >> program test
> > >> ...
> > >> ! Variable declarations
> > >> 
> > >> PetscCallA(PetscInitialize(PETSC_NULL_CHARACTER,ierr))
> > >> 
> > >> PetscCall(MatCreate(PETSC_COMM_WORLD,A,ierr))
> > >> PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n,ierr))
> > >> 

Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[晓峰 何]

Are there other approaches to solve this kind of systems in PETSc except for 
field-split methods?

Thanks,
Xiaofeng

On Sep 26, 2022, at 14:13, Jed Brown 
mailto:j...@jedbrown.org>> wrote:

This is the joy of factorization field-split methods. The actual Schur 
complement is dense, so we represent it implicitly. A common strategy is to 
assemble the mass matrix and drop it in the 11 block of the Pmat. You can check 
out some examples in the repository for incompressible flow (Stokes problems). 
The LSC (least squares commutator) is another option. You'll likely find that 
lumping diag(A00)^{-1} works poorly because the resulting operator behaves like 
a Laplacian rather than like a mass matrix.

晓峰 何 mailto:tlan...@hotmail.com>> writes:

If assigned a preconditioner to A11 with this cmd options:

  -fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu -fieldsplit_1_ksp_type 
gmres -fieldsplit_1_pc_type ilu

Then I got this error:

"Could not locate a solver type for factorization type ILU and matrix type 
schurcomplement"

How could I specify a preconditioner for A11?

BR,
Xiaofeng


On Sep 26, 2022, at 11:02, 晓峰 何 
mailto:tlan...@hotmail.com>> 
wrote:

-fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu -fieldsplit_1_ksp_type 
gmres -fieldsplit_1_pc_type none

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[fujisan]

OK thank you.

On Mon, Sep 26, 2022 at 10:53 AM Jose E. Roman  wrote:

> The QR factorization from SuiteSparse is sequential only, cannot be used
> in parallel.
> In parallel you can try PCBJACOBI with a PCQR local preconditioner.
> Pierre may have additional suggestions.
>
> Jose
>
>
> > El 26 sept 2022, a las 10:47, fujisan  escribió:
> >
> > I did configure Petsc with the option --download-suitesparse.
> >
> > The error is more like this:
> > PETSC ERROR: Could not locate a solver type for factorization type QR
> and matrix type mpiaij.
> >
> > Fuji
> >
> > On Mon, Sep 26, 2022 at 10:25 AM Jose E. Roman 
> wrote:
> > If the error message is "Could not locate a solver type for
> factorization type QR" then you should configure PETSc with
> --download-suitesparse
> >
> > Jose
> >
> >
> > > El 26 sept 2022, a las 9:06, fujisan  escribió:
> > >
> > > Thank you Pierre,
> > >
> > > I used PCNONE along with KSPLSQR and it worked.
> > > But as for PCQR, it cannot be found. There is nothing about it in the
> documentation as well.
> > >
> > > Fuji
> > >
> > > On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet 
> wrote:
> > > Yes, but you need to use a KSP that handles rectangular Mat, such as
> KSPLSQR (-ksp_type lsqr).
> > > PCLU does not handle rectangular Pmat. The only PC that handle
> rectangular Pmat are PCQR, PCNONE.
> > > If you supply the normal equations as the Pmat for LSQR, then you can
> use “standard” PC.
> > > You can have a look at
> https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html that covers most
> of these cases.
> > >
> > > Thanks,
> > > Pierre
> > >
> > > (sorry for the earlier answer sent wrongfully to petsc-maint, please
> discard the previous email)
> > >
> > >> On 21 Sep 2022, at 10:03 AM, fujisan  wrote:
> > >>
> > >> I'm trying to solve Ax=b with a sparse rectangular matrix A (of size
> 33x17 in my test) using
> > >> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
> > >>
> > >> And I always get an error saying "Incompatible vector local lengths"
> (see below).
> > >>
> > >> Here is the relevant lines of my code:
> > >>
> > >> program test
> > >> ...
> > >> ! Variable declarations
> > >>
> > >> PetscCallA(PetscInitialize(PETSC_NULL_CHARACTER,ierr))
> > >>
> > >> PetscCall(MatCreate(PETSC_COMM_WORLD,A,ierr))
> > >> PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n,ierr))
> > >> PetscCall(MatSetType(A,MATMPIAIJ,ierr))
> > >> PetscCall(MatSetFromOptions(A,ierr))
> > >> PetscCall(MatSetUp(A,ierr))
> > >> PetscCall(MatGetOwnershipRange(A,istart,iend,ierr))
> > >>
> > >> do irow=istart,iend-1
> > >> ... Reading from file ...
> > >> PetscCall(MatSetValues(A,1,irow,nzv,col,val,ADD_VALUES,ierr))
> > >> ...
> > >> enddo
> > >>
> > >> PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,ierr))
> > >> PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,ierr))
> > >>
> > >> ! Creating vectors x and b
> > >> PetscCallA(MatCreateVecs(A,x,b,ierr))
> > >>
> > >> ! Duplicating x in u.
> > >> PetscCallA(VecDuplicate(x,u,ierr))
> > >>
> > >> ! u is used to calculate b
> > >> PetscCallA(VecSet(u,1.0,ierr))
> > >>
> > >> PetscCallA(VecAssemblyBegin(u,ierr))
> > >> PetscCallA(VecAssemblyEnd(u,ierr))
> > >>
> > >> ! Calculating Au = b
> > >> PetscCallA(MatMult(A,u,b,ierr)) ! A.u = b
> > >>
> > >> PetscCallA(KSPSetType(ksp,KSPCG,ierr))
> > >>
> > >> PetscCallA(KSPSetOperators(ksp,A,A,ierr))
> > >>
> > >> PetscCallA(KSPSetFromOptions(ksp,ierr))
> > >>
> > >> ! Solving Ax = b, x unknown
> > >> PetscCallA(KSPSolve(ksp,b,x,ierr))
> > >>
> > >> PetscCallA(VecDestroy(x,ierr))
> > >> PetscCallA(VecDestroy(u,ierr))
> > >> PetscCallA(VecDestroy(b,ierr))
> > >> PetscCallA(MatDestroy(A,ierr))
> > >> PetscCallA(KSPDestroy(ksp,ierr))
> > >>
> > >> call PetscFinalize(ierr)
> > >> end program
> > >>
> > >> The code reads a sparse matrix from a binary file.
> > >> I also output the sizes of matrix A and vectors b, x, u.
> > >> They all seem consistent.
> > >>
> > >> What am I doing wrong?
> > >> Is it possible to solve Ax=b with A rectangular?
> > >>
> > >> Thank you in advance for your help.
> > >> Have a nice day.
> > >>
> > >> Fuji
> > >>
> > >>  Matrix size : m=  33  n=  17  cpu size:1
> > >>  Size of matrix A  :   33  17
> > >>  Size of vector b :   33
> > >>  Size of vector x :   17
> > >>  Size of vector u :   17
> > >> [0]PETSC ERROR: - Error Message
> --
> > >> [0]PETSC ERROR: Arguments are incompatible
> > >> [0]PETSC ERROR: Incompatible vector local lengths parameter # 1 local
> size 33 != parameter # 2 local size 17
> > >> [0]PETSC ERROR: See https://petsc.org/release/faq/ for trouble
> shooting.
> > >> [0]PETSC ERROR: Petsc Development GIT revision:
> v3.17.4-1341-g91b2b62a00  GIT Date: 2022-09-15 19:26:07 

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[Jose E. Roman]

The QR factorization from SuiteSparse is sequential only, cannot be used in 
parallel.
In parallel you can try PCBJACOBI with a PCQR local preconditioner.
Pierre may have additional suggestions.

Jose


> El 26 sept 2022, a las 10:47, fujisan  escribió:
> 
> I did configure Petsc with the option --download-suitesparse.
> 
> The error is more like this:
> PETSC ERROR: Could not locate a solver type for factorization type QR and 
> matrix type mpiaij.
> 
> Fuji
> 
> On Mon, Sep 26, 2022 at 10:25 AM Jose E. Roman  wrote:
> If the error message is "Could not locate a solver type for factorization 
> type QR" then you should configure PETSc with --download-suitesparse
> 
> Jose
> 
> 
> > El 26 sept 2022, a las 9:06, fujisan  escribió:
> > 
> > Thank you Pierre,
> > 
> > I used PCNONE along with KSPLSQR and it worked.
> > But as for PCQR, it cannot be found. There is nothing about it in the 
> > documentation as well.
> > 
> > Fuji
> > 
> > On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet  wrote:
> > Yes, but you need to use a KSP that handles rectangular Mat, such as 
> > KSPLSQR (-ksp_type lsqr).
> > PCLU does not handle rectangular Pmat. The only PC that handle rectangular 
> > Pmat are PCQR, PCNONE.
> > If you supply the normal equations as the Pmat for LSQR, then you can use 
> > “standard” PC.
> > You can have a look at 
> > https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html that covers most 
> > of these cases.
> > 
> > Thanks,
> > Pierre
> > 
> > (sorry for the earlier answer sent wrongfully to petsc-maint, please 
> > discard the previous email)
> > 
> >> On 21 Sep 2022, at 10:03 AM, fujisan  wrote:
> >> 
> >> I'm trying to solve Ax=b with a sparse rectangular matrix A (of size 33x17 
> >> in my test) using
> >> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
> >> 
> >> And I always get an error saying "Incompatible vector local lengths" (see 
> >> below).
> >> 
> >> Here is the relevant lines of my code:
> >> 
> >> program test
> >> ...
> >> ! Variable declarations
> >> 
> >> PetscCallA(PetscInitialize(PETSC_NULL_CHARACTER,ierr))
> >> 
> >> PetscCall(MatCreate(PETSC_COMM_WORLD,A,ierr))
> >> PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n,ierr))
> >> PetscCall(MatSetType(A,MATMPIAIJ,ierr))
> >> PetscCall(MatSetFromOptions(A,ierr))
> >> PetscCall(MatSetUp(A,ierr))
> >> PetscCall(MatGetOwnershipRange(A,istart,iend,ierr))
> >> 
> >> do irow=istart,iend-1
> >> ... Reading from file ...
> >> PetscCall(MatSetValues(A,1,irow,nzv,col,val,ADD_VALUES,ierr))
> >> ...
> >> enddo
> >> 
> >> PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,ierr))
> >> PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,ierr))
> >> 
> >> ! Creating vectors x and b
> >> PetscCallA(MatCreateVecs(A,x,b,ierr))
> >> 
> >> ! Duplicating x in u.
> >> PetscCallA(VecDuplicate(x,u,ierr))
> >> 
> >> ! u is used to calculate b
> >> PetscCallA(VecSet(u,1.0,ierr))
> >> 
> >> PetscCallA(VecAssemblyBegin(u,ierr))
> >> PetscCallA(VecAssemblyEnd(u,ierr))
> >> 
> >> ! Calculating Au = b
> >> PetscCallA(MatMult(A,u,b,ierr)) ! A.u = b
> >> 
> >> PetscCallA(KSPSetType(ksp,KSPCG,ierr))
> >> 
> >> PetscCallA(KSPSetOperators(ksp,A,A,ierr))
> >> 
> >> PetscCallA(KSPSetFromOptions(ksp,ierr))
> >> 
> >> ! Solving Ax = b, x unknown
> >> PetscCallA(KSPSolve(ksp,b,x,ierr))
> >> 
> >> PetscCallA(VecDestroy(x,ierr))
> >> PetscCallA(VecDestroy(u,ierr))
> >> PetscCallA(VecDestroy(b,ierr))
> >> PetscCallA(MatDestroy(A,ierr))
> >> PetscCallA(KSPDestroy(ksp,ierr))
> >> 
> >> call PetscFinalize(ierr)
> >> end program
> >> 
> >> The code reads a sparse matrix from a binary file.
> >> I also output the sizes of matrix A and vectors b, x, u.
> >> They all seem consistent.
> >> 
> >> What am I doing wrong?
> >> Is it possible to solve Ax=b with A rectangular?
> >> 
> >> Thank you in advance for your help.
> >> Have a nice day.
> >> 
> >> Fuji
> >> 
> >>  Matrix size : m=  33  n=  17  cpu size:1
> >>  Size of matrix A  :   33  17
> >>  Size of vector b :   33
> >>  Size of vector x :   17
> >>  Size of vector u :   17
> >> [0]PETSC ERROR: - Error Message 
> >> --
> >> [0]PETSC ERROR: Arguments are incompatible
> >> [0]PETSC ERROR: Incompatible vector local lengths parameter # 1 local size 
> >> 33 != parameter # 2 local size 17
> >> [0]PETSC ERROR: See https://petsc.org/release/faq/ for trouble shooting.
> >> [0]PETSC ERROR: Petsc Development GIT revision: v3.17.4-1341-g91b2b62a00  
> >> GIT Date: 2022-09-15 19:26:07 +
> >> [0]PETSC ERROR: ./bin/solve on a x86_64 named master by fujisan Tue Sep 20 
> >> 16:56:37 2022
> >> [0]PETSC ERROR: Configure options --with-petsc-arch=x86_64 --COPTFLAGS="-g 
> >> -O3" --FOPTFLAGS="-g -O3" --CXXOPTFLAGS="-g -O3" 

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[fujisan]

I did configure Petsc with the option --download-suitesparse.

The error is more like this:
PETSC ERROR: Could not locate a solver type for factorization type QR and
matrix type mpiaij.

Fuji

On Mon, Sep 26, 2022 at 10:25 AM Jose E. Roman  wrote:

> If the error message is "Could not locate a solver type for factorization
> type QR" then you should configure PETSc with --download-suitesparse
>
> Jose
>
>
> > El 26 sept 2022, a las 9:06, fujisan  escribió:
> >
> > Thank you Pierre,
> >
> > I used PCNONE along with KSPLSQR and it worked.
> > But as for PCQR, it cannot be found. There is nothing about it in the
> documentation as well.
> >
> > Fuji
> >
> > On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet  wrote:
> > Yes, but you need to use a KSP that handles rectangular Mat, such as
> KSPLSQR (-ksp_type lsqr).
> > PCLU does not handle rectangular Pmat. The only PC that handle
> rectangular Pmat are PCQR, PCNONE.
> > If you supply the normal equations as the Pmat for LSQR, then you can
> use “standard” PC.
> > You can have a look at
> https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html that covers most
> of these cases.
> >
> > Thanks,
> > Pierre
> >
> > (sorry for the earlier answer sent wrongfully to petsc-maint, please
> discard the previous email)
> >
> >> On 21 Sep 2022, at 10:03 AM, fujisan  wrote:
> >>
> >> I'm trying to solve Ax=b with a sparse rectangular matrix A (of size
> 33x17 in my test) using
> >> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
> >>
> >> And I always get an error saying "Incompatible vector local lengths"
> (see below).
> >>
> >> Here is the relevant lines of my code:
> >>
> >> program test
> >> ...
> >> ! Variable declarations
> >>
> >> PetscCallA(PetscInitialize(PETSC_NULL_CHARACTER,ierr))
> >>
> >> PetscCall(MatCreate(PETSC_COMM_WORLD,A,ierr))
> >> PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n,ierr))
> >> PetscCall(MatSetType(A,MATMPIAIJ,ierr))
> >> PetscCall(MatSetFromOptions(A,ierr))
> >> PetscCall(MatSetUp(A,ierr))
> >> PetscCall(MatGetOwnershipRange(A,istart,iend,ierr))
> >>
> >> do irow=istart,iend-1
> >> ... Reading from file ...
> >> PetscCall(MatSetValues(A,1,irow,nzv,col,val,ADD_VALUES,ierr))
> >> ...
> >> enddo
> >>
> >> PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,ierr))
> >> PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,ierr))
> >>
> >> ! Creating vectors x and b
> >> PetscCallA(MatCreateVecs(A,x,b,ierr))
> >>
> >> ! Duplicating x in u.
> >> PetscCallA(VecDuplicate(x,u,ierr))
> >>
> >> ! u is used to calculate b
> >> PetscCallA(VecSet(u,1.0,ierr))
> >>
> >> PetscCallA(VecAssemblyBegin(u,ierr))
> >> PetscCallA(VecAssemblyEnd(u,ierr))
> >>
> >> ! Calculating Au = b
> >> PetscCallA(MatMult(A,u,b,ierr)) ! A.u = b
> >>
> >> PetscCallA(KSPSetType(ksp,KSPCG,ierr))
> >>
> >> PetscCallA(KSPSetOperators(ksp,A,A,ierr))
> >>
> >> PetscCallA(KSPSetFromOptions(ksp,ierr))
> >>
> >> ! Solving Ax = b, x unknown
> >> PetscCallA(KSPSolve(ksp,b,x,ierr))
> >>
> >> PetscCallA(VecDestroy(x,ierr))
> >> PetscCallA(VecDestroy(u,ierr))
> >> PetscCallA(VecDestroy(b,ierr))
> >> PetscCallA(MatDestroy(A,ierr))
> >> PetscCallA(KSPDestroy(ksp,ierr))
> >>
> >> call PetscFinalize(ierr)
> >> end program
> >>
> >> The code reads a sparse matrix from a binary file.
> >> I also output the sizes of matrix A and vectors b, x, u.
> >> They all seem consistent.
> >>
> >> What am I doing wrong?
> >> Is it possible to solve Ax=b with A rectangular?
> >>
> >> Thank you in advance for your help.
> >> Have a nice day.
> >>
> >> Fuji
> >>
> >>  Matrix size : m=  33  n=  17  cpu size:1
> >>  Size of matrix A  :   33  17
> >>  Size of vector b :   33
> >>  Size of vector x :   17
> >>  Size of vector u :   17
> >> [0]PETSC ERROR: - Error Message
> --
> >> [0]PETSC ERROR: Arguments are incompatible
> >> [0]PETSC ERROR: Incompatible vector local lengths parameter # 1 local
> size 33 != parameter # 2 local size 17
> >> [0]PETSC ERROR: See https://petsc.org/release/faq/ for trouble
> shooting.
> >> [0]PETSC ERROR: Petsc Development GIT revision:
> v3.17.4-1341-g91b2b62a00  GIT Date: 2022-09-15 19:26:07 +
> >> [0]PETSC ERROR: ./bin/solve on a x86_64 named master by fujisan Tue Sep
> 20 16:56:37 2022
> >> [0]PETSC ERROR: Configure options --with-petsc-arch=x86_64
> --COPTFLAGS="-g -O3" --FOPTFLAGS="-g -O3" --CXXOPTFLAGS="-g -O3"
> --with-debugging=0 --with-cc=mpiicc --with-cxx=mpiicpc --with-fc=mpiifort
> --with-single-library=1 --with-mpiexec=mpiexec --with-precision=double
> --with-fortran-interfaces=1 --with-make=1 --with-mpi=1
> --with-mpi-compilers=1 --download-fblaslapack=0 --download-hypre=1
> --download-cmake=0 --with-cmake=1 --download-metis=1 --download-parmetis=1
> 

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[Jose E. Roman]

If the error message is "Could not locate a solver type for factorization type 
QR" then you should configure PETSc with --download-suitesparse

Jose


> El 26 sept 2022, a las 9:06, fujisan  escribió:
> 
> Thank you Pierre,
> 
> I used PCNONE along with KSPLSQR and it worked.
> But as for PCQR, it cannot be found. There is nothing about it in the 
> documentation as well.
> 
> Fuji
> 
> On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet  wrote:
> Yes, but you need to use a KSP that handles rectangular Mat, such as KSPLSQR 
> (-ksp_type lsqr).
> PCLU does not handle rectangular Pmat. The only PC that handle rectangular 
> Pmat are PCQR, PCNONE.
> If you supply the normal equations as the Pmat for LSQR, then you can use 
> “standard” PC.
> You can have a look at 
> https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html that covers most of 
> these cases.
> 
> Thanks,
> Pierre
> 
> (sorry for the earlier answer sent wrongfully to petsc-maint, please discard 
> the previous email)
> 
>> On 21 Sep 2022, at 10:03 AM, fujisan  wrote:
>> 
>> I'm trying to solve Ax=b with a sparse rectangular matrix A (of size 33x17 
>> in my test) using
>> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
>> 
>> And I always get an error saying "Incompatible vector local lengths" (see 
>> below).
>> 
>> Here is the relevant lines of my code:
>> 
>> program test
>> ...
>> ! Variable declarations
>> 
>> PetscCallA(PetscInitialize(PETSC_NULL_CHARACTER,ierr))
>> 
>> PetscCall(MatCreate(PETSC_COMM_WORLD,A,ierr))
>> PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n,ierr))
>> PetscCall(MatSetType(A,MATMPIAIJ,ierr))
>> PetscCall(MatSetFromOptions(A,ierr))
>> PetscCall(MatSetUp(A,ierr))
>> PetscCall(MatGetOwnershipRange(A,istart,iend,ierr))
>> 
>> do irow=istart,iend-1
>> ... Reading from file ...
>> PetscCall(MatSetValues(A,1,irow,nzv,col,val,ADD_VALUES,ierr))
>> ...
>> enddo
>> 
>> PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,ierr))
>> PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,ierr))
>> 
>> ! Creating vectors x and b
>> PetscCallA(MatCreateVecs(A,x,b,ierr))
>> 
>> ! Duplicating x in u.
>> PetscCallA(VecDuplicate(x,u,ierr))
>> 
>> ! u is used to calculate b
>> PetscCallA(VecSet(u,1.0,ierr))
>> 
>> PetscCallA(VecAssemblyBegin(u,ierr))
>> PetscCallA(VecAssemblyEnd(u,ierr))
>> 
>> ! Calculating Au = b
>> PetscCallA(MatMult(A,u,b,ierr)) ! A.u = b
>> 
>> PetscCallA(KSPSetType(ksp,KSPCG,ierr))
>> 
>> PetscCallA(KSPSetOperators(ksp,A,A,ierr))
>> 
>> PetscCallA(KSPSetFromOptions(ksp,ierr))
>> 
>> ! Solving Ax = b, x unknown
>> PetscCallA(KSPSolve(ksp,b,x,ierr))
>> 
>> PetscCallA(VecDestroy(x,ierr))
>> PetscCallA(VecDestroy(u,ierr))
>> PetscCallA(VecDestroy(b,ierr))
>> PetscCallA(MatDestroy(A,ierr))
>> PetscCallA(KSPDestroy(ksp,ierr))
>> 
>> call PetscFinalize(ierr)
>> end program
>> 
>> The code reads a sparse matrix from a binary file.
>> I also output the sizes of matrix A and vectors b, x, u.
>> They all seem consistent.
>> 
>> What am I doing wrong?
>> Is it possible to solve Ax=b with A rectangular?
>> 
>> Thank you in advance for your help.
>> Have a nice day.
>> 
>> Fuji
>> 
>>  Matrix size : m=  33  n=  17  cpu size:1
>>  Size of matrix A  :   33  17
>>  Size of vector b :   33
>>  Size of vector x :   17
>>  Size of vector u :   17
>> [0]PETSC ERROR: - Error Message 
>> --
>> [0]PETSC ERROR: Arguments are incompatible
>> [0]PETSC ERROR: Incompatible vector local lengths parameter # 1 local size 
>> 33 != parameter # 2 local size 17
>> [0]PETSC ERROR: See https://petsc.org/release/faq/ for trouble shooting.
>> [0]PETSC ERROR: Petsc Development GIT revision: v3.17.4-1341-g91b2b62a00  
>> GIT Date: 2022-09-15 19:26:07 +
>> [0]PETSC ERROR: ./bin/solve on a x86_64 named master by fujisan Tue Sep 20 
>> 16:56:37 2022
>> [0]PETSC ERROR: Configure options --with-petsc-arch=x86_64 --COPTFLAGS="-g 
>> -O3" --FOPTFLAGS="-g -O3" --CXXOPTFLAGS="-g -O3" --with-debugging=0 
>> --with-cc=mpiicc --with-cxx=mpiicpc --with-fc=mpiifort 
>> --with-single-library=1 --with-mpiexec=mpiexec --with-precision=double 
>> --with-fortran-interfaces=1 --with-make=1 --with-mpi=1 
>> --with-mpi-compilers=1 --download-fblaslapack=0 --download-hypre=1 
>> --download-cmake=0 --with-cmake=1 --download-metis=1 --download-parmetis=1 
>> --download-ptscotch=0 --download-suitesparse=1 --download-triangle=1 
>> --download-superlu=1 --download-superlu_dist=1 --download-scalapack=1 
>> --download-mumps=1 --download-elemental=1 --download-spai=0 
>> --download-parms=1 --download-moab=1 --download-chaco=0 --download-fftw=1 
>> --with-petsc4py=1 --download-mpi4py=1 --download-saws 
>> --download-concurrencykit=1 --download-revolve=1 --download-cams=1 
>> 

Re: [petsc-users] Problem solving Ax=b with rectangular matrix A

[fujisan]

Thank you Pierre,

I used PCNONE along with KSPLSQR and it worked.
But as for PCQR, it cannot be found. There is nothing about it in the
documentation as well.

Fuji

On Wed, Sep 21, 2022 at 12:20 PM Pierre Jolivet  wrote:

> Yes, but you need to use a KSP that handles rectangular Mat, such as
> KSPLSQR (-ksp_type lsqr).
> PCLU does not handle rectangular Pmat. The only PC that handle rectangular
> Pmat are PCQR, PCNONE.
> If you supply the normal equations as the Pmat for LSQR, then you can use
> “standard” PC.
> You can have a look at
> https://petsc.org/main/src/ksp/ksp/tutorials/ex27.c.html that covers most
> of these cases.
>
> Thanks,
> Pierre
>
> (sorry for the earlier answer sent wrongfully to petsc-maint, please
> discard the previous email)
>
> On 21 Sep 2022, at 10:03 AM, fujisan  wrote:
>
> I'm trying to solve Ax=b with a sparse rectangular matrix A (of size 33x17
> in my test) using
> options '-ksp_type stcg -pc_type lu' on 1 or 2 cpus.
>
> And I always get an error saying "Incompatible vector local lengths" (see
> below).
>
> Here is the relevant lines of my code:
>
> program test
> ...
> ! Variable declarations
>
> PetscCallA(PetscInitialize(PETSC_NULL_CHARACTER,ierr))
>
> PetscCall(MatCreate(PETSC_COMM_WORLD,A,ierr))
> PetscCall(MatSetSizes(A,PETSC_DECIDE,PETSC_DECIDE,m,n,ierr))
> PetscCall(MatSetType(A,MATMPIAIJ,ierr))
> PetscCall(MatSetFromOptions(A,ierr))
> PetscCall(MatSetUp(A,ierr))
> PetscCall(MatGetOwnershipRange(A,istart,iend,ierr))
>
> do irow=istart,iend-1
> ... Reading from file ...
> PetscCall(MatSetValues(A,1,irow,nzv,col,val,ADD_VALUES,ierr))
> ...
> enddo
>
> PetscCall(MatAssemblyBegin(A,MAT_FINAL_ASSEMBLY,ierr))
> PetscCall(MatAssemblyEnd(A,MAT_FINAL_ASSEMBLY,ierr))
>
> ! Creating vectors x and b
> PetscCallA(MatCreateVecs(A,x,b,ierr))
>
> ! Duplicating x in u.
> PetscCallA(VecDuplicate(x,u,ierr))
>
> ! u is used to calculate b
> PetscCallA(VecSet(u,1.0,ierr))
>
> PetscCallA(VecAssemblyBegin(u,ierr))
> PetscCallA(VecAssemblyEnd(u,ierr))
>
> ! Calculating Au = b
> PetscCallA(MatMult(A,u,b,ierr)) ! A.u = b
>
> PetscCallA(KSPSetType(ksp,KSPCG,ierr))
>
> PetscCallA(KSPSetOperators(ksp,A,A,ierr))
>
> PetscCallA(KSPSetFromOptions(ksp,ierr))
>
> ! Solving Ax = b, x unknown
> PetscCallA(KSPSolve(ksp,b,x,ierr))
>
> PetscCallA(VecDestroy(x,ierr))
> PetscCallA(VecDestroy(u,ierr))
> PetscCallA(VecDestroy(b,ierr))
> PetscCallA(MatDestroy(A,ierr))
> PetscCallA(KSPDestroy(ksp,ierr))
>
> call PetscFinalize(ierr)
> end program
>
> The code reads a sparse matrix from a binary file.
> I also output the sizes of matrix A and vectors b, x, u.
> They all seem consistent.
>
> What am I doing wrong?
> Is it possible to solve Ax=b with A rectangular?
>
> Thank you in advance for your help.
> Have a nice day.
>
> Fuji
>
>  Matrix size : m=  33  n=  17  cpu size:1
>  Size of matrix A  :   33  17
>  Size of vector b :   33
>  Size of vector x :   17
>  Size of vector u :   17
> [0]PETSC ERROR: - Error Message
> --
> [0]PETSC ERROR: Arguments are incompatible
> [0]PETSC ERROR: Incompatible vector local lengths parameter # 1 local size
> 33 != parameter # 2 local size 17
> [0]PETSC ERROR: See https://petsc.org/release/faq/ for trouble shooting.
> [0]PETSC ERROR: Petsc Development GIT revision: v3.17.4-1341-g91b2b62a00
> GIT Date: 2022-09-15 19:26:07 +
> [0]PETSC ERROR: ./bin/solve on a x86_64 named master by fujisan Tue Sep 20
> 16:56:37 2022
> [0]PETSC ERROR: Configure options --with-petsc-arch=x86_64 --COPTFLAGS="-g
> -O3" --FOPTFLAGS="-g -O3" --CXXOPTFLAGS="-g -O3" --with-debugging=0
> --with-cc=mpiicc --with-cxx=mpiicpc --with-fc=mpiifort
> --with-single-library=1 --with-mpiexec=mpiexec --with-precision=double
> --with-fortran-interfaces=1 --with-make=1 --with-mpi=1
> --with-mpi-compilers=1 --download-fblaslapack=0 --download-hypre=1
> --download-cmake=0 --with-cmake=1 --download-metis=1 --download-parmetis=1
> --download-ptscotch=0 --download-suitesparse=1 --download-triangle=1
> --download-superlu=1 --download-superlu_dist=1 --download-scalapack=1
> --download-mumps=1 --download-elemental=1 --download-spai=0
> --download-parms=1 --download-moab=1 --download-chaco=0 --download-fftw=1
> --with-petsc4py=1 --download-mpi4py=1 --download-saws
> --download-concurrencykit=1 --download-revolve=1 --download-cams=1
> --download-p4est=0 --with-zlib=1 --download-mfem=1 --download-glvis=0
> --with-opengl=0 --download-libpng=1 --download-libjpeg=1 --download-slepc=1
> --download-hpddm=1 --download-bamg=1 --download-mmg=0 --download-parmmg=0
> --download-htool=1 --download-egads=0 --download-opencascade=0
> PETSC_ARCH=x86_64
> [0]PETSC ERROR: #1 VecCopy() at
> 

Re: [petsc-users] Solve Linear System with Field Split Preconditioner

[Jed Brown]

This is the joy of factorization field-split methods. The actual Schur 
complement is dense, so we represent it implicitly. A common strategy is to 
assemble the mass matrix and drop it in the 11 block of the Pmat. You can check 
out some examples in the repository for incompressible flow (Stokes problems). 
The LSC (least squares commutator) is another option. You'll likely find that 
lumping diag(A00)^{-1} works poorly because the resulting operator behaves like 
a Laplacian rather than like a mass matrix.

晓峰 何  writes:

> If assigned a preconditioner to A11 with this cmd options:
>
>-fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu 
> -fieldsplit_1_ksp_type gmres -fieldsplit_1_pc_type ilu
>
> Then I got this error:
>
> "Could not locate a solver type for factorization type ILU and matrix type 
> schurcomplement"
>
> How could I specify a preconditioner for A11?
>
> BR,
> Xiaofeng
>
>
> On Sep 26, 2022, at 11:02, 晓峰 何 
> mailto:tlan...@hotmail.com>> wrote:
>
> -fieldsplit_0_ksp_type gmres -fieldsplit_0_pc_type ilu -fieldsplit_1_ksp_type 
> gmres -fieldsplit_1_pc_type none