[petsc-users] Regarding printing to standard output. and possible mistake in the code comments in PetscBinaryWrite.m
Satish Balay
balay at mcs.anl.gov
Mon Jan 17 17:25:39 CST 2011
Looks like you've installed petsc with --download-mpich - so you should
use the corresponding mpiexec [its in PETSC_DIR/PETSC_ARCH/bin/]
Since you already have 2 installs of MPI - you could have used one of
them for PETSc install [by specifying the corresponding mpicc,mpif90
to PETSc configure -] instead of --download-mpich.
Satish
On Mon, 17 Jan 2011, Gaurish Telang wrote:
> This is what I get on running mpiexec -n 2 ./ex23 -info
>
> Also, using mpirun in place of mpiexec and using the -info option I get the
> exact same output you see below.
>
> As far as the MPI implmentation I am using, I have OpenMPI and MPICH
> installed on my laptop.
>
> While installing PETSc there were some external packages required. In the
> external packages folder I can see the following softwares:
>
> fblaslapack-3.1.1 mpich2-1.0.8 ParMetis-dev-p3 SuperLU_DIST_2.4-hg-v2
>
> Possibly it is this mpich2 that should be used??
> Please let me know what I should do. I am quite new to PETSc.
>
> gaurish108 at gaurish108-laptop:~/Desktop/ResearchMeetings/SUPERPETS/petsc-3.1-p5/src/ksp/ksp/examples/tutorials$
> mpiexec -n 2 ./ex23 -info
> [0] PetscInitialize(): PETSc successfully started: number of processors = 1
> [0] PetscGetHostName(): Rejecting domainname, likely is NIS
> gaurish108-laptop.(none)
> [0] PetscInitialize(): Running on machine: gaurish108-laptop
> [0] PetscCommDuplicate(): Duplicating a communicator 1140850688 -2080374784
> max tags = 2147483647
> [0] PetscCommDuplicate(): returning tag 2147483647
> [0] PetscCommDuplicate(): returning tag 2147483646
> [0] PetscCommDuplicate(): returning tag 2147483645
> [0] PetscInitialize(): PETSc successfully started: number of processors = 1
> [0] PetscGetHostName(): Rejecting domainname, likely is NIS
> gaurish108-laptop.(none)
> [0] PetscInitialize(): Running on machine: gaurish108-laptop
> [0] PetscCommDuplicate(): Duplicating a communicator 1140850688 -2080374784
> max tags = 2147483647
> [0] PetscCommDuplicate(): returning tag 2147483647
> [0] PetscCommDuplicate(): returning tag 2147483646
> [0] PetscCommDuplicate(): returning tag 2147483645
> [0] PetscCommDuplicate(): Using internal PETSc communicator 1140850688
> -2080374784
> [0] PetscCommDuplicate(): returning tag 2147483644
> [0] MatSetUpPreallocation(): Warning not preallocating matrix storage
> [0] MatAssemblyEnd_SeqAIJ(): Matrix size: 10 X 10; storage space: 22
> unneeded,28 used
> [0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
> [0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 3
> [0] Mat_CheckInode(): Found 10 nodes out of 10 rows. Not using Inode
> routines
> [0] PetscCommDuplicate(): Using internal PETSc communicator 1140850688
> -2080374784
> [0] PetscCommDuplicate(): returning tag 2147483643
> [0] PetscCommDuplicate(): returning tag 2147483642
> [0] PetscCommDuplicate(): returning tag 2147483641
> [0] PetscCommDuplicate(): returning tag 2147483640
> [0] PetscCommDuplicate(): returning tag 2147483639
> [0] PetscCommDuplicate(): returning tag 2147483638
> [0] PetscCommDuplicate(): returning tag 2147483637
> [0] PCSetUp(): Setting up new PC
> [0] PetscCommDuplicate(): returning tag 2147483636
> [0] PetscCommDuplicate(): returning tag 2147483635
> [0] PetscCommDuplicate(): returning tag 2147483634
> [0] PetscCommDuplicate(): returning tag 2147483633
> [0] PetscCommDuplicate(): returning tag 2147483632
> [0] PetscCommDuplicate(): returning tag 2147483631
> [0] PetscCommDuplicate(): returning tag 2147483630
> [0] PetscCommDuplicate(): returning tag 2147483629
> [0] PetscCommDuplicate(): returning tag 2147483628
> [0] PetscCommDuplicate(): returning tag 2147483627
> [0] PetscCommDuplicate(): returning tag 2147483626
> [0] KSPDefaultConverged(): Linear solver has converged. Residual norm
> 4.50879e-16 is less than relative tolerance 1e-07 times initial right hand
> side norm 0.707107 at iteration 5
> [0] PetscCommDuplicate(): Using internal PETSc communicator 1140850688
> -2080374784
> [0] PetscCommDuplicate(): returning tag 2147483625
> KSP Object:
> type: gmres
> GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> Orthogonalization with no iterative refinement
> GMRES: happy breakdown tolerance 1e-30
> maximum iterations=10000, initial guess is zero
> tolerances: relative=1e-07, absolute=1e-50, divergence=10000
> left preconditioning
> using PRECONDITIONED norm type for convergence test
> PC Object:
> type: jacobi
> linear system matrix = precond matrix:
> Matrix Object:
> type=seqaij, rows=10, cols=10
> total: nonzeros=28, allocated nonzeros=50
> not using I-node routines
> Norm of error < 1.e-12, Iterations 5
> [0] PetscFinalize(): PetscFinalize() called
> [0] PetscCommDuplicate(): returning tag 2147483624
> [0] Petsc_DelViewer(): Deleting viewer data in an MPI_Comm -2080374784
> [0] Petsc_DelComm(): Deleting PETSc communicator imbedded in a user MPI_Comm
> 1140850688
> [0] PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374784
> [0] Petsc_DelCounter(): Deleting counter data in an MPI_Comm -2080374784
> [0] Petsc_DelComm(): Deleting PETSc communicator imbedded in a user MPI_Comm
> -2080374784
> [0] Petsc_DelViewer(): Deleting viewer data in an MPI_Comm -2080374784
> [0] PetscCommDuplicate(): Using internal PETSc communicator 1140850688
> -2080374784
> [0] PetscCommDuplicate(): returning tag 2147483644
> [0] MatSetUpPreallocation(): Warning not preallocating matrix storage
> [0] MatAssemblyEnd_SeqAIJ(): Matrix size: 10 X 10; storage space: 22
> unneeded,28 used
> [0] MatAssemblyEnd_SeqAIJ(): Number of mallocs during MatSetValues() is 0
> [0] MatAssemblyEnd_SeqAIJ(): Maximum nonzeros in any row is 3
> [0] Mat_CheckInode(): Found 10 nodes out of 10 rows. Not using Inode
> routines
> [0] PetscCommDuplicate(): Using internal PETSc communicator 1140850688
> -2080374784
> [0] PetscCommDuplicate(): returning tag 2147483643
> [0] PetscCommDuplicate(): returning tag 2147483642
> [0] PetscCommDuplicate(): returning tag 2147483641
> [0] PetscCommDuplicate(): returning tag 2147483640
> [0] PetscCommDuplicate(): returning tag 2147483639
> [0] PetscCommDuplicate(): returning tag 2147483638
> [0] PetscCommDuplicate(): returning tag 2147483637
> [0] PCSetUp(): Setting up new PC
> [0] PetscCommDuplicate(): returning tag 2147483636
> [0] PetscCommDuplicate(): returning tag 2147483635
> [0] PetscCommDuplicate(): returning tag 2147483634
> [0] PetscCommDuplicate(): returning tag 2147483633
> [0] PetscCommDuplicate(): returning tag 2147483632
> [0] PetscCommDuplicate(): returning tag 2147483631
> [0] PetscCommDuplicate(): returning tag 2147483630
> [0] PetscCommDuplicate(): returning tag 2147483629
> [0] PetscCommDuplicate(): returning tag 2147483628
> [0] PetscCommDuplicate(): returning tag 2147483627
> [0] PetscCommDuplicate(): returning tag 2147483626
> [0] KSPDefaultConverged(): Linear solver has converged. Residual norm
> 4.50879e-16 is less than relative tolerance 1e-07 times initial right hand
> side norm 0.707107 at iteration 5
> [0] PetscCommDuplicate(): Using internal PETSc communicator 1140850688
> -2080374784
> [0] PetscCommDuplicate(): returning tag 2147483625
> KSP Object:
> type: gmres
> GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> Orthogonalization with no iterative refinement
> GMRES: happy breakdown tolerance 1e-30
> maximum iterations=10000, initial guess is zero
> tolerances: relative=1e-07, absolute=1e-50, divergence=10000
> left preconditioning
> using PRECONDITIONED norm type for convergence test
> PC Object:
> type: jacobi
> linear system matrix = precond matrix:
> Matrix Object:
> type=seqaij, rows=10, cols=10
> total: nonzeros=28, allocated nonzeros=50
> not using I-node routines
> Norm of error < 1.e-12, Iterations 5
> [0] PetscFinalize(): PetscFinalize() called
> [0] PetscCommDuplicate(): returning tag 2147483624
> [0] Petsc_DelViewer(): Deleting viewer data in an MPI_Comm -2080374784
> [0] Petsc_DelComm(): Deleting PETSc communicator imbedded in a user MPI_Comm
> 1140850688
> [0] PetscCommDestroy(): Deleting PETSc MPI_Comm -2080374784
> [0] Petsc_DelCounter(): Deleting counter data in an MPI_Comm -2080374784
> [0] Petsc_DelComm(): Deleting PETSc communicator imbedded in a user MPI_Comm
> -2080374784
> [0] Petsc_DelViewer(): Deleting viewer data in an MPI_Comm -2080374784
> gaurish108 at gaurish108-laptop:~/Desktop/ResearchMeetings/SUPERPETS/petsc-3.1-p5/src/ksp/ksp/examples/tutorials$
>
>
> On Mon, Jan 17, 2011 at 5:46 PM, Gaurish Telang <gaurish108 at gmail.com>wrote:
>
> > Hi.
> >
> > I had two questions
> >
> > (1)
> >
> > I was curious to know why the following happens with the PETSc standard
> > output. Having created the executable 'test' when I try to run it with
> > mpiexec -n 2 ./test
> > the same output is printed to the terminal twice. If I use 3 processors,
> > then the same output is printed thrice.
> >
> > In short the number of processors = number of times the output from PETSc
> > is printed. Could this be a mistake with my PETSc installation???
> >
> > For example, consider the code in src/ksp/ksp/examples/tutorials/ex23.c
> > After creating ex23 the executable and running it with two processors gives
> > the following terminal output:
> >
> > gaurish108 at gaurish108-laptop:~/Desktop/ResearchMeetings/SUPERPETS/petsc-3.1-p5/src/ksp/ksp/examples/tutorials$
> > mpiexec -n 1 ./ex23
> > KSP Object:
> > type: gmres
> > GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> > Orthogonalization with no iterative refinement
> > GMRES: happy breakdown tolerance 1e-30
> > maximum iterations=10000, initial guess is zero
> > tolerances: relative=1e-07, absolute=1e-50, divergence=10000
> > left preconditioning
> > using PRECONDITIONED norm type for convergence test
> > PC Object:
> > type: jacobi
> > linear system matrix = precond matrix:
> > Matrix Object:
> > type=seqaij, rows=10, cols=10
> > total: nonzeros=28, allocated nonzeros=50
> > not using I-node routines
> > Norm of error < 1.e-12, Iterations 5
> > gaurish108 at gaurish108-laptop:~/Desktop/ResearchMeetings/SUPERPETS/petsc-3.1-p5/src/ksp/ksp/examples/tutorials$
> > mpiexec -n 2 ./ex23
> > KSP Object:
> > type: gmres
> > GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> > Orthogonalization with no iterative refinement
> > GMRES: happy breakdown tolerance 1e-30
> > maximum iterations=10000, initial guess is zero
> > tolerances: relative=1e-07, absolute=1e-50, divergence=10000
> > left preconditioning
> > using PRECONDITIONED norm type for convergence test
> > PC Object:
> > type: jacobi
> > linear system matrix = precond matrix:
> > Matrix Object:
> > type=seqaij, rows=10, cols=10
> > total: nonzeros=28, allocated nonzeros=50
> > not using I-node routines
> > Norm of error < 1.e-12, Iterations 5
> > KSP Object:
> > type: gmres
> > GMRES: restart=30, using Classical (unmodified) Gram-Schmidt
> > Orthogonalization with no iterative refinement
> > GMRES: happy breakdown tolerance 1e-30
> > maximum iterations=10000, initial guess is zero
> > tolerances: relative=1e-07, absolute=1e-50, divergence=10000
> > left preconditioning
> > using PRECONDITIONED norm type for convergence test
> > PC Object:
> > type: jacobi
> > linear system matrix = precond matrix:
> > Matrix Object:
> > type=seqaij, rows=10, cols=10
> > total: nonzeros=28, allocated nonzeros=50
> > not using I-node routines
> > Norm of error < 1.e-12, Iterations 5
> > gaurish108 at gaurish108-laptop:~/Desktop/ResearchMeetings/SUPERPETS/petsc-3.1-p5/src/ksp/ksp/examples/tutorials$
> >
> >
> >
> >
> > (2)
> >
> > Also I was told yesterday on the PETSC users mailing list that the MATLAB m
> > file PetscBinaryWrite.m converts a sparse matrix in MATLAB into Petsc Binary
> > format.
> > The following are the comments in the code near the heading saying that
> > it works only for square sparse matrices . But it seems to be working quite
> > well for rectangular sparse MATLAB matrices also.
> > I have tested this in conjunction with PetscBinaryRead.m also, which reads
> > in a Petsc binary file into MATLAB as a sparse matrix.
> >
> > Is there something I might have missed or some error that I might be
> > making???
> >
> > Comments in PetscBinaryWrite.m
> > "-================================================
> > % Writes in PETSc binary file sparse matrices and vectors
> > % if the array is multidimensional and dense it is saved
> > % as a one dimensional array
> > %
> > % Only works for square sparse matrices
> > %:
> > ..
> > ..
> > ..
> > ..
> > ..
> > ..
> > .
> > .
> > .
> >
> >
> >
> >
> >
>
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