On Mon, Sep 19, 2016 at 9:45 PM, Fande Kong <fdkong...@gmail.com> wrote:
> Placing PCReset(PC pc) before the second kspsolve might works.
>
> Fande Kong,
>
> On Mon, Sep 19, 2016 at 7:38 PM, murat keçeli <kec...@gmail.com> wrote:
>
>> Another guess: maybe you also need KSPSetUp(ksp); before the second
>> KSPSolve(ksp,b,x);.
>>
>> Murat Keceli
>>
>
Thanks for the suggestions. I just tried these, and they didn't work either
unfortunately.
David
>
>>
>> On Mon, Sep 19, 2016 at 8:33 PM, David Knezevic <
>> david.kneze...@akselos.com> wrote:
>>
>>> On Mon, Sep 19, 2016 at 7:26 PM, Dave May <dave.mayhe...@gmail.com>
>>> wrote:
>>>
>>>>
>>>>
>>>> On 19 September 2016 at 21:05, David Knezevic <
>>>> david.kneze...@akselos.com> wrote:
>>>>
>>>>> When I use MUMPS via PETSc, one issue is that it can sometimes fail
>>>>> with MUMPS error -9, which means that MUMPS didn't allocate a big enough
>>>>> workspace. This can typically be fixed by increasing MUMPS icntl 14, e.g.
>>>>> via the command line option -mat_mumps_icntl_14.
>>>>>
>>>>> However, instead of having to run several times with different command
>>>>> line options, I'd like to be able to automatically increment icntl 14
>>>>> value
>>>>> in a loop until the solve succeeds.
>>>>>
>>>>> I have a saved matrix which fails when I use it for a solve with MUMPS
>>>>> with 4 MPI processes and the default ictnl values, so I'm using this to
>>>>> check that I can achieve the automatic icntl 14 update, as described
>>>>> above.
>>>>> (The matrix is 14MB so I haven't attached it here, but I'd be happy to
>>>>> send
>>>>> it to anyone else who wants to try this test case out.)
>>>>>
>>>>> I've pasted some test code below which provides a simple test of this
>>>>> idea using two solves. The first solve uses the default value of icntl 14,
>>>>> which fails, and then we update icntl 14 to 30 and solve again. The second
>>>>> solve should succeed since icntl 14 of 30 is sufficient for MUMPS to
>>>>> succeed in this case, but for some reason the second solve still fails.
>>>>>
>>>>> Below I've also pasted the output from -ksp_view, and you can see that
>>>>> ictnl 14 is being updated correctly (see the ICNTL(14) lines in the
>>>>> output), so it's not clear to me why the second solve fails. It seems like
>>>>> MUMPS is ignoring the update to the ictnl value?
>>>>>
>>>>
>>>> I believe this parameter is utilized during the numerical factorization
>>>> phase.
>>>> In your code, the operator hasn't changed, however you haven't
>>>> signalled to the KSP that you want to re-perform the numerical
>>>> factorization.
>>>> You can do this by calling KSPSetOperators() before your second solve.
>>>> I think if you do this (please try it), the factorization will be
>>>> performed again and the new value of icntl will have an effect.
>>>>
>>>> Note this is a wild stab in the dark - I haven't dug through the
>>>> petsc-mumps code in detail...
>>>>
>>>
>>> That sounds like a plausible guess to me, but unfortunately it didn't
>>> work. I added KSPSetOperators(ksp,A,A); before the second solve and I
>>> got the same behavior as before.
>>>
>>> Thanks,
>>> David
>>>
>>>
>>>
>>>
>>>
>>>> ------------------------------------------------------------
>>>>> -----------------------------------------
>>>>> Test code:
>>>>>
>>>>> Mat A;
>>>>> MatCreate(PETSC_COMM_WORLD,&A);
>>>>> MatSetType(A,MATMPIAIJ);
>>>>>
>>>>> PetscViewer petsc_viewer;
>>>>> PetscViewerBinaryOpen( PETSC_COMM_WORLD,
>>>>> "matrix.dat",
>>>>> FILE_MODE_READ,
>>>>> &petsc_viewer);
>>>>> MatLoad(A, petsc_viewer);
>>>>> PetscViewerDestroy(&petsc_viewer);
>>>>>
>>>>> PetscInt m, n;
>>>>> MatGetSize(A, &m, &n);
>>>>>
>>>>> Vec x;
>>>>> VecCreate(PETSC_COMM_WORLD,&x);
>>>>> VecSetSizes(x,PETSC_DECIDE,m);
>>>>> VecSetFromOptions(x);
>>>>> VecSet(x,1.0);
>>>>>
>>>>> Vec b;
>>>>> VecDuplicate(x,&b);
>>>>>
>>>>> KSP ksp;
>>>>> PC pc;
>>>>>
>>>>> KSPCreate(PETSC_COMM_WORLD,&ksp);
>>>>> KSPSetOperators(ksp,A,A);
>>>>>
>>>>> KSPSetType(ksp,KSPPREONLY);
>>>>> KSPGetPC(ksp,&pc);
>>>>>
>>>>> PCSetType(pc,PCCHOLESKY);
>>>>>
>>>>> PCFactorSetMatSolverPackage(pc,MATSOLVERMUMPS);
>>>>> PCFactorSetUpMatSolverPackage(pc);
>>>>>
>>>>> KSPSetFromOptions(ksp);
>>>>> KSPSetUp(ksp);
>>>>>
>>>>> KSPSolve(ksp,b,x);
>>>>>
>>>>> {
>>>>> KSPConvergedReason reason;
>>>>> KSPGetConvergedReason(ksp, &reason);
>>>>> std::cout << "converged reason: " << reason << std::endl;
>>>>> }
>>>>>
>>>>> Mat F;
>>>>> PCFactorGetMatrix(pc,&F);
>>>>> MatMumpsSetIcntl(F,14,30);
>>>>>
>>>>> KSPSolve(ksp,b,x);
>>>>>
>>>>> {
>>>>> KSPConvergedReason reason;
>>>>> KSPGetConvergedReason(ksp, &reason);
>>>>> std::cout << "converged reason: " << reason << std::endl;
>>>>> }
>>>>>
>>>>> ------------------------------------------------------------
>>>>> -----------------------------------------
>>>>> -ksp_view output (ICNTL(14) changes from 20 to 30, but we get
>>>>> "converged reason: -11" for both solves)
>>>>>
>>>>> KSP Object: 4 MPI processes
>>>>> type: preonly
>>>>> maximum iterations=10000, initial guess is zero
>>>>> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
>>>>> left preconditioning
>>>>> using NONE norm type for convergence test
>>>>> PC Object: 4 MPI processes
>>>>> type: cholesky
>>>>> Cholesky: out-of-place factorization
>>>>> tolerance for zero pivot 2.22045e-14
>>>>> matrix ordering: natural
>>>>> factor fill ratio given 0., needed 0.
>>>>> Factored matrix follows:
>>>>> Mat Object: 4 MPI processes
>>>>> type: mpiaij
>>>>> rows=22878, cols=22878
>>>>> package used to perform factorization: mumps
>>>>> total: nonzeros=3361617, allocated nonzeros=3361617
>>>>> total number of mallocs used during MatSetValues calls =0
>>>>> MUMPS run parameters:
>>>>> SYM (matrix type): 2
>>>>> PAR (host participation): 1
>>>>> ICNTL(1) (output for error): 6
>>>>> ICNTL(2) (output of diagnostic msg): 0
>>>>> ICNTL(3) (output for global info): 0
>>>>> ICNTL(4) (level of printing): 0
>>>>> ICNTL(5) (input mat struct): 0
>>>>> ICNTL(6) (matrix prescaling): 7
>>>>> ICNTL(7) (sequentia matrix ordering):7
>>>>> ICNTL(8) (scalling strategy): 77
>>>>> ICNTL(10) (max num of refinements): 0
>>>>> ICNTL(11) (error analysis): 0
>>>>> ICNTL(12) (efficiency control):
>>>>> 0
>>>>> ICNTL(13) (efficiency control):
>>>>> 0
>>>>> ICNTL(14) (percentage of estimated workspace increase):
>>>>> 20
>>>>> ICNTL(18) (input mat struct):
>>>>> 3
>>>>> ICNTL(19) (Shur complement info):
>>>>> 0
>>>>> ICNTL(20) (rhs sparse pattern):
>>>>> 0
>>>>> ICNTL(21) (solution struct):
>>>>> 1
>>>>> ICNTL(22) (in-core/out-of-core facility):
>>>>> 0
>>>>> ICNTL(23) (max size of memory can be allocated
>>>>> locally):0
>>>>> ICNTL(24) (detection of null pivot rows):
>>>>> 0
>>>>> ICNTL(25) (computation of a null space basis):
>>>>> 0
>>>>> ICNTL(26) (Schur options for rhs or solution):
>>>>> 0
>>>>> ICNTL(27) (experimental parameter):
>>>>> -24
>>>>> ICNTL(28) (use parallel or sequential ordering):
>>>>> 1
>>>>> ICNTL(29) (parallel ordering):
>>>>> 0
>>>>> ICNTL(30) (user-specified set of entries in inv(A)):
>>>>> 0
>>>>> ICNTL(31) (factors is discarded in the solve phase):
>>>>> 0
>>>>> ICNTL(33) (compute determinant):
>>>>> 0
>>>>> CNTL(1) (relative pivoting threshold): 0.01
>>>>> CNTL(2) (stopping criterion of refinement): 1.49012e-08
>>>>> CNTL(3) (absolute pivoting threshold): 0.
>>>>> CNTL(4) (value of static pivoting): -1.
>>>>> CNTL(5) (fixation for null pivots): 0.
>>>>> RINFO(1) (local estimated flops for the elimination
>>>>> after analysis):
>>>>> [0] 1.84947e+08
>>>>> [1] 2.42065e+08
>>>>> [2] 2.53044e+08
>>>>> [3] 2.18441e+08
>>>>> RINFO(2) (local estimated flops for the assembly after
>>>>> factorization):
>>>>> [0] 945938.
>>>>> [1] 906795.
>>>>> [2] 897815.
>>>>> [3] 998840.
>>>>> RINFO(3) (local estimated flops for the elimination
>>>>> after factorization):
>>>>> [0] 1.59835e+08
>>>>> [1] 1.50867e+08
>>>>> [2] 2.27932e+08
>>>>> [3] 1.52037e+08
>>>>> INFO(15) (estimated size of (in MB) MUMPS internal data
>>>>> for running numerical factorization):
>>>>> [0] 36
>>>>> [1] 37
>>>>> [2] 38
>>>>> [3] 39
>>>>> INFO(16) (size of (in MB) MUMPS internal data used
>>>>> during numerical factorization):
>>>>> [0] 36
>>>>> [1] 37
>>>>> [2] 38
>>>>> [3] 39
>>>>> INFO(23) (num of pivots eliminated on this processor
>>>>> after factorization):
>>>>> [0] 6450
>>>>> [1] 5442
>>>>> [2] 4386
>>>>> [3] 5526
>>>>> RINFOG(1) (global estimated flops for the elimination
>>>>> after analysis): 8.98497e+08
>>>>> RINFOG(2) (global estimated flops for the assembly after
>>>>> factorization): 3.74939e+06
>>>>> RINFOG(3) (global estimated flops for the elimination
>>>>> after factorization): 6.9067e+08
>>>>> (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant):
>>>>> (0.,0.)*(2^0)
>>>>> INFOG(3) (estimated real workspace for factors on all
>>>>> processors after analysis): 4082184
>>>>> INFOG(4) (estimated integer workspace for factors on all
>>>>> processors after analysis): 231846
>>>>> INFOG(5) (estimated maximum front size in the complete
>>>>> tree): 678
>>>>> INFOG(6) (number of nodes in the complete tree): 1380
>>>>> INFOG(7) (ordering option effectively use after
>>>>> analysis): 5
>>>>> INFOG(8) (structural symmetry in percent of the permuted
>>>>> matrix after analysis): 100
>>>>> INFOG(9) (total real/complex workspace to store the
>>>>> matrix factors after factorization): 3521904
>>>>> INFOG(10) (total integer space store the matrix factors
>>>>> after factorization): 229416
>>>>> INFOG(11) (order of largest frontal matrix after
>>>>> factorization): 678
>>>>> INFOG(12) (number of off-diagonal pivots): 0
>>>>> INFOG(13) (number of delayed pivots after
>>>>> factorization): 0
>>>>> INFOG(14) (number of memory compress after
>>>>> factorization): 0
>>>>> INFOG(15) (number of steps of iterative refinement after
>>>>> solution): 0
>>>>> INFOG(16) (estimated size (in MB) of all MUMPS internal
>>>>> data for factorization after analysis: value on the most memory consuming
>>>>> processor): 39
>>>>> INFOG(17) (estimated size of all MUMPS internal data for
>>>>> factorization after analysis: sum over all processors): 150
>>>>> INFOG(18) (size of all MUMPS internal data allocated
>>>>> during factorization: value on the most memory consuming processor): 39
>>>>> INFOG(19) (size of all MUMPS internal data allocated
>>>>> during factorization: sum over all processors): 150
>>>>> INFOG(20) (estimated number of entries in the factors):
>>>>> 3361617
>>>>> INFOG(21) (size in MB of memory effectively used during
>>>>> factorization - value on the most memory consuming processor): 35
>>>>> INFOG(22) (size in MB of memory effectively used during
>>>>> factorization - sum over all processors): 136
>>>>> INFOG(23) (after analysis: value of ICNTL(6) effectively
>>>>> used): 0
>>>>> INFOG(24) (after analysis: value of ICNTL(12)
>>>>> effectively used): 1
>>>>> INFOG(25) (after factorization: number of pivots
>>>>> modified by static pivoting): 0
>>>>> INFOG(28) (after factorization: number of null pivots
>>>>> encountered): 0
>>>>> INFOG(29) (after factorization: effective number of
>>>>> entries in the factors (sum over all processors)): 2931438
>>>>> INFOG(30, 31) (after solution: size in Mbytes of memory
>>>>> used during solution phase): 0, 0
>>>>> INFOG(32) (after analysis: type of analysis done): 1
>>>>> INFOG(33) (value used for ICNTL(8)): 7
>>>>> INFOG(34) (exponent of the determinant if determinant is
>>>>> requested): 0
>>>>> linear system matrix = precond matrix:
>>>>> Mat Object: 4 MPI processes
>>>>> type: mpiaij
>>>>> rows=22878, cols=22878
>>>>> total: nonzeros=1219140, allocated nonzeros=1219140
>>>>> total number of mallocs used during MatSetValues calls =0
>>>>> using I-node (on process 0) routines: found 1889 nodes, limit
>>>>> used is 5
>>>>> converged reason: -11
>>>>> KSP Object: 4 MPI processes
>>>>> type: preonly
>>>>> maximum iterations=10000, initial guess is zero
>>>>> tolerances: relative=1e-05, absolute=1e-50, divergence=10000.
>>>>> left preconditioning
>>>>> using NONE norm type for convergence test
>>>>> PC Object: 4 MPI processes
>>>>> type: cholesky
>>>>> Cholesky: out-of-place factorization
>>>>> tolerance for zero pivot 2.22045e-14
>>>>> matrix ordering: natural
>>>>> factor fill ratio given 0., needed 0.
>>>>> Factored matrix follows:
>>>>> Mat Object: 4 MPI processes
>>>>> type: mpiaij
>>>>> rows=22878, cols=22878
>>>>> package used to perform factorization: mumps
>>>>> total: nonzeros=3361617, allocated nonzeros=3361617
>>>>> total number of mallocs used during MatSetValues calls =0
>>>>> MUMPS run parameters:
>>>>> SYM (matrix type): 2
>>>>> PAR (host participation): 1
>>>>> ICNTL(1) (output for error): 6
>>>>> ICNTL(2) (output of diagnostic msg): 0
>>>>> ICNTL(3) (output for global info): 0
>>>>> ICNTL(4) (level of printing): 0
>>>>> ICNTL(5) (input mat struct): 0
>>>>> ICNTL(6) (matrix prescaling): 7
>>>>> ICNTL(7) (sequentia matrix ordering):7
>>>>> ICNTL(8) (scalling strategy): 77
>>>>> ICNTL(10) (max num of refinements): 0
>>>>> ICNTL(11) (error analysis): 0
>>>>> ICNTL(12) (efficiency control):
>>>>> 0
>>>>> ICNTL(13) (efficiency control):
>>>>> 0
>>>>> ICNTL(14) (percentage of estimated workspace increase):
>>>>> 30
>>>>> ICNTL(18) (input mat struct):
>>>>> 3
>>>>> ICNTL(19) (Shur complement info):
>>>>> 0
>>>>> ICNTL(20) (rhs sparse pattern):
>>>>> 0
>>>>> ICNTL(21) (solution struct):
>>>>> 1
>>>>> ICNTL(22) (in-core/out-of-core facility):
>>>>> 0
>>>>> ICNTL(23) (max size of memory can be allocated
>>>>> locally):0
>>>>> ICNTL(24) (detection of null pivot rows):
>>>>> 0
>>>>> ICNTL(25) (computation of a null space basis):
>>>>> 0
>>>>> ICNTL(26) (Schur options for rhs or solution):
>>>>> 0
>>>>> ICNTL(27) (experimental parameter):
>>>>> -24
>>>>> ICNTL(28) (use parallel or sequential ordering):
>>>>> 1
>>>>> ICNTL(29) (parallel ordering):
>>>>> 0
>>>>> ICNTL(30) (user-specified set of entries in inv(A)):
>>>>> 0
>>>>> ICNTL(31) (factors is discarded in the solve phase):
>>>>> 0
>>>>> ICNTL(33) (compute determinant):
>>>>> 0
>>>>> CNTL(1) (relative pivoting threshold): 0.01
>>>>> CNTL(2) (stopping criterion of refinement): 1.49012e-08
>>>>> CNTL(3) (absolute pivoting threshold): 0.
>>>>> CNTL(4) (value of static pivoting): -1.
>>>>> CNTL(5) (fixation for null pivots): 0.
>>>>> RINFO(1) (local estimated flops for the elimination
>>>>> after analysis):
>>>>> [0] 1.84947e+08
>>>>> [1] 2.42065e+08
>>>>> [2] 2.53044e+08
>>>>> [3] 2.18441e+08
>>>>> RINFO(2) (local estimated flops for the assembly after
>>>>> factorization):
>>>>> [0] 945938.
>>>>> [1] 906795.
>>>>> [2] 897815.
>>>>> [3] 998840.
>>>>> RINFO(3) (local estimated flops for the elimination
>>>>> after factorization):
>>>>> [0] 1.59835e+08
>>>>> [1] 1.50867e+08
>>>>> [2] 2.27932e+08
>>>>> [3] 1.52037e+08
>>>>> INFO(15) (estimated size of (in MB) MUMPS internal data
>>>>> for running numerical factorization):
>>>>> [0] 36
>>>>> [1] 37
>>>>> [2] 38
>>>>> [3] 39
>>>>> INFO(16) (size of (in MB) MUMPS internal data used
>>>>> during numerical factorization):
>>>>> [0] 36
>>>>> [1] 37
>>>>> [2] 38
>>>>> [3] 39
>>>>> INFO(23) (num of pivots eliminated on this processor
>>>>> after factorization):
>>>>> [0] 6450
>>>>> [1] 5442
>>>>> [2] 4386
>>>>> [3] 5526
>>>>> RINFOG(1) (global estimated flops for the elimination
>>>>> after analysis): 8.98497e+08
>>>>> RINFOG(2) (global estimated flops for the assembly after
>>>>> factorization): 3.74939e+06
>>>>> RINFOG(3) (global estimated flops for the elimination
>>>>> after factorization): 6.9067e+08
>>>>> (RINFOG(12) RINFOG(13))*2^INFOG(34) (determinant):
>>>>> (0.,0.)*(2^0)
>>>>> INFOG(3) (estimated real workspace for factors on all
>>>>> processors after analysis): 4082184
>>>>> INFOG(4) (estimated integer workspace for factors on all
>>>>> processors after analysis): 231846
>>>>> INFOG(5) (estimated maximum front size in the complete
>>>>> tree): 678
>>>>> INFOG(6) (number of nodes in the complete tree): 1380
>>>>> INFOG(7) (ordering option effectively use after
>>>>> analysis): 5
>>>>> INFOG(8) (structural symmetry in percent of the permuted
>>>>> matrix after analysis): 100
>>>>> INFOG(9) (total real/complex workspace to store the
>>>>> matrix factors after factorization): 3521904
>>>>> INFOG(10) (total integer space store the matrix factors
>>>>> after factorization): 229416
>>>>> INFOG(11) (order of largest frontal matrix after
>>>>> factorization): 678
>>>>> INFOG(12) (number of off-diagonal pivots): 0
>>>>> INFOG(13) (number of delayed pivots after
>>>>> factorization): 0
>>>>> INFOG(14) (number of memory compress after
>>>>> factorization): 0
>>>>> INFOG(15) (number of steps of iterative refinement after
>>>>> solution): 0
>>>>> INFOG(16) (estimated size (in MB) of all MUMPS internal
>>>>> data for factorization after analysis: value on the most memory consuming
>>>>> processor): 39
>>>>> INFOG(17) (estimated size of all MUMPS internal data for
>>>>> factorization after analysis: sum over all processors): 150
>>>>> INFOG(18) (size of all MUMPS internal data allocated
>>>>> during factorization: value on the most memory consuming processor): 39
>>>>> INFOG(19) (size of all MUMPS internal data allocated
>>>>> during factorization: sum over all processors): 150
>>>>> INFOG(20) (estimated number of entries in the factors):
>>>>> 3361617
>>>>> INFOG(21) (size in MB of memory effectively used during
>>>>> factorization - value on the most memory consuming processor): 35
>>>>> INFOG(22) (size in MB of memory effectively used during
>>>>> factorization - sum over all processors): 136
>>>>> INFOG(23) (after analysis: value of ICNTL(6) effectively
>>>>> used): 0
>>>>> INFOG(24) (after analysis: value of ICNTL(12)
>>>>> effectively used): 1
>>>>> INFOG(25) (after factorization: number of pivots
>>>>> modified by static pivoting): 0
>>>>> INFOG(28) (after factorization: number of null pivots
>>>>> encountered): 0
>>>>> INFOG(29) (after factorization: effective number of
>>>>> entries in the factors (sum over all processors)): 2931438
>>>>> INFOG(30, 31) (after solution: size in Mbytes of memory
>>>>> used during solution phase): 0, 0
>>>>> INFOG(32) (after analysis: type of analysis done): 1
>>>>> INFOG(33) (value used for ICNTL(8)): 7
>>>>> INFOG(34) (exponent of the determinant if determinant is
>>>>> requested): 0
>>>>> linear system matrix = precond matrix:
>>>>> Mat Object: 4 MPI processes
>>>>> type: mpiaij
>>>>> rows=22878, cols=22878
>>>>> total: nonzeros=1219140, allocated nonzeros=1219140
>>>>> total number of mallocs used during MatSetValues calls =0
>>>>> using I-node (on process 0) routines: found 1889 nodes, limit
>>>>> used is 5
>>>>> converged reason: -11
>>>>>
>>>>> ------------------------------------------------------------
>>>>> -----------------------------------------
>>>>>
>>>>
>>>>
>>
>
