[petsc-users] SLEPc generalized eigenvalue problem question?

[John Chludzinski]

I have 2 files (matrices) in simply binary form (IEEE-754, generated by some
C code) and wished to get them into canonical "PETSc binary form". So I did:

Mat A;
PetscScalar *a;

ierr = PetscMalloc(SIZE*SIZE*sizeof(PetscScalar),&a);CHKERRQ(ierr);
// stored the file into the space malloc'ed for 'a'.
MatCreateSeqDense(PETSC_COMM_SELF, n, n, a, &A);
MatView(A,PETSC_VIEWER_BINARY_(PETSC_COMM_WORLD));

This works when I use: -eps_type lapack.  As long as I store the matrix in
column major order.

---John

On Mon, Aug 1, 2011 at 1:40 PM, Matthew Knepley <knepley at gmail.com> wrote:

On Mon, Aug 1, 2011 at 5:27 PM, John Chludzinski <jchludzinski at gmail.com>wrote:
>
>> I create 2 matrices using:
>>
>> MatCreateSeqDense(PETSC_COMM_SELF, n, n, Ka, &A);
>> MatCreateSeqDense(PETSC_COMM_SELF, n, n, Kb, &B);
>>
>> These matrices are 99% zeros ( 16,016,004 entries and 18660 non-zeros).
>>  They are symmetric and real.  Their tri-diagonal elements are non-zero plus
>> a few other entries.
>>
>
> Please give some justification for doing this? On the surface, it just
> seems perverse.
>
>    Matt
>
>
>> I tried to use ex7 for the generalized eigenvalue problem:
>>
>> ./ex7.exe -f1 k.dat -f2 m.dat -eps_gen_hermitian -eps_smallest_real >
>> x.out 2>&1
>>
>> without specifying an EPS and get:
>>
>> Generalized eigenproblem stored in file.
>>
>> Reading REAL matrices from binary files...
>> Number of iterations of the method: 500
>>  Number of linear iterations of the method: 4009
>> Solution method: krylovschur
>>
>> Number of requested eigenvalues: 1
>> Stopping condition: tol=1e-07, maxit=500
>> Number of converged approximate eigenpairs: 0
>>
>> Is krylovschur inappropriate for this problem or have I set up the problem
>> incorrectly by using   MatCreateSeqDense(...) to create the matrix input
>> files in PETSc binary form?
>>
>> ---John
>>
>
>
> --
> 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
>
>
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