Thanks for the fast answer !
The error coming from MUMPS is :
On return from DMUMPS, INFOG(1)= -9
On return from DMUMPS, INFOG(2)= 29088157
The matrix size : 4972410*4972410
I need only 1 eigen value, the one near zero.
In order to have more precision, i put ncv at 500.
I'm using : -eps_gen_non_hermitian -st_type sinvert -eps_target 0.1
-eps_ncv 500 -eps_tol 1e-9 -bv_type vecs
I'm doing linear stability analysis. I'm looking at eigen values near
zero, and if the first one is positive or negative.
The mass matrix is ill conditioned. On a smaller matrix, it seems that
using KSP without a preconditioner gives satisfactory results. With a
PC, it diverges.
Number of iterations of the method: 1
Number of linear iterations of the method: 1000
Solution method: krylovschur
Number of requested eigenvalues: 1
Stopping condition: tol=1e-08, maxit=711
Linear eigensolve converged (14 eigenpairs) due to CONVERGED_TOL;
iterations 1
---------------------- --------------------
k ||Ax-kBx||/||kx||
---------------------- --------------------
0.000005+0.016787i 7.87928e-07
0.000005-0.016787i 7.87928e-07
-0.001781 1.11832e-05
-0.001802 0.00274427
[...]
I'm trying that on the big one.
Thanks for your help,
Yann
Le 11/19/2019 à 5:25 PM, Jose E. Roman a écrit :
Are you getting an error from MUMPS or from BV? What is the error message you
get? What is the size of the matrix? How many eigenvalues do you need to
compute?
In principle you can use any KSP+PC, see section 3.4.1 of the users manual. If
you have a good preconditioner, then an alternative to Krylov methods is to use
Davidson-type methods https://doi.org/10.1145/2543696 - in some cases these can
be competitive.
Jose
El 19 nov 2019, a las 17:06, Yann Jobic via petsc-users
<petsc-users@mcs.anl.gov> escribió:
Hi all,
I'm trying to solve a huge generalize (unsymetric) eigen value problem with
SLEPc + MUMPS. We actually failed to allocate the requested memory for MUMPS
factorization (we tried BVVECS).
We would like to know if there is an alternate iterative way of solving such
problems.
Thank you,
Best regards,
Yann
