Sorry, running in parallel does not change the thing. I was wrong, the limitation is for the global size and not the local size. So what you have to do is use -bv_type vecs or also -bv_type mat Let me know how this works.
Jose > El 19 oct 2018, a las 13:12, Jan Grießer <griesser....@googlemail.com> > escribió: > > Thiis i already did with mpiexec -n 20 ... and there the error occured. I was > also a little bit surprised that this error occured. Our computation nodes > have 20 cores with 6GB RAM. > Is PETSc/ SLEPc saving the dense eigenvector error in one core ? > > > Am Fr., 19. Okt. 2018 um 12:52 Uhr schrieb Jan Grießer > <griesser....@googlemail.com>: > Thiis i already did with mpiexec -n 20 ... and there the error occured. I was > also a little bit surprised that this error occured. Our computation nodes > have 20 cores with 6GB RAM. > Is PETSc/ SLEPc saving the dense eigenvector error in one core ? > > Am Fr., 19. Okt. 2018 um 11:08 Uhr schrieb Jose E. Roman <jro...@dsic.upv.es>: > No, I mean to run in parallel: > > $ mpiexec -n 8 python ex1.py > > Jose > > > > El 19 oct 2018, a las 11:01, Jan Grießer <griesser....@googlemail.com> > > escribió: > > > > With more than 1 MPI process you mean i should use spectrum slicing in > > divide the full problem in smaller subproblems? > > The --with-64-bit-indices is not a possibility for me since i configured > > petsc with mumps, which does not allow to use the 64-bit version (At least > > this was the error message when i tried to configure PETSc ) > > > > Am Mi., 17. Okt. 2018 um 18:24 Uhr schrieb Jose E. Roman > > <jro...@dsic.upv.es>: > > To use BVVECS just add the command-line option -bv_type vecs > > This causes to use a separate Vec for each column, instead of a single long > > Vec of size n*m. But it is considerably slower than the default. > > > > Anyway, for such large problems you should consider using more than 1 MPI > > process. In that case the error may disappear because the local size is > > smaller than 768000. > > > > Jose > > > > > > > El 17 oct 2018, a las 17:58, Matthew Knepley <knep...@gmail.com> escribió: > > > > > > On Wed, Oct 17, 2018 at 11:54 AM Jan Grießer > > > <griesser....@googlemail.com> wrote: > > > Hi all, > > > i am using slepc4py and petsc4py to solve for the smallest real > > > eigenvalues and eigenvectors. For my test cases with a matrix A of the > > > size 30k x 30k solving for the smallest soutions works quite well, but > > > when i increase the dimension of my system to around A = 768000 x 768000 > > > or 3 million x 3 million and ask for the smallest real 3000 (the number > > > is increasing with increasing system size) eigenvalues and eigenvectors i > > > get the output (for the 768000): > > > The product 4001 times 768000 overflows the size of PetscInt; consider > > > reducing the number of columns, or use BVVECS instead > > > i understand that the requested number of eigenvectors and eigenvalues is > > > causing an overflow but i do not understand the solution of the problem > > > which is stated in the error message. Can someone tell me what exactly > > > BVVECS is and how i can use it? Or is there any other solution to my > > > problem ? > > > > > > You can also reconfigure with 64-bit integers: --with-64-bit-indices > > > > > > Thanks, > > > > > > Matt > > > > > > Thank you very much in advance, > > > Jan > > > > > > > > > > > > -- > > > 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/ > > >