[petsc-users] Retireve eigenvectors from a paralell job/ Spectrum slicing in order to solve big eigenvalue problem

Mon Sep 17 03:54:13 CDT 2018

For this you have to set a number of partitions equal to the number of MPI processes. If you get this error it is because these values are different.
Jose

> El 17 sept 2018, a las 10:50, Jan Grießer <griesser.jan at googlemail.com> escribió:
> 
> Is this relly necessary, because in the last sentences of the chapter it states that:
> An additional benefit of multi-communicator support is that it enables parallel spectrum slicing runs without the need to install a parallel direct solver (MUMPS). The following commandline example uses sequential linear solves in 4 partitions, one process each:
> Therefore i assumed that it is not necessary to compile PETsc4py with an external solver e.g. MUMPS
> 
> Am Mo., 17. Sep. 2018 um 10:47 Uhr schrieb Jose E. Roman <jroman at dsic.upv.es>:
> You need a parallel direct solver such as MUMPS. This is explained in section 3.4.5.
> Jose
> 
> 
> > El 17 sept 2018, a las 10:41, Jan Grießer <griesser.jan at googlemail.com> escribió:
> > 
> > def solve_eigensystem(DynMatrix_nn, Unity_nn, Dimension, LowerLimit, UpperLimit):
> >       # Create the EPS solver 
> >       E = SLEPc.EPS().create()
> > 
> >       # Create the preconditioner and set it to Cholesky
> >       pc = PETSc.PC().create()
> >       pc.setType(pc.Type.CHOLESKY)
> > 
> >       # Create the KSP object
> >       ksp = PETSc.KSP().create()
> >       ksp.setType(ksp.Type.PREONLY)
> >       ksp.setPC(pc)
> > 
> >       # Set up the spectral transformations 
> >       st = SLEPc.ST().create()
> >       st.setType("sinvert")
> >       st.setKSP(ksp)
> >       # Setup spectral transformation 
> >       E.setST(st)
> >       
> >       # Eigenvalues should be real, therefore we start to order them from the smallest real value |l.real|
> >       E.setWhichEigenpairs(E.Which.ALL)
> >       # Set the interval of spectrum slicing
> >       E.setInterval(LowerLimit, UpperLimit)
> >       # Since the dynamical matrix is symmetric and real it is hermitian. Use GHEP for the spectrum slicing. Operatormatrix B is just a unit matrix 
> >       E.setProblemType(SLEPc.EPS.ProblemType.GHEP)
> >       # Use the Krylov Schur method to solve the eigenvalue problem
> >       E.setType(E.Type.KRYLOVSCHUR)
> >       # Partition the Krylov schnur problem in npart procceses
> >       E.setKrylovSchurPartitions(10)
> >       # Set the convergence criterion to relative to the eigenvalue and the maximal number of iterations
> >       E.setConvergenceTest(E.Conv.REL)
> >       E.setTolerances(tol = 1e-7, max_it = 1000)
> >       # Set the matrix in order to solve 
> >       E.setOperators(DynMatrix_nn, Unity_nn)
> >       # Sets EPS options from the options database. 
> >       E.setFromOptions()
> >       # Sets up all the internal data structures necessary for the execution of the eigensolver.
> >       E.setUp()
> > 
> >       # Solve eigenvalue problem     
> >       startClock = time.clock()
> >       startTime = time.time()
> >       E.solve()
> > 
> > Has maybe one of you any idea why this happens and where the problem is ? 
> > 
> > Am Mo., 17. Sep. 2018 um 10:40 Uhr schrieb Jan Grießer <griesser.jan at googlemail.com>:
> > I am aware that SLEPc is not supposed to calculate all eigenvalues and eigenvectors, my problem is simply that i want for a physical large enough system all of them before i can make the transition to go to the smallest ones. 
> > Competitiveness is of secondary importance at the moment. 
> > But ihave a problem connected with spectrum slicing. I followed the instructions in the manual of Chap. 3.4.5 Spectrum Slicing and converted them to the python package. 
> > But now i get the following error. It appears to me that it is not able to find the ksp object, but i actually do not know why this is the case. 
> > aceback (most recent call last):
> >   File "Eigensolver_spectrum_slicing.py", line 216, in <module>
> >     solve_eigensystem(DynMatrix_nn, Unity_nn, D_nn.shape, opt_dict.LowLimit, opt_dict.UpperLimit)
> >   File "Eigensolver_spectrum_slicing.py", line 121, in solve_eigensystem
> >     E.setUp()
> >   File "SLEPc/EPS.pyx", line 1099, in slepc4py.SLEPc.EPS.setUp
> > petsc4py.PETSc.Error: error code 92
> > [14] EPSSetUp() line 165 in /tmp/pip-install-golhudw7/slepc/src/eps/interface/epssetup.c
> > [14] EPSSetUp_KrylovSchur() line 146 in /tmp/pip-install-golhudw7/slepc/src/eps/impls/krylov/krylovschur/krylovschur.c
> > [14] EPSSetUp_KrylovSchur_Slice() line 410 in /tmp/pip-install-golhudw7/slepc/src/eps/impls/krylov/krylovschur/ks-slice.c
> > [14] EPSSliceGetEPS() line 300 in /tmp/pip-install-golhudw7/slepc/src/eps/impls/krylov/krylovschur/ks-slice.c
> > [14] EPSSetUp() line 165 in /tmp/pip-install-golhudw7/slepc/src/eps/interface/epssetup.c
> > [14] EPSSetUp_KrylovSchur() line 146 in /tmp/pip-install-golhudw7/slepc/src/eps/impls/krylov/krylovschur/krylovschur.c
> > [14] EPSSetUp_KrylovSchur_Slice() line 461 in /tmp/pip-install-golhudw7/slepc/src/eps/impls/krylov/krylovschur/ks-slice.c
> > [14] EPSSliceGetInertia() line 331 in /tmp/pip-install-golhudw7/slepc/src/eps/impls/krylov/krylovschur/ks-slice.c
> > [14] STSetUp() line 271 in /tmp/pip-install-golhudw7/slepc/src/sys/classes/st/interface/stsolve.c
> > [14] STSetUp_Sinvert() line 132 in /tmp/pip-install-golhudw7/slepc/src/sys/classes/st/impls/sinvert/sinvert.c
> > [14] KSPSetUp() line 381 in /tmp/pip-install-xmiaat2t/petsc/src/ksp/ksp/interface/itfunc.c
> > [14] PCSetUp() line 923 in /tmp/pip-install-xmiaat2t/petsc/src/ksp/pc/interface/precon.c
> > [14] PCSetUp_Cholesky() line 86 in /tmp/pip-install-xmiaat2t/petsc/src/ksp/pc/impls/factor/cholesky/cholesky.c
> > [14] MatGetFactor() line 4318 in /tmp/pip-install-xmiaat2t/petsc/src/mat/interface/matrix.c
> > [14] See http://www.mcs.anl.gov/petsc/documentation/linearsolvertable.html for possible LU and Cholesky solvers
> > [14] Could not locate a solver package. Perhaps you must ./configure with --download-<package>
> > 
> > The code i used to solve the problem is 
> > 
> > Am Fr., 14. Sep. 2018 um 18:34 Uhr schrieb Matthew Knepley <knepley at gmail.com>:
> > On Fri, Sep 14, 2018 at 12:19 PM Jose E. Roman <jroman at dsic.upv.es> wrote:
> > El 14 sept 2018, a las 17:45, Jan Grießer <griesser.jan at googlemail.com> escribió:
> > 
> >> Hey there,
> >> first i want to say thanks to Satish and Matt for helping with with my last problem with the mpi compilation. I have two questions related to solving a big, hermitian, standard eigenvalue problem using SLEPc4py., compiled with Intel MKL and Intel MPI. 
> >> 
> >> - I am using slepc4py with 
> >> mpi and run it with around -n 20 cores at the moment and how i wanted to ask if there is an easy way to retrieve the eigenvectors? When i run my code and print  for i in range(nconv):
> >>              for i in range(nconv):
> >> 
> >>                      val = E.
> >> getEigenpair(i, vr
> >> , vi)
> >>                      Print(
> >> vr.getArray())
> >>  i get the parts of the eigenvectors according to the partition of the matrix. Is there any easy way to put them together in an array and write them to file ? (I am struggling a little bit with the building them in the correct order)
> > 
> > You need VecScatterCreateToZero. There must be an equivalent in python.
> > 
> > An alternative to this which you should consider, because it is simpler, is to write the vector to a file
> > using some format that PETSc understands, Then you just need vr.view(viewer) for a viewer like
> > the binary viewer or some ASCII format you like.
> > 
> >   Thanks,
> > 
> >     Matt
> >> - I need to solve eigenvalue problems up to a dimension of 100000 degrees of freedom and i need all eigenvalues and eigenvectors. I think solving all eigenvalues in one process is far too much and i thought about if it is possible to apply the spectrum slicing described in Chap. 3.4.5.  Due to the nature of my problem, i am able to simulate smaller systems of 10000 DOF and extract the biggest eigenvalue, which will be the same for larger systems sizes. Is this in general possible since i have a standard HEP problem or is there a better and faster possibility to do this?
> > 
> > In general, SLEPc is not intended for computing the whole spectrum. You can try with spectrum slicing but this will be competitive if computing just a percentage of eigenvalues, 50% say. 
> > 
> > Jose
> > 
> >> 
> >> Thank you very much!
> > 
> > 
> > -- 
> > 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/
> 