[petsc-users] Mysterious error code 77

[Jose E. Roman]

Your operator is not well formed. If you do this:

x, y = LHS.createVecs()
x.set(1)
LHS.mult(x,y)
y.view()

you will see that the output is all zeros. That is why SLEPc complains that "Initial vector is zero or belongs to the deflation space".

Jose


> El 5 may 2022, a las 10:46, Quentin Chevalier <quentin.chevalier at polytechnique.edu> escribió:
> 
> Just a quick amend on the previous statement ; the problem arises in
> sequential and parallel. The MWE as is is provided for the parallel
> case, but imposing m_local=m makes it go sequential.
> 
> Cheers,
> 
> Quentin CHEVALIER – IA parcours recherche
> LadHyX - Ecole polytechnique
> __________
> 
> 
> 
> On Thu, 5 May 2022 at 10:34, Quentin Chevalier
> <quentin.chevalier at polytechnique.edu> wrote:
>> 
>> Hello all and thanks for your great work in bringing this very helpful package to the community !
>> 
>> That said, I wouldn't need this mailing list if everything was running smoothly. I have a rather involved eigenvalue problem that I've been working on that's been throwing a mysterious error :
>>> 
>>> petsc4py.PETSc.Error: error code 77
>>> 
>>> [1] EPSSolve() at /usr/local/slepc/src/eps/interface/epssolve.c:149
>>> [1] EPSSolve_KrylovSchur_Default() at /usr/local/slepc/src/eps/impls/krylov/krylovschur/krylovschur.c:289
>>> [1] EPSGetStartVector() at /usr/local/slepc/src/eps/interface/epssolve.c:824
>>> [1] Petsc has generated inconsistent data
>>> [1] Initial vector is zero or belongs to the deflation space
>> 
>> 
>> This problem occurs in parallel with two processors, using the petsc4py library using the dolfinx/dolfinx docker container. I have PETSc version 3.16.0, in complex mode, python 3, and I'm running all of that on a OpenSUSE Leap 15.2 machine (but I think the docker container has a Ubuntu OS).
>> 
>> I wrote a minimal working example below, but I'm afraid the process for building the matrices is involved, so I decided to directly share the matrices instead : https://seminaris.polytechnique.fr/share/s/ryJ6L2nR4ketDwP
>> 
>> They are in binary format, but inside the container I hope someone could reproduce my issue. A word on the structure and intent behind these matrices :
>> 
>> QE is a diagonal rectangular real matrix. Think of it as some sort of preconditioner
>> L is the least dense of them all, the only one that is complex, and in order to avoid inverting it I'm using two KSPs to compute solve problems on the fly
>> Mf is a diagonal square real matrix, its on the right-hand side of the Generalised Hermitian Eigenvalue problem (I'm solving QE^H*L^-1H*L^-1*QE*x=lambda*Mf*x
>> 
>> Full MWE is below :
>> 
>> from petsc4py import PETSc as pet
>> from slepc4py import SLEPc as slp
>> from mpi4py.MPI import COMM_WORLD
>> 
>> # Global sizes
>> m_local=COMM_WORLD.rank*(490363-489780)+489780
>> n_local=COMM_WORLD.rank*(452259-451743)+451743
>> m=980143
>> n=904002
>> 
>> QE=pet.Mat().createAIJ([[m_local,m],[n_local,n]])
>> L=pet.Mat().createAIJ([[m_local,m],[m_local,m]])
>> Mf=pet.Mat().createAIJ([[n_local,n],[n_local,n]])
>> 
>> viewerQE = pet.Viewer().createMPIIO("QE.dat", 'r', COMM_WORLD)
>> QE.load(viewerQE)
>> viewerL = pet.Viewer().createMPIIO("L.dat", 'r', COMM_WORLD)
>> L.load(viewerL)
>> viewerMf = pet.Viewer().createMPIIO("Mf.dat", 'r', COMM_WORLD)
>> Mf.load(viewerMf)
>> 
>> QE.assemble()
>> L.assemble()
>> 
>> KSPs = []
>> # Useful solvers (here to put options for computing a smart R)
>> for Mat in [L,L.hermitianTranspose()]:
>> KSP = pet.KSP().create()
>> KSP.setOperators(Mat)
>> KSP.setFromOptions()
>> KSPs.append(KSP)
>> class LHS_class:
>> def mult(self,A,x,y):
>> w=pet.Vec().createMPI([m_local,m],comm=COMM_WORLD)
>> z=pet.Vec().createMPI([m_local,m],comm=COMM_WORLD)
>> QE.mult(x,w)
>> KSPs[0].solve(w,z)
>> KSPs[1].solve(z,w)
>> QE.multTranspose(w,y)
>> 
>> # Matrix free operator
>> LHS=pet.Mat()
>> LHS.create(comm=COMM_WORLD)
>> LHS.setSizes([[n_local,n],[n_local,n]])
>> LHS.setType(pet.Mat.Type.PYTHON)
>> LHS.setPythonContext(LHS_class())
>> LHS.setUp()
>> 
>> # Eigensolver
>> EPS = slp.EPS(); EPS.create()
>> EPS.setOperators(LHS,Mf) # Solve QE^T*L^-1H*L^-1*QE*x=lambda*Mf*x
>> EPS.setProblemType(slp.EPS.ProblemType.GHEP) # Specify that A is hermitian (by construction), and B is semi-positive
>> EPS.setWhichEigenpairs(EPS.Which.LARGEST_MAGNITUDE) # Find largest eigenvalues
>> EPS.setFromOptions()
>> EPS.solve()
>> 
>> Quentin CHEVALIER – IA parcours recherche
>> 
>> LadHyX - Ecole polytechnique
>> 
>> __________