Florian Lindner <[email protected]> writes: > Hello, > > I'm using petsc with petsc4py. > > A matrix is created like that > > MPIrank = MPI.COMM_WORLD.Get_rank() > MPIsize = MPI.COMM_WORLD.Get_size() > print("MPI Rank = ", MPIrank) > print("MPI Size = ", MPIsize) > parts = partitions() > > print("Dimension= ", nSupport + dimension, "bsize = ", > len(parts[MPIrank])) > > MPI.COMM_WORLD.Barrier() # Just to keep the output together > A = PETSc.Mat(); A.createDense( (nSupport + dimension, nSupport + > dimension), bsize = len(parts[MPIrank]) ) # <-- crash here
bsize is collective (must be the same on all processes). It is used for vector-valued problems (like elasticity -- bs=3 in 3 dimensions).
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