making solve() run in parallel

Question

the code I'm writing contains

problem = NonlinearVariationalProblem(L, u_, bcs, J)
solver = NonlinearVariationalSolver(problem)

while (t < T):
    t += dt
    u0_.vector()[:] = u_.vector()
    solver.solve()

and I'm running it in parallel

$ mpiexec -n 4 python2 rbc.py
...
Process 0: Solving linear system of size 124565 x 124565 (PETSc LU solver, mumps)
...

While the code does some things in parallel like applying boundary conditions, only one process does the Solving.

Answer 1

No that is not true. The output is only presented on the first process. The solver is run in parallel. At least if you are using PETSc or Epetra as linear algebra backends.