Fenics & singularity - saving data with mpirun

I had no issue running the code after remove your two MPI.rank if tests (and saving for every process), using:

Bootstrap: docker
From: quay.io/fenicsproject/stable:current
%files
    output 
%post
    apt-get -y update
    apt-get -y install python3 python3-pip
    python3 -m pip install --force-reinstall numpy
mkdir -p output
sudo singularity build dolfin.simg dolfin_singularity 
mpirun -n 4 singularity exec dolfin.simg python3 demo.py 

where demo.py is:

import random
from dolfin import *

# Class representing the intial conditions
class InitialConditions(UserExpression):
    def __init__(self, **kwargs):
        random.seed(2 + MPI.rank(MPI.comm_world))
        super().__init__(**kwargs)
    def eval(self, values, x):
        values[0] = 0.63 + 0.02*(0.5 - random.random())
        values[1] = 0.0
    def value_shape(self):
        return (2,)

# Class for interfacing with the Newton solver
class CahnHilliardEquation(NonlinearProblem):
    def __init__(self, a, L):
        NonlinearProblem.__init__(self)
        self.L = L
        self.a = a
    def F(self, b, x):
        assemble(self.L, tensor=b)
    def J(self, A, x):
        assemble(self.a, tensor=A)

# Model parameters
lmbda  = 1.0e-02  # surface parameter
dt     = 5.0e-06  # time step
theta  = 0.5      # time stepping family, e.g. theta=1 -> backward Euler, theta=0.5 -> Crank-Nicolson

# Form compiler options
parameters["form_compiler"]["optimize"]     = True
parameters["form_compiler"]["cpp_optimize"] = True

# Create mesh and build function space
mesh = UnitSquareMesh.create(96, 96, CellType.Type.quadrilateral)
P1 = FiniteElement("Lagrange", mesh.ufl_cell(), 1)
ME = FunctionSpace(mesh, P1*P1)

# Define trial and test functions
du    = TrialFunction(ME)
q, v  = TestFunctions(ME)
# Define functions
u   = Function(ME)  # current solution
u0  = Function(ME)  # solution from previous converged step

# Split mixed functions
dc, dmu = split(du)
c,  mu  = split(u)
c0, mu0 = split(u0)

# Create intial conditions and interpolate
u_init = InitialConditions(degree=1)
u.interpolate(u_init)
u0.interpolate(u_init)

# Compute the chemical potential df/dc
c = variable(c)
f    = 100*c**2*(1-c)**2
dfdc = diff(f, c)

# mu_(n+theta)
mu_mid = (1.0-theta)*mu0 + theta*mu

# Weak statement of the equations
L0 = c*q*dx - c0*q*dx + dt*dot(grad(mu_mid), grad(q))*dx
L1 = mu*v*dx - dfdc*v*dx - lmbda*dot(grad(c), grad(v))*dx
L = L0 + L1

# Compute directional derivative about u in the direction of du (Jacobian)
a = derivative(L, u, du)

# Create nonlinear problem and Newton solver
problem = CahnHilliardEquation(a, L)
solver = NewtonSolver()
solver.parameters["linear_solver"] = "lu"
solver.parameters["convergence_criterion"] = "incremental"
solver.parameters["relative_tolerance"] = 1e-6

# Output file
file = File("output/output.pvd", "compressed")
HDF5 = HDF5File(MPI.comm_world,"output/output.hdf5",'w')
vtkfile_phi = File("output/output.pvd", "compressed")

# Step in time
t = 0.0
T = 5*dt
while (t < T):
    t += dt
    u0.vector()[:] = u.vector()
    solver.solve(problem, u.vector())
    file << (u.split()[0], t)
    HDF5.write(u.split()[0], "fun",t)
    file << (u.split()[0], t)