Different results in serial and parallel run dolfinx

Hi,

I’m trying to simulate the transport of a quantity n flowing through a channel. I have successfully solved the problem in serial. When
I execute the same code in parallel, I obtained the same results as in a serial run for \mathrm{np} \leq 21, for \mathrm{np} \gt 21 the results for n present some strange behavior close to the inlet. Is that an issue with the DoFs ordering?

python3 stokes.py

mpirun -np 24 python3 stokes.py

stokes.py

import os
import datetime
import numpy as np
from mpi4py import MPI
from petsc4py import PETSc
from dolfinx.io import XDMFFile
import dolfinx
from dolfinx.cpp.mesh import CellType
from dolfinx import (RectangleMesh, DirichletBC, Function, FunctionSpace, NewtonSolver, NonlinearProblem, Constant, Form, log)
from dolfinx.fem import (locate_dofs_topological, assemble_matrix, assemble_vector, set_bc, apply_lifting)
from dolfinx.mesh import locate_entities_boundary
from ufl import (Identity, VectorElement, FiniteElement, MixedElement, TestFunction, TrialFunction,
derivative, dx, grad, div, dot, inner, sym, split)
from math import sqrt

log.set_log_level(log.LogLevel.INFO)

# Parameters
U     = 0.1
beta  = 1e-3
delta = 1e-3

# Mesh
mesh = RectangleMesh(
MPI.COMM_WORLD,
[np.array([0, -0.5, 0]), np.array([10, 0.5, 0])], [200, 20],

def inlet_boundary(x):
return np.isclose(x[0], 0.0)

def outlet_boundary(x):
return np.isclose(x[0], 10.0)

def wall_boundary(x):
return np.logical_or(np.isclose(x[1], -0.5), np.isclose(x[1], 0.5))

# Define Function Spaces
V = VectorElement("Lagrange", mesh.ufl_cell(), 2)
Q = FiniteElement("Lagrange", mesh.ufl_cell(), 1)
N = FiniteElement("Lagrange", mesh.ufl_cell(), 1)
W = FunctionSpace(mesh, MixedElement([V, Q, N]))

# Boundary conditions
inlet_facets = locate_entities_boundary(mesh, 1, inlet_boundary)
outlet_facets = locate_entities_boundary(mesh, 1, outlet_boundary)
wall_facets = locate_entities_boundary(mesh, 1, wall_boundary)

def u_bc_inlet(x):
return np.stack((U*np.ones(x.shape[1]), np.zeros(x.shape[1])))

def u_bc_wall(x):
return np.stack((np.zeros(x.shape[1]), np.zeros(x.shape[1])))

u_bc1 = Function(W.sub(0).collapse())
u_bc1.interpolate(u_bc_inlet)
dofs1 = locate_dofs_topological((W.sub(0), FunctionSpace(mesh, V)), 1, inlet_facets)
bc1 = DirichletBC(u_bc1, dofs1, W.sub(0))

u_bc2 = Function(W.sub(0).collapse())
u_bc2.vector.set(0.0)
dofs2 = locate_dofs_topological((W.sub(0).sub(1), FunctionSpace(mesh, V).sub(1)), 1, outlet_facets)
bc2 = DirichletBC(u_bc2, dofs2, W.sub(0).sub(1))

u_bc3 = Function(W.sub(0).collapse())
u_bc3.interpolate(u_bc_wall)
dofs3 = locate_dofs_topological((W.sub(0), FunctionSpace(mesh, V)), 1, wall_facets)
bc3 = DirichletBC(u_bc3, dofs3, W.sub(0))

n_bc = Function(W.sub(2).collapse())
n_bc.vector.set(1.0)
dofs4 = locate_dofs_topological((W.sub(2), FunctionSpace(mesh, N)), 1, inlet_facets)
bc4 = DirichletBC(n_bc, dofs4, W.sub(2))

bcs = [bc1, bc2, bc3, bc4]

# Define test and trial functions
w_trial = TrialFunction(W)
w_test = TestFunction(W)
v, q, c = split(w_test)

# Define function
w = Function(W)
u, p, n = split(w)

w0 = Function(W)
u0, p0, n0 = split(w0)

dw = Function(W)

# Initial conditions
def w_init(x):
values = np.zeros((4, x.shape[1]))
values[0] = 0.0
values[1] = 0.0
values[2] = 0.0
values[3] = 1.0
return values

w.interpolate(w_init)

# Strain rate tensor
def D(u):

# Identity tensor
I = Identity(len(u))

# Total stress
T = -p*I + 2*beta*D(u)

# Body force
f = Constant(mesh, (0, 0))

# Stokes - Equation
F = inner(grad(v), T)*dx - inner(v, f)*dx + q*div(u)*dx

# Jacobian
J = derivative(F, w, w_trial)

class NonlinearEquation(NonlinearProblem):
def __init__(self, a, L, bcs):
super().__init__()
self.L = Form(L)
self.a = Form(a)
self.bcs = bcs
self._F = None
self._J = None

def form(self, x):

def F(self, x):
if self._F is None:
self._F = assemble_vector(self.L)
else:
with self._F.localForm() as f_local:
f_local.set(0.0)
self._F = assemble_vector(self._F, self.L)
apply_lifting(self._F, [self.a], [self.bcs], [x], -1.0)
set_bc(self._F, self.bcs, x, -1.0)
return self._F

def J(self, x):
if self._J is None:
self._J = assemble_matrix(self.a, self.bcs)
else:
self._J.zeroEntries()
self._J = assemble_matrix(self._J, self.a, self.bcs)
self._J.assemble()
return self._J

problem = NonlinearEquation(J, F, bcs)
solver = NewtonSolver(MPI.COMM_WORLD)

# Files
u_file = XDMFFile(MPI.COMM_WORLD, "stokes/velocity.xdmf", "w")
u_file.write_mesh(mesh)

p_file = XDMFFile(MPI.COMM_WORLD, "stokes/pressure.xdmf", "w")
p_file.write_mesh(mesh)

n_file = XDMFFile(MPI.COMM_WORLD, "stokes/n.xdmf", "w")
n_file.write_mesh(mesh)

# Solver
solver.solve(problem, w.vector)

u_file.write_function(w.split()[0])
p_file.write_function(w.split()[1])
n_file.write_function(w.split()[2])

u_file.close()
p_file.close()
n_file.close()

Please try to make this problem a minimal example.
You should start by using a built in mesh to make it simpler for people to reproduce your problem.

Please also check that your inlet Bc is correct by writing it to file.

You could Also consider: Interpolate into function, and fail in PETSc vector norm (dolfinx)

Hi, @dokken. Thank you for your reply!. I have updated my code using a built in mesh. I checked the boundary conditions and it seems that was imposed correctly.

Does the issue occur on a single time step? If so, please remove the temporal loop and all parameters related to the loop.

I have removed the loop and update the code, the issue still occurs.

I cannot reproduce your error using 21,22, 23 or 28 processors using the latest dolfinx docker image.

I running on a ubuntu server machine with dolfinx installed from source

When did you install it? What is the latest commit on dolfinx?

Today a reinstalled dolfinx running again the commands of this post.

The bug seems rather strange. Can you try using docker on your server? (As I cannot reproduce it)

I don’t have docker installed on my server yet, I will try to install it and test the code.

I have installed dolfinx from docker and run the code, the issue persists.

Unfortunately I cannot do much as I cannot reproduce your issue.

Could you try compute the norm of w before saving the components to file? I.e. w.vector.norm() and see if it changes when ran on 1,2 or 25 processors

For np = 1, 2, and 24 (I only have 24 processors available). w.vector.norm() = 63.92201110501961, 63.9220111050196, and 62.52065094359216

edit: In fact I could run for 25 processor and the result was 63.92201110501959

I actually got that number on 24 processors as well. I will have a closer look at it tomorrow.

2 Likes

I would just like to give you an update:

• I can confirm that there is an issue when running on 24 processors.
• I’ve located that the error appears during the Newton solve, but are struggling to finding the source of the bug.

I’ve now been able to reproduce the issue with a much smaller example:

import dolfinx
from dolfinx import jit
import dolfinx.cpp
import dolfinx.io
import dolfinx.fem as fem
import numpy as np
from mpi4py import MPI
from petsc4py import PETSc
import ufl
import dolfinx.log as log

mesh = dolfinx.RectangleMesh(MPI.COMM_WORLD,
[np.array([0, -0.5, 0]), np.array([10, 0.5, 0])], [5, 5],

def inlet_boundary(x):
return np.isclose(x[0], 0.0)

# Define Function Spaces
CG1 = ufl.FiniteElement("Lagrange", mesh.ufl_cell(), 1)
V = dolfinx.FunctionSpace(mesh, CG1)

# Boundary conditions
inlet_facets = dolfinx.mesh.locate_entities_boundary(mesh, 1, inlet_boundary)

u_bc = dolfinx.Function(V)
u_bc.vector.set(1.0)
dofs = dolfinx.fem.locate_dofs_topological(V, 1, inlet_facets)
bc = dolfinx.DirichletBC(u_bc, dofs)
bcs = [bc]

v = ufl.TestFunction(V)
u = dolfinx.Function(V)

def u_init(x):
values = np.zeros((1, x.shape[1]))
values[0] = 1.0
return values

u.interpolate(u_init)

# Write out Newton solver
# Assemble initial residual
du = ufl.TrialFunction(V)
a = ufl.derivative(F, u, du)
b = dolfinx.Function(V)
b.vector.set(0.0)
fem.assemble_vector(b.vector, F)
dolfinx.fem.apply_lifting(b.vector, [a], [bcs], [u.vector], -1.0)