def test_subdimmiddle_notparallel(self):
"""
Tests application of an Operator consisting of a subdimension
defined over different sub-regions, explicitly created through the
use of SubDimensions.
Different from ``test_subdimmiddle_parallel`` because an interior
dimension cannot be evaluated in parallel.
"""
grid = Grid(shape=(20, 20))
x, y = grid.dimensions
t = grid.stepping_dim
thickness = 4
u = TimeFunction(name='u',
save=None,
grid=grid,
space_order=0,
time_order=1)
xi = SubDimension.middle(name='xi',
parent=x,
thickness_left=thickness,
thickness_right=thickness)
yi = SubDimension.middle(name='yi',
parent=y,
thickness_left=thickness,
thickness_right=thickness)
# flow dependencies in x and y which should force serial execution
# in reverse direction
centre = Eq(u[t + 1, xi, yi], u[t, xi, yi] + u[t + 1, xi + 1, yi + 1])
u.data[0, 10, 10] = 1.0
op = Operator([centre])
iterations = FindNodes(Iteration).visit(op)
assert all(i.is_Affine and i.is_Sequential for i in iterations
if i.dim == xi)
assert all(i.is_Affine and i.is_Parallel for i in iterations
if i.dim == yi)
op.apply(time_m=0, time_M=0)
for i in range(4, 11):
assert u.data[1, i, i] == 1.0
u.data[1, i, i] = 0.0
assert np.all(u.data[1, :] == 0)
def test_bcs(self):
"""
Tests application of an Operator consisting of multiple equations
defined over different sub-regions, explicitly created through the
use of :class:`SubDimension`s.
"""
grid = Grid(shape=(20, 20))
x, y = grid.dimensions
t = grid.stepping_dim
thickness = 4
u = TimeFunction(name='u',
save=None,
grid=grid,
space_order=0,
time_order=1)
xleft = SubDimension.left(name='xleft', parent=x, thickness=thickness)
xi = SubDimension.middle(name='xi',
parent=x,
thickness_left=thickness,
thickness_right=thickness)
xright = SubDimension.right(name='xright',
parent=x,
thickness=thickness)
yi = SubDimension.middle(name='yi',
parent=y,
thickness_left=thickness,
thickness_right=thickness)
t_in_centre = Eq(u[t + 1, xi, yi], 1)
leftbc = Eq(u[t + 1, xleft, yi], u[t + 1, xleft + 1, yi] + 1)
rightbc = Eq(u[t + 1, xright, yi], u[t + 1, xright - 1, yi] + 1)
op = Operator([t_in_centre, leftbc, rightbc])
op.apply(time_m=1, time_M=1)
assert np.all(u.data[0, :, 0:thickness] == 0.)
assert np.all(u.data[0, :, -thickness:] == 0.)
assert all(
np.all(u.data[0, i, thickness:-thickness] == (thickness + 1 - i))
for i in range(thickness))
assert all(
np.all(u.data[0, -i, thickness:-thickness] == (thickness + 2 - i))
for i in range(1, thickness + 1))
assert np.all(u.data[0, thickness:-thickness,
thickness:-thickness] == 1.)
def test_subdimmiddle_parallel(self):
"""
Tests application of an Operator consisting of a subdimension
defined over different sub-regions, explicitly created through the
use of :class:`SubDimension`s.
"""
grid = Grid(shape=(20, 20))
x, y = grid.dimensions
t = grid.stepping_dim
thickness = 4
u = TimeFunction(name='u',
save=None,
grid=grid,
space_order=0,
time_order=1)
xi = SubDimension.middle(name='xi',
parent=x,
thickness_left=thickness,
thickness_right=thickness)
yi = SubDimension.middle(name='yi',
parent=y,
thickness_left=thickness,
thickness_right=thickness)
# a 5 point stencil that can be computed in parallel
centre = Eq(
u[t + 1, xi, yi], u[t, xi, yi] + u[t, xi - 1, yi] +
u[t, xi + 1, yi] + u[t, xi, yi - 1] + u[t, xi, yi + 1])
u.data[0, 10, 10] = 1.0
op = Operator([centre])
iterations = FindNodes(Iteration).visit(op)
assert all(i.is_Affine and i.is_Parallel for i in iterations
if i.dim in [xi, yi])
op.apply(time_m=0, time_M=0)
assert np.all(u.data[1, 9:12, 10] == 1.0)
assert np.all(u.data[1, 10, 9:12] == 1.0)
# Other than those, it should all be 0
u.data[1, 9:12, 10] = 0.0
u.data[1, 10, 9:12] = 0.0
assert np.all(u.data[1, :] == 0)
def test_subdimleft_parallel(self):
"""
Tests application of an Operator consisting of a subdimension
defined over different sub-regions, explicitly created through the
use of :class:`SubDimension`s.
This tests that flow direction is not being automatically inferred
from whether the subdimension is on the left or right boundary.
"""
grid = Grid(shape=(20, 20))
x, y = grid.dimensions
t = grid.stepping_dim
thickness = 4
u = TimeFunction(name='u', save=None, grid=grid, space_order=0, time_order=1)
xl = SubDimension.left(name='xl', parent=x, thickness=thickness)
yi = SubDimension.middle(name='yi', parent=y,
thickness_left=thickness, thickness_right=thickness)
# Can be done in parallel
eq = Eq(u[t+1, xl, yi], u[t, xl, yi] + 1)
op = Operator([eq])
iterations = FindNodes(Iteration).visit(op)
assert all(i.is_Affine and i.is_Parallel for i in iterations if i.dim in [xl, yi])
op.apply(time_m=0, time_M=0)
assert np.all(u.data[1, 0:thickness, 0:thickness] == 0)
assert np.all(u.data[1, 0:thickness, -thickness:] == 0)
assert np.all(u.data[1, 0:thickness, thickness:-thickness] == 1)
assert np.all(u.data[1, thickness+1:, :] == 0)
def test_sub_dimension():
di = SubDimension.middle('di', Dimension(name='d'), 1, 1)
pkl_di = pickle.dumps(di)
new_di = pickle.loads(pkl_di)
assert di.name == new_di.name
assert di.dtype == new_di.dtype
assert di.parent == new_di.parent
assert di._thickness == new_di._thickness
assert di._interval == new_di._interval
def test_everything():
nt = 50
grid = Grid(shape=(6, 6))
x, y = grid.dimensions
time = grid.time_dim
xi = SubDimension.middle(name='xi', parent=x, thickness_left=2, thickness_right=2)
yi = SubDimension.middle(name='yi', parent=y, thickness_left=2, thickness_right=2)
factor = Constant(name='factor', value=5, dtype=np.int32)
t_sub = ConditionalDimension('t_sub', parent=time, factor=factor)
save_shift = Constant(name='save_shift', dtype=np.int32)
u = TimeFunction(name='u', grid=grid, time_order=0)
u1 = TimeFunction(name='u', grid=grid, time_order=0)
va = TimeFunction(name='va', grid=grid, time_order=0,
save=(int(nt//factor.data)), time_dim=t_sub)
vb = TimeFunction(name='vb', grid=grid, time_order=0,
save=(int(nt//factor.data)), time_dim=t_sub)
for i in range(va.save):
va.data[i, :] = i
vb.data[i, :] = i*2 - 1
vas = va.subs(t_sub, t_sub - save_shift)
vasb = va.subs(t_sub, t_sub - 1 - save_shift)
vasf = va.subs(t_sub, t_sub + 1 - save_shift)
eqns = [Eq(u.forward, u + (vasb + vas + vasf)*2. + vb)]
eqns = [e.xreplace({x: xi, y: yi}) for e in eqns]
op0 = Operator(eqns, opt='noop')
op1 = Operator(eqns, opt='buffering')
# Check generated code
assert len([i for i in FindSymbols().visit(op1) if i.is_Array]) == 2
op0.apply(time_m=15, time_M=35, save_shift=0)
op1.apply(time_m=15, time_M=35, save_shift=0, u=u1)
assert np.all(u.data == u1.data)
def test_sub_dimension(self):
"""
Test that SubDimensions with same name but different attributes do not
alias to the same SubDimension. Conversely, if the name and the attributes
are the same, they must alias to the same SubDimension.
"""
x = Dimension('x')
xi0 = SubDimension.middle('xi', x, 1, 1)
xi1 = SubDimension.middle('xi', x, 1, 1)
assert xi0 is xi1
xl0 = SubDimension.left('xl', x, 2)
xl1 = SubDimension.left('xl', x, 2)
assert xl0 is xl1
xl2asxi = SubDimension.left('xi', x, 2)
assert xl2asxi is not xl1
assert xl2asxi is not xi1
xr0 = SubDimension.right('xr', x, 1)
xr1 = SubDimension.right('xr', x, 1)
assert xr0 is xr1
def test_sub_dimension_cache():
"""
Test that SubDimensions with same name but different attributes do not
alias to the same SubDimension. Conversely, if the name and the attributes
are the same, they must alias to the same SubDimension.
"""
x = Dimension('x')
xi0 = SubDimension.middle('xi', x, 1, 1)
xi1 = SubDimension.middle('xi', x, 1, 1)
assert xi0 is xi1
xl0 = SubDimension.left('xl', x, 2)
xl1 = SubDimension.left('xl', x, 2)
assert xl0 is xl1
xl2asxi = SubDimension.left('xi', x, 2)
assert xl2asxi is not xl1
assert xl2asxi is not xi1
xr0 = SubDimension.right('xr', x, 1)
xr1 = SubDimension.right('xr', x, 1)
assert xr0 is xr1
def test_save_w_subdims(self):
nt = 10
grid = Grid(shape=(10, 10))
x, y = grid.dimensions
time_dim = grid.time_dim
xi = SubDimension.middle(name='xi',
parent=x,
thickness_left=3,
thickness_right=3)
yi = SubDimension.middle(name='yi',
parent=y,
thickness_left=3,
thickness_right=3)
factor = Constant(name='factor', value=2, dtype=np.int32)
time_sub = ConditionalDimension(name="time_sub",
parent=time_dim,
factor=factor)
u = TimeFunction(name='u', grid=grid)
usave = TimeFunction(name='usave',
grid=grid,
time_order=0,
save=int(nt // factor.data),
time_dim=time_sub)
eqns = [Eq(u.forward, u + 1), Eq(usave, u.forward)]
eqns = [e.xreplace({x: xi, y: yi}) for e in eqns]
op = Operator(eqns, opt=('buffering', 'tasking', 'orchestrate'))
op.apply(time_M=nt - 1)
for i in range(usave.save):
assert np.all(usave.data[i, 3:-3, 3:-3] == 2 * i + 1)
assert np.all(usave.data[i, :3, :] == 0)
assert np.all(usave.data[i, -3:, :] == 0)
assert np.all(usave.data[i, :, :3] == 0)
assert np.all(usave.data[i, :, -3:] == 0)
def test_expandingbox_like(self):
"""
Make sure SubDimensions aren't an obstacle to expanding boxes.
"""
grid = Grid(shape=(8, 8))
x, y = grid.dimensions
u = TimeFunction(name='u', grid=grid)
xi = SubDimension.middle(name='xi',
parent=x,
thickness_left=2,
thickness_right=2)
yi = SubDimension.middle(name='yi',
parent=y,
thickness_left=2,
thickness_right=2)
eqn = Eq(u.forward, u + 1)
eqn = eqn.subs({x: xi, y: yi})
op = Operator(eqn)
op.apply(time=3,
x_m=2,
x_M=5,
y_m=2,
y_M=5,
xi_ltkn=0,
xi_rtkn=0,
yi_ltkn=0,
yi_rtkn=0)
assert np.all(u.data[0, 2:-2, 2:-2] == 4.)
assert np.all(u.data[1, 2:-2, 2:-2] == 3.)
assert np.all(u.data[:, :2] == 0.)
assert np.all(u.data[:, -2:] == 0.)
assert np.all(u.data[:, :, :2] == 0.)
assert np.all(u.data[:, :, -2:] == 0.)
def test_subdimensions(self):
nt = 10
grid = Grid(shape=(10, 10, 10))
x, y, z = grid.dimensions
xi = SubDimension.middle(name='xi', parent=x, thickness_left=2, thickness_right=2)
yi = SubDimension.middle(name='yi', parent=y, thickness_left=2, thickness_right=2)
zi = SubDimension.middle(name='zi', parent=z, thickness_left=2, thickness_right=2)
u = TimeFunction(name='u', grid=grid, save=nt)
u1 = TimeFunction(name='u', grid=grid, save=nt)
eqn = Eq(u.forward, u + 1).xreplace({x: xi, y: yi, z: zi})
op0 = Operator(eqn, opt='noop')
op1 = Operator(eqn, opt='buffering')
# Check generated code
assert len(retrieve_iteration_tree(op1)) == 2
assert len([i for i in FindSymbols().visit(op1) if i.is_Array]) == 1
op0.apply(time_M=nt-2)
op1.apply(time_M=nt-2, u=u1)
assert np.all(u.data == u1.data)
def test_symbolic_size(self):
"""Check the symbolic size of all possible SubDimensions is as expected."""
grid = Grid(shape=(4,))
x, = grid.dimensions
thickness = 4
xleft = SubDimension.left(name='xleft', parent=x, thickness=thickness)
assert xleft.symbolic_size == xleft.thickness.left[0]
xi = SubDimension.middle(name='xi', parent=x,
thickness_left=thickness, thickness_right=thickness)
assert xi.symbolic_size == (x.symbolic_max - x.symbolic_min -
xi.thickness.left[0] - xi.thickness.right[0] + 1)
xright = SubDimension.right(name='xright', parent=x, thickness=thickness)
assert xright.symbolic_size == xright.thickness.right[0]
def test_subdimleft_notparallel(self):
"""
Tests application of an Operator consisting of a subdimension
defined over different sub-regions, explicitly created through the
use of :class:`SubDimension`s.
This tests that flow direction is not being automatically inferred
from whether the subdimension is on the left or right boundary.
"""
grid = Grid(shape=(20, 20))
x, y = grid.dimensions
t = grid.stepping_dim
thickness = 4
u = TimeFunction(name='u',
save=None,
grid=grid,
space_order=1,
time_order=0)
xl = SubDimension.left(name='xl', parent=x, thickness=thickness)
yi = SubDimension.middle(name='yi',
parent=y,
thickness_left=thickness,
thickness_right=thickness)
# Flows inward (i.e. forward) rather than outward
eq = Eq(u[t + 1, xl, yi], u[t + 1, xl - 1, yi] + 1)
op = Operator([eq])
iterations = FindNodes(Iteration).visit(op)
assert all(i.is_Affine and i.is_Sequential for i in iterations
if i.dim == xl)
assert all(i.is_Affine and i.is_Parallel for i in iterations
if i.dim == yi)
op.apply(time_m=1, time_M=1)
assert all(
np.all(u.data[0, :thickness, thickness + i] == [1, 2, 3, 4])
for i in range(12))
assert np.all(u.data[0, thickness:] == 0)
assert np.all(u.data[0, :, thickness + 12:] == 0)
def test_index_mode_detection(self, indexed, expected):
"""
Test detection of IterationInstance access modes (AFFINE vs IRREGULAR).
Proper detection of access mode is a prerequisite to any sort of
data dependence analysis.
"""
grid = Grid(shape=(4, 4, 4))
x, y, z = grid.dimensions # noqa
sx = SubDimension.middle('sx', x, 1, 1) # noqa
u = Function(name='u', grid=grid) # noqa
c = Constant(name='c') # noqa
sc = Scalar(name='sc', is_const=True) # noqa
s = Scalar(name='s') # noqa
ii = IterationInstance(eval(indexed))
assert ii.index_mode == expected
def test_bcs_basic(self):
"""
Test MPI in presence of boundary condition loops. Here, no halo exchange
is expected (as there is no stencil in the computed expression) but we
check that:
* the left BC loop is computed by the leftmost rank only
* the right BC loop is computed by the rightmost rank only
"""
grid = Grid(shape=(20, ))
x = grid.dimensions[0]
t = grid.stepping_dim
thickness = 4
u = TimeFunction(name='u', grid=grid, time_order=1)
xleft = SubDimension.left(name='xleft', parent=x, thickness=thickness)
xi = SubDimension.middle(name='xi',
parent=x,
thickness_left=thickness,
thickness_right=thickness)
xright = SubDimension.right(name='xright',
parent=x,
thickness=thickness)
t_in_centre = Eq(u[t + 1, xi], 1)
leftbc = Eq(u[t + 1, xleft], u[t + 1, xleft + 1] + 1)
rightbc = Eq(u[t + 1, xright], u[t + 1, xright - 1] + 1)
op = Operator([t_in_centre, leftbc, rightbc])
op.apply(time_m=1, time_M=1)
glb_pos_map = u.grid.distributor.glb_pos_map
if LEFT in glb_pos_map[x]:
assert np.all(u.data_ro_domain[0, thickness:] == 1.)
assert np.all(
u.data_ro_domain[0, :thickness] == range(thickness + 1, 1, -1))
else:
assert np.all(u.data_ro_domain[0, :-thickness] == 1.)
assert np.all(
u.data_ro_domain[0, -thickness:] == range(2, thickness + 2))
def test_index_mode_detection(self, indexed, expected):
"""
Test detection of IterationInstance access modes (AFFINE vs IRREGULAR).
Proper detection of access mode is a prerequisite to any sort of
data dependence analysis.
"""
grid = Grid(shape=(4, 4, 4))
x, y, z = grid.dimensions # noqa
sx = SubDimension.middle('sx', x, 1, 1) # noqa
u = Function(name='u', grid=grid) # noqa
c = Constant(name='c') # noqa
sc = Scalar(name='sc', is_const=True) # noqa
s = Scalar(name='s') # noqa
ii = IterationInstance(eval(indexed))
assert ii.index_mode == expected
def test_subdim_middle(self):
"""
Tests that instantiating SubDimensions using the classmethod
constructors works correctly.
"""
grid = Grid(shape=(4, 4, 4))
x, y, z = grid.dimensions
t = grid.stepping_dim # noqa
u = TimeFunction(name='u', grid=grid) # noqa
xi = SubDimension.middle(name='xi', parent=x,
thickness_left=1,
thickness_right=1)
eqs = [Eq(u.forward, u + 1)]
eqs = [e.subs(x, xi) for e in eqs]
op = Operator(eqs)
u.data[:] = 1.0
op.apply(time_M=1)
assert np.all(u.data[1, 0, :, :] == 1)
assert np.all(u.data[1, -1, :, :] == 1)
assert np.all(u.data[1, 1:3, :, :] == 2)
def test_nontrivial_operator(self):
"""
Test MPI in a non-trivial scenario: ::
* 9 processes logically organised in a 3x3 cartesian grid (as opposed to
most tests in this module, which only use 2 or 4 processed);
* star-like stencil expression;
* non-trivial Higdon-like BCs;
* simultaneous presence of TimeFunction(grid), Function(grid), and
Function(dimensions)
"""
size_x, size_y = 9, 9
tkn = 2
# Grid and Dimensions
grid = Grid(shape=(
size_x,
size_y,
))
x, y = grid.dimensions
t = grid.stepping_dim
# SubDimensions to implement BCs
xl, yl = [SubDimension.left('%sl' % d.name, d, tkn) for d in [x, y]]
xi, yi = [
SubDimension.middle('%si' % d.name, d, tkn, tkn) for d in [x, y]
]
xr, yr = [SubDimension.right('%sr' % d.name, d, tkn) for d in [x, y]]
# Functions
u = TimeFunction(name='f', grid=grid)
m = Function(name='m', grid=grid)
c = Function(name='c', grid=grid, dimensions=(x, ), shape=(size_x, ))
# Data initialization
u.data_with_halo[:] = 0.
m.data_with_halo[:] = 1.
c.data_with_halo[:] = 0.
# Equations
c_init = Eq(c, 1.)
eqn = Eq(u[t + 1, xi, yi], u[t, xi, yi] + m[xi, yi] + c[xi] + 1.)
bc_left = Eq(u[t + 1, xl, yi], u[t + 1, xl + 1, yi] + 1.)
bc_right = Eq(u[t + 1, xr, yi], u[t + 1, xr - 1, yi] + 1.)
bc_top = Eq(u[t + 1, xi, yl], u[t + 1, xi, yl + 1] + 1.)
bc_bottom = Eq(u[t + 1, xi, yr], u[t + 1, xi, yr - 1] + 1.)
op = Operator([c_init, eqn, bc_left, bc_right, bc_top, bc_bottom])
op.apply(time=0)
# Expected (global view):
# 0 0 5 5 5 5 5 0 0
# 0 0 4 4 4 4 4 0 0
# 5 4 3 3 3 3 3 4 5
# 5 4 3 3 3 3 3 4 5
# 5 4 3 3 3 3 3 4 5
# 5 4 3 3 3 3 3 4 5
# 0 0 4 4 4 4 4 0 0
# 0 0 5 5 5 5 5 0 0
assert np.all(u.data_ro_domain[0] == 0) # The write occures at t=1
glb_pos_map = u.grid.distributor.glb_pos_map
# Check cornes
if LEFT in glb_pos_map[x] and LEFT in glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[0, 0, 5], [0, 0, 4], [5, 4, 3]])
elif LEFT in glb_pos_map[x] and RIGHT in glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[5, 0, 0], [4, 0, 0], [3, 4, 5]])
elif RIGHT in glb_pos_map[x] and LEFT in glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[5, 4, 3], [0, 0, 4], [0, 0, 5]])
elif RIGHT in glb_pos_map[x] and RIGHT in glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[3, 4, 5], [4, 0, 0], [5, 0, 0]])
# Check sides
if not glb_pos_map[x] and LEFT in glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[5, 4, 3], [5, 4, 3], [5, 4, 3]])
elif not glb_pos_map[x] and RIGHT in glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[3, 4, 5], [3, 4, 5], [3, 4, 5]])
elif LEFT in glb_pos_map[x] and not glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[5, 5, 5], [4, 4, 4], [3, 3, 3]])
elif RIGHT in glb_pos_map[x] and not glb_pos_map[y]:
assert np.all(
u.data_ro_domain[1] == [[3, 3, 3], [4, 4, 4], [5, 5, 5]])
# Check center
if not glb_pos_map[x] and not glb_pos_map[y]:
assert np.all(u.data_ro_domain[1] == 3)
