def __init__(self, obj, r, gridpoints_data, coefficients_data):
if not isinstance(r, int):
raise TypeError('Need `r` int argument')
if r <= 0:
raise ValueError('`r` must be > 0')
self.r = r
self.obj = obj
self._npoint = obj._npoint
gridpoints = SubFunction(name="%s_gridpoints" % self.obj.name, dtype=np.int32,
dimensions=(self.obj.indices[-1], Dimension(name='d')),
shape=(self._npoint, self.obj.grid.dim), space_order=0,
parent=self.obj)
assert(gridpoints_data is not None)
gridpoints.data[:] = gridpoints_data[:]
self.obj._gridpoints = gridpoints
interpolation_coeffs = SubFunction(name="%s_interpolation_coeffs" % self.obj.name,
dimensions=(self.obj.indices[-1],
Dimension(name='d'),
Dimension(name='i')),
shape=(self.obj.npoint, self.obj.grid.dim,
self.r),
dtype=self.obj.dtype, space_order=0,
parent=self.obj)
assert(coefficients_data is not None)
interpolation_coeffs.data[:] = coefficients_data[:]
self.obj._interpolation_coeffs = interpolation_coeffs
warning("Ensure that the provided interpolation coefficient and grid point " +
"values are computed on the final grid that will be used for other " +
"computations.")
def _make_poke(self, hs, key, msgs):
lflag = Symbol(name='lflag')
gflag = Symbol(name='gflag')
# Init flags
body = [Expression(DummyEq(lflag, 0)), Expression(DummyEq(gflag, 1))]
# For each msg, build an Iteration calling MPI_Test on all peers
for msg in msgs:
dim = Dimension(name='i')
msgi = IndexedPointer(msg, dim)
rrecv = Byref(FieldFromComposite(msg._C_field_rrecv, msgi))
testrecv = Call(
'MPI_Test',
[rrecv, Byref(lflag),
Macro('MPI_STATUS_IGNORE')])
rsend = Byref(FieldFromComposite(msg._C_field_rsend, msgi))
testsend = Call(
'MPI_Test',
[rsend, Byref(lflag),
Macro('MPI_STATUS_IGNORE')])
update = AugmentedExpression(DummyEq(gflag, lflag), '&')
body.append(
Iteration([testsend, update, testrecv, update], dim,
msg.npeers - 1))
body.append(Return(gflag))
return make_efunc('pokempi%d' % key, List(body=body), retval='int')
def _make_copy(self, f, hse, key, swap=False):
buf_dims = []
buf_indices = []
for d in f.dimensions:
if d not in hse.loc_indices:
buf_dims.append(Dimension(name='buf_%s' % d.root))
buf_indices.append(d.root)
buf = Array(name='buf', dimensions=buf_dims, dtype=f.dtype, padding=0)
f_offsets = []
f_indices = []
for d in f.dimensions:
offset = Symbol(name='o%s' % d.root)
f_offsets.append(offset)
f_indices.append(offset +
(d.root if d not in hse.loc_indices else 0))
if swap is False:
eq = DummyEq(buf[buf_indices], f[f_indices])
name = 'gather_%s' % key
else:
eq = DummyEq(f[f_indices], buf[buf_indices])
name = 'scatter_%s' % key
iet = Expression(eq)
for i, d in reversed(list(zip(buf_indices, buf_dims))):
# The -1 below is because an Iteration, by default, generates <=
iet = Iteration(iet,
i,
d.symbolic_size - 1,
properties=(PARALLEL, AFFINE))
parameters = [buf] + list(buf.shape) + [f] + f_offsets
return Callable(name, iet, 'void', parameters, ('static', ))
def __new__(cls, **kwargs):
name = kwargs.pop('name')
grid = kwargs.pop('grid')
time_range = kwargs.pop('time_range')
time_order = kwargs.pop('time_order', 2)
p_dim = kwargs.pop('dimension', Dimension(name='p_%s' % name))
coordinates = kwargs.pop('coordinates',
kwargs.pop('coordinates_data', None))
# Either `npoint` or `coordinates` must be provided
npoint = kwargs.pop('npoint', None)
if npoint is None:
if coordinates is None:
raise TypeError("Need either `npoint` or `coordinates`")
npoint = coordinates.shape[0]
# Create the underlying SparseTimeFunction object
obj = SparseTimeFunction.__new__(cls,
name=name,
grid=grid,
dimensions=(grid.time_dim, p_dim),
npoint=npoint,
nt=time_range.num,
time_order=time_order,
coordinates=coordinates,
**kwargs)
obj._time_range = time_range._rebuild()
# If provided, copy initial data into the allocated buffer
data = kwargs.get('data')
if data is not None:
obj.data[:] = data
return obj
def _make_halowait(self, f, hse, key, msg=None):
cast = cast_mapper[(f.dtype, '*')]
fixed = {d: Symbol(name="o%s" % d.root) for d in hse.loc_indices}
dim = Dimension(name='i')
msgi = IndexedPointer(msg, dim)
bufs = FieldFromComposite(msg._C_field_bufs, msgi)
fromrank = FieldFromComposite(msg._C_field_from, msgi)
sizes = [FieldFromComposite('%s[%d]' % (msg._C_field_sizes, i), msgi)
for i in range(len(f._dist_dimensions))]
ofss = [FieldFromComposite('%s[%d]' % (msg._C_field_ofss, i), msgi)
for i in range(len(f._dist_dimensions))]
ofss = [fixed.get(d) or ofss.pop(0) for d in f.dimensions]
# The `scatter` must be guarded as we must not alter the halo values along
# the domain boundary, where the sender is actually MPI.PROC_NULL
scatter = Call('scatter%s' % key, [cast(bufs)] + sizes + [f] + ofss)
scatter = Conditional(CondNe(fromrank, Macro('MPI_PROC_NULL')), scatter)
rrecv = Byref(FieldFromComposite(msg._C_field_rrecv, msgi))
waitrecv = Call('MPI_Wait', [rrecv, Macro('MPI_STATUS_IGNORE')])
rsend = Byref(FieldFromComposite(msg._C_field_rsend, msgi))
waitsend = Call('MPI_Wait', [rsend, Macro('MPI_STATUS_IGNORE')])
# The -1 below is because an Iteration, by default, generates <=
ncomms = Symbol(name='ncomms')
iet = Iteration([waitsend, waitrecv, scatter], dim, ncomms - 1)
parameters = ([f] + list(fixed.values()) + [msg, ncomms])
return Callable('halowait%d' % key, iet, 'void', parameters, ('static',))
def _make_sendrecv(self, f, hse, key, **kwargs):
comm = f.grid.distributor._obj_comm
buf_dims = [
Dimension(name='buf_%s' % d.root) for d in f.dimensions
if d not in hse.loc_indices
]
bufg = Array(name='bufg',
dimensions=buf_dims,
dtype=f.dtype,
padding=0,
scope='heap')
bufs = Array(name='bufs',
dimensions=buf_dims,
dtype=f.dtype,
padding=0,
scope='heap')
ofsg = [Symbol(name='og%s' % d.root) for d in f.dimensions]
ofss = [Symbol(name='os%s' % d.root) for d in f.dimensions]
fromrank = Symbol(name='fromrank')
torank = Symbol(name='torank')
gather = Call('gather_%s' % key,
[bufg] + list(bufg.shape) + [f] + ofsg)
scatter = Call('scatter_%s' % key,
[bufs] + list(bufs.shape) + [f] + ofss)
# The `gather` is unnecessary if sending to MPI.PROC_NULL
gather = Conditional(CondNe(torank, Macro('MPI_PROC_NULL')), gather)
# The `scatter` must be guarded as we must not alter the halo values along
# the domain boundary, where the sender is actually MPI.PROC_NULL
scatter = Conditional(CondNe(fromrank, Macro('MPI_PROC_NULL')),
scatter)
count = reduce(mul, bufs.shape, 1)
rrecv = MPIRequestObject(name='rrecv')
rsend = MPIRequestObject(name='rsend')
recv = Call('MPI_Irecv', [
bufs, count,
Macro(dtype_to_mpitype(f.dtype)), fromrank,
Integer(13), comm, rrecv
])
send = Call('MPI_Isend', [
bufg, count,
Macro(dtype_to_mpitype(f.dtype)), torank,
Integer(13), comm, rsend
])
waitrecv = Call('MPI_Wait', [rrecv, Macro('MPI_STATUS_IGNORE')])
waitsend = Call('MPI_Wait', [rsend, Macro('MPI_STATUS_IGNORE')])
iet = List(body=[recv, gather, send, waitsend, waitrecv, scatter])
parameters = ([f] + list(bufs.shape) + ofsg + ofss +
[fromrank, torank, comm])
return Callable('sendrecv_%s' % key, iet, 'void', parameters,
('static', ))
def _make_haloupdate(self, f, hse, key, msg=None):
comm = f.grid.distributor._obj_comm
fixed = {d: Symbol(name="o%s" % d.root) for d in hse.loc_indices}
dim = Dimension(name='i')
msgi = IndexedPointer(msg, dim)
bufg = FieldFromComposite(msg._C_field_bufg, msgi)
bufs = FieldFromComposite(msg._C_field_bufs, msgi)
fromrank = FieldFromComposite(msg._C_field_from, msgi)
torank = FieldFromComposite(msg._C_field_to, msgi)
sizes = [
FieldFromComposite('%s[%d]' % (msg._C_field_sizes, i), msgi)
for i in range(len(f._dist_dimensions))
]
ofsg = [
FieldFromComposite('%s[%d]' % (msg._C_field_ofsg, i), msgi)
for i in range(len(f._dist_dimensions))
]
ofsg = [fixed.get(d) or ofsg.pop(0) for d in f.dimensions]
# The `gather` is unnecessary if sending to MPI.PROC_NULL
gather = Call('gather_%s' % key, [bufg] + sizes + [f] + ofsg)
gather = Conditional(CondNe(torank, Macro('MPI_PROC_NULL')), gather)
# Make Irecv/Isend
count = reduce(mul, sizes, 1)
rrecv = Byref(FieldFromComposite(msg._C_field_rrecv, msgi))
rsend = Byref(FieldFromComposite(msg._C_field_rsend, msgi))
recv = Call('MPI_Irecv', [
bufs, count,
Macro(dtype_to_mpitype(f.dtype)), fromrank,
Integer(13), comm, rrecv
])
send = Call('MPI_Isend', [
bufg, count,
Macro(dtype_to_mpitype(f.dtype)), torank,
Integer(13), comm, rsend
])
# The -1 below is because an Iteration, by default, generates <=
ncomms = Symbol(name='ncomms')
iet = Iteration([recv, gather, send], dim, ncomms - 1)
parameters = ([f, comm, msg, ncomms]) + list(fixed.values())
return Callable('haloupdate%d' % key, iet, 'void', parameters,
('static', ))
def _make_remainder(self, hs, key, callcompute, region):
assert callcompute.is_Call
dim = Dimension(name='i')
region_i = IndexedPointer(region, dim)
dynamic_args_mapper = {}
for i in hs.arguments:
if i.is_Dimension:
dynamic_args_mapper[i] = (FieldFromComposite(i.min_name, region_i),
FieldFromComposite(i.max_name, region_i))
else:
dynamic_args_mapper[i] = (FieldFromComposite(i.name, region_i),)
iet = callcompute._rebuild(dynamic_args_mapper=dynamic_args_mapper)
# The -1 below is because an Iteration, by default, generates <=
iet = Iteration(iet, dim, region.nregions - 1)
return make_efunc('remainder%d' % key, iet)
def _make_copy(self, f, fixed, swap=False):
"""
Construct a Callable performing a copy of:
* an arbitrary convex region of ``f`` into a contiguous Array, OR
* if ``swap=True``, a contiguous Array into an arbitrary convex
region of ``f``.
"""
buf_dims = []
buf_indices = []
for d in f.dimensions:
if d not in fixed:
buf_dims.append(Dimension(name='buf_%s' % d.root))
buf_indices.append(d.root)
buf = Array(name='buf', dimensions=buf_dims, dtype=f.dtype)
f_offsets = []
f_indices = []
for d in f.dimensions:
offset = Symbol(name='o%s' % d.root)
f_offsets.append(offset)
f_indices.append(offset + (d.root if d not in fixed else 0))
if swap is False:
eq = DummyEq(buf[buf_indices], f[f_indices])
name = 'gather%dd' % f.ndim
else:
eq = DummyEq(f[f_indices], buf[buf_indices])
name = 'scatter%dd' % f.ndim
iet = Expression(eq)
for i, d in reversed(list(zip(buf_indices, buf_dims))):
# The -1 below is because an Iteration, by default, generates <=
iet = Iteration(iet, i, d.symbolic_size - 1, properties=PARALLEL)
iet = List(body=[ArrayCast(f), ArrayCast(buf), iet])
# Optimize the memory copy with the DLE
from devito.dle import transform
state = transform(iet, 'simd', {'openmp': self._threaded})
parameters = [buf] + list(buf.shape) + [f] + f_offsets + state.input
return Callable(name, state.nodes, 'void', parameters,
('static', )), state.input
def __new__(cls, *args, **kwargs):
options = kwargs.get('options', {})
key = cls._cache_key(*args, **kwargs)
obj = cls._cache_get(key)
if obj is not None:
newobj = sympy.Function.__new__(cls, *args, **options)
newobj.__init_cached__(key)
return newobj
# Not in cache. Create a new PointSouce via devito.SparseTimeFunction
name = kwargs.pop('name')
grid = kwargs.pop('grid')
time_range = kwargs.pop('time_range')
time_order = kwargs.pop('time_order', 2)
p_dim = kwargs.pop('dimension', Dimension(name='p_%s' % name))
coordinates = kwargs.pop('coordinates', kwargs.pop('coordinates_data', None))
# Either `npoint` or `coordinates` must be provided
npoint = kwargs.pop('npoint', None)
if npoint is None:
if coordinates is None:
raise TypeError("Need either `npoint` or `coordinates`")
npoint = coordinates.shape[0]
# Create the underlying SparseTimeFunction object
obj = SparseTimeFunction.__new__(cls, name=name, grid=grid,
dimensions=(grid.time_dim, p_dim),
npoint=npoint, nt=time_range.num,
time_order=time_order,
coordinates=coordinates, **kwargs)
obj._time_range = time_range._rebuild()
# If provided, copy initial data into the allocated buffer
data = kwargs.get('data')
if data is not None:
obj.data[:] = data
return obj
def _make_poke(self, hs, key, msgs):
flag = Symbol(name='flag')
initflag = LocalExpression(DummyEq(flag, 0))
body = [initflag]
for msg in msgs:
dim = Dimension(name='i')
msgi = IndexedPointer(msg, dim)
rrecv = Byref(FieldFromComposite(msg._C_field_rrecv, msgi))
rsend = Byref(FieldFromComposite(msg._C_field_rsend, msgi))
testrecv = Call(
'MPI_Test',
[rrecv, Byref(flag),
Macro('MPI_STATUS_IGNORE')])
testsend = Call(
'MPI_Test',
[rsend, Byref(flag),
Macro('MPI_STATUS_IGNORE')])
body.append(Iteration([testsend, testrecv], dim, msg.npeers - 1))
return make_efunc('pokempi%d' % key, body)
def _make_sendrecv(self, f, fixed, extra=None):
extra = extra or []
comm = f.grid.distributor._obj_comm
buf_dims = [
Dimension(name='buf_%s' % d.root) for d in f.dimensions
if d not in fixed
]
bufg = Array(name='bufg',
dimensions=buf_dims,
dtype=f.dtype,
scope='heap')
bufs = Array(name='bufs',
dimensions=buf_dims,
dtype=f.dtype,
scope='heap')
ofsg = [Symbol(name='og%s' % d.root) for d in f.dimensions]
ofss = [Symbol(name='os%s' % d.root) for d in f.dimensions]
fromrank = Symbol(name='fromrank')
torank = Symbol(name='torank')
args = [bufg] + list(bufg.shape) + [f] + ofsg + extra
gather = Call('gather%dd' % f.ndim, args)
args = [bufs] + list(bufs.shape) + [f] + ofss + extra
scatter = Call('scatter%dd' % f.ndim, args)
# The `gather` is unnecessary if sending to MPI.PROC_NULL
gather = Conditional(CondNe(torank, Macro('MPI_PROC_NULL')), gather)
# The `scatter` must be guarded as we must not alter the halo values along
# the domain boundary, where the sender is actually MPI.PROC_NULL
scatter = Conditional(CondNe(fromrank, Macro('MPI_PROC_NULL')),
scatter)
srecv = MPIStatusObject(name='srecv')
ssend = MPIStatusObject(name='ssend')
rrecv = MPIRequestObject(name='rrecv')
rsend = MPIRequestObject(name='rsend')
count = reduce(mul, bufs.shape, 1)
recv = Call('MPI_Irecv', [
bufs, count,
Macro(dtype_to_mpitype(f.dtype)), fromrank,
Integer(13), comm, rrecv
])
send = Call('MPI_Isend', [
bufg, count,
Macro(dtype_to_mpitype(f.dtype)), torank,
Integer(13), comm, rsend
])
waitrecv = Call('MPI_Wait', [rrecv, srecv])
waitsend = Call('MPI_Wait', [rsend, ssend])
iet = List(body=[recv, gather, send, waitsend, waitrecv, scatter])
iet = List(body=iet_insert_C_decls(iet))
parameters = ([f] + list(bufs.shape) + ofsg + ofss +
[fromrank, torank, comm] + extra)
return Callable('sendrecv%dd' % f.ndim, iet, 'void', parameters,
('static', ))
