Commit 3b18545b authored by Michael Kuron's avatar Michael Kuron
Browse files

Remove old create_staggered_kernel

parent 69e3439d
import itertools
from types import MappingProxyType
import sympy as sp
......@@ -192,120 +191,7 @@ def create_indexed_kernel(assignments,
raise ValueError("Unknown target %s. Has to be either 'cpu' or 'gpu'" % (target,))
def create_staggered_kernel(*args, **kwargs):
"""Kernel that updates a staggered field. Dispatches to either create_staggered_kernel_1 or
create_staggered_kernel_2 depending on the argument types.
"""
if 'staggered_field' in kwargs or type(args[0]) is Field:
return create_staggered_kernel_1(*args, **kwargs)
else:
return create_staggered_kernel_2(*args, **kwargs)
def create_staggered_kernel_1(staggered_field, expressions, subexpressions=(), target='cpu',
gpu_exclusive_conditions=False, **kwargs):
"""Kernel that updates a staggered field.
.. image:: /img/staggered_grid.svg
Args:
staggered_field: field where the first index coordinate defines the location of the staggered value
can have 1 or 2 index coordinates, in case of two index coordinates at every staggered location
a vector is stored, expressions parameter has to be a sequence of sequences then
where e.g. ``f[0,0](0)`` is interpreted as value at the left cell boundary, ``f[1,0](0)`` the right cell
boundary and ``f[0,0](1)`` the southern cell boundary etc.
expressions: sequence of expressions of length dim, defining how the west, southern, (bottom) cell boundary
should be updated.
subexpressions: optional sequence of Assignments, that define subexpressions used in the main expressions
target: 'cpu' or 'gpu'
gpu_exclusive_conditions: if/else construct to have only one code block for each of 2**dim code paths
kwargs: passed directly to create_kernel, iteration slice and ghost_layers parameters are not allowed
Returns:
AST, see `create_kernel`
"""
assert 'iteration_slice' not in kwargs and 'ghost_layers' not in kwargs
assert staggered_field.index_dimensions in (1, 2), 'Staggered field must have one or two index dimensions'
dim = staggered_field.spatial_dimensions
counters = [LoopOverCoordinate.get_loop_counter_symbol(i) for i in range(dim)]
conditions = [counters[i] < staggered_field.shape[i] - 1 for i in range(dim)]
assert len(expressions) == dim
if staggered_field.index_dimensions == 2:
assert all(len(sublist) == len(expressions[0]) for sublist in expressions), \
"If staggered field has two index dimensions expressions has to be a sequence of sequences of all the " \
"same length."
final_assignments = []
last_conditional = None
def add(condition, dimensions, as_else_block=False):
nonlocal last_conditional
if staggered_field.index_dimensions == 1:
assignments = [Assignment(staggered_field(d), expressions[d]) for d in dimensions]
a_coll = AssignmentCollection(assignments, list(subexpressions))
a_coll = a_coll.new_filtered([staggered_field(d) for d in dimensions])
elif staggered_field.index_dimensions == 2:
assert staggered_field.has_fixed_index_shape
assignments = [Assignment(staggered_field(d, i), expr)
for d in dimensions
for i, expr in enumerate(expressions[d])]
a_coll = AssignmentCollection(assignments, list(subexpressions))
a_coll = a_coll.new_filtered([staggered_field(d, i) for i in range(staggered_field.index_shape[1])
for d in dimensions])
sp_assignments = [SympyAssignment(a.lhs, a.rhs) for a in a_coll.all_assignments]
if as_else_block and last_conditional:
new_cond = Conditional(condition, Block(sp_assignments))
last_conditional.false_block = Block([new_cond])
last_conditional = new_cond
else:
last_conditional = Conditional(condition, Block(sp_assignments))
final_assignments.append(last_conditional)
if target == 'cpu' or not gpu_exclusive_conditions:
for d in range(dim):
cond = sp.And(*[conditions[i] for i in range(dim) if d != i])
add(cond, [d])
elif target == 'gpu':
full_conditions = [sp.And(*[conditions[i] for i in range(dim) if d != i]) for d in range(dim)]
for include in itertools.product(*[[1, 0]] * dim):
case_conditions = sp.And(*[c if value else sp.Not(c) for c, value in zip(full_conditions, include)])
dimensions_to_include = [i for i in range(dim) if include[i]]
if dimensions_to_include:
add(case_conditions, dimensions_to_include, True)
ghost_layers = [(1, 0)] * dim
blocking = kwargs.get('cpu_blocking', None)
if blocking:
del kwargs['cpu_blocking']
cpu_vectorize_info = kwargs.get('cpu_vectorize_info', None)
if cpu_vectorize_info:
del kwargs['cpu_vectorize_info']
openmp = kwargs.get('cpu_openmp', None)
if openmp:
del kwargs['cpu_openmp']
ast = create_kernel(final_assignments, ghost_layers=ghost_layers, target=target, **kwargs)
if target == 'cpu':
remove_conditionals_in_staggered_kernel(ast)
move_constants_before_loop(ast)
omp_collapse = None
if blocking:
omp_collapse = loop_blocking(ast, blocking)
if openmp:
from pystencils.cpu import add_openmp
add_openmp(ast, num_threads=openmp, collapse=omp_collapse, assume_single_outer_loop=False)
if cpu_vectorize_info is True:
vectorize(ast)
elif isinstance(cpu_vectorize_info, dict):
vectorize(ast, **cpu_vectorize_info)
return ast
def create_staggered_kernel_2(assignments, gpu_exclusive_conditions=False, **kwargs):
def create_staggered_kernel(assignments, gpu_exclusive_conditions=False, **kwargs):
"""Kernel that updates a staggered field.
.. image:: /img/staggered_grid.svg
......@@ -330,15 +216,15 @@ def create_staggered_kernel_2(assignments, gpu_exclusive_conditions=False, **kwa
subexpressions = ()
if isinstance(assignments, AssignmentCollection):
subexpressions = assignments.subexpressions + [a for a in assignments.main_assignments
if type(a.lhs) is not Field.Access and
not FieldType.is_staggered(a.lhs.field)]
assignments = [a for a in assignments.main_assignments if type(a.lhs) is Field.Access and
FieldType.is_staggered(a.lhs.field)]
if type(a.lhs) is not Field.Access
and not FieldType.is_staggered(a.lhs.field)]
assignments = [a for a in assignments.main_assignments if type(a.lhs) is Field.Access
and FieldType.is_staggered(a.lhs.field)]
else:
subexpressions = [a for a in assignments if type(a.lhs) is not Field.Access and
not FieldType.is_staggered(a.lhs.field)]
assignments = [a for a in assignments if type(a.lhs) is Field.Access and
FieldType.is_staggered(a.lhs.field)]
subexpressions = [a for a in assignments if type(a.lhs) is not Field.Access
and not FieldType.is_staggered(a.lhs.field)]
assignments = [a for a in assignments if type(a.lhs) is Field.Access
and FieldType.is_staggered(a.lhs.field)]
if len(set([tuple(a.lhs.field.staggered_stencil) for a in assignments])) != 1:
raise ValueError("All assignments need to be made to staggered fields with the same stencil")
if len(set([a.lhs.field.shape for a in assignments])) != 1:
......
......@@ -11,8 +11,9 @@ def test_blocking_staggered():
f[0, 0, 0] - f[0, -1, 0],
f[0, 0, 0] - f[0, 0, -1],
]
kernel = ps.create_staggered_kernel(stag, terms, cpu_blocking=(3, 16, 8)).compile()
reference_kernel = ps.create_staggered_kernel(stag, terms).compile()
assignments = [ps.Assignment(stag.staggered_access(d), terms[i]) for i, d in enumerate(stag.staggered_stencil)]
kernel = ps.create_staggered_kernel(assignments, cpu_blocking=(3, 16, 8)).compile()
reference_kernel = ps.create_staggered_kernel(assignments).compile()
print(ps.show_code(kernel.ast))
f_arr = np.random.rand(80, 33, 19)
......
......@@ -55,7 +55,8 @@ def test_staggered_iteration():
for d in range(dim):
expressions.append(sum(f[o] for o in offsets_in_plane(d, 0, dim)) -
sum(f[o] for o in offsets_in_plane(d, -1, dim)))
func_optimized = create_staggered_kernel(s, expressions).compile()
assignments = [ps.Assignment(s.staggered_access(d), expressions[i]) for i, d in enumerate(s.staggered_stencil)]
func_optimized = create_staggered_kernel(assignments).compile()
assert not func_optimized.ast.atoms(Conditional), "Loop cutting optimization did not work"
func(f=f_arr, s=s_arr_ref)
......@@ -111,8 +112,10 @@ def test_staggered_gpu():
s = ps.fields("s({dim}): double[{dim}D]".format(dim=dim), field_type=FieldType.STAGGERED)
expressions = [(f[0, 0] + f[-1, 0]) / 2,
(f[0, 0] + f[0, -1]) / 2]
kernel_ast = ps.create_staggered_kernel(s, expressions, target='gpu', gpu_exclusive_conditions=True)
assignments = [ps.Assignment(s.staggered_access(d), expressions[i]) for i, d in enumerate(s.staggered_stencil)]
kernel_ast = ps.create_staggered_kernel(assignments, target='gpu', gpu_exclusive_conditions=True)
assert len(kernel_ast.atoms(Conditional)) == 4
kernel_ast = ps.create_staggered_kernel(s, expressions, target='gpu', gpu_exclusive_conditions=False)
assignments = [ps.Assignment(s.staggered_access(d), expressions[i]) for i, d in enumerate(s.staggered_stencil)]
kernel_ast = ps.create_staggered_kernel(assignments, target='gpu', gpu_exclusive_conditions=False)
assert len(kernel_ast.atoms(Conditional)) == 3
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