def can_be_applied(self, sdfg: SDFG, subgraph: SubgraphView) -> bool:
# get lowest scope maps of subgraph
# grab first node and see whether all nodes are in the same graph
# (or nested sdfgs therein)
graph = subgraph.graph
# next, get all the maps by obtaining a copy (for potential offsets)
map_entries = helpers.get_outermost_scope_maps(sdfg, graph, subgraph)
ranges = [dcpy(map_entry.range) for map_entry in map_entries]
# offset if option is toggled
if self.allow_offset == True:
for r in ranges:
r.offset(r.min_element(), negative=True)
brng = helpers.common_map_base_ranges(ranges)
# more than one outermost scoped map entry has to be availble
if len(map_entries) <= 1:
return False
# check whether any parameters are in common
if len(brng) == 0:
return False
# if option enabled, return false if any splits are introduced
if self.permutation_only == True:
for map_entry in map_entries:
if len(map_entry.params) != len(brng):
return False
# if option enabled, check contiguity in the last contiguous dimension
# if there is a map split ocurring with the last contiguous dimension being
# in the *outer* map, we fail (-> bad data access pattern)
if self.check_contiguity == True:
reassignment = helpers.find_reassignment(map_entries,
brng,
offset=self.allow_offset)
for map_entry in map_entries:
no_common = sum(
[1 for j in reassignment[map_entry] if j != -1])
if no_common != len(map_entry.params):
# check every memlet for access
for e in itertools.chain(
graph.out_edges(map_entry),
graph.in_edges(graph.exit_node(map_entry))):
subset = dcpy(e.data.subset)
subset.pop([i for i in range(subset.dims() - 1)])
for s in subset.free_symbols:
if reassignment[map_entry][
map_entry.map.params.index(s)] != -1:
warnings.warn(
"MultiExpansion::Contiguity fusion violation detected"
)
return False
return True
def match(sdfg: SDFG, subgraph: SubgraphView) -> bool:
### get lowest scope maps of subgraph
# grab first node and see whether all nodes are in the same graph
# (or nested sdfgs therein)
graph = subgraph.graph
for node in subgraph.nodes():
if node not in graph.nodes():
return False
# next, get all the maps
maps = helpers.get_highest_scope_maps(sdfg, graph, subgraph)
brng = helpers.common_map_base_ranges(maps)
# if leq than one map found -> fail
if len(maps) <= 1:
return False
# see whether they have common parameters; if not -> fail
if len(brng) == 0:
return False
return True
def expand(self, sdfg, graph, map_entries, map_base_variables=None):
"""
Expansion into outer and inner maps for each map in a specified set.
The resulting outer maps all have same range and indices, corresponding
variables and memlets get changed accordingly. The inner map contains
the leftover dimensions
:param sdfg: Underlying SDFG
:param graph: Graph in which we expand
:param map_entries: List of Map Entries(Type MapEntry) that we want to expand
:param map_base_variables: Optional parameter. List of strings
If None, then expand() searches for the maximal amount
of equal map ranges and pushes those and their corresponding
loop variables into the outer loop.
If specified, then expand() pushes the ranges belonging
to the loop iteration variables specified into the outer loop
(For instance map_base_variables = ['i','j'] assumes that
all maps have common iteration indices i and j with corresponding
correct ranges)
"""
maps = [entry.map for entry in map_entries]
if not map_base_variables:
# find the maximal subset of variables to expand
# greedy if there exist multiple ranges that are equal in a map
map_base_ranges = helpers.common_map_base_ranges(maps)
reassignments = helpers.find_reassignment(maps, map_base_ranges)
##### first, regroup and reassign
# create params_dict for every map
# first, let us define the outer iteration variable names,
# just take the first map and their indices at common ranges
map_base_variables = []
for rng in map_base_ranges:
for i in range(len(maps[0].params)):
if maps[0].range[i] == rng and maps[0].params[
i] not in map_base_variables:
map_base_variables.append(maps[0].params[i])
break
params_dict = {}
if self.debug:
print("MultiExpansion::Map_base_variables:", map_base_variables)
print("MultiExpansion::Map_base_ranges:", map_base_ranges)
for map in maps:
# for each map create param dict, first assign identity
params_dict_map = {param: param for param in map.params}
# now look for the correct reassignment
# for every element neq -1, need to change param to map_base_variables[]
# if param already appears in own dict, do a swap
# else we just replace it
for i, reassignment in enumerate(reassignments[map]):
if reassignment == -1:
# nothing to do
pass
else:
current_var = map.params[i]
current_assignment = params_dict_map[current_var]
target_assignment = map_base_variables[reassignment]
if current_assignment != target_assignment:
if target_assignment in params_dict_map.values():
# do a swap
key1 = current_var
for key, value in params_dict_map.items():
if value == target_assignment:
key2 = key
value1 = params_dict_map[key1]
value2 = params_dict_map[key2]
params_dict_map[key1] = key2
params_dict_map[key2] = key1
else:
# just reassign
params_dict_map[current_var] = target_assignment
# done, assign params_dict_map to the global one
params_dict[map] = params_dict_map
for map, map_entry in zip(maps, map_entries):
map_scope = graph.scope_subgraph(map_entry)
params_dict_map = params_dict[map]
for firstp, secondp in params_dict_map.items():
if firstp != secondp:
replace(map_scope, firstp, '__' + firstp + '_fused')
for firstp, secondp in params_dict_map.items():
if firstp != secondp:
replace(map_scope, '__' + firstp + '_fused', secondp)
# now also replace the map variables inside maps
for i in range(len(map.params)):
map.params[i] = params_dict_map[map.params[i]]
if self.debug:
print("MultiExpansion::Params replaced")
else:
# just calculate map_base_ranges
# do a check whether all maps correct
map_base_ranges = []
map0 = maps[0]
for var in map_base_variables:
index = map0.params.index(var)
map_base_ranges.append(map0.range[index])
for map in maps:
for var, rng in zip(map_base_variables, map_base_ranges):
assert map.range[map.params.index(var)] == rng
# then expand all the maps
for map, map_entry in zip(maps, map_entries):
if map.get_param_num() == len(map_base_variables):
# nothing to expand, continue
continue
map_exit = graph.exit_node(map_entry)
# create two new maps, outer and inner
params_outer = map_base_variables
ranges_outer = map_base_ranges
init_params_inner = []
init_ranges_inner = []
for param, rng in zip(map.params, map.range):
if param in map_base_variables:
continue
else:
init_params_inner.append(param)
init_ranges_inner.append(rng)
params_inner = init_params_inner
ranges_inner = subsets.Range(init_ranges_inner)
inner_map = nodes.Map(label = map.label + '_inner',
params = params_inner,
ndrange = ranges_inner,
schedule = dtypes.ScheduleType.Sequential \
if self.sequential_innermaps \
else dtypes.ScheduleType.Default)
map.label = map.label + '_outer'
map.params = params_outer
map.range = ranges_outer
# create new map entries and exits
map_entry_inner = nodes.MapEntry(inner_map)
map_exit_inner = nodes.MapExit(inner_map)
# analogously to Map_Expansion
for edge in graph.out_edges(map_entry):
graph.remove_edge(edge)
graph.add_memlet_path(map_entry,
map_entry_inner,
edge.dst,
src_conn=edge.src_conn,
memlet=edge.data,
dst_conn=edge.dst_conn)
dynamic_edges = dynamic_map_inputs(graph, map_entry)
for edge in dynamic_edges:
# Remove old edge and connector
graph.remove_edge(edge)
edge.dst._in_connectors.remove(edge.dst_conn)
# Propagate to each range it belongs to
path = []
for mapnode in [map_entry, map_entry_inner]:
path.append(mapnode)
if any(edge.dst_conn in map(str, symbolic.symlist(r))
for r in mapnode.map.range):
graph.add_memlet_path(edge.src,
*path,
memlet=edge.data,
src_conn=edge.src_conn,
dst_conn=edge.dst_conn)
for edge in graph.in_edges(map_exit):
graph.remove_edge(edge)
graph.add_memlet_path(edge.src,
map_exit_inner,
map_exit,
memlet=edge.data,
src_conn=edge.src_conn,
dst_conn=edge.dst_conn)