def bfs_sync_pg(graph: PropertyGraph, source, property_name):
next_level_number = 0
curr_level = InsertBag[np.uint64]()
next_level = InsertBag[np.uint64]()
timer = StatTimer("BFS Property Graph Numba: " + property_name)
timer.start()
distance = np.empty((len(graph), ), dtype=np.uint32)
initialize(graph, source, distance)
next_level.push(source)
while not next_level.empty():
curr_level.swap(next_level)
next_level.clear()
next_level_number += 1
do_all(
curr_level,
bfs_sync_operator_pg(graph, next_level, next_level_number,
distance),
steal=True,
loop_name="bfs_sync_pg",
)
timer.stop()
graph.add_node_property(pyarrow.table({property_name: distance}))
def kcore_async(graph: PropertyGraph, k_core_num, property_name):
num_nodes = graph.num_nodes()
initial_worklist = InsertBag[np.uint64]()
current_degree = LargeArray[np.uint64](num_nodes, AllocationPolicy.INTERLEAVED)
timer = StatTimer("Kcore: Property Graph Numba: " + property_name)
timer.start()
# Initialize
do_all(
range(num_nodes), compute_degree_count_operator(graph, current_degree.as_numpy()), steal=True,
)
# Setup initial worklist
do_all(
range(num_nodes),
setup_initial_worklist_operator(initial_worklist, current_degree.as_numpy(), k_core_num),
steal=True,
)
# Compute k-core
for_each(
initial_worklist,
compute_async_kcore_operator(graph, current_degree.as_numpy(), k_core_num),
steal=True,
disable_conflict_detection=True,
)
timer.stop()
# Add the ranks as a new property to the property graph
graph.add_node_property(pyarrow.table({property_name: current_degree}))
def cc_push_topo(graph: PropertyGraph, property_name):
print("Executing Push algo\n")
num_nodes = graph.num_nodes()
timer = StatTimer("CC: Property Graph Numba: " + property_name)
timer.start()
# Stores the component id assignment
comp_current = np.empty((num_nodes, ), dtype=np.uint32)
comp_old = np.empty((num_nodes, ), dtype=np.uint32)
# Initialize
do_all(
range(num_nodes),
initialize_cc_push_operator(graph, comp_current, comp_old),
steal=True,
loop_name="initialize_cc_push",
)
# Execute while component ids are updated
changed = GReduceLogicalOr()
changed.update(True)
while changed.reduce():
changed.reset()
do_all(
range(num_nodes),
cc_push_topo_operator(graph, changed, comp_current, comp_old),
steal=True,
loop_name="cc_push_topo",
)
timer.stop()
# Add the component assignment as a new property to the property graph
graph.add_node_property(pyarrow.table({property_name: comp_current}))
def calculate_degree(graph: PropertyGraph,
in_degree_property,
out_degree_property,
weight_property=None):
"""
Calculate the (potentially weighted) in and out degrees of a graph.
The function will modify the given graph by adding two new node properties,
one for the in degree and one for the out degree. Nothing is returned.
Parameters:
graph: a PropertyGraph
in_degree_property: the property name for the in degree
out_degree_property: the property name for the out degree
weight_property: an edge property to use in calculating the weighted degree
"""
num_nodes = graph.num_nodes()
nout = LargeArray[np.uint64](num_nodes, AllocationPolicy.INTERLEAVED)
nin = LargeArray[np.uint64](num_nodes, AllocationPolicy.INTERLEAVED)
do_all(range(num_nodes), initialize_in_degree(nin.as_numpy()), steal=False)
# are we calculating weighted degree?
if not weight_property:
count_operator = count_in_and_out_degree(graph, nout.as_numpy(),
nin.as_numpy())
else:
count_operator = count_weighted_in_and_out_degree(
graph, nout.as_numpy(), nin.as_numpy(),
graph.get_edge_property(weight_property))
do_all(range(num_nodes), count_operator, steal=True)
graph.add_node_property(
pyarrow.table({
in_degree_property: nin,
out_degree_property: nout
}))
def test_assert_valid(property_graph: PropertyGraph):
with raises(AssertionError):
bfs_assert_valid(property_graph, "workFrom")
property_name = "NewProp"
start_node = 0
bfs(property_graph, start_node, property_name)
v = property_graph.get_node_property(property_name).to_numpy().copy()
v[0] = 100
property_graph.add_node_property(table({"Prop2": v}))
with raises(AssertionError):
bfs_assert_valid(property_graph, "Prop2")
def pagerank_pull_sync_residual(graph: PropertyGraph, maxIterations, tolerance, property_name):
num_nodes = graph.num_nodes()
rank = LargeArray[float](num_nodes, AllocationPolicy.INTERLEAVED)
nout = LargeArray[np.uint64](num_nodes, AllocationPolicy.INTERLEAVED)
delta = LargeArray[float](num_nodes, AllocationPolicy.INTERLEAVED)
residual = LargeArray[float](num_nodes, AllocationPolicy.INTERLEAVED)
# Initialize
do_all(
range(num_nodes),
initialize_residual_operator(rank.as_numpy(), nout.as_numpy(), delta.as_numpy(), residual.as_numpy(),),
steal=True,
loop_name="initialize_pagerank_pull_residual",
)
# Compute out-degree for each node
do_all(
range(num_nodes), compute_out_deg_operator(graph, nout.as_numpy()), steal=True, loop_name="Compute_out_degree",
)
print("Out-degree of 0: ", nout[0])
changed = GReduceLogicalOr(True)
iterations = 0
timer = StatTimer("Pagerank: Property Graph Numba: " + property_name)
timer.start()
while iterations < maxIterations and changed.reduce():
print("Iter: ", iterations, "\n")
changed.reset()
iterations += 1
do_all(
range(num_nodes),
compute_pagerank_pull_delta_operator(
rank.as_numpy(), nout.as_numpy(), delta.as_numpy(), residual.as_numpy(), tolerance, changed,
),
steal=True,
loop_name="pagerank_delta",
)
do_all(
range(num_nodes),
compute_pagerank_pull_residual_operator(graph, delta.as_numpy(), residual.as_numpy()),
steal=True,
loop_name="pagerank",
)
timer.stop()
# Add the ranks as a new property to the property graph
graph.add_node_property(pyarrow.table({property_name: rank}))
def sssp(graph: PropertyGraph, source, length_property, shift, property_name):
dists = create_distance_array(graph, source, length_property)
# Define the struct type here so it can depend on the type of the weight property
UpdateRequest = np.dtype([("src", np.uint32), ("dist", dists.dtype)])
init_bag = InsertBag[UpdateRequest]()
init_bag.push((source, 0))
t = StatTimer("Total SSSP")
t.start()
for_each(
init_bag,
sssp_operator(graph, dists, graph.get_edge_property(length_property)),
worklist=OrderedByIntegerMetric(obim_indexer(shift)),
disable_conflict_detection=True,
loop_name="SSSP",
)
t.stop()
print("Elapsed time: ", t.get(), "milliseconds.")
graph.add_node_property(pyarrow.table({property_name: dists}))
