def __call__(self, machine_graph, machine):
""" Place a machine_graph so that each vertex is placed on a core
:param machine_graph: The machine_graph to place
:type machine_graph:\
:py:class:`pacman.model.graphs.machine.MachineGraph`
:return: A set of placements
:rtype: :py:class:`pacman.model.placements.Placements`
:raise pacman.exceptions.PacmanPlaceException: \
If something goes wrong with the placement
"""
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
placements = Placements()
vertices = sort_vertices_by_known_constraints(machine_graph.vertices)
# Iterate over vertices and generate placements
progress = ProgressBar(vertices, "Placing graph vertices")
resource_tracker = ResourceTracker(machine)
for vertex in progress.over(vertices):
# Create and store a new placement anywhere on the board
(x, y, p, _, _) = resource_tracker.allocate_constrained_resources(
vertex.resources_required, vertex.constraints, None)
placement = Placement(vertex, x, y, p)
placements.add_placement(placement)
return placements
def __call__(self, machine_graph, machine, plan_n_timesteps):
""" Place each vertex in a machine graph on a core in the machine.
:param MachineGraph machine_graph: The machine_graph to place
:param ~spinn_machine.Machine machine: A SpiNNaker machine object.
:param int plan_n_timesteps: number of timesteps to plan for
:return placements: Placements of vertices on the machine
:rtype: Placements
"""
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
placements = Placements()
vertices = sort_vertices_by_known_constraints(machine_graph.vertices)
# Iterate over vertices and generate placements
progress = ProgressBar(machine_graph.n_vertices,
"Placing graph vertices")
resource_tracker = ResourceTracker(
machine, plan_n_timesteps, self._generate_random_chips(machine))
vertices_on_same_chip = get_same_chip_vertex_groups(machine_graph)
vertices_placed = set()
for vertex in progress.over(vertices):
if vertex not in vertices_placed:
vertices_placed.update(
self._place_vertex(vertex, resource_tracker, machine,
placements, vertices_on_same_chip))
return placements
def __call__(self, machine_graph, machine, plan_n_timesteps):
""" Place a machine_graph so that each vertex is placed on a core
:param machine_graph: The machine_graph to place
:type machine_graph:\
:py:class:`pacman.model.graphs.machine.MachineGraph`
:param machine:\
The machine with respect to which to partition the application\
graph
:type machine: :py:class:`spinn_machine.Machine`
:param plan_n_timesteps: number of timesteps to plan for
:type plan_n_timesteps: int
:return: A set of placements
:rtype: :py:class:`pacman.model.placements.Placements`
:raise pacman.exceptions.PacmanPlaceException: \
If something goes wrong with the placement
"""
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
placements = Placements()
vertices = sort_vertices_by_known_constraints(machine_graph.vertices)
# Iterate over vertices and generate placements
progress = ProgressBar(vertices, "Placing graph vertices")
resource_tracker = ResourceTracker(machine, plan_n_timesteps)
for vertex in progress.over(vertices):
# Create and store a new placement anywhere on the board
(x, y, p, _, _) = resource_tracker.allocate_constrained_resources(
vertex.resources_required, vertex.constraints, None)
placement = Placement(vertex, x, y, p)
placements.add_placement(placement)
return placements
def __call__(self, machine_graph, machine, plan_n_timesteps):
""" Place each vertex in a machine graph on a core in the machine.
:param machine_graph: The machine_graph to place
:type machine_graph:\
:py:class:`pacman.model.graphs.machine.MachineGraph`
:param machine: A SpiNNaker machine object.
:type machine: :py:class:`spinn_machine.Machine`
:param plan_n_timesteps: number of timesteps to plan for
:type plan_n_timesteps: int
:return placements: Placements of vertices on the machine
:rtype :py:class:`pacman.model.placements.Placements`
"""
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
placements = Placements()
vertices = sort_vertices_by_known_constraints(machine_graph.vertices)
# Iterate over vertices and generate placements
progress = ProgressBar(machine_graph.n_vertices,
"Placing graph vertices")
resource_tracker = ResourceTracker(
machine, plan_n_timesteps, self._generate_random_chips(machine))
vertices_on_same_chip = get_same_chip_vertex_groups(machine_graph)
vertices_placed = set()
for vertex in progress.over(vertices):
if vertex not in vertices_placed:
vertices_placed.update(self._place_vertex(
vertex, resource_tracker, machine, placements,
vertices_on_same_chip))
return placements
def __gather_placements_with_tags(placement, collector):
"""
:param Placement placement:
:param list(Placement) collector:
"""
requires = placement.vertex.resources_required
if requires.iptags or requires.reverse_iptags:
ResourceTracker.check_constraints([placement.vertex])
collector.append(placement)
def _check_constraints(self,
vertices,
additional_placement_constraints=None):
if additional_placement_constraints is not None:
placement_constraints = additional_placement_constraints
else:
placement_constraints = {}
ResourceTracker.check_constraints(
vertices, additional_placement_constraints=placement_constraints)
def _check_constraints(
self, vertices, additional_placement_constraints=None):
placement_constraints = {
RadialPlacementFromChipConstraint, SameChipAsConstraint
}
if additional_placement_constraints is not None:
placement_constraints.update(additional_placement_constraints)
ResourceTracker.check_constraints(
vertices, additional_placement_constraints=placement_constraints)
def _check_constraints(self,
vertices,
additional_placement_constraints=None):
placement_constraints = {
RadialPlacementFromChipConstraint, SameChipAsConstraint
}
if additional_placement_constraints is not None:
placement_constraints.update(additional_placement_constraints)
ResourceTracker.check_constraints(
vertices, additional_placement_constraints=placement_constraints)
def test_n_cores_available(self):
machine = virtual_machine(width=2, height=2, n_cpus_per_chip=18)
chip = machine.get_chip_at(0, 0)
preallocated_resources = PreAllocatedResourceContainer(
specific_core_resources=[
SpecificCoreResource(chip=chip, cores=[1])
],
core_resources=[CoreResource(chip=chip, n_cores=2)])
tracker = ResourceTracker(
machine,
plan_n_timesteps=None,
preallocated_resources=preallocated_resources)
# Should be 14 cores = 18 - 1 monitor - 1 specific core - 2 other cores
self.assertEqual(tracker._n_cores_available(chip, (0, 0), None), 14)
# Should be 0 since the core is already pre allocated
self.assertEqual(tracker._n_cores_available(chip, (0, 0), 1), 0)
# Should be 1 since the core is not pre allocated
self.assertEqual(tracker._n_cores_available(chip, (0, 0), 2), 1)
# Should be 0 since the core is monitor
self.assertEqual(tracker._n_cores_available(chip, (0, 0), 0), 0)
# Allocate a core
tracker._allocate_core(chip, (0, 0), 2)
# Should be 13 cores as one now allocated
self.assertEqual(tracker._n_cores_available(chip, (0, 0), None), 13)
def test_allocate_resources_when_chip_used(self):
router = Router([])
sdram = SDRAM()
empty_chip = Chip(
0, 0, [], router, sdram, 0, 0, "127.0.0.1",
virtual=False, tag_ids=[1])
machine = Machine([empty_chip], 0, 0)
resource_tracker = ResourceTracker(machine, plan_n_timesteps=None)
with self.assertRaises(PacmanValueError):
resource_tracker.allocate_resources(
ResourceContainer(sdram=ConstantSDRAM(1024)))
def test_deallocation_of_resources(self):
machine = VirtualMachine(
width=2, height=2, n_cpus_per_chip=18, with_monitors=True)
chip_sdram = machine.get_chip_at(1, 1).sdram.size
res_sdram = 12345
tracker = ResourceTracker(machine, plan_n_timesteps=None,
preallocated_resources=None)
sdram_res = ConstantSDRAM(res_sdram)
resources = ResourceContainer(sdram=sdram_res)
chip_0 = machine.get_chip_at(0, 0)
# verify core tracker is empty
if (0, 0) in tracker._core_tracker:
raise Exception("shouldnt exist")
# verify sdram tracker
if tracker._sdram_tracker[0, 0] != chip_sdram:
raise Exception("incorrect sdram of {}".format(
tracker._sdram_tracker[0, 0]))
# allocate some res
chip_x, chip_y, processor_id, ip_tags, reverse_ip_tags = \
tracker.allocate_resources(resources, [(0, 0)])
# verify chips used is updated
cores = list(tracker._core_tracker[(0, 0)])
self.assertEqual(len(cores), chip_0.n_user_processors - 1)
# verify sdram used is updated
sdram = tracker._sdram_tracker[(0, 0)]
self.assertEqual(sdram, chip_sdram-res_sdram)
if (0, 0) not in tracker._chips_used:
raise Exception("should exist")
# deallocate res
tracker.unallocate_resources(
chip_x, chip_y, processor_id, resources, ip_tags, reverse_ip_tags)
# verify chips used is updated
if ((0, 0) in tracker._core_tracker and
len(tracker._core_tracker[(0, 0)]) !=
chip_0.n_user_processors):
raise Exception("shouldn't exist or should be right size")
if (0, 0) in tracker._chips_used:
raise Exception("shouldnt exist")
# verify sdram tracker
if tracker._sdram_tracker[0, 0] != chip_sdram:
raise Exception("incorrect sdram of {}".format(
tracker._sdram_tracker[0, 0]))
def test_deallocation_of_resources(self):
machine = virtual_machine(width=2, height=2, n_cpus_per_chip=18)
chip_sdram = machine.get_chip_at(1, 1).sdram.size
res_sdram = 12345
tracker = ResourceTracker(machine,
plan_n_timesteps=None,
preallocated_resources=None)
sdram_res = ConstantSDRAM(res_sdram)
resources = ResourceContainer(sdram=sdram_res)
chip_0 = machine.get_chip_at(0, 0)
# verify core tracker is empty
if (0, 0) in tracker._core_tracker:
raise Exception("shouldnt exist")
# verify sdram tracker
if tracker._sdram_tracker[0, 0] != chip_sdram:
raise Exception("incorrect sdram of {}".format(
tracker._sdram_tracker[0, 0]))
# allocate some res
chip_x, chip_y, processor_id, ip_tags, reverse_ip_tags = \
tracker.allocate_resources(resources, [(0, 0)])
# verify chips used is updated
cores = list(tracker._core_tracker[(0, 0)])
self.assertEqual(len(cores), chip_0.n_user_processors - 1)
# verify sdram used is updated
sdram = tracker._sdram_tracker[(0, 0)]
self.assertEqual(sdram, chip_sdram - res_sdram)
if (0, 0) not in tracker._chips_used:
raise Exception("should exist")
# deallocate res
tracker.unallocate_resources(chip_x, chip_y, processor_id, resources,
ip_tags, reverse_ip_tags)
# verify chips used is updated
if ((0, 0) in tracker._core_tracker and len(
tracker._core_tracker[(0, 0)]) != chip_0.n_user_processors):
raise Exception("shouldn't exist or should be right size")
if (0, 0) in tracker._chips_used:
raise Exception("shouldnt exist")
# verify sdram tracker
if tracker._sdram_tracker[0, 0] != chip_sdram:
raise Exception("incorrect sdram of {}".format(
tracker._sdram_tracker[0, 0]))
def test_n_cores_available(self):
machine = VirtualMachine(
width=2, height=2, n_cpus_per_chip=18, with_monitors=True)
chip = machine.get_chip_at(0, 0)
preallocated_resources = PreAllocatedResourceContainer(
specific_core_resources=[
SpecificCoreResource(chip=chip, cores=[1])],
core_resources=[
CoreResource(chip=chip, n_cores=2)])
tracker = ResourceTracker(
machine, plan_n_timesteps=None,
preallocated_resources=preallocated_resources)
# Should be 14 cores = 18 - 1 monitor - 1 specific core - 2 other cores
self.assertEqual(tracker._n_cores_available(chip, (0, 0), None), 14)
# Should be 0 since the core is already pre allocated
self.assertEqual(tracker._n_cores_available(chip, (0, 0), 1), 0)
# Should be 1 since the core is not pre allocated
self.assertEqual(tracker._n_cores_available(chip, (0, 0), 2), 1)
# Should be 0 since the core is monitor
self.assertEqual(tracker._n_cores_available(chip, (0, 0), 0), 0)
# Allocate a core
tracker._allocate_core(chip, (0, 0), 2)
# Should be 13 cores as one now allocated
self.assertEqual(tracker._n_cores_available(chip, (0, 0), None), 13)
def __call__(self,
nengo_operator_graph,
machine,
nengo_random_number_generator,
pre_allocated_resources=None):
machine_graph = MachineGraph(label=constants.MACHINE_GRAPH_LABEL)
graph_mapper = GraphMapper()
self._resource_tracker = ResourceTracker(
machine, preallocated_resources=pre_allocated_resources)
progress_bar = ProgressBar(
total_number_of_things_to_do=(
len(nengo_operator_graph.vertices) +
len(nengo_operator_graph.outgoing_edge_partitions)),
string_describing_what_being_progressed="partitioning")
# convert application vertices into machine vertices
for operator in progress_bar.over(nengo_operator_graph.vertices,
False):
# create the machine verts
operator.create_machine_vertices(self._resource_tracker,
machine_graph, graph_mapper)
self._handle_edges(nengo_operator_graph, machine_graph, graph_mapper,
progress_bar, nengo_random_number_generator)
return machine_graph, graph_mapper, self._resource_tracker.chips_used
def __call__(self, machine, placements):
""" See :py:meth:`AbstractTagAllocatorAlgorithm.allocate_tags`
"""
resource_tracker = ResourceTracker(machine)
# Keep track of ports allocated to reverse IP tags and tags that still
# need a port to be allocated
ports_to_allocate = dict()
tags_to_allocate_ports = list()
# Check that the algorithm can handle the constraints
progress = ProgressBar(placements.n_placements, "Discovering tags")
placements_with_tags = list()
for placement in progress.over(placements.placements):
self._gather_placements_with_tags(placement, placements_with_tags)
# Go through and allocate the IP tags and constrained reverse IP tags
tags = Tags()
progress = ProgressBar(placements_with_tags, "Allocating tags")
for placement in progress.over(placements_with_tags):
self._allocate_tags_for_placement(placement, resource_tracker,
tags, ports_to_allocate,
tags_to_allocate_ports)
# Finally allocate ports to the unconstrained reverse IP tags
self._allocate_ports_for_reverse_ip_tags(tags_to_allocate_ports,
ports_to_allocate, tags)
return list(tags.ip_tags), list(tags.reverse_ip_tags), tags
def _check_constraints(
self, vertices, additional_placement_constraints=None):
""" Ensure that the algorithm conforms to any required constraints.
:param list(AbstractVertex) vertices:
The vertices for which to check the constraints
:param set(AbstractPlacerConstraint) additional_placement_constraints:
Additional placement constraints supported by the algorithm doing
this check
"""
placement_constraints = {SameChipAsConstraint}
if additional_placement_constraints is not None:
placement_constraints.update(additional_placement_constraints)
ResourceTracker.check_constraints(
vertices, additional_placement_constraints=placement_constraints)
def __call__(self, machine_graph, machine, plan_n_timesteps):
"""
:param MachineGraph machine_graph: The machine_graph to place
:param ~spinn_machine.Machine machine: A SpiNNaker machine object.
:param int plan_n_timesteps: number of timesteps to plan for
:return: Placements of vertices on the machine
:rtype: Placements
"""
# check that the algorithm can handle the constraints
self._check_constraints(
machine_graph.vertices,
additional_placement_constraints={SameChipAsConstraint})
# in order to test isomorphism include:
# placements_copy = Placements()
placements = Placements()
vertices = sort_vertices_by_known_constraints(machine_graph.vertices)
progress = ProgressBar(
machine_graph.n_vertices, "Placing graph vertices")
resource_tracker = ResourceTracker(
machine, plan_n_timesteps, self._generate_hilbert_chips(machine))
# get vertices which must be placed on the same chip
vertices_on_same_chip = get_same_chip_vertex_groups(machine_graph)
# iterate over vertices and generate placements
all_vertices_placed = set()
for vertex in progress.over(vertices):
if vertex not in all_vertices_placed:
vertices_placed = self._place_vertex(
vertex, resource_tracker, machine,
placements, vertices_on_same_chip)
all_vertices_placed.update(vertices_placed)
return placements
def __setup_objects(self, app_graph, machine, plan_n_time_steps,
pre_allocated_resources):
""" sets up the machine_graph, resource_tracker, vertices, \
progress bar.
:param ApplicationGraph app_graph: app graph
:param ~spinn_machine.Machine machine: machine
:param int plan_n_time_steps: the number of time steps to run for.
:param pre_allocated_resources: pre allocated res from other systems.
:type PreAllocatedResourceContainer or None
:return: (machine graph, res tracker, verts, progress bar)
:rtype: tuple(MachineGraph, ResourceTracker, list(ApplicationVertex),
~.ProgressBar)
"""
# Load the vertices and create the machine_graph to fill
machine_graph = MachineGraph(label="partitioned graph for {}".format(
app_graph.label),
application_graph=app_graph)
resource_tracker = ResourceTracker(
machine,
plan_n_time_steps,
preallocated_resources=pre_allocated_resources)
# sort out vertex's by placement constraints
vertices = sort_vertices_by_known_constraints(app_graph.vertices)
# Group vertices that are supposed to be the same size
self.order_vertices_for_dependent_splitters(vertices)
# Set up the progress
progress = ProgressBar(len(app_graph.vertices),
self.__PROGRESS_BAR_VERTICES)
return machine_graph, resource_tracker, vertices, progress
def __call__(self, machine_graph, machine, plan_n_timesteps):
"""
:param MachineGraph machine_graph: The machine_graph to place
:param ~spinn_machine.Machine machine:
The machine with respect to which to partition the application
graph
:param int plan_n_timesteps: number of timesteps to plan for
:return: A set of placements
:rtype: Placements
:raise PacmanPlaceException:
If something goes wrong with the placement
"""
# check that the algorithm can handle the constraints
self._check_constraints(machine_graph.vertices)
placements = Placements()
vertices = sort_vertices_by_known_constraints(machine_graph.vertices)
# Iterate over vertices and generate placements
progress = ProgressBar(machine_graph.n_vertices,
"Placing graph vertices")
resource_tracker = ResourceTracker(
machine, plan_n_timesteps, self._generate_radial_chips(machine))
vertices_on_same_chip = get_same_chip_vertex_groups(machine_graph)
all_vertices_placed = set()
for vertex in progress.over(vertices):
if vertex not in all_vertices_placed:
vertices_placed = self._place_vertex(vertex, resource_tracker,
machine, placements,
vertices_on_same_chip,
machine_graph)
all_vertices_placed.update(vertices_placed)
return placements
def test_allocate_resources_when_chip_used(self):
router = Router([])
sdram = SDRAM()
empty_chip = Chip(0,
0, [],
router,
sdram,
0,
0,
"127.0.0.1",
virtual=False,
tag_ids=[1])
machine = Machine([empty_chip], 0, 0)
resource_tracker = ResourceTracker(machine)
with self.assertRaises(PacmanValueError):
resource_tracker.allocate_resources(
ResourceContainer(sdram=SDRAMResource(1024)))
def __allocate_tags_for_placement(placement, resource_tracker, tag_collector,
ports_collector, tag_port_tasks):
"""
:param Placement placement:
:param ResourceTracker resource_tracker:
:param Tags tag_collector:
:param dict(str,set(int)) ports_collector:
:param list(_Task) tag_port_tasks:
"""
vertex = placement.vertex
resources = vertex.resources_required
# Get the constraint details for the tags
(board_address, ip_tags, reverse_ip_tags) = \
ResourceTracker.get_ip_tag_info(resources, vertex.constraints)
# Allocate the tags, first-come, first-served, using the fixed
# placement of the vertex, and the required resources
chips = [(placement.x, placement.y)]
(_, _, _, returned_ip_tags, returned_reverse_ip_tags) = \
resource_tracker.allocate_resources(
resources, chips, placement.p, board_address, ip_tags,
reverse_ip_tags)
# Put the allocated IP tag information into the tag object
if returned_ip_tags is not None:
for (tag_constraint, (board_address, tag, dest_x, dest_y)) in \
zip(ip_tags, returned_ip_tags):
ip_tag = IPTag(
board_address=board_address,
destination_x=dest_x,
destination_y=dest_y,
tag=tag,
ip_address=tag_constraint.ip_address,
port=tag_constraint.port,
strip_sdp=tag_constraint.strip_sdp,
traffic_identifier=tag_constraint.traffic_identifier)
tag_collector.add_ip_tag(ip_tag, vertex)
if returned_reverse_ip_tags is None:
return
# Put the allocated reverse IP tag information into the tag object
for tag_constraint, (board_address, tag) in zip(reverse_ip_tags,
returned_reverse_ip_tags):
if board_address not in ports_collector:
ports_collector[board_address] = OrderedSet(_BOARD_PORTS)
if tag_constraint.port is not None:
reverse_ip_tag = ReverseIPTag(board_address, tag,
tag_constraint.port, placement.x,
placement.y, placement.p,
tag_constraint.sdp_port)
tag_collector.add_reverse_ip_tag(reverse_ip_tag, vertex)
ports_collector[board_address].discard(tag_constraint.port)
else:
tag_port_tasks.append(
_Task(tag_constraint, board_address, tag, vertex, placement))
def __call__(self,
app_graph,
machine,
plan_n_time_steps,
pre_allocated_resources=None):
"""
:param ApplicationGraph app_graph: The application_graph to partition
:param ~spinn_machine.Machine machine:
The machine with respect to which to partition the application
graph
:param plan_n_time_steps:
the number of time steps to plan to run for
:type plan_n_time_steps: int or None
:param pre_allocated_resources:
res needed to be preallocated before making new machine vertices
:type pre_allocated_resources: PreAllocatedResourceContainer or None
:return:
A machine_graph of partitioned vertices and partitioned edges,
and the number of chips needed to satisfy this partitioning.
:rtype: tuple(MachineGraph, int)
:raise PacmanPartitionException:
If something goes wrong with the partitioning
"""
# check resource tracker can handle constraints
ResourceTracker.check_constraints(app_graph.vertices)
# get the setup objects
(machine_graph, resource_tracker, vertices,
progress) = (self.__setup_objects(app_graph, machine,
plan_n_time_steps,
pre_allocated_resources))
self.__set_max_atoms_to_splitters(app_graph)
# Partition one vertex at a time
for vertex in progress.over(vertices):
vertex.splitter.split(resource_tracker, machine_graph)
# process edges
self.__process_machine_edges(app_graph, machine_graph,
resource_tracker)
# return the accepted things
return machine_graph, resource_tracker.chips_used
def _check_constraints(
self, vertices, additional_placement_constraints=None):
""" Ensure that the algorithm conforms to any required constraints.
:param vertices: The vertices for which to check the constraints
:type vertices: dict()
:param additional_placement_constraints:\
Additional placement constraints supported by the algorithm doing\
this check
:type additional_placement_constraints: set of \
:py:class:`pacman.model.constraints.placer_constraints.AbstractPlacerConstraint`
"""
placement_constraints = {SameChipAsConstraint}
if additional_placement_constraints is not None:
placement_constraints.update(additional_placement_constraints)
ResourceTracker.check_constraints(
vertices, additional_placement_constraints=placement_constraints)
def test_allocate_resources_when_chip_used(self):
router = Router([])
sdram = SDRAM()
empty_chip = Chip(0,
0,
1,
router,
sdram,
0,
0,
"127.0.0.1",
virtual=False,
tag_ids=[1])
machine = machine_from_chips([empty_chip])
resource_tracker = ResourceTracker(machine, plan_n_timesteps=None)
with self.assertRaises(PacmanValueError):
resource_tracker.allocate_resources(
ResourceContainer(sdram=ConstantSDRAM(1024)))
def __call__(self, machine_graph, machine):
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
placements = Placements()
vertices = sort_vertices_by_known_constraints(machine_graph.vertices)
# Iterate over vertices and generate placements
progress = ProgressBar(machine_graph.n_vertices,
"Placing graph vertices")
resource_tracker = ResourceTracker(
machine, self._generate_random_chips(machine))
vertices_on_same_chip = get_same_chip_vertex_groups(machine_graph)
vertices_placed = set()
for vertex in progress.over(vertices):
if vertex not in vertices_placed:
vertices_placed.update(
self._place_vertex(vertex, resource_tracker, machine,
placements, vertices_on_same_chip))
return placements
def __call__(self, machine_graph, machine):
"""
:param machine_graph: The machine_graph to measure
:type machine_graph:\
:py:class:`pacman.model.graph.machine.MachineGraph`
:return: The size of the graph in number of chips
:rtype: int
"""
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
ordered_vertices = sort_vertices_by_known_constraints(
machine_graph.vertices)
# Iterate over vertices and allocate
progress = ProgressBar(machine_graph.n_vertices, "Measuring the graph")
resource_tracker = ResourceTracker(machine)
for vertex in progress.over(ordered_vertices):
resource_tracker.allocate_constrained_resources(
vertex.resources_required, vertex.constraints)
return len(resource_tracker.keys)
def __call__(self, graph, machine, plan_n_timesteps):
"""
:param graph: The application_graph to partition
:type graph:\
:py:class:`pacman.model.graphs.application.ApplicationGraph`
:param machine:\
The machine with respect to which to partition the application\
graph
:type machine: :py:class:`spinn_machine.Machine`
:param plan_n_timesteps: number of timesteps to plan for
:type plan_n_timesteps: int
:return: A machine graph
:rtype:\
:py:class:`pacman.model.graphs.machine.MachineGraph`
:raise pacman.exceptions.PacmanPartitionException:\
If something goes wrong with the partitioning
"""
ResourceTracker.check_constraints(graph.vertices)
utility_calls.check_algorithm_can_support_constraints(
constrained_vertices=graph.vertices,
supported_constraints=[
MaxVertexAtomsConstraint, FixedVertexAtomsConstraint],
abstract_constraint_type=AbstractPartitionerConstraint)
# start progress bar
progress = ProgressBar(graph.n_vertices, "Partitioning graph vertices")
machine_graph = MachineGraph("Machine graph for " + graph.label)
graph_mapper = GraphMapper()
resource_tracker = ResourceTracker(machine, plan_n_timesteps)
# Partition one vertex at a time
for vertex in progress.over(graph.vertices):
self._partition_one_application_vertex(
vertex, resource_tracker, machine_graph, graph_mapper,
plan_n_timesteps)
generate_machine_edges(machine_graph, graph_mapper, graph)
return machine_graph, graph_mapper, resource_tracker.chips_used
def _run(self, machine_graph, machine, plan_n_timesteps):
"""
:param MachineGraph machine_graph: The machine_graph to place
:param ~spinn_machine.Machine machine:
The machine with respect to which to partition the application
graph
:param int plan_n_timesteps: number of timesteps to plan for
:return: A set of placements
:rtype: ~pacman.model.placements.Placements
:raise PacmanPlaceException:
If something goes wrong with the placement
"""
# check that the algorithm can handle the constraints
self._check_constraints(machine_graph.vertices)
# Sort the vertices into those with and those without
# placement constraints
placements = Placements()
constrained = list()
unconstrained = set()
for vertex in machine_graph.vertices:
if locate_constraints_of_type(vertex.constraints,
AbstractPlacerConstraint):
constrained.append(vertex)
else:
unconstrained.add(vertex)
# Iterate over constrained vertices and generate placements
progress = ProgressBar(machine_graph.n_vertices,
"Placing graph vertices")
resource_tracker = ResourceTracker(
machine, plan_n_timesteps, self._generate_radial_chips(machine))
constrained = sort_vertices_by_known_constraints(constrained)
vertices_on_same_chip = get_same_chip_vertex_groups(machine_graph)
for vertex in progress.over(constrained, False):
self._place_vertex(vertex, resource_tracker, machine, placements,
vertices_on_same_chip, machine_graph)
while unconstrained:
# Place the subgraph with the overall most connected vertex
max_connected_vertex = self._find_max_connected_vertex(
unconstrained, machine_graph)
self._place_unconstrained_subgraph(max_connected_vertex,
machine_graph, unconstrained,
machine, placements,
resource_tracker, progress,
vertices_on_same_chip)
# finished, so stop progress bar and return placements
progress.end()
return placements
def _allocate_tags_for_placement(self, placement, resource_tracker,
tag_collector, ports_collector,
tag_port_tasks):
vertex = placement.vertex
resources = vertex.resources_required
# Get the constraint details for the tags
(board_address, ip_tags, reverse_ip_tags) = \
ResourceTracker.get_ip_tag_info(resources, vertex.constraints)
# Allocate the tags, first-come, first-served, using the fixed
# placement of the vertex, and the required resources
chips = [(placement.x, placement.y)]
(_, _, _, returned_ip_tags, returned_reverse_ip_tags) = \
resource_tracker.allocate_resources(
resources, chips, placement.p, board_address, ip_tags,
reverse_ip_tags)
# Put the allocated IP tag information into the tag object
if returned_ip_tags is not None:
for (tag_constraint, (board_address, tag, dest_x, dest_y)) in \
zip(ip_tags, returned_ip_tags):
ip_tag = IPTag(
board_address=board_address, destination_x=dest_x,
destination_y=dest_y, tag=tag,
ip_address=tag_constraint.ip_address,
port=tag_constraint.port,
strip_sdp=tag_constraint.strip_sdp,
traffic_identifier=tag_constraint.traffic_identifier)
tag_collector.add_ip_tag(ip_tag, vertex)
if returned_reverse_ip_tags is None:
return
# Put the allocated reverse IP tag information into the tag object
for tag_constraint, (board_address, tag) in zip(
reverse_ip_tags, returned_reverse_ip_tags):
if board_address not in ports_collector:
ports_collector[board_address] = OrderedSet(_BOARD_PORTS)
if tag_constraint.port is not None:
reverse_ip_tag = ReverseIPTag(
board_address, tag, tag_constraint.port,
placement.x, placement.y, placement.p,
tag_constraint.sdp_port)
tag_collector.add_reverse_ip_tag(reverse_ip_tag, vertex)
ports_collector[board_address].discard(tag_constraint.port)
else:
tag_port_tasks.append(
(tag_constraint, board_address, tag, vertex, placement))
def __call__(self, graph, machine):
"""
:param graph: The application_graph to partition
:type graph:\
:py:class:`pacman.model.graphs.application.ApplicationGraph`
:param machine:\
The machine with respect to which to partition the application\
graph
:type machine: :py:class:`spinn_machine.Machine`
:return: A machine graph
:rtype:\
:py:class:`pacman.model.graphs.machine.MachineGraph`
:raise pacman.exceptions.PacmanPartitionException:\
If something goes wrong with the partitioning
"""
ResourceTracker.check_constraints(graph.vertices)
utility_calls.check_algorithm_can_support_constraints(
constrained_vertices=graph.vertices,
supported_constraints=[
MaxVertexAtomsConstraint, FixedVertexAtomsConstraint
],
abstract_constraint_type=AbstractPartitionerConstraint)
# start progress bar
progress = ProgressBar(graph.n_vertices, "Partitioning graph vertices")
machine_graph = MachineGraph("Machine graph for " + graph.label)
graph_mapper = GraphMapper()
resource_tracker = ResourceTracker(machine)
# Partition one vertex at a time
for vertex in progress.over(graph.vertices):
self._partition_one_application_vertex(vertex, resource_tracker,
machine_graph, graph_mapper)
utils.generate_machine_edges(machine_graph, graph_mapper, graph)
return machine_graph, graph_mapper, resource_tracker.chips_used
def basic_tag_allocator(machine, plan_n_timesteps, placements):
"""
Basic tag allocator that goes though the boards available and applies\
the IP tags and reverse IP tags as needed.
:param ~spinn_machine.Machine machine:
The machine with respect to which to partition the application
graph
:param int plan_n_timesteps: number of timesteps to plan for
:param Placements placements:
:return: list of IP Tags, list of Reverse IP Tags,
tag allocation holder
:rtype: tuple(list(~spinn_machine.tags.IPTag),
list(~spinn_machine.tags.ReverseIPTag), Tags)
"""
resource_tracker = ResourceTracker(machine, plan_n_timesteps)
# Keep track of ports allocated to reverse IP tags and tags that still
# need a port to be allocated
ports_to_allocate = dict()
tags_to_allocate_ports = list()
# Check that the algorithm can handle the constraints
progress = ProgressBar(placements.n_placements, "Discovering tags")
placements_with_tags = list()
for placement in progress.over(placements.placements):
__gather_placements_with_tags(placement, placements_with_tags)
# Go through and allocate the IP tags and constrained reverse IP tags
tags = Tags()
progress = ProgressBar(placements_with_tags, "Allocating tags")
for placement in progress.over(placements_with_tags):
__allocate_tags_for_placement(placement, resource_tracker, tags,
ports_to_allocate,
tags_to_allocate_ports)
# Finally allocate ports to the unconstrained reverse IP tags
__allocate_ports_for_reverse_ip_tags(tags_to_allocate_ports,
ports_to_allocate, tags)
return tags
def __call__(self, machine_graph, machine):
# check that the algorithm can handle the constraints
self._check_constraints(machine_graph.vertices)
# Sort the vertices into those with and those without
# placement constraints
placements = Placements()
constrained = list()
unconstrained = set()
for vertex in machine_graph.vertices:
if locate_constraints_of_type(vertex.constraints,
AbstractPlacerConstraint):
constrained.append(vertex)
else:
unconstrained.add(vertex)
# Iterate over constrained vertices and generate placements
progress = ProgressBar(machine_graph.n_vertices,
"Placing graph vertices")
resource_tracker = ResourceTracker(
machine, self._generate_radial_chips(machine))
constrained = sort_vertices_by_known_constraints(constrained)
for vertex in progress.over(constrained, False):
self._place_vertex(vertex, resource_tracker, machine, placements)
while unconstrained:
# Place the subgraph with the overall most connected vertex
max_connected_vertex = self._find_max_connected_vertex(
unconstrained, machine_graph)
self._place_unconstrained_subgraph(max_connected_vertex,
machine_graph, unconstrained,
machine, placements,
resource_tracker, progress)
# finished, so stop progress bar and return placements
progress.end()
return placements
def _do_allocation(self, vertices, machine, same_chip_vertex_groups,
machine_graph):
placements = Placements()
# Iterate over vertices and generate placements
progress = ProgressBar(machine_graph.n_vertices,
"Placing graph vertices")
resource_tracker = ResourceTracker(
machine, self._generate_radial_chips(machine))
all_vertices_placed = set()
# iterate over vertices
for vertex_list in vertices:
# if too many one to ones to fit on a chip, allocate individually
if len(vertex_list) > machine.maximum_user_cores_on_chip:
for vertex in progress.over(vertex_list, False):
self._allocate_individual(vertex, placements,
resource_tracker,
same_chip_vertex_groups,
all_vertices_placed)
continue
allocations = self._get_allocations(resource_tracker, vertex_list)
if allocations is not None:
# allocate cores to vertices
for vertex, (x, y, p, _,
_) in progress.over(zip(vertex_list, allocations),
False):
placements.add_placement(Placement(vertex, x, y, p))
else:
# Something went wrong, try to allocate each individually
for vertex in progress.over(vertex_list, False):
self._allocate_individual(vertex, placements,
resource_tracker,
same_chip_vertex_groups,
all_vertices_placed)
progress.end()
return placements
def __call__(self, machine_graph, machine):
"""
:param machine_graph: The machine_graph to measure
:type machine_graph:\
:py:class:`pacman.model.graph.machine.MachineGraph`
:return: The size of the graph in number of chips
:rtype: int
"""
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
ordered_vertices = sort_vertices_by_known_constraints(
machine_graph.vertices)
# Iterate over vertices and allocate
progress = ProgressBar(machine_graph.n_vertices, "Measuring the graph")
resource_tracker = ResourceTracker(machine)
for vertex in progress.over(ordered_vertices):
resource_tracker.allocate_constrained_resources(
vertex.resources_required, vertex.constraints)
return len(resource_tracker.keys)
def __call__(self, machine_graph, machine, plan_n_timesteps):
"""
:param ~.MachineGraph machine_graph:
:param ~.Machine machine:
:param int plan_n_timesteps:
:rtype: int
"""
# check that the algorithm can handle the constraints
ResourceTracker.check_constraints(machine_graph.vertices)
ordered_vertices = sort_vertices_by_known_constraints(
machine_graph.vertices)
# Iterate over vertices and allocate
progress = ProgressBar(machine_graph.n_vertices, "Measuring the graph")
resource_tracker = ResourceTracker(machine, plan_n_timesteps)
for vertex in progress.over(ordered_vertices):
resource_tracker.allocate_constrained_resources(
vertex.resources_required, vertex.constraints)
return len(resource_tracker.keys)
def _do_allocation(
self, one_to_one_groups, same_chip_vertex_groups,
machine, plan_n_timesteps, machine_graph, progress):
"""
:param list(set(MachineVertex)) one_to_one_groups:
Groups of vertexes that would be nice on same chip
:param same_chip_vertex_groups:
Mapping of Vertex to the Vertex that must be on the same Chip
:type same_chip_vertex_groups:
dict(MachineVertex, collection(MachineVertex))
:param ~spinn_machine.Machine machine:
The machine with respect to which to partition the application
graph
:param int plan_n_timesteps: number of timesteps to plan for
:param MachineGraph machine_graph: The machine_graph to place
:param ~spinn_utilities.progress_bar.ProgressBar progress:
:rtype: Placements
"""
placements = Placements()
resource_tracker = ResourceTracker(
machine, plan_n_timesteps, self._generate_radial_chips(machine))
all_vertices_placed = set()
# RadialPlacementFromChipConstraint won't work here
for vertex in machine_graph.vertices:
for constraint in vertex.constraints:
if isinstance(constraint, RadialPlacementFromChipConstraint):
raise PacmanPlaceException(
"A RadialPlacementFromChipConstraint will not work "
"with the OneToOnePlacer algorithm; use the "
"RadialPlacer algorithm instead")
# Find and place vertices with hard constraints
for vertex in machine_graph.vertices:
if isinstance(vertex, AbstractVirtual):
virtual_p = 0
while placements.is_processor_occupied(
vertex.virtual_chip_x, vertex.virtual_chip_y,
virtual_p):
virtual_p += 1
placements.add_placement(Placement(
vertex, vertex.virtual_chip_x, vertex.virtual_chip_y,
virtual_p))
all_vertices_placed.add(vertex)
elif locate_constraints_of_type(
vertex.constraints, ChipAndCoreConstraint):
self._allocate_same_chip_as_group(
vertex, placements, resource_tracker,
same_chip_vertex_groups, all_vertices_placed, progress,
machine_graph)
for grouped_vertices in one_to_one_groups:
# Get unallocated vertices and placements of allocated vertices
unallocated = list()
chips = list()
for vert in grouped_vertices:
if vert in all_vertices_placed:
placement = placements.get_placement_of_vertex(vert)
chips.append((placement.x, placement.y))
else:
unallocated.append(vert)
if not chips:
chips = None
if 0 < len(unallocated) <=\
resource_tracker.get_maximum_cores_available_on_a_chip():
# Try to allocate all vertices to the same chip
self._allocate_one_to_one_group(
resource_tracker, unallocated, progress, placements, chips,
all_vertices_placed, machine_graph)
# if too big or failed go on to other groups first
# check all have been allocated if not do so now.
for vertex in machine_graph.vertices:
if vertex not in all_vertices_placed:
self._allocate_same_chip_as_group(
vertex, placements, resource_tracker,
same_chip_vertex_groups, all_vertices_placed,
progress, machine_graph)
progress.end()
return placements
def test_n_cores_available(self):
machine = virtual_machine(width=2, height=2, n_cpus_per_chip=18)
preallocated_resources = PreAllocatedResourceContainer()
preallocated_resources.add_cores_all(2)
preallocated_resources.add_cores_ethernet(3)
tracker = ResourceTracker(
machine,
plan_n_timesteps=None,
preallocated_resources=preallocated_resources)
# Should be 15 cores = 18 - 1 Monitor -3 ethernet -2 all cores
self.assertEqual(tracker._get_core_tracker(0, 0).n_cores_available, 12)
# Should be 15 cores = 18 -2 other cores
self.assertEqual(tracker._get_core_tracker(0, 1).n_cores_available, 15)
# Should be True since the core is not pre allocated
self.assertTrue(tracker._get_core_tracker(0, 0).is_core_available(2))
# Should be False since the core is monitor
self.assertFalse(tracker._get_core_tracker(0, 0).is_core_available(0))
# Allocate a core
tracker._get_core_tracker(0, 0).allocate(2)
# Should be 11 cores as one now allocated
self.assertEqual(tracker._get_core_tracker(0, 0).n_cores_available, 11)
with self.assertRaises(PacmanInvalidParameterException):
tracker._get_core_tracker(2, 2)
def __call__(
self, graph, machine, plan_n_timesteps,
preallocated_resources=None):
"""
:param graph: The application_graph to partition
:type graph:\
:py:class:`pacman.model.graph.application.ApplicationGraph`
:param machine: The machine with respect to which to partition the\
application_graph
:type machine: :py:class:`spinn_machine.Machine`
:param plan_n_timesteps: number of timesteps to plan for
:type plan_n_timesteps: int
:return: \
A machine_graph of partitioned vertices and partitioned edges
:rtype:\
:py:class:`pacman.model.graph.machine.MachineGraph`
:raise pacman.exceptions.PacmanPartitionException: \
If something goes wrong with the partitioning
"""
ResourceTracker.check_constraints(graph.vertices)
utils.check_algorithm_can_support_constraints(
constrained_vertices=graph.vertices,
abstract_constraint_type=AbstractPartitionerConstraint,
supported_constraints=[MaxVertexAtomsConstraint,
SameAtomsAsVertexConstraint,
FixedVertexAtomsConstraint])
# Load the vertices and create the machine_graph to fill
machine_graph = MachineGraph(
label="partitioned graph for {}".format(graph.label))
graph_mapper = GraphMapper()
# sort out vertex's by placement constraints
vertices = sort_vertices_by_known_constraints(graph.vertices)
# Set up the progress
n_atoms = 0
for vertex in vertices:
n_atoms += vertex.n_atoms
progress = ProgressBar(n_atoms, "Partitioning graph vertices")
resource_tracker = ResourceTracker(
machine, plan_n_timesteps,
preallocated_resources=preallocated_resources)
# Group vertices that are supposed to be the same size
vertex_groups = get_same_size_vertex_groups(vertices)
# Partition one vertex at a time
for vertex in vertices:
# check that the vertex hasn't already been partitioned
machine_vertices = graph_mapper.get_machine_vertices(vertex)
# if not, partition
if machine_vertices is None:
self._partition_vertex(
vertex, plan_n_timesteps, machine_graph, graph_mapper,
resource_tracker, progress, vertex_groups)
progress.end()
generate_machine_edges(machine_graph, graph_mapper, graph)
return machine_graph, graph_mapper, resource_tracker.chips_used
def _gather_placements_with_tags(self, placement, collector):
if (placement.vertex.resources_required.iptags or
placement.vertex.resources_required.reverse_iptags):
ResourceTracker.check_constraints([placement.vertex])
collector.append(placement)
def __call__(self, machine_graph, machine, n_keys_map, plan_n_timesteps):
"""
:param MachineGraph machine_graph: the machine graph
:param ~spinn_machine.Machine machine: the SpiNNaker machine
:param AbstractMachinePartitionNKeysMap n_keys_map:
the n keys from partition map
:param int plan_n_timesteps: number of timesteps to plan for
:return: placements.
:rtype: Placements
"""
# create progress bar
progress_bar = ProgressBar(
(machine_graph.n_vertices * self.ITERATIONS) + self.STEPS,
"Placing graph vertices via spreading over an entire machine")
# check that the algorithm can handle the constraints
self._check_constraints(
machine_graph.vertices,
additional_placement_constraints={SameChipAsConstraint})
progress_bar.update()
# get same chip groups
same_chip_vertex_groups = get_same_chip_vertex_groups(machine_graph)
progress_bar.update()
# get chip and core placed verts
hard_chip_constraints = self._locate_hard_placement_verts(
machine_graph)
progress_bar.update()
# get one to one groups
one_to_one_groups = create_vertices_groups(
machine_graph.vertices,
functools.partial(self._find_one_to_one_vertices,
graph=machine_graph))
progress_bar.update()
# sort chips so that they are radial from a given point and other
# init data structs
chips_in_order = self._determine_chip_list(machine)
resource_tracker = ResourceTracker(machine,
plan_n_timesteps,
chips=chips_in_order)
placements = Placements()
placed_vertices = set()
cost_per_chip = defaultdict(int)
progress_bar.update()
# allocate hard ones
for hard_vertex in hard_chip_constraints:
(x, y, p, _, _) = resource_tracker.allocate_constrained_resources(
hard_vertex.resources_required, hard_vertex.constraints)
placements.add_placement(Placement(hard_vertex, x, y, p))
placed_vertices.add(hard_vertex)
cost_per_chip[x, y] += self._get_cost(hard_vertex, machine_graph,
n_keys_map)
# place groups of verts that need the same chip on the same chip,
self._place_same_chip_verts(same_chip_vertex_groups, chips_in_order,
placements, progress_bar, resource_tracker,
placed_vertices, cost_per_chip,
machine_graph, n_keys_map)
# place 1 group per chip if possible on same chip as any already
# placed verts. if not then radially from it.
self._place_one_to_one_verts(one_to_one_groups, chips_in_order,
placements, progress_bar,
resource_tracker, placed_vertices,
cost_per_chip, machine_graph, n_keys_map,
machine)
# place vertices which don't have annoying placement constraints.
# spread them over the chips so that they have minimal impact on the
# overall incoming packet cost per router.
self._place_left_over_verts(machine_graph, chips_in_order, placements,
progress_bar, resource_tracker,
placed_vertices, cost_per_chip, n_keys_map)
progress_bar.end()
# return the built placements
return placements
def _gather_placements_with_tags(self, placement, collector):
if (placement.vertex.resources_required.iptags
or placement.vertex.resources_required.reverse_iptags):
ResourceTracker.check_constraints([placement.vertex])
collector.append(placement)
def _find_one_to_one_vertices(vertex, graph):
""" Find vertices which have one to one connections with the given\
vertex, and where their constraints don't force them onto\
different chips.
:param vertex: the vertex to use as a basis for one to one connections
:param graph: the graph to look for other one to one vertices
:return: set of one to one vertices
"""
x, y, _ = ResourceTracker.get_chip_and_core(vertex.constraints)
found_vertices = [vertex]
vertices_seen = {vertex}
# look for one to ones leaving this vertex
outgoing = graph.get_edges_starting_at_vertex(vertex)
vertices_to_try = [edge.post_vertex for edge in outgoing]
while vertices_to_try:
next_vertex = vertices_to_try.pop()
if next_vertex not in vertices_seen:
vertices_seen.add(next_vertex)
post_x, post_y, _ = ResourceTracker.get_chip_and_core(
next_vertex.constraints)
edges = graph.get_edges_ending_at_vertex(next_vertex)
if is_single(edges) and not _conflict(x, y, post_x, post_y):
found_vertices.append(next_vertex)
if post_x is not None:
x = post_x
if post_y is not None:
y = post_y
outgoing = graph.get_edges_starting_at_vertex(next_vertex)
vertices_to_try.extend([
edge.post_vertex for edge in outgoing
if edge.post_vertex not in vertices_seen
])
# look for one to ones entering this vertex
incoming = graph.get_edges_ending_at_vertex(vertex)
vertices_to_try = [
edge.pre_vertex for edge in incoming
if edge.pre_vertex not in vertices_seen
]
while vertices_to_try:
next_vertex = vertices_to_try.pop()
if next_vertex not in vertices_seen:
vertices_seen.add(next_vertex)
pre_x, pre_y, _ = ResourceTracker.get_chip_and_core(
next_vertex.constraints)
edges = graph.get_edges_starting_at_vertex(next_vertex)
if is_single(edges) and not _conflict(x, y, pre_x, pre_y):
found_vertices.append(next_vertex)
if pre_x is not None:
x = pre_x
if pre_y is not None:
y = pre_y
incoming = graph.get_edges_ending_at_vertex(next_vertex)
vertices_to_try.extend([
edge.pre_vertex for edge in incoming
if edge.pre_vertex not in vertices_seen
])
return found_vertices
def _do_allocation(
self, one_to_one_groups, same_chip_vertex_groups,
machine, plan_n_timesteps, machine_graph, progress):
"""
:param one_to_one_groups:
Groups of vertexes that would be nice on same chip
:type one_to_one_groups:
list(set(vertex))
:param same_chip_vertex_groups:
Mapping of Vertex to the Vertex that must be on the same Chip
:type same_chip_vertex_groups:
dict(vertex, collection(vertex))
:param machine:\
The machine with respect to which to partition the application\
graph
:type machine: :py:class:`spinn_machine.Machine`
:param plan_n_timesteps: number of timesteps to plan for
:type plan_n_timesteps: int
:param machine_graph: The machine_graph to place
:type machine_graph:\
:py:class:`pacman.model.graphs.machine.MachineGraph`
:param progress:
:return:
"""
placements = Placements()
resource_tracker = ResourceTracker(
machine, plan_n_timesteps, self._generate_radial_chips(machine))
all_vertices_placed = set()
# RadialPlacementFromChipConstraint won't work here
for vertex in machine_graph.vertices:
for constraint in vertex.constraints:
if isinstance(constraint, RadialPlacementFromChipConstraint):
raise PacmanPlaceException(
"A RadialPlacementFromChipConstraint will not work "
"with the OneToOnePlacer algorithm; use the "
"RadialPlacer algorithm instead")
unconstrained = list()
# Find and place vertices with hard constraints
for vertex in machine_graph.vertices:
if isinstance(vertex, AbstractVirtualVertex):
virtual_p = 0
while placements.is_processor_occupied(
vertex.virtual_chip_x, vertex.virtual_chip_y,
virtual_p):
virtual_p += 1
placements.add_placement(Placement(
vertex, vertex.virtual_chip_x, vertex.virtual_chip_y,
virtual_p))
all_vertices_placed.add(vertex)
elif locate_constraints_of_type(
vertex.constraints, ChipAndCoreConstraint):
self._allocate_same_chip_as_group(
vertex, placements, resource_tracker,
same_chip_vertex_groups,
all_vertices_placed, progress)
else:
unconstrained.append(vertex)
for grouped_vertices in one_to_one_groups:
# Get unallocated vertices and placements of allocated vertices
unallocated = list()
chips = list()
for vert in grouped_vertices:
if vert in all_vertices_placed:
placement = placements.get_placement_of_vertex(vert)
chips.append((placement.x, placement.y))
else:
unallocated.append(vert)
if 0 < len(unallocated) <=\
resource_tracker.get_maximum_cores_available_on_a_chip():
# Try to allocate all vertices to the same chip
self._allocate_one_to_one_group(
resource_tracker, unallocated, progress, placements, chips,
all_vertices_placed)
# if too big or failed go on to other groups first
# check all have been allocated if not do so now.
for vertex in machine_graph.vertices:
if vertex not in all_vertices_placed:
self._allocate_same_chip_as_group(
vertex, placements, resource_tracker,
same_chip_vertex_groups, all_vertices_placed,
progress)
progress.end()
return placements
