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