def create_app_less():
    app_graph = ApplicationGraph("Test")

    mac_graph = MachineGraph("Test", app_graph)
    n_keys_map = DictBasedMachinePartitionNKeysMap()

    # An output vertex to aim things at (to make keys required)
    out_mac_vertex = SimpleMacVertex()
    mac_graph.add_vertex(out_mac_vertex)

    # Create 5 application vertices (3 bits)
    for app_index in range(5):

        # For each, create up to (5 x 4) + 1 = 21 machine vertices (5 bits)
        for mac_index in range((app_index * 4) + 1):
            mac_vertex = SimpleMacVertex()
            mac_graph.add_vertex(mac_vertex)

            # For each machine vertex create up to
            # (20 x 2) + 1 = 81(!) partitions (6 bits)
            for mac_edge_index in range((mac_index * 2) + 1):
                mac_edge = MachineEdge(mac_vertex, out_mac_vertex)
                part_name = "Part{}".format(mac_edge_index)
                mac_graph.add_edge(mac_edge, part_name)

                # Give the partition up to (40 x 4) + 1 = 161 keys (8 bits)
                p = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
                    mac_vertex, part_name)
                n_keys_map.set_n_keys_for_partition(
                    p, (mac_edge_index * 4) + 1)

    return app_graph, mac_graph, n_keys_map
def create_graphs_only_fixed():
    app_graph = ApplicationGraph("Test")
    # An output vertex to aim things at (to make keys required)
    out_app_vertex = SimpleAppVertex()
    app_graph.add_vertex(out_app_vertex)
    # Create 5 application vertices (3 bits)
    app_vertex = SimpleAppVertex()
    app_graph.add_vertex(app_vertex)

    mac_graph = MachineGraph("Test", app_graph)
    n_keys_map = DictBasedMachinePartitionNKeysMap()

    # An output vertex to aim things at (to make keys required)
    out_mac_vertex = SimpleMacVertex(app_vertex=out_app_vertex)
    mac_graph.add_vertex(out_mac_vertex)

    mac_vertex = SimpleMacVertex(app_vertex=app_vertex)
    mac_graph.add_vertex(mac_vertex)
    for mac_edge_index in range(2):
        mac_edge = MachineEdge(mac_vertex, out_mac_vertex)
        part_name = "Part{}".format(mac_edge_index)
        mac_graph.add_edge(mac_edge, part_name)
        p = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
            mac_vertex, part_name)
        if (mac_edge_index == 0):
            p.add_constraint(FixedKeyAndMaskConstraint(
                [BaseKeyAndMask(0x4c00000, 0xFFFFFFFE)]))
        if (mac_edge_index == 1):
            p.add_constraint(FixedKeyAndMaskConstraint(
                [BaseKeyAndMask(0x4c00000, 0xFFFFFFFF)]))
        n_keys_map.set_n_keys_for_partition(
                p, (mac_edge_index * 4) + 1)

    return app_graph, mac_graph, n_keys_map
Esempio n. 3
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def test_create_constraints_to_file(tmpdir):
    # Construct the sample machine and graph
    machine = VirtualMachine(version=3, with_wrap_arounds=None)
    # TODO: define some extra monitor cores (how?)
    graph = MachineGraph("foo")
    tag1 = IPtagResource("1.2.3.4", 5, False, tag="footag")
    tag2 = ReverseIPtagResource(tag="bartag")
    v0 = SimpleMachineVertex(ResourceContainer(iptags=[tag1],
                                               reverse_iptags=[tag2]),
                             constraints=[ChipAndCoreConstraint(1, 1, 3)])
    graph.add_vertex(v0)
    v0_id = ident(v0)
    v1 = MachineSpiNNakerLinkVertex(2,
                                    constraints=[ChipAndCoreConstraint(1, 1)])
    v1.set_virtual_chip_coordinates(0, 2)
    graph.add_vertex(v1)
    v1_id = ident(v1)

    algo = CreateConstraintsToFile()
    fn = tmpdir.join("foo.json")
    filename, mapping = algo(graph, machine, str(fn))
    assert filename == str(fn)
    for vid in mapping:
        assert vid in [v0_id, v1_id]
        assert vid == ident(mapping[vid])
    obj = json.loads(fn.read())
    baseline = [{
        "type": "reserve_resource",
        "location": None,
        "reservation": [0, 1],
        "resource": "cores"
    }, {
        "type": "location",
        "location": [1, 1],
        "vertex": v0_id
    }, {
        "type": "resource",
        "resource": "cores",
        "range": [3, 4],
        "vertex": v0_id
    }, {
        "type": "resource",
        "resource": "iptag",
        "range": [0, 1],
        "vertex": v0_id
    }, {
        "type": "resource",
        "resource": "reverse_iptag",
        "range": [0, 1],
        "vertex": v0_id
    }, {
        "type": "route_endpoint",
        "direction": "south",
        "vertex": v1_id
    }, {
        "type": "location",
        "location": [1, 0],
        "vertex": v1_id
    }]
    assert obj == baseline
def test_memory_io():
    vertex = MyVertex()
    graph = MachineGraph("Test")
    graph.add_vertex(vertex)
    placements = Placements()
    placements.add_placement(Placement(vertex, 0, 0, 1))
    transceiver = _MockTransceiver()
    temp = tempfile.mkdtemp()
    print("ApplicationDataFolder = {}".format(temp))
    inputs = {
        "MemoryTransceiver": transceiver,
        "MemoryMachineGraph": graph,
        "MemoryPlacements": placements,
        "IPAddress": "testing",
        "ApplicationDataFolder": temp,
        "APPID": 30
    }
    algorithms = ["WriteMemoryIOData"]
    executor = PACMANAlgorithmExecutor(
        algorithms, [],
        inputs, [], [], [],
        xml_paths=get_front_end_common_pacman_xml_paths())
    executor.execute_mapping()
    assert (vertex._test_tag == vertex._tag)
def create_graphs_no_edge():
    app_graph = ApplicationGraph("Test")
    # An output vertex to aim things at (to make keys required)
    out_app_vertex = SimpleAppVertex()
    app_graph.add_vertex(out_app_vertex)
    # Create 5 application vertices (3 bits)
    app_vertex = SimpleAppVertex()
    app_graph.add_vertex(app_vertex)

    mac_graph = MachineGraph("Test", app_graph)
    n_keys_map = DictBasedMachinePartitionNKeysMap()

    # An output vertex to aim things at (to make keys required)
    out_mac_vertex = SimpleMacVertex(app_vertex=out_app_vertex)
    mac_graph.add_vertex(out_mac_vertex)

    mac_vertex = SimpleMacVertex(app_vertex=app_vertex)
    mac_graph.add_vertex(mac_vertex)

    return app_graph, mac_graph, n_keys_map
    def test_write_synaptic_matrix_and_master_population_table(self):
        MockSimulator.setup()

        default_config_paths = os.path.join(
            os.path.dirname(abstract_spinnaker_common.__file__),
            AbstractSpiNNakerCommon.CONFIG_FILE_NAME)

        config = conf_loader.load_config(
            AbstractSpiNNakerCommon.CONFIG_FILE_NAME, default_config_paths)
        config.set("Simulation", "one_to_one_connection_dtcm_max_bytes", 40)

        machine_time_step = 1000.0

        pre_app_vertex = SimpleApplicationVertex(10)
        pre_vertex = SimpleMachineVertex(resources=None)
        pre_vertex_slice = Slice(0, 9)
        post_app_vertex = SimpleApplicationVertex(10)
        post_vertex = SimpleMachineVertex(resources=None)
        post_vertex_slice = Slice(0, 9)
        post_slice_index = 0
        one_to_one_connector_1 = OneToOneConnector(None)
        one_to_one_connector_1.set_projection_information(
            pre_app_vertex, post_app_vertex, None, machine_time_step)
        one_to_one_connector_1.set_weights_and_delays(1.5, 1.0)
        one_to_one_connector_2 = OneToOneConnector(None)
        one_to_one_connector_2.set_projection_information(
            pre_app_vertex, post_app_vertex, None, machine_time_step)
        one_to_one_connector_2.set_weights_and_delays(2.5, 2.0)
        all_to_all_connector = AllToAllConnector(None)
        all_to_all_connector.set_projection_information(
            pre_app_vertex, post_app_vertex, None, machine_time_step)
        all_to_all_connector.set_weights_and_delays(4.5, 4.0)
        direct_synapse_information_1 = SynapseInformation(
            one_to_one_connector_1, SynapseDynamicsStatic(), 0)
        direct_synapse_information_2 = SynapseInformation(
            one_to_one_connector_2, SynapseDynamicsStatic(), 1)
        all_to_all_synapse_information = SynapseInformation(
            all_to_all_connector, SynapseDynamicsStatic(), 0)
        app_edge = ProjectionApplicationEdge(
            pre_app_vertex, post_app_vertex, direct_synapse_information_1)
        app_edge.add_synapse_information(direct_synapse_information_2)
        app_edge.add_synapse_information(all_to_all_synapse_information)
        machine_edge = ProjectionMachineEdge(
            app_edge.synapse_information, pre_vertex, post_vertex)
        partition_name = "TestPartition"

        graph = MachineGraph("Test")
        graph.add_vertex(pre_vertex)
        graph.add_vertex(post_vertex)
        graph.add_edge(machine_edge, partition_name)

        graph_mapper = GraphMapper()
        graph_mapper.add_vertex_mapping(
            pre_vertex, pre_vertex_slice, pre_app_vertex)
        graph_mapper.add_vertex_mapping(
            post_vertex, post_vertex_slice, post_app_vertex)
        graph_mapper.add_edge_mapping(machine_edge, app_edge)

        weight_scales = [4096.0, 4096.0]

        key = 0
        routing_info = RoutingInfo()
        routing_info.add_partition_info(PartitionRoutingInfo(
            [BaseKeyAndMask(key, 0xFFFFFFF0)],
            graph.get_outgoing_edge_partition_starting_at_vertex(
                pre_vertex, partition_name)))

        temp_spec = tempfile.mktemp()
        spec_writer = FileDataWriter(temp_spec)
        spec = DataSpecificationGenerator(spec_writer, None)
        master_pop_sz = 1000
        master_pop_region = 0
        all_syn_block_sz = 2000
        synapse_region = 1
        spec.reserve_memory_region(master_pop_region, master_pop_sz)
        spec.reserve_memory_region(synapse_region, all_syn_block_sz)

        synapse_type = MockSynapseType()

        synaptic_manager = SynapticManager(
            synapse_type=synapse_type, ring_buffer_sigma=5.0,
            spikes_per_second=100.0, config=config)
        synaptic_manager._write_synaptic_matrix_and_master_population_table(
            spec, [post_vertex_slice], post_slice_index, post_vertex,
            post_vertex_slice, all_syn_block_sz, weight_scales,
            master_pop_region, synapse_region, routing_info, graph_mapper,
            graph, machine_time_step)
        spec.end_specification()
        spec_writer.close()

        spec_reader = FileDataReader(temp_spec)
        executor = DataSpecificationExecutor(
            spec_reader, master_pop_sz + all_syn_block_sz)
        executor.execute()

        master_pop_table = executor.get_region(0)
        synaptic_matrix = executor.get_region(1)

        all_data = bytearray()
        all_data.extend(master_pop_table.region_data[
            :master_pop_table.max_write_pointer])
        all_data.extend(synaptic_matrix.region_data[
            :synaptic_matrix.max_write_pointer])
        master_pop_table_address = 0
        synaptic_matrix_address = master_pop_table.max_write_pointer
        direct_synapses_address = struct.unpack_from(
            "<I", synaptic_matrix.region_data)[0]
        direct_synapses_address += synaptic_matrix_address + 8
        indirect_synapses_address = synaptic_matrix_address + 4
        placement = Placement(None, 0, 0, 1)
        transceiver = MockTransceiverRawData(all_data)

        # Get the master population table details
        items = synaptic_manager._poptable_type\
            .extract_synaptic_matrix_data_location(
                key, master_pop_table_address, transceiver,
                placement.x, placement.y)

        # The first entry should be direct, but the rest should be indirect;
        # the second is potentially direct, but has been restricted by the
        # restriction on the size of the direct matrix
        assert len(items) == 3

        # TODO: This has been changed because direct matrices are disabled!
        assert not items[0][2]
        assert not items[1][2]
        assert not items[2][2]

        data_1, row_len_1 = synaptic_manager._retrieve_synaptic_block(
            transceiver=transceiver, placement=placement,
            master_pop_table_address=master_pop_table_address,
            indirect_synapses_address=indirect_synapses_address,
            direct_synapses_address=direct_synapses_address, key=key,
            n_rows=pre_vertex_slice.n_atoms, index=0,
            using_extra_monitor_cores=False)
        connections_1 = synaptic_manager._synapse_io.read_synapses(
            direct_synapse_information_1, pre_vertex_slice, post_vertex_slice,
            row_len_1, 0, 2, weight_scales, data_1, None,
            app_edge.n_delay_stages, machine_time_step)

        # The first matrix is a 1-1 matrix, so row length is 1
        assert row_len_1 == 1

        # Check that all the connections have the right weight and delay
        assert len(connections_1) == post_vertex_slice.n_atoms
        assert all([conn["weight"] == 1.5 for conn in connections_1])
        assert all([conn["delay"] == 1.0 for conn in connections_1])

        data_2, row_len_2 = synaptic_manager._retrieve_synaptic_block(
            transceiver=transceiver, placement=placement,
            master_pop_table_address=master_pop_table_address,
            indirect_synapses_address=indirect_synapses_address,
            direct_synapses_address=direct_synapses_address, key=key,
            n_rows=pre_vertex_slice.n_atoms, index=1,
            using_extra_monitor_cores=False)
        connections_2 = synaptic_manager._synapse_io.read_synapses(
            direct_synapse_information_2, pre_vertex_slice, post_vertex_slice,
            row_len_2, 0, 2, weight_scales, data_2, None,
            app_edge.n_delay_stages, machine_time_step)

        # The second matrix is a 1-1 matrix, so row length is 1
        assert row_len_2 == 1

        # Check that all the connections have the right weight and delay
        assert len(connections_2) == post_vertex_slice.n_atoms
        assert all([conn["weight"] == 2.5 for conn in connections_2])
        assert all([conn["delay"] == 2.0 for conn in connections_2])

        data_3, row_len_3 = synaptic_manager._retrieve_synaptic_block(
            transceiver=transceiver, placement=placement,
            master_pop_table_address=master_pop_table_address,
            indirect_synapses_address=indirect_synapses_address,
            direct_synapses_address=direct_synapses_address, key=key,
            n_rows=pre_vertex_slice.n_atoms, index=2,
            using_extra_monitor_cores=False)
        connections_3 = synaptic_manager._synapse_io.read_synapses(
            all_to_all_synapse_information, pre_vertex_slice,
            post_vertex_slice, row_len_3, 0, 2, weight_scales, data_3, None,
            app_edge.n_delay_stages, machine_time_step)

        # The third matrix is an all-to-all matrix, so length is n_atoms
        assert row_len_3 == post_vertex_slice.n_atoms

        # Check that all the connections have the right weight and delay
        assert len(connections_3) == \
            post_vertex_slice.n_atoms * pre_vertex_slice.n_atoms
        assert all([conn["weight"] == 4.5 for conn in connections_3])
        assert all([conn["delay"] == 4.0 for conn in connections_3])
def create_graphs1(with_fixed):
    app_graph = ApplicationGraph("Test")
    # An output vertex to aim things at (to make keys required)
    out_app_vertex = SimpleAppVertex()
    app_graph.add_vertex(out_app_vertex)
    # Create 5 application vertices (3 bits)
    app_vertices = list()
    for app_index in range(5):
        app_vertices.append(SimpleAppVertex())
    app_graph.add_vertices(app_vertices)

    mac_graph = MachineGraph("Test", app_graph)
    n_keys_map = DictBasedMachinePartitionNKeysMap()

    # An output vertex to aim things at (to make keys required)
    out_mac_vertex = SimpleMacVertex(app_vertex=out_app_vertex)
    mac_graph.add_vertex(out_mac_vertex)

    # Create 5 application vertices (3 bits)
    for app_index, app_vertex in enumerate(app_vertices):

        # For each, create up to (5 x 4) + 1 = 21 machine vertices (5 bits)
        for mac_index in range((app_index * 4) + 1):
            mac_vertex = SimpleMacVertex(app_vertex=app_vertex)
            mac_graph.add_vertex(mac_vertex)

            # For each machine vertex create up to
            # (20 x 2) + 1 = 81(!) partitions (6 bits)
            for mac_edge_index in range((mac_index * 2) + 1):
                mac_edge = MachineEdge(mac_vertex, out_mac_vertex)
                part_name = "Part{}".format(mac_edge_index)
                mac_graph.add_edge(mac_edge, part_name)

                # Give the partition up to (40 x 4) + 1 = 161 keys (8 bits)
                p = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
                    mac_vertex, part_name)
                if with_fixed:
                    if (app_index == 2 and mac_index == 4 and
                            part_name == "Part7"):
                        p.add_constraint(FixedKeyAndMaskConstraint(
                            [BaseKeyAndMask(0xFE00000, 0xFFFFFFC0)]))
                    if (app_index == 2 and mac_index == 0 and
                            part_name == "Part1"):
                        p.add_constraint(FixedKeyAndMaskConstraint(
                            [BaseKeyAndMask(0x4c00000, 0xFFFFFFFE)]))
                    if (app_index == 2 and mac_index == 0 and
                            part_name == "Part1"):
                        p.add_constraint(FixedKeyAndMaskConstraint(
                            [BaseKeyAndMask(0x4c00000, 0xFFFFFFFF)]))
                    if (app_index == 3 and mac_index == 0 and
                            part_name == "Part1"):
                        p.add_constraint(FixedKeyAndMaskConstraint(
                            [BaseKeyAndMask(0x3300000, 0xFFFFFFFF)]))
                    if (app_index == 3 and mac_index == 0 and
                            part_name == "Part1"):
                        p.add_constraint(FixedKeyAndMaskConstraint(
                            [BaseKeyAndMask(0x3300001, 0)]))
                n_keys_map.set_n_keys_for_partition(
                    p, (mac_edge_index * 4) + 1)

    return app_graph, mac_graph, n_keys_map
def create_big(with_fixed):
    # This test shows how easy it is to trip up the allocator with a retina
    app_graph = ApplicationGraph("Test")
    # Create a single "big" vertex
    big_app_vertex = SimpleAppVertex(label="Retina")
    app_graph.add_vertex(big_app_vertex)
    # Create a single output vertex (which won't send)
    out_app_vertex = SimpleAppVertex(label="Destination")
    app_graph.add_vertex(out_app_vertex)
    # Create a load of middle vertex
    mid_app_vertex = SimpleAppVertex("Population")
    app_graph.add_vertex(mid_app_vertex)

    mac_graph = MachineGraph("Test", app_graph)
    n_keys_map = DictBasedMachinePartitionNKeysMap()

    # Create a single big machine vertex
    big_mac_vertex = SimpleMacVertex(app_vertex=big_app_vertex, label="RETINA")
    mac_graph.add_vertex(big_mac_vertex)

    # Create a single output vertex (which won't send)
    out_mac_vertex = SimpleMacVertex(app_vertex=out_app_vertex)
    mac_graph.add_vertex(out_mac_vertex)

    # Create a load of middle vertices and connect them up
    for _ in range(2000):  # 2000 needs 11 bits
        mid_mac_vertex = SimpleMacVertex(app_vertex=mid_app_vertex)
        mac_graph.add_vertex(mid_mac_vertex)
        edge = MachineEdge(big_mac_vertex, mid_mac_vertex)
        mac_graph.add_edge(edge, "Test")
        edge_2 = MachineEdge(mid_mac_vertex, out_mac_vertex)
        mac_graph.add_edge(edge_2, "Test")
        mid_part = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
            mid_mac_vertex, "Test")
        n_keys_map.set_n_keys_for_partition(mid_part, 100)

    big_mac_part = mac_graph.get_outgoing_edge_partition_starting_at_vertex(
        big_mac_vertex, "Test")
    if with_fixed:
        big_mac_part.add_constraint(FixedKeyAndMaskConstraint([
            BaseKeyAndMask(0x0, 0x180000)]))
    # Make the "retina" need 21 bits, so total is now 21 + 11 = 32 bits,
    # but the application vertices need some bits too
    n_keys_map.set_n_keys_for_partition(big_mac_part, 1024 * 768 * 2)
    return app_graph, mac_graph, n_keys_map
Esempio n. 9
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def test_convert_to_file_machine_graph_pure_multicast(tmpdir):
    # Construct the sample graph
    graph = MachineGraph("foo")
    v0 = SimpleMachineVertex(ResourceContainer())
    graph.add_vertex(v0)
    tag = IPtagResource("1.2.3.4", 5, False, tag="footag")
    v1 = SimpleMachineVertex(ResourceContainer(iptags=[tag]))
    graph.add_vertex(v1)
    t1id = md5("%s_tag" % ident(v1))
    tag = ReverseIPtagResource(tag="bartag")
    v2 = SimpleMachineVertex(ResourceContainer(reverse_iptags=[tag]))
    graph.add_vertex(v2)
    t2id = md5("%s_tag" % ident(v2))
    graph.add_edge(MachineEdge(v1, v0), "part1")
    p1 = graph.get_outgoing_edge_partition_starting_at_vertex(v1, "part1")
    graph.add_edge(MachineEdge(v0, v2, label="foobar"), "part2")
    p2 = graph.get_outgoing_edge_partition_starting_at_vertex(v0, "part2")

    # Convert it to JSON
    algo = ConvertToFileMachineGraphPureMulticast()
    fn = tmpdir.join("foo.json")
    filename, _vertex_by_id, _partition_by_id = algo(graph, str(fn))
    assert filename == str(fn)

    # Rebuild and compare; simplest way of checking given that order is not
    # preserved in the underlying string and altering that is hard
    obj = json.loads(fn.read())
    baseline = {
        "vertices_resources": {
            ident(v0): {
                "cores": 1,
                "sdram": 0
            },
            ident(v1): {
                "cores": 1,
                "sdram": 0
            },
            t1id: {
                "cores": 0,
                "sdram": 0
            },
            ident(v2): {
                "cores": 1,
                "sdram": 0
            },
            t2id: {
                "cores": 0,
                "sdram": 0
            }
        },
        "edges": {
            ident(p1): {
                "source": ident(v1),
                "sinks": [ident(v0)],
                "type": "multicast",
                "weight": 1
            },
            ident(p2): {
                "source": ident(v0),
                "sinks": [ident(v2)],
                "type": "multicast",
                "weight": 1
            },
            t1id: {
                "source": ident(v1),
                "sinks": [t1id],
                "weight": 1.0,
                "type": "FAKE_TAG_EDGE"
            },
            t2id: {
                "source": ident(v2),
                "sinks": [t2id],
                "weight": 1.0,
                "type": "FAKE_TAG_EDGE"
            }
        }
    }
    assert obj == baseline