Source code for spinnaker_graph_front_end

# Copyright (c) 2015 The University of Manchester
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.
The API for running SpiNNaker simulations based on a basic (non-neural) graph.

The general usage pattern for this API something like is::

    import spinnaker_graph_front_end as gfe

    # Uses information from your configuration file
    # You might need to specify how many SpiNNaker boards to allocate

    # Make the bits that do the computation
    for each vertex to add:

    # Connect them together so computations are coordinated
    for each edge to add:

    # Actually plan and run the simulation

    # Get the results back; what this means can be complex
    for each vertex:
        results += vertex.retrieve_relevant_results()

    # Shut everything down
    # Only your retrieved results really exist after this

    # Analyse/render the results; totally application-specific!

It is possible to use GFE-style vertices in a neural graph (e.g., to simulate
the external world). Talk to the SpiNNaker team for more details.

import os
import logging
import sys
from spinn_utilities.log import FormatAdapter
from spinn_utilities.socket_address import SocketAddress
from pacman.model.graphs.application.abstract import (
from pacman.model.graphs.application.application_edge import ApplicationEdge
from import FecDataView
from spinn_front_end_common.utility_models import (
    ReverseIpTagMultiCastSource as _RIPTMCS)
from spinnaker_graph_front_end._version import (
    __version__, __version_name__, __version_month__, __version_year__)
from spinnaker_graph_front_end.spinnaker import SpiNNaker
from spinnaker_graph_front_end import spinnaker as gfe_file

logger = FormatAdapter(logging.getLogger(__name__))

__all__ = ['add_edge_instance', 'add_socket_address', 'add_vertex_instance',
           'buffer_manager', 'get_number_of_available_cores_on_machine',
           'has_ran', 'is_allocated_machine', 'machine', 'placements',
           'ReverseIpTagMultiCastSource', 'routing_infos', 'run', 'setup',
# Cache of the simulator created by setup
__simulator = None

[docs]def setup(model_binary_module=None, model_binary_folder=None, database_socket_addresses=(), n_chips_required=None, n_boards_required=None, time_scale_factor=None, machine_time_step=None): """ Set up a graph, ready to have vertices and edges added to it, and the simulator engine that will execute the graph. .. note:: This must be called *before* the other functions in this API. :param ~types.ModuleType model_binary_module: the Python module where the binary files (``.aplx``) can be found for the compiled C code that is being used in this application; mutually exclusive with the ``model_binary_folder``. :param str model_binary_folder: the folder where the binary files can be found for the c code that is being used in this application; mutually exclusive with the ``model_binary_module``. :param database_socket_addresses: set of SocketAddresses to be added for the database notification system. These are over and above the ones used by the :py:class:`~spinn_front_end_common.utilities.connections.LiveEventConnection` :type database_socket_addresses: :param n_chips_required: Deprecated! Use ``n_boards_required`` instead. Must be ``None`` if ``n_boards_required`` specified. :type n_chips_required: int or None :param n_boards_required: if you need to be allocated a machine (for spalloc) before building your graph, then fill this in with a general idea of the number of boards you need so that the spalloc system can allocate you a machine big enough for your needs. :type n_boards_required: int or None :raise ~spinn_front_end_common.utilities.exceptions.ConfigurationException: if mutually exclusive options are given. """ global __simulator # pylint: disable=redefined-outer-name "SpiNNaker graph front end (c) {}, University of Manchester", __version_year__) parent_dir = os.path.split(os.path.split(gfe_file.__file__)[0])[0] "Release version {}({}) - {} {}. Installed in folder {}", __version__, __version_name__, __version_month__, __version_year__, parent_dir) # add the directories where the binaries are located if model_binary_module is not None: FecDataView.register_binary_search_path( os.path.dirname(model_binary_module.__file__)) elif model_binary_folder is not None: FecDataView.register_binary_search_path(model_binary_folder) else: file_dir = os.path.dirname(os.path.abspath(sys.argv[0])) FecDataView.register_binary_search_path(file_dir) # set up the spinnaker object; after this, _sim() returns this object __simulator = SpiNNaker( n_chips_required=n_chips_required, n_boards_required=n_boards_required, machine_time_step=machine_time_step, time_scale_factor=time_scale_factor) FecDataView.add_database_socket_addresses(database_socket_addresses)
[docs]def run(duration=None): """ Run a simulation for a number of microseconds. :param int duration: the number of microseconds the application code should run for """ FecDataView.check_valid_simulator()
def run_until_complete(n_steps=None): """ Run until the simulation is complete. :param int n_steps: If not ``None``, this specifies that the simulation should be requested to run for the given number of steps. The host will still wait until the simulation itself says it has completed """ FecDataView.check_valid_simulator() __simulator.run_until_complete(n_steps)
[docs]def stop(): """ Do any necessary cleaning up before exiting. Unregisters the controller. """ # pylint: disable=global-variable-undefined global _executable_finder FecDataView.check_valid_simulator() __simulator.stop() _executable_finder = None
def stop_run(): """ Stop a request to run forever. """ FecDataView.check_valid_simulator() __simulator.stop_run()
[docs]def add_vertex_instance(vertex_to_add): """ Add an existing application vertex to the unpartitioned graph. :param ~pacman.model.graphs.application.ApplicationVertex vertex_to_add: vertex instance to add to the graph """ FecDataView.add_vertex(vertex_to_add)
def _new_edge_label(): return f"Edge {FecDataView.get_next_none_labelled_edge_number()}"
[docs]def add_edge_instance(edge, partition_id): """ Add an edge to the unpartitioned graph. :param ~pacman.model.graphs.application.ApplicationEdge edge: The edge to add. :param str partition_id: The ID of the partition that the edge belongs to. """ FecDataView.add_edge(edge, partition_id)
def add_machine_vertex_instance(machine_vertex): """ Add a machine vertex instance to the graph. :param ~pacman.model.graphs.machine.MachineVertex machine_vertex: The vertex to add """ app_vertex = AbstractOneAppOneMachineVertex( machine_vertex, machine_vertex.label) FecDataView.add_vertex(app_vertex) machine_vertex._app_vertex = app_vertex def add_machine_edge_instance(edge, partition_id): """ Add a machine edge instance to the graph. :param ~pacman.model.graphs.machine.MachineEdge edge: The edge to add :param str partition_id: The ID of the partition that the edge belongs to. """ FecDataView.add_edge( ApplicationEdge( edge.pre_vertex.app_vertex, edge.post_vertex.app_vertex), partition_id)
[docs]def add_socket_address( database_ack_port_num, database_notify_host, database_notify_port_num): """ Add a socket address for the notification protocol. :param int database_ack_port_num: port number to send acknowledgement to :param str database_notify_host: host IP to send notification to :param int database_notify_port_num: port that the external device will be notified on. """ database_socket = SocketAddress( listen_port=database_ack_port_num, notify_host_name=database_notify_host, notify_port_no=database_notify_port_num) FecDataView.add_database_socket_address(database_socket)
[docs]def get_number_of_available_cores_on_machine(): """ Get the number of cores on this machine that are available to the simulation. :rtype: int """ FecDataView.check_valid_simulator() return __simulator.get_number_of_available_cores_on_machine
[docs]def has_ran(): """ Get whether the simulation has already run. :rtype: bool """ return FecDataView.is_ran_ever()
[docs]def routing_infos(): """ Get information about how messages are routed on the machine. :rtype: ~pacman.model.routing_info.RoutingInfo """ return FecDataView.get_routing_infos()
[docs]def placements(): """ Get the placements. .. deprecated:: 7.0 No Longer supported! Use View iterate_placements instead Instead of:: front_end.placements().placements Use:: FecDataView.iterate_placemements() :py:class:`` can be imported from `` """ raise NotImplementedError( "This method has been replaced with View methods such as " "iterate_placements. See " "")
def tags(): """ Get the IPTAGs allocated on the machine. :rtype: ~pacman.model.tags.Tags """ return FecDataView.get_tags()
[docs]def buffer_manager(): """ Get the buffer manager being used for loading/extracting buffers. :rtype: ~spinn_front_end_common.interface.buffer_management.BufferManager """ return FecDataView.get_buffer_manager()
[docs]def machine(): """ Get the model of the attached/allocated machine. :rtype: ~spinn_machine.Machine """ logger.warning( "If you are getting the machine object to locate how many cores you " "can use,\n" "please use the following function call, as it is more reliable and " "takes into account software resources as well:\n\n" "get_number_of_available_cores_on_machine()") return FecDataView.get_machine()
[docs]def is_allocated_machine(): """ Get whether a machine is allocated. :rtype: bool """ return FecDataView.has_machine()
[docs]class ReverseIpTagMultiCastSource(_RIPTMCS): """ For full documentation see :py:class:`~spinn_front_end_common.utility_models.ReverseIpTagMultiCastSource`. """ __slots__ = ()