Source code for spinn_front_end_common.interface.interface_functions.graph_measurer

# Copyright (c) 2017-2019 The University of Manchester
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program.  If not, see <http://www.gnu.org/licenses/>.

import logging
from spinn_utilities.progress_bar import ProgressBar
from pacman.utilities.utility_objs import ResourceTracker
from pacman.utilities.algorithm_utilities.placer_algorithm_utilities import (
    sort_vertices_by_known_constraints)

logger = logging.getLogger(__name__)


[docs]class GraphMeasurer(object): """ Works out how many chips a machine graph needs. """ __slots__ = [] def __call__(self, machine_graph, machine, plan_n_timesteps): """ :param machine_graph: The machine_graph to measure :type machine_graph:\ :py:class:`pacman.model.graph.machine.MachineGraph` :py:class:`pacman.model.graph.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: 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, 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)