These pages document the python code for the PACMAN module which is part of the SpiNNaker Project.

This code depends on SpiNNUtils and SpiNNMachine (Combined_documentation).

PACMAN

Provides various functions which together can be used to take a graph and split it into pieces that can be loaded on to a machine, along with routes between the pieces.

Functional Requirements

  • Creation of an Application Graph of Vertices indicating points of computation within the graph and Edges between the vertices indicating a directional communication between the vertices; and a similar Machine Graph.

    • Vertices in the Application Graph will have a number of atoms - an atom cannot be broken down in to anything smaller.

    • Vertices in the Application Graph must be able to indicate what machine resources are required by any given subset of the atoms.

    • Vertices in the Machine Graph must be able to fit on a single chip of the machine in terms of resource usage.

    • A Vertex can have a number of constraints which must be respected by any algorithm which uses the graph. Algorithms must check that they can support the given constraints and must fail if they cannot. Provided constraints include support for:

      • The maximum number of atoms which any Machine Graph Vertex can contain for a given Application Graph vertex
      • The chip and/or processor on to which a Machine Graph Vertex should be placed.
      • A set of Application Graph Vertices whose corresponding Machine Graph vertices should contain the same number of atoms.
      • A set of Application Graph Vertices whose corresponding Machine Graph vertices should be placed on the same chip if they contain the same atom.

    • It should be possible to create new constraints as the need arises.

    • Multiple edges can exist between the same two vertices.

    • It must be possible to build the Machine Graph directly without requiring that it is created by one of the other modules.

    • It is not required that there is a Machine Graph Edge between every pair of Machine Graph Vertex from the same Application Graph Vertex.

    • Where a Machine Graph is created from an Application Graph, it should be possible to find the corresponding Vertices and Edges from one graph to the other.

  • Creation of multicast routing info consisting of key/mask combinations assigned to Edges of the Machine Graph.

    • It must be possible to build this information directly without requiring that it is created by one of the other modules.
    • There should be exactly one key/mask combination for each Edge in the Machine Graph, which will represent all the keys which will be sent in all packets from the Vertex at the start of the Edge down that Edge.
    • It is possible for a Vertex to send several different keys down several different Edges, but only one per Edge (but note that it is acceptable for different keys to be assigned to different Edges between the same two Vertices).
    • There should be no overlap between the key/mask combinations of Edges which come from different Vertices i.e. no two Edges which start at different Vertices should have the same key/mask combination.

  • Partitioning of an Application graph with respect to a machine, such that the resources consumed by each Vertex does not exceed those provided by each chip on the machine.

    • It should be possible to select from a range of partitioning algorithms or provide one, although a default should be provided in the absence of such a choice .
    • Any partitioning constraints should be met; if there are any that cannot, or that are not understood by the algorithm in use an exception should be thrown. Non-partitioning constraints can be ignored, although these can be used if it makes sense for the given algorithm.
    • It must be possible to create at least one grouping of the generated Vertices so that each group fits within the resources provided by a single chip on the machine.
    • It should not be assumed that a given grouping of Vertices will be the final grouping on the machine, although it is acceptable to make hints through additional constraints about what is likely to work.
    • The machine itself must not be altered by the partitioning, so that it can be used in further processing.
    • The graph itself must not be altered by the partitioning, so that it can be used in further processing.
    • No two Machine Graph Vertices created from a single Application Graph Vertex can contain the same atom.
    • Any Edges in the Application Graph must be split with the Vertices to create a number of Machine Graph edges, such that where there was a vertex v connected to a vertex w by a single edge in the Application Graph, there should be an Edge in the Machine Graph between every Vertex of Application Graph Vertex v and every Vertex of Application Graph Vertex w; for example, if there are 2 Machine Graph Vertices for each of v and w, and one Edge between them in the Application Graph, then there will be 4 new Edges in the Machine Graph for this Edge.

  • Placement of a Machine Graph on a given machine, such that the resources required by any combination of Vertices placed on any chip in the machine does not exceed the resources provided by that chip.

    • It should be possible to choose from a range of placement algorithms or provide one, although a default should be provided in the absence of such a choice.
    • Any placement constraints should be met; if there are any that cannot, or that are not understood by placement algorithm, an exception should be thrown. Non-placement constraints can be ignored, although these can be used if it makes sense for the given algorithm.
    • The machine itself should not be altered by placement so that it can be used in further processing.
    • The graph itself should not be altered by placement so that it can be used in further processing.
    • The returned placements should only contain a single placement for each vertex.
    • The placements should be such that the vertices with edges between them must be able to communicate with each other.

  • Allocation of multicast routing keys and masks to a Machine Graph such that each vertex sends out packets with a different key/mask combination.

    • This can use the placement information if required. If an algorithm requires placement information but none is provided an exception is thrown.

  • Routing of edges between vertices with a given allocation of routing keys and masks with respect to a given machine.

    • It should be possible to choose from a range of routing algorithms, or provide one, although a default should be provided in the absence of such a choice
    • For any vertex, following the routes from the placement of the vertex should result exactly in the set of placements of the destination vertices described by all the edges which start at that vertex. No additional destination should be reached, and no fewer than this set of destinations should be reached.

  • It should be possible to call each of the modules independently. There should be no assumption that one of the other modules has produced the data input for any other module.

  • There should be no assumption about how the inputs and outputs are stored.

  • Any utility functions that provide access to internal structures within a data structure should operate in approximately O(1) time; for example, where an object of type obj holds a number of objects of type subobj with property prop, requesting a list of subobj objects contained within obj with property value prop = value should not iterate through a list of such objects, but should instead maintain a mapping that allows access to such objects in O(1) time. If this is not possible, obj should only provide access to a list of subobj objects, allowing the caller to filter these themselves. This will ensure that no misunderstanding can be made about the speed of operation of a function.

Contents:

pacman

pacman package

Subpackages

pacman.executor package
Subpackages
pacman.executor.algorithm_classes package
Submodules
pacman.executor.algorithm_classes.abstract_algorithm module
class pacman.executor.algorithm_classes.abstract_algorithm.AbstractAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens)[source]

Bases: object

Represents the metadata for an algorithm.

Parameters:
  • algorithm_id (str) – The unique ID of the algorithm
  • required_inputs (list(AbstractInput)) – The inputs required by the algorithm
  • optional_inputs (list(AbstractInput)) – The optional inputs for the algorithm, which will be provided when available
  • outputs (list(Output)) – The output types of the algorithm
  • required_input_tokens (list(Token)) – Tokens required to have been generated before this algorithm can start
  • optional_input_tokens (list(Token)) – Tokens required to have been generated before this algorithm can start if and only if at least one algorithm generates the token
  • generated_output_tokens (list(Token)) – Tokens generated by this algorithm
algorithm_id

The ID for this algorithm

call(inputs)[source]

Call the algorithm with the given inputs and return the outputs

Parameters:inputs – A dict of input type -> value
Returns:A dict of output type -> value
generated_output_tokens

The generated output tokens of the algorithm

optional_input_tokens

The optional input tokens of the algorithm

optional_inputs

The optional inputs of the algorithm

outputs

The outputs of the algorithm

required_input_tokens

The required input tokens of the algorithm

required_inputs

The required inputs of the algorithm

write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

pacman.executor.algorithm_classes.abstract_python_algorithm module
class pacman.executor.algorithm_classes.abstract_python_algorithm.AbstractPythonAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, python_module)[source]

Bases: pacman.executor.algorithm_classes.abstract_algorithm.AbstractAlgorithm

An algorithm written in Python.

Parameters:python_module – The module containing the python code to execute
call(inputs)[source]

Call the algorithm with the given inputs and return the outputs

Parameters:inputs – A dict of input type -> value
Returns:A dict of output type -> value
call_python(inputs)[source]

Call the algorithm

Parameters:inputs – A dict of parameter name -> value
Returns:The result of calling the python algorithm
pacman.executor.algorithm_classes.external_algorithm module
class pacman.executor.algorithm_classes.external_algorithm.ExternalAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, command_line_arguments)[source]

Bases: pacman.executor.algorithm_classes.abstract_algorithm.AbstractAlgorithm

An algorithm which is external to the SpiNNaker software, or rather its wrapper into PACMAN.

call(inputs)[source]

Call the algorithm with the given inputs and return the outputs

Parameters:inputs – A dict of input type -> value
Returns:A dict of output type -> value
write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

pacman.executor.algorithm_classes.python_class_algorithm module
class pacman.executor.algorithm_classes.python_class_algorithm.PythonClassAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, python_module, python_class, python_method=None)[source]

Bases: pacman.executor.algorithm_classes.abstract_python_algorithm.AbstractPythonAlgorithm

An algorithm that is a class.

Parameters:
  • python_class – The class of the algorithm
  • python_method – The method of the algorithm, or None if the class is callable
call_python(inputs)[source]

Call the algorithm

Parameters:inputs – A dict of parameter name -> value
Returns:The result of calling the python algorithm
write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

pacman.executor.algorithm_classes.python_function_algorithm module
class pacman.executor.algorithm_classes.python_function_algorithm.PythonFunctionAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, python_module, python_function)[source]

Bases: pacman.executor.algorithm_classes.abstract_python_algorithm.AbstractPythonAlgorithm

An algorithm that is a function.

Parameters:python_function – The name of the function to call
call_python(inputs)[source]

Call the algorithm

Parameters:inputs – A dict of parameter name -> value
Returns:The result of calling the python algorithm
write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

Module contents
class pacman.executor.algorithm_classes.AbstractAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens)[source]

Bases: object

Represents the metadata for an algorithm.

Parameters:
  • algorithm_id (str) – The unique ID of the algorithm
  • required_inputs (list(AbstractInput)) – The inputs required by the algorithm
  • optional_inputs (list(AbstractInput)) – The optional inputs for the algorithm, which will be provided when available
  • outputs (list(Output)) – The output types of the algorithm
  • required_input_tokens (list(Token)) – Tokens required to have been generated before this algorithm can start
  • optional_input_tokens (list(Token)) – Tokens required to have been generated before this algorithm can start if and only if at least one algorithm generates the token
  • generated_output_tokens (list(Token)) – Tokens generated by this algorithm
algorithm_id

The ID for this algorithm

call(inputs)[source]

Call the algorithm with the given inputs and return the outputs

Parameters:inputs – A dict of input type -> value
Returns:A dict of output type -> value
generated_output_tokens

The generated output tokens of the algorithm

optional_input_tokens

The optional input tokens of the algorithm

optional_inputs

The optional inputs of the algorithm

outputs

The outputs of the algorithm

required_input_tokens

The required input tokens of the algorithm

required_inputs

The required inputs of the algorithm

write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

class pacman.executor.algorithm_classes.AbstractPythonAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, python_module)[source]

Bases: pacman.executor.algorithm_classes.abstract_algorithm.AbstractAlgorithm

An algorithm written in Python.

Parameters:python_module – The module containing the python code to execute
call(inputs)[source]

Call the algorithm with the given inputs and return the outputs

Parameters:inputs – A dict of input type -> value
Returns:A dict of output type -> value
call_python(inputs)[source]

Call the algorithm

Parameters:inputs – A dict of parameter name -> value
Returns:The result of calling the python algorithm
class pacman.executor.algorithm_classes.ExternalAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, command_line_arguments)[source]

Bases: pacman.executor.algorithm_classes.abstract_algorithm.AbstractAlgorithm

An algorithm which is external to the SpiNNaker software, or rather its wrapper into PACMAN.

call(inputs)[source]

Call the algorithm with the given inputs and return the outputs

Parameters:inputs – A dict of input type -> value
Returns:A dict of output type -> value
write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

class pacman.executor.algorithm_classes.PythonClassAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, python_module, python_class, python_method=None)[source]

Bases: pacman.executor.algorithm_classes.abstract_python_algorithm.AbstractPythonAlgorithm

An algorithm that is a class.

Parameters:
  • python_class – The class of the algorithm
  • python_method – The method of the algorithm, or None if the class is callable
call_python(inputs)[source]

Call the algorithm

Parameters:inputs – A dict of parameter name -> value
Returns:The result of calling the python algorithm
write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

class pacman.executor.algorithm_classes.PythonFunctionAlgorithm(algorithm_id, required_inputs, optional_inputs, outputs, required_input_tokens, optional_input_tokens, generated_output_tokens, python_module, python_function)[source]

Bases: pacman.executor.algorithm_classes.abstract_python_algorithm.AbstractPythonAlgorithm

An algorithm that is a function.

Parameters:python_function – The name of the function to call
call_python(inputs)[source]

Call the algorithm

Parameters:inputs – A dict of parameter name -> value
Returns:The result of calling the python algorithm
write_provenance_header(provenance_file)[source]

Writes the header info for this algorithm So things like name, module, class, function and command_line_arguments

But not anything about input and outputs as this is done elsewhere :param provenance_file: File to write to :type provenance_file: file

pacman.executor.algorithm_decorators package
Submodules
pacman.executor.algorithm_decorators.abstract_input module
class pacman.executor.algorithm_decorators.abstract_input.AbstractInput[source]

Bases: object

An abstract input to an algorithm

get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

pacman.executor.algorithm_decorators.algorithm_decorator module
class pacman.executor.algorithm_decorators.algorithm_decorator.AllOf(*items)[source]

Bases: object

Indicates that all of the items specified are required.

Parameters:items (str, pacman.executor.algorithm_decorators.AllOf, pacman.executor.algorithm_decorators.OneOf) – The items required
items

The items specified

real_class

The AbstractInput class to use for this input

class pacman.executor.algorithm_decorators.algorithm_decorator.OneOf(*items)[source]

Bases: object

Indicates that one of the items specified is required.

Parameters:items (str, pacman.executor.algorithm_decorators.AllOf, pacman.executor.algorithm_decorators.OneOf) – The items required
items

The items specified

real_class

The AbstractInput class to use for this input

pacman.executor.algorithm_decorators.algorithm_decorator.algorithm(input_definitions, outputs, algorithm_id=None, required_inputs=None, optional_inputs=None, method=None, required_input_tokens=None, optional_input_tokens=None, generated_output_tokens=None)[source]

Define an object to be a PACMAN algorithm that can be executed by the pacman.executor.pacman_algorithm_executor.PACMANAlgorithmExecutor.

Can be used to decorate either a class or a function (not a method). If this decorates a class, the class must be callable (i.e., have a __call__ method), or else a method must be specified to call to run the algorithm.

The inputs and outputs referenced below refer to the parameters of the method or function.

Parameters:
  • input_definitions (dict(str, str or list(str))) – dict of algorithm parameter name to list of types, one for each required algorithm parameter, and one for each optional parameter that is used in this algorithm call
  • outputs (list(str)) – A list of types output from the algorithm that must match the order in which they are returned.
  • algorithm_id (str) – Optional unique ID of the algorithm; if not specified, the name of the class or function is used.
  • required_inputs (list(str or pacman.executor.algorithm_decorators.OneOf or pacman.executor.algorithm_decorators.AllOf)) – Optional list of required algorithm parameter names; if not specified those parameters which have no default values are used.
  • optional_inputs (list(str or pacman.executor.algorithm_decorators.OneOf or pacman.executor.algorithm_decorators.AllOf)) – Optional list of optional algorithm parameter names; if not specified those parameters which have default values are used.
  • method – The optional name of the method to call if decorating a class; if not specified, __call__ is used (i.e. it is assumed to be callable). Must not be used if decorating a function
  • required_input_tokens – A list of tokens required to have been generated before this algorithm runs
  • optional_input_tokens – A list of tokens that if generated by any algorithm, must have been generated before this algorithm runs
  • generated_output_tokens – A list of tokens generated by running this algorithm
pacman.executor.algorithm_decorators.algorithm_decorator.algorithms(algorithms)[source]

Specify multiple algorithms for a single class or function

Parameters:algorithms – A list of algorithm definitions
pacman.executor.algorithm_decorators.algorithm_decorator.get_algorithms()[source]

Get the dict of known algorithm ID -> algorithm data

pacman.executor.algorithm_decorators.algorithm_decorator.reset_algorithms()[source]

Reset the known algorithms

pacman.executor.algorithm_decorators.algorithm_decorator.scan_packages(packages, recursive=True)[source]

Scan packages for algorithms

Parameters:
  • packages – The names of the packages to scan (using dotted notation), or the actual package modules
  • recursive – True if sub-packages should be examined
Returns:

A dict of algorithm name -> algorithm data
pacman.executor.algorithm_decorators.all_of_input module
class pacman.executor.algorithm_decorators.all_of_input.AllOfInput(inputs)[source]

Bases: pacman.executor.algorithm_decorators.abstract_input.AbstractInput

A composite input for which all input parameters must be matched.

Parameters:inputs – The inputs that make up this input
get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

pacman.executor.algorithm_decorators.one_of_input module
class pacman.executor.algorithm_decorators.one_of_input.OneOfInput(inputs)[source]

Bases: pacman.executor.algorithm_decorators.abstract_input.AbstractInput

An input for which one of the input parameters must be matched.

Parameters:inputs – The inputs that make up this input
get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

pacman.executor.algorithm_decorators.output module
class pacman.executor.algorithm_decorators.output.Output(output_type, file_name_type=None)[source]

Bases: object

Represents an output from an algorithm.

Parameters:
  • output_type – The type of the output
  • file_name_type – If the output is file based, the type of the input holding the file name
file_name_type
output_type
pacman.executor.algorithm_decorators.single_input module
class pacman.executor.algorithm_decorators.single_input.SingleInput(name, param_types)[source]

Bases: pacman.executor.algorithm_decorators.abstract_input.AbstractInput

An input that is just one item.

Parameters:
  • name (str) – The name of the input parameter
  • param_types (list(str)) – The ordered possible types of the input parameter
get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

pacman.executor.algorithm_decorators.token module
class pacman.executor.algorithm_decorators.token.Token(name, part=None)[source]

Bases: object

A token in the algorithm flow that indicates a process or part of a process.

name
part
Module contents
class pacman.executor.algorithm_decorators.AbstractInput[source]

Bases: object

An abstract input to an algorithm

get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

class pacman.executor.algorithm_decorators.AllOfInput(inputs)[source]

Bases: pacman.executor.algorithm_decorators.abstract_input.AbstractInput

A composite input for which all input parameters must be matched.

Parameters:inputs – The inputs that make up this input
get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

class pacman.executor.algorithm_decorators.OneOfInput(inputs)[source]

Bases: pacman.executor.algorithm_decorators.abstract_input.AbstractInput

An input for which one of the input parameters must be matched.

Parameters:inputs – The inputs that make up this input
get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

class pacman.executor.algorithm_decorators.Output(output_type, file_name_type=None)[source]

Bases: object

Represents an output from an algorithm.

Parameters:
  • output_type – The type of the output
  • file_name_type – If the output is file based, the type of the input holding the file name
file_name_type
output_type
class pacman.executor.algorithm_decorators.SingleInput(name, param_types)[source]

Bases: pacman.executor.algorithm_decorators.abstract_input.AbstractInput

An input that is just one item.

Parameters:
  • name (str) – The name of the input parameter
  • param_types (list(str)) – The ordered possible types of the input parameter
get_fake_inputs(inputs)[source]

Get input types that are not in inputs but which satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are not available in inputs
get_inputs_by_name(inputs)[source]

Get the inputs that match this input by parameter name

Parameters:inputs – A dict of type to value
Returns:A dict of parameter name to value
Return type:dict
get_matching_inputs(inputs)[source]

Get input types that are in inputs and satisfy this input

Parameters:inputs – A set of input types
Returns:A set of input parameter names that are available in inputs
input_matches(inputs)[source]

Determine if this input is in the set of inputs

Parameters:inputs – A set of input types
Returns:True if this input type is in the list
name

The name of the input

param_types

The types of the input

class pacman.executor.algorithm_decorators.AllOf(*items)[source]

Bases: object

Indicates that all of the items specified are required.

Parameters:items (str, pacman.executor.algorithm_decorators.AllOf, pacman.executor.algorithm_decorators.OneOf) – The items required
items

The items specified

real_class

The AbstractInput class to use for this input

class pacman.executor.algorithm_decorators.OneOf(*items)[source]

Bases: object

Indicates that one of the items specified is required.

Parameters:items (str, pacman.executor.algorithm_decorators.AllOf, pacman.executor.algorithm_decorators.OneOf) – The items required
items

The items specified

real_class

The AbstractInput class to use for this input

pacman.executor.algorithm_decorators.algorithm(input_definitions, outputs, algorithm_id=None, required_inputs=None, optional_inputs=None, method=None, required_input_tokens=None, optional_input_tokens=None, generated_output_tokens=None)[source]

Define an object to be a PACMAN algorithm that can be executed by the pacman.executor.pacman_algorithm_executor.PACMANAlgorithmExecutor.

Can be used to decorate either a class or a function (not a method). If this decorates a class, the class must be callable (i.e., have a __call__ method), or else a method must be specified to call to run the algorithm.

The inputs and outputs referenced below refer to the parameters of the method or function.

Parameters:
  • input_definitions (dict(str, str or list(str))) – dict of algorithm parameter name to list of types, one for each required algorithm parameter, and one for each optional parameter that is used in this algorithm call
  • outputs (list(str)) – A list of types output from the algorithm that must match the order in which they are returned.
  • algorithm_id (str) – Optional unique ID of the algorithm; if not specified, the name of the class or function is used.
  • required_inputs (list(str or pacman.executor.algorithm_decorators.OneOf or pacman.executor.algorithm_decorators.AllOf)) – Optional list of required algorithm parameter names; if not specified those parameters which have no default values are used.
  • optional_inputs (list(str or pacman.executor.algorithm_decorators.OneOf or pacman.executor.algorithm_decorators.AllOf)) – Optional list of optional algorithm parameter names; if not specified those parameters which have default values are used.
  • method – The optional name of the method to call if decorating a class; if not specified, __call__ is used (i.e. it is assumed to be callable). Must not be used if decorating a function
  • required_input_tokens – A list of tokens required to have been generated before this algorithm runs
  • optional_input_tokens – A list of tokens that if generated by any algorithm, must have been generated before this algorithm runs
  • generated_output_tokens – A list of tokens generated by running this algorithm
pacman.executor.algorithm_decorators.algorithms(algorithms)[source]

Specify multiple algorithms for a single class or function

Parameters:algorithms – A list of algorithm definitions
pacman.executor.algorithm_decorators.get_algorithms()[source]

Get the dict of known algorithm ID -> algorithm data

pacman.executor.algorithm_decorators.reset_algorithms()[source]

Reset the known algorithms

pacman.executor.algorithm_decorators.scan_packages(packages, recursive=True)[source]

Scan packages for algorithms

Parameters:
  • packages – The names of the packages to scan (using dotted notation), or the actual package modules
  • recursive – True if sub-packages should be examined
Returns:

A dict of algorithm name -> algorithm data
class pacman.executor.algorithm_decorators.Token(name, part=None)[source]

Bases: object

A token in the algorithm flow that indicates a process or part of a process.

name
part
Submodules
pacman.executor.algorithm_metadata_xml_reader module
class pacman.executor.algorithm_metadata_xml_reader.AlgorithmMetadataXmlReader(xml_paths)[source]

Bases: object

Converts an XML file into algorithm data.

Parameters:xml_paths – paths to extra metadata files
Return type:None
decode_algorithm_data_objects()[source]
Returns:the algorithm data objects which represent all the algorithm’s inputs and outputs
pacman.executor.injection_decorator module
exception pacman.executor.injection_decorator.InjectionException[source]

Bases: Exception

Raised when there is an error with injection.

pacman.executor.injection_decorator.clear_injectables()[source]

Clear the current set of injectables

pacman.executor.injection_decorator.do_injection(objects_to_inject, objects_to_inject_into=None)[source]

Perform the actual injection of objects.

Parameters:
  • objects_to_inject (dict(str)->object) – The objects to be injected as a dict of type name -> object of type
  • objects_to_inject_into (list) – The objects whose classes support_injection, or None to use all instances that have been created
pacman.executor.injection_decorator.inject(type_to_inject)[source]

Marks a method as something to be called to inject an object of the given type. The type is just a name for the type, and should match up at some point with some generated data.

Parameters:type_to_inject – The type to be injected using this method
pacman.executor.injection_decorator.inject_items(types)[source]

Indicates values that need to be injected into the method

Parameters:types – A dict of method argument name to type name to be injected
class pacman.executor.injection_decorator.injection_context(injection_dictionary)[source]

Bases: object

Provides a context for injection to use with with.

Parameters:injection_dictionary – The dictionary of items to inject whilst in the context
pacman.executor.injection_decorator.provide_injectables(injectables)[source]

Set the objects from which values should be injected into methods

Parameters:injectables – A dict of type to value
pacman.executor.injection_decorator.requires_injection(types_required)[source]

Indicates that injection of the given types is required before this method is called; an Exception is raised if the types have not been injected.

Parameters:types_required (list(str)) – A list of types that must have been injected
pacman.executor.injection_decorator.supports_injection(injectable_class)[source]

Indicate that the class has methods on which objects can be injected.

pacman.executor.pacman_algorithm_executor module
class pacman.executor.pacman_algorithm_executor.PACMANAlgorithmExecutor(algorithms, optional_algorithms, inputs, required_outputs, tokens, required_output_tokens, xml_paths=None, packages=None, do_timings=True, print_timings=False, do_immediate_injection=True, do_post_run_injection=False, inject_inputs=True, do_direct_injection=True, use_unscanned_annotated_algorithms=True, provenance_path=None, provenance_name=None)[source]

Bases: object

An executor of PACMAN algorithms where the order is deduced from the input and outputs of the algorithm using an XML description of the algorithm.

Parameters:
  • algorithms – A list of algorithms that must all be run
  • optional_algorithms – A list of algorithms that must be run if their inputs are available
  • inputs – A dict of input type to value
  • required_outputs – A list of output types that must be generated
  • tokens – A list of tokens that should be considered to have been generated
  • required_output_tokens – A list of tokens that should be generated by the end of the run
  • xml_paths – An optional list of paths to XML files containing algorithm descriptions; if not specified, only detected algorithms will be used (or else those found in packages)
  • packages – An optional list of packages to scan for decorated algorithms; if not specified, only detected algorithms will be used (or else those specified in packages
  • do_timings – True if timing information should be printed after each algorithm, False otherwise
  • do_immediate_injection – Perform injection with objects as they are created; can result in multiple calls to the same inject-annotated methods
  • do_post_run_injection – Perform injection at the end of the run. This will only set the last object of any type created.
  • inject_inputs – True if inputs should be injected; only active if one of do_immediate_injection or do_post_run_injection is True. These variables define when the injection of inputs is done; if immediate injection is True, injection of inputs is done at the start of the run, otherwise it is done at the end.
  • do_direct_injection – True if direct injection into methods should be supported. This will allow any of the inputs or generated outputs to be injected into a method
  • use_unscanned_annotated_algorithms – True if algorithms that have been detected outside of the packages argument specified above should be used
  • provenance_path – Path to file to append full provenance data to If None no provenance is written
algorithm_timings
execute_mapping()[source]

Executes the algorithms

Return type:None
get_completed_tokens()[source]

Get all of the tokens that have completed as part of this execution

Returns:A list of tokens
get_item(item_type)[source]

Get an item from the outputs of the execution

Parameters:item_type – the item from the internal type mapping to be returned
Returns:the returned item
get_items()[source]

Get all the outputs from a execution

Returns:dictionary of types as keys and values.
pacman.executor.token_states module
class pacman.executor.token_states.TokenStates[source]

Bases: object

Keeps track of multiple token state objects to determine if they are complete

get_completed_tokens()[source]

Get a list of tokens that have been completed

is_token_complete(token)[source]

True if the given token has completed

is_tracking_token(token)[source]

Determine if the token is being tracked

process_output_token(output_token)[source]

Process an output token marking a process or part as complete

track_token(token)[source]

Start tracking a token

Module contents
class pacman.executor.AlgorithmMetadataXmlReader(xml_paths)[source]

Bases: object

Converts an XML file into algorithm data.

Parameters:xml_paths – paths to extra metadata files
Return type:None
decode_algorithm_data_objects()[source]
Returns:the algorithm data objects which represent all the algorithm’s inputs and outputs
class pacman.executor.PACMANAlgorithmExecutor(algorithms, optional_algorithms, inputs, required_outputs, tokens, required_output_tokens, xml_paths=None, packages=None, do_timings=True, print_timings=False, do_immediate_injection=True, do_post_run_injection=False, inject_inputs=True, do_direct_injection=True, use_unscanned_annotated_algorithms=True, provenance_path=None, provenance_name=None)[source]

Bases: object

An executor of PACMAN algorithms where the order is deduced from the input and outputs of the algorithm using an XML description of the algorithm.

Parameters:
  • algorithms – A list of algorithms that must all be run
  • optional_algorithms – A list of algorithms that must be run if their inputs are available
  • inputs – A dict of input type to value
  • required_outputs – A list of output types that must be generated
  • tokens – A list of tokens that should be considered to have been generated
  • required_output_tokens – A list of tokens that should be generated by the end of the run
  • xml_paths – An optional list of paths to XML files containing algorithm descriptions; if not specified, only detected algorithms will be used (or else those found in packages)
  • packages – An optional list of packages to scan for decorated algorithms; if not specified, only detected algorithms will be used (or else those specified in packages
  • do_timings – True if timing information should be printed after each algorithm, False otherwise
  • do_immediate_injection – Perform injection with objects as they are created; can result in multiple calls to the same inject-annotated methods
  • do_post_run_injection – Perform injection at the end of the run. This will only set the last object of any type created.
  • inject_inputs – True if inputs should be injected; only active if one of do_immediate_injection or do_post_run_injection is True. These variables define when the injection of inputs is done; if immediate injection is True, injection of inputs is done at the start of the run, otherwise it is done at the end.
  • do_direct_injection – True if direct injection into methods should be supported. This will allow any of the inputs or generated outputs to be injected into a method
  • use_unscanned_annotated_algorithms – True if algorithms that have been detected outside of the packages argument specified above should be used
  • provenance_path – Path to file to append full provenance data to If None no provenance is written
algorithm_timings
execute_mapping()[source]

Executes the algorithms

Return type:None
get_completed_tokens()[source]

Get all of the tokens that have completed as part of this execution

Returns:A list of tokens
get_item(item_type)[source]

Get an item from the outputs of the execution

Parameters:item_type – the item from the internal type mapping to be returned
Returns:the returned item
get_items()[source]

Get all the outputs from a execution

Returns:dictionary of types as keys and values.
pacman.model package
Subpackages
pacman.model.constraints package
Subpackages
pacman.model.constraints.key_allocator_constraints package
Submodules
pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint module
class pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint[source]

Bases: pacman.model.constraints.abstract_constraint.AbstractConstraint

A constraint on key allocation

pacman.model.constraints.key_allocator_constraints.contiguous_key_range_constraint module
class pacman.model.constraints.key_allocator_constraints.contiguous_key_range_constraint.ContiguousKeyRangeContraint[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Key allocator constraint that keeps the keys allocated to a contiguous range. Without this constraint, keys can be allocated across the key space.

pacman.model.constraints.key_allocator_constraints.fixed_key_and_mask_constraint module
class pacman.model.constraints.key_allocator_constraints.fixed_key_and_mask_constraint.FixedKeyAndMaskConstraint(keys_and_masks, key_list_function=None)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Key allocator constraint that fixes the key and mask of an edge.

Parameters:
key_list_function

A function to call to generate the keys

Returns:A python function, or None if the default function can be used
keys_and_masks

The keys and masks to be fixed

Returns:An iterable of key and mask combinations
Return type:iterable(pacman.model.routing_info.BaseKeyAndMask)
pacman.model.constraints.key_allocator_constraints.fixed_key_field_constraint module
class pacman.model.constraints.key_allocator_constraints.fixed_key_field_constraint.FixedKeyFieldConstraint(fields=None)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Constraint that indicates fields in the mask of a key.

Parameters:fields (iterable(pacman.utilities.utility_objs.Field)) – any fields that define regions in the mask with further limitations
Raises:PacmanInvalidParameterException – if any of the fields are outside of the mask i.e. mask & field.value != field.value or if any of the field masks overlap i.e., field.value & other_field.value != 0
fields

Any fields in the mask, i.e., ranges of the mask that have further limitations

Returns:Iterable of fields, ordered by mask with the highest bit range first
Return type:iterable(pacman.utilities.utility_objs.Field)
pacman.model.constraints.key_allocator_constraints.fixed_mask_constraint module
class pacman.model.constraints.key_allocator_constraints.fixed_mask_constraint.FixedMaskConstraint(mask)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

A key allocator that fixes the mask to be assigned to an edge.

Parameters:mask (int) – the mask to be used during key allocation
mask

The mask to be used

Returns:The mask to be used
Return type:int
pacman.model.constraints.key_allocator_constraints.flexi_key_field_constraint module
class pacman.model.constraints.key_allocator_constraints.flexi_key_field_constraint.FlexiKeyFieldConstraint(fields)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Constraint that indicates fields in the mask without a specific size or position.

fields
pacman.model.constraints.key_allocator_constraints.share_key_constraint module
class pacman.model.constraints.key_allocator_constraints.share_key_constraint.ShareKeyConstraint(other_partitions)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Constraint to allow the same keys to be allocated to multiple edges via partitions.

Parameters:other_partitions – the other edges which keys are shared with.
other_partitions
Module contents
class pacman.model.constraints.key_allocator_constraints.AbstractKeyAllocatorConstraint[source]

Bases: pacman.model.constraints.abstract_constraint.AbstractConstraint

A constraint on key allocation

class pacman.model.constraints.key_allocator_constraints.ContiguousKeyRangeContraint[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Key allocator constraint that keeps the keys allocated to a contiguous range. Without this constraint, keys can be allocated across the key space.

class pacman.model.constraints.key_allocator_constraints.FixedKeyFieldConstraint(fields=None)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Constraint that indicates fields in the mask of a key.

Parameters:fields (iterable(pacman.utilities.utility_objs.Field)) – any fields that define regions in the mask with further limitations
Raises:PacmanInvalidParameterException – if any of the fields are outside of the mask i.e. mask & field.value != field.value or if any of the field masks overlap i.e., field.value & other_field.value != 0
fields

Any fields in the mask, i.e., ranges of the mask that have further limitations

Returns:Iterable of fields, ordered by mask with the highest bit range first
Return type:iterable(pacman.utilities.utility_objs.Field)
class pacman.model.constraints.key_allocator_constraints.FixedKeyAndMaskConstraint(keys_and_masks, key_list_function=None)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Key allocator constraint that fixes the key and mask of an edge.

Parameters:
key_list_function

A function to call to generate the keys

Returns:A python function, or None if the default function can be used
keys_and_masks

The keys and masks to be fixed

Returns:An iterable of key and mask combinations
Return type:iterable(pacman.model.routing_info.BaseKeyAndMask)
class pacman.model.constraints.key_allocator_constraints.FixedMaskConstraint(mask)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

A key allocator that fixes the mask to be assigned to an edge.

Parameters:mask (int) – the mask to be used during key allocation
mask

The mask to be used

Returns:The mask to be used
Return type:int
class pacman.model.constraints.key_allocator_constraints.FlexiKeyFieldConstraint(fields)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Constraint that indicates fields in the mask without a specific size or position.

fields
class pacman.model.constraints.key_allocator_constraints.ShareKeyConstraint(other_partitions)[source]

Bases: pacman.model.constraints.key_allocator_constraints.abstract_key_allocator_constraint.AbstractKeyAllocatorConstraint

Constraint to allow the same keys to be allocated to multiple edges via partitions.

Parameters:other_partitions – the other edges which keys are shared with.
other_partitions
pacman.model.constraints.partitioner_constraints package
Submodules
pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint module
class pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint.AbstractPartitionerConstraint[source]

Bases: pacman.model.constraints.abstract_constraint.AbstractConstraint

A constraint on the partitioning of a graph

pacman.model.constraints.partitioner_constraints.fixed_vertex_atoms_constraint module
class pacman.model.constraints.partitioner_constraints.fixed_vertex_atoms_constraint.FixedVertexAtomsConstraint(size)[source]

Bases: pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint.AbstractPartitionerConstraint

A constraint which specifies the exact number of atoms on each division of a vertex.

Parameters:size (int) – The exact number of atoms to split the vertex into
size

The exact number of atoms to split the vertex into

Return type:int
pacman.model.constraints.partitioner_constraints.max_vertex_atoms_constraint module
class pacman.model.constraints.partitioner_constraints.max_vertex_atoms_constraint.MaxVertexAtomsConstraint(size)[source]

Bases: pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint.AbstractPartitionerConstraint

A constraint which limits the number of atoms on each division of a vertex.

Parameters:size (int) – The maximum number of atoms to split the vertex into
size

The maximum number of atoms to split the vertex into

Return type:int
pacman.model.constraints.partitioner_constraints.same_atoms_as_vertex_constraint module
class pacman.model.constraints.partitioner_constraints.same_atoms_as_vertex_constraint.SameAtomsAsVertexConstraint(vertex)[source]

Bases: pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint.AbstractPartitionerConstraint

A constraint which indicates that a vertex must be split in the same way as another vertex.

Parameters:vertex (pacman.model.graphs.application.ApplicationVertex) – The vertex to which the constraint refers
Raises:None – does not raise any known exceptions
vertex

The vertex to partition with

Returns:the vertex
Return type:pacman.model.graphs.application.ApplicationVertex
Raises:None – does not raise any known exceptions
Module contents
class pacman.model.constraints.partitioner_constraints.AbstractPartitionerConstraint[source]

Bases: pacman.model.constraints.abstract_constraint.AbstractConstraint

A constraint on the partitioning of a graph

class pacman.model.constraints.partitioner_constraints.FixedVertexAtomsConstraint(size)[source]

Bases: pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint.AbstractPartitionerConstraint

A constraint which specifies the exact number of atoms on each division of a vertex.

Parameters:size (int) – The exact number of atoms to split the vertex into
size

The exact number of atoms to split the vertex into

Return type:int
class pacman.model.constraints.partitioner_constraints.MaxVertexAtomsConstraint(size)[source]

Bases: pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint.AbstractPartitionerConstraint

A constraint which limits the number of atoms on each division of a vertex.

Parameters:size (int) – The maximum number of atoms to split the vertex into
size

The maximum number of atoms to split the vertex into

Return type:int
class pacman.model.constraints.partitioner_constraints.SameAtomsAsVertexConstraint(vertex)[source]

Bases: pacman.model.constraints.partitioner_constraints.abstract_partitioner_constraint.AbstractPartitionerConstraint

A constraint which indicates that a vertex must be split in the same way as another vertex.

Parameters:vertex (pacman.model.graphs.application.ApplicationVertex) – The vertex to which the constraint refers
Raises:None – does not raise any known exceptions
vertex

The vertex to partition with

Returns:the vertex
Return type:pacman.model.graphs.application.ApplicationVertex
Raises:None – does not raise any known exceptions
pacman.model.constraints.placer_constraints package
Submodules
pacman.model.constraints.placer_constraints.abstract_placer_constraint module
class pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint[source]

Bases: pacman.model.constraints.abstract_constraint.AbstractConstraint

A constraint on placement

pacman.model.constraints.placer_constraints.board_constraint module
class pacman.model.constraints.placer_constraints.board_constraint.BoardConstraint(board_address)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

A constraint on the board on which a placement is made.

Parameters:board_address – The IP address of the Ethernet of the board to be used
board_address

The board of the constraint

pacman.model.constraints.placer_constraints.chip_and_core_constraint module
class pacman.model.constraints.placer_constraints.chip_and_core_constraint.ChipAndCoreConstraint(x, y, p=None)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

A constraint to place a vertex on a specific chip and, optionally, a specific core on that chip.

Parameters:
  • x (int) – the x-coordinate of the chip
  • y (int) – the y-coordinate of the chip
  • p (int) – the processor (if any) of the chip
Raises:

None – does not raise any known exceptions
location

The location as a dictionary with three keys: “x”, “y” and “p”

Returns:a dictionary containing the location
Return type:dict of {“x”: int, “y”: int, “p”: int}
Raises:None – does not raise any known exceptions
p

The processor on the chip

Returns:the processor ID, or None if that is not constrained
Return type:int or None
Raises:None – does not raise any known exceptions
x

The x-coordinate of the chip

Returns:the x-coordinate
Return type:int
Raises:None – does not raise any known exceptions
y

The y-coordinate of the chip

Returns:the y-coordinate
Return type:int
Raises:None – does not raise any known exceptions
pacman.model.constraints.placer_constraints.radial_placement_from_chip_constraint module
class pacman.model.constraints.placer_constraints.radial_placement_from_chip_constraint.RadialPlacementFromChipConstraint(x, y)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

A constraint that attempts to place a vertex as close to a chip as possible (including on it).

Parameters:
  • x (int) – the x-coordinate of the chip
  • y (int) – the y-coordinate of the chip
Raises:

None – does not raise any known exceptions
x
y
pacman.model.constraints.placer_constraints.same_chip_as_constraint module
class pacman.model.constraints.placer_constraints.same_chip_as_constraint.SameChipAsConstraint(vertex)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

Indicates that a vertex should be placed on the same chip as another vertex.

Parameters:vertex – The vertex to place on the same chip
vertex

The vertex to place on the same chip

Module contents
class pacman.model.constraints.placer_constraints.AbstractPlacerConstraint[source]

Bases: pacman.model.constraints.abstract_constraint.AbstractConstraint

A constraint on placement

class pacman.model.constraints.placer_constraints.BoardConstraint(board_address)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

A constraint on the board on which a placement is made.

Parameters:board_address – The IP address of the Ethernet of the board to be used
board_address

The board of the constraint

class pacman.model.constraints.placer_constraints.ChipAndCoreConstraint(x, y, p=None)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

A constraint to place a vertex on a specific chip and, optionally, a specific core on that chip.

Parameters:
  • x (int) – the x-coordinate of the chip
  • y (int) – the y-coordinate of the chip
  • p (int) – the processor (if any) of the chip
Raises:

None – does not raise any known exceptions
location

The location as a dictionary with three keys: “x”, “y” and “p”

Returns:a dictionary containing the location
Return type:dict of {“x”: int, “y”: int, “p”: int}
Raises:None – does not raise any known exceptions
p

The processor on the chip

Returns:the processor ID, or None if that is not constrained
Return type:int or None
Raises:None – does not raise any known exceptions
x

The x-coordinate of the chip

Returns:the x-coordinate
Return type:int
Raises:None – does not raise any known exceptions
y

The y-coordinate of the chip

Returns:the y-coordinate
Return type:int
Raises:None – does not raise any known exceptions
class pacman.model.constraints.placer_constraints.RadialPlacementFromChipConstraint(x, y)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

A constraint that attempts to place a vertex as close to a chip as possible (including on it).

Parameters:
  • x (int) – the x-coordinate of the chip
  • y (int) – the y-coordinate of the chip
Raises:

None – does not raise any known exceptions
x
y
class pacman.model.constraints.placer_constraints.SameChipAsConstraint(vertex)[source]

Bases: pacman.model.constraints.placer_constraints.abstract_placer_constraint.AbstractPlacerConstraint

Indicates that a vertex should be placed on the same chip as another vertex.

Parameters:vertex – The vertex to place on the same chip
vertex

The vertex to place on the same chip

Submodules
pacman.model.constraints.abstract_constraint module
class pacman.model.constraints.abstract_constraint.AbstractConstraint[source]

Bases: object

A constraint of some sort which an algorithm might or might not support

Module contents
class pacman.model.constraints.AbstractConstraint[source]

Bases: object

A constraint of some sort which an algorithm might or might not support

pacman.model.decorators package
Submodules
pacman.model.decorators.overrides module
Module contents
pacman.model.graphs package
Subpackages
pacman.model.graphs.application package
Submodules
pacman.model.graphs.application.application_edge module
class pacman.model.graphs.application.application_edge.ApplicationEdge(pre_vertex, post_vertex, traffic_type=<EdgeTrafficType.MULTICAST: 1>, label=None, machine_edge_type=<class 'pacman.model.graphs.machine.machine_edge.MachineEdge'>)[source]

Bases: pacman.model.graphs.abstract_edge.AbstractEdge

A simple implementation of an application edge.

Parameters:
create_machine_edge(pre_vertex, post_vertex, label)[source]

Create a machine edge between two machine vertices

Parameters:
Returns:

The created machine edge
Return type:

pacman.model.graphs.machine.MachineEdge
label

The label of the edge

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
post_vertex

The vertex at the end of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
pre_vertex

The vertex at the start of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
traffic_type

The traffic type of the edge

Return type:pacman.model.graphs.common.edge_traffic_type.EdgeTrafficType
pacman.model.graphs.application.application_fpga_vertex module
class pacman.model.graphs.application.application_fpga_vertex.ApplicationFPGAVertex(n_atoms, fpga_id, fpga_link_id, board_address=None, label=None, constraints=None, max_atoms_per_core=9223372036854775807)[source]

Bases: pacman.model.graphs.application.application_vertex.ApplicationVertex, pacman.model.graphs.abstract_fpga.AbstractFPGA

A virtual vertex on an FPGA link.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
create_machine_vertex(vertex_slice, resources_required, label=None, constraints=None)[source]

Create a machine vertex from this application vertex

Parameters:
  • vertex_slice (Slice) – The slice of atoms that the machine vertex will cover
  • resources_required (ResourceContainer) – the resources used by the machine vertex
  • label (str or None) – human readable label for the machine vertex
  • constraints (iterable(AbstractConstraint)) – Constraints to be passed on to the machine vertex
fpga_id

The ID of the FPGA to which the vertex is connected.

Return type:int

The link of the FPGA to which the vertex is connected.

Return type:int
get_resources_used_by_atoms(vertex_slice)[source]

Get the separate resource requirements for a range of atoms

Parameters:vertex_slice (Slice) – the low value of atoms to calculate resources from
Returns:a Resource container that contains a CPUCyclesPerTickResource, DTCMResource and SDRAMResource
Return type:ResourceContainer
Raises:None – this method does not raise any known exception
n_atoms

The number of atoms in the vertex

Return type:int
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip
virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
pacman.model.graphs.application.application_graph module
class pacman.model.graphs.application.application_graph.ApplicationGraph(label)[source]

Bases: pacman.model.graphs.impl.graph.Graph

An application-level abstraction of a graph.

pacman.model.graphs.application.application_outgoing_edge_partition module
class pacman.model.graphs.application.application_outgoing_edge_partition.ApplicationOutgoingEdgePartition(identifier, constraints=None, label=None)[source]

Bases: pacman.model.graphs.impl.outgoing_edge_partition.OutgoingEdgePartition

Edge partition for the application graph.

pacman.model.graphs.application.application_vertex module
class pacman.model.graphs.application.application_vertex.ApplicationVertex(label=None, constraints=None, max_atoms_per_core=9223372036854775807)[source]

Bases: pacman.model.graphs.abstract_vertex.AbstractVertex

A vertex that can be broken down into a number of smaller vertices based on the resources that the vertex requires.

Parameters:
  • label (str) – The optional name of the vertex
  • constraints (iterable(AbstractConstraint)) – The optional initial constraints of the vertex
  • max_atoms_per_core (int) – the max number of atoms that can be placed on a core, used in partitioning
Raises:

pacman.exceptions.PacmanInvalidParameterException –

  • If one of the constraints is not valid
create_machine_vertex(vertex_slice, resources_required, label=None, constraints=None)[source]

Create a machine vertex from this application vertex

Parameters:
  • vertex_slice (Slice) – The slice of atoms that the machine vertex will cover
  • resources_required (ResourceContainer) – the resources used by the machine vertex
  • label (str or None) – human readable label for the machine vertex
  • constraints (iterable(AbstractConstraint)) – Constraints to be passed on to the machine vertex
get_max_atoms_per_core()[source]
get_resources_used_by_atoms(vertex_slice)[source]

Get the separate resource requirements for a range of atoms

Parameters:vertex_slice (Slice) – the low value of atoms to calculate resources from
Returns:a Resource container that contains a CPUCyclesPerTickResource, DTCMResource and SDRAMResource
Return type:ResourceContainer
Raises:None – this method does not raise any known exception
n_atoms

The number of atoms in the vertex

Return type:int
Module contents
class pacman.model.graphs.application.ApplicationEdge(pre_vertex, post_vertex, traffic_type=<EdgeTrafficType.MULTICAST: 1>, label=None, machine_edge_type=<class 'pacman.model.graphs.machine.machine_edge.MachineEdge'>)[source]

Bases: pacman.model.graphs.abstract_edge.AbstractEdge

A simple implementation of an application edge.

Parameters:
create_machine_edge(pre_vertex, post_vertex, label)[source]

Create a machine edge between two machine vertices

Parameters:
Returns:

The created machine edge
Return type:

pacman.model.graphs.machine.MachineEdge
label

The label of the edge

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
post_vertex

The vertex at the end of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
pre_vertex

The vertex at the start of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
traffic_type

The traffic type of the edge

Return type:pacman.model.graphs.common.edge_traffic_type.EdgeTrafficType
class pacman.model.graphs.application.ApplicationFPGAVertex(n_atoms, fpga_id, fpga_link_id, board_address=None, label=None, constraints=None, max_atoms_per_core=9223372036854775807)[source]

Bases: pacman.model.graphs.application.application_vertex.ApplicationVertex, pacman.model.graphs.abstract_fpga.AbstractFPGA

A virtual vertex on an FPGA link.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
create_machine_vertex(vertex_slice, resources_required, label=None, constraints=None)[source]

Create a machine vertex from this application vertex

Parameters:
  • vertex_slice (Slice) – The slice of atoms that the machine vertex will cover
  • resources_required (ResourceContainer) – the resources used by the machine vertex
  • label (str or None) – human readable label for the machine vertex
  • constraints (iterable(AbstractConstraint)) – Constraints to be passed on to the machine vertex
fpga_id

The ID of the FPGA to which the vertex is connected.

Return type:int

The link of the FPGA to which the vertex is connected.

Return type:int
get_resources_used_by_atoms(vertex_slice)[source]

Get the separate resource requirements for a range of atoms

Parameters:vertex_slice (Slice) – the low value of atoms to calculate resources from
Returns:a Resource container that contains a CPUCyclesPerTickResource, DTCMResource and SDRAMResource
Return type:ResourceContainer
Raises:None – this method does not raise any known exception
n_atoms

The number of atoms in the vertex

Return type:int
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip
virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
class pacman.model.graphs.application.ApplicationGraph(label)[source]

Bases: pacman.model.graphs.impl.graph.Graph

An application-level abstraction of a graph.

class pacman.model.graphs.application.ApplicationOutgoingEdgePartition(identifier, constraints=None, label=None)[source]

Bases: pacman.model.graphs.impl.outgoing_edge_partition.OutgoingEdgePartition

Edge partition for the application graph.

class pacman.model.graphs.application.ApplicationVertex(label=None, constraints=None, max_atoms_per_core=9223372036854775807)[source]

Bases: pacman.model.graphs.abstract_vertex.AbstractVertex

A vertex that can be broken down into a number of smaller vertices based on the resources that the vertex requires.

Parameters:
  • label (str) – The optional name of the vertex
  • constraints (iterable(AbstractConstraint)) – The optional initial constraints of the vertex
  • max_atoms_per_core (int) – the max number of atoms that can be placed on a core, used in partitioning
Raises:

pacman.exceptions.PacmanInvalidParameterException –

  • If one of the constraints is not valid
create_machine_vertex(vertex_slice, resources_required, label=None, constraints=None)[source]

Create a machine vertex from this application vertex

Parameters:
  • vertex_slice (Slice) – The slice of atoms that the machine vertex will cover
  • resources_required (ResourceContainer) – the resources used by the machine vertex
  • label (str or None) – human readable label for the machine vertex
  • constraints (iterable(AbstractConstraint)) – Constraints to be passed on to the machine vertex
get_max_atoms_per_core()[source]
get_resources_used_by_atoms(vertex_slice)[source]

Get the separate resource requirements for a range of atoms

Parameters:vertex_slice (Slice) – the low value of atoms to calculate resources from
Returns:a Resource container that contains a CPUCyclesPerTickResource, DTCMResource and SDRAMResource
Return type:ResourceContainer
Raises:None – this method does not raise any known exception
n_atoms

The number of atoms in the vertex

Return type:int
class pacman.model.graphs.application.ApplicationSpiNNakerLinkVertex(n_atoms, spinnaker_link_id, board_address=None, label=None, constraints=None, max_atoms_per_core=9223372036854775807)[source]

Bases: pacman.model.graphs.application.application_vertex.ApplicationVertex, pacman.model.graphs.abstract_spinnaker_link.AbstractSpiNNakerLink

A virtual vertex on a SpiNNaker Link.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
create_machine_vertex(vertex_slice, resources_required, label=None, constraints=None)[source]

Create a machine vertex from this application vertex

Parameters:
  • vertex_slice (Slice) – The slice of atoms that the machine vertex will cover
  • resources_required (ResourceContainer) – the resources used by the machine vertex
  • label (str or None) – human readable label for the machine vertex
  • constraints (iterable(AbstractConstraint)) – Constraints to be passed on to the machine vertex
get_resources_used_by_atoms(vertex_slice)[source]

Get the separate resource requirements for a range of atoms

Parameters:vertex_slice (Slice) – the low value of atoms to calculate resources from
Returns:a Resource container that contains a CPUCyclesPerTickResource, DTCMResource and SDRAMResource
Return type:ResourceContainer
Raises:None – this method does not raise any known exception
n_atoms

The number of atoms in the vertex

Return type:int
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip

The SpiNNaker Link that the vertex is connected to.

virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
pacman.model.graphs.common package
Submodules
pacman.model.graphs.common.constrained_object module
class pacman.model.graphs.common.constrained_object.ConstrainedObject(constraints=None)[source]

Bases: object

An implementation of an object which holds constraints.

Parameters:constraints – Any initial constraints
add_constraint(constraint)[source]

Add a new constraint to the collection of constraints

Parameters:constraint (pacman.model.constraints.AbstractConstraint) – constraint to add
Return type:None
Raises:pacman.exceptions.PacmanInvalidParameterException – If the constraint is not valid
add_constraints(constraints)[source]

Add an iterable of constraints to the collection of constraints

Parameters:constraints (iterable(pacman.model.constraints.AbstractConstraint)) – the constraints to add
Return type:None
Raises:pacman.exceptions.PacmanInvalidParameterException – If one of the constraints is not valid
constraints

An iterable of constraints

Returns:the constraints
Return type:iterable(pacman.model.constraints.AbstractConstraint)
Raises:None – Raises no known exceptions
pacman.model.graphs.common.edge_traffic_type module
class pacman.model.graphs.common.edge_traffic_type.EdgeTrafficType[source]

Bases: enum.IntEnum

Indicates the traffic type of an Edge in a graph

FIXED_ROUTE = 2
MULTICAST = 1
SDRAM = 3
pacman.model.graphs.common.graph_mapper module
class pacman.model.graphs.common.graph_mapper.GraphMapper[source]

Bases: object

A mapping between an Application Graph and a Machine Graph.

add_edge_mapping(machine_edge, application_edge)[source]

Add a mapping between a machine edge and an application edge

Parameters:
  • machine_edge – An edge from a Machine Graph
  • application_edge – An edge from an Application Graph
add_vertex_mapping(machine_vertex, vertex_slice, application_vertex)[source]

Add a mapping between application and machine vertices

Parameters:
  • machine_vertex – A vertex from a Machine Graph
  • vertex_slice (pacman.model.graphs.common.Slice) – The range of atoms from the application vertex that is going to be in the machine_vertex
  • application_vertex – A vertex from an Application Graph
Raises:

pacman.exceptions.PacmanValueError – If atom selection is out of bounds.
get_application_edge(machine_edge)[source]

Get the application edge mapped to a machine edge

Parameters:machine_edge – An edge from a Machine Graph
Returns:A machine edge, or None if none
get_application_vertex(machine_vertex)[source]

Get the application vertex mapped to a machine vertex

Parameters:machine_vertex – A vertex from a Machine Graph
Returns:an application vertex, or None if none
get_machine_edges(application_edge)[source]

Get all machine edges mapped to a given application edge

Parameters:application_edge – An edge from an Application Graph
Returns:An iterable of machine edges or None if none
get_machine_vertex_index(machine_vertex)[source]

Get the index of a machine vertex within the list of such vertices associated with an application vertex

get_machine_vertices(application_vertex)[source]

Get all machine vertices mapped to a given application vertex

Parameters:application_vertex – A vertex from an Application Graph
Returns:An iterable of machine vertices or None if none
get_slice(machine_vertex)[source]

Get the slice mapped to a machine vertex

Parameters:machine_vertex – A vertex in a Machine Graph
Returns:a slice object containing the low and high atom or None if none
get_slices(application_vertex)[source]

Get all the slices mapped to an application vertex

pacman.model.graphs.common.slice module
class pacman.model.graphs.common.slice.Slice[source]

Bases: pacman.model.graphs.common.slice.Slice

Represents a slice of a vertex.

Attr int lo_atom:
 The lowest atom represented in the slice.
Attr int hi_atom:
 The highest atom represented in the slice.
Attr int n_atoms:
 The number of atoms represented by the slice.
Attr as_slice:This slice represented as a slice() object (for use in indexing lists, arrays, etc.)

Create a new Slice object.

Parameters:
  • lo_atom (int) – Index of the lowest atom to represent.
  • hi_atom (int) – Index of the highest atom to represent.
Raises:

PacmanValueError – If the bounds of the slice are invalid.
Module contents
class pacman.model.graphs.common.ConstrainedObject(constraints=None)[source]

Bases: object

An implementation of an object which holds constraints.

Parameters:constraints – Any initial constraints
add_constraint(constraint)[source]

Add a new constraint to the collection of constraints

Parameters:constraint (pacman.model.constraints.AbstractConstraint) – constraint to add
Return type:None
Raises:pacman.exceptions.PacmanInvalidParameterException – If the constraint is not valid
add_constraints(constraints)[source]

Add an iterable of constraints to the collection of constraints

Parameters:constraints (iterable(pacman.model.constraints.AbstractConstraint)) – the constraints to add
Return type:None
Raises:pacman.exceptions.PacmanInvalidParameterException – If one of the constraints is not valid
constraints

An iterable of constraints

Returns:the constraints
Return type:iterable(pacman.model.constraints.AbstractConstraint)
Raises:None – Raises no known exceptions
class pacman.model.graphs.common.EdgeTrafficType[source]

Bases: enum.IntEnum

Indicates the traffic type of an Edge in a graph

FIXED_ROUTE = 2
MULTICAST = 1
SDRAM = 3
class pacman.model.graphs.common.GraphMapper[source]

Bases: object

A mapping between an Application Graph and a Machine Graph.

add_edge_mapping(machine_edge, application_edge)[source]

Add a mapping between a machine edge and an application edge

Parameters:
  • machine_edge – An edge from a Machine Graph
  • application_edge – An edge from an Application Graph
add_vertex_mapping(machine_vertex, vertex_slice, application_vertex)[source]

Add a mapping between application and machine vertices

Parameters:
  • machine_vertex – A vertex from a Machine Graph
  • vertex_slice (pacman.model.graphs.common.Slice) – The range of atoms from the application vertex that is going to be in the machine_vertex
  • application_vertex – A vertex from an Application Graph
Raises:

pacman.exceptions.PacmanValueError – If atom selection is out of bounds.
get_application_edge(machine_edge)[source]

Get the application edge mapped to a machine edge

Parameters:machine_edge – An edge from a Machine Graph
Returns:A machine edge, or None if none
get_application_vertex(machine_vertex)[source]

Get the application vertex mapped to a machine vertex

Parameters:machine_vertex – A vertex from a Machine Graph
Returns:an application vertex, or None if none
get_machine_edges(application_edge)[source]

Get all machine edges mapped to a given application edge

Parameters:application_edge – An edge from an Application Graph
Returns:An iterable of machine edges or None if none
get_machine_vertex_index(machine_vertex)[source]

Get the index of a machine vertex within the list of such vertices associated with an application vertex

get_machine_vertices(application_vertex)[source]

Get all machine vertices mapped to a given application vertex

Parameters:application_vertex – A vertex from an Application Graph
Returns:An iterable of machine vertices or None if none
get_slice(machine_vertex)[source]

Get the slice mapped to a machine vertex

Parameters:machine_vertex – A vertex in a Machine Graph
Returns:a slice object containing the low and high atom or None if none
get_slices(application_vertex)[source]

Get all the slices mapped to an application vertex

class pacman.model.graphs.common.Slice[source]

Bases: pacman.model.graphs.common.slice.Slice

Represents a slice of a vertex.

Attr int lo_atom:
 The lowest atom represented in the slice.
Attr int hi_atom:
 The highest atom represented in the slice.
Attr int n_atoms:
 The number of atoms represented by the slice.
Attr as_slice:This slice represented as a slice() object (for use in indexing lists, arrays, etc.)

Create a new Slice object.

Parameters:
  • lo_atom (int) – Index of the lowest atom to represent.
  • hi_atom (int) – Index of the highest atom to represent.
Raises:

PacmanValueError – If the bounds of the slice are invalid.
pacman.model.graphs.impl package
Submodules
pacman.model.graphs.impl.graph module
class pacman.model.graphs.impl.graph.Graph(allowed_vertex_types, allowed_edge_types, allowed_partition_types, label)[source]

Bases: pacman.model.graphs.common.constrained_object.ConstrainedObject, pacman.model.graphs.abstract_graph.AbstractGraph

A graph implementation that specifies the allowed types of the vertices and edges.

Parameters:
  • allowed_vertex_types – A single or tuple of types of vertex to be allowed in the graph
  • allowed_edge_types – A single or tuple of types of edges to be allowed in the graph
  • allowed_partition_types – A single or tuple of types of partitions to be allowed in the graph
  • label – The label on the graph, or None
add_edge(edge, outgoing_edge_partition_name)[source]

Add an edge to the graph.

Parameters:
  • edge (pacman.model.graphs.AbstractEdge) – The edge to add
  • outgoing_edge_partition_name (str) – The name of the edge partition to add the edge to; each edge partition is the partition of edges that start at the same vertex
Raises:

PacmanInvalidParameterException – If the edge is not of a valid type or if edges have already been added to this partition that start at a different vertex to this one
add_outgoing_edge_partition(outgoing_edge_partition)[source]

Add an outgoing edge partition to the graph.

Parameters:outgoing_edge_partition (pacman.model.graphs.AbstractOutgoingEdgePartition) – The outgoing edge partition to add
Raises:PacmanAlreadyExistsException – If a partition already exists with the same pre_vertex and identifier
add_vertex(vertex)[source]

Add a vertex to the graph.

Parameters:

vertex (pacman.model.graphs.AbstractVertex) – The vertex to add
Raises:
edges

The edges in the graph

Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex(vertex)[source]

Get all the edges that end at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get end
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex_with_partition_name(vertex, partition_name)[source]

Get all the edges that end at the given vertex, and reside in the correct partition ID.

Parameters:
Returns:

iterable(pacman.model.graphs.AbstractEdge)
get_edges_starting_at_vertex(vertex)[source]

Get all the edges that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get start
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_outgoing_edge_partition_starting_at_vertex(vertex, outgoing_edge_partition_name)[source]

Get the given outgoing edge partition that starts at the given vertex, or None if no such edge partition exists.

Parameters:
  • vertex (pacman.model.graphs.AbstractVertex) – The vertex at the start of the edges in the partition
  • outgoing_edge_partition_name (str) – The name of the edge partition
Return type:

pacman.model.graphs.AbstractOutgoingEdgePartition
get_outgoing_edge_partitions_starting_at_vertex(vertex)[source]

Get all the edge partitions that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edge partitions to find starts
Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
get_outgoing_partition_for_edge(edge)[source]

gets the outgoing partition this edge is associated with.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to find associated partition
Returns:the outgoing partition
Return type:pacman.model.graphs.AbstractOutgoingEdgePartition
label

The label of the graph.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_outgoing_edge_partitions

The number of outgoing edge partitions in the graph.

Return type:int
n_vertices

The number of vertices in the graph.

Return type:int
outgoing_edge_partitions

The outgoing edge partitions in the graph.

Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
vertex_by_label(label)[source]
vertices

The vertices in the graph.

Return type:iterable(pacman.model.graphs.AbstractVertex)
pacman.model.graphs.impl.outgoing_edge_partition module
class pacman.model.graphs.impl.outgoing_edge_partition.OutgoingEdgePartition(identifier, allowed_edge_types, constraints=None, label=None, traffic_weight=1)[source]

Bases: pacman.model.graphs.common.constrained_object.ConstrainedObject, pacman.model.graphs.abstract_outgoing_edge_partition.AbstractOutgoingEdgePartition

A collection of edges which start at a single vertex which have the same semantics and so can share a single key.

Parameters:
  • identifier – The identifier of the partition
  • allowed_edge_types – The types of edges allowed
  • constraints – Any initial constraints
  • label – An optional label of the partition
  • traffic_weight – The weight of traffic going down this partition
add_edge(edge)[source]

Add an edge to the outgoing edge partition.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to add
Raises:pacman.exceptions.PacmanInvalidParameterException – If the starting vertex of the edge does not match that of the edges already in the partition
edges

The edges in this outgoing edge partition.

Return type:iterable(pacman.model.graphs.AbstractEdge)
identifier

The identifier of this outgoing edge partition.

Return type:str
label

The label of the outgoing edge partition.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_edges

The number of edges in the outgoing edge partition.

Return type:int
pre_vertex

The vertex at which all edges in this outgoing edge partition start.

Return type:pacman.model.graphs.AbstractVertex
traffic_type

The traffic type of all the edges in this outgoing edge partition.

Return type:pacman.model.graphs.common.EdgeTrafficType
traffic_weight

The weight of the traffic in this outgoing edge partition compared to other partitions.

Return type:int
Module contents
class pacman.model.graphs.impl.Graph(allowed_vertex_types, allowed_edge_types, allowed_partition_types, label)[source]

Bases: pacman.model.graphs.common.constrained_object.ConstrainedObject, pacman.model.graphs.abstract_graph.AbstractGraph

A graph implementation that specifies the allowed types of the vertices and edges.

Parameters:
  • allowed_vertex_types – A single or tuple of types of vertex to be allowed in the graph
  • allowed_edge_types – A single or tuple of types of edges to be allowed in the graph
  • allowed_partition_types – A single or tuple of types of partitions to be allowed in the graph
  • label – The label on the graph, or None
add_edge(edge, outgoing_edge_partition_name)[source]

Add an edge to the graph.

Parameters:
  • edge (pacman.model.graphs.AbstractEdge) – The edge to add
  • outgoing_edge_partition_name (str) – The name of the edge partition to add the edge to; each edge partition is the partition of edges that start at the same vertex
Raises:

PacmanInvalidParameterException – If the edge is not of a valid type or if edges have already been added to this partition that start at a different vertex to this one
add_outgoing_edge_partition(outgoing_edge_partition)[source]

Add an outgoing edge partition to the graph.

Parameters:outgoing_edge_partition (pacman.model.graphs.AbstractOutgoingEdgePartition) – The outgoing edge partition to add
Raises:PacmanAlreadyExistsException – If a partition already exists with the same pre_vertex and identifier
add_vertex(vertex)[source]

Add a vertex to the graph.

Parameters:

vertex (pacman.model.graphs.AbstractVertex) – The vertex to add
Raises:
edges

The edges in the graph

Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex(vertex)[source]

Get all the edges that end at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get end
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex_with_partition_name(vertex, partition_name)[source]

Get all the edges that end at the given vertex, and reside in the correct partition ID.

Parameters:
Returns:

iterable(pacman.model.graphs.AbstractEdge)
get_edges_starting_at_vertex(vertex)[source]

Get all the edges that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get start
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_outgoing_edge_partition_starting_at_vertex(vertex, outgoing_edge_partition_name)[source]

Get the given outgoing edge partition that starts at the given vertex, or None if no such edge partition exists.

Parameters:
  • vertex (pacman.model.graphs.AbstractVertex) – The vertex at the start of the edges in the partition
  • outgoing_edge_partition_name (str) – The name of the edge partition
Return type:

pacman.model.graphs.AbstractOutgoingEdgePartition
get_outgoing_edge_partitions_starting_at_vertex(vertex)[source]

Get all the edge partitions that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edge partitions to find starts
Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
get_outgoing_partition_for_edge(edge)[source]

gets the outgoing partition this edge is associated with.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to find associated partition
Returns:the outgoing partition
Return type:pacman.model.graphs.AbstractOutgoingEdgePartition
label

The label of the graph.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_outgoing_edge_partitions

The number of outgoing edge partitions in the graph.

Return type:int
n_vertices

The number of vertices in the graph.

Return type:int
outgoing_edge_partitions

The outgoing edge partitions in the graph.

Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
vertex_by_label(label)[source]
vertices

The vertices in the graph.

Return type:iterable(pacman.model.graphs.AbstractVertex)
class pacman.model.graphs.impl.OutgoingEdgePartition(identifier, allowed_edge_types, constraints=None, label=None, traffic_weight=1)[source]

Bases: pacman.model.graphs.common.constrained_object.ConstrainedObject, pacman.model.graphs.abstract_outgoing_edge_partition.AbstractOutgoingEdgePartition

A collection of edges which start at a single vertex which have the same semantics and so can share a single key.

Parameters:
  • identifier – The identifier of the partition
  • allowed_edge_types – The types of edges allowed
  • constraints – Any initial constraints
  • label – An optional label of the partition
  • traffic_weight – The weight of traffic going down this partition
add_edge(edge)[source]

Add an edge to the outgoing edge partition.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to add
Raises:pacman.exceptions.PacmanInvalidParameterException – If the starting vertex of the edge does not match that of the edges already in the partition
edges

The edges in this outgoing edge partition.

Return type:iterable(pacman.model.graphs.AbstractEdge)
identifier

The identifier of this outgoing edge partition.

Return type:str
label

The label of the outgoing edge partition.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_edges

The number of edges in the outgoing edge partition.

Return type:int
pre_vertex

The vertex at which all edges in this outgoing edge partition start.

Return type:pacman.model.graphs.AbstractVertex
traffic_type

The traffic type of all the edges in this outgoing edge partition.

Return type:pacman.model.graphs.common.EdgeTrafficType
traffic_weight

The weight of the traffic in this outgoing edge partition compared to other partitions.

Return type:int
pacman.model.graphs.machine package
Submodules
pacman.model.graphs.machine.machine_edge module
class pacman.model.graphs.machine.machine_edge.MachineEdge(pre_vertex, post_vertex, traffic_type=<EdgeTrafficType.MULTICAST: 1>, label=None, traffic_weight=1)[source]

Bases: pacman.model.graphs.abstract_edge.AbstractEdge

A simple implementation of a machine edge.

Parameters:
label

The label of the edge

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
post_vertex

The vertex at the end of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
pre_vertex

The vertex at the start of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
traffic_type

The traffic type of the edge

Return type:pacman.model.graphs.common.edge_traffic_type.EdgeTrafficType
traffic_weight

The amount of traffic expected to go down this edge relative to other edges

pacman.model.graphs.machine.machine_fpga_vertex module
class pacman.model.graphs.machine.machine_fpga_vertex.MachineFPGAVertex(fpga_id, fpga_link_id, board_address=None, label=None, constraints=None)[source]

Bases: pacman.model.graphs.machine.machine_vertex.MachineVertex, pacman.model.graphs.abstract_fpga.AbstractFPGA

A virtual vertex on an FPGA link.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
fpga_id

The ID of the FPGA to which the vertex is connected.

Return type:int

The link of the FPGA to which the vertex is connected.

Return type:int
resources_required

The resources required by the vertex

Return type:ResourceContainer
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip
virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
pacman.model.graphs.machine.machine_graph module
class pacman.model.graphs.machine.machine_graph.MachineGraph(label)[source]

Bases: pacman.model.graphs.impl.graph.Graph

A graph whose vertices can fit on the chips of a machine.

pacman.model.graphs.machine.machine_outgoing_edge_partition module
class pacman.model.graphs.machine.machine_outgoing_edge_partition.MachineOutgoingEdgePartition(identifier, constraints=None, label=None, traffic_weight=1)[source]

Bases: pacman.model.graphs.impl.outgoing_edge_partition.OutgoingEdgePartition

An outgoing edge partition for a Machine Graph.

Parameters:
  • identifier – The identifier of the partition
  • constraints – Any initial constraints
  • label – An optional label of the partition
  • traffic_weight – the weight of this partition in relation to other partitions
pacman.model.graphs.machine.machine_vertex module
class pacman.model.graphs.machine.machine_vertex.MachineVertex(label=None, constraints=None)[source]

Bases: pacman.model.graphs.abstract_vertex.AbstractVertex

A machine graph vertex.

Parameters:
  • label (str) – The optional name of the vertex
  • constraints (iterable(AbstractConstraint)) – The optional initial constraints of the vertex
Raises:

pacman.exceptions.PacmanInvalidParameterException – If one of the constraints is not valid
resources_required

The resources required by the vertex

Return type:ResourceContainer
pacman.model.graphs.machine.simple_machine_vertex module
class pacman.model.graphs.machine.simple_machine_vertex.SimpleMachineVertex(resources, label=None, constraints=None)[source]

Bases: pacman.model.graphs.machine.machine_vertex.MachineVertex

A MachineVertex that stores its own resources.

resources_required

The resources required by the vertex

Return type:ResourceContainer
Module contents
class pacman.model.graphs.machine.MachineEdge(pre_vertex, post_vertex, traffic_type=<EdgeTrafficType.MULTICAST: 1>, label=None, traffic_weight=1)[source]

Bases: pacman.model.graphs.abstract_edge.AbstractEdge

A simple implementation of a machine edge.

Parameters:
label

The label of the edge

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
post_vertex

The vertex at the end of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
pre_vertex

The vertex at the start of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
traffic_type

The traffic type of the edge

Return type:pacman.model.graphs.common.edge_traffic_type.EdgeTrafficType
traffic_weight

The amount of traffic expected to go down this edge relative to other edges

class pacman.model.graphs.machine.MachineFPGAVertex(fpga_id, fpga_link_id, board_address=None, label=None, constraints=None)[source]

Bases: pacman.model.graphs.machine.machine_vertex.MachineVertex, pacman.model.graphs.abstract_fpga.AbstractFPGA

A virtual vertex on an FPGA link.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
fpga_id

The ID of the FPGA to which the vertex is connected.

Return type:int

The link of the FPGA to which the vertex is connected.

Return type:int
resources_required

The resources required by the vertex

Return type:ResourceContainer
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip
virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
class pacman.model.graphs.machine.MachineGraph(label)[source]

Bases: pacman.model.graphs.impl.graph.Graph

A graph whose vertices can fit on the chips of a machine.

class pacman.model.graphs.machine.MachineOutgoingEdgePartition(identifier, constraints=None, label=None, traffic_weight=1)[source]

Bases: pacman.model.graphs.impl.outgoing_edge_partition.OutgoingEdgePartition

An outgoing edge partition for a Machine Graph.

Parameters:
  • identifier – The identifier of the partition
  • constraints – Any initial constraints
  • label – An optional label of the partition
  • traffic_weight – the weight of this partition in relation to other partitions
class pacman.model.graphs.machine.MachineSpiNNakerLinkVertex(spinnaker_link_id, board_address=None, label=None, constraints=None)[source]

Bases: pacman.model.graphs.machine.machine_vertex.MachineVertex, pacman.model.graphs.abstract_spinnaker_link.AbstractSpiNNakerLink

A virtual vertex on a SpiNNaker Link.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
resources_required

The resources required by the vertex

Return type:ResourceContainer
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip

The SpiNNaker Link that the vertex is connected to.

virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
class pacman.model.graphs.machine.MachineVertex(label=None, constraints=None)[source]

Bases: pacman.model.graphs.abstract_vertex.AbstractVertex

A machine graph vertex.

Parameters:
  • label (str) – The optional name of the vertex
  • constraints (iterable(AbstractConstraint)) – The optional initial constraints of the vertex
Raises:

pacman.exceptions.PacmanInvalidParameterException – If one of the constraints is not valid
resources_required

The resources required by the vertex

Return type:ResourceContainer
class pacman.model.graphs.machine.SimpleMachineVertex(resources, label=None, constraints=None)[source]

Bases: pacman.model.graphs.machine.machine_vertex.MachineVertex

A MachineVertex that stores its own resources.

resources_required

The resources required by the vertex

Return type:ResourceContainer
Submodules
pacman.model.graphs.abstract_edge module
class pacman.model.graphs.abstract_edge.AbstractEdge[source]

Bases: object

A directed edge in a graph between two vertices.

label

The label of the edge

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
post_vertex

The vertex at the end of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
pre_vertex

The vertex at the start of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
traffic_type

The traffic type of the edge

Return type:pacman.model.graphs.common.edge_traffic_type.EdgeTrafficType
pacman.model.graphs.abstract_fpga module
class pacman.model.graphs.abstract_fpga.AbstractFPGA[source]

Bases: pacman.model.graphs.abstract_virtual.AbstractVirtual

An Object (most likely a vertex) connected to an FPGA.

Note: It is expected that everything that is an instance of AbstractFPGA is also an instance of AbstractVertex, This is not enforced to avoid diamond inheritance.

fpga_id

The ID of the FPGA to which the vertex is connected.

Return type:int

The link of the FPGA to which the vertex is connected.

Return type:int
pacman.model.graphs.abstract_graph module
class pacman.model.graphs.abstract_graph.AbstractGraph[source]

Bases: object

A graph.

add_constraint(constraint)[source]

Add a constraint to the graph.

Parameters:constraint (AbstractConstraint) – The constraint to add
add_constraints(constraints)[source]

Add a list of constraints to the graph.

Parameters:constraints (list(AbstractConstraint)) – The list of constraints to add
add_edge(edge, outgoing_edge_partition_name)[source]

Add an edge to the graph.

Parameters:
  • edge (pacman.model.graphs.AbstractEdge) – The edge to add
  • outgoing_edge_partition_name (str) – The name of the edge partition to add the edge to; each edge partition is the partition of edges that start at the same vertex
Raises:

PacmanInvalidParameterException – If the edge is not of a valid type or if edges have already been added to this partition that start at a different vertex to this one
add_edges(edges, outgoing_edge_partition_name)[source]

Add a collection of edges to the graph.

Parameters:
  • edges (iterable(pacman.model.graphs.AbstractEdge)) – The edges to add
  • outgoing_edge_partition_name (str) – The name of the edge partition to add the edges to; each edge partition is the partition of edges that start at the same vertex
Raises:

PacmanInvalidParameterException – If any edge is not of a valid type or if edges have already been added to this partition that start at a different vertex to this one
add_outgoing_edge_partition(outgoing_edge_partition)[source]

Add an outgoing edge partition to the graph.

Parameters:outgoing_edge_partition (pacman.model.graphs.AbstractOutgoingEdgePartition) – The outgoing edge partition to add
Raises:PacmanAlreadyExistsException – If a partition already exists with the same pre_vertex and identifier
add_vertex(vertex)[source]

Add a vertex to the graph.

Parameters:

vertex (pacman.model.graphs.AbstractVertex) – The vertex to add
Raises:
add_vertices(vertices)[source]

Add a collection of vertices to the graph.

Parameters:

vertices (iterable(pacman.model.graphs.AbstractVertex)) – The vertices to add
Raises:
constraints

The constraints of the graph.

Return type:iterable(AbstractConstraint)
edges

The edges in the graph

Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex(vertex)[source]

Get all the edges that end at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get end
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex_with_partition_name(vertex, partition_name)[source]

Get all the edges that end at the given vertex, and reside in the correct partition ID.

Parameters:
Returns:

iterable(pacman.model.graphs.AbstractEdge)
get_edges_starting_at_vertex(vertex)[source]

Get all the edges that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get start
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_outgoing_edge_partition_starting_at_vertex(vertex, outgoing_edge_partition_name)[source]

Get the given outgoing edge partition that starts at the given vertex, or None if no such edge partition exists.

Parameters:
  • vertex (pacman.model.graphs.AbstractVertex) – The vertex at the start of the edges in the partition
  • outgoing_edge_partition_name (str) – The name of the edge partition
Return type:

pacman.model.graphs.AbstractOutgoingEdgePartition
get_outgoing_edge_partitions_starting_at_vertex(vertex)[source]

Get all the edge partitions that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edge partitions to find starts
Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
get_outgoing_partition_for_edge(edge)[source]

gets the outgoing partition this edge is associated with.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to find associated partition
Returns:the outgoing partition
Return type:pacman.model.graphs.AbstractOutgoingEdgePartition
label

The label of the graph.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_outgoing_edge_partitions

The number of outgoing edge partitions in the graph.

Return type:int
n_vertices

The number of vertices in the graph.

Return type:int
outgoing_edge_partitions

The outgoing edge partitions in the graph.

Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
vertices

The vertices in the graph.

Return type:iterable(pacman.model.graphs.AbstractVertex)
pacman.model.graphs.abstract_outgoing_edge_partition module
class pacman.model.graphs.abstract_outgoing_edge_partition.AbstractOutgoingEdgePartition[source]

Bases: object

A group of edges that start at the same vertex and share the same semantics; used to group edges that can use the same multicast key.

add_constraint(constraint)[source]

Add a constraint to the outgoing edge partition.

Parameters:constraint (AbstractConstraint) – The constraint to add
add_constraints(constraints)[source]

Add a list of constraints to the outgoing edge partition.

Parameters:constraints (iterable(AbstractConstraint)) – The list of constraints to add
add_edge(edge)[source]

Add an edge to the outgoing edge partition.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to add
Raises:pacman.exceptions.PacmanInvalidParameterException – If the starting vertex of the edge does not match that of the edges already in the partition
constraints

The constraints of the outgoing edge partition.

Return type:iterable(AbstractConstraint)
edges

The edges in this outgoing edge partition.

Return type:iterable(pacman.model.graphs.AbstractEdge)
identifier

The identifier of this outgoing edge partition.

Return type:str
label

The label of the outgoing edge partition.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_edges

The number of edges in the outgoing edge partition.

Return type:int
pre_vertex

The vertex at which all edges in this outgoing edge partition start.

Return type:pacman.model.graphs.AbstractVertex
traffic_type

The traffic type of all the edges in this outgoing edge partition.

Return type:pacman.model.graphs.common.EdgeTrafficType
traffic_weight

The weight of the traffic in this outgoing edge partition compared to other partitions.

Return type:int
pacman.model.graphs.abstract_vertex module
class pacman.model.graphs.abstract_vertex.AbstractVertex(label=None, constraints=None)[source]

Bases: pacman.model.graphs.common.constrained_object.ConstrainedObject

A vertex in a graph.

Parameters:
Raises:

pacman.exceptions.PacmanInvalidParameterException –

  • If one of the constraints is not valid
addedToGraph()[source]

Records that the vertex has been added to a graph

Raises:PacmanConfigurationException – If there is an attempt to add the same vertex more than once
label

Returns the current label to the vertex.

This label could change when the vertex is added to the graph. :return: The label :rtype: str

set_label(label)[source]

Changes the label for a vertex NOT yet ADDED to a graph

Parameters:label – new value for the label
Raises:PacmanConfigurationException – If there is an attempt to change the label once the vertex has been added to a graph
pacman.model.graphs.abstract_virtual module
class pacman.model.graphs.abstract_virtual.AbstractVirtual[source]

Bases: object

An Object (most likely a vertex) which exists outside of the machine, allowing a graph to formally participate in I/O.

Note: It is expected that everything that is an instance of AbstractVirtual is also an instance of AbstractVertex, This is not enforced to avoid diamond inheritance.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip
virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
Module contents
class pacman.model.graphs.AbstractEdge[source]

Bases: object

A directed edge in a graph between two vertices.

label

The label of the edge

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
post_vertex

The vertex at the end of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
pre_vertex

The vertex at the start of the edge

Return type:pacman.model.graphs.abstract_vertex.AbstractVertex
traffic_type

The traffic type of the edge

Return type:pacman.model.graphs.common.edge_traffic_type.EdgeTrafficType
class pacman.model.graphs.AbstractFPGA[source]

Bases: pacman.model.graphs.abstract_virtual.AbstractVirtual

An Object (most likely a vertex) connected to an FPGA.

Note: It is expected that everything that is an instance of AbstractFPGA is also an instance of AbstractVertex, This is not enforced to avoid diamond inheritance.

fpga_id

The ID of the FPGA to which the vertex is connected.

Return type:int

The link of the FPGA to which the vertex is connected.

Return type:int
class pacman.model.graphs.AbstractGraph[source]

Bases: object

A graph.

add_constraint(constraint)[source]

Add a constraint to the graph.

Parameters:constraint (AbstractConstraint) – The constraint to add
add_constraints(constraints)[source]

Add a list of constraints to the graph.

Parameters:constraints (list(AbstractConstraint)) – The list of constraints to add
add_edge(edge, outgoing_edge_partition_name)[source]

Add an edge to the graph.

Parameters:
  • edge (pacman.model.graphs.AbstractEdge) – The edge to add
  • outgoing_edge_partition_name (str) – The name of the edge partition to add the edge to; each edge partition is the partition of edges that start at the same vertex
Raises:

PacmanInvalidParameterException – If the edge is not of a valid type or if edges have already been added to this partition that start at a different vertex to this one
add_edges(edges, outgoing_edge_partition_name)[source]

Add a collection of edges to the graph.

Parameters:
  • edges (iterable(pacman.model.graphs.AbstractEdge)) – The edges to add
  • outgoing_edge_partition_name (str) – The name of the edge partition to add the edges to; each edge partition is the partition of edges that start at the same vertex
Raises:

PacmanInvalidParameterException – If any edge is not of a valid type or if edges have already been added to this partition that start at a different vertex to this one
add_outgoing_edge_partition(outgoing_edge_partition)[source]

Add an outgoing edge partition to the graph.

Parameters:outgoing_edge_partition (pacman.model.graphs.AbstractOutgoingEdgePartition) – The outgoing edge partition to add
Raises:PacmanAlreadyExistsException – If a partition already exists with the same pre_vertex and identifier
add_vertex(vertex)[source]

Add a vertex to the graph.

Parameters:

vertex (pacman.model.graphs.AbstractVertex) – The vertex to add
Raises:
add_vertices(vertices)[source]

Add a collection of vertices to the graph.

Parameters:

vertices (iterable(pacman.model.graphs.AbstractVertex)) – The vertices to add
Raises:
constraints

The constraints of the graph.

Return type:iterable(AbstractConstraint)
edges

The edges in the graph

Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex(vertex)[source]

Get all the edges that end at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get end
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_edges_ending_at_vertex_with_partition_name(vertex, partition_name)[source]

Get all the edges that end at the given vertex, and reside in the correct partition ID.

Parameters:
Returns:

iterable(pacman.model.graphs.AbstractEdge)
get_edges_starting_at_vertex(vertex)[source]

Get all the edges that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edges to get start
Return type:iterable(pacman.model.graphs.AbstractEdge)
get_outgoing_edge_partition_starting_at_vertex(vertex, outgoing_edge_partition_name)[source]

Get the given outgoing edge partition that starts at the given vertex, or None if no such edge partition exists.

Parameters:
  • vertex (pacman.model.graphs.AbstractVertex) – The vertex at the start of the edges in the partition
  • outgoing_edge_partition_name (str) – The name of the edge partition
Return type:

pacman.model.graphs.AbstractOutgoingEdgePartition
get_outgoing_edge_partitions_starting_at_vertex(vertex)[source]

Get all the edge partitions that start at the given vertex.

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex at which the edge partitions to find starts
Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
get_outgoing_partition_for_edge(edge)[source]

gets the outgoing partition this edge is associated with.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to find associated partition
Returns:the outgoing partition
Return type:pacman.model.graphs.AbstractOutgoingEdgePartition
label

The label of the graph.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_outgoing_edge_partitions

The number of outgoing edge partitions in the graph.

Return type:int
n_vertices

The number of vertices in the graph.

Return type:int
outgoing_edge_partitions

The outgoing edge partitions in the graph.

Return type:iterable(pacman.model.graphs.AbstractOutgoingEdgePartition)
vertices

The vertices in the graph.

Return type:iterable(pacman.model.graphs.AbstractVertex)
class pacman.model.graphs.AbstractOutgoingEdgePartition[source]

Bases: object

A group of edges that start at the same vertex and share the same semantics; used to group edges that can use the same multicast key.

add_constraint(constraint)[source]

Add a constraint to the outgoing edge partition.

Parameters:constraint (AbstractConstraint) – The constraint to add
add_constraints(constraints)[source]

Add a list of constraints to the outgoing edge partition.

Parameters:constraints (iterable(AbstractConstraint)) – The list of constraints to add
add_edge(edge)[source]

Add an edge to the outgoing edge partition.

Parameters:edge (pacman.model.graphs.AbstractEdge) – the edge to add
Raises:pacman.exceptions.PacmanInvalidParameterException – If the starting vertex of the edge does not match that of the edges already in the partition
constraints

The constraints of the outgoing edge partition.

Return type:iterable(AbstractConstraint)
edges

The edges in this outgoing edge partition.

Return type:iterable(pacman.model.graphs.AbstractEdge)
identifier

The identifier of this outgoing edge partition.

Return type:str
label

The label of the outgoing edge partition.

Returns:The label
Return type:str
Raises:None – Raises no known exceptions
n_edges

The number of edges in the outgoing edge partition.

Return type:int
pre_vertex

The vertex at which all edges in this outgoing edge partition start.

Return type:pacman.model.graphs.AbstractVertex
traffic_type

The traffic type of all the edges in this outgoing edge partition.

Return type:pacman.model.graphs.common.EdgeTrafficType
traffic_weight

The weight of the traffic in this outgoing edge partition compared to other partitions.

Return type:int

Bases: pacman.model.graphs.abstract_virtual.AbstractVirtual

An Object (most likely a vertex) connected to a SpiNNaker Link.

Note: It is expected that everything that is an instance of AbstractSpiNNakerLink is also an instance of AbstractVertex, This is not enforced to avoid diamond inheritance.

The SpiNNaker Link that the vertex is connected to.

class pacman.model.graphs.AbstractVertex(label=None, constraints=None)[source]

Bases: pacman.model.graphs.common.constrained_object.ConstrainedObject

A vertex in a graph.

Parameters:
Raises:

pacman.exceptions.PacmanInvalidParameterException –

  • If one of the constraints is not valid
addedToGraph()[source]

Records that the vertex has been added to a graph

Raises:PacmanConfigurationException – If there is an attempt to add the same vertex more than once
label

Returns the current label to the vertex.

This label could change when the vertex is added to the graph. :return: The label :rtype: str

set_label(label)[source]

Changes the label for a vertex NOT yet ADDED to a graph

Parameters:label – new value for the label
Raises:PacmanConfigurationException – If there is an attempt to change the label once the vertex has been added to a graph
class pacman.model.graphs.AbstractVirtual[source]

Bases: object

An Object (most likely a vertex) which exists outside of the machine, allowing a graph to formally participate in I/O.

Note: It is expected that everything that is an instance of AbstractVirtual is also an instance of AbstractVertex, This is not enforced to avoid diamond inheritance.

board_address

The IP address of the board to which the device is connected, or None for the boot board.

Return type:str
set_virtual_chip_coordinates(virtual_chip_x, virtual_chip_y)[source]

Set the details of the virtual chip that has been added to the machine for this vertex.

Parameters:
  • virtual_chip_x – The x-coordinate of the added chip
  • virtual_chip_y – The y-coordinate of the added chip
virtual_chip_x

The x-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
virtual_chip_y

The y-coordinate of the virtual chip where this vertex is to be placed.

Return type:int
pacman.model.placements package
Submodules
pacman.model.placements.placement module
class pacman.model.placements.placement.Placement(vertex, x, y, p)[source]

Bases: object

The placement of a vertex on to a machine chip and core.

Parameters:
  • vertex (pacman.model.graphs.machine.MachineVertex) – The vertex that has been placed
  • x (int) – the x-coordinate of the chip on which the vertex is placed
  • y (int) – the y-coordinate of the chip on which the vertex is placed
  • p (int or None) – the ID of the processor on which the vertex is placed
p

The ID of the processor of the chip where the vertex is placed

Returns:The processor ID
Return type:int
vertex

The vertex that was placed

Returns:a vertex
Return type:pacman.model.graph.machine.MachineVertex
Raises:None – does not raise any known exceptions
x

The x-coordinate of the chip where the vertex is placed

Returns:The x-coordinate
Return type:int
y

The y-coordinate of the chip where the vertex is placed

Returns:The y-coordinate
Return type:int
pacman.model.placements.placements module
class pacman.model.placements.placements.Placements(placements=None)[source]

Bases: object

The placements of vertices on the chips of the machine.

Parameters:

placements (iterable(pacman.model.placements.Placement)) – Any initial placements
Raises:
add_placement(placement)[source]

Add a placement

Parameters:

placement (pacman.model.placements.placement.Placement) – The placement to add
Raises:
add_placements(placements)[source]

Add some placements

Parameters:placements (iterable(pacman.model.placements.Placement)) – The placements to add
get_placed_processors()[source]

Return an iterable of processors with assigned vertices.

Returns:Iterable of (x, y, p) tuples
Return type:iterable(tuple(int, int, int))
get_placement_of_vertex(vertex)[source]

Return the placement information for a vertex

Parameters:vertex (pacman.model.graphs.machine.MachineVertex) – The vertex to find the placement of
Returns:The placement
Return type:pacman.model.placements.Placement
Raises:PacmanNotPlacedError – If the vertex has not been placed.
get_vertex_on_processor(x, y, p)[source]

Return the vertex on a specific processor or None if the processor has not been allocated

Parameters:
  • x (int) – the x coordinate of the chip
  • y (int) – the y coordinate of the chip
  • p (int) – the processor on the chip
Returns:

the vertex placed on the given processor
Return type:

pacman.model.graphs.machine.MachineVertex
Raises:

PacmanProcessorNotOccupiedError – If the processor is not occupied
is_processor_occupied(x, y, p)[source]

Determine if a processor has a vertex on it

Parameters:
  • x (int) – x coordinate of processor.
  • y (int) – y coordinate of processor.
  • p (int) – Index of processor.
Return bool:

Whether the processor has an assigned vertex.
n_placements

The number of placements

Return type:int
placements

All of the placements

Returns:iterable of placements
Return type:iterable(pacman.model.placements.Placement)
Raises:None – does not raise any known exceptions
Module contents
class pacman.model.placements.Placement(vertex, x, y, p)[source]

Bases: object

The placement of a vertex on to a machine chip and core.

Parameters:
  • vertex (pacman.model.graphs.machine.MachineVertex) – The vertex that has been placed
  • x (int) – the x-coordinate of the chip on which the vertex is placed
  • y (int) – the y-coordinate of the chip on which the vertex is placed
  • p (int or None) – the ID of the processor on which the vertex is placed
p

The ID of the processor of the chip where the vertex is placed

Returns:The processor ID
Return type:int
vertex

The vertex that was placed

Returns:a vertex
Return type:pacman.model.graph.machine.MachineVertex
Raises:None – does not raise any known exceptions
x

The x-coordinate of the chip where the vertex is placed

Returns:The x-coordinate
Return type:int
y

The y-coordinate of the chip where the vertex is placed

Returns:The y-coordinate
Return type:int
class pacman.model.placements.Placements(placements=None)[source]

Bases: object

The placements of vertices on the chips of the machine.

Parameters:

placements (iterable(pacman.model.placements.Placement)) – Any initial placements
Raises:
add_placement(placement)[source]

Add a placement

Parameters:

placement (pacman.model.placements.placement.Placement) – The placement to add
Raises:
add_placements(placements)[source]

Add some placements

Parameters:placements (iterable(pacman.model.placements.Placement)) – The placements to add
get_placed_processors()[source]

Return an iterable of processors with assigned vertices.

Returns:Iterable of (x, y, p) tuples
Return type:iterable(tuple(int, int, int))
get_placement_of_vertex(vertex)[source]

Return the placement information for a vertex

Parameters:vertex (pacman.model.graphs.machine.MachineVertex) – The vertex to find the placement of
Returns:The placement
Return type:pacman.model.placements.Placement
Raises:PacmanNotPlacedError – If the vertex has not been placed.
get_vertex_on_processor(x, y, p)[source]

Return the vertex on a specific processor or None if the processor has not been allocated

Parameters:
  • x (int) – the x coordinate of the chip
  • y (int) – the y coordinate of the chip
  • p (int) – the processor on the chip
Returns:

the vertex placed on the given processor
Return type:

pacman.model.graphs.machine.MachineVertex
Raises:

PacmanProcessorNotOccupiedError – If the processor is not occupied
is_processor_occupied(x, y, p)[source]

Determine if a processor has a vertex on it

Parameters:
  • x (int) – x coordinate of processor.
  • y (int) – y coordinate of processor.
  • p (int) – Index of processor.
Return bool:

Whether the processor has an assigned vertex.
n_placements

The number of placements

Return type:int
placements

All of the placements

Returns:iterable of placements
Return type:iterable(pacman.model.placements.Placement)
Raises:None – does not raise any known exceptions
pacman.model.resources package
Submodules
pacman.model.resources.abstract_sdram module
class pacman.model.resources.abstract_sdram.AbstractSDRAM[source]

Bases: object

Represents an amount of SDRAM used on a chip in the machine.

fixed

Returns the fixed SDRAM cost

get_total_sdram(n_timesteps)[source]

The total SDRAM.

Parameters:n_timesteps (int) – number of timesteps to cost for
Returns:
per_timestep

Returns extra SDRAM cost for each additional timestep

Warning may well be zero

sub_from(other)[source]

Creates a new SDRAM which is the other less this one

Parameters:other (AbstractSDRAM) – another SDRAM resource
Returns:a New AbstractSDRAM
Return type:AbstractSDRAM
pacman.model.resources.constant_sdram module
class pacman.model.resources.constant_sdram.ConstantSDRAM(sdram)[source]

Bases: pacman.model.resources.abstract_sdram.AbstractSDRAM

Represents an amount of SDRAM used on a chip in the machine.

This is used when the amount of SDRAM needed is not effected by runtime

Parameters:sdram (int) – The amount of SDRAM in bytes
Raises:None – No known exceptions are raised
fixed

Returns the fixed SDRAM cost

get_total_sdram(n_timesteps)[source]

The total SDRAM.

Parameters:n_timesteps (int) – number of timesteps to cost for
Returns:
per_timestep

Returns extra SDRAM cost for each additional timestep

Warning may well be zero

sub_from(other)[source]

Creates a new SDRAM which is the other less this one

Parameters:other (AbstractSDRAM) – another SDRAM resource
Returns:a New AbstractSDRAM
Return type:AbstractSDRAM
pacman.model.resources.core_resource module
class pacman.model.resources.core_resource.CoreResource(chip, n_cores)[source]

Bases: object

Represents the number of cores that need to be allocated.

Parameters:
  • n_cores (int) – The number of cores to allocate
  • chip (spinn_machine.Chip) – chip of where these cores are to be allocated
Raises:

None – No known exceptions are raised
chip
get_value()[source]
Returns:The chip and the cores required on it.
n_cores
pacman.model.resources.cpu_cycles_per_tick_resource module
class pacman.model.resources.cpu_cycles_per_tick_resource.CPUCyclesPerTickResource(cycles)[source]

Bases: object

Represents the number of CPU clock cycles per tick used or available on a core of a chip in the machine.

Parameters:cycles (int) – The number of CPU clock cycles
Raises:None – No known exceptions are raised
get_value()[source]
Returns:The number of CPU clock cycles needed per simulation tick.
pacman.model.resources.dtcm_resource module
class pacman.model.resources.dtcm_resource.DTCMResource(dtcm)[source]

Bases: object

Represents the amount of local core memory available or used on a core on a chip of the machine.

Parameters:dtcm (int) – The amount of DTCM in bytes
Raises:None – No known exceptions are raised
get_value()[source]
Returns:The required amount of DTCM, in bytes.
pacman.model.resources.element_free_space module
class pacman.model.resources.element_free_space.ElementFreeSpace(start_address, size)[source]

Bases: object

size
start_address
pacman.model.resources.iptag_resource module
class pacman.model.resources.iptag_resource.IPtagResource(ip_address, port, strip_sdp, tag=None, traffic_identifier='DEFAULT')[source]

Bases: object

Represents the ability to have a SpiNNaker machine send messages to you during execution.

Parameters:
  • ip_address (str) – The IP address of the host that will receive data from this tag
  • port (int or None) – The port that will
  • strip_sdp (bool) – Whether the tag requires that SDP headers are stripped before transmission of data
  • tag (int or None) – A fixed tag ID to assign, or None if any tag is OK
  • traffic_identifier (str) – The traffic to be sent using this tag; traffic with the same traffic_identifier can be sent using the same tag
get_value()[source]
Returns:The description of the IP tag.
ip_address

The IP address to assign to the tag

Returns:An IP address
Return type:str
port

The port of the tag

Returns:The port of the tag
Return type:int
strip_sdp

Whether SDP headers should be stripped for this tag

Returns:True if the headers should be stripped, False otherwise
Return type:bool
tag

The tag required, or None if any tag is OK

Returns:The tag or None
Return type:int
traffic_identifier

The traffic identifier for this IP tag

pacman.model.resources.pre_allocated_resource_container module
class pacman.model.resources.pre_allocated_resource_container.PreAllocatedResourceContainer(specific_sdram_usage=None, specific_core_resources=None, core_resources=None, specific_iptag_resources=None, specific_reverse_iptag_resources=None)[source]

Bases: object

Container object for preallocated resources

Parameters:
core_resources
extend(other)[source]
specific_core_resources
specific_iptag_resources
specific_reverse_iptag_resources
specific_sdram_usage
pacman.model.resources.resource_container module
class pacman.model.resources.resource_container.ResourceContainer(dtcm=None, sdram=None, cpu_cycles=None, iptags=None, reverse_iptags=None)[source]

Bases: object

Container for the types of resources so that ordering is no longer a problem.

Parameters:
  • dtcm (None or pacman.models.resources.dtcm_resource.DTCMResource) – the amount of dtcm used
  • sdram (None or pacman.models.resources.sdram_resource.SDRAMResource) – the amount of SDRAM used
  • cpu_cycles (None or pacman.models.resources.cpu_cycles_per_tick_resource.CPUCyclesPerTickResource) – the amount of CPU used
  • iptags (None or list(pacman.models.resources.iptag_resource.IPtagResource)) – the IP tags required
  • reverse_iptags (None or list(pacman.models.resources.reverse_iptag_resource.ReverseIPtagResource)) – the reverse IP tags required
Return type:

pacman.models.resources.resource_container.ResourceContainer
Raises:

None – does not raise any known exception
cpu_cycles
dtcm
extend(other)[source]
iptags
reverse_iptags
sdram
pacman.model.resources.reverse_iptag_resource module
class pacman.model.resources.reverse_iptag_resource.ReverseIPtagResource(port=None, sdp_port=1, tag=None)[source]

Bases: object

Represents the ability to talk to a SpiNNaker machine by sending UDP packets to it during execution.

Parameters:
  • port (int) – The target port of the tag or None to assign elsewhere
  • port – The UDP port to listen to on the board for this tag
  • sdp_port (int) – The SDP port number to be used when constructing SDP packets from the received UDP packets for this tag
  • tag (int or None) – A fixed tag ID to assign, or None if any tag is OK
get_value()[source]
Returns:The description of the reverse IP tag.
port

The port of the tag

Returns:The port of the tag
Return type:int
sdp_port

The SDP port to use when constructing the SDP message from the received UDP message

tag

The tag required, or None if any tag is OK

Returns:The tag or None
Return type:int
pacman.model.resources.specific_board_iptag_resource module
class pacman.model.resources.specific_board_iptag_resource.SpecificBoardTagResource(board, ip_address, port, strip_sdp, tag=None, traffic_identifier='DEFAULT')[source]

Bases: object

A resource that allocates a tag on a specific board before the class needing it has been built.

Parameters:
  • board (str) – The IP address of the board to which this tag is to be associated with
  • ip_address (str) – The IP address of the host that will receive data from this tag
  • port (int or None) – The port that will
  • strip_sdp (bool) – Whether the tag requires that SDP headers are stripped before transmission of data
  • tag (int) – A fixed tag ID to assign, or None if any tag is OK
  • traffic_identifier (str) – The traffic to be sent using this tag; traffic with the same traffic_identifier can be sent using the same tag
board

The board IP address that this tag is to reside on

Returns:IP address
get_value()[source]
Returns:A description of the specific board’s IP tag required.
ip_address

The IP address to assign to the tag.

Returns:An IP address
Return type:str
port

The port of the tag

Returns:The port of the tag
Return type:int
strip_sdp

Whether SDP headers should be stripped for this tag

Returns:True if the headers should be stripped, False otherwise
Return type:bool
tag

The tag required, or None if any tag is OK.

Returns:The tag or None
Return type:int
traffic_identifier

The traffic identifier for this IP tag

pacman.model.resources.specific_board_reverse_iptag_resource module
class pacman.model.resources.specific_board_reverse_iptag_resource.ReverseIPtagResource(board, port=None, sdp_port=1, tag=None)[source]

Bases: object

Represents the ability to talk to a specific board of a SpiNNaker machine by sending UDP packets to it during execution.

Parameters:
  • board (str) – A board IP address which is where this reverse IP tag is to be placed
  • port (int) – The target port of the tag or None to assign elsewhere
  • port – The UDP port to listen to on the board for this tag
  • sdp_port (int) – The SDP port number to be used when constructing SDP packets from the received UDP packets for this tag.
  • tag (int or None) – A fixed tag ID to assign, or None if any tag is OK
board

A board IP address which is where this reverse IP tag is to be placed.

Returns:str
get_value()[source]
Returns:A description of the specific board’s reverse IP tag required.
port

The port of the tag

Returns:The port of the tag
Return type:int
sdp_port

The SDP port to use when constructing the SDP message from the received UDP message.

tag

The tag required, or None if any tag is OK

Returns:The tag or None
Return type:int
pacman.model.resources.specific_chip_sdram_resource module
class pacman.model.resources.specific_chip_sdram_resource.SpecificChipSDRAMResource(chip, sdram_usage)[source]

Bases: object

Represents the SDRAM required for this Chip

Parameters:
  • sdram_usage (AbstractSDRAM The amount of SDRAM in bytes needed to be preallocated) – The amount of SDRAM in bytes needed to be pre-allocated
  • chip (spinn_machine.Chip) – chip of where the SDRAM is to be allocated
Raises:

None – No known exceptions are raised
chip
get_value()[source]
Returns:The chip for which it is required, and the amount of SDRAM required thereon, in bytes.
sdram_usage
pacman.model.resources.specific_core_resource module
class pacman.model.resources.specific_core_resource.SpecificCoreResource(chip, cores)[source]

Bases: object

Represents specific cores that need to be allocated.

Parameters:
  • cores (iterable(int)) – The specific cores that need to be allocated (list of processor IDs)
  • chip (spinn_machine.Chip) – chip of where these cores are to be allocated
Raises:

None – No known exceptions are raised
chip
cores
get_value()[source]
Returns:The chip and the cores required on it.
pacman.model.resources.variable_sdram module
class pacman.model.resources.variable_sdram.VariableSDRAM(fixed_sdram, per_timestep_sdram)[source]

Bases: pacman.model.resources.abstract_sdram.AbstractSDRAM

Represents an amount of SDRAM used on a chip in the machine.

This is where the usage increase as the run time increases

Parameters:sdram (int) – The amount of SDRAM in bytes
Raises:None – No known exceptions are raised
fixed

Returns the fixed SDRAM cost

get_total_sdram(n_timesteps)[source]

The total SDRAM.

Parameters:n_timesteps (int) – number of timesteps to cost for
Returns:
per_timestep

Returns extra SDRAM cost for each additional timestep

Warning may well be zero

sub_from(other)[source]

Creates a new SDRAM which is the other less this one

Parameters:other (AbstractSDRAM) – another SDRAM resource
Returns:a New AbstractSDRAM
Return type:AbstractSDRAM
Module contents
class pacman.model.resources.AbstractSDRAM[source]

Bases: object

Represents an amount of SDRAM used on a chip in the machine.

fixed

Returns the fixed SDRAM cost

get_total_sdram(n_timesteps)[source]

The total SDRAM.

Parameters:n_timesteps (int) – number of timesteps to cost for
Returns:
per_timestep

Returns extra SDRAM cost for each additional timestep

Warning may well be zero

sub_from(other)[source]

Creates a new SDRAM which is the other less this one

Parameters:other (AbstractSDRAM) – another SDRAM resource
Returns:a New AbstractSDRAM
Return type:AbstractSDRAM
class pacman.model.resources.ConstantSDRAM(sdram)[source]

Bases: pacman.model.resources.abstract_sdram.AbstractSDRAM

Represents an amount of SDRAM used on a chip in the machine.

This is used when the amount of SDRAM needed is not effected by runtime

Parameters:sdram (int) – The amount of SDRAM in bytes
Raises:None – No known exceptions are raised
fixed

Returns the fixed SDRAM cost

get_total_sdram(n_timesteps)[source]

The total SDRAM.

Parameters:n_timesteps (int) – number of timesteps to cost for
Returns:
per_timestep

Returns extra SDRAM cost for each additional timestep

Warning may well be zero

sub_from(other)[source]

Creates a new SDRAM which is the other less this one

Parameters:other (AbstractSDRAM) – another SDRAM resource
Returns:a New AbstractSDRAM
Return type:AbstractSDRAM
class pacman.model.resources.CoreResource(chip, n_cores)[source]

Bases: object

Represents the number of cores that need to be allocated.

Parameters:
  • n_cores (int) – The number of cores to allocate
  • chip (spinn_machine.Chip) – chip of where these cores are to be allocated
Raises:

None – No known exceptions are raised
chip
get_value()[source]
Returns:The chip and the cores required on it.
n_cores
class pacman.model.resources.CPUCyclesPerTickResource(cycles)[source]

Bases: object

Represents the number of CPU clock cycles per tick used or available on a core of a chip in the machine.

Parameters:cycles (int) – The number of CPU clock cycles
Raises:None – No known exceptions are raised
get_value()[source]
Returns:The number of CPU clock cycles needed per simulation tick.
class pacman.model.resources.DTCMResource(dtcm)[source]

Bases: object

Represents the amount of local core memory available or used on a core on a chip of the machine.

Parameters:dtcm (int) – The amount of DTCM in bytes
Raises:None – No known exceptions are raised
get_value()[source]
Returns:The required amount of DTCM, in bytes.
class pacman.model.resources.ElementFreeSpace(start_address, size)[source]

Bases: object

size
start_address
class pacman.model.resources.IPtagResource(ip_address, port, strip_sdp, tag=None, traffic_identifier='DEFAULT')[source]

Bases: object

Represents the ability to have a SpiNNaker machine send messages to you during execution.

Parameters:
  • ip_address (str) – The IP address of the host that will receive data from this tag
  • port (int or None) – The port that will
  • strip_sdp (bool) – Whether the tag requires that SDP headers are stripped before transmission of data
  • tag (int or None) – A fixed tag ID to assign, or None if any tag is OK
  • traffic_identifier (str) – The traffic to be sent using this tag; traffic with the same traffic_identifier can be sent using the same tag
get_value()[source]
Returns:The description of the IP tag.
ip_address

The IP address to assign to the tag

Returns:An IP address
Return type:str
port

The port of the tag

Returns:The port of the tag
Return type:int
strip_sdp

Whether SDP headers should be stripped for this tag

Returns:True if the headers should be stripped, False otherwise
Return type:bool
tag

The tag required, or None if any tag is OK

Returns:The tag or None
Return type:int
traffic_identifier

The traffic identifier for this IP tag

class pacman.model.resources.ResourceContainer(dtcm=None, sdram=None, cpu_cycles=None, iptags=None, reverse_iptags=None)[source]

Bases: object

Container for the types of resources so that ordering is no longer a problem.

Parameters:
  • dtcm (None or pacman.models.resources.dtcm_resource.DTCMResource) – the amount of dtcm used
  • sdram (None or pacman.models.resources.sdram_resource.SDRAMResource) – the amount of SDRAM used
  • cpu_cycles (None or pacman.models.resources.cpu_cycles_per_tick_resource.CPUCyclesPerTickResource) – the amount of CPU used
  • iptags (None or list(pacman.models.resources.iptag_resource.IPtagResource)) – the IP tags required
  • reverse_iptags (None or list(pacman.models.resources.reverse_iptag_resource.ReverseIPtagResource)) – the reverse IP tags required
Return type:

pacman.models.resources.resource_container.ResourceContainer
Raises:

None – does not raise any known exception
cpu_cycles
dtcm
extend(other)[source]
iptags
reverse_iptags
sdram
class pacman.model.resources.ReverseIPtagResource(port=None, sdp_port=1, tag=None)[source]

Bases: object

Represents the ability to talk to a SpiNNaker machine by sending UDP packets to it during execution.

Parameters:
  • port (int) – The target port of the tag or None to assign elsewhere
  • port – The UDP port to listen to on the board for this tag
  • sdp_port (int) – The SDP port number to be used when constructing SDP packets from the received UDP packets for this tag
  • tag (int or None) – A fixed tag ID to assign, or None if any tag is OK
get_value()[source]
Returns:The description of the reverse IP tag.
port

The port of the tag

Returns:The port of the tag
Return type:int
sdp_port

The SDP port to use when constructing the SDP message from the received UDP message

tag

The tag required, or None if any tag is OK

Returns:The tag or None
Return type:int
class pacman.model.resources.PreAllocatedResourceContainer(specific_sdram_usage=None, specific_core_resources=None, core_resources=None, specific_iptag_resources=None, specific_reverse_iptag_resources=None)[source]

Bases: object

Container object for preallocated resources

Parameters:
core_resources
extend(other)[source]
specific_core_resources
specific_iptag_resources
specific_reverse_iptag_resources
specific_sdram_usage
class pacman.model.resources.SpecificChipSDRAMResource(chip, sdram_usage)[source]

Bases: object

Represents the SDRAM required for this Chip

Parameters:
  • sdram_usage (AbstractSDRAM The amount of SDRAM in bytes needed to be preallocated) – The amount of SDRAM in bytes needed to be pre-allocated
  • chip (spinn_machine.Chip) – chip of where the SDRAM is to be allocated
Raises:

None – No known exceptions are raised
chip
get_value()[source]
Returns:The chip for which it is required, and the amount of SDRAM required thereon, in bytes.
sdram_usage
class pacman.model.resources.SpecificCoreResource(chip, cores)[source]

Bases: object

Represents specific cores that need to be allocated.

Parameters:
  • cores (iterable(int)) – The specific cores that need to be allocated (list of processor IDs)
  • chip (spinn_machine.Chip) – chip of where these cores are to be allocated
Raises:

None – No known exceptions are raised
chip
cores
get_value()[source]
Returns:The chip and the cores required on it.
pacman.model.resources.SpecificBoardIPtagResource

alias of pacman.model.resources.specific_board_iptag_resource.SpecificBoardTagResource

pacman.model.resources.SpecificBoardReverseIPtagResource

alias of pacman.model.resources.specific_board_reverse_iptag_resource.ReverseIPtagResource

class pacman.model.resources.VariableSDRAM(fixed_sdram, per_timestep_sdram)[source]

Bases: pacman.model.resources.abstract_sdram.AbstractSDRAM

Represents an amount of SDRAM used on a chip in the machine.

This is where the usage increase as the run time increases

Parameters:sdram (int) – The amount of SDRAM in bytes
Raises:None – No known exceptions are raised
fixed

Returns the fixed SDRAM cost

get_total_sdram(n_timesteps)[source]

The total SDRAM.

Parameters:n_timesteps (int) – number of timesteps to cost for
Returns:
per_timestep

Returns extra SDRAM cost for each additional timestep

Warning may well be zero

sub_from(other)[source]

Creates a new SDRAM which is the other less this one

Parameters:other (AbstractSDRAM) – another SDRAM resource
Returns:a New AbstractSDRAM
Return type:AbstractSDRAM
pacman.model.routing_info package
Submodules
pacman.model.routing_info.abstract_machine_partition_n_keys_map module
class pacman.model.routing_info.abstract_machine_partition_n_keys_map.AbstractMachinePartitionNKeysMap[source]

Bases: object

A map that provides the number of keys required by each partition

n_keys_for_partition(partition)[source]

The number of keys required by the given partition

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to set the number of keys for
Returns:The number of keys required by the partition
Return type:int
pacman.model.routing_info.base_key_and_mask module
class pacman.model.routing_info.base_key_and_mask.BaseKeyAndMask(base_key, mask)[source]

Bases: object

A Key and Mask to be used for routing.

Parameters:
  • base_key (int) – The routing key
  • mask (int) – The routing mask
Raises:

PacmanConfigurationException – If key & mask != key i.e. the key is not valid for the given mask
get_keys(key_array=None, offset=0, n_keys=None)[source]

Get the ordered list of keys that the combination allows

Parameters:
  • key_array (array-like of int) – Optional array into which the returned keys will be placed
  • offset (int) – Optional offset into the array at which to start placing keys
  • n_keys (int) – Optional limit on the number of keys returned. If less than this number of keys are available, only the keys available will be added
Returns:

A tuple of an array of keys and the number of keys added to the array
Return type:

tuple(array-like of int, int)
key

The base key

Returns:The base key
Return type:int
key_combo

The key combined with the mask

mask

The mask

Returns:The mask
Return type:int
n_keys

The total number of keys that can be generated given the mask

Returns:The number of keys
Return type:int
pacman.model.routing_info.dict_based_machine_partition_n_keys_map module
class pacman.model.routing_info.dict_based_machine_partition_n_keys_map.DictBasedMachinePartitionNKeysMap[source]

Bases: pacman.model.routing_info.abstract_machine_partition_n_keys_map.AbstractMachinePartitionNKeysMap

A python dict-based implementation of the pacman.model.routing_info.AbstractMachinePartitionNKeysMap

n_keys_for_partition(partition)[source]

The number of keys required by the given partition

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to set the number of keys for
Returns:The number of keys required by the partition
Return type:int
set_n_keys_for_partition(partition, n_keys)[source]

Set the number of keys required by a machine outgoing edge partition

Parameters:
pacman.model.routing_info.partition_routing_info module
class pacman.model.routing_info.partition_routing_info.PartitionRoutingInfo(keys_and_masks, partition)[source]

Bases: object

Associates a partition to its routing information (keys and masks).

Parameters:
first_key

The first key (or only one if there is only one)

first_key_and_mask

The first key and mask (or only one if there is only one)

first_mask

The first mask (or only one if there is only one)

get_keys(n_keys=None)[source]

Get the ordered list of individual keys allocated to the edge

Parameters:n_keys (int) – Optional limit on the number of keys to return
Returns:An array of keys
Return type:array-like of int
keys_and_masks
partition
pacman.model.routing_info.routing_info module
class pacman.model.routing_info.routing_info.RoutingInfo(partition_info_items=None)[source]

Bases: object

An association of a set of edges to a non-overlapping set of keys and masks.

Parameters:partition_info_items (iterable(pacman.model.routing_info.PartitionRoutingInfo) or None) – The partition information items to add
Raises:pacman.exceptions.PacmanAlreadyExistsException – If there are two partition information objects with the same partition
add_partition_info(partition_info)[source]

Add a partition information item

Parameters:partition_info (pacman.model.routing_info.PartitionRoutingInfo) – The partition information item to add
Return type:None
Raises:pacman.exceptions.PacmanAlreadyExistsException – If the partition is already in the set of edges
get_first_key_for_edge(edge)[source]

Get routing key for an edge

Parameters:edge – The edge to search for
get_first_key_from_partition(partition)[source]

Get the first key associated with a particular partition

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to get the first key of
Returns:The routing key or None if the partition does not exist
Return type:int
Raises:None – does not raise any known exceptions
get_first_key_from_pre_vertex(vertex, partition_id)[source]

Get the first key for the partition starting at a (pre)vertex

Parameters:
  • vertex – The vertex which the partition starts at
  • partition_id – The ID of the partition for which to get the routing information
Returns:

The routing key of the partition
Return type:

int
get_routing_info_for_edge(edge)[source]

Get routing information for an edge

Parameters:edge – The edge to search for
get_routing_info_from_partition(partition)[source]

Get the routing information for a given partition.

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to obtain routing informaton about.
Returns:the partition_routing_info for the partition, if any exists
Return type:pacman.model.routing_info.PartitionRoutingInfo or None
get_routing_info_from_pre_vertex(vertex, partition_id)[source]

Get routing information for edges with a given partition_id from a prevertex

Parameters:
  • vertex – The prevertex to search for
  • partition_id – The ID of the partition for which to get the routing information
Module contents
class pacman.model.routing_info.AbstractMachinePartitionNKeysMap[source]

Bases: object

A map that provides the number of keys required by each partition

n_keys_for_partition(partition)[source]

The number of keys required by the given partition

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to set the number of keys for
Returns:The number of keys required by the partition
Return type:int
class pacman.model.routing_info.BaseKeyAndMask(base_key, mask)[source]

Bases: object

A Key and Mask to be used for routing.

Parameters:
  • base_key (int) – The routing key
  • mask (int) – The routing mask
Raises:

PacmanConfigurationException – If key & mask != key i.e. the key is not valid for the given mask
get_keys(key_array=None, offset=0, n_keys=None)[source]

Get the ordered list of keys that the combination allows

Parameters:
  • key_array (array-like of int) – Optional array into which the returned keys will be placed
  • offset (int) – Optional offset into the array at which to start placing keys
  • n_keys (int) – Optional limit on the number of keys returned. If less than this number of keys are available, only the keys available will be added
Returns:

A tuple of an array of keys and the number of keys added to the array
Return type:

tuple(array-like of int, int)
key

The base key

Returns:The base key
Return type:int
key_combo

The key combined with the mask

mask

The mask

Returns:The mask
Return type:int
n_keys

The total number of keys that can be generated given the mask

Returns:The number of keys
Return type:int
class pacman.model.routing_info.DictBasedMachinePartitionNKeysMap[source]

Bases: pacman.model.routing_info.abstract_machine_partition_n_keys_map.AbstractMachinePartitionNKeysMap

A python dict-based implementation of the pacman.model.routing_info.AbstractMachinePartitionNKeysMap

n_keys_for_partition(partition)[source]

The number of keys required by the given partition

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to set the number of keys for
Returns:The number of keys required by the partition
Return type:int
set_n_keys_for_partition(partition, n_keys)[source]

Set the number of keys required by a machine outgoing edge partition

Parameters:
class pacman.model.routing_info.PartitionRoutingInfo(keys_and_masks, partition)[source]

Bases: object

Associates a partition to its routing information (keys and masks).

Parameters:
first_key

The first key (or only one if there is only one)

first_key_and_mask

The first key and mask (or only one if there is only one)

first_mask

The first mask (or only one if there is only one)

get_keys(n_keys=None)[source]

Get the ordered list of individual keys allocated to the edge

Parameters:n_keys (int) – Optional limit on the number of keys to return
Returns:An array of keys
Return type:array-like of int
keys_and_masks
partition
class pacman.model.routing_info.RoutingInfo(partition_info_items=None)[source]

Bases: object

An association of a set of edges to a non-overlapping set of keys and masks.

Parameters:partition_info_items (iterable(pacman.model.routing_info.PartitionRoutingInfo) or None) – The partition information items to add
Raises:pacman.exceptions.PacmanAlreadyExistsException – If there are two partition information objects with the same partition
add_partition_info(partition_info)[source]

Add a partition information item

Parameters:partition_info (pacman.model.routing_info.PartitionRoutingInfo) – The partition information item to add
Return type:None
Raises:pacman.exceptions.PacmanAlreadyExistsException – If the partition is already in the set of edges
get_first_key_for_edge(edge)[source]

Get routing key for an edge

Parameters:edge – The edge to search for
get_first_key_from_partition(partition)[source]

Get the first key associated with a particular partition

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to get the first key of
Returns:The routing key or None if the partition does not exist
Return type:int
Raises:None – does not raise any known exceptions
get_first_key_from_pre_vertex(vertex, partition_id)[source]

Get the first key for the partition starting at a (pre)vertex

Parameters:
  • vertex – The vertex which the partition starts at
  • partition_id – The ID of the partition for which to get the routing information
Returns:

The routing key of the partition
Return type:

int
get_routing_info_for_edge(edge)[source]

Get routing information for an edge

Parameters:edge – The edge to search for
get_routing_info_from_partition(partition)[source]

Get the routing information for a given partition.

Parameters:partition (pacman.model.graphs.impl.OutgoingEdgePartition) – The partition to obtain routing informaton about.
Returns:the partition_routing_info for the partition, if any exists
Return type:pacman.model.routing_info.PartitionRoutingInfo or None
get_routing_info_from_pre_vertex(vertex, partition_id)[source]

Get routing information for edges with a given partition_id from a prevertex

Parameters:
  • vertex – The prevertex to search for
  • partition_id – The ID of the partition for which to get the routing information
pacman.model.routing_table_by_partition package
Submodules
pacman.model.routing_table_by_partition.multicast_routing_table_by_partition module
class pacman.model.routing_table_by_partition.multicast_routing_table_by_partition.MulticastRoutingTableByPartition[source]

Bases: object

A set of multicast routing path objects

add_path_entry(entry, router_x, router_y, partition)[source]

Adds a multicast routing path entry

Parameters:
get_entries_for_router(router_x, router_y)[source]

Get the set of multicast path entries assigned to this router

Parameters:
  • router_x – the x coord of the router
  • router_y – the y coord of the router
Returns:

return all router_path_entries for the router.
get_entry_on_coords_for_edge(partition, router_x, router_y)[source]

Get an entry from a specific coordinate

get_routers()[source]

Get the coordinates of all stored routers

pacman.model.routing_table_by_partition.multicast_routing_table_by_partition_entry module
class pacman.model.routing_table_by_partition.multicast_routing_table_by_partition_entry.MulticastRoutingTableByPartitionEntry(out_going_links, outgoing_processors, incoming_processor=None, incoming_link=None)[source]

Bases: object

An entry in a path of a multicast route.

Parameters:
  • out_going_links (iterable(int)) – the edges this path entry goes down, each of which is between 0 and 5
  • outgoing_processors (iterable(int)) – the processors this path entry goes to, each of which is between 0 and 17
  • incoming_processor (int) – the direction this entry came from (between 0 and 17)
  • incoming_link (int) – the direction this entry came from in link (between 0 and 5)
defaultable

The defaultable status of the entry

The source link for this path entry

Return type:int or None
incoming_processor

The source processor

Return type:int or Non

The destination links of the entry

Return type:set(int)
merge_entry(other)[source]

Merges the another entry with this one and returns a new MulticastRoutingTableByPartitionEntry

Parameters:other – the MulticastRoutingTableByPartitionEntry to merge into this one
Returns:a merged MulticastRoutingTableByPartitionEntry
processor_ids

The destination processors of the entry

Return type:set(int)
Module contents
class pacman.model.routing_table_by_partition.MulticastRoutingTableByPartition[source]

Bases: object

A set of multicast routing path objects

add_path_entry(entry, router_x, router_y, partition)[source]

Adds a multicast routing path entry

Parameters:
get_entries_for_router(router_x, router_y)[source]

Get the set of multicast path entries assigned to this router

Parameters:
  • router_x – the x coord of the router
  • router_y – the y coord of the router
Returns:

return all router_path_entries for the router.
get_entry_on_coords_for_edge(partition, router_x, router_y)[source]

Get an entry from a specific coordinate

get_routers()[source]

Get the coordinates of all stored routers

class pacman.model.routing_table_by_partition.MulticastRoutingTableByPartitionEntry(out_going_links, outgoing_processors, incoming_processor=None, incoming_link=None)[source]

Bases: object

An entry in a path of a multicast route.

Parameters:
  • out_going_links (iterable(int)) – the edges this path entry goes down, each of which is between 0 and 5
  • outgoing_processors (iterable(int)) – the processors this path entry goes to, each of which is between 0 and 17
  • incoming_processor (int) – the direction this entry came from (between 0 and 17)
  • incoming_link (int) – the direction this entry came from in link (between 0 and 5)
defaultable

The defaultable status of the entry

The source link for this path entry

Return type:int or None
incoming_processor

The source processor

Return type:int or Non

The destination links of the entry

Return type:set(int)
merge_entry(other)[source]

Merges the another entry with this one and returns a new MulticastRoutingTableByPartitionEntry

Parameters:other – the MulticastRoutingTableByPartitionEntry to merge into this one
Returns:a merged MulticastRoutingTableByPartitionEntry
processor_ids

The destination processors of the entry

Return type:set(int)
pacman.model.routing_tables package
Submodules
pacman.model.routing_tables.multicast_routing_table module
class pacman.model.routing_tables.multicast_routing_table.MulticastRoutingTable(x, y, multicast_routing_entries=None)[source]

Bases: object

Represents a routing table for a chip.

Parameters:
  • x (int) – The x-coordinate of the chip for which this is the routing table
  • y (int) – The y-coordinate of the chip for which this is the routing tables
  • multicast_routing_entries (iterable(spinn_machine.MulticastRoutingEntry)) – The routing entries to add to the table
Raises:

pacman.exceptions.PacmanAlreadyExistsException – If any two routing entries contain the same key-mask combination
add_multicast_routing_entry(multicast_routing_entry)[source]

Adds a routing entry to this table

Parameters:multicast_routing_entry (spinn_machine.MulticastRoutingEntry) – The route to add
Return type:None
Raises:pacman.exceptions.PacmanAlreadyExistsException – If a routing entry with the same key-mask combination already exists
get_multicast_routing_entry_by_routing_entry_key(routing_entry_key, mask)[source]

Get the routing entry associated with the specified key_combo-mask combination or None if the routing table does not match the key_combo

Parameters:
  • routing_entry_key (int) – the routing key to be searched
  • mask (int) – the routing mask to be searched
Returns:

the routing entry associated with the routing key_combo or None if no such entry exists
Return type:

spinn_machine.MulticastRoutingEntry
multicast_routing_entries

The multicast routing entries in the table

Returns:an iterable of multicast routing entries
Return type:iterable(spinn_machine.MulticastRoutingEntry)
Raises:None – does not raise any known exceptions
number_of_defaultable_entries

The number of multi-cast routing entries that are set to be defaultable within this multicast routing table

Returns:int
number_of_entries

The number of multi-cast routing entries there are in the multicast routing table

x

The x-coordinate of the chip of this table

Returns:The x-coordinate
Return type:int
y

The y-coordinate of the chip of this table

Returns:The y-coordinate
Return type:int
pacman.model.routing_tables.multicast_routing_tables module
class pacman.model.routing_tables.multicast_routing_tables.MulticastRoutingTables(routing_tables=None)[source]

Bases: object

Represents the multicast routing tables for a number of chips.

Parameters:routing_tables (iterable(pacman.model.routing_tables.MulticastRoutingTable)) – The routing tables to add
Raises:pacman.exceptions.PacmanAlreadyExistsException – If any two routing tables are for the same chip
add_routing_table(routing_table)[source]

Add a routing table

Parameters:routing_table (pacman.model.routing_tables.MulticastRoutingTable) – a routing table to add
Return type:None
Raises:pacman.exceptions.PacmanAlreadyExistsException – If a routing table already exists for the chip
get_routing_table_for_chip(x, y)[source]

Get a routing table for a particular chip

Parameters:
  • x (int) – The x-coordinate of the chip
  • y (int) – The y-coordinate of the chip
Returns:

The routing table, or None if no such table exists
Return type:

pacman.model.routing_tables.MulticastRoutingTable or None
Raises:

None – No known exceptions are raised
routing_tables

The routing tables stored within

Returns:an iterable of routing tables
Return type:iterable(pacman.model.routing_tables.MulticastRoutingTable)
Raises:None – does not raise any known exceptions
pacman.model.routing_tables.multicast_routing_tables.from_json(j_router)[source]
pacman.model.routing_tables.multicast_routing_tables.to_json(router_table)[source]
Module contents
class pacman.model.routing_tables.MulticastRoutingTable(x, y, multicast_routing_entries=None)[source]

Bases: object

Represents a routing table for a chip.

Parameters:
  • x (int) – The x-coordinate of the chip for which this is the routing table
  • y (int) – The y-coordinate of the chip for which this is the routing tables
  • multicast_routing_entries (iterable(spinn_machine.MulticastRoutingEntry)) – The routing entries to add to the table
Raises:

pacman.exceptions.PacmanAlreadyExistsException – If any two routing entries contain the same key-mask combination
add_multicast_routing_entry(multicast_routing_entry)[source]

Adds a routing entry to this table

Parameters:multicast_routing_entry (spinn_machine.MulticastRoutingEntry) – The route to add
Return type:None
Raises:pacman.exceptions.PacmanAlreadyExistsException – If a routing entry with the same key-mask combination already exists
get_multicast_routing_entry_by_routing_entry_key(routing_entry_key, mask)[source]

Get the routing entry associated with the specified key_combo-mask combination or None if the routing table does not match the key_combo

Parameters:
  • routing_entry_key (int) – the routing key to be searched
  • mask (int) – the routing mask to be searched
Returns:

the routing entry associated with the routing key_combo or None if no such entry exists
Return type:

spinn_machine.MulticastRoutingEntry
multicast_routing_entries

The multicast routing entries in the table

Returns:an iterable of multicast routing entries
Return type:iterable(spinn_machine.MulticastRoutingEntry)
Raises:None – does not raise any known exceptions
number_of_defaultable_entries

The number of multi-cast routing entries that are set to be defaultable within this multicast routing table

Returns:int
number_of_entries

The number of multi-cast routing entries there are in the multicast routing table

x

The x-coordinate of the chip of this table

Returns:The x-coordinate
Return type:int
y

The y-coordinate of the chip of this table

Returns:The y-coordinate
Return type:int
class pacman.model.routing_tables.MulticastRoutingTables(routing_tables=None)[source]

Bases: object

Represents the multicast routing tables for a number of chips.

Parameters:routing_tables (iterable(pacman.model.routing_tables.MulticastRoutingTable)) – The routing tables to add
Raises:pacman.exceptions.PacmanAlreadyExistsException – If any two routing tables are for the same chip
add_routing_table(routing_table)[source]

Add a routing table

Parameters:routing_table (pacman.model.routing_tables.MulticastRoutingTable) – a routing table to add
Return type:None
Raises:pacman.exceptions.PacmanAlreadyExistsException – If a routing table already exists for the chip
get_routing_table_for_chip(x, y)[source]

Get a routing table for a particular chip

Parameters:
  • x (int) – The x-coordinate of the chip
  • y (int) – The y-coordinate of the chip
Returns:

The routing table, or None if no such table exists
Return type:

pacman.model.routing_tables.MulticastRoutingTable or None
Raises:

None – No known exceptions are raised
routing_tables

The routing tables stored within

Returns:an iterable of routing tables
Return type:iterable(pacman.model.routing_tables.MulticastRoutingTable)
Raises:None – does not raise any known exceptions
pacman.model.tags package
Submodules
pacman.model.tags.tags module
class pacman.model.tags.tags.Tags[source]

Bases: object

Represents assigned IP Tag and Reverse IP Tags.

add_ip_tag(ip_tag, vertex)[source]

Add an IP tag

Parameters:
Raises:

PacmanInvalidParameterException –

  • If the combination of (board-address, tag) has already been assigned to an IP tag with different properties
  • If the combination of (board-address, tag) has already been assigned to a reverse IP tag
add_reverse_ip_tag(reverse_ip_tag, vertex)[source]

Add a reverse IP tag

Parameters:
Raises:

PacmanInvalidParameterException –

  • If the combination of (board-address, tag) has already been assigned to an IP tag or Reverse IP tag
  • If the port of the tag has already been assigned on the given board-address
get_ip_tags_for_vertex(vertex)[source]

Get the IP Tags assigned to a given machine vertex

Parameters:vertex (pacman.model.graphs.machine.MachineVertex) – The vertex to get the tags for
Returns:An iterable of IPTag, or None if the vertex has no tags
Return type:iterable(spinn_machine.tags.IPTag) or None
get_reverse_ip_tags_for_vertex(vertex)[source]

Get the Reverse IP Tags assigned to a given machine vertex

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex to get the tags for
Returns:An iterable of ReverseIPTag, or None if the vertex has no tags
Return type:iterable(spinn_machine.tags.ReverseIPTag) or None
ip_tags

The IP tags assigned

Returns:iterable of IPTag
Return type:iterable(spinn_machine.tags.IPTag)
reverse_ip_tags

The reverse IP tags assigned

Returns:iterable of ReverseIPTag
Return type:iterable(spinn_machine.tags.ReverseIPTag)
Module contents
class pacman.model.tags.Tags[source]

Bases: object

Represents assigned IP Tag and Reverse IP Tags.

add_ip_tag(ip_tag, vertex)[source]

Add an IP tag

Parameters:
Raises:

PacmanInvalidParameterException –

  • If the combination of (board-address, tag) has already been assigned to an IP tag with different properties
  • If the combination of (board-address, tag) has already been assigned to a reverse IP tag
add_reverse_ip_tag(reverse_ip_tag, vertex)[source]

Add a reverse IP tag

Parameters:
Raises:

PacmanInvalidParameterException –

  • If the combination of (board-address, tag) has already been assigned to an IP tag or Reverse IP tag
  • If the port of the tag has already been assigned on the given board-address
get_ip_tags_for_vertex(vertex)[source]

Get the IP Tags assigned to a given machine vertex

Parameters:vertex (pacman.model.graphs.machine.MachineVertex) – The vertex to get the tags for
Returns:An iterable of IPTag, or None if the vertex has no tags
Return type:iterable(spinn_machine.tags.IPTag) or None
get_reverse_ip_tags_for_vertex(vertex)[source]

Get the Reverse IP Tags assigned to a given machine vertex

Parameters:vertex (pacman.model.graphs.AbstractVertex) – The vertex to get the tags for
Returns:An iterable of ReverseIPTag, or None if the vertex has no tags
Return type:iterable(spinn_machine.tags.ReverseIPTag) or None
ip_tags

The IP tags assigned

Returns:iterable of IPTag
Return type:iterable(spinn_machine.tags.IPTag)
reverse_ip_tags

The reverse IP tags assigned

Returns:iterable of ReverseIPTag
Return type:iterable(spinn_machine.tags.ReverseIPTag)
Module contents
pacman.operations package
Subpackages
pacman.operations.algorithm_reports package
Submodules
pacman.operations.algorithm_reports.convert_to_json_machine_graph module
class pacman.operations.algorithm_reports.convert_to_json_machine_graph.ConvertToJsonMachineGraph[source]

Bases: object

Converter from MulticastRoutingTables to json

static do_convert(machine_graph, file_path, progress=None)[source]

Runs the code to write the machine in Java readable JSON.

Parameters:
pacman.operations.algorithm_reports.convert_to_json_routing_tables module
class pacman.operations.algorithm_reports.convert_to_json_routing_tables.ConvertToJsonRoutingTables[source]

Bases: object

Converter from MulticastRoutingTables to json

static do_convert(router_table, file_path, progress=None)[source]

Runs the code to write the machine in Java readable JSON.

Parameters:
  • machine (spinn_machine.machine.Machine) – Machine to convert
  • file_path (str) – Location to write file to. Warning will overwrite!
pacman.operations.algorithm_reports.network_specification module
class pacman.operations.algorithm_reports.network_specification.NetworkSpecification[source]

Bases: object

Generate report on the user’s network specification.

pacman.operations.algorithm_reports.reports module
pacman.operations.algorithm_reports.reports.format_route(entry)[source]
pacman.operations.algorithm_reports.reports.generate_comparison_router_report(report_folder, routing_tables, compressed_routing_tables)[source]

Make a report on comparison of the compressed and uncompressed routing tables

Parameters:
  • report_folder – the folder to store the resulting report
  • routing_tables – the original routing tables
  • compressed_routing_tables – the compressed routing tables
Return type:

None
pacman.operations.algorithm_reports.reports.partitioner_report(report_folder, hostname, graph, graph_mapper)[source]

Generate report on the placement of vertices onto cores. :param report_folder: the folder to which the reports are being written :param hostname: the machine’s hostname to which the placer worked on

pacman.operations.algorithm_reports.reports.placement_report_with_application_graph_by_core(report_folder, hostname, placements, machine, graph_mapper)[source]

Generate report on the placement of vertices onto cores by core.

Parameters:
  • report_folder – the folder to which the reports are being written
  • hostname – the machine’s hostname to which the placer worked on
  • graph_mapper – the mapping between application and machine graphs
  • machine – the SpiNNaker machine object
  • placements – the placements objects built by the placer.
pacman.operations.algorithm_reports.reports.placement_report_with_application_graph_by_vertex(report_folder, hostname, graph, graph_mapper, placements)[source]

Generate report on the placement of vertices onto cores by vertex.

Parameters:
  • report_folder – the folder to which the reports are being written
  • hostname – the machine’s hostname to which the placer worked on
  • graph – the graph to which placements were built
  • graph_mapper – the mapping between graphs
  • placements – the placements objects built by the placer.
pacman.operations.algorithm_reports.reports.placement_report_without_application_graph_by_core(report_folder, hostname, placements, machine)[source]

Generate report on the placement of vertices onto cores by core.

Parameters:
  • report_folder – the folder to which the reports are being written
  • hostname – the machine’s hostname to which the placer worked on
  • machine – the SpiNNaker machine object
  • placements – the placements objects built by the placer.
pacman.operations.algorithm_reports.reports.placement_report_without_application_graph_by_vertex(report_folder, hostname, placements, machine_graph)[source]

Generate report on the placement of vertices onto cores by vertex.

Parameters:
  • report_folder – the folder to which the reports are being written
  • hostname – the machine’s hostname to which the placer worked on
  • placements – the placements objects built by the placer.
  • machine_graph – the machine graph generated by the end user
pacman.operations.algorithm_reports.reports.placer_reports_with_application_graph(report_folder, hostname, graph, graph_mapper, placements, machine)[source]

Reports that can be produced from placement given a application graph’s existence

Parameters:
  • report_folder – the folder to which the reports are being written
  • hostname – the machine’s hostname to which the placer worked on
  • graph – the application graph to which placements were built
  • graph_mapper – the mapping between application and machine graphs
  • placements – the placements objects built by the placer.
  • machine – the python machine object
Return type:

None
pacman.operations.algorithm_reports.reports.placer_reports_without_application_graph(report_folder, hostname, machine_graph, placements, machine)[source]
Parameters:
  • report_folder – the folder to which the reports are being written
  • hostname – the machine’s hostname to which the placer worked on
  • placements – the placements objects built by the placer.
  • machine – the python machine object
  • machine_graph – the machine graph to which the reports are to operate on
Return type:

None
pacman.operations.algorithm_reports.reports.router_compressed_summary_report(report_folder, routing_tables, hostname, machine)[source]

Generates a text file of routing summaries

Parameters:
  • report_folder – the report folder to store this value
  • routing_tables – the original routing tables
  • hostname – the machine’s hostname to which the placer worked on
  • machine – the python machine object
Return type:

None
pacman.operations.algorithm_reports.reports.router_report_from_compressed_router_tables(report_folder, routing_tables)[source]
Parameters:
  • report_folder – the report folder to store this value
  • routing_tables – the original routing tables
Return type:

None
pacman.operations.algorithm_reports.reports.router_report_from_paths(report_folder, routing_tables, routing_infos, hostname, machine_graph, placements, machine)[source]

Generates a text file of routing paths

Parameters:
  • report_folder – the report folder to store this value
  • routing_tables – the original routing tables
  • hostname – the machine’s hostname to which the placer worked on
  • routing_infos –
  • machine_graph –
  • placements –
  • machine – the python machine object
Return type:

None
pacman.operations.algorithm_reports.reports.router_report_from_router_tables(report_folder, routing_tables)[source]
Parameters:
  • report_folder – the report folder to store this value
  • routing_tables – the original routing tables
Return type:

None
pacman.operations.algorithm_reports.reports.router_summary_report(report_folder, routing_tables, hostname, machine)[source]

Generates a text file of routing summaries

Parameters:
  • report_folder – the report folder to store this value
  • routing_tables – the original routing tables
  • hostname – the machine’s hostname to which the placer worked on
  • machine – the python machine object
Return type:

None
pacman.operations.algorithm_reports.reports.routing_info_report(report_folder, machine_graph, routing_infos)[source]

Generates a report which says which keys is being allocated to each vertex

Parameters:
  • report_folder – the report folder to store this value
  • machine_graph –
  • routing_infos –
pacman.operations.algorithm_reports.reports.sdram_usage_report_per_chip(report_folder, hostname, placements, machine, plan_n_timesteps, data_n_timesteps)[source]

Reports the SDRAM used per chip

Parameters:
  • report_folder – the folder to which the reports are being written
  • hostname – the machine’s hostname to which the placer worked on
  • placements – the placements objects built by the placer.
  • machine – the python machine object
  • plan_n_timesteps – The number of timesteps for which placer reserved space.
  • data_n_timesteps – The number of timesteps for which data can be saved on the machine.
Return type:

None
pacman.operations.algorithm_reports.reports.tag_allocator_report(report_folder, tag_infos)[source]

Reports the tags that are being used by the tool chain for this simulation

Parameters:
  • report_folder – the folder to which the reports are being written
  • tag_infos – the tags container generated by the tools.
Return type:

None
pacman.operations.algorithm_reports.routing_compression_checker_report module
pacman.operations.algorithm_reports.routing_compression_checker_report.calc_remainders(o_code, c_code)[source]
pacman.operations.algorithm_reports.routing_compression_checker_report.codify(route, length=32)[source]

This method discovers all the routing keys covered by this route.

Starts of with the assumption that the key is always covered.

Whenever a mask bit is zero the list of covered keys is doubled to include both the key with a zero and a one at that place.

Parameters:
Returns:

set of routing_keys covered by this route
Return type:

str
pacman.operations.algorithm_reports.routing_compression_checker_report.codify_table(table, length=32)[source]
pacman.operations.algorithm_reports.routing_compression_checker_report.compare_route(o_route, compressed_dict, o_code=None, start=0, f=None)[source]
pacman.operations.algorithm_reports.routing_compression_checker_report.compare_tables(original, compressed)[source]

Compares the two tables without generating any out

Parameters:
  • original – The orginal routing tables
  • compressed – The compressed routing tables. Which will be considered in order.
Raises:

PacmanRoutingException if there is any error
pacman.operations.algorithm_reports.routing_compression_checker_report.covers(o_code, c_code)[source]
pacman.operations.algorithm_reports.routing_compression_checker_report.generate_routing_compression_checker_report(report_folder, routing_tables, compressed_routing_tables)[source]

Make a full report of how the compressed covers all routes in the and uncompressed routing table

Parameters:
  • report_folder – the folder to store the resulting report
  • routing_tables – the original routing tables
  • compressed_routing_tables – the compressed routing tables
Return type:

None
Module contents
pacman.operations.chip_id_allocator_algorithms package
Submodules
pacman.operations.chip_id_allocator_algorithms.malloc_based_chip_id_allocator module
class pacman.operations.chip_id_allocator_algorithms.malloc_based_chip_id_allocator.MallocBasedChipIdAllocator[source]

Bases: pacman.utilities.algorithm_utilities.element_allocator_algorithm.ElementAllocatorAlgorithm

A Chip ID Allocation Allocator algorithm that keeps track of chip IDs and attempts to allocate them as requested

allocate_chip_ids(machine, graph)[source]

Go through the chips (real and virtual) and allocate keys for each

Bases: pacman.exceptions.PacmanConfigurationException

Bases: pacman.exceptions.PacmanConfigurationException

Module contents
class pacman.operations.chip_id_allocator_algorithms.MallocBasedChipIdAllocator[source]

Bases: pacman.utilities.algorithm_utilities.element_allocator_algorithm.ElementAllocatorAlgorithm

A Chip ID Allocation Allocator algorithm that keeps track of chip IDs and attempts to allocate them as requested

allocate_chip_ids(machine, graph)[source]

Go through the chips (real and virtual) and allocate keys for each

pacman.operations.fixed_route_router package
Submodules
pacman.operations.fixed_route_router.fixed_route_router module
class pacman.operations.fixed_route_router.fixed_route_router.FixedRouteRouter[source]

Bases: object

Module contents
class pacman.operations.fixed_route_router.FixedRouteRouter[source]

Bases: object

pacman.operations.multi_cast_router_check_functionality package
Submodules
pacman.operations.multi_cast_router_check_functionality.valid_routes_checker module

Collection of functions which together validate routes.

class pacman.operations.multi_cast_router_check_functionality.valid_routes_checker.PlacementTuple(x, y, p)

Bases: tuple

Create new instance of PlacementTuple(x, y, p)

p

Alias for field number 2

x

Alias for field number 0

y

Alias for field number 1

pacman.operations.multi_cast_router_check_functionality.valid_routes_checker.validate_routes(machine_graph, placements, routing_infos, routing_tables, machine, graph_mapper=None)[source]

Go though the placements given and check that the routing entries within the routing tables support reach the correction destinations as well as not producing any cycles.

Parameters:
  • machine_graph – the graph
  • placements – the placements container
  • routing_infos – the routing info container
  • routing_tables – the routing tables generated by the routing algorithm
  • graph_mapper – the mapping between graphs or none if only using a machine graph
  • machine (spinn_machine.Machine object) – the python machine object
Return type:

None
Raises:

PacmanRoutingException – when either no routing table entry is found by the search on a given router, or a cycle is detected
Module contents
pacman.operations.multi_cast_router_check_functionality.validate_routes(machine_graph, placements, routing_infos, routing_tables, machine, graph_mapper=None)[source]

Go though the placements given and check that the routing entries within the routing tables support reach the correction destinations as well as not producing any cycles.

Parameters:
  • machine_graph – the graph
  • placements – the placements container
  • routing_infos – the routing info container
  • routing_tables – the routing tables generated by the routing algorithm
  • graph_mapper – the mapping between graphs or none if only using a machine graph
  • machine (spinn_machine.Machine object) – the python machine object
Return type:

None
Raises:

PacmanRoutingException – when either no routing table entry is found by the search on a given router, or a cycle is detected
pacman.operations.partition_algorithms package
Submodules
pacman.operations.partition_algorithms.basic_partitioner module
class pacman.operations.partition_algorithms.basic_partitioner.BasicPartitioner[source]

Bases: object

An basic algorithm that can partition an application graph based on the number of atoms in the vertices.

pacman.operations.partition_algorithms.partition_and_place_partitioner module
class pacman.operations.partition_algorithms.partition_and_place_partitioner.PartitionAndPlacePartitioner[source]

Bases: object

A partitioner that tries to ensure that SDRAM is not overloaded by keeping track of the SDRAM usage on the various chips

Module contents
class pacman.operations.partition_algorithms.BasicPartitioner[source]

Bases: object

An basic algorithm that can partition an application graph based on the number of atoms in the vertices.

class pacman.operations.partition_algorithms.PartitionAndPlacePartitioner[source]

Bases: object

A partitioner that tries to ensure that SDRAM is not overloaded by keeping track of the SDRAM usage on the various chips

pacman.operations.placer_algorithms package
Submodules
pacman.operations.placer_algorithms.basic_placer module
class pacman.operations.placer_algorithms.basic_placer.BasicPlacer[source]

Bases: object

A basic placement algorithm that can place a machine graph onto a machine using the chips as they appear in the machine

pacman.operations.placer_algorithms.one_to_one_placer module
class pacman.operations.placer_algorithms.one_to_one_placer.OneToOnePlacer[source]

Bases: pacman.operations.placer_algorithms.radial_placer.RadialPlacer

Placer that puts vertices which are directly connected to only its destination on the same chip

pacman.operations.placer_algorithms.radial_placer module
class pacman.operations.placer_algorithms.radial_placer.RadialPlacer[source]

Bases: object

A placement algorithm that can place a machine graph onto a machine choosing chips radiating in a circle from the boot chip

pacman.operations.placer_algorithms.spreader_placer module
class pacman.operations.placer_algorithms.spreader_placer.SpreaderPlacer[source]

Bases: pacman.operations.placer_algorithms.one_to_one_placer.OneToOnePlacer

ITERATIONS = 4
STEPS = 4
Module contents
class pacman.operations.placer_algorithms.RadialPlacer[source]

Bases: object

A placement algorithm that can place a machine graph onto a machine choosing chips radiating in a circle from the boot chip

class pacman.operations.placer_algorithms.BasicPlacer[source]

Bases: object

A basic placement algorithm that can place a machine graph onto a machine using the chips as they appear in the machine

class pacman.operations.placer_algorithms.OneToOnePlacer[source]

Bases: pacman.operations.placer_algorithms.radial_placer.RadialPlacer

Placer that puts vertices which are directly connected to only its destination on the same chip

class pacman.operations.placer_algorithms.SpreaderPlacer[source]

Bases: pacman.operations.placer_algorithms.one_to_one_placer.OneToOnePlacer

ITERATIONS = 4
STEPS = 4
pacman.operations.rigged_algorithms package
Submodules
pacman.operations.rigged_algorithms.hilbert_placer module
class pacman.operations.rigged_algorithms.hilbert_placer.HilbertPlacer[source]

Bases: object

A simple placing algorithm using the Hilbert space-filling curve, translated from RIG.

pacman.operations.rigged_algorithms.hilbert_state module
class pacman.operations.rigged_algorithms.hilbert_state.HilbertState(xpos=0, ypos=0, xchange=1, ychange=0)[source]

Bases: object

A mutable self object for the Hilbert placer algorithm.

Parameters:
  • xpos (int) – the x coordinate on the generated curve
  • ypos (int) – the y coordinate on the generated curve
  • xchange (int) – the change in x coordinate on the generated curve
  • ychange (int) – the change in y coordinate on the generated curve
move_forward()[source]

Move forward in the generation of a Hilbert curve

Returns:the x,y coordinates on the generated curve
turn_left(angle)[source]

Turn left in the generation of a Hilbert curve

Parameters:angle (int) – determines the direction in which the curve turns
Returns:the x,y coordinates on the generated curve
turn_right(angle)[source]

Turn right in the generation of a Hilbert curve

Parameters:angle (int) – determines the direction in which the curve turns
Returns:the x,y coordinates on the generated curve
x_pos
y_pos
pacman.operations.rigged_algorithms.isomorph_check module
class pacman.operations.rigged_algorithms.isomorph_check.IsomorphicChecker[source]

Bases: object

A short algorithm to check if there is an isomorphism of the placement of vertices by two separate placement algorithms. One of the algorithms must output to memory placements_copy in its method and <param_type>MemoryPlacements2</param_type> in algorithms_metadata.xml.

check(placements, placements_copy)[source]

Checks if the placements on each processor are the same for two placement algorithms.

Parameters:
Returns:

True if the placements are the same
Return type:

bool
pacman.operations.rigged_algorithms.random_placer module
class pacman.operations.rigged_algorithms.random_placer.RandomPlacer[source]

Bases: object

THRESHOLD = 3
Module contents
class pacman.operations.rigged_algorithms.HilbertPlacer[source]

Bases: object

A simple placing algorithm using the Hilbert space-filling curve, translated from RIG.

class pacman.operations.rigged_algorithms.HilbertState(xpos=0, ypos=0, xchange=1, ychange=0)[source]

Bases: object

A mutable self object for the Hilbert placer algorithm.

Parameters:
  • xpos (int) – the x coordinate on the generated curve
  • ypos (int) – the y coordinate on the generated curve
  • xchange (int) – the change in x coordinate on the generated curve
  • ychange (int) – the change in y coordinate on the generated curve
move_forward()[source]

Move forward in the generation of a Hilbert curve

Returns:the x,y coordinates on the generated curve
turn_left(angle)[source]

Turn left in the generation of a Hilbert curve

Parameters:angle (int) – determines the direction in which the curve turns
Returns:the x,y coordinates on the generated curve
turn_right(angle)[source]

Turn right in the generation of a Hilbert curve

Parameters:angle (int) – determines the direction in which the curve turns
Returns:the x,y coordinates on the generated curve
x_pos
y_pos
class pacman.operations.rigged_algorithms.IsomorphicChecker[source]

Bases: object

A short algorithm to check if there is an isomorphism of the placement of vertices by two separate placement algorithms. One of the algorithms must output to memory placements_copy in its method and <param_type>MemoryPlacements2</param_type> in algorithms_metadata.xml.

check(placements, placements_copy)[source]

Checks if the placements on each processor are the same for two placement algorithms.

Parameters:
Returns:

True if the placements are the same
Return type:

bool
class pacman.operations.rigged_algorithms.RandomPlacer[source]

Bases: object

THRESHOLD = 3
pacman.operations.router_algorithms package
Submodules
pacman.operations.router_algorithms.basic_dijkstra_routing module
class pacman.operations.router_algorithms.basic_dijkstra_routing.BasicDijkstraRouting[source]

Bases: object

An routing algorithm that can find routes for edges between vertices in a machine graph that have been placed on a machine by the use of a Dijkstra shortest path algorithm.

BW_PER_ROUTE_ENTRY = 0.01
MAX_BW = 250
pacman.operations.router_algorithms.ner_route module

Neighbour Exploring Routing (NER) algorithm from J. Navaridas et al.

Algorithm refrence: J. Navaridas et al. SpiNNaker: Enhanced multicast routing, Parallel Computing (2014).

http://dx.doi.org/10.1016/j.parco.2015.01.002

Based on https://github.com/project-rig/rig/blob/master/rig/place_and_route/route/ner.py https://github.com/project-rig/rig/blob/master/rig/geometry.py https://github.com/project-rig/rig/blob/master/rig/place_and_route/route/utils.py

class pacman.operations.router_algorithms.ner_route.NerRoute[source]

Bases: object

Performs routing using rig algorithm

pacman.operations.router_algorithms.routing_tree module

An explicit representation of a routing tree in a machine.

This representation of a route explicitly describes a tree-structure and the complete path taken by a route. This is used during place and route in preference to a set of RoutingTableEntry tuples since it is more easily verified and more accurately represents the problem at hand.

Based on https://github.com/project-rig/rig/blob/master/rig/place_and_route/routing_tree.py

class pacman.operations.router_algorithms.routing_tree.RoutingTree(chip)[source]

Bases: object

Explicitly defines a multicast route through a SpiNNaker machine.

Each instance represents a single hop in a route and recursively refers to following steps.

Parameters:chip (tuple(int,int)) – The chip the route is currently passing through.
append_child(child)[source]
children

A iterable of the next steps in the route represented by a (route, object) tuple.

Note

Up until Rig 1.5.1, this structure used sets to store children. This was changed to lists since sets incur a large memory overhead and in practice the set-like behaviour of the list of children is not useful.

The object indicates the intended destination of this step in the route. It may be one of:

  • RoutingTree representing the continuation of the routing tree after following a given link.
  • A vertex (i.e. some other Python object) when the route terminates at the supplied vertex. Note that the direction may be None and so additional logic may be required to determine what core to target to reach the vertex.
Return type:iterable
chip

The chip the route is currently passing through.

Return type:tuple(int,int)
remove_child(child)[source]
traverse()[source]

Traverse the tree yielding the direction taken to a node, the coordinates of that node and the directions leading from the Node.

Returns:(direction, (x, y), set(route)) Direction taken to reach a Node in the tree, the (x, y) coordinate of that Node and routes leading to children of the Node.
Module contents
class pacman.operations.router_algorithms.BasicDijkstraRouting[source]

Bases: object

An routing algorithm that can find routes for edges between vertices in a machine graph that have been placed on a machine by the use of a Dijkstra shortest path algorithm.

BW_PER_ROUTE_ENTRY = 0.01
MAX_BW = 250
class pacman.operations.router_algorithms.NerRoute[source]

Bases: object

Performs routing using rig algorithm

pacman.operations.router_compressors package
Subpackages
pacman.operations.router_compressors.mundys_router_compressor package
Submodules
pacman.operations.router_compressors.mundys_router_compressor.ordered_covering module
Ordered Covering

An novel algorithm for the minimisation of SpiNNaker’s multicast routing tables devised by Andrew Mundy.

Background

SpiNNaker routing tables consist of entries made up of a 32-bit key, a 32-bit mask and a 24-bit route value. The key and mask of every entry act as a sieve for the keys found on incoming multicast packets. Each bit of the key-mask pair can be considered as matching 0, 1 or 2 values in the same bit of a multicast packet key:

Key Mask Matches Key Values Written
0 0 0 or 1 X
0 1 0 0
1 1 1 1
1 0 Nothing !

If a packet matches the key-mask of an entry then the packet is transmitted to the cores and links indicated by the route field.

For example, if the table were:

Key Mask Route
0000 1111 North, North East
0111 0111 South

Which, from now on, will be written as:

0000 -> N NE
X111 -> S

Then any packets with the key 0000 would be sent out of the north and north-east links. Any packets with the keys 0111 or 1111 would be sent out of the south link only.

Entries in table are ordered, with entries at the top of the table having higher priority than those lower down the table. Only the highest priority entry which matches a packet is used. If, for example, the table were:

0000 -> N NE
1111 -> 1 2
X111 -> S

Then packets with the keys 0000 and 0111 would be treated as before. However, packets with the key 1111 would be sent to cores 1 and 2 as only the higher priority entry has effect.

Merging routing table entries

Routing tables can be minimised by merging together entries with equivalent routes. This is done by creating a new key-mask pair with an X wherever the key-mask pairs of any of the original entries differed.

For example, merging of the entries:

0000 -> N
0001 -> N

Would lead to the new entry:

000X -> N

Which would match any of the keys matched by the original entries but no more. In contrast the merge of 0001 and 0010 would generate the new entry 00XX which would match keys matched by either of the original entries but also 0000 and 0011.

Clearly, if we are to attempt to minimise tables such as:

0001 -> N
0010 -> N
0000 -> S, SE
0011 -> SE

We need a set of rules for:

  1. Where merged entries are to be inserted into the table
  2. Which merges are allowed
“Ordered Covering”

The algorithm implemented here, “Ordered Covering”, provides the following rule:

  • The only merges allowed are those which:
    1. would not cause one of the entries in the merge to be “hidden” below an entry of lesser generality than the merged entry but which matched any of the same keys. For example, merging 0010 and 0001 would not be allowed if the new entry would be placed below the existing entry 000X as this would “hide” 0001.
    2. would not cause an entry “contained” within an entry of higher generality to be hidden by the insertion of a new entry. For example, if the entry XXXX had been formed by merging the entries 0011 and 1100 then merging of the entries 1101 and 1110 would not be allowed as it would cause the entry 11XX to be inserted above XXXX in the table and would hide 1100.

Following these rules ensures that the minimised table will be functionally equivalent to the original table provided that the original table was invariant under reordering OR was provided in increasing order of generality.

As a heuristic:

  • Routing tables are to be kept sorted in increasing order of “generality”, that is the number of X``s in the entry. An entry with the key-mask pair ``00XX must be placed below any entries with fewer X``s in their key-mask pairs (e.g., below ``0000 and 000X).
    1. New entries must also be inserted below any entries of the same generality. If XX00 were already present in the table the new entry 0XX0 must be inserted below it.

based on https://github.com/project-rig/rig/blob/master/rig/routing_table/ordered_covering.py

pacman.operations.router_compressors.mundys_router_compressor.ordered_covering.minimise(routing_table, target_length)[source]

Reduce the size of a routing table by merging together entries where possible and by removing any remaining default routes.

Warning

The input routing table must also include entries which could be removed and replaced by default routing.

Warning

It is assumed that the input routing table is not in any particular order and may be reordered into ascending order of generality (number of don’t cares/Xs in the key-mask) without affecting routing correctness. It is also assumed that if this table is unordered it is at least orthogonal (i.e., there are no two entries which would match the same key) and reorderable.

Parameters:
  • routing_table (Entry) – Routing entries to be merged.
  • target_length (int or None) – Target length of the routing table; the minimisation procedure will halt once either this target is reached or no further minimisation is possible. If None then the table will be made as small as possible.
Returns:

list(RoutingTableEntry)
Raises:

MinimisationFailedError – If the smallest table that can be produced is larger than target_length.
pacman.operations.router_compressors.mundys_router_compressor.ordered_covering.ordered_covering(routing_table, target_length, aliases=None, no_raise=False)[source]

Reduce the size of a routing table by merging together entries where possible.

Warning

The input routing table must also include entries which could be removed and replaced by default routing.

Warning

It is assumed that the input routing table is not in any particular order and may be reordered into ascending order of generality (number of don’t cares/Xs in the key-mask) without affecting routing correctness. It is also assumed that if this table is unordered it is at least orthogonal (i.e., there are no two entries which would match the same key) and reorderable.

Parameters:
  • routing_table (Entry) – Routing entries to be merged.
  • target_length (int or None) – Target length of the routing table; the minimisation procedure will halt once either this target is reached or no further minimisation is possible. If None then the table will be made as small as possible.
  • aliases (dict((int, int): set((int, int))) – Dictionary of which keys and masks in the routing table are combinations of other (now removed) keys and masks; this allows us to consider only the keys and masks the user actually cares about when determining if inserting a new entry will break the correctness of the table. This should be supplied when using this method to update an already minimised table.
  • no_raise (bool) – If False (the default) then an error will be raised if the table cannot be minimised to be smaller than target_length and target_length is not None. If True then a table will be returned regardless of the size of the final table.
Returns:

list(RoutingTableEntry) , {(key, mask): {(key, mask), …}, …} new routing table, A new aliases dictionary.
Raises:

MinimisationFailedError – If the smallest table that can be produced is larger than target_length.
pacman.operations.router_compressors.mundys_router_compressor.remove_default_routes module

based on https://github.com/project-rig/rig/blob/master/rig/routing_table/remove_default_routes.py

pacman.operations.router_compressors.mundys_router_compressor.remove_default_routes.minimise(table, target_length, check_for_aliases=True)[source]

Remove from the routing table any entries which could be replaced by default routing.

Parameters:
  • routing_table (RoutingTableEntry) – Routing entries to be merged.
  • target_length – Target length of the routing table; the minimisation procedure will halt once either this target is reached or no further minimisation is possible. If None then the table will be made as small as possible. :type target_length: int or None
  • check_for_aliases –

    If True (the default), default-route candidates are checked for aliased entries before suggesting a route may be default routed. This check is required to ensure correctness in the general case but has a runtime complexity of O(N^2) in the worst case for N-entry tables.

    If False, the alias-check is skipped resulting in O(N) runtime. This option should only be used if the supplied table is guaranteed not to contain any aliased entries.
Return type:

list(RoutingTableEntry)
Raises:

MinimisationFailedError – If the smallest table that can be produced is larger than target_length.
pacman.operations.router_compressors.mundys_router_compressor.routing_table_condenser module
class pacman.operations.router_compressors.mundys_router_compressor.routing_table_condenser.MundyRouterCompressor[source]

Bases: pacman.operations.router_compressors.abstract_compressor.AbstractCompressor

Compressor from rig that has been tied into the main tool chain stack.

compress_table(router_table)[source]
pacman.operations.router_compressors.mundys_router_compressor.utils module

based on https://github.com/project-rig/rig/blob/master/rig/routing_table/utils.py

pacman.operations.router_compressors.mundys_router_compressor.utils.intersect(key_a, mask_a, key_b, mask_b)[source]

Return if key-mask pairs intersect (i.e., would both match some of the same keys).

For example, the key-mask pairs 00XX and 001X both match the keys 0010 and 0011 (i.e., they do intersect):

>>> intersect(0b0000, 0b1100, 0b0010, 0b1110)
True

But the key-mask pairs 00XX and 11XX do not match any of the same keys (i.e., they do not intersect):

>>> intersect(0b0000, 0b1100, 0b1100, 0b1100)
False
Parameters:
  • key_a –
  • mask_a – The first key-mask pair
  • key_b –
  • mask_b – The second key-mask pair
Return type:

bool
Returns:

True if the two key-mask pairs intersect, otherwise False.
Module contents
Submodules
pacman.operations.router_compressors.abstract_compressor module

based on https://github.com/project-rig/

class pacman.operations.router_compressors.abstract_compressor.AbstractCompressor(ordered=True)[source]

Bases: object

MAX_SUPPORTED_LENGTH = 1023
compress_table(router_table)[source]
compress_tables(router_tables, progress)[source]

Compress all the unordered routing tables

Tables who start of smaller than target_length are not compressed

Parameters:
  • router_tables (MulticastRoutingTable) – Routing tables
  • progress – Progress bar to show while working
Tpye progress:

ProgressBar
Returns:

The compressed but still unordered routing tables
static intersect(key_a, mask_a, key_b, mask_b)[source]

Return if key-mask pairs intersect (i.e., would both match some of the same keys).

For example, the key-mask pairs 00XX and 001X both match the keys``0010`` and 0011 (i.e., they do intersect):

>>> intersect(0b0000, 0b1100, 0b0010, 0b1110)
True

But the key-mask pairs 00XX and 11XX do not match any of the same keys (i.e., they do not intersect):

>>> intersect(0b0000, 0b1100, 0b1100, 0b1100)
False
Parameters:
  • key_a (int) – The key of first key-mask pair
  • mask_a – The mask of first key-mask pair
  • key_b (int) – The key of second key-mask pair
  • mask_b – The mask of second key-mask pair
Returns:

True if the two key-mask pairs intersect otherwise False.
Return type:

bool
merge(entry1, entry2)[source]

Merges two entries/triples into one that covers both

The assumption is that they both have the same known spinnaker_route

Parameters:
  • entry1 (Entry) – Key, Mask, defaultable from the first entry
  • entry2 (Entry) – Key, Mask, defaultable from the second entry
Returns:

Key, Mask, defaultable from merged entry
Return type:

(int, int, bool)
ordered
pacman.operations.router_compressors.basic_route_merger module
class pacman.operations.router_compressors.basic_route_merger.BasicRouteMerger[source]

Bases: object

Merges routing tables entries via different masks and an exploration process

pacman.operations.router_compressors.checked_unordered_compressor module
class pacman.operations.router_compressors.checked_unordered_compressor.CheckedUnorderedCompressor[source]

Bases: pacman.operations.router_compressors.unordered_compressor.UnorderedCompressor

verify_lengths(compressed)[source]
pacman.operations.router_compressors.clash_compressor module
class pacman.operations.router_compressors.clash_compressor.ClashCompressor(ordered=True)[source]

Bases: pacman.operations.router_compressors.abstract_compressor.AbstractCompressor

compress_by_route(route_entries)[source]
compress_ignore_clashers(router_table, top_entries)[source]
compress_table(router_table)[source]
find_merge(an_entry, route_entries)[source]
pacman.operations.router_compressors.entry module
class pacman.operations.router_compressors.entry.Entry(key, mask, defaultable, spinnaker_route)[source]

Bases: object

defaultable
static from_MulticastRoutingEntry(mre)[source]
key
mask
spinnaker_route
to_MulticastRoutingEntry()[source]
pacman.operations.router_compressors.malloc_based_route_merger module
class pacman.operations.router_compressors.malloc_based_route_merger.MallocBasedRouteMerger[source]

Bases: object

Routing table entry merging function, that merges based off a malloc memory style.

pacman.operations.router_compressors.pair_compressor module
class pacman.operations.router_compressors.pair_compressor.PairCompressor(ordered=True)[source]

Bases: pacman.operations.router_compressors.abstract_compressor.AbstractCompressor

Routing Table compressor based on brute force. Finds mergable pairs to replace.

This algorithm assumes unordered routing tables and returns a possibly ordered routing tables. If unordered it can be used as a precompressor for another that makes use of order.

In the simplest format the algorithm is:

  1. For every pair of entries in the table
    1. If they have the same spinnaker_route
      1. Create a merged entry
      2. Check that does not intersect any entry with a different route
        1. Remove the two original entries
        2. Add the merged entry
        3. Start over

A slightly optimised algorithm is:

  1. Split the entries into buckets based on spinnaker route
  2. Process the buckets one at a time
    1. For each entry in the buckets
      1. For each other entry in the bucket
        1. Create a merge entry
        2. Make sure there is no clash with an entry in another bucket
        3. Replace the two entries and add the merge
        4. Start the bucket over
      2. If no merge found move the entry from the bucket to the result list
    2. When the bucket is empty the result list becomes the bucket

A farther optimisation is to do the whole thing in place in a single list:

  1. Step 1 is sort the list by route in place
  2. Step 2 do the compression route by route using indexes into the array
    1. The array is split into 6 parts.
      1. 0 to _previous_pointer(-1): Entries in buckets that have already been compressed
      2. _previous_pointer to _write_pointer(-1): Finished entries for the current bucket
      3. _write_pointer to left(-1): Unused space due to previous merges
      4. left to right: Not yet finished entries from the current bucket
      5. right(+ 1) to _remaining_index(-1): Unused space due to previous merges
      6. _remaining_index to max_index(-1): Entries in buckets not yet compressed
  3. Step 3 use only the entries up to _write_pointer(-1)

A farther optimisation is to uses order. The entries are sorted by route frequency from low to high. The results are considered ordered so previous routes are not considered.

The advantage is this allows all the entries from the most frequent route to be merged into a single entry. And the second most frequent only has to consider the most frequent routes.

Step 1 requires the counting of the frequency of routes and the sorting the routes based on this frequency. The current tie break between routes with the same frequency is the route but this is arbitrary at the algorithm level. This code does not use a dictionary to keep the code the same as the C.

Step 2 is change in that the previous entries (0 to _previous_pointer(-1)) are not considered for clash checking

compress_table(router_table)[source]

Compresses all the entries for a single table.

Compressed the entries for this unordered table returning a new table with possibly fewer entries but still unordered

Parameters:router_table (MulticastRoutingTable) – Original Routing table for a single chip
Returns:Compressed routing table for the same chip
Return type:MulticastRoutingTable
update_frequency(route)[source]
pacman.operations.router_compressors.unordered_compressor module
class pacman.operations.router_compressors.unordered_compressor.UnorderedCompressor[source]

Bases: pacman.operations.router_compressors.pair_compressor.PairCompressor

Module contents
class pacman.operations.router_compressors.AbstractCompressor(ordered=True)[source]

Bases: object

MAX_SUPPORTED_LENGTH = 1023
compress_table(router_table)[source]
compress_tables(router_tables, progress)[source]

Compress all the unordered routing tables

Tables who start of smaller than target_length are not compressed

Parameters:
  • router_tables (MulticastRoutingTable) – Routing tables
  • progress – Progress bar to show while working
Tpye progress:

ProgressBar
Returns:

The compressed but still unordered routing tables
static intersect(key_a, mask_a, key_b, mask_b)[source]

Return if key-mask pairs intersect (i.e., would both match some of the same keys).

For example, the key-mask pairs 00XX and 001X both match the keys``0010`` and 0011 (i.e., they do intersect):

>>> intersect(0b0000, 0b1100, 0b0010, 0b1110)
True

But the key-mask pairs 00XX and 11XX do not match any of the same keys (i.e., they do not intersect):

>>> intersect(0b0000, 0b1100, 0b1100, 0b1100)
False
Parameters:
  • key_a (int) – The key of first key-mask pair
  • mask_a – The mask of first key-mask pair
  • key_b (int) – The key of second key-mask pair
  • mask_b – The mask of second key-mask pair
Returns:

True if the two key-mask pairs intersect otherwise False.
Return type:

bool
merge(entry1, entry2)[source]

Merges two entries/triples into one that covers both

The assumption is that they both have the same known spinnaker_route

Parameters:
  • entry1 (Entry) – Key, Mask, defaultable from the first entry
  • entry2 (Entry) – Key, Mask, defaultable from the second entry
Returns:

Key, Mask, defaultable from merged entry
Return type:

(int, int, bool)
ordered
class pacman.operations.router_compressors.CheckedUnorderedCompressor[source]

Bases: pacman.operations.router_compressors.unordered_compressor.UnorderedCompressor

verify_lengths(compressed)[source]
class pacman.operations.router_compressors.Entry(key, mask, defaultable, spinnaker_route)[source]

Bases: object

defaultable
static from_MulticastRoutingEntry(mre)[source]
key
mask
spinnaker_route
to_MulticastRoutingEntry()[source]
class pacman.operations.router_compressors.PairCompressor(ordered=True)[source]

Bases: pacman.operations.router_compressors.abstract_compressor.AbstractCompressor

Routing Table compressor based on brute force. Finds mergable pairs to replace.

This algorithm assumes unordered routing tables and returns a possibly ordered routing tables. If unordered it can be used as a precompressor for another that makes use of order.

In the simplest format the algorithm is:

  1. For every pair of entries in the table
    1. If they have the same spinnaker_route
      1. Create a merged entry
      2. Check that does not intersect any entry with a different route
        1. Remove the two original entries
        2. Add the merged entry
        3. Start over

A slightly optimised algorithm is:

  1. Split the entries into buckets based on spinnaker route
  2. Process the buckets one at a time
    1. For each entry in the buckets
      1. For each other entry in the bucket
        1. Create a merge entry
        2. Make sure there is no clash with an entry in another bucket
        3. Replace the two entries and add the merge
        4. Start the bucket over
      2. If no merge found move the entry from the bucket to the result list
    2. When the bucket is empty the result list becomes the bucket

A farther optimisation is to do the whole thing in place in a single list:

  1. Step 1 is sort the list by route in place
  2. Step 2 do the compression route by route using indexes into the array
    1. The array is split into 6 parts.
      1. 0 to _previous_pointer(-1): Entries in buckets that have already been compressed
      2. _previous_pointer to _write_pointer(-1): Finished entries for the current bucket
      3. _write_pointer to left(-1): Unused space due to previous merges
      4. left to right: Not yet finished entries from the current bucket
      5. right(+ 1) to _remaining_index(-1): Unused space due to previous merges
      6. _remaining_index to max_index(-1): Entries in buckets not yet compressed
  3. Step 3 use only the entries up to _write_pointer(-1)

A farther optimisation is to uses order. The entries are sorted by route frequency from low to high. The results are considered ordered so previous routes are not considered.

The advantage is this allows all the entries from the most frequent route to be merged into a single entry. And the second most frequent only has to consider the most frequent routes.

Step 1 requires the counting of the frequency of routes and the sorting the routes based on this frequency. The current tie break between routes with the same frequency is the route but this is arbitrary at the algorithm level. This code does not use a dictionary to keep the code the same as the C.

Step 2 is change in that the previous entries (0 to _previous_pointer(-1)) are not considered for clash checking

compress_table(router_table)[source]

Compresses all the entries for a single table.

Compressed the entries for this unordered table returning a new table with possibly fewer entries but still unordered

Parameters:router_table (MulticastRoutingTable) – Original Routing table for a single chip
Returns:Compressed routing table for the same chip
Return type:MulticastRoutingTable
update_frequency(route)[source]
class pacman.operations.router_compressors.UnorderedCompressor[source]

Bases: pacman.operations.router_compressors.pair_compressor.PairCompressor

pacman.operations.routing_info_allocator_algorithms package
Subpackages
pacman.operations.routing_info_allocator_algorithms.field_based_routing_allocator package
Module contents
pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator package
Submodules
pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.compressible_malloc_based_routing_info_allocator module
class pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.compressible_malloc_based_routing_info_allocator.CompressibleMallocBasedRoutingInfoAllocator[source]

Bases: pacman.utilities.algorithm_utilities.element_allocator_algorithm.ElementAllocatorAlgorithm

A Routing Info Allocation Allocator algorithm that keeps track of free keys and attempts to allocate them as requested, but that also looks at routing tables in an attempt to make things more compressible

pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.key_field_generator module
class pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.key_field_generator.KeyFieldGenerator(fixed_mask, fields, free_space_list)[source]

Bases: object

Handle fields in a routing key.

is_next_key
next()[source]
next_key
pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.malloc_based_routing_info_allocator module
class pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.malloc_based_routing_info_allocator.MallocBasedRoutingInfoAllocator[source]

Bases: pacman.utilities.algorithm_utilities.element_allocator_algorithm.ElementAllocatorAlgorithm

A Routing Info Allocation Allocator algorithm that keeps track of free keys and attempts to allocate them as requested

pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.utils module
pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.utils.get_possible_masks(n_keys, mask_width=32, contiguous_keys=True)[source]

Get the possible masks given the number of keys.

Parameters:
  • n_keys (int) – The number of keys to generate a mask for
  • mask_width – Number of bits that are meaningful in the mask. 32 by default.
  • mask_width – int
  • contiguous_keys – True if the mask should only have zeros in the LSBs
Returns:

A generator of all possible masks
Return type:

iterable(int)
pacman.operations.routing_info_allocator_algorithms.malloc_based_routing_allocator.utils.zero_out_bits(all_ones_mask, bits_to_zero)[source]

Takes a mask (with all interesting bits set to 1) and zeroes out the bits at the given indices.

Parameters:
  • all_ones_mask (int) – Initial mask
  • bits_to_zero (iterable(int)) – Which bits to clear. The LSB is zero.
Returns:

A single mask, with zeroes in all required places
Return type:

int
Module contents
Submodules
pacman.operations.routing_info_allocator_algorithms.basic_routing_info_allocator module
class pacman.operations.routing_info_allocator_algorithms.basic_routing_info_allocator.BasicRoutingInfoAllocator[source]

Bases: object

An basic algorithm that can produce routing keys and masks for edges in a graph based on the x,y,p of the placement of the preceding vertex.

Note

No constraints are supported, and that the number of keys required by each edge must be 2048 or less, and that all edges coming out of a vertex will be given the same key/mask assignment.

pacman.operations.routing_info_allocator_algorithms.destination_based_key_allocator module
class pacman.operations.routing_info_allocator_algorithms.destination_based_key_allocator.DestinationBasedRoutingInfoAllocator[source]

Bases: object

A routing key allocator that operates for people who wish to have a separate key for each destination (making a multicast into a point-to-point cast).

MASK = 4294965248
MAX_KEYS_SUPPORTED = 2048
pacman.operations.routing_info_allocator_algorithms.zoned_routing_info_allocator module
class pacman.operations.routing_info_allocator_algorithms.zoned_routing_info_allocator.ZonedRoutingInfoAllocator[source]

Bases: object

An basic algorithm that can produce routing keys and masks for edges in a graph based on the x,y,p of the placement of the preceding vertex.

Note

No constraints are supported, and that the number of keys required by each edge must be 2048 or less, and that all edges coming out of a vertex will be given the same key/mask assignment.

Module contents
class pacman.operations.routing_info_allocator_algorithms.BasicRoutingInfoAllocator[source]

Bases: object

An basic algorithm that can produce routing keys and masks for edges in a graph based on the x,y,p of the placement of the preceding vertex.

Note

No constraints are supported, and that the number of keys required by each edge must be 2048 or less, and that all edges coming out of a vertex will be given the same key/mask assignment.

class pacman.operations.routing_info_allocator_algorithms.CompressibleMallocBasedRoutingInfoAllocator[source]

Bases: pacman.utilities.algorithm_utilities.element_allocator_algorithm.ElementAllocatorAlgorithm

A Routing Info Allocation Allocator algorithm that keeps track of free keys and attempts to allocate them as requested, but that also looks at routing tables in an attempt to make things more compressible

class pacman.operations.routing_info_allocator_algorithms.DestinationBasedRoutingInfoAllocator[source]

Bases: object

A routing key allocator that operates for people who wish to have a separate key for each destination (making a multicast into a point-to-point cast).

MASK = 4294965248
MAX_KEYS_SUPPORTED = 2048
class pacman.operations.routing_info_allocator_algorithms.MallocBasedRoutingInfoAllocator[source]

Bases: pacman.utilities.algorithm_utilities.element_allocator_algorithm.ElementAllocatorAlgorithm

A Routing Info Allocation Allocator algorithm that keeps track of free keys and attempts to allocate them as requested

pacman.operations.routing_table_generators package
Submodules
pacman.operations.routing_table_generators.basic_routing_table_generator module
class pacman.operations.routing_table_generators.basic_routing_table_generator.BasicRoutingTableGenerator[source]

Bases: object

An basic algorithm that can produce routing tables

pacman.operations.routing_table_generators.zoned_routing_table_generator module
class pacman.operations.routing_table_generators.zoned_routing_table_generator.SharedEntry(entry)[source]

Bases: object

slots = ['link_ids', 'processor_ids', 'defaultable']
still_defaultable(entry)[source]
class pacman.operations.routing_table_generators.zoned_routing_table_generator.ZonedRoutingTableGenerator[source]

Bases: object

An basic algorithm that can produce routing tables

Module contents
pacman.operations.tag_allocator_algorithms package
Submodules
pacman.operations.tag_allocator_algorithms.basic_tag_allocator module
class pacman.operations.tag_allocator_algorithms.basic_tag_allocator.BasicTagAllocator[source]

Bases: object

Basic tag allocator that goes though the boards available and applies the IP tags and reverse IP tags as needed.

Module contents
class pacman.operations.tag_allocator_algorithms.BasicTagAllocator[source]

Bases: object

Basic tag allocator that goes though the boards available and applies the IP tags and reverse IP tags as needed.

Module contents
pacman.utilities package
Subpackages
pacman.utilities.algorithm_utilities package
Submodules
pacman.utilities.algorithm_utilities.element_allocator_algorithm module
class pacman.utilities.algorithm_utilities.element_allocator_algorithm.ElementAllocatorAlgorithm(size_begin, size_end)[source]

Bases: object

Abstract element allocator algorithm which allocates elements from a pool of a given size

pacman.utilities.algorithm_utilities.field_based_system_utilities module
class pacman.utilities.algorithm_utilities.field_based_system_utilities.TYPES_OF_FIELDS[source]

Bases: enum.Enum

An enumeration.

FIXED_FIELD = 2
FIXED_KEY = 1
FIXED_MASK = 0
pacman.utilities.algorithm_utilities.field_based_system_utilities.convert_mask_into_fields(entity)[source]
Parameters:entity –
pacman.utilities.algorithm_utilities.field_based_system_utilities.deduce_types(graph)[source]

Deducing the number of applications required for this key space.

Parameters:graph –
pacman.utilities.algorithm_utilities.field_based_system_utilities.handle_flexi_field(constraint, seen_fields, known_fields)[source]
Parameters:
  • constraint –
  • seen_fields –
  • known_fields –
Return type:

None:
pacman.utilities.algorithm_utilities.machine_algorithm_utilities module
pacman.utilities.algorithm_utilities.machine_algorithm_utilities.create_virtual_chip(machine, link_data, virtual_chip_x, virtual_chip_y)[source]
pacman.utilities.algorithm_utilities.partition_algorithm_utilities module

A collection of methods which support partitioning algorithms.

pacman.utilities.algorithm_utilities.partition_algorithm_utilities.generate_machine_edges(machine_graph, graph_mapper, application_graph)[source]

Generate the machine edges for the vertices in the graph

Parameters:
pacman.utilities.algorithm_utilities.partition_algorithm_utilities.get_remaining_constraints(vertex)[source]

Gets the rest of the constraints from a vertex after removing partitioning constraints

pacman.utilities.algorithm_utilities.partition_algorithm_utilities.get_same_size_vertex_groups(vertices)[source]

Get a dictionary of vertex to vertex that must be partitioned the same size

pacman.utilities.algorithm_utilities.placer_algorithm_utilities module
pacman.utilities.algorithm_utilities.placer_algorithm_utilities.add_set(all_sets, new_set)[source]

Adds a new set into the list of sets, concatenating sets if required.

If the new set does not overlap any existing sets it is added.

However if the new sets overlaps one or more existing sets, a superset is created combining all the overlapping sets. Existing overlapping sets are removed and only the new superset is added.

Parameters:
  • all_sets – List of Non overlapping sets
  • new_set – A new set which may or may not overlap the previous sets.
pacman.utilities.algorithm_utilities.placer_algorithm_utilities.create_vertices_groups(vertices, same_group_as_function)[source]
pacman.utilities.algorithm_utilities.placer_algorithm_utilities.get_same_chip_vertex_groups(graph)[source]

Get a dictionary of vertex to list of vertices that must be placed on the same chip

Parameters:graph – The graph containing the vertices
pacman.utilities.algorithm_utilities.placer_algorithm_utilities.get_vertices_on_same_chip(vertex, graph)[source]

Get the vertices that must be on the same chip as the given vertex

Parameters:
  • vertex – The vertex to search with
  • graph – The graph containing the vertex
pacman.utilities.algorithm_utilities.placer_algorithm_utilities.group_vertices(vertices, same_group_as_function)[source]

Group vertices according to some function that can indicate the groups that any vertex can be contained within

Parameters:
  • vertices – The vertices to group
  • same_group_as_function – A function which takes a vertex and returns vertices that should be in the same group (excluding the original vertex)
Returns:

A dictionary of vertex to list of vertices that are grouped with it
pacman.utilities.algorithm_utilities.placer_algorithm_utilities.sort_vertices_by_known_constraints(vertices)[source]

Sort vertices to be placed by constraint so that those with more restrictive constraints come first.

pacman.utilities.algorithm_utilities.routing_info_allocator_utilities module
class pacman.utilities.algorithm_utilities.routing_info_allocator_utilities.ConstraintGroup(values)[source]

Bases: list

constraint
pacman.utilities.algorithm_utilities.routing_info_allocator_utilities.check_types_of_edge_constraint(machine_graph)[source]

Go through the graph for operations and checks that the constraints are compatible.

Parameters:machine_graph – the graph to search through
Return type:None:
pacman.utilities.algorithm_utilities.routing_info_allocator_utilities.get_edge_groups(machine_graph, traffic_type)[source]

Utility method to get groups of edges using any KeyAllocatorSameKeyConstraint constraints. Note that no checking is done here about conflicts related to other constraints.

Parameters:
  • machine_graph – the machine graph
  • traffic_type – the traffic type to group
pacman.utilities.algorithm_utilities.routing_info_allocator_utilities.get_fixed_mask(same_key_group)[source]

Get a fixed mask from a group of edges if a FixedMaskConstraint constraint exists in any of the edges in the group.

Parameters:same_key_group (iterable(pacman.model.graphs.machine.MachineEdge)) – Set of edges that are to be assigned the same keys and masks
Returns:The fixed mask if found, or None
Raises:PacmanValueError – If two edges conflict in their requirements
Module contents
class pacman.utilities.algorithm_utilities.ElementAllocatorAlgorithm(size_begin, size_end)[source]

Bases: object

Abstract element allocator algorithm which allocates elements from a pool of a given size

pacman.utilities.file_format_converters package
Submodules
pacman.utilities.file_format_converters.convert_to_java_machine module
class pacman.utilities.file_format_converters.convert_to_java_machine.ConvertToJavaMachine[source]

Bases: object

Converter from memory machine to java machine

static do_convert(machine, file_path, progress=None)[source]

Runs the code to write the machine in Java readable JSON.

Parameters:
  • machine (spinn_machine.machine.Machine) – Machine to convert
  • file_path (str) – Location to write file to. Warning will overwrite!
Module contents
class pacman.utilities.file_format_converters.ConvertToJavaMachine[source]

Bases: object

Converter from memory machine to java machine

static do_convert(machine, file_path, progress=None)[source]

Runs the code to write the machine in Java readable JSON.

Parameters:
  • machine (spinn_machine.machine.Machine) – Machine to convert
  • file_path (str) – Location to write file to. Warning will overwrite!
pacman.utilities.file_format_schemas package
Module contents

A simple bit of support code for validation.

pacman.utilities.file_format_schemas.validate(json_obj, schema_filename)[source]

Check that the given JSON object (or array) is valid against the given schema. The schema is given by filename relative to this package.

Parameters:
  • json_obj (dict or list) – The entity to validate
  • schema_filename (str) – The name of the file containing the schema (e.g., “routes.json”)
Return type:

None
Raises:
  • IOError – If the schema file doesn’t exist.
  • ValidationError – If the JSON object isn’t valid.
pacman.utilities.utility_objs package
Submodules
pacman.utilities.utility_objs.field module
class pacman.utilities.utility_objs.field.Field(lo, hi, value, tag=<SUPPORTED_TAGS.ROUTING: 1>, name=None)[source]

Bases: object

Field object used in a field constraint for key allocation

hi
lo
name
tag
value
pacman.utilities.utility_objs.flexi_field module
class pacman.utilities.utility_objs.flexi_field.FlexiField(flexi_field_name, value=None, instance_n_keys=None, tag=None, nested_level=0)[source]

Bases: object

Field who’s location is not fixed in key allocation

instance_n_keys
name

The name for this Flexible field

tag
value
class pacman.utilities.utility_objs.flexi_field.SUPPORTED_TAGS[source]

Bases: enum.Enum

An enumeration.

APPLICATION = 0
ROUTING = 1
pacman.utilities.utility_objs.resource_tracker module
class pacman.utilities.utility_objs.resource_tracker.ResourceTracker(machine, plan_n_timesteps, chips=None, preallocated_resources=None)[source]

Bases: object

Tracks the usage of resources of a machine.

Parameters:
  • machine (spinn_machine.Machine) – The machine to track the usage of
  • plan_n_timesteps (int) – number of timesteps to plan for
  • chips (iterable(tuple(int, int))) – If specified, this list of chips will be used instead of the list from the machine. Note that the order will be maintained, so this can be used either to reduce the set of chips used, or to re-order the chips. Note also that on deallocation, the order is no longer guaranteed.
allocate_constrained_group_resources(resource_and_constraint_list, chips=None)[source]

Allocates a group of cores on the same chip for these resources

Parameters:
  • resource_and_constraint_list – A list of tuples of (resources, list of constraints) to allocate
  • chips – a list of chips that can be used
Returns:

list of The x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

iterable(tuple(int, int, int, list(tuple(int, int)), list(tuple(int, int))))
allocate_constrained_resources(resources, constraints, chips=None)[source]

Attempts to use the given resources of the machine, constrained by the given placement constraints.

Parameters:
Returns:

The x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

tuple(int, int, int, list(tuple(int, int)), list(tuple(int, int)))
Raises:

PacmanValueError – If the constraints cannot be met given the current allocation of resources
allocate_group_resources(group_resources, chips=None, processor_ids=None, board_address=None, group_ip_tags=None, group_reverse_ip_tags=None)[source]

Attempts to use the given group of resources on a single chip of the machine. Can be given specific place to use the resources, or else it will allocate them on the first place that the resources of the group fit together.

Parameters:
  • group_resources (list(pacman.model.resources.ResourceContainer)) – The resources to be allocated
  • chips (iterable(tuple(int, int))) – An iterable of (x, y) tuples of chips that are to be used
  • processor_ids (list(int or None)) – The specific processor to use on any chip for each resource of the group
  • board_address (str) – the board address to allocate resources of a chip
  • group_ip_tags (list(list(pacman.model.resources.IptagResource))) – list of lists of IP tag resources
  • group_reverse_ip_tags (list(list(pacman.model.resources.ReverseIptagResource))) – list of lists of reverse IP tag resources
Returns:

An iterable of tuples of the x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

iterable(tuple(int, int, int, list(tuple(int, int)), list(tuple(int, int))))
Raises:

pacman.exceptions.PacmanValueError – If there aren’t chips available that can take the allocation.
allocate_resources(resources, chips=None, processor_id=None, board_address=None, ip_tags=None, reverse_ip_tags=None)[source]

Attempts to use the given resources of the machine. Can be given specific place to use the resources, or else it will allocate them on the first place that the resources fit.

Parameters:
  • resources (pacman.model.resources.ResourceContainer) – The resources to be allocated
  • chips (iterable(tuple(int, int))) – An iterable of (x, y) tuples of chips that are to be used
  • processor_id (int) – The specific processor to use on any chip.
  • board_address (str) – the board address to allocate resources of a chip
  • ip_tags (iterable(pacman.model.resources.IptagResource)) – iterable of IP tag resources
  • reverse_ip_tags (iterable(pacman.model.resources.ReverseIPtagResource)) – iterable of reverse IP tag resources
Returns:

The x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

tuple(int, int, int, list(tuple(int, int, int, int)), list(tuple(int, int)))
Raises:

pacman.exceptions.PacmanValueError – If there isn’t a chip available that can take the allocation.
static check_constraints(vertices, additional_placement_constraints=None)[source]

Check that the constraints on the given vertices are supported by the resource tracker

Parameters:
  • vertices – The vertices to check the constraints of
  • additional_placement_constraints – Additional placement constraints supported by the algorithm doing this check
chips_available

The chips currently available

chips_used

The number of chips used in this allocation.

static get_chip_and_core(constraints, chips=None)[source]

Get an assigned chip and core from a set of constraints

Parameters:
  • constraints (iterable(pacman.model.constraints.AbstractConstraint)) – The set of constraints to get the values from. Note that any type of constraint can be in the list but only those relevant will be used
  • chips (iterable(int, int)) – Optional list of tuples of (x, y) coordinates of chips, restricting the allowed chips
Returns:

tuple of a chip x and y coordinates, and processor ID, any of which might be None
Return type:

tuple(int or None, int or None, int or None)
static get_ip_tag_info(resources, constraints)[source]

Get the IP tag resource information

Parameters:
Returns:

A tuple of board address, iterable of IP tag resources and iterable of reverse IP tag resources
Return type:

tuple(str, iterable(pacman.model.resources.IptagResource), iterable(pacman.model.resources.ReverseIPtabResource))
get_maximum_constrained_resources_available(resources, constraints)[source]

Get the maximum resources available given the constraints

Parameters:
get_maximum_cores_available_on_a_chip()[source]

returns the number of available cores of a real chip with the maximum number of available cores

Returns:the max cores available on the best real chip
Return type:int
get_maximum_cores_available_on_a_virtual_chip()[source]

returns the number of available cores of a virtual chip with the maximum number of available cores :return: the max cores available on the best real chip :rtype: int

get_maximum_resources_available(area_code=None)[source]

Get the maximum resources available

Parameters:area_code – A set of valid (x, y) coordinates to choose from
Returns:a resource which shows max resources available
Return type:pacman.model.resources.ResourceContainer
is_chip_available(chip_x, chip_y)[source]

Check if a given chip is available

Parameters:
  • chip_x (int) – the x coord of the chip
  • chip_y (int) – the y coord of the chip
Returns:

True if the chip is available, False otherwise
Return type:

bool
keys

The chip coordinates assigned

sdram_avilable_on_chip(chip_x, chip_y)[source]

Get the available SDRAM on the chip at coordinates chip_x, chip_y

Parameters:
  • chip_x – x coord of the chip in question
  • chip_y – y coord of the chip in question
Returns:

the SDRAM remaining
unallocate_resources(chip_x, chip_y, processor_id, resources, ip_tags, reverse_ip_tags)[source]

Undo the allocation of resources

Parameters:
  • chip_x (int) – the x coord of the chip allocated
  • chip_y (int) – the y coord of the chip allocated
  • processor_id (int) – the processor ID
  • resources (pacman.model.resources.ResourceContainer) – The resources to be unallocated
  • ip_tags (iterable(tuple(str, int)) or None) – the details of the IP tags allocated
  • reverse_ip_tags (iterable(tuple(str, int)) or None) – the details of the reverse IP tags allocated
Return type:

None
Module contents
class pacman.utilities.utility_objs.Field(lo, hi, value, tag=<SUPPORTED_TAGS.ROUTING: 1>, name=None)[source]

Bases: object

Field object used in a field constraint for key allocation

hi
lo
name
tag
value
class pacman.utilities.utility_objs.FlexiField(flexi_field_name, value=None, instance_n_keys=None, tag=None, nested_level=0)[source]

Bases: object

Field who’s location is not fixed in key allocation

instance_n_keys
name

The name for this Flexible field

tag
value
class pacman.utilities.utility_objs.ResourceTracker(machine, plan_n_timesteps, chips=None, preallocated_resources=None)[source]

Bases: object

Tracks the usage of resources of a machine.

Parameters:
  • machine (spinn_machine.Machine) – The machine to track the usage of
  • plan_n_timesteps (int) – number of timesteps to plan for
  • chips (iterable(tuple(int, int))) – If specified, this list of chips will be used instead of the list from the machine. Note that the order will be maintained, so this can be used either to reduce the set of chips used, or to re-order the chips. Note also that on deallocation, the order is no longer guaranteed.
allocate_constrained_group_resources(resource_and_constraint_list, chips=None)[source]

Allocates a group of cores on the same chip for these resources

Parameters:
  • resource_and_constraint_list – A list of tuples of (resources, list of constraints) to allocate
  • chips – a list of chips that can be used
Returns:

list of The x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

iterable(tuple(int, int, int, list(tuple(int, int)), list(tuple(int, int))))
allocate_constrained_resources(resources, constraints, chips=None)[source]

Attempts to use the given resources of the machine, constrained by the given placement constraints.

Parameters:
Returns:

The x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

tuple(int, int, int, list(tuple(int, int)), list(tuple(int, int)))
Raises:

PacmanValueError – If the constraints cannot be met given the current allocation of resources
allocate_group_resources(group_resources, chips=None, processor_ids=None, board_address=None, group_ip_tags=None, group_reverse_ip_tags=None)[source]

Attempts to use the given group of resources on a single chip of the machine. Can be given specific place to use the resources, or else it will allocate them on the first place that the resources of the group fit together.

Parameters:
  • group_resources (list(pacman.model.resources.ResourceContainer)) – The resources to be allocated
  • chips (iterable(tuple(int, int))) – An iterable of (x, y) tuples of chips that are to be used
  • processor_ids (list(int or None)) – The specific processor to use on any chip for each resource of the group
  • board_address (str) – the board address to allocate resources of a chip
  • group_ip_tags (list(list(pacman.model.resources.IptagResource))) – list of lists of IP tag resources
  • group_reverse_ip_tags (list(list(pacman.model.resources.ReverseIptagResource))) – list of lists of reverse IP tag resources
Returns:

An iterable of tuples of the x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

iterable(tuple(int, int, int, list(tuple(int, int)), list(tuple(int, int))))
Raises:

pacman.exceptions.PacmanValueError – If there aren’t chips available that can take the allocation.
allocate_resources(resources, chips=None, processor_id=None, board_address=None, ip_tags=None, reverse_ip_tags=None)[source]

Attempts to use the given resources of the machine. Can be given specific place to use the resources, or else it will allocate them on the first place that the resources fit.

Parameters:
  • resources (pacman.model.resources.ResourceContainer) – The resources to be allocated
  • chips (iterable(tuple(int, int))) – An iterable of (x, y) tuples of chips that are to be used
  • processor_id (int) – The specific processor to use on any chip.
  • board_address (str) – the board address to allocate resources of a chip
  • ip_tags (iterable(pacman.model.resources.IptagResource)) – iterable of IP tag resources
  • reverse_ip_tags (iterable(pacman.model.resources.ReverseIPtagResource)) – iterable of reverse IP tag resources
Returns:

The x and y coordinates of the used chip, the processor_id, and the IP tag and reverse IP tag allocation tuples
Return type:

tuple(int, int, int, list(tuple(int, int, int, int)), list(tuple(int, int)))
Raises:

pacman.exceptions.PacmanValueError – If there isn’t a chip available that can take the allocation.
static check_constraints(vertices, additional_placement_constraints=None)[source]

Check that the constraints on the given vertices are supported by the resource tracker

Parameters:
  • vertices – The vertices to check the constraints of
  • additional_placement_constraints – Additional placement constraints supported by the algorithm doing this check
chips_available

The chips currently available

chips_used

The number of chips used in this allocation.

static get_chip_and_core(constraints, chips=None)[source]

Get an assigned chip and core from a set of constraints

Parameters:
  • constraints (iterable(pacman.model.constraints.AbstractConstraint)) – The set of constraints to get the values from. Note that any type of constraint can be in the list but only those relevant will be used
  • chips (iterable(int, int)) – Optional list of tuples of (x, y) coordinates of chips, restricting the allowed chips
Returns:

tuple of a chip x and y coordinates, and processor ID, any of which might be None
Return type:

tuple(int or None, int or None, int or None)
static get_ip_tag_info(resources, constraints)[source]

Get the IP tag resource information

Parameters:
Returns:

A tuple of board address, iterable of IP tag resources and iterable of reverse IP tag resources
Return type:

tuple(str, iterable(pacman.model.resources.IptagResource), iterable(pacman.model.resources.ReverseIPtabResource))
get_maximum_constrained_resources_available(resources, constraints)[source]

Get the maximum resources available given the constraints

Parameters:
get_maximum_cores_available_on_a_chip()[source]

returns the number of available cores of a real chip with the maximum number of available cores

Returns:the max cores available on the best real chip
Return type:int
get_maximum_cores_available_on_a_virtual_chip()[source]

returns the number of available cores of a virtual chip with the maximum number of available cores :return: the max cores available on the best real chip :rtype: int

get_maximum_resources_available(area_code=None)[source]

Get the maximum resources available

Parameters:area_code – A set of valid (x, y) coordinates to choose from
Returns:a resource which shows max resources available
Return type:pacman.model.resources.ResourceContainer
is_chip_available(chip_x, chip_y)[source]

Check if a given chip is available

Parameters:
  • chip_x (int) – the x coord of the chip
  • chip_y (int) – the y coord of the chip
Returns:

True if the chip is available, False otherwise
Return type:

bool
keys

The chip coordinates assigned

sdram_avilable_on_chip(chip_x, chip_y)[source]

Get the available SDRAM on the chip at coordinates chip_x, chip_y

Parameters:
  • chip_x – x coord of the chip in question
  • chip_y – y coord of the chip in question
Returns:

the SDRAM remaining
unallocate_resources(chip_x, chip_y, processor_id, resources, ip_tags, reverse_ip_tags)[source]

Undo the allocation of resources

Parameters:
  • chip_x (int) – the x coord of the chip allocated
  • chip_y (int) – the y coord of the chip allocated
  • processor_id (int) – the processor ID
  • resources (pacman.model.resources.ResourceContainer) – The resources to be unallocated
  • ip_tags (iterable(tuple(str, int)) or None) – the details of the IP tags allocated
  • reverse_ip_tags (iterable(tuple(str, int)) or None) – the details of the reverse IP tags allocated
Return type:

None
Submodules
pacman.utilities.constants module
class pacman.utilities.constants.EDGES

Bases: enum.Enum

An enumeration.

EAST = 0
NORTH = 2
NORTH_EAST = 1
SOUTH = 5
SOUTH_WEST = 4
WEST = 3
pacman.utilities.json_utils module
pacman.utilities.json_utils.constraint_from_json(json_dict, graph=None)[source]
pacman.utilities.json_utils.constraint_to_json(constraint)[source]

Converts a constraint to JSON.

Note: Vertexes are represented by just their label.

Note: If an unexpected constraint is received, the str() and repr() values are saved

If an Exception occurs, that is caught and added to the JSON object.

Parameters:constraint – The constraint to describe
Returns:A dict describing the constraint
pacman.utilities.json_utils.constraints_from_json(json_list, graph)[source]
pacman.utilities.json_utils.constraints_to_json(constraints)[source]
pacman.utilities.json_utils.edge_from_json(json_dict, graph=None)[source]
pacman.utilities.json_utils.edge_to_json(edge)[source]
pacman.utilities.json_utils.graph_from_json(json_dict)[source]
pacman.utilities.json_utils.graph_to_json(graph)[source]
pacman.utilities.json_utils.iptag_resource_from_json(json_dict)[source]
pacman.utilities.json_utils.iptag_resource_to_json(iptag)[source]
pacman.utilities.json_utils.iptag_resources_from_json(json_list)[source]
pacman.utilities.json_utils.iptag_resources_to_json(iptags)[source]
pacman.utilities.json_utils.json_to_object(json_object)[source]

Makes sure this is a JSON object reading in a file if required

Parameters:json_object – Either a JSON Object or a string pointing to a file
Returns:a JSON object
pacman.utilities.json_utils.key_mask_from_json(json_dict)[source]
pacman.utilities.json_utils.key_mask_to_json(key_mask)[source]
pacman.utilities.json_utils.key_masks_from_json(json_list)[source]
pacman.utilities.json_utils.key_masks_to_json(key_masks)[source]
pacman.utilities.json_utils.resource_container_from_json(json_dict)[source]
pacman.utilities.json_utils.resource_container_to_json(container)[source]
pacman.utilities.json_utils.vertex_add_contstraints_from_json(json_dict, graph)[source]
pacman.utilities.json_utils.vertex_from_json(json_dict, convert_constraints=True)[source]
pacman.utilities.json_utils.vertex_lookup(label, graph=None)[source]
pacman.utilities.json_utils.vertex_to_json(vertex)[source]
pacman.utilities.utility_calls module
pacman.utilities.utility_calls.check_algorithm_can_support_constraints(constrained_vertices, supported_constraints, abstract_constraint_type)[source]

Helper method to find out if an algorithm can support all the constraints given the objects its expected to work on

Parameters:
Returns:

Nothing is returned
Return type:

None
Raises:

pacman.exceptions.PacmanInvalidParameterException – When the algorithm cannot support the constraints demanded of it
pacman.utilities.utility_calls.check_constrained_value(value, current_value)[source]

Checks that the current value and a new value match

Parameters:
  • value – The value to check
  • current_value – The existing value
pacman.utilities.utility_calls.compress_bits_from_bit_array(bit_array, bit_positions)[source]

Compress specific positions from a bit array of 32 uint8 value, where is a 1 or 0, into a 32-bit value.

Parameters:
  • bit_array (numpy.array(uint8)) – The array to extract the value from
  • bit_positions (numpy.array(int)) – The positions of the bits to extract, each value being between 0 and 31
Return type:

int
pacman.utilities.utility_calls.compress_from_bit_array(bit_array)[source]

Compress a bit array of 32 uint8 values, where each is a 1 or 0, into a 32-bit value

Parameters:bit_array (numpy.array(uint8)) – The array to compress
Return type:int
pacman.utilities.utility_calls.expand_to_bit_array(value)[source]

Expand a 32-bit value in to an array of length 32 of uint8 values, each of which is a 1 or 0

Parameters:value (int) – The value to expand
Return type:numpy.array(uint8)
pacman.utilities.utility_calls.ident(object)[source]

Get the ID of the given object.

Return type:str
pacman.utilities.utility_calls.is_equal_or_None(a, b)[source]

If a and b are both not None, return True iff they are equal, otherwise return True

pacman.utilities.utility_calls.is_single(iterable)[source]

Test if there is exactly one item in the iterable

pacman.utilities.utility_calls.locate_constraints_of_type(constraints, constraint_type)[source]

Locates all constraints of a given type out of a list

Parameters:
  • constraints (iterable(pacman.model.constraints.AbstractConstraint)) – The constraints to filter
  • constraint_type (pacman.model.constraints.partitioner_constraints.AbstractPartitionConstraint) – The type of constraints to return
Returns:

The constraints of constraint_type that are found in the constraints given
Return type:

iterable(pacman.model.constraints.AbstractConstraint)
Raises:

None – no known exceptions
pacman.utilities.utility_calls.locate_first_constraint_of_type(constraints, constraint_type)[source]

Locates the first constraint of a given type out of a list

Parameters:
  • constraints (iterable(pacman.model.constraints.AbstractConstraint)) – The constraints to select from
  • constraint_type (pacman.model.constraints.partitioner_constraints.AbstractPartitionConstraint) – The type of constraints to return
Returns:

The first constraint of constraint_type that was found in the constraints given
Return type:

pacman.model.constraints.AbstractConstraint
Raises:

pacman.exceptions.PacmanInvalidParameterException – If no such constraint is present
pacman.utilities.utility_calls.md5(string)[source]

Get the MD5 hash of the given string, which is UTF-8 encoded.

Return type:str
pacman.utilities.vertex_sorter module
class pacman.utilities.vertex_sorter.ConstraintOrder(constraint_class, relative_order, required_optional_properties=None)[source]

Bases: object

A constraint order definition for sorting.

Parameters:
  • constraint_class – The class of the constraint
  • relative_order – The order of the constraint relative to other constraints to be sorted
  • required_optional_properties – Properties of the constraint instances that must not be None for the constraint to match this ordering
constraint_class

property method for the constraint class

relative_order

property method for the relative order

required_optional_properties

property method for the required optional properties

class pacman.utilities.vertex_sorter.VertexSorter(constraint_order)[source]

Bases: object

Sorts vertices based on constraints with given criteria.

Parameters:constraint_order (list(ConstraintOrder)) – The order in which the constraints are to be sorted
sort(vertices)[source]

Sort the given set of vertices by the constraint ordering

Parameters:vertices – The vertices to sort
Returns:The sorted list of vertices
Module contents
class pacman.utilities.ConstraintOrder(constraint_class, relative_order, required_optional_properties=None)[source]

Bases: object

A constraint order definition for sorting.

Parameters:
  • constraint_class – The class of the constraint
  • relative_order – The order of the constraint relative to other constraints to be sorted
  • required_optional_properties – Properties of the constraint instances that must not be None for the constraint to match this ordering
constraint_class

property method for the constraint class

relative_order

property method for the relative order

required_optional_properties

property method for the required optional properties

class pacman.utilities.VertexSorter(constraint_order)[source]

Bases: object

Sorts vertices based on constraints with given criteria.

Parameters:constraint_order (list(ConstraintOrder)) – The order in which the constraints are to be sorted
sort(vertices)[source]

Sort the given set of vertices by the constraint ordering

Parameters:vertices – The vertices to sort
Returns:The sorted list of vertices

Submodules

pacman.exceptions module

exception pacman.exceptions.MachineHasDisconnectedSubRegion[source]

Bases: pacman.exceptions.PacmanException

Some part of the machine has no paths connecting it to the rest of the machine.

exception pacman.exceptions.MinimisationFailedError(target_length, final_length=None, chip=None)[source]

Bases: pacman.exceptions.PacmanException

Raised when a routing table could not be minimised to reach a specified target.

Parameters:
  • target_length (int) – The target number of routing entries.
  • final_length (int or None) – The number of routing entries reached when the algorithm completed. (final_length > target_length)
  • chip (tuple(int, int) or None) – The coordinates of the chip on which routing table minimisation first failed. Only set when minimisation is performed across many chips simultaneously.
exception pacman.exceptions.PacmanAlgorithmFailedToCompleteException(algorithm, exception, tb)[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that a pacman algorithm ran from inside the software stack has failed to complete for some unknown reason.

exception pacman.exceptions.PacmanAlgorithmFailedToGenerateOutputsException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that an algorithm has not generated the correct outputs for some unknown reason.

exception pacman.exceptions.PacmanAlreadyExistsException(item_type, item_id)[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something already exists and that adding another would be a conflict.

Parameters:
  • item_type (str) – The type of the item that already exists
  • item_id (str) – The ID of the item which is in conflict
exception pacman.exceptions.PacmanAlreadyPlacedError[source]

Bases: ValueError

An exception that indicates multiple placements are being made for a vertex.

exception pacman.exceptions.PacmanCanNotFindChipException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates the chip was not in the list of chips.

exception pacman.exceptions.PacmanConfigurationException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something went wrong with configuring some part of PACMAN.

exception pacman.exceptions.PacmanElementAllocationException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something went wrong with element allocation.

exception pacman.exceptions.PacmanException[source]

Bases: Exception

Indicates a general exception from Pacman

exception pacman.exceptions.PacmanExternalAlgorithmFailedToCompleteException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that an algorithm ran from outside the software stack has failed to complete for some unknown reason.

exception pacman.exceptions.PacmanInvalidParameterException(parameter, value, problem)[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that a parameter has an invalid value.

Parameters:
  • parameter (str) – The name of the parameter
  • value (str) – The value of the parameter
  • problem (str) – The problem with the value of the parameter
exception pacman.exceptions.PacmanNoMergeException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates to indicate that there are no merges worth performing.

exception pacman.exceptions.PacmanNotExistException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that a routing table entry was attempted to be removed from a routing table which didn’t have such an entry.

exception pacman.exceptions.PacmanNotFoundError[source]

Bases: KeyError, pacman.exceptions.PacmanException

An exception that indicates that some object has not been found when requested.

exception pacman.exceptions.PacmanNotPlacedError[source]

Bases: KeyError

An exception that indicates no placements are made for a vertex.

exception pacman.exceptions.PacmanPartitionException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something went wrong with partitioning

exception pacman.exceptions.PacmanPlaceException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something went wrong with placement

exception pacman.exceptions.PacmanProcessorAlreadyOccupiedError[source]

Bases: ValueError

An exception that indicates multiple placements are being made to a processor.

exception pacman.exceptions.PacmanProcessorNotAvailableError(x, y, p)[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that a processor is unavailable for some reason.

exception pacman.exceptions.PacmanProcessorNotOccupiedError[source]

Bases: KeyError

An exception that indicates that no placement has been made to a processor.

exception pacman.exceptions.PacmanPruneException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something went wrong with pruning

exception pacman.exceptions.PacmanRouteInfoAllocationException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something went wrong with route info allocation.

exception pacman.exceptions.PacmanRoutingException[source]

Bases: pacman.exceptions.PacmanException

An exception that indicates that something went wrong with routing.

exception pacman.exceptions.PacmanTypeError[source]

Bases: TypeError, pacman.exceptions.PacmanException

An exception that indicates that an object is of incorrect type.

exception pacman.exceptions.PacmanValueError[source]

Bases: ValueError, pacman.exceptions.PacmanException

An exception that indicates that a value is invalid for some reason.

Module contents

Provides various functions which together can be used to take a graph and split it into pieces that can be loaded on to a machine, along with routes between the pieces.

Functional Requirements

  • Creation of an Application Graph of Vertices indicating points of computation within the graph and Edges between the vertices indicating a directional communication between the vertices; and a similar Machine Graph.

    • Vertices in the Application Graph will have a number of atoms - an atom cannot be broken down in to anything smaller.

    • Vertices in the Application Graph must be able to indicate what machine resources are required by any given subset of the atoms.

    • Vertices in the Machine Graph must be able to fit on a single chip of the machine in terms of resource usage.

    • A Vertex can have a number of constraints which must be respected by any algorithm which uses the graph. Algorithms must check that they can support the given constraints and must fail if they cannot. Provided constraints include support for:

      • The maximum number of atoms which any Machine Graph Vertex can contain for a given Application Graph vertex
      • The chip and/or processor on to which a Machine Graph Vertex should be placed.
      • A set of Application Graph Vertices whose corresponding Machine Graph vertices should contain the same number of atoms.
      • A set of Application Graph Vertices whose corresponding Machine Graph vertices should be placed on the same chip if they contain the same atom.

    • It should be possible to create new constraints as the need arises.

    • Multiple edges can exist between the same two vertices.

    • It must be possible to build the Machine Graph directly without requiring that it is created by one of the other modules.

    • It is not required that there is a Machine Graph Edge between every pair of Machine Graph Vertex from the same Application Graph Vertex.

    • Where a Machine Graph is created from an Application Graph, it should be possible to find the corresponding Vertices and Edges from one graph to the other.

  • Creation of multicast routing info consisting of key/mask combinations assigned to Edges of the Machine Graph.

    • It must be possible to build this information directly without requiring that it is created by one of the other modules.
    • There should be exactly one key/mask combination for each Edge in the Machine Graph, which will represent all the keys which will be sent in all packets from the Vertex at the start of the Edge down that Edge.
    • It is possible for a Vertex to send several different keys down several different Edges, but only one per Edge (but note that it is acceptable for different keys to be assigned to different Edges between the same two Vertices).
    • There should be no overlap between the key/mask combinations of Edges which come from different Vertices i.e. no two Edges which start at different Vertices should have the same key/mask combination.

  • Partitioning of an Application graph with respect to a machine, such that the resources consumed by each Vertex does not exceed those provided by each chip on the machine.

    • It should be possible to select from a range of partitioning algorithms or provide one, although a default should be provided in the absence of such a choice .
    • Any partitioning constraints should be met; if there are any that cannot, or that are not understood by the algorithm in use an exception should be thrown. Non-partitioning constraints can be ignored, although these can be used if it makes sense for the given algorithm.
    • It must be possible to create at least one grouping of the generated Vertices so that each group fits within the resources provided by a single chip on the machine.
    • It should not be assumed that a given grouping of Vertices will be the final grouping on the machine, although it is acceptable to make hints through additional constraints about what is likely to work.
    • The machine itself must not be altered by the partitioning, so that it can be used in further processing.
    • The graph itself must not be altered by the partitioning, so that it can be used in further processing.
    • No two Machine Graph Vertices created from a single Application Graph Vertex can contain the same atom.
    • Any Edges in the Application Graph must be split with the Vertices to create a number of Machine Graph edges, such that where there was a vertex v connected to a vertex w by a single edge in the Application Graph, there should be an Edge in the Machine Graph between every Vertex of Application Graph Vertex v and every Vertex of Application Graph Vertex w; for example, if there are 2 Machine Graph Vertices for each of v and w, and one Edge between them in the Application Graph, then there will be 4 new Edges in the Machine Graph for this Edge.

  • Placement of a Machine Graph on a given machine, such that the resources required by any combination of Vertices placed on any chip in the machine does not exceed the resources provided by that chip.

    • It should be possible to choose from a range of placement algorithms or provide one, although a default should be provided in the absence of such a choice.
    • Any placement constraints should be met; if there are any that cannot, or that are not understood by placement algorithm, an exception should be thrown. Non-placement constraints can be ignored, although these can be used if it makes sense for the given algorithm.
    • The machine itself should not be altered by placement so that it can be used in further processing.
    • The graph itself should not be altered by placement so that it can be used in further processing.
    • The returned placements should only contain a single placement for each vertex.
    • The placements should be such that the vertices with edges between them must be able to communicate with each other.

  • Allocation of multicast routing keys and masks to a Machine Graph such that each vertex sends out packets with a different key/mask combination.

    • This can use the placement information if required. If an algorithm requires placement information but none is provided an exception is thrown.

  • Routing of edges between vertices with a given allocation of routing keys and masks with respect to a given machine.

    • It should be possible to choose from a range of routing algorithms, or provide one, although a default should be provided in the absence of such a choice
    • For any vertex, following the routes from the placement of the vertex should result exactly in the set of placements of the destination vertices described by all the edges which start at that vertex. No additional destination should be reached, and no fewer than this set of destinations should be reached.

  • It should be possible to call each of the modules independently. There should be no assumption that one of the other modules has produced the data input for any other module.

  • There should be no assumption about how the inputs and outputs are stored.

  • Any utility functions that provide access to internal structures within a data structure should operate in approximately O(1) time; for example, where an object of type obj holds a number of objects of type subobj with property prop, requesting a list of subobj objects contained within obj with property value prop = value should not iterate through a list of such objects, but should instead maintain a mapping that allows access to such objects in O(1) time. If this is not possible, obj should only provide access to a list of subobj objects, allowing the caller to filter these themselves. This will ensure that no misunderstanding can be made about the speed of operation of a function.

Indices and tables