The version described here is no longer supported.
The SpiNNakerGraphFrontEnd is a interface to the SpiNNaker software stack that is designed with the intention of allowing developers / users to build applications that run on SpiNNaker machines without having to worry about the low level support of:
- Booting/powering on the SpiNNaker machine.
- Mapping the application onto the SpiNNaker machine.
- Loading the application onto the SpiNNaker machine.
- Buffering data in/out from/to to the SpiNNaker machine during an application run.
- Reducing the ethernet bandwidth.
- Verifying that the application is running on the SpiNNaker machine.
- Implementing a interface for interacting with the SpiNNaker machine.
- Acquiring Provenance data from the SpiNNaker machine after an application run.
- Acquiring debug data from the SpiNNaker machine after / during an application run.
- Shutting down the SpiNNaker machine correctly after an application run.
How the SpiNNakerGraphFrontEnd supports the developer/user
The SpiNNakerGraphFrontEnd allows a developer / user to write applications by representing the problem as a graph, where the nodes in the graph represent a collection of computation and edges represent communication between these computations.
The developer should read the SpiNNakerGraphFrontEnd new application tutorial to learn how to exploit the software stack to it’s most potential. A summary is that a developer needs to develop both a python and c representation of any computation nodes (vertices) and often just a python version for any unique communication requirements.
SpiNNakerGraphFrontEnd interface
The SpiNNakerGraphFrontEnd supports the following interface for developers to use.
| Name | Definition |
|---|---|
| setup() | This is the first call that needs to be executed at all times. It sets up all the basic data structures the software stack requires |
| add_partitionable_vertex() | This adds a vertex that can be split over multiple computational nodes |
| add_partitioned_vertex() | This adds a vertex that can only reside on one computational node |
| add_partitionable_edge() | This adds a edge between vertices that can be split over multiple computational nodes |
| add_partitioned_edge() | This adds a edge between vertices that can only reside on individual computational nodes |
| read_partitionable_graph_xml_file() | This function supports reading in a graph, represented in XML, containing vertices which can be split over multiple computational nodes |
| read_partitioned_graph_xml_file() | This function supports reading in a graph, represented in XML, containing vertices which can only reside on individual computational nodes |
| get_machine_dimensions() | This function supports inquiring the SpiNNaker machine and being given the dimensions of the machine |
| machine() | This function returns the python representation of the SpiNNaker machine |
| transceiver() | This function returns the python communication interface to the SpiNNaker machine |
| run() | This function executes: mapping, loading, running, extraction of provenance and debug data on the SpiNNaker machine |
| stop() | This function shuts down the SpiNNaker machine cleanly |
To be extended in the future.