spinnaker-pacman
Partition and Configuration Manager for SpiNNaker
Science Score: 54.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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✓Committers with academic emails
8 of 18 committers (44.4%) from academic institutions -
○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (16.9%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Partition and Configuration Manager for SpiNNaker
Basic Info
Statistics
- Stars: 9
- Watchers: 17
- Forks: 7
- Open Issues: 15
- Releases: 5
Topics
Metadata Files
README.md
This package provides utilities for partitioning, placing a routing on a SpiNNaker machine
Requirements
In addition to a standard Python installation, this package depends on:
- SpiNNMachine
These requirements can be install using pip:
pip install SpiNNMachine
User Installation
If you want to install for all users, run:
sudo pip install PACMAN
If you want to install only for yourself, run:
pip install PACMAN --user
To install in a virtualenv, with the virtualenv enabled, run:
pip install PACMAN
Using a virtual environment is recommended for all SpiNNaker software.
Developer Installation
If you want to be able to edit the source code, but still have it referenced from other Python modules, you can set the install to be a developer install. In this case, download the source code, and extract it locally, or else clone the git repository:
git clone http://github.com/SpiNNakerManchester/PACMAN.git
To install as a development version which all users will then be able to use, run the following where the code has been extracted:
sudo pip install -e .
To install as a development version for only yourself, run:
pip install -e . --user
To install as a development version in a virtualenv, with the virutalenv
enabled, run:
pip install -e .
Test Installation
To be able to run the unitests add [Test] to the pip installs above
pip install -e .[Test]
Documentation
PACMAN python documentation
Combined python documentation
PACMAN Executor
PACMAN contains a simple workflow execution system which allows the user to specify a set of available algorithms which, when provided with a set of inputs can produce a set of outputs. The executor will then work out the order in which the algorithms should be run (and indeed if the algorithms can be run) by looking at the inputs required and outputs generated by each algorithm.
As well as parameters required by the algorithms, the workflow system additionally supports the concept of "tokens". A token can be used to represent the action of an algorithm that does not produce a specific output. For example, on a SpiNNaker machine, this might include the loading of data or the loading of application binaries, neither of which produces a Python object as output, but performs and important task in any case. Each token can also be specified to be "part" of a whole task. This allows an algorithm to declare that it has done part of a task, and have a future algorithm require that all of the task has been completed without knowing what parts need to be done. Again, the example of loading of data can be used here where there may be several algorithms that can load data in different ways but all the data must be loaded before the application binaries are loaded; however the application binary loader can just say that all data loading is done before execution, avoiding the need to modify the algorithm in the event that a new algorithm is created.
The arguments of the algorithms that can be represented as Python objects are specified using semantic types. These are simply represented as strings; the values of the strings are only important in that they must match between the inputs and outputs of algorithms in the flow for an algorithm to be recognised as producing an output that another algorithm can use as an input.
Each algorithm to be run by this executor specifies: - The required inputs of the algorithm. This can include both arguments of the algorithm and tokens required. - The optional inputs of the algorithm, again including both arguments and tokens. - The outputs generated by the algorithm, both as semantic types and tokens.
The executor is provided with: - A list of algorithms that must be executed. If it is not possible to execute these, an error is raised. These will be executed regardless of if the output of the algorithm is already available. - A list of algorithms that can be executed optionally to produce an output. If one of these algorithms generates an input type or a partial or complete token that is an optional input to a required algorithm, and no other required algorithm can generate this input, the optional algorithm will be run before that required algorithm. An optional algorithm will not be run if it doesn't generate an output which is an input for another algorithm which isn't already provided in some other way. - A list of inputs to seed the workflow with. This can be used to provide initial inputs to the workflow, or to stop an optional algorithm from executing by providing in advance the output that the algorithm generates. - A list of input tokens to seed the workflow with. These can only be specified as complete tokens which are provided. Partial tokens cannot currently be provided. - A list of required outputs that the workflow must generate. In addition to the list of algorithms to run, these outputs must be generated by the workflow at some stage, or else an error is raised. - A list of required output tokens that the workflow must generate. As with the outputs these must be generated by the workflow at some stage or else an error is raised.
Owner
- Name: SpiNNaker - University of Manchester
- Login: SpiNNakerManchester
- Kind: organization
- Email: spinnakerusers@googlegroups.com
- Location: Manchester, UK
- Website: http://spinnakermanchester.github.io/
- Repositories: 78
- Profile: https://github.com/SpiNNakerManchester
Software for the SpiNNaker Million Core Neuromorphic Machine. Part of the Human Brain Project and EBRAINS
Citation (CITATION.cff)
# Copyright (c) 2017 The University of Manchester
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
cff-version: 1.2.0
message: If you use this software, please cite it as below.
preferred-citation:
type: article
doi: 10.3389/fnins.2019.00231
issn: 1662-453X
url: https://www.frontiersin.org/articles/10.3389/fnins.2019.00231
title: "SpiNNTools: The Execution Engine for the SpiNNaker Platform"
journal: Frontiers in Neuroscience
volume: 13
year: 2019
month: 3
abstract: SpiNNaker is a massively parallel distributed architecture primarily focused on real time simulation of spiking neural networks. The largest realization of the architecture consists of one million general purpose processors, making it the largest neuromorphic computing platform in the world at the present time. Utilizing these processors efficiently requires expert knowledge of the architecture to generate executable code and to harness the potential of the unique inter-processor communications infra-structure that lies at the heart of the SpiNNaker architecture. This work introduces a software suite called SpiNNTools that can map a computational problem described as a graph into the required set of executables, application data and routing information necessary for simulation on this novel machine. The SpiNNaker architecture is highly scalable, giving rise to unique challenges in mapping the problem to the machines resources, loading the generated files to the machine and subsequently retrieving the results of simulation. In this paper we describe these challenges in detail and the solutions implemented.
authors:
- given-names: Andrew
family-names: Rowley
affiliation: University Of Manchester
email: Andrew.Rowley@manchester.ac.uk
orcid: https://orcid.org/0000-0002-2646-8520
website: https://www.researchgate.net/profile/Andrew_Rowley2
- given-names: Christian Y.
family-names: Brenninkmeijer
affiliation: University Of Manchester
email: christian.brenninkmeijer@manchester.ac.uk
orcid: https://orcid.org/0000-0002-2937-7819
website: https://www.researchgate.net/profile/Christian_Brenninkmeijer
- given-names: Simon
family-names: Davidson
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0001-5385-442X
website: https://research.manchester.ac.uk/en/persons/simon.davidson
- given-names: Donal
family-names: Fellows
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0002-9091-5938
website: https://www.researchgate.net/profile/Donal-Fellows
- given-names: Andrew
family-names: Gait
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0001-9349-1096
website: https://personalpages.manchester.ac.uk/staff/andrew.gait/
- given-names: David R.
family-names: Lester
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0002-7267-291X
- given-names: Luis A.
family-names: Plana
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0002-6113-3929
website: https://research.manchester.ac.uk/en/persons/luis.plana
- given-names: Oliver
family-names: Rhodes
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0003-1728-2828
website: https://research.manchester.ac.uk/en/persons/oliver.rhodes
- given-names: Alan B.
family-names: Stokes
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0002-6110-1484
- given-names: Steve B.
family-names: Furber
affiliation: University Of Manchester
orcid: https://orcid.org/0000-0002-6524-3367
website: https://research.manchester.ac.uk/en/persons/steve.furber
title: The Mapping algorthims from a graph to SpiNNaker machine data structures and
work flow manager for executing said algorithms
authors:
- name: SpiNNaker Software Team
alias: For a list of contributors see https://github.com/SpiNNakerManchester/PACMAN/graphs/contributors or for a combined list see https://spinnakermanchester.github.io/latest/LicenseAgreement.html#contributors
address: University of Manchester, Oxford Road
city: Manchester
country: GB
email: spinnakerusers@googlegroups.com
post-code: M13 9PL
website: https://apt.cs.manchester.ac.uk/projects/SpiNNaker/
url: https://spinnakermanchester.github.io/
contact:
- address: University of Manchester, Oxford Road
city: Manchester
country: GB
email: spinnakerusers@googlegroups.com
name: SpiNNaker Software Team
post-code: M13 9PL
license: Apache-2.0
repository: https://github.com/SpiNNakerManchester/PACMAN
GitHub Events
Total
- Issues event: 4
- Watch event: 1
- Delete event: 26
- Issue comment event: 5
- Push event: 91
- Pull request review comment event: 2
- Pull request review event: 7
- Pull request event: 46
- Create event: 28
Last Year
- Issues event: 4
- Watch event: 1
- Delete event: 26
- Issue comment event: 5
- Push event: 91
- Pull request review comment event: 2
- Pull request review event: 7
- Pull request event: 46
- Create event: 28
Committers
Last synced: almost 3 years ago
All Time
- Total Commits: 3,226
- Total Committers: 18
- Avg Commits per committer: 179.222
- Development Distribution Score (DDS): 0.645
Top Committers
| Name | Commits | |
|---|---|---|
| Christian Y. Brenninkmeijer | c****r@m****k | 1,144 |
| alan-stokes | a****s@g****m | 765 |
| Andrew Rowley | A****y@m****k | 685 |
| Donal Fellows | d****s@m****k | 321 |
| Petrut Antoniu Bogdan | p****8@g****m | 106 |
| sara | s****a@g****m | 72 |
| Christian | b****c@c****k | 62 |
| Andrew Gait | a****t@m****k | 26 |
| sergiodavies | d****s@c****k | 11 |
| Andrew Mundy | a****y@i****g | 11 |
| zzalsar4 | z****4@z****4 | 7 |
| daviess | s****s@g****m | 6 |
| Gary | c****n@g****m | 3 |
| SpiNNaker | S****r@1****3 | 2 |
| Christoph Richter | p****h@g****m | 2 |
| Petrut Antoniu Bogdan | p****n@p****k | 1 |
| Arthur | g****a@g****m | 1 |
| Christian Y. Brenninkmeijer | C****B@u****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 46
- Total pull requests: 164
- Average time to close issues: about 2 years
- Average time to close pull requests: 3 months
- Total issue authors: 5
- Total pull request authors: 9
- Average comments per issue: 2.22
- Average comments per pull request: 0.69
- Merged pull requests: 126
- Bot issues: 0
- Bot pull requests: 2
Past Year
- Issues: 2
- Pull requests: 34
- Average time to close issues: 1 day
- Average time to close pull requests: 6 days
- Issue authors: 1
- Pull request authors: 2
- Average comments per issue: 0.0
- Average comments per pull request: 0.09
- Merged pull requests: 24
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Christian-B (33)
- rowleya (8)
- alan-stokes (2)
- dkfellows (2)
- pabogdan (1)
Pull Request Authors
- Christian-B (161)
- rowleya (24)
- dkfellows (12)
- alan-stokes (3)
- andrewgait (2)
- dependabot[bot] (2)
- jofas (1)
- Sakuyui (1)
- lucaperes (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 136 last-month
- Total dependent packages: 0
- Total dependent repositories: 1
- Total versions: 27
- Total maintainers: 5
pypi.org: spinnaker-pacman
Partition and Configuration Manager
- Homepage: https://github.com/SpiNNakerManchester/PACMAN
- Documentation: https://spinnaker-pacman.readthedocs.io/
- License: Apache-2.0
-
Latest release: 3.0.1
published over 9 years ago
Rankings
Maintainers (5)
Dependencies
- coverage >=4.4,<5.0
- flake8 *
- pylint *
- pytest-cov *
- sphinx >=4
- testfixtures *
- SpiNNMachine ==1
- SpiNNUtilities ==1
- jsonschema *
- jsonschema <4.4
- sortedcollections *
- SpiNNMachine *
- SpiNNUtilities *
- jsonschema *
- sortedcollections *
- ./support/actions/check-copyrights * composite
- ./support/actions/checkout-spinn-deps * composite
- ./support/actions/pylint * composite
- ./support/actions/pytest * composite
- ./support/actions/python-tools * composite
- ./support/actions/run-setup * composite
- ./support/actions/sphinx * composite
- actions/checkout v3 composite
- actions/setup-python v4 composite