nir

Neuromorphic Intermediate Representation reference implementation

https://github.com/neuromorphs/nir

Science Score: 59.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
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DOI references
Found 4 DOI reference(s) in README
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Links to: nature.com, zenodo.org
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4 of 16 committers (25.0%) from academic institutions
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Scientific vocabulary similarity
Low similarity (11.4%) to scientific vocabulary

Keywords

machine-learning neuromorphic

Last synced: 6 months ago · JSON representation

Repository

Neuromorphic Intermediate Representation reference implementation

Basic Info

Host: GitHub
Owner: neuromorphs
License: bsd-3-clause
Language: Jupyter Notebook
Default Branch: main
Homepage: https://neuroir.org/docs
Size: 33.9 MB

Statistics

Stars: 125
Watchers: 12
Forks: 28
Open Issues: 22
Releases: 14

Topics

machine-learning neuromorphic

Created over 2 years ago · Last pushed 7 months ago

Metadata Files

Readme License Citation

NIR - Neuromorphic Intermediate Representation

NIR is a set of computational primitives, shared across different neuromorphic frameworks and technology stacks. NIR is currently supported by 8 simulators and 5 hardware platforms, allowing users to seamlessly move between any of these platforms.

NIR is useful when you want to move a model from one platform to another, for instance from a simulator to a hardware platform.

Read more about NIR in our documentation about NIR primitives

See which frameworks are currently supported by NIR.

Usage

Read more in our documentation about NIR usage and see more examples in our examples section

NIR serves as a format between neuromorphic platforms and will be installed alongside your framework of choice. Using NIR is typically a part of your favorite framework's workflow, but follows the same pattern when you want to move from a source to a target platform:

```python

Define a model

my_model = ...

Save the model (source platform)

nir.write("mygraph.nir", mymodel)

Load the model (target platform)

importedgraph = nir.read("mygraph.nir") ```

See our example section for how to use NIR with your favorite framework.

Frameworks that currently support NIR

Read more in our documentation about NIR support

| Framework | Write to NIR | Read from NIR | Examples | | --------------- | :--: | :--: | :------: | | jaxsnn (BrainScaleS-2) | | | jaxsnn examples | | Lava-DL | | | Lava/Loihi examples | | Nengo | | | Nengo examples | | Norse | | | Norse examples | | Rockpool (SynSense Xylo chip) | | | Rockpool/Xylo examples | Sinabs (SynSense Speck chip) | | | Sinabs/Speck examples | | snnTorch | | | snnTorch examples | | SpiNNaker2 | | | SpiNNaker2 examples | | Spyx | | | Spyx examples

Acknowledgements

This work was originally conceived at the Telluride Neuromorphic Workshop 2023 by the authors below (in alphabetical order): * Steven Abreu * Felix Bauer * Jason Eshraghian * Matthias Jobst * Gregor Lenz * Jens Egholm Pedersen * Sadique Sheik * Peng Zhou

If you use NIR in your work, please cite the following paper

article{NIR2024, title={Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing}, author={Pedersen, Jens E. and Abreu, Steven and Jobst, Matthias and Lenz, Gregor and Fra, Vittorio and Bauer, Felix Christian and Muir, Dylan Richard and Zhou, Peng and Vogginger, Bernhard and Heckel, Kade and Urgese, Gianvito and Shankar, Sadasivan and Stewart, Terrence C. and Sheik, Sadique and Eshraghian, Jason K.}, rights={2024 The Author(s)}, DOI={10.1038/s41467-024-52259-9}, number={1}, journal={Nature Communications}, volume={15}, year={2024}, month=sep, pages={8122}, }

Owner

Name: Institute of Neuromorphic Engineering
Login: neuromorphs
Kind: organization

Repositories: 9
Profile: https://github.com/neuromorphs

GitHub Events

Total

Create event: 12
Release event: 2
Issues event: 12
Watch event: 40
Delete event: 7
Issue comment event: 68
Member event: 3
Push event: 32
Pull request review comment event: 9
Pull request review event: 14
Pull request event: 43
Fork event: 16

Last Year

Create event: 12
Release event: 2
Issues event: 12
Watch event: 40
Delete event: 7
Issue comment event: 68
Member event: 3
Push event: 32
Pull request review comment event: 9
Pull request review event: 14
Pull request event: 43
Fork event: 16

Committers

Last synced: about 1 year ago

All Time

Total Commits: 209
Total Committers: 16
Avg Commits per committer: 13.063
Development Distribution Score (DDS): 0.67

Past Year

Commits: 76
Committers: 11
Avg Commits per committer: 6.909
Development Distribution Score (DDS): 0.487

Top Committers

Name	Email	Commits
Steve Abreu	s**u@r**l	69
jegp	j**s@j**k	65
Matthias Jobst	m**2@t**e	25
Sadique Sheik	s**k@s**i	11
VitF	v**a@p**t	8
Gregor Lenz	m**l@l**m	7
Peng Zhou	z**n@g**m	5
Jason Eshraghian	4****n	4
Kade Heckel	5****l	4
Bernhard Vogginger	b**r@t**e	3
Felix Bauer	f**r@s**i	3
Connor Hanley	1****1	1
Ben Kroehs	1****s	1
Alex Fan	f**9@g**m	1
Nogay Kuepelioglu	n**u@s**i	1
Bernhard Vogginger	B**r@t**e	1

Committer Domains (Top 20 + Academic)

synsense.ai: 3 tu-dresden.de: 3 lenzgregor.com: 1 polito.it: 1 jepedersen.dk: 1 rug.nl: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 49
Total pull requests: 129
Average time to close issues: 3 months
Average time to close pull requests: 15 days
Total issue authors: 16
Total pull request authors: 20
Average comments per issue: 2.04
Average comments per pull request: 1.47
Merged pull requests: 101
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 15
Pull requests: 52
Average time to close issues: 19 days
Average time to close pull requests: 9 days
Issue authors: 8
Pull request authors: 11
Average comments per issue: 0.87
Average comments per pull request: 1.25
Merged pull requests: 36
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

Jegp (14)
matjobst (11)
sheiksadique (5)
benkroehs (3)
rowleya (3)
fabio-innatera (2)
stevenabreu7 (2)
orihane-psee (1)
jeromehue (1)
Tobias-Fischer (1)
bvogginger (1)
chanokin (1)
erdalkaraca (1)
bauerfe (1)
jeremyforest (1)

Pull Request Authors

Jegp (39)
stevenabreu7 (27)
matjobst (26)
benkroehs (11)
fabio-innatera (10)
mrontio (6)
sheiksadique (5)
bvogginger (5)
bauerfe (4)
biphasic (3)
alexfanqi (2)
ColonelParrot (2)
LuukvanKeeken (2)
hanleyc01 (2)
VitF (2)

Top Labels

Issue Labels

after-paper (6) help wanted (2)

Pull Request Labels

Packages

Total packages: 1
Total downloads:
- pypi 14,114 last-month

Total dependent packages: 6
Total dependent repositories: 2
Total versions: 14
Total maintainers: 3

pypi.org: nir

Neuromorphic Intermediate Representation

Documentation: https://nir.readthedocs.io/
License: BSD License
Latest release: 1.0.6
published 8 months ago

Versions: 14
Dependent Packages: 6
Dependent Repositories: 2
Downloads: 14,114 Last month

Rankings

Dependent packages count: 1.9%

Downloads: 3.6%

Average: 5.7%

Dependent repos count: 11.5%

Maintainers (3)

jensegholm matjobst stevenabreu7

Last synced: 6 months ago

Dependencies

.github/workflows/build.yml actions

actions/checkout v3 composite
actions/setup-python v4 composite

.github/workflows/pypi.yml actions

actions/checkout v2 composite
pypa/gh-action-pypi-publish release/v1 composite

dev_requirements.txt pypi

black * development
h5py * development
numpy * development
pre-commit * development
pytest * development
ruff * development
sphinx * development

docs/requirements.txt pypi

h5py *
jupyter-book *
myst-parser *
numpy *
sphinx ==5.0.2
sphinx-book-theme *
sphinx_external_toc *
sphinxcontrib-mermaid *

pyproject.toml pypi

h5py *
numpy *

nir

Science Score: 59.0%

Keywords

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

NIR - Neuromorphic Intermediate Representation

Usage

Define a model

Save the model (source platform)

Load the model (target platform)

Frameworks that currently support NIR

Acknowledgements

Owner

GitHub Events

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Committer Domains (Top 20 + Academic)

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Packages

pypi.org: nir

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Maintainers (3)

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