NIR is a set of computational primitives, shared across different neuromorphic frameworks and technology stacks. NIR is currently supported by 9 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.

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:

Recently, NIR has been extended by an intermediate representation for data exchange in spiking neural networks: NIRData.

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},
}