Supported simulators and hardware#

NIR is currently supported by 7 simulators and 4 hardware platforms, allowing users to seamlessly move between any of these platforms. The 6 simulators include Lava-DL, Nengo, Norse, Rockpool, Sinabs, and snnTorch. The 4 hardware platforms include Intel Loihi (via Lava-DL), Xylo, Speck, and SpiNNaker2.

The table below shows the integration progress for the respective frameworks. By “reading” a NIR graph, we mean converting it into a platform-specific representation. “Writing” a NIR graph means converting a platform-specific representation into a NIR graph.

Framework

Write to NIR

Read from NIR

Examples

Lava-DL

Nengo

Nengo examples

Norse

Norse examples

Rockpool (SynSense Xylo chip)

Sinabs (SynSense Speck chip)

snnTorch

SpiNNaker2

Spyx

Spyx Examples

Why are some platforms only reading or writing but not both?#

Some platforms support both reading and writing, but in other cases it does not make sense to both read and write NIR graphs. For example hardware platforms are meant as a runtime of NIR graphs, so it rarely makes sense to convert the hardware representation back into NIR.

What about other simulators and hardware platforms?#

NIR is a recent invention, and we are working hard to integrate it with as many simulators and hardware platforms as possible. If you know of a simulator or hardware accelerator we should include, please get in touch with us here on GitHub.