Brian2Loihi: An emulator for the neuromorphic chip Loihi using the spiking neural network simulator Brian
This provides a user-friendly tool for researchers and developers to streamline algorithm design and deployment on neuromorphic hardware, though it is incremental as it builds on existing simulators.
The authors tackled the challenge of prototyping neuromorphic algorithms for the Loihi chip by developing an open-source emulator using the Brian simulator, achieving errorless emulation for single neurons and recurrent networks with reasonable discrepancies in on-chip learning due to stochastic rounding.
Developing intelligent neuromorphic solutions remains a challenging endeavour. It requires a solid conceptual understanding of the hardware's fundamental building blocks. Beyond this, accessible and user-friendly prototyping is crucial to speed up the design pipeline. We developed an open source Loihi emulator based on the neural network simulator Brian that can easily be incorporated into existing simulation workflows. We demonstrate errorless Loihi emulation in software for a single neuron and for a recurrently connected spiking neural network. On-chip learning is also reviewed and implemented, with reasonable discrepancy due to stochastic rounding. This work provides a coherent presentation of Loihi's computational unit and introduces a new, easy-to-use Loihi prototyping package with the aim to help streamline conceptualisation and deployment of new algorithms.