James S. Plank, Keegan E. M. Dent, Bryson Gullett, Charles P. Rizzo and Catherine D. Schuman

December, 2024

IEEE International Conference on Rebooting Computing (ICRC)

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Abstract

Neuromorphic computing offers exciting possibilities for embedded systems and edge-computing, due to its combination of computational ability and low size, weight, and power. However, open source solutions for embedded neuromorphic computing are lacking. In this paper, we present open source support for the RISP neuroprocessor, which features simple integrate-and-fire neurons and synapses with discrete delays. There are two software repositories to support RISP – one that provides simulation and network manipulation, and one that implements RISP networks on FPGAs. We detail each of these, discuss capacity and performance, and present examples. Highlights include the large networks supported by commodity FPGAs, with tens of thousands of neurons and synapses. The UART communication is a clear bottleneck; however there are multiple straightforward avenues for improving communication.

Citation Information

Text

author     J. S. Plank and K. E. M. Dent and B. Gullett and C. P. Rizzo and C. D. Schuman
title      The {RISP} Neuroprocessor -- Open Source Support for Embedded Neuromorphic Computing
booktitle  IEEE International Conference on Rebooting Computing (ICRC)
month      December
year       2024
address    San Diego

Bibtex

@INPROCEEDINGS{pdg:24:risp,
    author = "J. S. Plank and K. E. M. Dent and B. Gullett and C. P. Rizzo and C. D. Schuman",
    title = "The {RISP} Neuroprocessor -- Open Source Support for Embedded Neuromorphic Computing",      
    booktitle = "IEEE International Conference on Rebooting Computing (ICRC)",
    month = "December",
    year = "2024",
    address = "San Diego"
}