tinyODIN is a low-cost spiking neural network (SNN) processor that was reduced to the simplest form of a crossbar array. It is adapted from the open-source ODIN SNN processor, which was published in 2019 in the IEEE Transactions on Biomedical Circuits and Systems journal. tinyODIN embeds 256 12-bit leaky integrate-and-fire (LIF) neurons and 64k 4-bit synapses. As opposed to ODIN, there is no phenomenological Izhikevich neuron model nor online-learning synapses in tinyODIN.

In case you decide to use the tinyODIN HDL source code for academic or commercial use, we would appreciate it if you let us know; feedback is welcome.

Disclaimer -- Both the HDL code and the documentation of tinyODIN are derived from the open-source repository of ODIN.

Upon usage of the HDL source code of tinyODIN, please cite the associated ODIN paper:

[C. Frenkel, M. Lefebvre, J.-D. Legat and D. Bol, "A 0.086-mm² 12.7-pJ/SOP 64k-Synapse 256-Neuron Online-Learning Digital Spiking Neuromorphic Processor in 28-nm CMOS," IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 1, pp. 145-158, 2019.]

Documentation on the contents, usage and features of the tinyODIN HDL source code can be found in the doc folder.

Copyright (C) 2019-2022, Université catholique de Louvain (UCLouvain, Belgium), University of Zürich (UZH, Switzerland), Katholieke Universiteit Leuven (KU Leuven, Belgium), and Delft University of Technology (TU Delft, Netherlands)

The HDL source code of tinyODIN is under a Solderpad Hardware License v2.1 (see LICENSE file or https://solderpad.org/licenses/SHL-2.1/).

The documentation of tinyODIN is under a Creative Commons Attribution 4.0 International License (see doc/LICENSE file or http://creativecommons.org/licenses/by/4.0/).