Axon: The STICK Software Development Kit

The brain, a truly efficient computation machine, encodes and processes information using discrete spikes. Inspired by this, we’ve built Axon, a neuromorphic software framework for building, simulating, and compiling Spiking Neural Networks (SNNs) for general-purpose computation. Axon allows to build complex computation by combining modular computation kernels, avoiding the challenge of having to train case-specific SNN while maintaining the sparsity of spike computing.

Axon is an extension of STICK (Spike Time Interval Computational Kernel).

Axon Architecture

The code is open-source on Gihub > Axon SDK

Axon provides an end-to-end pipeline for deploying deterministic algorithms as interval-coded SNNs to ultra-low-power neuromorphic hardware.

At Neucom, we’re building one of such neuromorphic chips and we’re calling it ADA. ADA aims to marry together the low-power consumption of FPGAs and ASICS while keeping the flexibility and ease of use of microcontrollers.

The Axon SDK includes:

  • A SNN simulator for accurate emulation of the interval-coded symbolic computation.
  • A compiler for translating Python-defined algorithms into spiking circuits, ready for simulation or deployment.
  • Resource reporting tools for latency estimation and performance profiling of the deployed algorithms.

If you’re building symbolic SNNs for embedded inference, signal processing, control, or cryptographic tasks, Axon makes it easy to translate deterministic computations into spiking neural networks.

Axon SDK structure

ComponentDescription
axon_sdk.primitivesBase clases defining the low level components and engine used by the spiking networks
axon_sdk.networksLibrary of modular spiking computation kernels
axon_sdk.simulatorSpiking network simulator to input spikes, simulate dynamics and read outputs
axon_sdk.compilationCompiler for transforming high-level algorithms into spiking networks

Example: Float multiplication SNN

from axon_sdk.simulator import Simulator
from axon_sdk.networks import MultiplierNetwork

encoder = DataEncoder(Tmin=10.0, Tcod=100.0)
net = MultiplierNetwork(encoder)

val1 = 0.1
val2 = 0.5

sim = Simulator(net, encoder, dt=0.01)

# Apply both input values
sim.apply_input_value(val1, neuron=net.input1, t0=10)
sim.apply_input_value(val2, neuron=net.input2, t0=10)

# Simulate long enough to see output
sim.simulate(simulation_time=400)

spikes = sim.spike_log.get(net.output.uid, [])
interval = spikes[1] - spikes[0]
decoded_val = encoder.decode_interval(interval)

decoded_val
>> 0.05

Citation

If you use Axon in your research, please cite:

@misc{axon2025,
  title        = {Axon: A Software Development Kit for Symbolic Spiking Networks},
  author       = {Neucom},
  howpublished = {\url{https://github.com/neucom/axon}},
  year         = {2025}
}

License

The Axon SDK is open-sourced under a GPLv3 license, preventing by default its inclusion in closed-source projects. However, reach out to initiate a collaboration if you’d like to incorporate Axon into your closed-source project.

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