# Scalable neuromorphic computing from autonomous spiking dynamics in a clockless reconfigurable chip

arXiv: https://arxiv.org/abs/2605.16114 · HTML: https://mlsanity.com/paper/2605.16114/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 13 of its 61 references that are in the map.
- First posted on arXiv 15 May 2026.

## Builds on (most cited first, 13 of 13)

- [The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks](https://mlsanity.com/paper/1910.07407/) (2019)
- [Photonics for artificial intelligence and neuromorphic computing](https://mlsanity.com/paper/2011.00111/) (2020)
- [Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings](https://mlsanity.com/paper/2306.17670/) (2023)
- [The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity](https://mlsanity.com/paper/2201.11063/) (2022)
- [Scalable Event-by-event Processing of Neuromorphic Sensory Signals With Deep State-Space Models](https://mlsanity.com/paper/2404.18508/) (2024)
- [Vowel recognition with four coupled spin-torque nano-oscillators](https://mlsanity.com/paper/1711.02704/) (2017)
- [Spiker+: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edge](https://mlsanity.com/paper/2401.01141/) (2024)
- [DenRAM: Neuromorphic Dendritic Architecture with RRAM for Efficient Temporal Processing with Delays](https://mlsanity.com/paper/2312.08960/) (2023)
- [Advancing Spatio-Temporal Processing in Spiking Neural Networks through Adaptation](https://mlsanity.com/paper/2408.07517/) (2024)
- [A Fully-Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture](https://mlsanity.com/paper/2404.02248/) (2024)
- [Large-scale spatiotemporal photonic reservoir computer for image classification](https://mlsanity.com/paper/2004.02542/) (2020)
- [Temporal and Spatial Reservoir Ensembling Techniques for Liquid State Machines](https://mlsanity.com/paper/2411.11414/) (2024)
- [A spiking photonic neural network of 40.000 neurons, trained with rank-order coding for leveraging sparsity](https://mlsanity.com/paper/2411.19209/) (2024)

## Abstract (arXiv)

We propose a scalable neuromorphic architecture based on spiking dynamics emerging from the autonomous time-continuous evolution of clockless (asynchronous) digital circuits. Implemented on commercially available field-programmable gate arrays (FPGAs), our system implements networks of interacting Boolean spiking neurons with configurable excitatory and inhibitory synaptic weights. A complete processing pipeline enables efficient handling of spike-encoded data for solving machine-learning tasks. We demonstrate competitive performance for an audio classification task with spike-based encoding and high-speed processing. Power consumption is significantly lower than traditional digital implementations; this makes our approach an efficient alternative that bridges the gap to dedicated analog neuromorphic systems without the need for specialized hardware design. More generally, our approach establishes clockless digital hardware as a viable platform for neuromorphic computing. It paves the way for reconfigurable chips to be turned into energy-efficient quasi-analog neuromorphic processors.