# ReckOn: A 28nm Sub-mm2 Task-Agnostic Spiking Recurrent Neural Network Processor Enabling On-Chip Learning over Second-Long Timescales

arXiv: https://arxiv.org/abs/2208.09759 · HTML: https://mlsanity.com/paper/2208.09759/

## Key facts

- Cited by 35 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Aug 2022.

## Built on by (most cited first, 30 of 35)

- [Online learning of long-range dependencies](https://mlsanity.com/paper/2305.15947/) (2023)
- [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)
- [Spiking neural networks for nonlinear regression](https://mlsanity.com/paper/2210.03515/) (2022)
- [To Spike or Not To Spike: A Digital Hardware Perspective on Deep Learning Acceleration](https://mlsanity.com/paper/2306.15749/) (2023)
- [Online Spatio-Temporal Learning with Target Projection](https://mlsanity.com/paper/2304.05124/) (2023)
- [Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network](https://mlsanity.com/paper/2304.11857/) (2023)
- [Improving equilibrium propagation without weight symmetry through Jacobian homeostasis](https://mlsanity.com/paper/2309.02214/) (2023)
- [Design Principles for Lifelong Learning AI Accelerators](https://mlsanity.com/paper/2310.04467/) (2023)
- [Optimising Event-Driven Spiking Neural Network with Regularisation and Cutoff](https://mlsanity.com/paper/2301.09522/) (2023)
- [Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applications](https://mlsanity.com/paper/2410.09218/) (2024)
- [TESS: A Scalable Temporally and Spatially Local Learning Rule for Spiking Neural Networks](https://mlsanity.com/paper/2502.01837/) (2025)
- [Intelligence Processing Units Accelerate Neuromorphic Learning](https://mlsanity.com/paper/2211.10725/) (2022)
- [Compressed Latent Replays for Lightweight Continual Learning on Spiking Neural Networks](https://mlsanity.com/paper/2407.03111/) (2024)
- [Three-Factor Learning in Spiking Neural Networks: An Overview of Methods and Trends from a Machine Learning Perspective](https://mlsanity.com/paper/2504.05341/) (2025)
- [ElfCore: A 28nm Neural Processor Enabling Dynamic Structured Sparse Training and Online Self-Supervised Learning with Activity-Dependent Weight Update](https://mlsanity.com/paper/2512.21153/) (2025)
- [Benchmarking Spiking Neural Network Learning Methods with Varying Locality](https://mlsanity.com/paper/2402.01782/) (2024)
- [DeltaKWS: A 65nm 36nJ/Decision Bio-inspired Temporal-Sparsity-Aware Digital Keyword Spotting IC with 0.6V Near-Threshold SRAM](https://mlsanity.com/paper/2405.03905/) (2024)
- [A Systematic Review of ECG Arrhythmia Classification: Adherence to Standards, Fair Evaluation, and Embedded Feasibility](https://mlsanity.com/paper/2503.07276/) (2025)
- [Adaptive Robotic Arm Control with a Spiking Recurrent Neural Network on a Digital Accelerator](https://mlsanity.com/paper/2405.12849/) (2024)
- [When In-memory Computing Meets Spiking Neural Networks -- A Perspective on Device-Circuit-System-and-Algorithm Co-design](https://mlsanity.com/paper/2408.12767/) (2024)
- [An Event-Based Digital Compute-In-Memory Accelerator with Flexible Operand Resolution and Layer-Wise Weight/Output Stationarity](https://mlsanity.com/paper/2410.23082/) (2024)
- [Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks](https://mlsanity.com/paper/2505.05375/) (2025)
- [Three factor delay learning rules for spiking neural networks](https://mlsanity.com/paper/2601.00668/) (2026)
- [BitFair: A 12-nm Bit-Serial CNN Accelerator with Learnable Early Termination and Adaptive Bit Ordering for Ultra-Low-Power XR Vision](https://mlsanity.com/paper/2607.05445/) (2026)
- [A method for the ethical analysis of brain-inspired AI](https://mlsanity.com/paper/2305.10938/) (2023)
- [SpiDR: A Reconfigurable Digital Compute-in-Memory Spiking Neural Network Accelerator for Event-based Perception](https://mlsanity.com/paper/2411.02854/) (2024)
- [Bruno: Backpropagation Running Undersampled for Novel device Optimization](https://mlsanity.com/paper/2505.17791/) (2025)
- [A Scalable Hybrid Training Approach for Recurrent Spiking Neural Networks](https://mlsanity.com/paper/2506.14464/) (2025)
- [A High-Throughput Spiking Neural Network Processor Enabling Synaptic Delay Emulation](https://mlsanity.com/paper/2511.01158/) (2025)
- [DendroNN: Dendrocentric Neural Networks for Energy-Efficient Classification of Event-Based Data](https://mlsanity.com/paper/2603.09274/) (2026)

## Abstract (arXiv)

A robust real-world deployment of autonomous edge devices requires on-chip adaptation to user-, environment- and task-induced variability. Due to on-chip memory constraints, prior learning devices were limited to static stimuli with no temporal contents. We propose a 0.45-mm2 spiking RNN processor enabling task-agnostic online learning over seconds, which we demonstrate for navigation, gesture recognition, and keyword spotting within a 0.8-% memory overhead and a <150-μW training power budget.