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An Ultra-Low-Power Synthesizable Asynchronous AER Encoder for Neuromorphic Edge Devices

Systems and Control 2026-04-08 v1 Systems and Control

Abstract

This paper presents a fully synthesizable, treebased Address-Event Representation (AER) encoder designed for scalable neuromorphic computing systems. To achieve high throughput while maintaining strict compatibility with commercial EDA workflows, the asynchronous design employs a bundled-data protocol within a semi-decoupled micropipeline. The architecture replaces traditional transparent latches with standard edge-triggered flip-flops, enabling digital synthesis and place-and-route (PnR) using Cadence toolkits. A cross-coupled NAND-based random-priority arbiter is embedded within the encoder of each tree node to resolve event collisions efficiently. An 8-event AER prototype is fabricated in 65 nm CMOS technology utilizing a purely digital standard-cell flow. Post-fabrication silicon measurements validate the design, demonstrating a peak throughput of 33 MEvent/s and an average event latency of 50 ns, equating to a propagation delay of 17 ns/(event-bit). The design consumes only 435 fJ per encoded event.

Keywords

Cite

@article{arxiv.2604.05313,
  title  = {An Ultra-Low-Power Synthesizable Asynchronous AER Encoder for Neuromorphic Edge Devices},
  author = {Yihui Wang and Sheng-Yu Peng and Sahil Shah},
  journal= {arXiv preprint arXiv:2604.05313},
  year   = {2026}
}
R2 v1 2026-07-01T11:56:26.517Z