将脉冲神经网络部署到Xylo芯片，实现边缘计算超低功耗高效运行。
Deployment Pipeline from Rockpool to Xylo for Edge Computing
- 通过Rockpool框架对接Xylo芯片，构建端到端部署流程。
- 在保证精度前提下，实现远低于传统方案的能耗水平。
- 适合实时、高能效要求的边缘智能应用开发。
通过Rockpool框架将脉冲神经网络（SNNs）部署至Xylo类脑芯片，是实现边缘计算场景下超低功耗与高计算效率的重要进展。本文提出一种新型部署管道，重点融合Rockpool的能力与Xylo芯片架构特性，并从能效和精度两方面评估系统性能。Xylo芯片独有的数字脉冲架构与事件驱动处理模式，使其在实时、功耗敏感型应用中表现出显著优势。
原文摘要 · Abstract (English)
Deploying Spiking Neural Networks (SNNs) on the Xylo neuromorphic chip via the Rockpool framework represents a significant advancement in achieving ultra-low-power consumption and high computational efficiency for edge applications. This paper details a novel deployment pipeline, emphasizing the integration of Rockpool's capabilities with Xylo's architecture, and evaluates the system's performance in terms of energy efficiency and accuracy. The unique advantages of the Xylo chip, including its digital spiking architecture and event-driven processing model, are highlighted to demonstrate its suitability for real-time, power-sensitive applications.
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