Spiffy: Efficient Implementation of CoLaNET for Raspberry Pi
Spiffy: Efficient Implementation of CoLaNET for Raspberry Pi
This paper presents a lightweight software-based approach for running spiking neural networks (SNNs) without relying on specialized neuromorphic hardware or frameworks. Instead, we implement a specific SNN architecture (CoLaNET) in Rust and optimize it for common computing platforms. As a case study, we demonstrate our implementation, called Spiffy, on a Raspberry Pi using the MNIST dataset. Spiffy achieves 92% accuracy with low latency - just 0.9 ms per training step and 0.45 ms per inference step. The code is open-source.
Andrey Derzhavin、Denis Larionov
计算技术、计算机技术
Andrey Derzhavin,Denis Larionov.Spiffy: Efficient Implementation of CoLaNET for Raspberry Pi[EB/OL].(2025-06-23)[2025-07-09].https://arxiv.org/abs/2506.18306.点此复制
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