Oltra-Oltra, JosepVallejo, BernardoMadrenas, JordiMata-Hernández, DianaZapata, MireyaSato, Shigeo2022-06-202022-06-202021https://ieeexplore.ieee.org/document/9401615https://hdl.handle.net/20.500.14809/3264This paper introduces a novel workflow for Distributed Spiking Neural Network Architecture (DSNA). As such, the hardware implementation of Single Instruction Multiple Data (SIMD)-based Spiking Neural Network (SNN) requires the development of user-friendly and efficient toolchain in order to maximise the potential that the architecture brings. By using a novel SNN architecture, a custom designed hardware/software toolchain has been developed. The toolchain performance has been experimentally checked on a Band-Pass Filter (BPF), obtaining optimized code and datengopenAccesshttps://creativecommons.org/licenses/by/4.0/article