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https://repositorio.uti.edu.ec//handle/123456789/3264| Título : | Hardware-software co-design for efficient and scalable real-time emulation of SNNs on the edge |
| Autor : | Oltra-Oltra, Josep Vallejo, Bernardo Madrenas, Jordi Mata-Hernández, Diana Zapata, Mireya Sato, Shigeo |
| Fecha de publicación : | 2021 |
| Editorial : | Proceedings - IEEE International Symposium on Circuits and Systems. Volume 2021-May. 3rd IEEE International Symposium on Circuits and Systems, ISCAS 2021. Daegu. 22 May 2021 through 28 May 2021 |
| Resumen : | This 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 dat |
| URI : | https://ieeexplore.ieee.org/document/9401615 http://repositorio.uti.edu.ec//handle/123456789/3264 |
| Aparece en las colecciones: | Artículos Científicos Indexados |
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