SNAVA: A Generic Threshold-Based-SNN Emulation Solution
[ANGLÈS] Spiking Neural Networks has been the focus of research of the decade. It has been proved possible to mimic several mechanisms of the mammalian brain with SNN models. Several dedicated hardware, both analog and digital, have been built for SNN emulation in the past decade. In this work an ex...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2013 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099.1/19633 |
| Acceso en línea: | https://hdl.handle.net/2099.1/19633 |
| Access Level: | acceso abierto |
| Palabra clave: | Neural networks (Computer science) FPGA Spiking Neural Networks SIMD Digital Logic Design Algorithms and Architectures Redes Neuronales Spiking Diseño Digital Algoritmos y arquitecturas Xarxes neuronals (Informàtica) Àrees temàtiques de la UPC::Enginyeria de la telecomunicació |
| Sumario: | [ANGLÈS] Spiking Neural Networks has been the focus of research of the decade. It has been proved possible to mimic several mechanisms of the mammalian brain with SNN models. Several dedicated hardware, both analog and digital, have been built for SNN emulation in the past decade. In this work an existing SIMD processor architecture called Ubichip has been analyzed, bottlenecks have been identified and improvements have been proposed. A new vector processing Architecture called SNAVA has been proposed with features of virtualization and real-time parameter monitoring. It has been implemented on a Xilinx KC705 kit. A proof of concept application has also been developed and experimental results have been presented. |
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