Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866913281103364096 |
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| author | Sanaullah Koravuna, Shamini Rückert, Ulrich Jungeblut, Thorsten |
| author_facet | Sanaullah Koravuna, Shamini Rückert, Ulrich Jungeblut, Thorsten |
| contents | With the motivation and the difficulties that currently exist in comprehending and utilizing the promising features of SNNs, we proposed a novel run-time multi-core architecture-based simulator called "RAVSim" (Runtime Analysis and Visualization Simulator), a cutting-edge SNN simulator, developed using LabVIEW and it is publicly available on their website as an official module. RAVSim is a runtime virtual simulation environment tool that enables the user to interact with the model, observe its behavior of output concentration, and modify the set of parametric values at any time while the simulation is in execution. Recently some popular tools have been presented, but we believe that none of the tools allow users to interact with the model simulation in run time. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_12061 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures Sanaullah Koravuna, Shamini Rückert, Ulrich Jungeblut, Thorsten Neural and Evolutionary Computing Artificial Intelligence With the motivation and the difficulties that currently exist in comprehending and utilizing the promising features of SNNs, we proposed a novel run-time multi-core architecture-based simulator called "RAVSim" (Runtime Analysis and Visualization Simulator), a cutting-edge SNN simulator, developed using LabVIEW and it is publicly available on their website as an official module. RAVSim is a runtime virtual simulation environment tool that enables the user to interact with the model, observe its behavior of output concentration, and modify the set of parametric values at any time while the simulation is in execution. Recently some popular tools have been presented, but we believe that none of the tools allow users to interact with the model simulation in run time. |
| title | Design-Space Exploration of SNN Models using Application-Specific Multi-Core Architectures |
| topic | Neural and Evolutionary Computing Artificial Intelligence |
| url | https://arxiv.org/abs/2403.12061 |