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EnforceSNN: Enabling resilient and energy-efficient spiking neural network inference considering approximate DRAMs for embedded systems
Spiking Neural Networks (SNNs) have shown capabilities of achieving high accuracy under unsupervised settings and low operational power/energy due to their bio-plausible computations. Previous studies identified that DRAM-based off-chip memory accesses dominate the energy consumption of SNN processi...
Autores principales: | Putra, Rachmad Vidya Wicaksana, Hanif, Muhammad Abdullah, Shafique, Muhammad |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9399768/ https://www.ncbi.nlm.nih.gov/pubmed/36033624 http://dx.doi.org/10.3389/fnins.2022.937782 |
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