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...

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Detalles Bibliográficos
Autores principales: Putra, Rachmad Vidya Wicaksana, Hanif, Muhammad Abdullah, Shafique, Muhammad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Neuroscience
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

Internet

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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