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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Autores principales:	Rachmad Vidya Wicaksana Putra, Muhammad Abdullah Hanif, Muhammad Shafique
Formato:	Artigo
Lenguaje:	Inglês
Publicado:	Frontiers Media S.A. 2022-08-01
Colección:	Frontiers in Neuroscience
Materias:	spiking neural networks high performance energy efficiency approximate computing approximate DRAM DRAM errors
Acceso en línea:	https://www.frontiersin.org/articles/10.3389/fnins.2022.937782/full
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