SPINDLE

Abstract

Deep Learning Networks (DLNs) are bio-inspired large-scale neural networks that are widely used in emerging vision, analytics, and search applications. The high computation and storage requirements of DLNs have led to the exploration of various avenues for their efficient realization. Concurrently, the ability of emerging post-CMOS devices to efficiently mimic neurons and synapses has led to great interest in their use for neuromorphic computing.