Energy-efficient Mott activation neuron for full-hardware implementation of neural networks.

ABSTRACT: To circumvent the von Neumann bottleneck, substantial progress has been made towards in-memory computing with synaptic devices. However, compact nanodevices implementing non-linear activation functions are required for efficient full-hardware implementation of deep neural networks. Here, we present an energy-efficient and compact Mott activation neuron based on vanadium dioxide and its successful integration with a conductive bridge random access memory (CBRAM) crossbar array in hardware. The Mott activation neuron implements the rectified linear unit function in the analogue domain. The neuron devices consume substantially less energy and occupy two orders of magnitude smaller area than those of analogue complementary metal-oxide semiconductor implementations. The LeNet-5 network with Mot

SUBMITTER: Oh S 

PROVIDER: S-EPMC8627686 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature