Neuromemristive Circuits for Edge Computing: A Review

Olga Krestinskaya, Alex Pappachen James, Leon Ong Chua

Research output: Contribution to journalArticlepeer-review

156 Scopus citations

Abstract

The volume, veracity, variability, and velocity of data produced from the ever increasing network of sensors connected to Internet pose challenges for power management, scalability, and sustainability of cloud computing infrastructure. Increasing the data processing capability of edge computing devices at lower power requirements can reduce several overheads for cloud computing solutions. This paper provides the review of neuromorphic CMOS-memristive architectures that can be integrated into edge computing devices. We discuss why the neuromorphic architectures are useful for edge devices and show the advantages, drawbacks, and open problems in the field of neuromemristive circuits for edge computing.
Original languageEnglish (US)
Pages (from-to)4-23
Number of pages20
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume31
Issue number1
DOIs
StatePublished - Jan 1 2020
Externally publishedYes

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