Big data

Engineering

Pure mathematics

Field (mathematics)

Operating system

The Internet

Telecommunications

Scalability

Computer science

Cloud computing

Edge device

Distributed computing

Electronic circuit

Computer architecture

Mathematics

Enhanced Data Rates for GSM Evolution

Neuromorphic engineering

Electronic engineering

Artificial intelligence

Edge computing

Artificial neural network

CMOS

Electrical engineering

IEEE Transactions on Neural Networks and Learning Systems

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 neuro-memristive circuits for edge computing.

Neuromemristive Circuits for Edge Computing: A Review