Energy harvesting (EH) IoT devices that operate intermittently without batteries, coupled with
advances in deep neural networks (DNNs), have opened up new opportunities for en-abling …

This paper proposes a spin-orbit torque (SOT) magnetoresistive random access memory
(MRAM)-based digital computing in memory (CIM) structure for advanced CIM edge AI …

Federated learning has gained significant attention as a distributed machine learning
paradigm, particularly due to its ability to preserve privacy by keeping data on IoT devices …

In-memory deep neural network (DNN) accelerators will be the key for energy-efficient
autonomous edge systems. The resistive random access memory (ReRAM) is a potential …

Modern science and technology witness the breakthroughs of deep learning during the past
decades. Fueled by the rapid improvements of computational resources, learning …

Ever since the emergence of the electrical computer and the Von Neumann model,
computer architects have adhered to a well‐structured hierarchy of memory solutions …