Along with the rapid developments in communication technologies and the surge in the use
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …

Electric vehicles are widely adopted globally as a sustainable mode of transportation. With
the increased availability of onboard computation and communication capabilities, vehicles …

Low-precision integer arithmetic is a necessary ingredient for enabling Deep Learning
inference on tiny and resource-constrained IoT edge devices. This brief presents CMix-NN …

This paper presents the first experimental demonstration of a ternary memristor-CMOS logic
family. We systematically design, simulate and experimentally verify the primitive logic …

Along with the proliferation of the Internet of Things (IoT) and the surge in the use of artificial
intelligence (AI), Edge Computing has proved considerable success in reducing latency …

Memristive devices arranged in cross-bar architectures have shown great promise to
facilitate the acceleration and improve the power efficiency of Deep Learning (DL) systems …

Recently, the Logic-in-Memory (LiM) concept has been widely studied in the literature. This
paradigm represents one of the most efficient ways to solve the limitations of a Von …

In this paper, we propose a new crossbar architecture of memristors with bipolar inputs for
an image recognition application. The performance of the proposed crossbar array with …

Federated learning (FL), particularly when data is distributed across multiple clients, helps
reducing the learning time by avoiding training on a massive pile-up of data. Nonetheless …

The data movement between the processing and storage units has been one of the most
critical issues in modern computer systems. The emerging Resistive Random Access …