Over the past six decades, the computing systems field has experienced significant
transformations, profoundly impacting society with transformational developments, such as …

Edge artificial intelligence (AI) is an innovative computing paradigm that aims to shift the
training and inference of machine learning models to the edge of the network. This paradigm …

In the era of the IoT revolution, applications are becoming ever more sophisticated and
accompanied by diverse functional and non-functional requirements, including those related …

In the big data era, the requirement for data clustering methods that can handle massive and
heterogeneous datasets with varying distributions increases. This study proposes a …

Neuromorphic in-sensor computing has provided an energy-efficient solution to smart
sensor design and on-chip data processing. In recent years, various free-space-configured …

The need for novel memory devices with low energy usage, strong reliability, and multi-level
capacity is growing significantly nowadays. Among one of the promising candidates, hafnia …

Current advancements in neuromorphic computing systems are focused on decreasing
power consumption and enriching computational functions. Correspondingly, state-of-the-art …

Among neuromorphic devices, resistive random-access memory (RRAM) is considered one
of the promising blocks in artificial intelligence technology for its simple structure and ability …

Emerging device technologies such as Resistive RAMs (RRAMs) are under investigation by
many researchers and semiconductor companies; not only to realize eg, embedded non …

Modern computing environments are evolving towards the compute continuum paradigm,
which promises to manage the heterogeneity and dynamism of geographically spread …