Tensor processing units (TPUs) are one of the most well-known machine learning (ML)
accelerators utilized at large scale in data centers as well as in tiny ML applications. TPUs …

This paper explores the synergistic potential of neuromorphic and edge computing to create
a versatile machine learning (ML) system tailored for processing data captured by dynamic …

Brain-computer interfaces (BCIs) are electrophysiological devices (eg, electrode arrays) that
connect the brain to a computer. They offer neuroscientific and neurological innovations by …

This paper addresses the challenge of deploying machine learning (ML)-based
segmentation models on edge platforms to facilitate real-time scene segmentation for …

Driven by rapid advancements in interconnection, packaging, integration, and computing
technologies, parallel and distributed systems have significantly evolved in recent years …

Abstract Machine learning (ML) has become ubiquitous, integrating into numerous real-life
applications. However, meeting the computational demands of ML systems is challenging …