Currently, machine learning (ML) techniques are at the heart of smart cyber-physical
systems (CPSs) and Internet-of-Things (loT). This article discusses various challenges and …

Variations in process parameters affect the operation of integrated circuits (ICs) and pose a
significant threat to the continued scaling of transistor dimensions. Such parameter …

Machine learning is commonly being used in almost all the areas that involve advanced
data analytics and intelligent control. From applications like Natural Language Processing …

The paper addresses some of the opportunities and challenges related to test and reliability
of three major emerging computing paradigms; ie, Quantum Computing, Computing engines …

Elevated power densities result in the so-called Dark Silicon constraint that prohibits
simultaneous activation of all the cores in an on-chip system (in the full performance mode) …

The generation of unique keys by Integrated Circuits (IC) has important applications in areas
such as Intellectual Property (IP) counter-plagiarism and embedded security integration. To …

The real-world use cases of Machine Learning (ML) have exploded over the past few years.
However, the current computing infrastructure is insufficient to support all real-world …

Ensuring lifetime reliability of microprocessors has become more critical. Continuous scaling
and increasing temperatures due to growing power density are threatening lifetime …

Negative-bias temperature instability (NBTI) and positive-bias temperature instability (PBTI)
weaken PFET and NFET over the lifetime of usage, leading to performance and reliability …

Negative bias temperature instability (NBTI) in PMOS transistors has become a major
reliability concern in present-day digital circuit design. Further, with the recent usage of Hf …