The advent of High-Performance Computing has led to the adoption of Convolutional Neural
Networks (CNNs) in safety-critical applications such as autonomous vehicles. However …

As technologies continue to shrink, memory system failure rates have increased, demanding
support for stronger forms of reliability. In this work, we take inspiration from the two-tier …

The cells in dynamic random access memory (DRAM) degrade over time as a result of
aging, leading to poor performance and potential security vulnerabilities. With a globalized …

The rowhammer vulnerability primarily emanates from the physical characteristics of
dynamic random access memory (DRAM). Various factors influence the timing of bit flips in …

Memory is one of the key components that affects reliability and performance of datacenter
servers. Memory in today's servers is organized and shared in several ways to provide the …

Memory security and reliability are two major design concerns in cloud computing systems.
State-of-the-art memory security–reliability co-designs (eg, Synergy) have achieved a good …

Abstract Convolutional Neural Networks (CNNs) are broadly used in safety-critical
applications such as autonomous vehicles. While demonstrating high accuracy, CNN …

Due to the ubiquitous presence of memory components in all electronic computing systems,
memory-based signatures are considered low-cost alternatives to generate unique device …