Machine learning is among the greatest advancements in computer science and
engineering and is today used to classify or detect objects, a key feature in autonomous …

We propose AVGI, a new Statistical Fault Injection (SFI)-based methodology, which delivers
orders of magnitude faster assessment of the Architectural Vulnerability Factor (AVF) of a …

Hyperdimensional Computing (HDC), also known as Vector Symbolic Architecture (VSA), is
an emerging AI algorithm inspired by the way the human brain functions. Compared with …

Today more than ever before, academia, manufacturers, and hyperscalers acknowledge the
major challenge of silent data corruptions (SDCs) and aim on solutions to minimize its …

Microprocessor power consumption and dependability are both crucial challenges that
designers have to cope with due to shrinking feature sizes and increasing transistor counts …

Chip manufacturers and hyperscalers are becoming increasingly aware of the problem
posed by Silent Data Errors (SDE) and are taking steps to address it. Major computing …

In this paper, we present gem5-MARVEL, the first consolidated microarchitecture-level fault
injection infrastructure for heterogeneous System-on-Chip architectures comprising CPUs of …

Silent Data Corruptions (SDCs) pose a significant threat to the integrity of digital systems.
These stealthy saboteurs silently corrupt data, remaining undetected by traditional error …

Pre-silicon reliability evaluation of processors is usually performed at the microarchitecture
or at the software level. Recent studies on CPUs have, however, shown that software level …

Silent data corruptions (SDCs) pose a significant challenge to the reliable operation of
modern microprocessors. As the need for enhanced performance and reliability continues to …