In this paper, we revisit the system vulnerability stack for transient faults. We reveal severe
pitfalls in widely used vulnerability measurement approaches, which separate the hardware …

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 …

This paper discusses principles and techniques to evaluate processors for dependable
computing in space applications. The focus is on soft errors, which dominate the failure rate …

Fault injection in early microarchitecture-level simulation CPU models and beam
experiments on the final physical CPU chip are two established methodologies to access the …

Extensive research efforts are being carried out to evaluate and improve the reliability of
computing devices either through beam experiments or simulation-based fault injection …

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 …

Miniaturization of integrated circuits brings more devices (thus more functionality) on the
same silicon area but also makes them more vulnerable to soft (transient) errors …

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 …

Early reliability assessment of hardware structures using microarchitecture level simulators
can effectively guide major error protection decisions in microprocessor design. Statistical …