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 …

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 …

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 …

Reduction in leakage power has become an important concern in low voltage, low power
and high performance applications. In this paper, we use dual threshold technique to reduce …

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 …

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

Virtual platform frameworks have been extended to allow earlier soft error analysis of more
realistic multicore systems (ie, real software stacks and state-of-the-art ISAs). The high …

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 …

Several hyperscalers have recently disclosed the occurrence of Silent Data Corruptions
(SDCs) in their systems fleets, sparking concerns about the severity of known and the …

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