Silent Data Errors (SDEs) are a subset of Defective Parts per Million (DPPM) test escapes
that cause unnoticed data corruption. Even at very low levels of DPPM, these are visible at …

Resource-intensive applications such as scientific applications require the architecture or
system on which they execute to display a very high level of dependability to reduce the …

Analyzing application fault behavior on large-scale systems is time-consuming and resource-
demanding. Currently, researchers need to perform fault injection campaigns at full scale to …

Silent data corruption (SDC) and fail-stop errors are the most hazardous error types in high-
performance computing (HPC) systems. In this study, we present an automatic, efficient and …

State-of-the-art approaches formulate error detection as a semi-supervised classification
problem. Recent research suggests that active learning is insufficiently effective for error …

Single-Event Effects are an increasingly important issue in electronic circuits due to
technology scaling, efficient error detection schemes are thus required for circuits dedicated …

This work focuses on resilience techniques at extreme scale. Many papers deal with fail-stop
errors. Many others deal with silent errors (or silent data corruptions). But very few papers …

The trend of rapid technology scaling is expected to make the hardware of high-performance
computing (HPC) systems more susceptible to computational errors due to random bit flips …

Silent Data Corruption (SDC) is a serious reliability issue in many domains, including
embedded systems. However, current protection techniques are brittle and do not allow …

Radiation-induced soft errors degrade the reliability of aerospace-based computing. Silent
data corruption (SDC) is the most dangerous and insidious type of soft error result. To detect …