Deep neural networks (DNNs) have been widely-adopted in various safety-critical
applications such as computer vision and autonomous driving. However, as technology …

Silent Data Corruption (SDC) can have negative impact on large-scale infrastructure
services. SDCs are not captured by error reporting mechanisms within a Central Processing …

As the exascale era approaches, the increasing capacity of high-performance computing
(HPC) systems with targeted power and energy budget goals introduces significant …

Hardware reliability is adversely affected by the downscaling of semiconductor devices and
the scale-out of systems necessitated by modern applications. Apart from crashes, this …

Deep neural network (DNN) has been widely utilized in many areas due to its increasingly
high accuracy. However, DNN models could also produce wrong outputs due to internal …

Soft errors can lead to silent data corruption (SDC), seriously compromising the reliability of
a system. To detect SDC, a profiling of SDC-causing instructions is usually needed to decide …

The exceptional performance of Deep neural networks (DNNs) encourages their
deployment in safety-and dependability-critical systems. However, DNNs often demonstrate …

Hardware failures pose critical threats to deep neural network (DNN) training workloads,
and the urgency of tackling this challenge (known as the Silent Data Corruption challenge in …

As technology scales to lower feature sizes, devices become more susceptible to soft errors.
Soft errors can lead to silent data corruptions (SDCs), seriously compromising the reliability …

With the continuous improvement of the integration of semiconductor chips, it has brought
great challenges to the reliability and safety of the system. Among them, Silent Data …