The adoption of deep neural networks (DNNs) in safety-critical domains has engendered
serious reliability concerns. A prominent example is hardware transient faults that are …

As machine learning (ML) becomes pervasive in high performance computing, ML has
found its way into safety-critical domains (eg, autonomous vehicles). Thus the reliability of …

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 …

As CNNs are being extensively employed in high performance and safety-critical
applications that demand high reliability, it is important to ensure that they are resilient to …

GPUs have emerged as general-purpose accelerators in high-performance computing
(HPC) and scientific applications. However, the reliability characteristics of GPU applications …

Supercomputers offer new opportunities for scientific computing as they grow in size.
However, their growth also poses new challenges. Resilience has been recognized as one …

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 …

We present an in-depth analysis of transient faults effects on HPC applications in Intel Xeon
Phi processors based on radiation experiments and high-level fault injection. Besides …

Compiler-based fault injection (FI) has become a popular technique for resilience studies to
understand the impact of soft errors in supercomputing systems. Compiler-based FI …

While many algorithm-based fault tolerance (ABFT) schemes have been proposed to detect
soft errors offline in the fast Fourier transform (FFT) after computation finishes, none of the …