Deep learning tasks cover a broad range of domains and an even more extensive range of
applications, from entertainment to extremely safety-critical fields. Thus, Deep Neural …

Graphics processing units (GPUs) are playing a critical role in convolutional neural networks
(CNNs) for image detection. As GPU-enabled CNNs move into safety-critical environments …

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 …

Increase in graphics hardware performance and improvements in programmability has
enabled GPUs to evolve from a graphics-specific accelerator to a general-purpose …

In this article, we investigate the reliability of Google's coral tensor processing units (TPUs)
to both high-energy atmospheric neutrons (at ChipIR) and thermal neutrons from a pulsed …

Convolutional Neural Networks (CNNs) have truly gained attention in object recognition and
object classification in particular. When being implemented on Graphics Processing Units …

Graphics processing units (GPUs) are increasingly attractive for both safety-critical and High-
Performance Computing applications. GPU reliability is a primary concern for both the …

In this paper, we evaluate the reliability of the You Only Look Once (YOLO) object detection
framework. We have exposed to controlled neutron beams GPUs designed with three …

Graphics Processing Units (GPUs) offer high computational power but require high
scheduling strain to manage parallel processes, which increases the GPU cross section …

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 …