Testability and dependability of AI hardware: Survey, trends, challenges, and perspectives
Hardware realization of artificial intelligence (AI) requires new design styles and even
underlying technologies than those used in traditional digital processors or logic circuits …
underlying technologies than those used in traditional digital processors or logic circuits …
A systematic literature review on hardware reliability assessment methods for deep neural networks
Artificial Intelligence (AI) and, in particular, Machine Learning (ML), have emerged to be
utilized in various applications due to their capability to learn how to solve complex …
utilized in various applications due to their capability to learn how to solve complex …
A low-cost fault corrector for deep neural networks through range restriction
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 …
serious reliability concerns. A prominent example is hardware transient faults that are …
Understanding and mitigating hardware failures in deep learning training systems
Y He, M Hutton, S Chan, R De Gruijl… - Proceedings of the 50th …, 2023 - dl.acm.org
Deep neural network (DNN) training workloads are increasingly susceptible to hardware
failures in datacenters. For example, Google experienced" mysterious, difficult to identify …
failures in datacenters. For example, Google experienced" mysterious, difficult to identify …
[PDF][PDF] Optimizing Selective Protection for CNN Resilience.
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 …
applications that demand high reliability, it is important to ensure that they are resilient to …
Snr: S queezing n umerical r ange defuses bit error vulnerability surface in deep neural networks
As deep learning algorithms are widely adopted, an increasing number of them are
positioned in embedded application domains with strict reliability constraints. The …
positioned in embedded application domains with strict reliability constraints. The …
Deep learning based an efficient hybrid prediction model for Covid-19 cross-country spread among E7 and G7 countries
A Utku - Decision Making: Applications in Management and …, 2023 - dmame-journal.org
The COVID-19 pandemic has caused the death of many people around the world and has
also caused economic problems for all countries in the world. In the literature, there are …
also caused economic problems for all countries in the world. In the literature, there are …
Understanding the Effects of Permanent Faults in GPU's Parallelism Management and Control Units
Modern Graphics Processing Units (GPUs) demand life expectancy extended to many years,
exposing the hardware to aging (ie, permanent faults arising after the end-of-manufacturing …
exposing the hardware to aging (ie, permanent faults arising after the end-of-manufacturing …
Structural coding: A low-cost scheme to protect cnns from large-granularity memory faults
The advent of High-Performance Computing has led to the adoption of Convolutional Neural
Networks (CNNs) in safety-critical applications such as autonomous vehicles. However …
Networks (CNNs) in safety-critical applications such as autonomous vehicles. However …
Transient-fault-aware design and training to enhance dnns reliability with zero-overhead
Deep Neural Networks (DNNs) enable a wide series of technological advancements,
ranging from clinical imaging, to predictive industrial maintenance and autonomous driving …
ranging from clinical imaging, to predictive industrial maintenance and autonomous driving …