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 …

Architecture Design for Soft Errors provides a comprehensive description of the architectural
techniques to tackle the soft error problem. It covers the new methodologies for quantitative …

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 …

With technology scaling, transient faults are becoming an increasing threat to hardware
reliability. Commodity systems must be made resilient to these in-field faults through very …

Traditionally, fault tolerance researchers have required architectural state to be numerically
perfect for program execution to be correct. However, in many programs, even if execution is …

Rapid progress in the CMOS technology for the past 25 years has increased the
vulnerability of processors towards faults. Subsequently, focus of computer architects shifted …

ACE analysis is a technique to provide an early reliability estimate for microprocessors. ACE
analysis couples data from abstract performance models with low level design details to …

Traditional fault-tolerance techniques typically utilize resources ineffectively because they
cannot adapt to the changing reliability and performance demands of a system. This paper …

Exponentially growing rate of soft errors makes reliability a major concern in modern
processor design. Since software-oriented approaches offer flexible protection even in off …

As transistors become increasingly smaller and faster with tighter noise margins, modern
processors are becoming increasingly more susceptible to transient hardware faults …