As DNNs become increasingly common in mission-critical applications, ensuring their
reliable operation has become crucial. Conventional resilience techniques fail to account for …

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 …

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 …

As GPUs become more pervasive in both scalable high-performance computing systems
and safety-critical embedded systems, evaluating and analyzing their resilience to soft errors …

Magnetic Random Access Memory (MRAM) is a very promising emerging memory
technology because of its various advantages such as nonvolatility, high density and …

Reliability concerns due to technology scaling have been a major focus of researchers and
designers for several technology nodes. Therefore, many new techniques for enhancing and …

The architectural vulnerability factor (AVF) of a hardware structure is the probability that a
fault in the structure will affect the output of a program. AVF captures both microarchitectural …

As the computational power of GPUs continues to scale with Moore's Law, an increasing
number of applications are becoming limited by memory bandwidth. We propose an …

We propose AVGI, a new Statistical Fault Injection (SFI)-based methodology, which delivers
orders of magnitude faster assessment of the Architectural Vulnerability Factor (AVF) of a …

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 …