Abstract: Abstract: The use of GPUs has been pivotal in driving the progress of AI. AI has been enabling new autonomous capabilities in vehicles, robots, and drones, significantly expanding their practical applications. However, with the growing adoption of GPUs in safety-critical systems, it is important to analyze safety and resilience of these applications to unforeseen events. This presentation will provide an overview of transient hardware errors, which are one of the sources of errors, and the assessment tools and methodologies developed to analyze their effects on system safety. It will also cover error mitigation techniques being developed to improve safety. In recent years, significant research has been conducted in this domain, and the talk will highlight some of these developments, with a focus on the resilience and safety of DNN and AV systems. The presenter will also discuss outstanding problems that can benefit from further research.

Short Bio: Bio: Siva Hari is a Senior Research Scientist in the Architecture Research Group at NVIDIA. His research interests are in the fields of computer architecture, system design, and artificial intelligence, with focus on resilience, safety, and efficiency of autonomous and high-performance computing systems. Some of his research has been recognized recently with IEEE Micro's Top Picks in 2022, Best Research Paper Award at ISSRE 2020, and Best Paper Award Runner-up at DSN 2018. He received the David J. Kuck Outstanding Ph.D. Thesis Award by the CS Department at the University of Illinois at Urbana-Champaign, where he obtained his Ph.D. He obtained his bachelor's degree in computer science and engineering from the Indian Institute of Technology (IIT) Madras.