Can we Rely on Self-Driving Vehicles?
Driverless cars are the new trend in the automotive market and, to burst deep space exploration, NASA and ESA are willing to add self-driving capabilities to their rovers. Ingenuity, landed in Mars in 2021, is the first autonomous vehicle to move outside of the Earth. To be implemented, a self-driving system needs to be able to analyze a huge amount of images and signals in real time. This is achieved thanks to Convolutional Neural Networks (CNNs) executed on Graphics Processing Units (GPUs) or dedicated accelerators, such as the Google’s Tensor Processing Unit (TPU). The Tesla self-driving system, for instance, is powered by embedded GPUs executing CNNs-based object-detection. In the talk we will discuss the reliability of GPUs and other accelerators and evaluate if they are compliant with the strict ISO 26262, which is the standard that define the reliability constraints for automotive applications. The talk will focus on the reliability of object-detection algorithm and convolution neutral networks (including YOLO, Faster RCNN, and ResNet). We will understand how to identify radiation-induced errors in GPUs and distinguish between tolerable errors and critical errors.
After a brief description of radiation effects at physical level we will show the real impact of neutrons in CNNs by presenting accelerated neutron beam results that correspond to more than 150,000 years of natural exposure. Our data demonstrates that most of radiation-induced errors in CNNs can be tolerated, even in safety-critical applications. By hardening only critical error sources, we will be able to increase the reliability of the application without unnecessary overhead.
BIO
Paolo Rech received his master and Ph.D. degrees from Padova University, Padova, Italy, in 2006 and 2009, respectively. He was then a Post Doc at LIRMM in Montpellier, France. Since 2012 Paolo is an associate professor at UFRGS in Brazil. He is the 2019 Rosen Scholar Fellow at the Los Alamos National Laboratory, he received the 2020 impact in society award from the Rutherford Appleton Laboratory, UK. Since 2020 Paolo is a Marie Curie Fellow at Politecnico di Torino. His main research interests include the evaluation and mitigation of radiation-induced effects in large-scale HPC centers and in autonomous vehicles for automotive applications and space explorations.