During the RAPIDO workshop some relevant personalities of our community will held a keynote.
Abstract Abstract TBD
Short CV Nikil D. Dutt is a Chancellor’s Professor at the University of California, Irvine, with academic appointments in the CS, EECS, and Cognitive Sciences departments. He received a B.E.(Hons) in Mechanical Engineering from the Birla Institute of Technology and Science, Pilani, India in 1980, an M.S. in Computer Science from the Pennsylvania State University in 1983, and a Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign in 1989. He is affiliated with the following Centers at UCI: Center for Embedded Computer Systems (CECS), Center for Cognitive Neuroscience and Engineering (CENCE), California Institute for Telecommunications and Information Technology (Calit2), the Center for Pervasive Communications and Computing (CPCC), and the Laboratory for Ubiquitous Computing and Interaction (LUCI). Professor Dutt’s research interests are in embedded systems, electronic design automation, computer architecture, optimizing compilers, system specification techniques, distributed systems, formal methods, and brain-inspired architectures and computing.
Abstract Cross-layer approach is becoming the preferred solution when reliability is a concern in the design of a microprocessor-based system. Nevertheless, deciding how to distribute the error management across the different layers of the system is a very complex task that requires the support of dedicated frameworks for cross-layer reliability analysis. In other words, the designer has to know what are the “critical” components of the system in order to properly introduce error management mechanisms. Unfortunately, system-level reliability estimation is a complex task that usually requires huge simulation campaign. This presentation aims at proposing a cross-layer system-level reliability analysis framework for soft-errors in microprocessor-based systems. The framework exploits a multi-level hybrid Bayesian model to describe the target system and takes advantage of Bayesian inference to estimate different reliability metrics. Experimental results, carried out on different microprocessor architectures (i.e., Intel x86, ARM Cortex-A15, ARM Cortex-A9), show that the simulation time is significantly lower than state-of-the-art fault-injection experiments with an accuracy high enough to take effective design decision.
Short CV Alberto Bosio received the PhD in Computer Engineering from Politecnico di Torino in Italy in 2006 and the HDR (Habilitation Diriger les Recherches) in 2015 from the University of Montpellier (France). Currently he is an associate professor in the Laboratory of Informatics, Robotics and Microelectronics of Montpellier (LIRMM)-University of Montpellier 2 in France. He has published articles in publications spanning diverse disciplines, including memory testing, fault tolerance, diagnosis and functional verification. He is an IEEE member.