Bayesian models for early cross-layer reliability analysis and design space exploration

Designing soft-errors resilient systems is a complex engineering task, which nowadays follows a cross-layer approach. It requires a careful planning for different fault-tolerance mechanisms at different system's layers: starting from the technology up to the software domain. While these design decisions have a positive effect on the reliability of the system, they usually have a detrimental effect on its size, power consumption, performance and cost. Design space exploration for cross-layer reliability is therefore a multi-objective search problem in which reliability must be traded-off with other design dimensions. Assessing the reliability of a complex system and performing design space exploration in the early phases of the design cycle is a complex task and designers are increasing looking at stochastic models able to provide fast results to quickly drive early design decisions. This paper summarizes some of the results achieved by the authors in more than five years of research in this domain.