Formal analysis of SEU mitigation for early dependability and performability analysis of FPGA-based space applications

Abstract

SRAM-based FPGAs are increasingly popular in the aerospace industry due to their field programmability and low cost. However, they suffer from cosmic radiation induced Single Event Upsets (SEUs). In safety-critical applications, the dependability of the design is a prime concern since failures may have catastrophic consequences. An early analysis of the relationship between dependability metrics, performability-area trade-off, and different mitigation techniques for such applications can reduce the design effort while increasing the design confidence. This paper introduces a novel methodology based on probabilistic model checking, for the analysis of the reliability, availability, safety and performance-area tradeoffs of safety-critical systems for early design decisions. Starting from the high-level description of a system, a Markov reward model is constructed from the Control Data Flow Graph (CDFG) and a component characterization library targeting FPGAs. The proposed model and exhaustive analysis capture all the failure states (based on the fault detection coverage) and repairs possible in the system. We present quantitative results based on an FIR filter circuit to illustrate the applicability of the proposed approach and to demonstrate that a wide range of useful dependability and performability properties can be analyzed using the proposed methodology. The modeling results show the relationship between different mitigation techniques and fault detection coverage, exposing their direct impact on the design for early decisions.