  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.
