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

Formal Analysis of SEU Mitigation for Early Dependability and Performability Analysis of FPGA-based Space Applications