GemV: A Validated Micro-architecture Vulnerability Estimation Tool

abstract: Several decades of transistor technology scaling has brought the threat of soft errors to modern embedded processors. Several techniques have been proposed to protect these systems from soft errors. However, their effectiveness in protecting the computation cannot be ascertained without accurate and quantitative estimation of system reliability. Vulnerability -- a metric that defines the probability of system-failure (reliability) through analytical models -- is the most effective mechanism for our current estimation and early design space exploration needs. Previous vulnerability estimation tools are based around the Sim-Alpha simulator which has been to shown to have several limitations. In this thesis, I present gemV: an accurate and comprehensive vulnerability estimation tool based on gem5. Gem5 is a popular cycle-accurate micro-architectural simulator that can model several different processor models in close to real hardware form. GemV can be used for fast and early design space exploration and also evaluate the protection afforded by commodity processors. gemV is comprehensive, since it models almost all sequential components of the processor. gemV is accurate because of fine-grain vulnerability tracking, accurate vulnerability modeling of squashed instructions, and accurate vulnerability modeling of shared data structures in gem5. gemV has been thoroughly validated against extensive fault injection experiments and achieves a 97\% accuracy with 95\% confidence. A micro-architect can use gemV to discover micro-architectural variants of a processor that minimize vulnerability for allowed performance penalty. A software developer can use gemV to explore the performance-vulnerability trade-off by choosing different algorithms and compiler optimizations, while the system designer can use gemV to explore the performance-vulnerability trade-offs of choosing different Insruction Set Architectures (ISA).Dissertation/ThesisMasters Thesis Computer Science 201