Finding resilience-friendly compiler optimizations using meta-heuristic search techniques

With the projected increase in hardware error rates in the future, software needs to be resilient to hardware faults. An important factor affecting a program's error resilience is the set of optimizations used when compiling it. Compiler optimizations typically optimize for performance or space, and rarely for error resilience. However, prior work has found that applying optimizations injudiciously can lower the program's error resilience as they often eliminate redundancy in the program. In this work, we propose automated techniques to find the set of compiler optimizations that can boost performance without degrading its overall resilience. Due to the large size of the search space, we use search heuristic algorithms to efficiently explore the space and find an optimal sequence of optimizations for a given program. We find that the resulting optimization sequences have significantly higher error resilience than the standard optimization levels (i.e., O1, O2, O3), while attaining comparable performance improvements with the optimizations levels. We also find that the resulting sequences reduce the overall vulnerability of the applications compared to the standard optimization levels.Applied Science, Faculty ofElectrical and Computer Engineering, Department ofGraduat