Exploring the Synergy of Emerging Workloads and Silicon Reliability Trends

Technology constraints and application characteristics are radically changing as we scale to the end of silicon technology. Devices are becoming increasingly brittle, highly varying in their properties, and error-prone, leading to a fundamentally unpredictable hardware substrate. Applications are also changing, and emerging new classes of applications are increasingly relying on probabilistic methods. They have an inherent tolerance for uncertainty and can tolerate hardware errors. This paper explores this synergy between application error tolerance and hardware uncertainity. Our key insight is to expose device-level errors up the system stack instead of masking them. Using a compiler instrumentation-based fault-injection methodology, we study the behavior of a set of PARSEC benchmarks under different error rates. Our methodology allows us to run programs to completion, and we quantitatively measure quality degradation in the programs’ output using application-specific quality metrics. Our results show that many applications have a high tolerance to errors. Injecting errors into individual static instructions at rates of 1% and higher, we find that between 70% to 95% of those instructions cause only minimal degradation in the quality of the program’s output. Based on a detailed analysis of these programs, we propose light-weight application-agnostic mechanisms in hardware to mitigate the impact of errors.