Quantitative evaluation of soft error injection techniques for robust system design

Choosing the correct error injection technique is of primary importance in simulation-based design and evaluation of robust systems that are resilient to soft errors. Many low-level (e.g., flip-flop-level) error injection techniques are generally used for small systems due to long execution times and significant memory requirements. High-level error injections at the architecture or memory levels are generally fast but can be inaccurate. Unfortunately, there exists very little research literature on quantitative analysis of the inaccuracies associated with high-level error injection techniques. In this paper, we use simulation and emulation results to understand the accuracy tradeoffs associated with a variety of high-level error injection techniques. A detailed analysis of error propagation explains the causes of high degrees of inaccuracies associated with error injection techniques at higher levels of abstraction.