Using Input-to-Output Masking for System-Level Vulnerability Estimation in High-Performance Processors

In this paper, we enhance previously suggested vulnerability estimation techniques by presenting a detailed modeling technique based on Input-to-Output Masking (IOM). Moreover we use our model to compute the System-level Vulnerability Factor (SVF) for data-path components in a highperformance processor. As we show, recent suggested estimation techniques overlook the issue of error masking, mainly focusing on time periods in which an error could potentially propagate in the system. In this work we show that this is incomplete as it ignores the masking impact. Our results show that including the IOM factor can significantly affect the system-level vulnerability for data-path components. As a case study, we analyze the IOM factor for CPUs with different configurations. Our results show that the average variation of the IOM factor is less than 5%. Meantime, the IOM factor varies between 24% to 76% for the applications studied here. Accordingly we find the IOM factor to be less configuration dependent and mainly workload dependent.