Reliability Analysis Of Complex Models Using Sure Bounds

As computer and communications systems become more complex it becomes increasingly more difficult to analyze their hardware reliability, because simple models may fail to adequately capture subtle but important model features. This paper describes a number of ways we have addressed this problem for analyses based upon White's SURE theorem. We point out how reliability analysis based on SURE mathematics can be extracted from a general C language description of the model behavior, how it can attack very large problems by accepting recomputation in order to reduce memory usage, how such analysis can be parallelized both on multiprocessors and on networks of ordinary workstations, and observe excellent performance gains by doing so. We also discuss how the SURE theorem supports efficient Monte Carlo based estimation of reliability, and show the advantages of the method. Reliability, Markov modeling.