Reliability analysis of complex models using SURE bounds

As computer and communication systems become more complex it becomes increasingly more difficult to analyze their hardware reliability, because simple models can fail to adequately-capture subtle but important features. This paper describes several ways the authors have addressed this problem for analyses based upon White's SURE theorem. They show: how reliability analysis based on SURE mathematics 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 obtain excellent performance gains by doing so; how the SURE theorem supports efficient Monte Carlo based estimation of reliability; and the advantages of the method. Empirical studies of large models solved using these methods show that they are effective in reducing the solution-time of large complex problems