Extracting Useful Computation From Error-Prone Processors For Streaming Applications
As semiconductor fabrics scale closer to fundamental physical limits, their reliability is decreasing due to process variation, noise margin effects, aging effects, and increased susceptibility to soft errors. Reliability can be regained through redundancy, error checking with recovery, voltage scaling and other means, but these techniques impose area/energy costs. Since some applications (e.g. media) can tolerate limited computation errors and still provide useful results, error-tolerant computation models have been explored, with both the application and computation fabric having stochastic characteristics.