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. Stochastic computation has, however, largely focused on application-specific hardware solutions, and is not general enough to handle arbitrary bit errors that impact memory addressing or control in processors. In response, this paper addresses requirements for error-tolerant execution by proposing and evaluating techniques for running error-tolerant software on a general-purpose processor built from an unreliable fabric. We study the minimum error-protection required, from a microarchitecture perspective, to still produce useful results at the application output. Even with random errors as frequent as every 250 μs, our proposed design allows JPEG and MP3 benchmarks to sustain good output quality-14dB and 7dB respectively. Overall, this work establishes the potential for error-tolerant single-threaded execution, and details its required hardware/system support.