Exploiting Application-Level Correctness for Low-Cost Fault Tolerance

Traditionally, fault tolerance researchers have required architectural state to be numerically perfect for program execution to be correct. However, in many programs, even if execution is not 100 % numerically correct, the program can still appear to execute correctly from the user’s perspective. Hence, whether a fault is unacceptable or benign may depend on the level of abstraction at which correctness is evaluated, with more faults being benign at higher levels of abstraction, i.e. at the user or application level, compared to lower levels of abstraction, i.e. at the architecture level. The extent to which programs are more fault resilient at higher levels of abstraction is application dependent. Programs that produce inexact and/or approximate outputs can be very resilient at the application level. We call such programs soft computations, and we find they are common in multimedia workloads, as well as artificial intelligence (AI) workloads. Programs that compute exact numerical outputs offer less error resilience at the application level. However, we find all programs studied in this paper exhibit some enhanced fault resilience at the application level, including those that are traditionall