Abstract. In this paper, the results of an experimental study on the error sensitivities of application data are presented. We develop a portable software-implemented fault-injection (SWIFI) tool that, on top of performing single-bit flip fault injections and capturing their effects on application behavior, is also data-level aware and tracks the corrupted application data to report their high-level characteristics (usage type, size, user, memory space location). After extensive testing of NPB-serial (7.8M fault injections), we are able to characterize the sensitivities of data based on their high-level characteristics. Moreover, we conclude that application data are error sensitive in parts; depending on their type, they have distinct and wide less-sensitive bit ranges either at the MSBs or LSBs. Among other uses, such gained insight could drive the development of sensitivity-aware protection mechanisms of application data.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.