Future microprocessors need low-cost solutions for reliable operation in the presence of failure-prone devices. A promising approach is to detect hardware faults by deploying low-cost monitors of software-level symptoms of such faults. Recently, researchers have shown these mechanisms work well, but there remains a nonnegligible risk that several faults may escape the symptom detectors and result in silent data corruptions (SDCs). Most prior evaluations of symptom-based detectors perform fault injection campaigns on application benchmarks, where each run simulates the impact of a fault injected at a hardware site at a certain point in the application’s execution (application fault site). Since the total number of application fault sites is very large (trillions for standard benchmark suites), it is not feasible to study all possible faults. Previous work therefore typically studies a randomly selected sample of faults. Such studies do not provide any feedback on the portions of the ...
Siva Kumar Sastry Hari, Sarita V. Adve, Helia Naei