With continued CMOS scaling, future shipped hardware will be increasingly vulnerable to in-the-field faults. To be broadly deployable, the hardware reliability solution must incur low overheads, precluding use of expensive redundancy. We explore a cooperative hardware-software solution that watches for anomalous software behavior to indicate the presence of hardware faults. Fundamental to such a solution is a characterization of how hardware faults in different microarchitectural structures of a modern processor propagate through the application and OS.This paper aims to provide such a characterization, resulting in identifying low-cost detection methods and providing guidelines for implementation of the recovery and diagnosis components of such a reliability solution. We focus on hard faults because they are increasingly important and have different system implications than the much studied transients. We achieve our goals through fault injection experiments with a microarchitecture-level full system timing simulator. Our main results are: (1) we are able to detect 95% of the unmasked faults in 7 out of 8 studied microarchitectural structures with simple detectors that incur zero to little hardware overhead; (2) over 86% of these detections are within latencies that existing hardware checkpointing schemes can handle, while others require software checkpointing; and (3) a surprisingly large fraction of the detected faults corrupt OS state, but almost all of these are detected with latencies short enough to use hardware checkpointing, thereby enabling OS recovery in virtually all such cases.

In the near future, hardware is expected to become increasingly vulnerable to faults due to continuously decreasing feature size. Software-level symptoms have previously been used to detect permanent hardwarefaults. However, they can not detect a smallfraction offaults, which may lead to Silent Data Corruptions(SDCs). In this paper, we present a system that uses invariants to improve the coverage and latency of existing detection techniques for permanent faults. The basic idea is to use training inputs to create likely invariants based on value ranges of selected program variables and then use them to identifyfaults at runtime. Likely invariants, however, can have false positives which makes them challenging to use for permanent faults. We use our on-line diagnosis framework for detecting false positives at runtime and limit the number offalse positives to keep the associated overhead minimal. Experimental results using microarchitecture level fault injections in full-system simulation show 28.6% reduction in the number of undetected faults and 74.2% reduction in the number of SDCs over existing techniques, with reasonable overheadfor checking code.

Abstract

As devices continue to scale, future shipped hardware will likely fail due to in-the-field hardware faults. As traditional redundancy-based hardware reliability solutions that tackle these faults will be too expensive to be broadly deployable, recent research has focused on low-overhead reliability solutions. One approach is to employ lowoverhead ("always-on")

With continued CMOS scaling, future shipped hardware will be increasingly vulnerable to in-the-field faults. To be broadly deployable, the hardware reliability solution must incur low overheads, precluding use of expensive redundancy. We explore a cooperative hardware-software solution that watches for anomalous software behavior to indicate the presence of hardware faults. Fundamental to such a solution is a characterization of how hardware faults in different microarchitectural structures of a modern processor propagate through the application and OS.This paper aims to provide such a characterization, resulting in identifying low-cost detection methods and providing guidelines for implementation of the recovery and diagnosis components of such a reliability solution. We focus on hard faults because they are increasingly important and have different system implications than the much studied transients. We achieve our goals through fault injection experiments with a microarchitecture-level full system timing simulator. Our main results are: (1) we are able to detect 95% of the unmasked faults in 7 out of 8 studied microarchitectural structures with simple detectors that incur zero to little hardware overhead; (2) over 86% of these detections are within latencies that existing hardware checkpointing schemes can handle, while others require software checkpointing; and (3) a surprisingly large fraction of the detected faults corrupt OS state, but almost all of these are detected with latencies short enough to use hardware checkpointing, thereby enabling OS recovery in virtually all such cases.