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MH-QEMU: Memory-State-Aware Fault Injection Platform

Authors: Hideyuki Jitsumoto; Yuya Kobayashi; Akihiro Nomura 0002; Satoshi Matsuoka;

MH-QEMU: Memory-State-Aware Fault Injection Platform

Abstract

As we move towards higher-density, larger-scale, and lower-power computing hardware, new types of failures are being experienced with increasing frequency. Hardware designed for the post-Moore generation are also bringing about novel resiliency challenges. In order to improve the efficiency of resiliency methods, fault injection plays an important role in understanding how errors affect the OS and application. Memory-state-aware fault injection, in particular, can be used to investigate the memory-related faults caused by using current and future hardware under extreme conditions and assess the costs/benefit trade-off of resiliency methods. We introduce MH-QEMU, a memory-state-aware fault injection platform implemented by extending a virtual machine (VM) to intercepting memory accesses. MH-QEMU supports collecting the physical and virtual addresses of memory accesses and defining appropriate injections condition using the collected information. MH-QEMU incurs a \(3.4{\times }\) overhead, and we demonstrate how row-hammer faults can be injected using MH-QEMU to analyzing the resiliency modified NPB CG’s algorithm.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
hybrid