SC18: International Conference for High Performance Computing, Networking, Storage and Analysis 2018
DOI: 10.1109/sc.2018.00011
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FlipTracker: Understanding Natural Error Resilience in HPC Applications

Abstract: As high-performance computing systems scale in size and computational power, the danger of silent errors, i.e., errors that can bypass hardware detection mechanisms and impact application state, grows dramatically. Consequently, applications running on HPC systems need to exhibit resilience to such errors. Previous work has found that, for certain codes, this resilience can come for free, i.e., some applications are naturally resilient, but few studies have shown the code patterns-combinations or sequences of … Show more

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Cited by 23 publications
(9 citation statements)
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“…For (3), we use crash tests, but we can avoid them by an application characterization study. In particular, we can detect computation patterns that tolerate computation inaccuracy as in [25]. Then we set up a model to correlate those patterns and application recomputability.…”
Section: Discussionmentioning
confidence: 99%
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“…For (3), we use crash tests, but we can avoid them by an application characterization study. In particular, we can detect computation patterns that tolerate computation inaccuracy as in [25]. Then we set up a model to correlate those patterns and application recomputability.…”
Section: Discussionmentioning
confidence: 99%
“…For (2), when the application outcome is different from that of the golden run, the users can claim a silent data corruption (SDC) happens [25,70]. With the acceptance verification, many applications treat this kind of SDC as benign and ignorable.…”
Section: Discussionmentioning
confidence: 99%
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“…These crucial facts lead to increasing importance of and challenges for developing efficient and effective fault tolerance designs for scaling HPC systems [4], [5]. There are numerous fault tolerance techniques proposed to protect MPI application execution from system failures.…”
Section: Introductionmentioning
confidence: 99%