… A SVM classifier is learned by the signature of residue to detect soft errors [17]. MACORD,
an adaptive, online and machine learning based SDC detection framework is proposed to …

… , we test parallel solvers in a simple resilience framework with emulated silent errors. As in
previous … MACORD: online adaptive machine learning framework for silent error detection. In: …

… errors can lead to application/system crash or even to silent … We present a machine
learning based approach to observe a … detectors as potential predictors: • Adaptive Impact-driven …

… Many types of software-based soft error detectors have been … [9], and detectors that fit a
machine learning model around the “… (DMR) can rigorously detect silent data corruptions by …

… heart of DOE application codes to be more adaptive, usually through the use of simple …
MACORD) [210] presents a SciMLbased framework for detecting silent errors in HPC machines…

… This paper shows an average error detection of 90% considering … an online adaptive SDC
detection algorithm using machine … exploration framework using machine learning supervised …

… [27] proposed a machine learning based detection method in terms of the AID … Cappello,
“Macord: Online adaptive machine learning framework for silent error detection,” in 2017 IEEE …

… Subasi O, Di S, Balaprakash P et al (2017) MACORD: online adaptive machine learning
framework for silent error detection. In: Proceedings of 2017 IEEE international conference on …

… A good example would be Silent Data Corruption (SDC) errors … detection methods have
been proposed such as Adaptive … -driven approaches via machine learning techniques can be …

… (DMR) can rigorously detect silent data corruptions by utilizing a … unlike those are generated
through machine learning [45… AID is an adaptive SDC detector wherein a best-fit prediction …