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First CE Matters: On the Importance of Long Term Properties on Memory Failure Prediction by Bogatinovski, Jasmin; Yu, Qiao; Cardoso, Jorge; Kao, Odej is a scholarly article available to read on EtoBox.

What is First CE Matters: On the Importance of Long Term Properties on Memory Failure Prediction about?

Dynamic random access memory failures are a threat to the reliability of data centres as they lead to data loss and system crashes. Timely predictions of memory failures allow for taking preventive measures such as server migration and memory replacement. Thereby, memory failure prediction prevents failures from externalizing, and it is a vital task to improve system reliability. In this paper, we revisited the problem of memory failure prediction. We analyzed the correctable errors (CEs) from hardware logs as indicators for a degraded memory state. As memories do not always work with full occupancy, access to faulty memory parts is time distributed. Following this intuition, we observed that important properties for memory failure prediction are distributed through long time intervals. In contrast, related studies, to fit practical constraints, frequently only analyze the CEs from the last fixed-size time interval while ignoring the predating information. Motivated by the observed discrepancy, we study the impact of including the overall (long-range) CE evolution and propose novel features that are calculated incrementally to preserve long-range properties. By coupling the extract

Author

Bogatinovski, Jasmin; Yu, Qiao; Cardoso, Jorge; Kao, Odej

Published

2022

Language

EN