Advanced Data Storage Technologies
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Examining CPU SDCs from a production-oriented perspective reveals discrepancies between traditional assumptions and practical observations, helping to explain why many existing strategies and models remain inefficient or misaligned with practice.
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Silent data corruptions (SDCs) originating from CPUs are increasingly recognized as a reliability concern in modern datacenters. Unlike crashes and exceptions, SDCs silently compromise data integrity, often remaining undetected until their impact propagates through large-scale datacenters. Despite growing awareness, existing strategies against CPU SDCs remain inefficient, in part because they are grounded in assumptions that do not fully reflect operational realities. In this article, we revisit CPU SDCs from a systematic, production-oriented perspective. Drawing on practical observations, we examine their presence in the wild, analyze patterns in corrupted data and SDC occurrence, and reassess existing strategies against CPU SDCs. Our findings reveal discrepancies between traditional assumptions and practical observations, helping to explain why many existing strategies and models remain inefficient or misaligned with practice. Based on these insights, we outline future directions for promoting the reliability of modern datacenter services.
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@article{Wang2026Revisiting,
title = {Revisiting CPU Silent Data Corruptions in Modern Datacenters},
author = {S. M. Wang and Guangyan Zhang},
journal = {Communications of the ACM},
year = {2026},
doi = {10.1145/3799406},
url = {https://doi.org/10.1145/3799406}
}FAQ
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