From Correctable Memory Errors to Uncorrectable Memory Errors: What Error Bits Tell
Cong Li, Yu Zhang, Jialei Wang, Hang Chen, Xian Liu, Tai Huang, Liang Peng, Shen Zhou, Lixin Wang, Shijian Ge
摘要
Uncorrectable memory errors are one of the major failure causes in datacenters. In this paper, we present an empirical study correlating correctable errors (CEs) and uncorrectable errors (UEs) using the large-scale field data across 3 major dual in-line memory module (DIMM) manufacturers from a contemporary server farm of ByteDance. Different from the previous studies, our study is the first to comprehend the error-bit information of CEs and the DIMM part numbers. Unlike the traditional chipkill error correction code (ECC), in contemporary Intel server platforms the ECC gets weakened, not able to tolerate some error-bit patterns from a single chip. Using obtainable coarse-grained ECC knowledge, we derive a new indicator from the error-bit information: risky CE occurrence in terms of ECC guaranteed coverage. From the data, we show that the new indicator has a consistently high sensitivity and specificity in the test of future UE occurrences across DIMMs from different manufacturers. This leads us to conjecture that the weakened ECC substantially contributes to many UEs today. The new risky CE indicator is then applied in predicting the future UE occurrence based on the CE history. We empirically demonstrate how practically useful predictors are constructed in conjunction with other useful attributes such as certain micro-level fault indicators and DIMM part numbers, achieving the state-of-the-art performance.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
引用它的顶会 Paper4
- Removing Obstacles before Breaking Through the Memory Wall: A Close Look at HBM Errors in the FieldRonglong Wu, Shuyue Zhou, Jiahao Lu, Zhirong Shen 等USENIX ATC 2024 · 被引用 17 次
- Reinforcement Learning-based Adaptive Mitigation of Uncorrected DRAM Errors in the FieldIsaac Boixaderas, Sergi Moré, Javier Bartolome, David Vicente 等HPDC 2024 · 被引用 1 次
- Cerberus: Cross-Layer ECC Co-Design for Robust and Efficient Memory ProtectionJunhwan Kim, Seunghyun Kim, Yesin Ryu, Saeid Gorgin 等ISCA 2026 · 被引用 1 次
- RangeGuard: Efficient, Bounded Approximate Error Correction for Reliable DNNsHanum Ko, Sangheum Yeon, Jong Hwan Ko, Jungrae KimISCA 2026
相关 Paper
- Predicting DRAM Failures at Scale: A Two-Stage Approach for Heterogeneous SystemsChenglin Wang, Shouxin Wang, Zhirong Shen, Lu Tang 等HPCA 2026
- Bit-Exact ECC Recovery (BEER): Determining DRAM On-Die ECC Functions by Exploiting DRAM Data Retention CharacteristicsMinesh Patel, Jeremie S. Kim, Taha Shahroodi, Hasan Hassan 等MICRO 2020 · 被引用 55 次
- Unity ECC: Unified Memory Protection Against Bit and Chip ErrorsDongwhee Kim, Jaeyoon Lee, Wonyeong Jung, Michael B. Sullivan 等SC 2023 · 被引用 23 次
- Polymorphic Error CorrectionEvgeny Manzhosov, Simha SethumadhavanMICRO 2024 · 被引用 1 次
- CARE: Coordinated Augmentation for Elastic Resilience on DRAM Errors in Data CentersJian Chen, Xiaowei Jiang, Ying Zhang, Liyin Liu 等HPCA 2021 · 被引用 9 次
