Predicting DRAM reliability in the field with machine learning
Author:
Affiliation:
1. IBM Research - Zurich
2. IBM Technology Support Services
Publisher
ACM Press
Reference23 articles.
1. G. Fu D. Chen Z. Dimitrijevic D. Lie D. Devi A. Riska A. Messer, P. Bernadat and D. Milojicic. 2004. Susceptibility of Commodity Systems and Software to Memory Soft Errors.IEEE Trans. Comput.53, 12 (2004).
2. R. Baumann. 2005. Soft Errors in Advanced Computer Systems.IEEE Design and Test of Computers(2005), 258--266.
3. Mirela Botezatu, Ioana Giurgiu, Jasmina Bogojeska, and Dorothea Wiesmann. 2016. Predicting Disk Replacement towards Reliable Data Centers. InCIKM.39--48.
4. Leo Breiman. 2001. Random Forests.Machine Learning(2001).
5. Kay H. Brodersen, Fabian Gallusser, Jim Koehler, Nicolas Remy, and Steven L. Scott. 2015. Inferring Causal Impact using Bayesian Structural Time-series Models.Annals of Applied Statistics9 (2015), 247--274.
Cited by 30 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. ML-driven risk estimation for memory failure in a data center environment with convolutional neural networks, self-supervised data labeling and distribution-based model drift determination;Journal of Parallel and Distributed Computing;2024-03
2. Exploring Error Bits for Memory Failure Prediction: An In-Depth Correlative Study;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28
3. HiMFP: Hierarchical Intelligent Memory Failure Prediction for Cloud Service Reliability;2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN);2023-06
4. EXPERT: EXPloiting DRAM ERror Types to Improve the Effective Forecasting Coverage in the Field;2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S);2023-06
5. First CE Matters: On the Importance of Long Term Properties on Memory Failure Prediction;2022 IEEE International Conference on Big Data (Big Data);2022-12-17
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3