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Nosayba El-Sayed
Researcher at Emory University
Publications - 19
Citations - 666
Nosayba El-Sayed is an academic researcher from Emory University. The author has contributed to research in topics: Cache & Efficient energy use. The author has an hindex of 9, co-authored 19 publications receiving 524 citations. Previous affiliations of Nosayba El-Sayed include Kuwait University & Qatar Computing Research Institute.
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Proceedings ArticleDOI
Temperature management in data centers: why some (might) like it hot
TL;DR: A multi-faceted study of temperature management in data centers using a large collection of field data from different production environments to study the impact of temperature on hardware reliability, including the reliability of the storage subsystem, the memory subsystem and server reliability as a whole.
Proceedings ArticleDOI
Reading between the lines of failure logs: Understanding how HPC systems fail
TL;DR: This paper uses a decade worth of field data made available by Los Alamos National Lab to study the impact of a diverse set of factors on the reliability of HPC systems, and provides insights into the nature of correlations between failures.
Proceedings ArticleDOI
KPart: A Hybrid Cache Partitioning-Sharing Technique for Commodity Multicores
Nosayba El-Sayed,Anurag Mukkara,Po-An Tsai,Harshad Kasture,Harshad Kasture,Xiaosong Ma,Daniel Sanchez +6 more
TL;DR: KPart is presented, a hybrid cache partitioning-sharing technique that sidesteps the limitations of way-partitioning and unlocks significant performance on current systems, and achieves most of the performance of more advanced partitioning techniques that are not yet available in hardware.
Proceedings ArticleDOI
Learning from Failure Across Multiple Clusters: A Trace-Driven Approach to Understanding, Predicting, and Mitigating Job Terminations
TL;DR: A machine learning-based framework for predicting job and task terminations is designed and shown that job failures can be predicted relatively early with high precision and recall, and also identify attributes that have strong predictive power of job failure.
Proceedings ArticleDOI
P-Store: An Elastic Database System with Predictive Provisioning
Rebecca Taft,Nosayba El-Sayed,Marco Serafini,Yu Lu,Ashraf Aboulnaga,Michael Stonebraker,Ricardo Mayerhofer,Francisco Andrade +7 more
TL;DR: P-Store is presented, the first elastic OLTP DBMS to use prediction, and it is shown that P-Store outperforms a reactive system on B2W's workload by causing 72% fewer latency violations, and achieves performance comparable to static allocation for peak demand while using 50% fewer servers.