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Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning.

, , , , , , , , и . IEEE Trans. Parallel Distributed Syst., 35 (4): 693-706 (апреля 2024)

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Omar Ahmad-Omar

Nora Omar Mahmoud

Sanaa Hamdy Omar

Ahmed Said Omar

Salah Ibrahim Omara Tayel

 

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A Methodology for Characterizing the Correspondence Between Real and Proxy Applications., , , , , и . CLUSTER, стр. 190-200. IEEE Computer Society, (2018)Runtime Performance Anomaly Diagnosis in Production HPC Systems Using Active Learning., , , , , , , , и . IEEE Trans. Parallel Distributed Syst., 35 (4): 693-706 (апреля 2024)Proctor: A Semi-Supervised Performance Anomaly Diagnosis Framework for Production HPC Systems., , , , , , , , и . ISC, том 12728 из Lecture Notes in Computer Science, стр. 195-214. Springer, (2021)Evaluating HPC Job Run Time Predictions Using Application Input Parameters., , , , , и . DEBS, стр. 127-138. ACM, (2023)YAViT (Yet Another Viz Tool): Raising the Level of Abstraction in End-User HPC Interactions., , и . CLUSTER, стр. 814-817. IEEE Computer Society, (2017)Proxy or Imposter? A Method and Case Study to Determine the Answer., , , и . CLUSTER, стр. 1-9. IEEE, (2019)LDMS Darshan Connector: For Run Time Diagnosis of HPC Application I/O Performance., , , и . CLUSTER, стр. 626-634. IEEE, (2022)Exploring and Quantifying How Communication Behaviors in Proxies Relate to Real Applications., , , и . PMBS@SC, стр. 12-22. IEEE, (2018)Push Me Pull You: Integrating Opposing Data Transport Modes for Efficient HPC Application Monitoring., , и . CLUSTER, стр. 674-681. IEEE Computer Society, (2015)E2EWatch: An End-to-End Anomaly Diagnosis Framework for Production HPC Systems., , , , , , и . Euro-Par, том 12820 из Lecture Notes in Computer Science, стр. 70-85. Springer, (2021)