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UID:submissions.supercomputing.org_SC23_sess180@linklings.com
SUMMARY:Resource Management
DESCRIPTION:Mirage: Toward Low-interruption Services on Batch GPU Clusters
  with Reinforcement Learning\n\nAccommodating long-running deep learning (
 DL) training and inference jobs is challenging on GPU clusters that use tr
 aditional batch schedulers, such as Slurm. Given fixed wall clock time lim
 its, DL researchers usually need to run a sequence of batch jobs and exper
 ience long interruptions on overload...\n\n\nQiyang Ding (University of Te
 xas), Pengfei Zheng (University of Wisconsin), Shreyas Kudari (University 
 of Texas), Shivaram Venkataraman (University of Wisconsin), and Zhao Zhang
  (Texas Advanced Computing Center (TACC))\n---------------------\nProdigy:
  Toward Unsupervised Anomaly Detection in Production HPC Systems\n\nPerfor
 mance variations caused by anomalies in modern High Performance Computing 
 (HPC) systems lead to decreased efficiency, impaired application performan
 ce, and increased operational costs. While machine learning (ML)-based fra
 meworks for automated anomaly detection (often based on time series tele..
 .\n\n\nBurak Aksar (Boston University, Sandia National Laboratories); Efe 
 Sencan (Boston University); Benjamin Schwaller, Omar Aaziz, Vitus J. Leung
 , and Jim Brandt (Sandia National Laboratories); and Brian Kulis, Manuel E
 gele, and Ayse K. Coskun (Boston University)\n---------------------\nDPS: 
 Adaptive Power Management for Overprovisioned Systems\n\nMaximizing perfor
 mance under a power budget is essential for HPC systems and has inspired t
 he development of many power management frameworks.  These can be broadly 
 characterized into two groups: model-based and stateless.  Model-based fra
 meworks achieve good performance under a power budget but are...\n\n\nJian
 ru Ding and Henry Hoffmann (University of Chicago)\n\nTag: Architecture an
 d Networks, Performance Measurement, Modeling, and Tools, Resource Managem
 ent\n\nRegistration Category: Tech Program Reg Pass\n\nReproducibility Bad
 ges: Artifact Available, Artifact Functional, Results Reproduced\n\nSessio
 n Chair: Ann Gentile (Sandia National Laboratories)
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