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UID:submissions.supercomputing.org_SC22_sess275_rpost186@linklings.com
SUMMARY:A Multifaceted Approach to Automated I/O Bottleneck Detection for 
 HPC Workloads
DESCRIPTION:Posters, Research Posters\n\nA Multifaceted Approach to Automa
 ted I/O Bottleneck Detection for HPC Workloads\n\nYildirim, Devarajan, Kou
 gkas, Sun, Mohror\n\nReal-world HPC workloads impose a lot of pressure on 
 storage systems as they are highly data dependent. On the other hand, as a
  result of recent developments in storage hardware, it is expected that th
 e storage diversity in upcoming HPC systems will grow. This growing comple
 xity in the storage system presents challenges to users, and often results
  in I/O bottlenecks due to inefficient usage. There have been several stud
 ies on reducing I/O bottlenecks. The earliest attempts worked to solve thi
 s problem by combining I/O characteristics with expert insight. The recent
  attempts rely on the performance analysis from the I/O characterization t
 ools. However, the problem is multifaceted with many metrics to consider, 
 hence difficult to do manually, even for experts. In this work, we develop
  a methodology that produces a multifaceted view of the I/O behavior of a 
 workload to identify potential I/O bottlenecks automatically.\n\nRegistrat
 ion Category: Tech Program Reg Pass, Exhibits Reg Pass
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