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DTSTART;TZID=America/Denver:20231112T092600
DTEND;TZID=America/Denver:20231112T094300
UID:submissions.supercomputing.org_SC23_sess422_ws_hpcsysp102@linklings.co
 m
SUMMARY:Self-Service Monitoring of HPC and Openstack Jobs for Users
DESCRIPTION:Simon Guilbault (Université Laval)\n\nUsing correctly the comp
 ute capacity of an HPC or Openstack cluster is often a stumbling block for
  users, especially those from non-traditional domains where a cluster is o
 nly a tool and not the subject of their research.<br /> <br />This paper d
 escribes a web portal called TrailblazingTurtle built for HPC and Openstac
 k Cluster to let users view the resources used and wasted by their jobs, w
 ithout having to modify their workflow. The metrics are collected from var
 ious data sources on the cluster to enable monitoring at the job and VM le
 vel and are presented to the users and staff members as a simple web appli
 cation. This platform makes it easy for newer users to request the correct
  quantity of computing resources for their work, see their impact on the s
 hared file system, and the evolution of the priority of their group in Slu
 rm.\n\nTag: Artificial Intelligence/Machine Learning, Cloud Computing, Dis
 tributed Computing, Data Analysis, Visualization, and Storage, Data Moveme
 nt and Memory, Fault Handling and Tolerance, I/O and File Systems, Large S
 cale Systems, Performance Optimization, Resource Management, Security, Sta
 te of the Practice\n\nRegistration Category: Workshop Reg Pass\n\nSession 
 Chairs: Matt Bidwell (National Renewable Energy Laboratory (NREL)) and Joh
 n Blaas (National Center for Atmospheric Research (NCAR))\n\n
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