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DTSTAMP:20260522T150118Z
LOCATION:D170
DTSTART;TZID=America/Chicago:20181112T144000
DTEND;TZID=America/Chicago:20181112T150000
UID:submissions.supercomputing.org_SC18_sess169_ws_daac103@linklings.com
SUMMARY:Simulating Data Centers with Redfish-Enabled Equipment
DESCRIPTION:Ali Akbar Nosrati, Alan Sill, and Yong Chen (Texas Tech Univer
 sity)\n\nAnalytic data, such as temperature and power consumption of equip
 ment, are becoming growingly critical in high-end enterprise and also in h
 igh-performance computing platforms, especially for current petascale and 
 future exascale systems on the horizon, consisting of tens of thousands or
  even hundreds of thousands of servers. Also, these data are important for
  accurate and real-time system monitoring.  Examining new ideas for data g
 athering, data analysis and systems management by running different tests 
 against production data center could negatively affect the production envi
 ronment and also could have unintentional consequences. For these reasons,
  a simulated data center can enable researchers, developers, and administr
 ators to perform thorough tests before carrying out on a real data center 
 or even to eliminate the need for physical examination. This research aims
  to discuss a new methodology and a framework we have developed via using 
 container technology to simulate a scalable data center with Redfish-enabl
 ed equipment to achieve the objectives.\n\nTag: Build Systems, Clouds and 
 Distributed Computing, Data Analytics, Deep Learning, Education, HPC Cente
 r Planning and Operations, Heterogeneous Systems, Resource Management, Sch
 eduling, Scientific Computing, State of the Practice, Visualization, HPC, 
 Containers, Datacenter, Industry, monitoring\n\nRegistration Category: Wor
 kshop Reg Pass\n\nSession Chairs: Yong Chen (Texas Tech University), Tim C
 ockerill (Texas Advanced Computing Center (TACC)), Dong Dai (University of
  Delaware), and Alan Sill (Texas Tech University)\n\n
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