BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20250626T234543Z
LOCATION:B312
DTSTART;TZID=America/New_York:20241117T161000
DTEND;TZID=America/New_York:20241117T163000
UID:submissions.supercomputing.org_SC24_sess739_ws_ss105@linklings.com
SUMMARY:AIOps and Sustainability: Transforming Data Centers for a Greener 
 Future
DESCRIPTION:Subrahmanya Vinayak Joshi, Sergey Serebryakov, Deepak Nanjunda
 iah, Tejas Hegde, and Martin Foltin (Hewlett Packard Enterprise (HPE))\n\n
 Enterprise and high-performance computing data centers are dealing with th
 ousands of sensor metrics and associated data. A top-end target for exasca
 le machines is 10 million data points per second. The escalating volume an
 d speed of data generation are making things more difficult, and outages a
 re increasing. Uptime Institute's Outage Analysis report, published in Jun
 e 2022, states that 30% of all outages in 2021 lasted more than 24 hours, 
 a disturbing increase from 8% in 2017. While equipment is idle during down
 time, it often continues to consume power, especially for cooling systems.
  This leads to wasted energy and higher operational costs. We propose an A
 IOps solution that uses advanced data analytics, machine learning, and dee
 p learning methods to develop automated and advanced anomaly detection and
  predictive tools for data centers. They perform at scale and speed, and i
 mprove data center resiliency and energy efficiency, thereby promoting the
  sustainability of data centers.\n\nTag: Energy Efficiency, HPC Infrastruc
 ture, Sustainability\n\nRegistration Category: Workshop Reg Pass\n\nSessio
 n Chairs: Cate Berard (US Department of Energy); James H. Rogers (Oak Ridg
 e National Laboratory (ORNL)); Fumiyoshi Shoji (RIKEN, Center for Computat
 ional Science); Michèle Weiland (EPCC, The University of Edinburgh; The Un
 iversity of Edinburgh); and Mike Woodacre (Hewlett Packard Enterprise (HPE
 ))\n\n
END:VEVENT
END:VCALENDAR