BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20250822T115806Z
LOCATION:Room 5.0A52
DTSTART;TZID=Europe/Stockholm:20250618T140000
DTEND;TZID=Europe/Stockholm:20250618T143000
UID:submissions.pasc-conference.org_PASC25_sess127_msa216@linklings.com
SUMMARY:Monitoring and Analysis of Energy Consumption in HPC Systems
DESCRIPTION:Mario Bielert (ZIH, CIDS, TU Dresden)\n\nEnergy efficiency is 
 a critical challenge in modern data centers facing an ever-growing scale a
 nd complexity. This talk presents energy monitoring and analysis strategie
 s employed in the data center of the TU Dresden. The focus is on how energ
 y consumption and other metrics are measured and analyzed across different
  levels, including the building infrastructure, HPC clusters and racks, as
  well as down to individual nodes. We will provide insights into practical
  challenges and solutions for monitoring HPC systems and offer a perspecti
 ve on how such tools and techniques contribute to improving energy efficie
 ncy and sustainability in large-scale computing environments. We outline t
 he methodology behind capturing comprehensive measurement data to better u
 nderstand consumption patterns and enable system-level optimizations. This
  process includes integrating sensor data and metrics from various sources
  within the data center to provide a comprehensive view of energy usage. A
  key component of our approach is using MetricQ, an in-house developed, hi
 ghly scalable, distributed metric data processing framework. MetricQ suppo
 rts scalable, high-resolution data collection and real-time visualization,
  allowing us to analyze trends in order to identify inefficiencies accurat
 ely. Its responsiveness facilitates iterative exploration in many long-run
 ning data sets.\n\nDomain: Engineering, Computational Methods and Applied 
 Mathematics\n\nSession Chair: Lubomir Riha (IT4Innovations National Superc
 omputing Center, VSB-TU Ostrava)\n\n
END:VEVENT
END:VCALENDAR