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BEGIN:VEVENT
DTSTAMP:20261003T013345Z
UID:CDE7A4F4-6B89-4AB0-BC3D-59003F25B58C
DTSTART;TZID=America/Los_Angeles:20261002T163000
DTEND;TZID=America/Los_Angeles:20261002T173000
DESCRIPTION:Recent studies predict that power demand per rack in data cente
 rs could increase from approximately 100 kW to 1 MW\, while the overall el
 ectricity demand associated with “AI factories” could reach 1\,000 TWh
  annually by 2030. These trends are creating an emerging “Power Wall” 
 that cannot be addressed through conventional approaches alone.\n\nIn this
  talk\, Dr. Don Tan will explore the technical challenges and emerging sol
 utions associated with powering AI infrastructure. Topics will include pow
 er conversion and distribution\, thermal management\, networking\, energy-
 efficient computing architectures\, microgrids\, UPS systems\, and next-ge
 neration power processing technologies. The discussion will also introduce
  Flexible electronic Large Power Transformers (FeLPTs) and examine their p
 otential role in interfacing large data centers with the electrical grid.\
 n\nThe session will provide students\, researchers\, engineers\, and indus
 try professionals with an overview of how advances across power electronic
 s and energy systems may help address the rapidly increasing power require
 ments of AI computing.\n\nSpeaker(s): Dr. Don Tan\, \n\nRoom: KAIS 2020\, 
 Bldg: Kaiser\, 2332 Main Mall\, Vancouver\, British Columbia\, Canada\, V6
 T 1Z4
LOCATION:Room: KAIS 2020\, Bldg: Kaiser\, 2332 Main Mall\, Vancouver\, Brit
 ish Columbia\, Canada\, V6T 1Z4
ORGANIZER:malinda@ieee.org
SEQUENCE:18
SUMMARY:Kaiser Chair Talk Series Sponsored by IEEE PELS: Data Center Challe
 nges: Powering “the AI Factories”
URL;VALUE=URI:https://events.vtools.ieee.org/m/577185
X-ALT-DESC:Description: <br /><p class="PDq2pG_selectionAnchorContainer" da
 ta-start="623" data-end="1011">Recent studies predict that power demand pe
 r rack in data centers could increase from approximately <strong data-star
 t="723" data-end="741">100 kW to 1 MW</strong>\, while the overall electri
 city demand associated with &ldquo\;AI factories&rdquo\; could reach <stro
 ng data-start="823" data-end="853">1\,000 TWh annually by 2030</strong>. T
 hese trends are creating an emerging <strong data-start="893" data-end="90
 9">&ldquo\;Power Wall&rdquo\;</strong> that cannot be addressed through co
 nventional approaches alone.</p>\n<p data-start="1013" data-end="1576">In 
 this talk\, Dr. Don Tan will explore the technical challenges and emerging
  solutions associated with powering AI infrastructure. Topics will include
  <strong data-start="1164" data-end="1351">power conversion and distributi
 on\, thermal management\, networking\, energy-efficient computing architec
 tures\, microgrids\, UPS systems\, and next-generation power processing te
 chnologies</strong>. The discussion will also introduce <strong data-start
 ="1388" data-end="1445">Flexible electronic Large Power Transformers (FeLP
 Ts)</strong> and examine their potential role in interfacing large data ce
 nters with the electrical grid.</p>\n<p data-start="1578" data-end="1816">
 The session will provide students\, researchers\, engineers\, and industry
  professionals with an overview of how advances across power electronics a
 nd energy systems may help address the rapidly increasing power requiremen
 ts of AI computing.</p>
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