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DTSTAMP:20260422T143138Z
LOCATION:B312-B313A
DTSTART;TZID=America/New_York:20241119T153000
DTEND;TZID=America/New_York:20241119T160000
UID:submissions.supercomputing.org_SC24_sess375_pap388@linklings.com
SUMMARY:An Evaluation of the Effect of Network Cost Optimization for Leade
 rship Class Supercomputers
DESCRIPTION:Awais Khan, John Lange, Nick Hagerty, Edwin F. Posada, John Ho
 lmen, James White, Austin Harris, Veronica Melesse Vergara, Christopher Zi
 mmer, and Scott Atchley (Oak Ridge National Laboratory (ORNL))\n\nThe Drag
 onfly is an extensively deployed network\ntopology in large-scale high-per
 formance computing (HPC) due\nto its cost-effectiveness and efficiency. In
  comparison to other in-\ndirect networks of similar scale, the Dragonfly 
 network has shown\na considerable reduction in cable lengths and network c
 osts.\nThree of the deployed and upcoming Exascale supercomputers\nfor lea
 dership, class workloads will be deployed using Dragonfly\nnetworks. \nIt 
 is imperative to evaluate its performance across\na broad range of HPC wor
 kloads to facilitate optimal system\nprocurement. While previous work has 
 focused on understanding\nthe topology from a capacity computing workload 
 perspective, this study assesses extreme-scale leadership workloads on a d
 ragonfly network. To accomplish this, we conduct a comprehensive evaluatio
 n of various workload efficiencies using state-of-the-art Slingshot 11 Dra
 gonfly topology and compare it against Summit supercomputers EDR InfiniBan
 d non-blocking fat-tree.\nThese evaluations are conducted utilizing resour
 ces at the OLCF (Frontier and Summit)\n\nTag: Accelerators, HPC Infrastruc
 ture, Performance Evaluation and/or Optimization Tools, State of the Pract
 ice\n\nRegistration Category: Tech Program Reg Pass\n\nAward Finalist: Bes
 t Paper Finalist\n\nSession Chair: Zachary Tschirhart (Sustainment)\n\n
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