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DTSTART:19700308T020000
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DTSTART:19701101T020000
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DTSTAMP:20260202T201259Z
LOCATION:Second Floor Atrium
DTSTART;TZID=America/Chicago:20251121T080000
DTEND;TZID=America/Chicago:20251121T120000
UID:submissions.supercomputing.org_SC25_sess620_post256@linklings.com
SUMMARY:Unmasking Performance Variability in GPU Codes on Supercomputers
DESCRIPTION:Cunyang Wei and Keshav Pradeep (University of Maryland, Colleg
 e Park) and Abhinav Bhatele (University of Maryland)\n\nPerformance variab
 ility is often a critical issue on GPU-accelerated systems, undermining ef
 ficiency and reproducibility. Since large-scale investigations of performa
 nce variability on GPU clusters are lacking, we set up a longitudinal expe
 riment on Perlmutter and Frontier. We benchmark representative HPC and AI 
 applications and collect detailed performance data to assess the impact of
  compute variability, allocated node topology, and network conditions on o
 verall runtime. We also use an ML-based approach to identify potential cor
 relations between these factors and to forecast the execution time. Our an
 alysis identifies network performance as the dominant source of runtime va
 riability. These findings provide crucial insights that can inform the dev
 elopment of future mitigation strategies.\n\nTag: Research & ACM SRC Poste
 rs\n\nRegistration Category: Technical Program Reg Pass\n\nSession Chairs:
  Kento Sato (RIKEN Center for Computational Science (R-CCS)); Anja Gerbes 
 (Georg-August-Universität Göttingen); and Chris Schlipalius (Pawsey Superc
 omputing Research Centre; Commonwealth Scientific and Industrial Research 
 Organisation (CSIRO), Australia)\n\n
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