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DTSTART;TZID=America/Chicago:20251117T120000
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UID:submissions.supercomputing.org_SC25_sess198_ws_pmbss116@linklings.com
SUMMARY:PerfAnalyzer: Revealing Performance Trends using Version Oriented 
 Visual Analysis of Scientific Software
DESCRIPTION:Sayef Azad Sakin (University of Utah, Los Alamos National Labo
 ratory (LANL)) and James Ahrens (Los Alamos National Laboratory (LANL))\n\
 nUnderstanding the behavior of scientific software is essential in maintai
 ning the integrity and transparency of computational research. Tracking th
 e changes in computational parameters (input-output parameters, configurat
 ion parameters for hardware and software) across different versions of sof
 tware executions helps in understanding by providing a context to correlat
 e the outcomes with meaningful changes and to interpret the results reliab
 ly. Diverse computing environments and software platforms add complexity i
 n tracking the evolution of computational parameters across multiple runs.
  We present PerfAnalyzer, an interactive dashboard to simplify the collect
 ion, management, and visual analysis of computational parameters across Gi
 t commits. We demonstrate the usefulness of the dashboard in identifying p
 erformance issues through a case study on collecting and analyzing computa
 tional parameters of the CloverLeaf mini-application. The results of the c
 ase study show PerfAnalyzer's ability to highlight performance changes acr
 oss versions and identify parameters related to the changes that are diffi
 cult to locate using isolated measurements.\n\nRecording: Livestreamed, Re
 corded\n\nRegistration Category: Technical Program Reg Pass, Workshop Reg 
 Pass\n\nSession Chairs: Steven A. Wright (University of York, England); Si
 mon Hammond (National Nuclear Security Administration (NNSA)); and Sascha 
 Hunold (Technical University of Vienna)\n\n
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