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DTSTAMP:20260422T000712Z
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DTSTART;TZID=America/Denver:20231112T120600
DTEND;TZID=America/Denver:20231112T123000
UID:submissions.supercomputing.org_SC23_sess424_ws_ross107@linklings.com
SUMMARY:Analysis and Characterization of Performance Variability for OpenM
 P Runtime
DESCRIPTION:Minyu Cui, Nikela Papadopoulou, and Miquel Pericàs (Chalmers U
 niversity of Technology, Sweden)\n\nIn the high performance computing (HPC
 ) domain, performance variability is a major scalability issue for paralle
 l computing applications with heavy synchronization and communication.  We
  present an experimental performance analysis of OpenMP benchmarks regardi
 ng the variation of execution time, and determine the potential factors ca
 using performance variability.\n\nOur work offers some understanding of pe
 rformance distributions and directions for future work on how to mitigate 
 variability for OpenMP-based applications. Two representative OpenMP bench
 marks from the EPCC OpenMP micro-benchmark suite and BabelStream are run a
 cross two x86 multicore platforms featuring up to 256 threads. From the ob
 tained results, we characterize and explain the execution time variability
  as a function of thread-pinning, simultaneous multithreading (SMT) and co
 re frequency variation.\n\nTag: Middleware and System Software, Programmin
 g Frameworks and System Software, Runtime Systems\n\nRegistration Category
 : Workshop Reg Pass\n\nSession Chairs: Balazs Gerofi (Intel Corporation, R
 IKEN Center for Computational Science (R-CCS)); Torsten Hoefler (ETH Züric
 h, Microsoft Corporation); and Kamil Iskra (Argonne National Laboratory (A
 NL))\n\n
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