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DTSTART;TZID=America/New_York:20241118T114500
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UID:submissions.supercomputing.org_SC24_sess751_ws_p3hpc111@linklings.com
SUMMARY:Performance and Power: Systematic Evaluation of AI Workloads on Ac
 celerators with CARAML
DESCRIPTION:Chelsea Maria John, Andreas Herten, Stepan Nassyr, and Carolin
  Penke (Forschungszentrum Jülich, Jülich Supercomputing Centre (JSC))\n\nT
 he rapid advancement of machine learning (ML) technologies has driven the 
 development of specialized hardware accelerators designed to facilitate mo
 re efficient model training. This paper introduces the CARAML benchmark su
 ite, which is employed to assess performance and energy consumption during
  the training of transformer-based large language models and computer visi
 on models on a range of hardware accelerators, including systems from NVID
 IA, AMD, and Graphcore. CARAML provides a compact, automated, extensible, 
 and reproducible framework for assessing the performance and energy of ML 
 workloads across various novel hardware architectures. The design and impl
 ementation of CARAML, along with a custom power measurement tool called jp
 wr, are discussed in detail.\n\nTag: Performance Optimization, Programming
  Frameworks and System Software\n\nRegistration Category: Workshop Reg Pas
 s\n\nSession Chairs: CJ Newburn (NVIDIA Corporation), Scott J. Parker (Arg
 onne National Laboratory (ANL)), John Pennycook (Intel Corporation), and K
 enneth Weiss (Lawrence Livermore National Laboratory (LLNL))\n\n
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