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DTSTART:19700308T020000
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DTSTAMP:20200129T163557Z
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DTSTART;TZID=America/Denver:20191117T110000
DTEND;TZID=America/Denver:20191117T113000
UID:submissions.supercomputing.org_SC19_sess112_pec241@linklings.com
SUMMARY:A Codesign Framework for Online Data Analysis and Reduction
DESCRIPTION:Workshop\n\nA Codesign Framework for Online Data Analysis and 
 Reduction\n\nMehta, Allen, Wolf, Logan, Suchyta...\n\nIn this paper we dis
 cuss our design of a toolset for automating performance studies of compose
 d HPC applications that perform online data reduction and analysis. We des
 cribe Cheetah, a new framework for performing parametric studies on couple
 d applications. Cheetah facilitates understanding the impact of various fa
 ctors such as process placement, synchronicity of algorithms, and storage 
 vs. compute requirements for online analysis of large data. Ultimately, we
  aim to create a catalog of performance results that can help scientists u
 nderstand tradeoffs when designing next-generation simulations that make u
 se of online processing techniques. We illustrate the design choices of Ch
 eetah by using a reaction-diffusion simulation (Gray-Scott) paired with an
  analysis application to demonstrate initial results of fine-grained proce
 ss placement on Summit, a pre-exascale supercomputer at Oak Ridge National
  Laboratory.\n\nTag: Workshop Reg Pass, Extreme Scale Computing, Scalable 
 Computing, Scientific Workflows\n\nRegistration Category: Workshop Reg Pas
 s, Extreme Scale Computing, Scalable Computing, Scientific Workflows
URL:https://sc19.supercomputing.org/presentation/?id=pec241&sess=sess112
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