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DTSTART;TZID=America/Denver:20231114T100000
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UID:submissions.supercomputing.org_SC23_sess291_rpost130@linklings.com
SUMMARY:Software Development Case Study: The Acceleration of a Distributed
  Application Using GPUs
DESCRIPTION:Martin Kuhnel, Alex Loddoch, and Tao Sun (Chevron)\n\nWe prese
 nt a practical approach for the acceleration of an industrial and scientif
 ic application using graphics processing units (GPUs). Our original applic
 ation is a computational stratigraphy codebase that couples fluid flow and
  sediment deposition submodels. The application uses domain decomposition 
 and a halo exchange to split the workload among multiple workers in a dist
 ributed system. Our methodology abstracts and conserves the host data stru
 ctures while re-writing computational elements in the GPU programming lang
 uage CUDA. Utilizing high performance GPU machines in the Azure cloud, we 
 show a minimum 90x speedup compared to a high-end CPU based cluster. In th
 is poster, we give a brief description of the original algorithm, followed
  by a discussion of required software changes and additions. Although this
  case study focuses on a specific example, we hope this approach inspires 
 similar efforts in other applications.\n\nTag: Artificial Intelligence/Mac
 hine Learning, Architecture and Networks, Heterogeneous Computing, I/O and
  File Systems, Performance Measurement, Modeling, and Tools, Post-Moore Co
 mputing, Programming Frameworks and System Software, Quantum Computing\n\n
 Registration Category: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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