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DTSTART;TZID=America/Denver:20231112T153000
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UID:submissions.supercomputing.org_SC23_sess435_ws_pdsw111@linklings.com
SUMMARY:Enhancing Metadata Transfer Efficiency: Unlocking the Potential of
  DAOS in the ADIOS Context
DESCRIPTION:Ranjan Sarpangala Venkatesh and Greg Eisenhauer (Georgia Insti
 tute of Technology), Scott Klasky (Oak Ridge National Laboratory (ORNL)), 
 and Ada Gavrilovska (Georgia Institute of Technology)\n\nIn HPC, data move
 ment between applications is typically facilitated by I/O middleware, such
  as the Adaptable I/O System (ADIOS). This middleware leverages the capabi
 lities of the underlying storage services, to facilitate data movement and
  distribution. A recent storage system, Intel DAOS, promises to deliver ne
 w capabilities for achieving performance and scalability on emerging memor
 y/storage systems. DAOS has already deployed in University of Cambridge, T
 ACC, and the upcoming Aurora supercomputer. This paper investigates the pe
 rformance tradeoffs associated with mapping ADIOS over one of the many dif
 ferent DAOS interfaces and data models, and makes recommendations for thei
 r efficient use.\n\nTag: Data Analysis, Visualization, and Storage, Data M
 ovement and Memory\n\nRegistration Category: Workshop Reg Pass\n\nSession 
 Chairs: Suren Byna (The Ohio State University, Lawrence Berkeley National 
 Laboratory (LBNL)); Jay Lofstead (Sandia National Laboratories, University
  of New Mexico); Bing Xie (Microsoft Corporation); and Amelie Chi Zhou (Ho
 ng Kong Baptist University)\n\n
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