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DTSTAMP:20250626T233532Z
LOCATION:B302-B305
DTSTART;TZID=America/New_York:20241121T100000
DTEND;TZID=America/New_York:20241121T170000
UID:submissions.supercomputing.org_SC24_sess534_post222@linklings.com
SUMMARY:I/O Characterization of Heterogeneous Workflows
DESCRIPTION:Olga Kogiou (Florida State University), Hariharan Devarajan an
 d Chen Wang (Lawrence Livermore National Laboratory (LLNL)), Weikuan Yu (F
 lorida State University), and Kathryn Mohror (Lawrence Livermore National 
 Laboratory (LLNL))\n\nWorkflows consist of individual applications such as
  scientific simulations and data analytics. These applications constitute 
 different stages of the workflow, each comprising heterogeneous characteri
 stics such as run-times and system requirements. The heterogeneity in thes
 e workflow stages dictates the need to efficiently characterize them in te
 rms of I/O to provide insights that can lead to informed decisions for the
 ir optimization. In this work we have analyzed the run-times of the workfl
 ows Montage, 1000 Genome and MuMMI and have categorized their stages as I/
 O or Non-I/O bound. For the I/O bound stages we perform a detailed analysi
 s of their bandwidth and resource requirements. Our findings conclude that
  Montage's mBgModel could benefit from Dynamic Resource Scheduling, while 
 Genome's individuals_merge could benefit from data aggregations in the PFS
  requests and the usage of isolated storage solutions such as node-local s
 torage. These optimizations could aid in serving the bandwidth requirement
 s of this workflow stage.\n\nRegistration Category: Tech Program Reg Pass,
  Exhibits Reg Pass\n\nSession Chairs: Ayesha Afzal (Friedrich-Alexander Un
 iversity, Erlangen-Nuremberg; Erlangen National High Performance Computing
  Center); Sally Ellingson (University of Kentucky); and Alan Sussman (Univ
 ersity of Maryland)\n\n
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