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DTSTAMP:20250626T234542Z
LOCATION:B309
DTSTART;TZID=America/New_York:20241117T160000
DTEND;TZID=America/New_York:20241117T160500
UID:submissions.supercomputing.org_SC24_sess736_ws_pdswwip114@linklings.co
 m
SUMMARY:Jarvis: Towards a Shared, User-Friendly, and Reproducible I/O Infr
 astructure
DESCRIPTION:Jaime Cernuda and Luke Logan (Illinois Institute of Technology
 ), Noah Lewis and Suren Byna (The Ohio State University), and Xian-He Sun 
 and Anthony Kougkas (Illinois Institute of Technology)\n\nHardware is beco
 ming increasingly heterogeneous in modern high-performance computing clust
 ers. However, computing environments for developing tools to harness these
  technologies are not easily available to researchers. This work showcases
  the need for a new high-pace, heterogeneous I/O research cluster and pres
 ents a novel software deployment framework named Jarvis to manage its hard
 ware diversity. Jarvis is an extensible Python framework that allows users
  to create packages that deploy, manage, and monitor software, including c
 omplex applications (e.g., scientific simulations), support tools (e.g., D
 arshan, GDB), and storage systems (e.g., Lustre, DAOS). These packages can
  be combined to form complex deployment pipelines. To ensure pipelines are
  portable across hardware, Jarvis defines a novel resource graph schema fi
 le, which is a snapshot of a cluster's machine-specific information. This 
 schema can be queried by Jarvis packages to deploy software across diverse
  hardware compositions with minimal user effort.\n\nTag: Data Movement and
  Memory, I/O, Storage, Archive\n\nRegistration Category: Workshop Reg Pass
 \n\nSession Chairs: Suren Byna (The Ohio State University, Lawrence Berkel
 ey National Laboratory (LBNL)); Dean Hildebrand (Google LLC); Anthony Koug
 kas (Illinois Institute of Technology, Argonne National Laboratory (ANL));
  Jay Lofstead (Sandia National Laboratories, University of New Mexico); an
 d Bing Xie (Microsoft Corporation)\n\n
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