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DTSTART;TZID=America/Denver:20231113T115700
DTEND;TZID=America/Denver:20231113T121500
UID:submissions.supercomputing.org_SC23_sess450_ws_worksp120@linklings.com
SUMMARY:Fluxion:  A Scalable Graph-Based Resource Model for HPC Scheduling
  Challenges
DESCRIPTION:Tapasya Patki (Lawrence Livermore National Laboratory (LLNL));
  Dong Ahn (NVIDIA Corporation); Daniel Milroy, Jae-Seung Yeom, Jim Garlick
 , and Mark Grondona (Lawrence Livermore National Laboratory (LLNL)); Steph
 en Herbein (NVIDIA Corporation); and Thomas Scogland (Lawrence Livermore N
 ational Laboratory (LLNL))\n\nThe current era of exascale supercomputing a
 nd the emergence of a computing continuum present several significant reso
 urce management challenges. These include, but are not limited to, managem
 ent of complex scientific workflows, diverse resources such as power, elas
 ticity in user jobs, and converged environments. The resource models that 
 underpin today's job scheduling frameworks reflect the node- (or core-) ce
 ntric system architectures prevalent when the frameworks were designed.  C
 onsequently, they are not suited to capturing resource relationships or dy
 namism.  This greatly limits their applicability to the emerging multiface
 ted challenges in high-performance computing (HPC) and other converged env
 ironments. We propose a scalable graph-based resource model to overcome th
 ese challenges, which allows for representation of complex, changing resou
 rce relationships and multiple containment hierarchies. We implement this 
 model, Fluxion, in a production-quality framework, and evaluate its perfor
 mance. Additionally, we present emerging and advanced scheduling use cases
  that are enabled by our model.\n\nTag: Data Analysis, Visualization, and 
 Storage, Large Scale Systems, Programming Frameworks and System Software, 
 Reproducibility, Resource Management, Runtime Systems\n\nRegistration Cate
 gory: Workshop Reg Pass\n\nSession Chairs: Silvina Caino-Lores (National I
 nstitute for Research in Digital Science and Technology (Inria)) and Anirb
 an Mandal (Renaissance Computing Institute (RENCI), University of North Ca
 rolina at Chapel Hill)\n\n
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