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DTSTART;TZID=America/Chicago:20251118T080000
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UID:submissions.supercomputing.org_SC25_sess537_drs109@linklings.com
SUMMARY:Taming the Beast of Dynamic Resource Management in HPC
DESCRIPTION:Dominik Huber (Technical University of Munich)\n\nDynamic reso
 urce management (DRM) enables the resources assigned to a job to be adjust
 ed during execution. From a system perspective, DRM adds flexibility to re
 source allocation and job scheduling, with the potential to improve utiliz
 ation, throughput, energy efficiency, and responsiveness. From an applicat
 ion perspective, it allows users to match resource requests to evolving ne
 eds, potentially reducing queue times and costs.\n\nDespite these benefits
  and a decade of research, DRM remains largely an academic concept in HPC 
 rather than a production feature. This is due to the need for coordinated 
 changes across the entire software stack—applications, programming models,
  process managers, and resource managers—along with a holistic co-design e
 ffort to develop new scheduling and optimization policies.\n\nWe present a
  novel, end-to-end approach to DRM in HPC, introducing generic design prin
 ciples for parallel programming models that integrate applications’ dynami
 c process management with the resource managers’ optimization capabilities
 . We apply these principles across the HPC stack, incorporating standards 
 such as MPI and PMIx, to create a fully dynamic environment supporting div
 erse applications. This is paired with a performance-aware scheduling stra
 tegy based on steepest-ascent optimization.\n\nExperiments on up to 100 no
 des show moderate overheads for application process reconfiguration while 
 delivering substantial gains in system throughput and average job turnarou
 nd time compared to static scheduling under high-load conditions.\n\nTag: 
 Research & ACM SRC Posters\n\nRecording: Not Livestreamed, Not Recorded\n\
 nRegistration Category: Technical Program Reg Pass\n\nSession Chairs: Kent
 o Sato (RIKEN Center for Computational Science (R-CCS)); Chris Schlipalius
  (Pawsey Supercomputing Research Centre; Commonwealth Scientific and Indus
 trial Research Organisation (CSIRO), Australia); and Anja Gerbes (Georg-Au
 gust-Universität Göttingen)\n\n
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