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DTSTAMP:20260924T172459Z
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DTSTART;TZID=America/New_York:20241119T120000
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UID:submissions.supercomputing.org_SC24_sess487_post207@linklings.com
SUMMARY:Proposal for a Parallel Automatic Tuning Using d-Spline According 
 to the Operating State of the Computer System
DESCRIPTION:Yuga Yajima, Akihiro Fujii, and Teruo Tanaka (Kogakuin Univers
 ity, Japan)\n\nSoftware auto-tuning (AT) is a technology that parameterize
 s factors that affect performance as "performance parameters" and automati
 cally tunes performance. In AT, the tool searches for better values for pe
 rformance parameters by repeatedly running the program. Therefore, if the 
 target is a program with long execution times, such as machine learning, A
 T will take a very long time. For this problem, we have tried to reduce th
 e time by running the target program in parallel. However, simple parallel
 ization does not always take full advantage of the parallelism of the comp
 uter system.\nIn this study, we proposed the system-resource-based search.
  This method increases the number of execution targets, and the system doe
 s not have excess computing resources. The system-resource-based search wa
 s independent of the size of the search space and made the best use of the
  computational resources available on the supercomputer.\n\nRegistration C
 ategory: Tech Program Reg Pass, Exhibits Reg Pass\n\nSession Chairs: Ayesh
 a Afzal (FAU Erlangen-Nürnberg, Erlangen National High Performance Computi
 ng Center); Sally Ellingson (University of Kentucky); and Alan Sussman (Un
 iversity of Maryland)\n\n
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