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DTSTAMP:20211207T055404Z
LOCATION:223
DTSTART;TZID=America/Chicago:20211115T153000
DTEND;TZID=America/Chicago:20211115T155500
UID:submissions.supercomputing.org_SC21_sess332_ws_pdsw108@linklings.com
SUMMARY:SCTuner: An Auto-Tuner Addressing Dynamic I/O Needs on Supercomput
 er I/O Sub-Systems
DESCRIPTION:Workshop\n\nSCTuner: An Auto-Tuner Addressing Dynamic I/O Need
 s on Supercomputer I/O Sub-Systems\n\nTang, Xie, Byna, Carns, Koziol...\n\
 nThis work proposes SCTuner, an auto-tuner integrated within I/O library i
 tself to dynamically tune both the I/O library and the underlying I/O stac
 k at application runtime. To this end, we introduce a statistical benchmar
 king method to profile the behaviors of individual supercomputer I/O sub-s
 ystems with varied configurations across I/O layers. We use the benchmarki
 ng results as the built-in knowledge in SCTuner, implement an I/O pattern 
 extractor and plan to implement an online performance tuner as the SCTuner
  runtime. We conducted a benchmarking analysis on the Summit supercomputer
  and its GPFS file system Alpine. The preliminary results show that our me
 thod can effectively extract the consistent I/O behaviors of the target sy
 stem under production load, building the base for I/O auto-tuning at appli
 cation runtime.\n\nTag: Data Analytics, Data Management, File Systems and 
 I/O, Storage\n\nRegistration Category: Workshop Reg Pass
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