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SUMMARY:SCTuner— an autotuner for I/O library
DTSTART;VALUE=DATE-TIME:20211202T131500Z
DTEND;VALUE=DATE-TIME:20211202T134500Z
DTSTAMP;VALUE=DATE-TIME:20260718T085440Z
UID:indico-contribution-1488@events.chpc.ac.za
DESCRIPTION:Speakers: Bing Xie (ORNL)\nIn  HPC\,  typical scientific codes
   often  manage   a   massive   amount   of   data   utilizing I/O  middle
 ware libraries\, such as HDF5\, PnetCDF\, ADIOS\, etc.  These  libraries  
 support a variety of data structures and allow end users to optimize I/O p
 erformance by tuning configurations across multiple layers of the HPC I/O 
 middleware stack. This work proposes SCTuner\, an autotuner built within t
 he I/O library itself to tune the configurations across I/O layers dynamic
 ally and agilely at application runtime.  To  this  end\,  we  introduce  
 an I/O statistical benchmarking method to profile the behaviors of individ
 ual supercomputer I/O subsystems with varied configurations across I/O lay
 ers. Next\, we use the benchmarking results as the built-in knowledge in S
 CTuner\,  implement an I/O pattern extractor\, and plan to implement an on
 line performance tuner as the runtime of SCTuner. We conducted a benchmark
 ing analysis on the Summit supercomputer and its GPFS file system Alpine. 
 The preliminary results show that our method can effectively extract the c
 onsistent I/O   behaviors  of   the   target   system   under   production
    load\, building  the  base  for  I/O  autotuning  at  application  runt
 ime.\n\nhttps://events.chpc.ac.za/event/98/contributions/1488/
LOCATION:
URL:https://events.chpc.ac.za/event/98/contributions/1488/
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