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DTSTART;TZID=America/Denver:20231112T114200
DTEND;TZID=America/Denver:20231112T120600
UID:submissions.supercomputing.org_SC23_sess419_ws_prot104@linklings.com
SUMMARY:Filtering and Ranking of Code Regions for Parallelization via Hots
 pot Detection and OpenMP Overhead Analysis
DESCRIPTION:Seyed Ali Mohammadi, Lukas Rothenberger, Gustavo de Morais, Be
 rtin Nico Görlich, Erik Lille, Hendrik Rüthers, and Felix Wolf (Technical 
 University of Darmstadt)\n\nMany high-performance computing applications r
 each millions of code lines and hundreds of code regions. Analyzing all co
 de regions for parallelization with OpenMP is neither efficient nor necess
 ary. To facilitate this task and minimize the effort by the user, the code
  regions of the application need to be filtered and ranked. We provide a s
 imple filtering method to detect the critical code regions by clearly defi
 ning a hotspot. Afterward, we identify parallelizable loops by analyzing t
 heir data dependencies using an automatic tool. As the number of parallel 
 opportunities can be high and the users must verify these parallel suggest
 ions, we suggest a ranking strategy based on parallelization overhead to h
 elp them prioritize their endeavors and present a set of OpenMP microbench
 marks for overhead analysis. We calculate optimistic expected benefits usi
 ng overhead estimations as ranking metrics and show how our ranking provid
 es an improvement on the ranking based on serial runtime.\n\nTag: Performa
 nce Measurement, Modeling, and Tools, Programming Frameworks and System So
 ftware\n\nRegistration Category: Workshop Reg Pass\n\nSession Chairs: Davi
 d Boehme (Lawrence Livermore National Laboratory (LLNL)), Anthony Danalis 
 (AMD), and Josef Weidendorfer (Dresden University of Technology)\n\n
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