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BEGIN:VEVENT
DTSTAMP:20260522T150120Z
LOCATION:D175
DTSTART;TZID=America/Chicago:20181112T160000
DTEND;TZID=America/Chicago:20181112T163000
UID:submissions.supercomputing.org_SC18_sess176_ws_llvmf107@linklings.com
SUMMARY:PInT: Pattern Instrumentation Tool for Analyzing and Classifying H
 PC Applications
DESCRIPTION:Fabian Schlebusch, Yannik Müller, Sandra Wienke, Julian Miller
 , and Matthias Müller (RWTH Aachen University)\n\nThe relationship of appl
 ication performance to its required development effort plays an important 
 role in today’s budget-oriented HPC environment. This effort-performance r
 elationship is especially affected by the structure and characterization o
 f an HPC application. We aim at a classification of HPC applications using
  (design) patterns for parallel programming. For an efficient analysis of 
 parallel patterns and applicable pattern definitions, we introduce our too
 l PInT that is based on source code instrumentation and Clang LibTooling. 
 Furthermore, we propose metrics to examine occurrences and compositions of
  patterns that can be automatically evaluated by PInT. In two case studies
 , we show the applicability and functionality of PInT.\n\nTag: Program Tra
 nsformation, Programming Systems\n\nRegistration Category: Workshop Reg Pa
 ss\n\n
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