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DTSTAMP:20260522T150120Z
LOCATION:C154
DTSTART;TZID=America/Chicago:20181111T083000
DTEND;TZID=America/Chicago:20181111T170000
UID:submissions.supercomputing.org_SC18_sess254_tut150@linklings.com
SUMMARY:How to Analyze the Performance of Parallel Codes 101
DESCRIPTION:Martin Schulz (Technical University Munich, Chair for Computer
  Architecture and Parallel Systems); Jim Galarowicz and Don Maghrak (Krell
  Institute); and Jennifer Green and David Montoya (Los Alamos National Lab
 oratory)\n\nPerformance analysis is an essential step in the development o
 f HPC codes. It will even gain in importance with the rising complexity of
  machines and applications that we are seeing today. Many tools exist to h
 elp with this analysis, but the user is too often left alone with interpre
 ting the results.\n\nWe will provide a practical road map for the performa
 nce analysis of HPC codes and will provide users step-by-step advice on ho
 w to detect and optimize common performance problems, covering both on-nod
 e performance and communication optimization as well as issues on threaded
  and accelerator-based architectures. In addition, we will review current 
 approached in ubiquitous monitoring of performance utilizing lightweight t
 ools. Throughout this tutorial, we will show live demos using Open|SpeedSh
 op, a comprehensive and easy to use tool set.  Additionally, at the end of
  each section we will provide hands-on exercises for attendees to try out 
 the new techniques learned with performance comparison across multiple arc
 hitectures.  All techniques will, however, apply broadly to any tool, and 
 we will point out alternative tools where useful.\n\nTag: Performance, Too
 ls\n\nRegistration Category: Tutorial Reg Pass\n\n
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