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DTSTART;TZID=America/Chicago:20181111T153000
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UID:submissions.supercomputing.org_SC18_sess152_ws_vpa101@linklings.com
SUMMARY:Visual Analytics Challenges in Analyzing Calling Context Trees
DESCRIPTION:Alexandre Bergel (University of Chile); Abhinav Bhatele and Da
 vid Boehme (Lawrence Livermore National Laboratory); Patrick Gralka (Unive
 rsity of Stuttgart, Visualization Research Center); Kevin Griffin (Lawrenc
 e Livermore National Laboratory); Marc-André Hermanns (Forschungszentrum J
 uelich); Dusan Okanovic (University of Stuttgart); Olga Pearce (Lawrence L
 ivermore National Laboratory); and Tom Vierjahn (RWTH Aachen University; W
 estphalian University of Applied Sciences, Bocholt)\n\nPerformance analysi
 s is an integral part of developing and optimizing parallel applications f
 or high-performance computing (HPC) platforms. Hierarchical data from diff
 erent sources is typically available to identify performance issues or ano
 malies. Some hierarchical data such as the calling context can be very lar
 ge in terms of breadth and depth of the hierarchy. Classic tree visualizat
 ions quickly reach their limits in analyzing such hierarchies with the abu
 ndance of information to display. In this position paper, we identify the 
 challenges commonly faced by the HPC community in visualizing hierarchical
  performance data, with a focus on calling context trees. Furthermore, we 
 motivate and lay out the bases of a visualization that addresses some of t
 hese challenges.\n\nTag: Data Analytics, Performance, Visualization\n\nReg
 istration Category: Workshop Reg Pass\n\n
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