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DTSTART;TZID=America/Chicago:20181115T083000
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UID:submissions.supercomputing.org_SC18_sess324_post168@linklings.com
SUMMARY:SpotSDC: an Information Visualization System to Analyze Silent Dat
 a Corruption
DESCRIPTION:Zhimin Li (University of Utah), Harshitha Menon (Lawrence Live
 rmore National Laboratory), Yarden Livnat (University of Utah), Kathryn Mo
 hror (Lawrence Livermore National Laboratory), and Valerio Pascucci (Unive
 rsity of Utah)\n\nAggressive technology scaling trends are expected to mak
 e the hardware of HPC systems more susceptible to transient faults. Transi
 ent faults in hardware may be masked without affecting the program output,
  cause a program to crash, or lead to silent data corruptions (SDC). While
  fault injection studies can give an overall resiliency profile for an app
 lication, without a good visualization tool it is difficult to summarize a
 nd highlight critical information obtained. In this work, we design SpotSD
 C, a visualization system to analyze a program's resilience characteristic
 s to SDC. SpotSDC provides an overview of the SDC impact on an application
  by highlighting regions of code that are most susceptible to SDC and will
  have a high impact on the program's output. SpotSDC also enables users to
  visualize the propagation of error through an application execution.\n\nR
 egistration Category: Tech Program Reg Pass, Exhibits Reg Pass\n\n
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