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DTSTART;TZID=America/Chicago:20181113T110000
DTEND;TZID=America/Chicago:20181113T113000
UID:submissions.supercomputing.org_SC18_sess203_pap109@linklings.com
SUMMARY:FlipTracker: Understanding Natural Error Resilience in HPC Applica
 tions
DESCRIPTION:Luanzheng Guo and Dong Li (University of California, Merced); 
 Ignacio Laguna (Lawrence Livermore National Laboratory); and Martin Schulz
  (Technical University Munich)\n\nAs high-performance computing systems sc
 ale in size and computational power, the danger of silent errors, i.e., er
 rors that can bypass hardware detection mechanisms and impact application 
 state, grows dramatically. Consequently, applications running on HPC syste
 ms need to exhibit resilience to such errors. Previous work has found that
 , for certain codes, this resilience can come for free, i.e., some applica
 tions are naturally resilient, but few works have shown the code patterns—
 combinations or sequences of computations—that make an application natural
 ly resilient. In this paper, we present FlipTracker, a framework designed 
 to extract these patterns using fine-grained tracking of error propagation
  and resilience properties, and we use it to present a set of computation 
 patterns that are responsible for making representative HPC applications n
 aturally resilient to errors. This not only enables a deeper understanding
  of resilience properties of these codes, but also can guide future applic
 ation designs toward patterns with natural resilience.\n\nTag: GPUs, Resil
 iency, State of the Practice, System Software\n\nRegistration Category: Te
 ch Program Reg Pass\n\nFinalist: BSP Finalist\n\nSession Chair: Ron Bright
 well (Sandia National Laboratories)\n\n
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