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DTSTART:19700308T020000
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DTSTAMP:20211207T055339Z
LOCATION:Online
DTSTART;TZID=America/Chicago:20211114T103500
DTEND;TZID=America/Chicago:20211114T110000
UID:submissions.supercomputing.org_SC21_sess428_ws_ftxs102@linklings.com
SUMMARY:Doubt and Redundancy Kill Soft Errors—Toward Detection and Correct
 ion of Silent Data Corruption in Task-Based Numerical Software
DESCRIPTION:Workshop\n\nDoubt and Redundancy Kill Soft Errors—Toward Detec
 tion and Correction of Silent Data Corruption in Task-Based Numerical Soft
 ware\n\nSamfass, Weinzierl, Reinarz, Bader\n\nResilient algorithms in high
 -performance computing are subject to rigorous non-functional constraints.
  Resiliency must not increase the runtime, memory footprint or I/O demands
  too significantly. We propose a task-based soft error detection scheme th
 at relies on error criteria per task outcome. They formalise how “dubious”
  an outcome is, i.e., how likely it contains an error. Our whole simulatio
 n is replicated once, forming two teams of MPI ranks that share their task
  results. Thus, ideally each team handles only around half of the workload
 . If a task yields large error criteria values, i.e. is dubious, we comput
 e the task redundantly and compare the outcomes. Whenever they disagree, t
 he task result with a lower error likeliness is accepted. We obtain a self
 -healing, resilient algorithm which can compensate silent floating-point e
 rrors without a significant performance, I/O or memory footprint penalty. 
 Case studies however suggest that a careful, domain-specific tailoring of 
 the error criteria remains essential.\n\nTag: Online Only, Extreme Scale C
 omputing, Reliability and Resiliency\n\nRegistration Category: Workshop Re
 g Pass
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