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DTSTAMP:20190719T085744Z
LOCATION:HG D 1.1
DTSTART;TZID=Europe/Stockholm:20190613T114500
DTEND;TZID=Europe/Stockholm:20190613T121500
UID:submissions.pasc-conference.org_PASC19_sess125_msa145@linklings.com
SUMMARY:Compression-Based Resilience for Linear Solvers
DESCRIPTION:Minisymposium\nComputer Science and Applied Mathematics, Clima
 te and Weather\n\nCompression-Based Resilience for Linear Solvers\n\nGoedd
 eke, Altenbernd\n\nThere are three general approaches to improve the resil
 ience of computations in software: (i) checkpoint-restart, (ii) algorithm-
 based fault tolerance and (iii) triple modular redundancy. We present two 
 different approaches towards resilience of linear solvers, that constitute
  hybrids of checkpoint-restart and algorithm-based fault tolerance. The ab
 stract idea is to use different forms of compression, and we evaluate both
  built-in compression of hierarchical solvers (e.g., multigrid, multilevel
  Schwarz) and data-driven compression using the sz-technique. Both approac
 hes are evaluated for silent data corruption, and the loss of entire compu
 te nodes. Finally, a performance model is developed to help guide the deci
 sion on which technique to apply in a concrete setting.<br /><br />This is
  joint work with M. Altenbernd (Stuttgart) and J. Calhoun (Clemson).
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