Resiliency in exascale systems and computations using chaotic-identity maps

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

For exascale computing systems, we propose (i) light-weight computational modules that utilize chaotic computations and customized identity maps to detect component failures, and (ii) statistical estimation methods that generate robustness estimates for the system and computations based on the module outputs. The diagnosis modules execute multiple Poincare and identity maps, which are customized to detect certain classes of failures in the compute nodes and interconnects. We propose statistical methods that generate robustness estimates for the system using the outputs of pipelined chains of diagnosis modules.

Original languageEnglish
Title of host publicationEuro-Par 2012 - Parallel Processing Workshops
Subtitle of host publicationBDMC, CGWS, HeteroPar, HiBB, OMHI, Paraphrase, PROPER, Resilience, UCHPC, VHPC, Revised Selected Papers
Pages494-495
Number of pages2
DOIs
StatePublished - 2013
EventParallel Processing Workshops, Euro-Par 2012: BDMC 2012, CGWS 2012, HeteroPar 2012, HiBB 2012, OMHI 2012, Paraphrase 2012, PROPER 2012, Resilience 2012, UCHPC 2012, VHPC 2012 - Rhodes Island, Greece
Duration: Aug 27 2012Aug 31 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7640 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceParallel Processing Workshops, Euro-Par 2012: BDMC 2012, CGWS 2012, HeteroPar 2012, HiBB 2012, OMHI 2012, Paraphrase 2012, PROPER 2012, Resilience 2012, UCHPC 2012, VHPC 2012
Country/TerritoryGreece
CityRhodes Island
Period08/27/1208/31/12

Keywords

  • Exascale systems
  • chaotic maps
  • resiliency
  • statistical estimation

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