Programmer-guided reliability for extreme-scale applications

David E. Bernholdt, Wael R. Elwasif, Christos Kartsaklis, Seyong Lee, Tiffany M. Mintz

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

Abstract

We present 'programmer-guided reliability' (PGR) as a systematic conceptual approach to address the expected rise in soft errors in coming extreme-scale systems at the application level. The approach involves instrumentation of the application with code to detect data corruption errors. The location and nature of these error detectors are at the discretion of the programmer, who uses their knowledge and experience with the problem domain, the application, the solution algorithms, etc., to determine the most vulnerable areas of the code and the most appropriate ways to detect data corruption. To illustrate the approach, we provide examples of error detectors from four different benchmark-scale applications. We also describe a simple control framework that allows for runtime configuration of the error detectors without recompilation of the application, as well as dynamic reconfiguration during the execution of the application. Finally, we discuss a number of future directions building on the basic PGR approach, including the incorporation of some general error detectors into the programming environment in order to make them more easily usable by the programmer.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Conference on Cluster Computing, CLUSTER 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages571-579
Number of pages9
ISBN (Electronic)9781467365987
DOIs
StatePublished - Oct 26 2015
EventIEEE International Conference on Cluster Computing, CLUSTER 2015 - Chicago, United States
Duration: Sep 8 2015Sep 11 2015

Publication series

NameProceedings - IEEE International Conference on Cluster Computing, ICCC
Volume2015-October
ISSN (Print)1552-5244

Conference

ConferenceIEEE International Conference on Cluster Computing, CLUSTER 2015
Country/TerritoryUnited States
CityChicago
Period09/8/1509/11/15

Keywords

  • Application resilience
  • Fault tolerance
  • Scientific computing

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