Predicting faults in high performance computing systems: An in-depth survey of the state-of-the-practice

David Jauk, Dai Yang, Martin Schulz

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

25 Scopus citations

Abstract

As we near exascale, resilience remains a major technical hurdle. Any technique with the goal of achieving resilience suffers from having to be reactive, as failures can appear at any time. A wide body of research aims at predicting failures, i.e., forecasting failures so that evasive actions can be taken while the system is still fully functional, which has the benefit of giving insight into the global system state. This research area has grown very diverse with a large number of approaches, yet is currently poorly classified, making it hard to understand the impact and coverage of existing work. In this paper, we perform an extensive survey of existing literature in failure prediction by analyzing and comparing more than 30 different failure prediction approaches. We develop a taxonomy, which aids in categorizing the methods, and we show how this can help us to understand the state-of-the-practice of this field and to identify opportunities, gaps as well as future work.

Original languageEnglish
Title of host publicationProceedings of SC 2019
Subtitle of host publicationThe International Conference for High Performance Computing, Networking, Storage and Analysis
PublisherIEEE Computer Society
ISBN (Electronic)9781450362290
DOIs
StatePublished - 17 Nov 2019
Event2019 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2019 - Denver, United States
Duration: 17 Nov 201922 Nov 2019

Publication series

NameInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC
ISSN (Print)2167-4329
ISSN (Electronic)2167-4337

Conference

Conference2019 International Conference for High Performance Computing, Networking, Storage and Analysis, SC 2019
Country/TerritoryUnited States
CityDenver
Period17/11/1922/11/19

Keywords

  • Exascale computing
  • Fault prediction
  • High performance computing
  • Resillience

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