Exploring Automatic, Online Failure Recovery for Scientific Applications at Extreme Scales

Marc Gamell, Daniel S. Katz, Hemanth Kolla, Jacqueline Chen, Scott Klasky, Manish Parashar

Research output: Contribution to journalConference articlepeer-review

Abstract

Application resilience is a key challenge that must be addressed in order to realize the exascale vision. Process/node failures, an important class of failures, are typically handled today by terminating the job and restarting it from the last stored checkpoint. This approach is not expected to scale to exascale. In this paper we present Fenix, a framework for enabling recovery from process/node/blade/cabinet failures for MPI-based parallel applications in an online (i.e., Without disrupting the job) and transparent manner. Fenix provides mechanisms for transparently capturing failures, re-spawning new processes, fixing failed communicators, restoring application state, and returning execution control back to the application. To enable automatic data recovery, Fenix relies on application-driven, diskless, implicitly coordinated check pointing. Using the S3D combustion simulation running on the Titan Cray-XK7 production system at ORNL, we experimentally demonstrate Felix's ability to tolerate high failure rates (e.g., More than one per minute) with low overhead while sustaining performance.

Original languageEnglish (US)
Article number7013060
Pages (from-to)895-906
Number of pages12
JournalInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC
Volume2015-January
Issue numberJanuary
DOIs
StatePublished - Jan 16 2014
Externally publishedYes
EventInternational Conference for High Performance Computing, Networking, Storage and Analysis, SC 2014 - New Orleans, United States
Duration: Nov 16 2014Nov 21 2014

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Software

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