Resilient N-Body Tree Computations with Algorithm-Based Focused Recovery: Model and Performance Analysis

  • Aurélien CavelanEmail author
  • Aiman Fang
  • Andrew A. Chien
  • Yves Robert
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10724)


This paper presents a model and performance study for Algorithm-Based Focused Recovery (ABFR) applied to N-body computations, subject to latent errors. We make a detailed comparison with the classical Checkpoint/Restart (CR) approach. While the model applies to general frameworks, the performance study is limited to perfect binary trees, due to the inherent difficulty of the analysis. With ABFR, the crucial parameter is the detection interval, which bounds the error latency. We show that the detection interval has a dramatic impact on the overhead, and that optimally choosing its value leads to significant gains over the CR approach.


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Aurélien Cavelan
    • 1
    • 2
    Email author
  • Aiman Fang
    • 3
  • Andrew A. Chien
    • 3
    • 4
  • Yves Robert
    • 2
    • 5
  1. 1.University of BaselBaselSwitzerland
  2. 2.Laboratoire LIP, ENS Lyon and InriaLyonFrance
  3. 3.University of ChicagoChicagoUSA
  4. 4.Argonne National LaboratoryLemontUSA
  5. 5.University of Tennessee KnoxvilleKnoxvilleUSA

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