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Fault Tolerance in an Inner-Outer Solver: A GVR-Enabled Case Study

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High Performance Computing for Computational Science -- VECPAR 2014 (VECPAR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8969))

Abstract

Resilience is a major challenge for large-scale systems. It is particularly important for iterative linear solvers, since they take much of the time of many scientific applications. We show that single bit flip errors in the Flexible GMRES iterative linear solver can lead to high computational overhead or even failure to converge to the right answer. Informed by these results, we design and evaluate several strategies for fault tolerance in both inner and outer solvers appropriate across a range of error rates. We implement them, extending Trilinos’ solver library with the Global View Resilience (GVR) programming model, which provides multi-stream snapshots, multi-version data structures with portable and rich error checking/recovery. Experimental results validate correct execution with low performance overhead under varied error conditions.

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Acknowledgments

We thank Mark Hoemmen from Sandia National Laboratories for his advice. This work supported by the Office of Advanced Scientific Computing Research, Office of Science, U.S. Department of Energy, under Award DE-SC0008603 and Contract DE-AC02-06CH11357. Also under the DOE National Nuclear Security Administration (NNSA) Advanced Simulation and Computing (ASC) program. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy National Nuclear Security Administration under contract DE-AC04-94AL85000.

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Authors and Affiliations

  1. University of Chicago, Chicago, IL, 60637, USA

    Ziming Zheng & Andrew A. Chien

  2. Sandia National Laboratories, Livermore, CA, 94551, USA

    Keita Teranishi

Authors
  1. Ziming Zheng
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  2. Andrew A. Chien
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  3. Keita Teranishi
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Corresponding author

Correspondence to Andrew A. Chien .

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Editors and Affiliations

  1. IRIT, ENSEEIHT, Toulouse Cedex, France

    Michel Daydé

  2. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Osni Marques

  3. Information Technology Center, The University of Tokyo, Tokyo, Japan

    Kengo Nakajima

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© 2015 Springer International Publishing Switzerland

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Zheng, Z., Chien, A.A., Teranishi, K. (2015). Fault Tolerance in an Inner-Outer Solver: A GVR-Enabled Case Study. In: Daydé, M., Marques, O., Nakajima, K. (eds) High Performance Computing for Computational Science -- VECPAR 2014. VECPAR 2014. Lecture Notes in Computer Science(), vol 8969. Springer, Cham. https://doi.org/10.1007/978-3-319-17353-5_11

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  • DOI: https://doi.org/10.1007/978-3-319-17353-5_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17352-8

  • Online ISBN: 978-3-319-17353-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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