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Low-Overhead Fault-Tolerance Support Using DISC Programming Model

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Languages and Compilers for Parallel Computing (LCPC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9519))

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Abstract

DISC is a newly proposed parallel programming paradigm that models many classes of iterative scientific applications through specification of a domain and interactions among domain elements. Accompanied with an associated runtime, it hides the details of inter-process communication and work partitioning (including partitioning in the presence of heterogeneous processing elements) from the programmers. In this paper, we show how these abstractions, particularly the concepts of compute-function and computation-space objects, can be also used to leverage low-overhead fault-tolerance support. While computation-space objects enable automated application level checkpointing, replicated execution of compute-functions helps detect soft errors with low overheads. Experimental results show the effectiveness of the proposed solutions.

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Notes

  1. 1.

    Please see https://software.sandia.gov/mantevo.

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Acknowledgments

This work was supported by National Science Foundation under the award CCF-1319420, and by the Department of Energy, Office of Science, under award DE-SC0014135.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, USA

    Mehmet Can Kurt & Gagan Agrawal

  2. Pacific Northwest National Laboratory, Richland, WA, USA

    Bin Ren

Authors
  1. Mehmet Can Kurt
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  2. Bin Ren
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  3. Gagan Agrawal
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Corresponding author

Correspondence to Mehmet Can Kurt .

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Editors and Affiliations

  1. North Carolina State University, Raleigh, North Carolina, USA

    Xipeng Shen

  2. North Carolina State University, Raleigh, North Carolina, USA

    Frank Mueller

  3. North Carolina State University, Raleigh, North Carolina, USA

    James Tuck

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Kurt, M.C., Ren, B., Agrawal, G. (2016). Low-Overhead Fault-Tolerance Support Using DISC Programming Model. In: Shen, X., Mueller, F., Tuck, J. (eds) Languages and Compilers for Parallel Computing. LCPC 2015. Lecture Notes in Computer Science(), vol 9519. Springer, Cham. https://doi.org/10.1007/978-3-319-29778-1_2

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  • DOI: https://doi.org/10.1007/978-3-319-29778-1_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29777-4

  • Online ISBN: 978-3-319-29778-1

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