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Automatic Parameter Tuning of Hierarchical Incremental Checkpointing

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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))

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Abstract

As future HPC systems become larger, the failure rates and the cost of checkpointing to the global file system are expected to increase. Hierarchical incremental CPR is a promising approach to solve this problem. It utilizes a hierarchical storage system of local and global storages and performs incremental checkpointing by writing only updated memory pages between two consecutive checkpoints. In this paper, we response to an open question; how to optimize the checkpoint interval when the checkpoint overheads are changing with time as in hierarchical incremental CPR. We propose a runtime checkpoint interval autotuning technique to optimize the efficiency of hierarchical incremental CPR. Evaluation results show that the efficiency can be significantly increased if the storage hierarchy can be exploited with appropriate checkpoint intervals.

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Acknowledgments

This research is partially supported by JST CREST “An Evolutionary Approach to Construction of a Software Development Environment for Massively-Parallel Heterogeneous Systems” and Grant-in-Aid for Scientific Research(B) #25280041. The first author, Alfian Amrizal, is financially supported by Monbukagakusho.

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Authors and Affiliations

  1. Graduate School of Information Science, Tohoku University, Sendai, Miyagi, 980-8578, Japan

    Alfian Amrizal, Shoichi Hirasawa, Hiroyuki Takizawa & Hiroaki Kobayashi

  2. Cyberscience Center, Tohoku University, Sendai, Japan

    Hiroaki Kobayashi

  3. Japan Science and Technology Agency, CREST, Kawaguchi, Japan

    Alfian Amrizal, Shoichi Hirasawa, Hiroyuki Takizawa & Hiroaki Kobayashi

Authors
  1. Alfian Amrizal
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  2. Shoichi Hirasawa
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  3. Hiroyuki Takizawa
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  4. Hiroaki Kobayashi
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Corresponding author

Correspondence to Hiroyuki Takizawa .

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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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Amrizal, A., Hirasawa, S., Takizawa, H., Kobayashi, H. (2015). Automatic Parameter Tuning of Hierarchical Incremental Checkpointing. 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_25

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  • DOI: https://doi.org/10.1007/978-3-319-17353-5_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17352-8

  • Online ISBN: 978-3-319-17353-5

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