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Tuning lock-based multicore program based on sliding windows to tolerate data race

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Abstract

Because in-house debugging and test are difficult to discover all potential data races in multicore programs, it is necessary and significant to tolerate the potential data races in the production-run phase to secure the correct execution. However, the existing tolerating methods are limited to some kinds of data races. This paper proposes a new data-race tolerating approach, which can detect and adjust the data races whether it is in the protection of critical section or lack of protection to improve the correctness of multicore programs. It uses sliding windows to accommodate the memory instructions in critical section or recent memory instructions lack of protection and detects the potential data races which are more likely to cause errors. Then, by delaying the critical reversion points, data races are adjusted to reduce the probability of software failure. To implement the tolerating approach, the current multicore processor need not change its original cache coherence protocol and just adds very little hardware. Simulation results show that it brings low hardware, low bandwidth overhead, and negligible slowdown.

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Acknowledgements

The research has been supported by National Natural Youth Science Foundation of China (61502123), Heilongjiang Provincial Youth Science Foundation (QC2015084), and the National Key R&D Plan of China (2017YFB1302701). We thank the anonymous reviewers and our group members for their comments.

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Authors and Affiliations

  1. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China

    Suxia Zhu & Guanglu Sun

  2. School of Mechatronics Engineering, Harbin Institute of Technology, Harbin, 150001, China

    Zhigang Chen

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  1. Suxia Zhu
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  2. Zhigang Chen
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  3. Guanglu Sun
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Correspondence to Zhigang Chen.

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Zhu, S., Chen, Z. & Sun, G. Tuning lock-based multicore program based on sliding windows to tolerate data race. J Supercomput 75, 7872–7894 (2019). https://doi.org/10.1007/s11227-019-02921-7

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