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Research Article | Open Access |

Spin-Then-Sleep: A Machine Learning Alternative to Queue-based Spin-then-Block Strategy

Author 1: Fadai Ganjaliyev
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 10, No. 3 · Published 2019

DOI: https://doi.org/10.14569/IJACSA.2019.0100377

Abstract

One of the issues with spinlock protocols is excessive spinning which results in a waste of CPU cycles. Some protocols use the hybrid, spin-then-block approach to avoid this problem. In this case, the contending thread may prefer relinquishing the CPU instead of spinning, and resumes execution once notified. This paper presents a machine learning framework for intelligent sleeping and spinning as an alternative to the spin-then-block strategy. This framework can be used to address one of the challenges faced by this strategy: the delay in the critical path. The work suggests a reinforcement learning based approach for queue-based locks that aims at having threads learn to spin or sleep. The challenges of the suggested technique and future work are also discussed.

Keywords

How to Cite this Article

Fadai Ganjaliyev. "Spin-Then-Sleep: A Machine Learning Alternative to Queue-based Spin-then-Block Strategy". International Journal of Advanced Computer Science and Applications (IJACSA), Vol. 10, No. 3, 2019. https://doi.org/10.14569/IJACSA.2019.0100377

BibTeX

@article{Ganjaliyev2019,
  title     = {Spin-Then-Sleep: A Machine Learning Alternative to Queue-based Spin-then-Block Strategy},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {3},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {Fadai Ganjaliyev},
  doi       = {10.14569/IJACSA.2019.0100377},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100377}
}

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