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Supercomputing with an Efficient Task Scheduler as an Infrastructure for Big Multimedia Processing

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Handbook of Multimedia Information Security: Techniques and Applications

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Abstract

Today, we are observing an intense utilization of computationally high-performance environments such as multiprocessor supercomputing systems for different scientific, economic, engineering, industry, and military purposes. One of the most demanding areas is indeed big data processing that needs a huge amount of computational capacity, and multimedia is responsible for more than 80% of the big data all over the world. Another recent and severe application is in conjunction with the development of deep learning and deep neural networks, the predominant technology to analyze multimedia content, where hundreds to thousands collaborative neural layers consume billions of operations, and cannot be operational unless the efficient and optimized computing environments can be provided. In this paper, an enhanced version of Cuckoo Optimization Algorithm (COA), named E-COA, is proposed to cope with static task-scheduling problem in multiprocessor supercomputing environments for processing big volume of multimedia data. E-COA is equipped with an adaptive and efficient non-stochastic egg-laying strategy that significantly improves the local and global search potentiality of the basic COA. Experiments on a comprehensive set of randomly-generated task-graphs with different structural parameters reveal the efficiency of the proposed approach from the performance point of view, especially for the small-scale samples, and where the number of processors in the machine is very restricted i.e. we are in the lack of computational resources.

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Notes

  1. 1.

    Highest Level First with Estimated Time.

  2. 2.

    Insertion Scheduling Heuristic.

  3. 3.

    Which uses the cluster-like CLANs to partition the task graph.

  4. 4.

    Localized Allocation of Static Tasks.

  5. 5.

    Earliest Time First.

  6. 6.

    Dynamic Level Scheduling.

  7. 7.

    Modified Critical Path.

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Acknowledgements

This work was supported by Sama Technical and Vocational Training College, Islamic Azad University, Shoushtar Branch, Shoushtar, Iran.

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  1. Sama Technical and Vocational Training College, Islamic Azad University, Shoushtar Branch, Shoushtar, Iran

    Hamid Reza Boveiri

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  1. Hamid Reza Boveiri
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Correspondence to Hamid Reza Boveiri .

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  1. Department of Computer Science and Engineering, NIT Patna, Patna, India

    Amit Kumar Singh

  2. Department of Electronics Engineering, Indian Institute of Technology, BHU, Varanasi, Uttar Pradesh, India

    Anand Mohan

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Boveiri, H.R. (2019). Supercomputing with an Efficient Task Scheduler as an Infrastructure for Big Multimedia Processing. In: Singh, A., Mohan, A. (eds) Handbook of Multimedia Information Security: Techniques and Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-15887-3_35

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  • DOI: https://doi.org/10.1007/978-3-030-15887-3_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15886-6

  • Online ISBN: 978-3-030-15887-3

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