Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Emulearner: Deep Learning Library for Utilizing Emulab

  • Song, Gi-Beom (Department of Computer Engineering, Hannam University) ;
  • Lee, Man-Hee (Department of Computer Engineering, Hannam University)
  • Received : 2018.06.29
  • Accepted : 2018.10.30
  • Published : 2018.12.31
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Abstract

Recently, deep learning has been actively studied and applied in various fields even to novel writing and painting in ways we could not imagine before. A key feature is that high-performance computing device, especially CUDA-enabled GPU, supports this trend. Researchers who have difficulty accessing such systems fall behind in this fast-changing trend. In this study, we propose and implement a library called Emulearner that helps users to utilize Emulab with ease. Emulab is a research framework equipped with up to thousands of nodes developed by the University of Utah. To use Emulab nodes for deep learning requires a lot of human interactions, however. To solve this problem, Emulearner completely automates operations from authentication of Emulab log-in, node creation, configuration of deep learning to training. By installing Emulearner with a legitimate Emulab account, users can focus on their research on deep learning without hassle.

Keywords

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Fig. 1. Begin an Experiment page.

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Fig. 2. Experiment creation page.

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Fig. 3. Node and topology creation.

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Fig. 4. Reserved node Information.

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Fig. 5. Node Information.

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Fig. 6. TensorFlow installation command.

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Fig. 7. Tensorflow script editing.

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Fig. 8. Script running command.

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Fig. 9. Library usage example.

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Fig. 10. Learning() source code.

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Fig. 11. Total overhead and preparation time prediction.

Table 1. Units for magnetic properties

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Table 2. User and library overhead

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References

  1. J. H. Park, "Understand of artificial intelligence: approach by cognitive science," Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, vol. 6, no. 10, pp. 539-547, 2016. DOI: 10.14257/AJMAHS.2016.10.44.
  2. Amazon AWS Deep Learning AMI [Internet], Available: https://aws.amazon.com/ko/machine-learning/amis/.
  3. Microsoft Azure Machine Learning Studio [Internet], Available: https://azure.microsoft.com/en-us/services/machine-learning-studio/.
  4. IBM Deep Learning [Internet], Available: https://www.ibm.com/cloud/deep-learning.
  5. Google Cloud Machine Learning Engine [Internet], Available: https://cloud.google.com/ml-engine/.
  6. M. H. Lee and W. J. Seok, "Research on the trend of utilizing Emulab as cyber security research framework," Journal of the Korea Institute of Information Security and Cryptology, vol. 23, no. 6, pp. 1169-1180, 2013. DOI: 10.13089/JKIISC.2013.23.6.1169.
  7. KREONet Emulab [Internet], Available: https://www.emulab.kreonet.net/.
  8. N. Gupta, "Artificial neural network," Network and Complex Systems, vol. 3, no. 1, pp. 24-28, 2013.
  9. M. Abadi, P. Barham, J. Chen, Z. Chen, A. Davis, J. Dean, et al., "TensorFlow: a system for large-scale machine learning," in Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI), Savannah, GA, pp. 265-283, 2016.
  10. Ubuntu package, "python-dev," [Internet], Available: https://packages.ubuntu.com/search?keywords=python-dev.
  11. Ubuntu package, "python-pip," [Internet], Available: https://packages.ubuntu.com/search?keywords=python-pip.
  12. Python Software Foundation, "urllib2," [Internet], Available: https://docs.python.org/2/library/urllib2.html
  13. Python Software Foundation, "mechanize," [Internet], Available: https://pypi.org/project/mechanize/.
  14. PuTTY: a free SSH and telnet client for Windows [Internet], Available: https://www.putty.org/.
  15. J. Gu, Z. Wang, J. Kuen, L. Ma, A. Shahroudy, B. Shuai, et al., "Recent advances in convolutional neural networks," Pattern Recognition, vol. 77, pp. 354-377, 2018. DOI: 10.1016/j.patcog.2017.10.013.