Distributed Parallel Deep Learning for Fast Extraction of Similar Weather Map

Boseon Kang, Jae Heon Jeong, Chang-Sung Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For real time weather forecasting, it is necessary to search most similar weather map very fast among a large amount of data accumulated so far. Recently, deep learning is used for more accurate weather forecasting. However, it takes a huge amount of time for training deep learning model in order to process a number of previous weather maps. In this paper, we shall present fast distributed parallel algorithms for training deep neural network model based on CNN on parallel and distributed environment with GPUs for various number of models in order to extract most similar weather map from CNN. For each case of single and multi nodes, we compare the performance of our algorithm increasing the number of GPUs, and for the case of multi nodes, compare the performance for two ways of communications: synchronous and asynchronous. Also, we shall show the performance of our algorithm for the various number of models on single and multi nodes.

Original languageEnglish
Title of host publicationProceedings of TENCON 2018 - 2018 IEEE Region 10 Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1426-1429
Number of pages4
ISBN (Electronic)9781538654576
DOIs
Publication statusPublished - 2019 Feb 22
Event2018 IEEE Region 10 Conference, TENCON 2018 - Jeju, Korea, Republic of
Duration: 2018 Oct 282018 Oct 31

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume2018-October
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450

Conference

Conference2018 IEEE Region 10 Conference, TENCON 2018
CountryKorea, Republic of
CityJeju
Period18/10/2818/10/31

Fingerprint

Weather forecasting
Parallel algorithms
Deep learning
Communication
Graphics processing unit
Deep neural networks

Keywords

  • Deep learning
  • Distributed Environment
  • Similar weather map
  • Weather Prediction

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

Cite this

Kang, B., Jeong, J. H., & Jeong, C-S. (2019). Distributed Parallel Deep Learning for Fast Extraction of Similar Weather Map. In Proceedings of TENCON 2018 - 2018 IEEE Region 10 Conference (pp. 1426-1429). [8650104] (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2018-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2018.8650104

Distributed Parallel Deep Learning for Fast Extraction of Similar Weather Map. / Kang, Boseon; Jeong, Jae Heon; Jeong, Chang-Sung.

Proceedings of TENCON 2018 - 2018 IEEE Region 10 Conference. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1426-1429 8650104 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2018-October).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kang, B, Jeong, JH & Jeong, C-S 2019, Distributed Parallel Deep Learning for Fast Extraction of Similar Weather Map. in Proceedings of TENCON 2018 - 2018 IEEE Region 10 Conference., 8650104, IEEE Region 10 Annual International Conference, Proceedings/TENCON, vol. 2018-October, Institute of Electrical and Electronics Engineers Inc., pp. 1426-1429, 2018 IEEE Region 10 Conference, TENCON 2018, Jeju, Korea, Republic of, 18/10/28. https://doi.org/10.1109/TENCON.2018.8650104
Kang B, Jeong JH, Jeong C-S. Distributed Parallel Deep Learning for Fast Extraction of Similar Weather Map. In Proceedings of TENCON 2018 - 2018 IEEE Region 10 Conference. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1426-1429. 8650104. (IEEE Region 10 Annual International Conference, Proceedings/TENCON). https://doi.org/10.1109/TENCON.2018.8650104
Kang, Boseon ; Jeong, Jae Heon ; Jeong, Chang-Sung. / Distributed Parallel Deep Learning for Fast Extraction of Similar Weather Map. Proceedings of TENCON 2018 - 2018 IEEE Region 10 Conference. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1426-1429 (IEEE Region 10 Annual International Conference, Proceedings/TENCON).
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