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Volumn , Issue , 2018, Pages 218-219

High performance computing and industry 4.0: Experiences from the DISRUPT project

Author keywords

High performance computing; Industrial internet of things; Industry 4.0

Indexed keywords

EMBEDDED SYSTEMS; INDUSTRY 4.0;

EID: 85061001360     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/3229631.3264660     Document Type: Conference Paper
Times cited : (9)

References (14)
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  • 2
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    • Rafael Ferreira da Silva, Rosa Filgueira, Ilia Pietri, Ming Jiang, Rizos Sakellariou, and Ewa Deelman. 2017. A characterization of workflow management systems for extreme-scale applications. Future Generation Computer Systems 75 (2017), 228-238. DOI: http://dx. doi. org/https://doi. org/10. 1016/j. future. 2017. 02. 026
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    • Ferreira Da Silva, R.1    Filgueira, R.2    Pietri, I.3    Jiang, M.4    Sakellariou, R.5    Deelman, E.6
  • 4
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    • An evaluation of information consistency in grid information systems
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    • Laurence Field and Rizos Sakellariou. 2017. An Evaluation of Information Consistency in Grid Information Systems. Journal of Grid Computing 15, 1 (01 Mar 2017), 127-137. DOI: http://dx. doi. org/10. 1007/s10723-016-9373-z
    • (2017) Journal of Grid Computing , vol.15 , Issue.1 , pp. 127-137
    • Field, L.1    Sakellariou, R.2
  • 6
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    • Sustainable Industry 4. 0 framework: A systematic literature review identifying the current trends and future perspectives
    • 2018 https://doi. org/10. 1016/j. psep. 2018. 05. 009
    • Sachin S. Kamble, Angappa Gunasekaran, and Shradha A. Gawankar. 2018. Sustainable Industry 4. 0 framework: A systematic literature review identifying the current trends and future perspectives. Process Safety and Environmental Protection 117 (2018), 408-425. DOI: http://dx. doi. org/https://doi. org/10. 1016/j. psep. 2018. 05. 009
    • (2018) Process Safety and Environmental Protection , vol.117 , pp. 408-425
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    • S. Kodiyalam, R. J. Yang, L. Gu, and C.-H. Tho. 2004. Multidisciplinary design optimization of a vehicle system in a scalable, high performance computing environment. Structural and Multidisciplinary Optimization 26, 3 (01 Feb 2004), 256-263. DOI: http://dx. doi. org/10. 1007/s00158-003-0343-2
    • (2004) Structural and Multidisciplinary Optimization , vol.26 , Issue.3 , pp. 256-263
    • Kodiyalam, S.1    Yang, R.J.2    Gu, L.3    Tho, C.-H.4
  • 9
    • 84904510850 scopus 로고    scopus 로고
    • Cyber-physical production systems: Roots, expectations and r&d challenges
    • 2014 https://doi. org/10. 1016/j. procir. 2014. 03. 115
    • László Monostori. 2014. Cyber-physical Production Systems: Roots, Expectations and R&D Challenges. Procedia CIRP 17 (2014), 9-13. DOI: http://dx. doi. org/https://doi. org/10. 1016/j. procir. 2014. 03. 115
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  • 12
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    • Daniel A. Reed and Jack Dongarra. 2015. Exascale Computing and Big Data. Commun. ACM 58, 7 (June 2015), 56-68. DOI: http://dx. doi. org/10. 1145/2699414
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  • 13
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    • Data processing in industrie 4. 0
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    • Frank Werner and Robert Woitsch. 2018. Data Processing in Industrie 4. 0. Datenbank-Spektrum 18, 1 (01 Mar 2018), 15-25. DOI: http://dx. doi. org/10. 1007/s13222-018-0277-x
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    • Internet of things in industries: A survey
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    • Li Da Xu, Wu He, and Shancang Li. 2014. Internet of Things in Industries: A Survey. IEEE Transactions on Industrial Informatics 10, 4 (Nov 2014), 2233-2243. DOI: http://dx. doi. org/10. 1109/TII. 2014. 2300753
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.