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ReconOS64: High-Performance Embedded Computing for Industrial Analytics on a Reconfigurable System-on-Chip

Published:21 June 2021Publication History

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References

  1. Andreas Agne, Markus Happe, Ariane Keller, Enno Lubbers, Bernhard Plattner, Marco Platzner, and Christian Plessl. 2014. ReconOS: An Operating System Approach for Reconfigurable Computing. 34, 1 (2014), 60--71. https://doi.org/10.1109/MM.2013.110Google ScholarGoogle Scholar
  2. Carlos Paiz Gatica and Marco Platzner. 2020. Adaptable Realization of Industrial Analytics Functions on Edge-Devices using Reconfigurable Architectures. In Machine Learning for Cyber Physical Systems (ML4CPS 2017). Springer.Google ScholarGoogle Scholar
  3. Hassan Ghasemzadeh Mohammadi, Rahil Arshad, Sneha Rautmare, Suraj Manjunatha, Maurice Kuschel, Felix Paul Jentzsch, Marco Platzner, Alexander Boschmann, and Dirk Schollbach. 2020. DeepWind: An Accurate Wind Turbine Condition Monitoring Framework via Deep Learning on Embedded Platforms. In 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) (Vienna, Austria, 2020-09). IEEE, 1431--1434. https://doi.org/10.1109/ETFA46521.2020.9211880Google ScholarGoogle ScholarCross RefCross Ref

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  1. ReconOS64: High-Performance Embedded Computing for Industrial Analytics on a Reconfigurable System-on-Chip

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        • Published in

          cover image ACM Other conferences
          HEART '21: Proceedings of the 11th International Symposium on Highly Efficient Accelerators and Reconfigurable Technologies
          June 2021
          76 pages
          ISBN:9781450385497
          DOI:10.1145/3468044

          Copyright © 2021 Owner/Author

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          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 21 June 2021

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