PUB - Publikationen an der Universität Bielefeld

Alle markieren

• [10]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982048

  Mika K, Griessl R, Kucza N, et al. VEDLIoT. Next generation accelerated AIoT systems and applications. In: CF '23: Proceedings of the 20th ACM International Conference on Computing Frontiers. New York, NY: ACM; 2023: 291-296.

  PUB | DOI
   
• [9]
  

  2023 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2979799

  Griessl R, Porrmann F, Kucza N, et al. Evaluation of heterogeneous AIoT Accelerators within VEDLIoT. In: 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE). IEEE; 2023: 1-6.

  PUB | DOI
   
• [8]
  

  2022 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2964196

  Kaiser M, Griessl R, Kucza N, et al. VEDLIoT: Very Efficient Deep Learning in IoT. In: Institut of Electrical and Electronics Engineers (IEEE), ed. DATE '22: Proceedings of the 2022 Conference & Exhibition on Design, Automation & Test in Europe. Leuven: European Design and Automation Association; 2022: 963-968.

  PUB | DOI
   
• [7]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982047

  Salami B, Parasyris K, Cristal A, et al. LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing. In: 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE). Piscataway, NJ: IEEE; 2020: 169-174.

  PUB | DOI
   
• [6]
  

  2020 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2941646

  Pilz S, Porrmann F, Kaiser M, Hagemeyer J, Hogan JM, Rückert U. Accelerating Binary String Comparisons with a Scalable, Streaming-Based System Architecture Based on FPGAs. Algorithms. 2020;13(2): 47.

  PUB | PDF | DOI | Download (ext.) | WoS
   
• [5]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2982045

  Cristal A, Unsal OS, Martorell X, et al. LEGaTO. First steps towards energy-efficient toolset for heterogeneous computing. In: SAMOS '18. Proceedings of the 18th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation. New York, NY: ACM; 2018: 210-217.

  PUB | DOI
   
• [4]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2979448

  Cristal A, Unsal OS, Martorell X, et al. LEGaTO. First steps towards energy-efficient toolset for heterogeneous computing. In: Mudge T, ed. Proceedings of the 18th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation. New York, NY, USA: ACM; 2018: 210-217.

  PUB | DOI
   
• [3]
  

  2018 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2955564

  Cristal A, Unsal OS, Martorell X, et al. LEGaTO Project: Towards Energy-Efficient, Secure, Fault-tolerant Toolset for Heterogeneous Computing. In: Kaeli D, ed. Proceedings of the 15th ACM International Conference on Computing Frontiers. New York, NY: ACM; 2018: 276-278.

  PUB | DOI | Download (ext.)
   
• [2]
  

  2018 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2918788

  Kaiser M, Pilz S, Porrmann F, Hagemeyer J, Porrmann M. Accelerating Hamming Distance Comparisons for Locality Sensitive Hashing (LSH) using FPGAs. In: 12th CeBiTec Symposium - Big Data in Medicine and Biotechnology - Abstract Book. Vol 12. Bielefeld; 2018: 48-49.

  PUB | PDF
   
• [1]
  

  2017 | Kurzbeitrag Konferenz / Poster | Veröffentlicht | PUB-ID: 2918683

  Kaiser M, Griessl R, Hagemeyer J, et al. A Reconfigurable Heterogeneous Microserver Architecture for Energy-efficient Computing. In: Third International Workshop on Heterogeneous High-performance Reconfigurable Computing (H2RC'17). Denver, CO; 2017.

  PUB | PDF | Download (ext.)