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• [7]
  

  2022 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2963591

  Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2022). Benchmarking Neuromorphic Hardware and Its Energy Expenditure. Frontiers in Neuroscience, 16, 873935. https://doi.org/10.3389/fnins.2022.873935

  PUB | PDF | DOI | Download (ext.) | WoS | PubMed | Europe PMC
   
• [6]
  

  2022 | Bielefelder E-Dissertation | PUB-ID: 2962759

  Ostrau, C. (2022). Energy and Performance Estimation for Neuromorphic Systems. Bielefeld: Universität Bielefeld. https://doi.org/10.4119/unibi/2962759

  PUB | PDF | DOI
   
• [5]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2942322

  Ostrau, C., Homburg, J. D., Klarhorst, C., Thies, M., & Rückert, U. (2020). Benchmarking Deep Spiking Neural Networks on Neuromorphic Hardware. Artificial Neural Networks and Machine Learning – ICANN 2020 Springer International Publishing. https://doi.org/10.1007/978-3-030-61616-8_49

  PUB | Dateien verfügbar | DOI | arXiv
   
• [4]
  

  2020 | Konferenzbeitrag | Veröffentlicht | PUB-ID: 2941831

  Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (2020). Benchmarking of Neuromorphic Hardware Systems. Neuro-inspired Computational Elements Workshop (NICE ’20), March 17–20, 2020, Heidelberg, Germany, International Conference Proceeding Series (ICPS) Association for Computing Machinery (ACM). https://doi.org/10.1145/3381755.3381772

  PUB | Dateien verfügbar | DOI
   
• [3]
  

  2019 | Konferenzbeitrag | Angenommen | PUB-ID: 2941207

  Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (Accepted). Comparing Neuromorphic Systems by Solving Sudoku Problems. Conference Proceedings: 2019 International Conference on High Performance Computing & Simulation (HPCS) Piscataway, NJ: IEEE. https://doi.org/10.1109/HPCS48598.2019.9188207

  PUB | Dateien verfügbar | DOI
   
• [2]
  

  2019 | Kurzbeitrag Konferenz / Poster | Angenommen | PUB-ID: 2935328

  Ostrau, C., Klarhorst, C., Thies, M., & Rückert, U. (Accepted). Benchmarking and Characterization of event-based Neuromorphic Hardware. Presented at the FastPath 2019 - International Workshop on Performance Analysis of Machine Learning Systems, Madison, Wisconsin, USA.

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• [1]
  

  2017 | Zeitschriftenaufsatz | Veröffentlicht | PUB-ID: 2913968

  Stöckel, A., Jenzen, C., Thies, M., & Rückert, U. (2017). Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware. Frontiers in Computational Neuroscience, 11, 71. doi:10.3389/fncom.2017.00071

  PUB | PDF | DOI | WoS | PubMed | Europe PMC