Mark Plagge
Orcid: 0000-0002-6903-911X
  According to our database1,
  Mark Plagge
  authored at least 13 papers
  between 2013 and 2025.
  
  
Collaborative distances:
Collaborative distances:
Timeline
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Bibliography
  2025
    IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., August, 2025
    
  
  2024
    Proceedings of the Neuro Inspired Computational Elements Conference, 2024
    
  
    Proceedings of the International Conference on Hardware/Software Codesign and System Synthesis, 2024
    
  
  2023
A Comparison of Spectral and Spatial Graph Convolutional Neural Network Kernels Using GraphSAGE-Sparse.
    
  
    Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023
    
  
Performance and Energy Simulation of Spiking Neuromorphic Architectures for Fast Exploration.
    
  
    Proceedings of the 2023 International Conference on Neuromorphic Systems, 2023
    
  
  2022
    Proceedings of the IEEE International Conference on Rebooting Computing, 2022
    
  
  2020
Extreme-scale neuromorphic architecture modeling using massively parallel optimistic simulation.
    
  
    PhD thesis, 2020
    
  
Comparing Neural Accelerators & Neuromorphic Architectures The False Idol of Operations.
    
  
    Proceedings of the NICE '20: Neuro-inspired Computational Elements Workshop, 2020
    
  
  2019
    Proceedings of the 2019 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, 2019
    
  
  2018
NeMo: A Massively Parallel Discrete-Event Simulation Model for Neuromorphic Architectures.
    
  
    ACM Trans. Model. Comput. Simul., 2018
    
  
Evaluating the Impact of Spiking Neural Network Traffic on Extreme-Scale Hybrid Systems.
    
  
    Proceedings of the 2018 IEEE/ACM Performance Modeling, 2018
    
  
  2016
NeMo: A Massively Parallel Discrete-Event Simulation Model for Neuromorphic Architectures.
    
  
    Proceedings of the 2016 annual ACM Conference on SIGSIM Principles of Advanced Discrete Simulation, 2016
    
  
  2013
Using artificial neural networks to predict first-year traditional students second year retention rates.
    
  
    Proceedings of the ACM Southeast Regional Conference 2013, 2013