Mark Plagge

Orcid: 0000-0002-6903-911X

According to our database1, Mark Plagge authored at least 12 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Expressive Dendrites in Spiking Networks.
Proceedings of the Neuro Inspired Computational Elements Conference, 2024

Tutorial: Large-Scale Spiking Neuromorphic Architecture Exploration using SANA-FE.
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
ATHENA: Enabling Codesign for Next-Generation AI/ML Architectures.
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
Using Scientific Visualization Techniques to Visualize Parallel Network Simulations.
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


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