A Machine Learning Approach to Predicting Single Event Upsets

Archit Gupta, Chong Yock Eng, Deon Lim Meng Wee, Rashna Analia Ahmed, See Min Sim
10/9/2023
cs.LG

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Abstract

A single event upset (SEU) is a critical soft error that occurs in semiconductor devices on exposure to ionising particles from space environments. SEUs cause bit flips in the memory component of semiconductors. This creates a multitude of safety hazards as stored information becomes less reliable. Currently, SEUs are only detected several hours after their occurrence. CREMER, the model presented in this paper, predicts SEUs in advance using machine learning. CREMER uses only positional data to predict SEU occurrence, making it robust, inexpensive and scalable. Upon implementation, the improved reliability of memory devices will create a digitally safer environment onboard space vehicles.

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Cite this paper

@article{gupta2023machine,
  title  = {A Machine Learning Approach to Predicting Single Event Upsets},
  author = {Archit Gupta and Chong Yock Eng and Deon Lim Meng Wee and Rashna Analia Ahmed and See Min Sim},
  year   = {2023},
  eprint = {2310.05878},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2310.05878v1}
}

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