@inproceedings{2b005e71fc3f4727a7c5c677271afc7f,
title = "Assessing Self-Repair on FPGAs with Biologically Realistic Astrocyte-Neuron Networks",
abstract = "This paper presents a hardware based implementation of a biologically-faithful astrocyte-based selfrepairing mechanism for Spiking Neural Networks. Spiking Astrocyte-neuron Networks (SANNs) are a new computing paradigm which capture the key mechanisms of how the human brain performs repairs. Using SANN in hardware affords the potential for realizing computing architecture that can self-repair. This paper demonstrates that Spiking Astrocyte Neural Network (SANN) in hardware have a resilience to significant levels of faults. The key novelty of the paper resides in implementing an SANN on FPGAs using fixed-point representation and demonstrating graceful performance degradation to different levels of injected faults via its self-repair capability. A fixed-point implementation of astrocyte, neurons and tripartite synapses are presented and compared against previous hardware floating-point and Matlab software implementations of SANN. All results are obtained from the SANN FPGA implementation and show how the reduced fixedpoint representation can maintain the biologically-realistic repair capability.",
keywords = "Astrocytes, Bio-inspired computing, FPGA, Self-repair, Spiking neural networks",
author = "Shvan Karim and Jim Harkin and Liam McDaid and Bryan Gardiner and Junxiu Liu and Halliday, {David M.} and Tyrrell, {Andy M.} and Jon Timmis and Alan Millard and Anju Johnson",
note = "Funding Information: The authors would like to acknowledge the EPSRC funding council grant (EP/N00714X/1 & EP/N007050/1) and Ulster University for supporting this research. Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2017 ; Conference date: 03-07-2017 Through 05-07-2017",
year = "2017",
month = jul,
day = "20",
doi = "10.1109/ISVLSI.2017.80",
language = "English",
series = "Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI",
publisher = "IEEE Press",
pages = "421--426",
editor = "Ricardo Reis and Mircea Stan and Michael Huebner and Nikolaos Voros",
booktitle = "Proceedings - 2017 IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2017",
address = "United States of America",
}