@inproceedings{5b6fe58312474d4e8ba888d4850551e3,
title = "TID Response of an Analog In-Memory Neural Network Accelerator",
abstract = "A vector-matrix multiply (VMM) characterization chip was designed and fabricated in 350nm CMOS, including pulsers and a 10-bit analog to digital converter. The response of total ionizing dose (TID) was assessed using gamma radiation from a Cobalt-60 source. Inference was performed in situ during irradiation and VMMs computed by the accelerator were measured at increasing TID levels. Experimental results were used to create a circuit model, which was enabled a neural network accuracy simulation with CrossSim. Accuracy degradation on the CIFAR-10 task was a function of network architecture and was significantly reduced following >150 krad exposure.",
author = "B. Tolleson and C. Bennett and Xiao, \{T. Patrick\} and D. Wilson and J. Short and J. Kim and Hughart, \{D. R.\} and N. Gilbert and S. Agarwal and Barnaby, \{H. J.\} and Marinella, \{M. J.\}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 61st IEEE International Reliability Physics Symposium, IRPS 2023 ; Conference date: 26-03-2023 Through 30-03-2023",
year = "2023",
doi = "10.1109/IRPS48203.2023.10118139",
language = "English (US)",
series = "IEEE International Reliability Physics Symposium Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2023 IEEE International Reliability Physics Symposium, IRPS 2023 - Proceedings",
}