@inproceedings{4a8a1a16975a44a78a616bc839dfe97d,
title = "Integrated Sensing and Computing using Energy-Efficient Magnetic Synapses",
abstract = "This work presents a processing-in-sensor platform leveraging magnetic devices as a flexible and efficient solution for real-time and smart image processing in AI devices. The main idea is to combine the typical sensing mechanism with an intrinsic coarse-grained convolution operation at the edge to remarkably reduce the power consumption of data conversion and transmission to an off-chip processor imposed by the first layer of deep neural networks. Our initial results demonstrate acceptable accuracy on the SVHN image data-set, while the proposed platform substantially reduces data conversion and transmission energy compared with a baseline sensor-CPU platform.",
keywords = "In-sensor computing, image processing, magnetic memories",
author = "Shaahin Angizi and Arman Roohi",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 23rd International Symposium on Quality Electronic Design, ISQED 2022 ; Conference date: 06-04-2022 Through 07-04-2022",
year = "2022",
doi = "10.1109/ISQED54688.2022.9806293",
language = "English (US)",
series = "Proceedings - International Symposium on Quality Electronic Design, ISQED",
publisher = "IEEE Computer Society",
booktitle = "Proceedings of the 23rd International Symposium on Quality Electronic Design, ISQED 2022",
address = "United States",
}