@inproceedings{e7b55e458da340efba54ab3ce3e04b12,
title = "KeyRAM: A 0.34 uJ/decision 18 k decisions/s Recurrent Attention In-memory Processor for Keyword Spotting",
abstract = "This paper presents a 0.34 uJ/decision deep learning-based classifier for keyword spotting (KWS) in 65 nm CMOS with all weights stored on-chip. This work adapts a Recurrent Attention Model (RAM) algorithm for the KWS task, and employs an in-memory computing (IMC) architecture to achieve up to 9× savings in energy/decision and more than 23× savings in EDP of decisions over a state-of-the art IMC IC for KWS using the Google Speech dataset while achieving the highest reported decision throughput of 18.32 k decisions/s.",
keywords = "in-memory computing, keyword spotting, machine learning, recurrent attention networks",
author = "Hassan Dbouk and Gonugondla, {Sujan K.} and Charbel Sakr and Shanbhag, {Naresh R.}",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE Custom Integrated Circuits Conference, CICC 2020 ; Conference date: 22-03-2020 Through 25-03-2020",
year = "2020",
month = mar,
doi = "10.1109/CICC48029.2020.9075923",
language = "English (US)",
series = "Proceedings of the Custom Integrated Circuits Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE Custom Integrated Circuits Conference, CICC 2020",
address = "United States",
}