@inproceedings{b75a9cb21d3e4a7c87e6f802b7a76f71,
title = "A variation robust inference engine based on STT-MRAM with parallel read-out",
abstract = "STT-MRAM is a promising candidate as embedded non-volatile memory (NVM) at 28nm and beyond. Due to its limited on/off ratio, STT-MRAM is often used as digital memory that only allows row-by-row read-out for near-memory computing. This work proposes design strategies to overcome this limitation with a new bit-cell design to enable parallel read-out for in-memory computing, which is of great interests for deep neural network (DNN) acceleration. We consider the non-ideal device properties that degrade inference accuracy including small on/off ratio, cell-to-cell MTJ conductance variation and current sense amplifier (CSA) offset. We propose three techniques to minimize inference accuracy degradation: 1) a 2T-2MTJ bit-cell design with high on/off ratio, 2) redundancy for MSB weights to mitigate the impact of MTJ conductance variations, and 3) a hybrid-layer mapping scheme to reduce column current thus mitigating CSA offset effect. DNN benchmarking results show that on CIFAR-10 dataset, the inference accuracy can be maintained at > 90% in the presence of 10% MTJ conductance variations, and >87.5% after considering CSA offset effect, with minimal 8% energy and 4% chip area overhead.",
keywords = "DNN, In-memory computing, STT-MRAM",
author = "Yandong Luo and Xiaochen Peng and Ryan Hatcher and Titash Rakshit and Jorge Kittl and Rodder, {Mark S.} and Seo, {Jae Sun} and Shimeng Yu",
note = "Funding Information: This work is in part supported by ASCENT, one of the SRC/DARPA JUMP centers, and Samsung Electronics. Publisher Copyright: {\textcopyright} 2020 IEEE; 52nd IEEE International Symposium on Circuits and Systems, ISCAS 2020 ; Conference date: 10-10-2020 Through 21-10-2020",
year = "2020",
language = "English (US)",
series = "Proceedings - IEEE International Symposium on Circuits and Systems",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2020 IEEE International Symposium on Circuits and Systems, ISCAS 2020 - Proceedings",
}