@inproceedings{358de03a2d28417086e1d53f3e72a797,
title = "Ultra-low power neuromorphic computing with spin-torque devices",
abstract = "Emerging spin transfer torque (ST) devices such as lateral spin valves and domain wall magnets may lead to ultra-low-voltage, current-mode, spin-torque switches that can offer attractive computing capabilities, beyond digital switches. This paper reviews our work on ST-based non-Boolean data-processing applications, like neural-networks, which involve analog processing. Integration of such spin-torque devices with charge-based devices like CMOS can lead to highly energy-efficient information processing hardware for applicatons like pattern-matching, neuromorphic-computing, image-processing and data-conversion. Simulation results for analog image processing and associative computing has shown the possibility of ∼100X improvement in energy efficiency as compared to a 15nm CMOS ASIC.",
keywords = "analog, interconnect, logic, low power, neural networks, non-Boolean, programmable logic array, spin, threshold logic",
author = "Mrigank Sharad and Deliang Fan and Karthik Yogendra and Kaushik Roy",
year = "2013",
doi = "10.1109/E3S.2013.6705865",
language = "English (US)",
isbn = "9781479933723",
series = "2013 3rd Berkeley Symposium on Energy Efficient Electronic Systems, E3S 2013 - Proceedings",
booktitle = "2013 3rd Berkeley Symposium on Energy Efficient Electronic Systems, E3S 2013 - Proceedings",
note = "2013 3rd Berkeley Symposium on Energy Efficient Electronic Systems, E3S 2013 ; Conference date: 28-10-2013 Through 29-10-2013",
}