@inproceedings{bd7f06a255d14ff28c4de3d386533a2f,
title = "Low-power approximate convolution computing unit with domain-wall motion based {"}spin-memristor{"} for image processing applications",
abstract = "Convolution serves as the basic computational primitive for various associative computing tasks ranging from edge detection to image matching. CMOS implementation of such computations entails significant bottlenecks in area and energy consumption due to the large number of multiplication and addition operations involved. In this paper, we propose an ultra-low power and compact hybrid spintronic-CMOS design for the convolution computing unit. Low-voltage operation of domain-wall motion based magneto-metallic {"}Spin-Memristor{"}s interfaced with CMOS circuits is able to perform the convolution operation with reasonable accuracy. Simulation results of Gabor filtering for edge detection reveal ∼ 2.5× lower energy consumption compared to a baseline 45nm-CMOS implementation.",
author = "Yong Shim and Abhronil Sengupta and Kaushik Roy",
note = "Publisher Copyright: {\textcopyright} 2016 ACM.; 53rd Annual ACM IEEE Design Automation Conference, DAC 2016 ; Conference date: 05-06-2016 Through 09-06-2016",
year = "2016",
month = jun,
day = "5",
doi = "10.1145/2897937.2898042",
language = "English (US)",
series = "Proceedings - Design Automation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceedings of the 53rd Annual Design Automation Conference, DAC 2016",
address = "United States",
}