Binarized neural network of diode array with high concordance to vector–matrix multiplication

Abstract In this study, a binarized neural network (BNN) of silicon diode arrays achieved vector–matrix multiplication (VMM) between the binarized weights and inputs in these arrays. The diodes that operate in a positive-feedback loop in their p+-n-p-n+ device structure possess steep switching and b...

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Main Authors: Yunwoo Shin, Kyoungah Cho, Sangsig Kim
Format: Article
Language:English
Published: Nature Portfolio 2024-03-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-024-56575-4
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author Yunwoo Shin
Kyoungah Cho
Sangsig Kim
author_facet Yunwoo Shin
Kyoungah Cho
Sangsig Kim
author_sort Yunwoo Shin
collection DOAJ
description Abstract In this study, a binarized neural network (BNN) of silicon diode arrays achieved vector–matrix multiplication (VMM) between the binarized weights and inputs in these arrays. The diodes that operate in a positive-feedback loop in their p+-n-p-n+ device structure possess steep switching and bistable characteristics with an extremely low subthreshold swing (below 1 mV) and a high current ratio (approximately 108). Moreover, the arrays show a self-rectifying functionality and an outstanding linearity by an R-squared value of 0.99986, which allows to compose a synaptic cell with a single diode. A 2 × 2 diode array can perform matrix multiply-accumulate operations for various binarized weight matrix cases with some input vectors, which is in high concordance with the VMM, owing to the high reliability and uniformity of the diodes. Moreover, the disturbance-free, nondestructive readout, and semi-permanent holding characteristics of the diode arrays support the feasibility of implementing the BNN.
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spelling doaj.art-83756f46aba04eaaa245de1f3c1942082024-03-17T12:22:27ZengNature PortfolioScientific Reports2045-23222024-03-011411910.1038/s41598-024-56575-4Binarized neural network of diode array with high concordance to vector–matrix multiplicationYunwoo Shin0Kyoungah Cho1Sangsig Kim2Department of Electrical Engineering, Korea UniversityDepartment of Electrical Engineering, Korea UniversityDepartment of Electrical Engineering, Korea UniversityAbstract In this study, a binarized neural network (BNN) of silicon diode arrays achieved vector–matrix multiplication (VMM) between the binarized weights and inputs in these arrays. The diodes that operate in a positive-feedback loop in their p+-n-p-n+ device structure possess steep switching and bistable characteristics with an extremely low subthreshold swing (below 1 mV) and a high current ratio (approximately 108). Moreover, the arrays show a self-rectifying functionality and an outstanding linearity by an R-squared value of 0.99986, which allows to compose a synaptic cell with a single diode. A 2 × 2 diode array can perform matrix multiply-accumulate operations for various binarized weight matrix cases with some input vectors, which is in high concordance with the VMM, owing to the high reliability and uniformity of the diodes. Moreover, the disturbance-free, nondestructive readout, and semi-permanent holding characteristics of the diode arrays support the feasibility of implementing the BNN.https://doi.org/10.1038/s41598-024-56575-4Binarized neural networkMultiply-accumulateVector–matrix multiplicationGated p+-n-p-n+ diodesPositive-feedback loop mechanism
spellingShingle Yunwoo Shin
Kyoungah Cho
Sangsig Kim
Binarized neural network of diode array with high concordance to vector–matrix multiplication
Scientific Reports
Binarized neural network
Multiply-accumulate
Vector–matrix multiplication
Gated p+-n-p-n+ diodes
Positive-feedback loop mechanism
title Binarized neural network of diode array with high concordance to vector–matrix multiplication
title_full Binarized neural network of diode array with high concordance to vector–matrix multiplication
title_fullStr Binarized neural network of diode array with high concordance to vector–matrix multiplication
title_full_unstemmed Binarized neural network of diode array with high concordance to vector–matrix multiplication
title_short Binarized neural network of diode array with high concordance to vector–matrix multiplication
title_sort binarized neural network of diode array with high concordance to vector matrix multiplication
topic Binarized neural network
Multiply-accumulate
Vector–matrix multiplication
Gated p+-n-p-n+ diodes
Positive-feedback loop mechanism
url https://doi.org/10.1038/s41598-024-56575-4
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