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Paper Abstract and Keywords
Presentation 2021-08-05 14:25
Digital Implement of 3-layered Neural Networks with Stochastic Activation, Shunting Inhibition, and a Dual-rail Backpropagation
Yoshiaki Sasaki, Seiya Muramatsu, Kohei Nishida, Megumi Akai-Kasaya, Tetsuya Asai (Hokkaido Univ.) CCS2021-16
Abstract (in Japanese) (See Japanese page) 
(in English) Stochastic computing (SC) is an arithmetic technique that enables various operations to be performed with a small number of logic gates in exchange for operational accuracy. In this paper, we discuss the realization of an edge AI integrated circuit with a learning function based on the SC. First, we propose a logic circuit that realizes an area-efficient activation function that does not require decoding in the midst of forward operations. Next, we propose a method to realize an operation equivalent to subtraction, which is considered to be difficult in SC, as well as propose a new arithmetic method that mimics the synaptic transmission of neural circuits. By assuming the input to the activation function, we also propose a summation operation that utilizes imperfect addition, which has rarely been used in SC. By introducing these arithmetic methods, we propose a digital implementation of a multilayer perceptron based on the SC. First, we learn simple logic operations and then learn linear and nonlinear regression problems. We then demonstrate the feasibility of SC-based machine learning. The method presented herein will expand the options of edge AI integrated circuits using SC and may contribute to the development of edge AI integrated circuits in the future.
Keyword (in Japanese) (See Japanese page) 
(in English) Stochastic Computing / Machine Learning / Neural Network / Edge AI Integrated Circuit / Backpropagation / / /  
Reference Info. IEICE Tech. Rep., vol. 121, no. 134, CCS2021-16, pp. 7-13, Aug. 2021.
Paper # CCS2021-16 
Date of Issue 2021-07-29 (CCS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
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reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF CCS2021-16

Conference Information
Committee IN CCS  
Conference Date 2021-08-05 - 2021-08-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network Science, Future Network, Cloud/SDN/Virtualization, Contents Delivery/Contents Exchange, and others 
Paper Information
Registration To CCS 
Conference Code 2021-08-IN-CCS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Digital Implement of 3-layered Neural Networks with Stochastic Activation, Shunting Inhibition, and a Dual-rail Backpropagation 
Sub Title (in English)  
Keyword(1) Stochastic Computing  
Keyword(2) Machine Learning  
Keyword(3) Neural Network  
Keyword(4) Edge AI Integrated Circuit  
Keyword(5) Backpropagation  
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1st Author's Name Yoshiaki Sasaki  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Seiya Muramatsu  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Kohei Nishida  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Megumi Akai-Kasaya  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
5th Author's Name Tetsuya Asai  
5th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker
Date Time 2021-08-05 14:25:00 
Presentation Time 25 
Registration for CCS 
Paper # IEICE-CCS2021-16 
Volume (vol) IEICE-121 
Number (no) no.134 
Page pp.7-13 
#Pages IEICE-7 
Date of Issue IEICE-CCS-2021-07-29 


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