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Paper Abstract and Keywords
Presentation 2022-12-16 13:50
Evaluation of Fault Tolerance in Stochastic Computing Based Neural Network Inference Accelerators
Ryoga Nagashima, Stefan Holst, Xiaoqing Wen (Kyutech) DC2022-74
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, neural networks have become increasingly complex. Stochastic computing (SC) techniques are currently being explored to address the increased circuit area and power consumption. Besides area and power benefits of SC, fault tolerance is often mentioned as a big advantage over classic binary computing. However, the effects of faults in SC have yet to be fully investigated. In this study, we focus on the fault tolerance of stochastic computing and implement the processing element (PE) of a neural network using a conventional binary circuit and a stochastic computing circuit, and conduct a comparative evaluation of the fault-tolerant performance.
Keyword (in Japanese) (See Japanese page) 
(in English) Stochastic / Neural Network / Fault / / / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 318, DC2022-74, pp. 12-16, Dec. 2022.
Paper # DC2022-74 
Date of Issue 2022-12-09 (DC) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
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)
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Conference Information
Committee DC  
Conference Date 2022-12-16 - 2022-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Safety, etc. 
Paper Information
Registration To DC 
Conference Code 2022-12-DC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of Fault Tolerance in Stochastic Computing Based Neural Network Inference Accelerators 
Sub Title (in English)  
Keyword(1) Stochastic  
Keyword(2) Neural Network  
Keyword(3) Fault  
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1st Author's Name Ryoga Nagashima  
1st Author's Affiliation Kyushu Institute of Technology (Kyutech)
2nd Author's Name Stefan Holst  
2nd Author's Affiliation Kyushu Institute of Technology (Kyutech)
3rd Author's Name Xiaoqing Wen  
3rd Author's Affiliation Kyushu Institute of Technology (Kyutech)
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Speaker Author-1 
Date Time 2022-12-16 13:50:00 
Presentation Time 20 minutes 
Registration for DC 
Paper # DC2022-74 
Volume (vol) vol.122 
Number (no) no.318 
Page pp.12-16 
#Pages 5 
Date of Issue 2022-12-09 (DC) 

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