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Paper Abstract and Keywords
Presentation 2019-11-15 16:10
Analysis of databases used for hot spot test cases
Hiroki Ogura, Hidekazu Takahashi, Sinpei Sato, Atsushi Takahashi (Tokyo Tech) VLD2019-52 DC2019-76
Abstract (in Japanese) (See Japanese page) 
(in English) With the miniaturization of semiconductor circuit patterns, the importance of photolithography has increased. In the state-of-the-art process, design rules are established to obtain fine and dense circuit patterns. However, there are places in the layout that are likely to cause defects called hot spots due to manufacturing variations. If a hot spot exists in the layout, modify the layout to eliminate the hot spot. Lithography simulation is generally used to eliminate hot spots. Layout modification using simulation is time consuming and requires a great deal of cost to eliminate one hot spot. For this reason, attention has been paid to a method that efficiently eliminates the huge number of hot spots on the layout. In the machine learning-based hot spot detection method, feature quantity, machine learning model selection and learning data are important for accurate detection. In terms of what, when the reliability of the learning data is low, even if the correctness of the detection result in machine learning is correct, there may be factors other than the feature selection and the performance of the selected learning model. The evaluation may not be performed correctly. This paper analyzes ICCAD 2012 benchmark data, which is a frequently used database. As a result, it was confirmed that ICCAD 2012 benchmark data had similar data trends between training data and test data, but there was no data diversity. From these facts, we have concluded that there are insufficient elements as learning data and that a better data set should be used.
Keyword (in Japanese) (See Japanese page) 
(in English) Hotspot / ICCAD 2012 benchmark data / / / / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 282, VLD2019-52, pp. 191-196, Nov. 2019.
Paper # VLD2019-52 
Date of Issue 2019-11-06 (VLD, DC) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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 VLD2019-52 DC2019-76

Conference Information
Conference Date 2019-11-13 - 2019-11-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Ehime Prefecture Gender Equality Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Design Gaia 2019 -New Field of VLSI Design- 
Paper Information
Registration To VLD 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of databases used for hot spot test cases 
Sub Title (in English)  
Keyword(1) Hotspot  
Keyword(2) ICCAD 2012 benchmark data  
1st Author's Name Hiroki Ogura  
1st Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
2nd Author's Name Hidekazu Takahashi  
2nd Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
3rd Author's Name Sinpei Sato  
3rd Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
4th Author's Name Atsushi Takahashi  
4th Author's Affiliation Tokyo Institute of Technology (Tokyo Tech)
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Date Time 2019-11-15 16:10:00 
Presentation Time 25 
Registration for VLD 
Paper # IEICE-VLD2019-52,IEICE-DC2019-76 
Volume (vol) IEICE-119 
Number (no) no.282(VLD), no.283(DC) 
Page pp.191-196 
#Pages IEICE-6 
Date of Issue IEICE-VLD-2019-11-06,IEICE-DC-2019-11-06 

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