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| Presentation | 2020-01-17 13:15 [Poster Presentation] Investigation of Placement Order Optimization for Adiabatic Quantum- Flux-Parametron Integrated Circuits via Machine Learning Takehisa Yamada, Christopher L. Ayala, Ro Saito, Tomoyuki Tanaka, Nobuyuki Yoshikawa (Yokohama Natl Univ)  SCE2019-55 Link to ES Tech. Rep. Archives: SCE2019-55 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Adiabatic quantum-flux-parametron (AQFP) logic is one kind of superconducting logic family featuring low energy and high computational speed compared to CMOS. Because of its unique structure, we cannot immediately apply CMOS EDA tools to AQFP circuits. In previous studies, we developed an AQFP cell placement optimization tool using the genetic algorithm (GA). However, GA-based optimization time is enormous when it is applied to very large integrated circuits (IC). In this study, we have been focusing on optimization by machine learning. Once such an optimization model has been created, an optimized placement result can be obtained very quickly by utilizing the model. We first generated pseudo-circuit data, and we trained an order optimization model using the pseudo-circuit data. To apply machine learning to the placement optimization problem, a series data must be created from the AQFP graph data. In this paper, we propose the following two methods. In the first method, we create feature vectors for each AQFP cell from the graph data to make the series data. In the second method, we optimize the placement order by applying the vectors in machine learning. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | AQFP / placement / optimization / machine learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 369, SCE2019-55, pp. 103-105, Jan. 2020. | |
| Paper # | SCE2019-55 | |
| Date of Issue | 2020-01-09 (SCE) | |
| ISSN | Print edition: ISSN 0913-5685 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) | |
| Download PDF | SCE2019-55 Link to ES Tech. Rep. Archives: SCE2019-55 |
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| Conference Information | |
| Committee | SCE |
| Conference Date | 2020-01-16 - 2020-01-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SCE |
| Conference Code | 2020-01-SCE |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Investigation of Placement Order Optimization for Adiabatic Quantum- Flux-Parametron Integrated Circuits via Machine Learning |
| Sub Title (in English) | |
| Keyword(1) | AQFP |
| Keyword(2) | placement |
| Keyword(3) | optimization |
| Keyword(4) | machine learning |
| Keyword(5) | |
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| 1st Author's Name | Takehisa Yamada |
| 1st Author's Affiliation | Yokohama National University (Yokohama Natl Univ) |
| 2nd Author's Name | Christopher L. Ayala |
| 2nd Author's Affiliation | Yokohama National University (Yokohama Natl Univ) |
| 3rd Author's Name | Ro Saito |
| 3rd Author's Affiliation | Yokohama National University (Yokohama Natl Univ) |
| 4th Author's Name | Tomoyuki Tanaka |
| 4th Author's Affiliation | Yokohama National University (Yokohama Natl Univ) |
| 5th Author's Name | Nobuyuki Yoshikawa |
| 5th Author's Affiliation | Yokohama National University (Yokohama Natl Univ) |
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| Speaker | Author-1 |
| Date Time | 2020-01-17 13:15:00 |
| Presentation Time | 135 minutes |
| Registration for | SCE |
| Paper # | SCE2019-55 |
| Volume (vol) | vol.119 |
| Number (no) | no.369 |
| Page | pp.103-105 |
| #Pages | 3 |
| Date of Issue | 2020-01-09 (SCE) |
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