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| Presentation | 2021-03-03 10:25 Evaluation on Approximate Multiplier for CNN Calculation Yuechuan Zhang, Masahiro Fujita, Takashi Matsumoto (UTokyo)  VLD2020-68 HWS2020-43 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Improving the accuracy of a convolutional neural network (CNN) typically requires larger hardware with more energy consumption. On the other hand, the error tolerance of CNNs allows approximate computing to cut down the implementation costs. Given that multiplication is the most resource-intensive and power-hungry operation in CNNs, approximate multipliers (AMs) can be used to reduce hardware cost. There are various existing approximate multiplier generation methods. However, it remains unknown whether a specific AM is suitable for CNN calculation and its effect on inference accuracy. In this paper, we implement an 8-bit quantized Alexnet into hardware. The relationship between error caused by AMs and the accuracy of CNN inference is established. Mainly two AMs are considered: 1) Cartesian Genetic Programming (CGP)-based AMs 2) flexible Error-estimating based AMs. Besides, we propose two techniques, input zoom and error compensation to improve the performance of AMs in CNN calculation. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | CNN / Approximate multiplier / Error compensation / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 400, VLD2020-68, pp. 7-12, March 2021. | |
| Paper # | VLD2020-68 | |
| Date of Issue | 2021-02-24 (VLD, HWS) | |
| 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) | |
| Download PDF | VLD2020-68 HWS2020-43 |
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| Conference Information | |
| Committee | HWS VLD |
| Conference Date | 2021-03-03 - 2021-03-04 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Design Technology for System-on-Silicon, Hardware Security, etc. |
| Paper Information | |
| Registration To | VLD |
| Conference Code | 2021-03-HWS-VLD |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Evaluation on Approximate Multiplier for CNN Calculation |
| Sub Title (in English) | |
| Keyword(1) | CNN |
| Keyword(2) | Approximate multiplier |
| Keyword(3) | Error compensation |
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| 1st Author's Name | Yuechuan Zhang |
| 1st Author's Affiliation | Univerisity of Tokyo (UTokyo) |
| 2nd Author's Name | Masahiro Fujita |
| 2nd Author's Affiliation | Univerisity of Tokyo (UTokyo) |
| 3rd Author's Name | Takashi Matsumoto |
| 3rd Author's Affiliation | Univerisity of Tokyo (UTokyo) |
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| Speaker | Author-1 |
| Date Time | 2021-03-03 10:25:00 |
| Presentation Time | 25 minutes |
| Registration for | VLD |
| Paper # | VLD2020-68, HWS2020-43 |
| Volume (vol) | vol.120 |
| Number (no) | no.400(VLD), no.401(HWS) |
| Page | pp.7-12 |
| #Pages | 6 |
| Date of Issue | 2021-02-24 (VLD, HWS) |
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