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| Presentation | 2016-08-09 11:15 A simulation study on fault tolerancy of parallel machine learning systems with parameter servers Mingxi Li (Univ. of Tsukuba), Yusuke Tanimura, Hidemoto Nakada (AIST)  CPSY2016-20 DC2016-17 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Parallel computation is essential for machine learning systems to be more faster. There are two techniques to build parallel machine learning systems; namely data parallel method and model parallel method. In this paper, we only discuss data parallel where large number of parameter servers and computation servers communicate each other to perform computation. Fault tolerancy is a big problem on large scale computation system in general, however, there are not much discussions about the fault folerancy of parallel machine learning system. in this paper, we discuss the fault tolerancy of parallel machine learning systems which use parameter servers. Parameter servers gives extra redundancy to the system and could double as the checkpoint server. We also quantitatively evaluate several fault tolerance method using parallel environment simulator SimGrid. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Fault Tolerancy / Parameter Server / Machine Learning / Simulations / Distributed Systems / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 177, CPSY2016-20, pp. 125-130, Aug. 2016. | |
| Paper # | CPSY2016-20 | |
| Date of Issue | 2016-08-01 (CPSY), 2016-08-02 (DC) | |
| 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 | CPSY2016-20 DC2016-17 |
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| Conference Information | |
| Committee | CPSY DC IPSJ-ARC |
| Conference Date | 2016-08-08 - 2016-08-10 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Kissei-Bunka-Hall (Matsumoto) |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Parallel, Distributed and Cooperative Processing |
| Paper Information | |
| Registration To | CPSY |
| Conference Code | 2016-08-CPSY-DC-ARC |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A simulation study on fault tolerancy of parallel machine learning systems with parameter servers |
| Sub Title (in English) | |
| Keyword(1) | Fault Tolerancy |
| Keyword(2) | Parameter Server |
| Keyword(3) | Machine Learning |
| Keyword(4) | Simulations |
| Keyword(5) | Distributed Systems |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Mingxi Li |
| 1st Author's Affiliation | University of Tsukubay (Univ. of Tsukuba) |
| 2nd Author's Name | Yusuke Tanimura |
| 2nd Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST) |
| 3rd Author's Name | Hidemoto Nakada |
| 3rd Author's Affiliation | National Institute of Advanced Industrial Science and Technology (AIST) |
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| Speaker | Author-1 |
| Date Time | 2016-08-09 11:15:00 |
| Presentation Time | 30 minutes |
| Registration for | CPSY |
| Paper # | CPSY2016-20, DC2016-17 |
| Volume (vol) | vol.116 |
| Number (no) | no.177(CPSY), no.178(DC) |
| Page | pp.125-130(CPSY), pp.1-6(DC) |
| #Pages | 6 |
| Date of Issue | 2016-08-01 (CPSY), 2016-08-02 (DC) |
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