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| Presentation | 2011-03-28 11:30 MPI/OpenMP Hybrid Parallel Inference for Latent Dirichlet Allocation Shotaro Tora, Koji Eguchi (Kobe Univ.)  IBISML2010-118 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In recent years, probabilistic topic models have been applied to various kinds of data including text data, and its effectiveness has been demonstrated. Latent Dirichlet Allocation (LDA) is one of the well-known topic models. Variational Bayesian inference or Collapsed Gibbs sampling is often employed to estimate parameters in LDA; however, these inference methods require high computational cost for large-scale data. Therefore, high efficiency technology is needed for this purpose. In this paper, we make use of parallel computation technology for the sake of efficient Collapsed Gibbs sampling inference for LDA. We assume to use a shared memory cluster (SMP cluster), which is widely used in recent years. In prior work of efficient inference for LDA, MPI or OpenMP has been used alone. On the other hand, for a SMP cluster it is more suitable to adopt hybrid parallel programming models which use message passing for communication between SMP nodes and loop directives for parallelization within each SMP node. In this paper, we developed a MPI/OpenMP hybrid parallel inference method for LDA, and achieved remarkable speed-up under various settings of a SMP cluster. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Topic models / Latent Dirichlet Allocation / Gibbs sampling / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 110, no. 476, IBISML2010-118, pp. 101-108, March 2011. | |
| Paper # | IBISML2010-118 | |
| Date of Issue | 2011-03-21 (IBISML) | |
| 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 | IBISML2010-118 |
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| Conference Information | |
| Committee | IBISML |
| Conference Date | 2011-03-28 - 2011-03-29 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nakanoshima Center, Osaka Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Text and Web mining, etc. |
| Paper Information | |
| Registration To | IBISML |
| Conference Code | 2011-03-IBISML |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | MPI/OpenMP Hybrid Parallel Inference for Latent Dirichlet Allocation |
| Sub Title (in English) | |
| Keyword(1) | Topic models |
| Keyword(2) | Latent Dirichlet Allocation |
| Keyword(3) | Gibbs sampling |
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| 1st Author's Name | Shotaro Tora |
| 1st Author's Affiliation | Kobe University (Kobe Univ.) |
| 2nd Author's Name | Koji Eguchi |
| 2nd Author's Affiliation | Kobe University (Kobe Univ.) |
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| Speaker | Author-1 |
| Date Time | 2011-03-28 11:30:00 |
| Presentation Time | 20 minutes |
| Registration for | IBISML |
| Paper # | IBISML2010-118 |
| Volume (vol) | vol.110 |
| Number (no) | no.476 |
| Page | pp.101-108 |
| #Pages | 8 |
| Date of Issue | 2011-03-21 (IBISML) |
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