Paper Abstract and Keywords |
Presentation |
2017-07-28 11:15
Avoiding redundant data transfer on GPU-enabled Apache Spark Ryo Asai, Masao Okita, Kenichi Hagihara (Osaka Univ.) CPSY2017-33 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Apache Spark is a fast and general engine for parallel distributed processing on PC cluster. IBMSparkGPU is a Spark plugin that enables GPU offloading. The IBMSparkGPU provides in-VRAM cache instruction for avoiding data transfer between the host PC and the GPU. Programmers are responsible for this cache management. In this paper, we propose an extention of IBMSparkGPU for automatically avoiding redundant data transfer. The proposed method manages in-VRAM cache so that redundant data transfer does not occur be- tween batched processes on the GPU. The batched processes can be identified by analyzing the data flow provided by Spark runtime. Experimental results show that the proposed method avoids redundant data transfer in a logistic regression program with overhead of at most 2.4%. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
CUDA / Design optimization / In-VRAM cache / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 117, no. 153, CPSY2017-33, pp. 185-190, July 2017. |
Paper # |
CPSY2017-33 |
Date of Issue |
2017-07-19 (CPSY) |
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) |
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CPSY2017-33 |
Conference Information |
Committee |
CPSY DC IPSJ-ARC |
Conference Date |
2017-07-26 - 2017-07-28 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Akita Atorion-Building (Akita) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Parallel, Distributed and Cooperative Processing |
Paper Information |
Registration To |
CPSY |
Conference Code |
2017-07-CPSY-DC-ARC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Avoiding redundant data transfer on GPU-enabled Apache Spark |
Sub Title (in English) |
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CUDA |
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Design optimization |
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In-VRAM cache |
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1st Author's Name |
Ryo Asai |
1st Author's Affiliation |
Osaka University (Osaka Univ.) |
2nd Author's Name |
Masao Okita |
2nd Author's Affiliation |
Osaka University (Osaka Univ.) |
3rd Author's Name |
Kenichi Hagihara |
3rd Author's Affiliation |
Osaka University (Osaka Univ.) |
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Speaker |
Author-1 |
Date Time |
2017-07-28 11:15:00 |
Presentation Time |
30 minutes |
Registration for |
CPSY |
Paper # |
CPSY2017-33 |
Volume (vol) |
vol.117 |
Number (no) |
no.153 |
Page |
pp.185-190 |
#Pages |
6 |
Date of Issue |
2017-07-19 (CPSY) |
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