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Paper Abstract and Keywords
Presentation 2021-03-25 16:00
Optimizing Data Transfer between CPU and GPU in Model Parallel Training with Mesh TensorFlow
Hironori Yokote, Shinobu Miwa, Hayato Yamaki, Hiroki Honda (UEC) CPSY2020-56 DC2020-86
Abstract (in Japanese) (See Japanese page) 
(in English) Since deep learning requires an enormous amount of computation time, it is often executed on multiple GPUs. Mesh TensorFlow has been proposed as a language for model parallelization, which is one of the parallelization methods for deep learning. In this paper, we optimize data transfer between CPU and GPU in model parallelization using Mesh TensorFlow. Specifically, our optimization enables training data to be transferred from the CPU to each GPU directly in parallel, though it is originally transferred via a specific GPU in the sample code of Mesh TensorFlow. Our experimental results show that our optimization can both reduce the time of the data transfer and improve the efficiency of GPU-memory utilization.
Keyword (in Japanese) (See Japanese page) 
(in English) Mesh TensorFlow / Model Parallel / GPU / / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 435, CPSY2020-56, pp. 37-42, March 2021.
Paper # CPSY2020-56 
Date of Issue 2021-03-18 (CPSY, DC) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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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Conference Information
Committee CPSY DC IPSJ-SLDM IPSJ-EMB IPSJ-ARC  
Conference Date 2021-03-25 - 2021-03-26 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) ETNET2021 
Paper Information
Registration To CPSY 
Conference Code 2021-03-CPSY-DC-SLDM-EMB-ARC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Optimizing Data Transfer between CPU and GPU in Model Parallel Training with Mesh TensorFlow 
Sub Title (in English)  
Keyword(1) Mesh TensorFlow  
Keyword(2) Model Parallel  
Keyword(3) GPU  
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1st Author's Name Hironori Yokote  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Shinobu Miwa  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Hayato Yamaki  
3rd Author's Affiliation The University of Electro-Communications (UEC)
4th Author's Name Hiroki Honda  
4th Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2021-03-25 16:00:00 
Presentation Time 20 minutes 
Registration for CPSY 
Paper # CPSY2020-56, DC2020-86 
Volume (vol) vol.120 
Number (no) no.435(CPSY), no.436(DC) 
Page pp.37-42 
#Pages
Date of Issue 2021-03-18 (CPSY, DC) 


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