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Paper Abstract and Keywords
Presentation 2016-11-18 15:55
GPGPU-accelerated simulation and accuracy evaluation for various neuron models
Shun Okuno (UEC), Kazuhisa Fujita (NIT), Yoshiki Kashimori (UEC) NC2016-32
Abstract (in Japanese) (See Japanese page) 
(in English) To understand the processing mechanisms of sensory information in the brain, it is necessary to simulate a huge size of network that consists of complicated neuronal model imitating the actual neurons. However, such a simulation requires a very long computation time, failing to perform computer simulation with a realistic time scale. In order to solve the problem of computation time, we focus on the reduction of computation time by GPGPU, providing an efficient method for simulation of huge number of neurons. In this paper, we develop a computational architecture of GPGPU, by which computation of neurons is performed in parallel. Using this architecture, we show that the GPGPU method significantly reduces the computation time of neural simulation. We also show that the simulations with single and double float precision give little significant difference in the results, independently of the neuron models used. These results suggest that the GPGPU calculation with single float precision is most efficient method for simulation of a huge size of neural network.
Keyword (in Japanese) (See Japanese page) 
(in English) GPGPU / Accelertion / Accuracy evalution / Neural simulation / / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 313, NC2016-32, pp. 1-6, Nov. 2016.
Paper # NC2016-32 
Date of Issue 2016-11-11 (NC) 
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 NC2016-32

Conference Information
Committee MBE NC  
Conference Date 2016-11-18 - 2016-11-19 
Place (in Japanese) (See Japanese page) 
Place (in English) Tohoku University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To NC 
Conference Code 2016-11-MBE-NC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) GPGPU-accelerated simulation and accuracy evaluation for various neuron models 
Sub Title (in English)  
Keyword(1) GPGPU  
Keyword(2) Accelertion  
Keyword(3) Accuracy evalution  
Keyword(4) Neural simulation  
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1st Author's Name Shun Okuno  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Kazuhisa Fujita  
2nd Author's Affiliation National Institute of Technology, Tsuyama College (NIT)
3rd Author's Name Yoshiki Kashimori  
3rd Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2016-11-18 15:55:00 
Presentation Time 25 minutes 
Registration for NC 
Paper # NC2016-32 
Volume (vol) vol.116 
Number (no) no.313 
Page pp.1-6 
#Pages 6 
Date of Issue 2016-11-11 (NC) 

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